diff --git a/impetusModel/impetusModel_files/figure-html/Basin monthly-1.png b/impetusModel/impetusModel_files/figure-html/Basin monthly-1.png
index 03781953b1638ac9f848d87a661c2a7e5c87c255..cb235bbd3887814eca77ebfc86679259685bfb1c 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Basin monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Basin monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Bath monthly-1.png b/impetusModel/impetusModel_files/figure-html/Bath monthly-1.png
index e1264dc9d3af6b722aec27e27849887c112e9eb3..32d4fbfc794317d9f4dc80767bf2c928a844120e 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Bath monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Bath monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Bath monthly-2.png b/impetusModel/impetusModel_files/figure-html/Bath monthly-2.png
index 975e23b5dff76444d31005fa83d9037963d04284..581fad93e44ca493ddec63989d5422501bad2684 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Bath monthly-2.png and b/impetusModel/impetusModel_files/figure-html/Bath monthly-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare External-1.png b/impetusModel/impetusModel_files/figure-html/Compare External-1.png
index 3dec199a118d4ce1aca27bf3113e13a78eea6b8f..153419863dd655c005855636cdb7423dfb027ac3 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare External-1.png and b/impetusModel/impetusModel_files/figure-html/Compare External-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare External-2.png b/impetusModel/impetusModel_files/figure-html/Compare External-2.png
index aa6a9555e82fa816b2336fdef38579ca3af8c3c7..8e37ecb0c712c25d1b6072b59003e3f5829e5261 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare External-2.png and b/impetusModel/impetusModel_files/figure-html/Compare External-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare WC-1.png b/impetusModel/impetusModel_files/figure-html/Compare WC-1.png
index 73948a5320daa5b5ed053c2e75fd2c6ec23ca168..d42eed389d18785994bcec64976de7d2f5d420a2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare WC-1.png and b/impetusModel/impetusModel_files/figure-html/Compare WC-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare WC-2.png b/impetusModel/impetusModel_files/figure-html/Compare WC-2.png
index d477ff417a56cef9f632b868383a208462e30bc6..1d5f6886805579cc560f71390aa5b01880028b7a 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare WC-2.png and b/impetusModel/impetusModel_files/figure-html/Compare WC-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare shower-1.png b/impetusModel/impetusModel_files/figure-html/Compare shower-1.png
index d2974c286c9d4b3ff39f020e7c9a6104b3370c3f..8a9baedccd16fd42f528f1bbf60cdbd0ddaa4286 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare shower-1.png and b/impetusModel/impetusModel_files/figure-html/Compare shower-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Compare shower-2.png b/impetusModel/impetusModel_files/figure-html/Compare shower-2.png
index 00923ad516164eb2093a7eb4370a753b4588fbb2..7bbfa674174137f8128551e10631d2f1fe00a828 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Compare shower-2.png and b/impetusModel/impetusModel_files/figure-html/Compare shower-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Dishwasher monthly-1.png b/impetusModel/impetusModel_files/figure-html/Dishwasher monthly-1.png
index 69a07e8a4f2724ae4b030021f8ae0375861a58f7..750d713ff1aa99854ca4963ba9f030e319d1c9a2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Dishwasher monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Dishwasher monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Drought model - TUB-1.png b/impetusModel/impetusModel_files/figure-html/Drought model - TUB-1.png
index 715e6c450bfb4bf096d778ed58e2d26314318735..899c53c7644211a3d575784be6caf599ea2de2d2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Drought model - TUB-1.png and b/impetusModel/impetusModel_files/figure-html/Drought model - TUB-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Drought model - TUB-2.png b/impetusModel/impetusModel_files/figure-html/Drought model - TUB-2.png
index caf5e4a586fd576bc078e6804c731f7e0d82c4c0..290d66f267c1eb5c2bb0f944ad34238a69beb1ba 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Drought model - TUB-2.png and b/impetusModel/impetusModel_files/figure-html/Drought model - TUB-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Drought model - WC-1.png b/impetusModel/impetusModel_files/figure-html/Drought model - WC-1.png
index a4f0f15c7369d5d7ad0acfee7a6ac7d3b3173bc1..ab8617a20ea5dd7248904c6f1133b09b27116ea7 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Drought model - WC-1.png and b/impetusModel/impetusModel_files/figure-html/Drought model - WC-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Drought model - shower-1.png b/impetusModel/impetusModel_files/figure-html/Drought model - shower-1.png
index 069187b255e1d5450239a6121a7f55bac3e5c02d..bc6b8fc69b57da1723ed16ad445431d60bea146e 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Drought model - shower-1.png and b/impetusModel/impetusModel_files/figure-html/Drought model - shower-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/External monthly-1.png b/impetusModel/impetusModel_files/figure-html/External monthly-1.png
index 6d5f5e10e96003d7f5a69960ce3d8058c4ba71af..c5398de901e0bb0a1de90227dc2b587e5add9203 100644
Binary files a/impetusModel/impetusModel_files/figure-html/External monthly-1.png and b/impetusModel/impetusModel_files/figure-html/External monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/External monthly-2.png b/impetusModel/impetusModel_files/figure-html/External monthly-2.png
index e1339681ef35a10a1d7358ad3e88ba9b8044c0e1..c92deb978bab2beaa21fa009cbce053fc32c4ae1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/External monthly-2.png and b/impetusModel/impetusModel_files/figure-html/External monthly-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Household size-1.png b/impetusModel/impetusModel_files/figure-html/Household size-1.png
index a57007fbc4727eb8241a650f3cb247a35c04c652..3cb290a7cb5bded6a17e3a03fe5c7bf5efd28249 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Household size-1.png and b/impetusModel/impetusModel_files/figure-html/Household size-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Kitchen sink monthly-1.png b/impetusModel/impetusModel_files/figure-html/Kitchen sink monthly-1.png
index 1bf0b0bb7bced4e95c14054783f416c1c271ca4f..08f87013cf8149f0822d235eccf1428fa9077614 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Kitchen sink monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Kitchen sink monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Number metered-1.png b/impetusModel/impetusModel_files/figure-html/Number metered-1.png
index b2753119fe97290614d84737b65c568023a22d6b..93acaf4c8f28e1c2945243790f38f74dd55ad46f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Number metered-1.png and b/impetusModel/impetusModel_files/figure-html/Number metered-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Shower monthly-1.png b/impetusModel/impetusModel_files/figure-html/Shower monthly-1.png
index c7a919ba3b3bd6793dffcbf2b0e31e8fcb2927d6..43e67afb18393c692e20392fd05774b7636f85cf 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Shower monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Shower monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Total daily demand by household size & metering-1.png b/impetusModel/impetusModel_files/figure-html/Total daily demand by household size & metering-1.png
index bb9861cbfc4e57426b149f769f9baf59fc3f78a8..ca22e98c680c4b3cb4a98e4e781686465c89611b 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Total daily demand by household size & metering-1.png and b/impetusModel/impetusModel_files/figure-html/Total daily demand by household size & metering-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Total monthly demand by household size-1.png b/impetusModel/impetusModel_files/figure-html/Total monthly demand by household size-1.png
index 7ac4d2d1c8239b9b27782f629fe6f73f0bc2e8d2..e3e5991d02f052ac6fe5419c778e29eaa7292173 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Total monthly demand by household size-1.png and b/impetusModel/impetusModel_files/figure-html/Total monthly demand by household size-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Total monthly demand by metering-1.png b/impetusModel/impetusModel_files/figure-html/Total monthly demand by metering-1.png
index 8238cac13a451483caf41770936bb2759ac5d801..6a6853db2befa0b94e8447926abcfb2f631767a2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Total monthly demand by metering-1.png and b/impetusModel/impetusModel_files/figure-html/Total monthly demand by metering-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Total monthly external demand by household size-1.png b/impetusModel/impetusModel_files/figure-html/Total monthly external demand by household size-1.png
index 441e30d6ef112f48cee28b400f0aef9b1db23e3f..6cc8d09fd25aecff63612a6f7d00ed7e00151a76 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Total monthly external demand by household size-1.png and b/impetusModel/impetusModel_files/figure-html/Total monthly external demand by household size-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/WC monthly-1.png b/impetusModel/impetusModel_files/figure-html/WC monthly-1.png
index 08e8723e29c3777334f55a3b661ff38aa126b805..fd2dba90a124111cd8075838f78d31a492c0cd2a 100644
Binary files a/impetusModel/impetusModel_files/figure-html/WC monthly-1.png and b/impetusModel/impetusModel_files/figure-html/WC monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/Washing machine monthly-1.png b/impetusModel/impetusModel_files/figure-html/Washing machine monthly-1.png
index 7c325771bedc13738279d7eef70ce3ea0e8952bb..1cd1a13bf54e744dfa191b2b68e619c4565ff4ff 100644
Binary files a/impetusModel/impetusModel_files/figure-html/Washing machine monthly-1.png and b/impetusModel/impetusModel_files/figure-html/Washing machine monthly-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/allUses1995-1.png b/impetusModel/impetusModel_files/figure-html/allUses1995-1.png
index 2b6670967cfcad9cb65655c534e2b9618ac9861f..4f758e55767ee30993b7252a01735f37bf3372f1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/allUses1995-1.png and b/impetusModel/impetusModel_files/figure-html/allUses1995-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/allUsesLastYear-1.png b/impetusModel/impetusModel_files/figure-html/allUsesLastYear-1.png
index 3934934fb5f513c6bafc2420abd5a28f97739743..c0b907f56233d6b7899f499f1d06194fbc2e4885 100644
Binary files a/impetusModel/impetusModel_files/figure-html/allUsesLastYear-1.png and b/impetusModel/impetusModel_files/figure-html/allUsesLastYear-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/allUsesLastYear-2.png b/impetusModel/impetusModel_files/figure-html/allUsesLastYear-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..d29fd6fbcc9ec4f5471dc944618ff1ba02659a3d
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/allUsesLastYear-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bath water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/bath water demand plot-1.png
index c9bda55cefc9b1acfcac4ec6b7e9fdfc48f24c90..a59d68446409e4326aaae2d3479aba5769224d06 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bath water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/bath water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bath water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/bath water demand plot-2.png
index cd134364ca80dfac2dbb4ec3119f8c6930940936..91163ae7a34d39056fe63fd0b31cf7a5e424cdd6 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bath water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/bath water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bath water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/bath water demand plot-3.png
index be3e0445298f3ed95c04f64067828e4afeef2aa5..d0db7cc05e221f57b7d9e3d36b05b3fbafb8666f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bath water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/bath water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-1.png
index 213dd721f38be675f4adbf8148de659ff9a46ce2..84285c694c29229fda34011b19c8637a1460bfb1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-2.png
index 36f6c0874d8e8a6acdac79f5ed2f6eae2b581932..2788e0655bac16e137cfd1823a080620622ac46c 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-3.png
index 04166b0746a6230dd39eaa19ff6bc735a5a5ca0b..80a3c0801362d31b4ea99b691472eb656e554e30 100644
Binary files a/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/bathsink water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-1.png
index c15c73b2750e592b978ff316b798d3bc73b2f359..fde9ca0144456e621f4a1c6273dca14eb903c912 100644
Binary files a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-2.png
index 79e13ccff0d1cfc1deba71c5f00bddb2f6054d71..a96f503b9d3b12b8ab6716577d1503f187bd42b9 100644
Binary files a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-3.png
index 6d5825297698f4d041cdcc5e4517c303ab2f8be2..8fe78c19af4223674930a9aba7360b9bce9c02e2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/carwashing water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/check uptake rates-1.png b/impetusModel/impetusModel_files/figure-html/check uptake rates-1.png
index 0785bb25053c40dea4f9b4fc4729f8747d915bc6..768e83711a8327f9cab329d68c67f958ba1bcdc3 100644
Binary files a/impetusModel/impetusModel_files/figure-html/check uptake rates-1.png and b/impetusModel/impetusModel_files/figure-html/check uptake rates-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/check uptake rates-2.png b/impetusModel/impetusModel_files/figure-html/check uptake rates-2.png
index 19f960f98cdb6fe2968f080f96341ca211eeee08..f88cf74e211c1e6297288630844d11324b585c68 100644
Binary files a/impetusModel/impetusModel_files/figure-html/check uptake rates-2.png and b/impetusModel/impetusModel_files/figure-html/check uptake rates-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/check uptake rates-3.png b/impetusModel/impetusModel_files/figure-html/check uptake rates-3.png
index eb9df96a916c2d07ba82c67f5e8bc67022031217..96e47fe4f769fe4cda1d9e0263bec11dff7cda59 100644
Binary files a/impetusModel/impetusModel_files/figure-html/check uptake rates-3.png and b/impetusModel/impetusModel_files/figure-html/check uptake rates-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-1.png b/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-1.png
index 1153e60a9253286dbdd255475a10030897e93270..cf62b6146c98644bd906798062b5ae97aa853ced 100644
Binary files a/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-1.png and b/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-2.png b/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-2.png
index f801097f0a2133940d0b1f0fe998f6e91805b9ca..413f3c0517ddd3502118ff6cc830cd4a51ee0d98 100644
Binary files a/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-2.png and b/impetusModel/impetusModel_files/figure-html/compareESTmcm v1-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-1.png b/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-1.png
index 406db8676d3ea99185a632d1681f0e86d9e002a6..df862f96a1c912b676bf287d440b344beffa11a4 100644
Binary files a/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-1.png and b/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-2.png b/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-2.png
index 06b7da3d9488cf9172b9fa64cf517ec3ac6f60ea..c6b05c7bb8f4c50cf5c13ae91ea360878a491133 100644
Binary files a/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-2.png and b/impetusModel/impetusModel_files/figure-html/compareESTmcm v2-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compare_v_1.3-1.png b/impetusModel/impetusModel_files/figure-html/compare_v_1.3-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..1bcd6be301b2f44c75db4d4ae6140c15db6aaaed
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/compare_v_1.3-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/compare_v_2_0-1.png b/impetusModel/impetusModel_files/figure-html/compare_v_2_0-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..ca4fb67df358764023bf6bd2e727118da3476038
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/compare_v_2_0-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-1.png
index 2dd4a43142d307aee5783a3434c2118bc15858dc..832e380974eb4dd18607a6090266e1472f47eb72 100644
Binary files a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-2.png
index 4cd75eec02de3f74e1699759e8cc5b12f5d3f5fe..37c8f0e1abd4090d981b93a58960fe339b94c97f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-3.png
index a202ddacd57e70133d845f273846730c0d29bfe7..ee3d7fd6062b6cd1c09e609a833b75e944d2e67f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/dishwasher water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-1.png b/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-1.png
index 2f2a039c190c81e9abf860e56ebb060335270f6c..0fd6e28e90b8af79c48adf37314e06d5d04380fd 100644
Binary files a/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-1.png and b/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-2.png b/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-2.png
index 2720fb2b0220c39a6793507418b8cb59a4bfd631..d1a31bfee27676207b46efb99ba4556a6817759b 100644
Binary files a/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-2.png and b/impetusModel/impetusModel_files/figure-html/final model v1_3 2012 by month-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v1_3 all dates-1.png b/impetusModel/impetusModel_files/figure-html/final model v1_3 all dates-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..dc29f7a958dc5dfc7b8ac173a0a0221fa691ec68
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/final model v1_3 all dates-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-1.png b/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..bd9b79065be57a7405dd86d721017e12b36f3d3c
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-2.png b/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..bdf44cc266bf844b1cf86172477e8e6cf8033997
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/final model v2_0 2012 by month-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/final model v2_0 all dates-1.png b/impetusModel/impetusModel_files/figure-html/final model v2_0 all dates-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..3a31e49dd8fa4c3ea45fe786e9ddfaae0fd4dbc8
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/final model v2_0 all dates-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-1.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-1.png
index 13dc50f264313833be3a23dc043a7f43ea6a1b08..6b2fd38d105f45e7f065b6a7fc432323ae199ad1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-1.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-2.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-2.png
index d1779721d60e283e4203fd56c181dd84a86942f6..0550cf9b9685084119d2a3eb3d3a16aa4385af79 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-2.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-3.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-3.png
index 33d9cef61af05a051e3585ae0e91f73208174416..f9e4db0a4ed4c759b373bc93fbac6b41363a637e 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-3.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-4.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-4.png
index 14b2dc72372ec0ae4c9a5f38ea9a4a65138f1d1f..c556416b80dfc679d09e14901d59052162339ab2 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-4.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-5.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-5.png
index 0adb8559a73928508e810039fc813a21b13b28e6..0cf9dcdb91f4e685905d30f3bb8b4c9f978d38a0 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-5.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-5.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-6.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-6.png
index 4be938cd019e70f44d3c2f3f202a036360ebd609..aa2ae244f84db47cadd742fb2d25b160cf201cfe 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-6.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-6.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-7.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-7.png
index b715ab2f3ced15dafb5ada2aeb9e7f0150a3301f..d3d8c9128513217bcc62e6f5b3bafcc7594349f0 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-7.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-7.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-8.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-8.png
index cdce8d11a3e50e86393244e19d7a7e447148e212..ec47f869b2b712065e5927d261cc881d411d642a 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-8.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-8.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-9.png b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-9.png
index 865a082c4d1c0c20b369b55eb677ec289dab3ced..5eaced0b78c4f8cd1cfbd59c6bd2873384364eb6 100644
Binary files a/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-9.png and b/impetusModel/impetusModel_files/figure-html/finalBaseHHDataTests-9.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-1.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-1.png
index d02712303807b6a4829de2037652b4cf0f20c25f..ff701568a4f8dc4bed422ad15b612f21e46ab587 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-1.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-2.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-2.png
index c9c2980a91932ee12eeb5d08059f5dab53795803..464720160c706d036fd5a505b34541c58718ed2c 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-2.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-3.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-3.png
index 580e2dc4a2937806bc88917a92dbe789fc7d8870..73ee272b9be33c219bc2b8fe28e51a8a4863b253 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-3.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-4.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-4.png
index e296166abbcf241f076604ab71fcf453e37c3588..ac61ce2c72e419d3eaa8115309cc7594e356a5e5 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-4.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-5.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-5.png
index 0a1740cee741235d4066e79f4791d39b10ed340f..8f2038acb3b8720e59a61faa437f0789ae5602c7 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-5.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-5.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-6.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-6.png
index 36900e976acdb009f2895e79bf4e66d0daa40c7b..ca7671874ed7d1a4515bfe711931ce14ec38e1f3 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-6.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-6.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-7.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-7.png
index 8b03e7ee9208233e73e2944df0bf9a834ac24e24..d81f722d32a9030cfe87ba4e412a8fb0048f6661 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-7.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-7.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-8.png b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-8.png
index 0ad6f8bc67c0476277fac26c11fb9b1b59d894d9..26cc2372951cb60a56a1cfa099b1723820f1caa8 100644
Binary files a/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-8.png and b/impetusModel/impetusModel_files/figure-html/fixBaselineDistributions-8.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/garden water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/garden water demand plot-1.png
index 50778844195f554e776cfa9036fd880a70597876..5256e1c4c8ef962055db03bdbebd2fc8108acbca 100644
Binary files a/impetusModel/impetusModel_files/figure-html/garden water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/garden water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/garden water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/garden water demand plot-2.png
index 4183a317d89782d5664ba4378f20e04d4d30f0e5..7184faabe1380356929f29912ba3aa4103148c24 100644
Binary files a/impetusModel/impetusModel_files/figure-html/garden water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/garden water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/garden water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/garden water demand plot-3.png
index ffee22f4d93a09bdf3f4e1db4f516c5ff0a4f0c5..7b1469bd52c2dc0091ece953907b70f7ab732d7e 100644
Binary files a/impetusModel/impetusModel_files/figure-html/garden water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/garden water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/garden water demand plot-4.png b/impetusModel/impetusModel_files/figure-html/garden water demand plot-4.png
index 4880956b44ea8f7ba6bf3b10b71448e85064dce8..fc19162a8cb1211fff87fbb7502696b09adcbc91 100644
Binary files a/impetusModel/impetusModel_files/figure-html/garden water demand plot-4.png and b/impetusModel/impetusModel_files/figure-html/garden water demand plot-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/iwaBath_paperFig-1.png b/impetusModel/impetusModel_files/figure-html/iwaBath_paperFig-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..c1af718f36cd2aaa877d2fe24f910f2729d53e23
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/iwaBath_paperFig-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-1.png
index ffae9840f6db2610a089cbbfc82b157b34be5173..c3b2e1177d8c203a675297b3f69419d98ea347f4 100644
Binary files a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-2.png
index 42918073723cd24c1e2a995b8424e2960632f25d..51ce6e474d27d259b31906ce3082c5ac143bf21f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-3.png
index 31887cbc8f17370fc0f1d738ca30103273c4fba6..3fc95051a670abb0c818eac3f2f655568581d536 100644
Binary files a/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/kitchensink water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/metDataTests-1.png b/impetusModel/impetusModel_files/figure-html/metDataTests-1.png
index c692a1f81244fab6374a1669914d1a624b8a6623..fa05c7b55da8b7c53c252445d87fb83dcfe44851 100644
Binary files a/impetusModel/impetusModel_files/figure-html/metDataTests-1.png and b/impetusModel/impetusModel_files/figure-html/metDataTests-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/metDataTests-2.png b/impetusModel/impetusModel_files/figure-html/metDataTests-2.png
index 4e247d07de5865361148eaad16eee3be51645c46..7ac4a4e082827e38cc39c104d897880efde0c8d3 100644
Binary files a/impetusModel/impetusModel_files/figure-html/metDataTests-2.png and b/impetusModel/impetusModel_files/figure-html/metDataTests-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/metDataTests-3.png b/impetusModel/impetusModel_files/figure-html/metDataTests-3.png
index 7745b1a7a35a4acf3e3c05c78632c036c8717bb5..129947767427fbe96d452f682af36684888bad34 100644
Binary files a/impetusModel/impetusModel_files/figure-html/metDataTests-3.png and b/impetusModel/impetusModel_files/figure-html/metDataTests-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/model v1_3 savings-1.png b/impetusModel/impetusModel_files/figure-html/model v1_3 savings-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..8de2038d78eed7bd01133f36d6e0ce99b69c4ca7
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/model v1_3 savings-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/model v1_3 savings-2.png b/impetusModel/impetusModel_files/figure-html/model v1_3 savings-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..1722bd82c05450c7dbf961b36075d96457a7025b
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/model v1_3 savings-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/model v1_3 with ci-1.png b/impetusModel/impetusModel_files/figure-html/model v1_3 with ci-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..c1ec13d4a47ed38733d3717b57c0d151b0917468
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/model v1_3 with ci-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/model v2 with ci-1.png b/impetusModel/impetusModel_files/figure-html/model v2 with ci-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..0236e750d20d9a4e7a8e59167ad228cbc7e5f7d8
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/model v2 with ci-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-1.png b/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-1.png
index ee422097ee5ce09e5c9763f12bc269500289b4a2..eeeee8efbb24d2dbb8964ce8ee186a31d041da3a 100644
Binary files a/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-1.png and b/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-2.png b/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-2.png
index dca94d09ccd79f43623a5d7271e64ebf9108d679..7782d89f245be966ef522fc169ffb44c8acdde87 100644
Binary files a/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-2.png and b/impetusModel/impetusModel_files/figure-html/plot we adjusted shower and WC use-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/reportESTocc-1.png b/impetusModel/impetusModel_files/figure-html/reportESTocc-1.png
index 5fc8c2f3728440baa181a6903a83a971ecfcffaa..1a219d5a321793f64d77e0082cf3e4a32db8953a 100644
Binary files a/impetusModel/impetusModel_files/figure-html/reportESTocc-1.png and b/impetusModel/impetusModel_files/figure-html/reportESTocc-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/shower water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/shower water demand plot-1.png
index 97dae0d50f8f73cd51c47d11b00f675694412fb6..50cb9175b51a129eff1898d2ac0f163ea8dd4e2f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/shower water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/shower water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/shower water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/shower water demand plot-2.png
index 15ec490487f07a2d9989a2bdd01c736643529053..a40d03bb19deababe51dcdd0e247090bd725590f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/shower water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/shower water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/shower water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/shower water demand plot-3.png
index a00c3154f6e28677bdcf81ffe0e0440e7a1f3cde..0dd49407cbba76b2ca9ee28b0225e5dae209bb2b 100644
Binary files a/impetusModel/impetusModel_files/figure-html/shower water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/shower water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-1.png b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-1.png
index b6fee2edb61aa68f813a82c5bdc7d1ea69a02c46..12a4b55634eae152b48b595d9afb336955615a8d 100644
Binary files a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-1.png and b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-2.png b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-2.png
index 733d3ab116c390585eb1651c7324c7cc8a1230a9..296db1d00ca0ce8763c92ba5ab66aa4f1dfa6199 100644
Binary files a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-2.png and b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-3.png b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-3.png
index 4a8fc306a06e6027c56890f469e8db4493b10dc4..f45132522e068c57f1e3dba9fabd4d5afdae7c00 100644
Binary files a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-3.png and b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-4.png b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-4.png
index 47449d6dab80ca9f10f06a6be99081a2bf8f29c6..8c44546c1f99345c89598f979eb0b7631ed0cb90 100644
Binary files a/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-4.png and b/impetusModel/impetusModel_files/figure-html/test Colne drought history and climate data-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-1.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..17a1e0264dfc264d514f8385b2883eec69851284
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-2.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..86060c1fc4c90557a3232d3db620892ee58209e6
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-3.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-3.png
new file mode 100644
index 0000000000000000000000000000000000000000..13466078fc61ab30eaff290f58216d2f2915e5d5
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-4.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-4.png
new file mode 100644
index 0000000000000000000000000000000000000000..e5f54a2256660a68229ccbc7e52676b9a0fd3101
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-5.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-5.png
new file mode 100644
index 0000000000000000000000000000000000000000..ba3715ce9693690fa73e977d8479403f87bc2154
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-5.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-6.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-6.png
new file mode 100644
index 0000000000000000000000000000000000000000..0a53ec39a9a6c9401a54a2a9a9f7289250932d2d
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-6.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-7.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-7.png
new file mode 100644
index 0000000000000000000000000000000000000000..ef454f39c2ba51c890a96fa0483014446921bdfe
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 by component-7.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v1_3 total-1.png b/impetusModel/impetusModel_files/figure-html/test model v1_3 total-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..5d872dbc36f574a3b20b2316d7ea3756b7ff8aa1
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v1_3 total-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-1.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..1eea3094e290f31237a222cf883d95f2c0999d53
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-2.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..0434a1e473ccc303993c54a24f6bd7910b50a5e6
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-3.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-3.png
new file mode 100644
index 0000000000000000000000000000000000000000..e66460ccb14611c1cf94fae3a6977cd8fde73706
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-4.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-4.png
new file mode 100644
index 0000000000000000000000000000000000000000..6cb03e1b45d3c2058c91e69f6ba362ae24235656
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-5.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-5.png
new file mode 100644
index 0000000000000000000000000000000000000000..73a9183daa5ca854115266d9caa5e9ac9145d5aa
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-5.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-6.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-6.png
new file mode 100644
index 0000000000000000000000000000000000000000..854941dc09fe27750e5d28f0a6ebea472d8527c3
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-6.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 by component-7.png b/impetusModel/impetusModel_files/figure-html/test model v2 by component-7.png
new file mode 100644
index 0000000000000000000000000000000000000000..a5054035cd68e4c9994a74ae36aa83f4ee4d2db0
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 by component-7.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 total-1.png b/impetusModel/impetusModel_files/figure-html/test model v2 total-1.png
new file mode 100644
index 0000000000000000000000000000000000000000..1ecb2374ff902a566d62020428639fb17cc344f2
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 total-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/test model v2 total-2.png b/impetusModel/impetusModel_files/figure-html/test model v2 total-2.png
new file mode 100644
index 0000000000000000000000000000000000000000..39eb9ca51699e7418475feee77b60d3f5190835c
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/test model v2 total-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-1.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-1.png
index 0bca5245465105d2c62837de02dd8574ac61eca4..aa2c3bab1a05c0680ae2c49b556932a2385d4e88 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-1.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-10.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-10.png
index a6dcc5846c3508e45013f30d9f1606d64fa418f1..fa43ed6fcd24be8ca645ebf2524e6b90b8b5ce6d 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-10.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-10.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-11.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-11.png
new file mode 100644
index 0000000000000000000000000000000000000000..4ed5d43c9a26f51ce140b96cfde69dd641759a91
Binary files /dev/null and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-11.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-2.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-2.png
index e982592ac72b33d3b01c13bdab3e50cca7747deb..6da6dd382d8de0dc490910324b31f628c71d06b3 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-2.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-3.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-3.png
index 8d554edc537a3df6dd0ffd2e225e034aca599641..2fad892d8ed583cf8222ce2959e6ed2a4610b34d 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-3.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-4.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-4.png
index 991b8954ec2eeef70ee6b0570f17c9c2401395ce..5a33cc022764e89c358858463748dcbf2fb7d832 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-4.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-4.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-5.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-5.png
index a236c5d0f6f1a1b1541b703e2a8d4707c9c97ddc..b826a54b5cc9cd23f91941488eb3f2f4d33e17b7 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-5.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-5.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-6.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-6.png
index f464174ba5024336f7fa8c4c5c52008fbe0d952c..2a99db8ba2b9123c1944e9ef15bd51b3a010f772 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-6.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-6.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-7.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-7.png
index d893bfb5d831cad6425039c7a59a134297e12927..e7f9e0770081498038eccb8f2ec836a625d36b6f 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-7.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-7.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-8.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-8.png
index b1c91198d72e9ee7a0921936bf001fb36df3e25d..cea763878949e1634e8548874f198ad823715ad1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-8.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-8.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-9.png b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-9.png
index ad131195f06a77a9e5cea1bca88f5eb53f2bf5e1..62904100b877d5e7ee7d7d20f28f3083fde76488 100644
Binary files a/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-9.png and b/impetusModel/impetusModel_files/figure-html/testYearlyLitresPerDay-9.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-1.png
index a235ad5a0e2906c374690a8aa166485586ad4abc..455718858d38f5e424a6cce19407335467bcecc1 100644
Binary files a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-2.png
index bd45ea56a58cd0aac3b3ab426a355e40e2a70782..49a21be471a1fa21a1172fba52f4b58476aa20a7 100644
Binary files a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-3.png
index bcc7912e5fb3a8579f114b5cbb9a612de72f680a..db3bfc87028fd188111e59adb3407fb5e2b278ad 100644
Binary files a/impetusModel/impetusModel_files/figure-html/toilet water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/toilet water demand plot-3.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-1.png b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-1.png
index dc476bef9bb5ab00864b31da6b686273ba374bc1..e61a7d7a00f7bb627e1851e5f55595a7c3099646 100644
Binary files a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-1.png and b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-1.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-2.png b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-2.png
index bf8fd141311a8352b3a3e1fb85be5d281172c5ad..4be39c0a6365b4caefef19257af4b2cc39d87b3d 100644
Binary files a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-2.png and b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-2.png differ
diff --git a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-3.png b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-3.png
index 5d5e15211abb07a4ded6daf9220b8f6f9aa90125..1cb6d6c968697d2ca5c4f3cc66588ee81fb5369d 100644
Binary files a/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-3.png and b/impetusModel/impetusModel_files/figure-html/washingmachine water demand plot-3.png differ
diff --git a/impetusModel/plots_v1/Fig2_CompareModelv1_3withEST2013.pdf b/impetusModel/plots_v1/Fig2_CompareModelv1_3withEST2013.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..40f7dfc5a4064b43f83b8863821b12d6e4a1ec9b
Binary files /dev/null and b/impetusModel/plots_v1/Fig2_CompareModelv1_3withEST2013.pdf differ
diff --git a/impetusModel/plots_v1/Fig3_Final_model_v1_3_2012_by_month.pdf b/impetusModel/plots_v1/Fig3_Final_model_v1_3_2012_by_month.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..88fd78e093a7cf0b4ad296f035dae49594a0c126
Binary files /dev/null and b/impetusModel/plots_v1/Fig3_Final_model_v1_3_2012_by_month.pdf differ
diff --git a/impetusModel/plots_v1/Fig4_5_DroughtPlotKey.pdf b/impetusModel/plots_v1/Fig4_5_DroughtPlotKey.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..be55fa050f41c0ea681b7873f635f62ebd2ddbf4
Binary files /dev/null and b/impetusModel/plots_v1/Fig4_5_DroughtPlotKey.pdf differ
diff --git a/impetusModel/plots_v1/Fig4_Compare_sum_model_v1_3.pdf b/impetusModel/plots_v1/Fig4_Compare_sum_model_v1_3.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..e13824cf897c706ba16634e69ec2cf32549de882
Binary files /dev/null and b/impetusModel/plots_v1/Fig4_Compare_sum_model_v1_3.pdf differ
diff --git a/impetusModel/plots_v1/Fig5_Chart_savings_v1_3_by_month.pdf b/impetusModel/plots_v1/Fig5_Chart_savings_v1_3_by_month.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..d3ba5c56a8e4350333d10ccc92c5180097de53dc
Binary files /dev/null and b/impetusModel/plots_v1/Fig5_Chart_savings_v1_3_by_month.pdf differ
diff --git a/impetusModel/plots_v1/baselineMadjWeMonthlyByYearMetering.pdf b/impetusModel/plots_v1/baselineMadjWeMonthlyByYearMetering.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..dc71c49b8de540c0e86f37b407f8d3f947cd620e
Binary files /dev/null and b/impetusModel/plots_v1/baselineMadjWeMonthlyByYearMetering.pdf differ
diff --git a/impetusModel/plots_v1/compareBaselineWEDroughtWE_v1.3.pdf b/impetusModel/plots_v1/compareBaselineWEDroughtWE_v1.3.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..5eddc372045f620c88da084fac5fb141074bde7c
Binary files /dev/null and b/impetusModel/plots_v1/compareBaselineWEDroughtWE_v1.3.pdf differ
diff --git a/impetusModel/plots_v1/pcSavedBaselineWEDroughtWE_v1.3.pdf b/impetusModel/plots_v1/pcSavedBaselineWEDroughtWE_v1.3.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..d1b2e3886b1fd0dc6684b560a0d626e3774b0b1a
Binary files /dev/null and b/impetusModel/plots_v1/pcSavedBaselineWEDroughtWE_v1.3.pdf differ
diff --git a/impetusModel/plots_v2/.DS_Store b/impetusModel/plots_v2/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..5008ddfcf53c02e82d7eee2e57c38e5672ef89f6
Binary files /dev/null and b/impetusModel/plots_v2/.DS_Store differ
diff --git a/impetusModel/plots_v2/Final_model_v2_0_2012_by_month.pdf b/impetusModel/plots_v2/Final_model_v2_0_2012_by_month.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..2eee47ba9506b95fde5175da0ce71ae52068f65e
Binary files /dev/null and b/impetusModel/plots_v2/Final_model_v2_0_2012_by_month.pdf differ
diff --git a/impetusModel/plots_v2/baselineByMetering.pdf b/impetusModel/plots_v2/baselineByMetering.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..145590623fea9f6c5942958f52206fa13666b508
Binary files /dev/null and b/impetusModel/plots_v2/baselineByMetering.pdf differ
diff --git a/impetusModel/plots_v2/baselineMadjWeMonthlyByYearMetering.pdf b/impetusModel/plots_v2/baselineMadjWeMonthlyByYearMetering.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..22df1963fb088d9d6df4f5afa4aea30ce480f75f
Binary files /dev/null and b/impetusModel/plots_v2/baselineMadjWeMonthlyByYearMetering.pdf differ
diff --git a/impetusModel/plots_v2/baselineMadjWeMonthlyComponentByMetering.pdf b/impetusModel/plots_v2/baselineMadjWeMonthlyComponentByMetering.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..b42f22d6cf63ea8dfaafff6ee0d2d502e3715a0d
Binary files /dev/null and b/impetusModel/plots_v2/baselineMadjWeMonthlyComponentByMetering.pdf differ
diff --git a/impetusModel/plots_v2/baselineMadjWeMonthlyTotalByMetering.pdf b/impetusModel/plots_v2/baselineMadjWeMonthlyTotalByMetering.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..6861497e8c6bc6622a809d6092ee1a8a880e9e0e
Binary files /dev/null and b/impetusModel/plots_v2/baselineMadjWeMonthlyTotalByMetering.pdf differ
diff --git a/impetusModel/plots_v2/baselineWeDroughtModelPcSavings.pdf b/impetusModel/plots_v2/baselineWeDroughtModelPcSavings.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..591e0b952c6702829eb66e2d0dd30d106955c984
Binary files /dev/null and b/impetusModel/plots_v2/baselineWeDroughtModelPcSavings.pdf differ
diff --git a/impetusModel/plots_v2/compareBaselineWEDroughtWE_v1.3.pdf b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v1.3.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..4bbc77e19d25c1090fbd9d199a41d86943c6b4ed
Binary files /dev/null and b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v1.3.pdf differ
diff --git a/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2.0.pdf b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2.0.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..a926d530b887d174116c012088f88ab08a7483ad
Binary files /dev/null and b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2.0.pdf differ
diff --git a/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2_0.pdf b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2_0.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..57d14f828310d3746d6d895672fd2cc348528915
Binary files /dev/null and b/impetusModel/plots_v2/compareBaselineWEDroughtWE_v2_0.pdf differ
diff --git a/impetusModel/plots_v2/compareWithESTlitres.pdf b/impetusModel/plots_v2/compareWithESTlitres.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..29b0868229d8e80ac4a9ff4df0602d6778cd037e
Binary files /dev/null and b/impetusModel/plots_v2/compareWithESTlitres.pdf differ
diff --git a/impetusModel/plots_v2/compareWithESTpercent.pdf b/impetusModel/plots_v2/compareWithESTpercent.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..1ba6763175d75edf1aa8b9b928fa7c18be139072
Binary files /dev/null and b/impetusModel/plots_v2/compareWithESTpercent.pdf differ
diff --git a/impetusModel/plots_v2/pcSavedBaselineWEDroughtEnhancedWE_v2_0.pdf b/impetusModel/plots_v2/pcSavedBaselineWEDroughtEnhancedWE_v2_0.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..125d31e5edcdb45edcd2a7a2ef09c6a049a86a60
Binary files /dev/null and b/impetusModel/plots_v2/pcSavedBaselineWEDroughtEnhancedWE_v2_0.pdf differ
diff --git a/impetusModel/plots_v2/pcSavedBaselineWEDroughtWE_v1.3.pdf b/impetusModel/plots_v2/pcSavedBaselineWEDroughtWE_v1.3.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..5595739315cb70397ed8d39b53806de0b02cc305
Binary files /dev/null and b/impetusModel/plots_v2/pcSavedBaselineWEDroughtWE_v1.3.pdf differ
diff --git a/model_v2/SPRG_demand_v2.1_BA.Rmd b/model_v2/SPRG_demand_v2.1_BA.Rmd
index 076caa0a751db4a93753adb309cc942a12ec7f63..997e5743ca02c92bf01e44662c4a61738ae8488c 100644
--- a/model_v2/SPRG_demand_v2.1_BA.Rmd
+++ b/model_v2/SPRG_demand_v2.1_BA.Rmd
@@ -15,7 +15,7 @@ output:
toc: yes
toc_depth: 4
toc_float: yes
-bibliography: ~/bibliography.bib
+bibliography: '`r paste0(here::here(), "/bibliography.bib")`'
---
```{r setup, include=FALSE}
@@ -34,27 +34,15 @@ knitr::opts_chunk$set(tidy = TRUE) # tidy up code in case echo = TRUE
# libraries required should already be loaded
# library(tidyverse)
# library (knitr)
-
-# Housekeeping ----
-rm(list=ls(all=TRUE)) # remove all objects from workspace
+library(here)
# Set start time ----
startTime <- Sys.time()
# default code location - needed to load functions & parameters correctly so
# has to be run here and not in the functions file as we can't find the functions file without it!
-# use Mikey Harper's code to work out where we are
-# only problem with this is that if you print projLoc this will reveal the full path (including username) in any output document
-mh_findParentDirectory <- function(Parent){
- directory <-getwd()
- while(basename(directory) != Parent){
- directory <- dirname(directory)
-
- }
-return(directory)
-}
-
-projLoc <- mh_findParentDirectory("IMPETUS")
+
+projLoc <- here::here()
# Functions ----
print(paste0("Loading functions from ", projLoc,"/impetusFunctions.R"))
@@ -83,7 +71,7 @@ print(paste0("Running on ", sysName, " with projLoc = ", projLoc)) # sysName is
if(startsWith(userName, "ben")) # => BA laptop
iPath <- paste0(iPath, "model_v2/")
if(startsWith(userName, "ben")) # => BA laptop
- oPath <- paste0(oPath, "model_v2/")
+ oPath <- paste0(dPath, "/model_outputs/")
# set paths for DM laptop ----
if(startsWith(userName, "despina")) # => DM laptop
diff --git a/model_v2/SPRG_demand_v2.1_BA.html b/model_v2/SPRG_demand_v2.1_BA.html
index 0aa4b4f6fab5964624415d0d1382b7485b4026bb..340d811c09f5bf3f53222560ecb178b83fd12654 100644
--- a/model_v2/SPRG_demand_v2.1_BA.html
+++ b/model_v2/SPRG_demand_v2.1_BA.html
@@ -1,12 +1,12 @@
<!DOCTYPE html>
-<html xmlns="http://www.w3.org/1999/xhtml">
+<html>
<head>
<meta charset="utf-8" />
-<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
+<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
<meta name="author" content="Despina Manouseli & Ben Anderson" />
@@ -24,8 +24,19 @@
<link href="SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.css" rel="stylesheet" />
<script src="SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.js"></script>
<script src="SPRG_demand_v2.1_BA_files/navigation-1.1/tabsets.js"></script>
-<link href="SPRG_demand_v2.1_BA_files/highlightjs-1.1/default.css" rel="stylesheet" />
-<script src="SPRG_demand_v2.1_BA_files/highlightjs-1.1/highlight.js"></script>
+<link href="SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/default.css" rel="stylesheet" />
+<script src="SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/highlight.js"></script>
+<link href="SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.css" rel="stylesheet" />
+<script src="SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.js"></script>
+
+<style type="text/css">
+ code{white-space: pre-wrap;}
+ span.smallcaps{font-variant: small-caps;}
+ span.underline{text-decoration: underline;}
+ div.column{display: inline-block; vertical-align: top; width: 50%;}
+ div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+ ul.task-list{list-style: none;}
+ </style>
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
@@ -34,10 +45,12 @@
}
</style>
<script type="text/javascript">
-if (window.hljs && document.readyState && document.readyState === "complete") {
- window.setTimeout(function() {
- hljs.initHighlighting();
- }, 0);
+if (window.hljs) {
+ hljs.configure({languages: []});
+ hljs.initHighlightingOnLoad();
+ if (document.readyState && document.readyState === "complete") {
+ window.setTimeout(function() { hljs.initHighlighting(); }, 0);
+ }
}
</script>
@@ -71,9 +84,7 @@ h6 {
</style>
-</head>
-<body>
<style type = "text/css">
.main-container {
@@ -87,58 +98,83 @@ code {
}
img {
max-width:100%;
- height: auto;
}
.tabbed-pane {
padding-top: 12px;
}
+.html-widget {
+ margin-bottom: 20px;
+}
button.code-folding-btn:focus {
outline: none;
}
+summary {
+ display: list-item;
+}
</style>
-<div class="container-fluid main-container">
-
<!-- tabsets -->
-<script>
-$(document).ready(function () {
- window.buildTabsets("TOC");
-});
-</script>
-<!-- code folding -->
+<style type="text/css">
+.tabset-dropdown > .nav-tabs {
+ display: inline-table;
+ max-height: 500px;
+ min-height: 44px;
+ overflow-y: auto;
+ background: white;
+ border: 1px solid #ddd;
+ border-radius: 4px;
+}
+.tabset-dropdown > .nav-tabs > li.active:before {
+ content: "";
+ font-family: 'Glyphicons Halflings';
+ display: inline-block;
+ padding: 10px;
+ border-right: 1px solid #ddd;
+}
+.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
+ content: "";
+ border: none;
+}
+.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
+ content: "";
+ font-family: 'Glyphicons Halflings';
+ display: inline-block;
+ padding: 10px;
+ border-right: 1px solid #ddd;
+}
-<script>
-$(document).ready(function () {
+.tabset-dropdown > .nav-tabs > li.active {
+ display: block;
+}
- // move toc-ignore selectors from section div to header
- $('div.section.toc-ignore')
- .removeClass('toc-ignore')
- .children('h1,h2,h3,h4,h5').addClass('toc-ignore');
+.tabset-dropdown > .nav-tabs > li > a,
+.tabset-dropdown > .nav-tabs > li > a:focus,
+.tabset-dropdown > .nav-tabs > li > a:hover {
+ border: none;
+ display: inline-block;
+ border-radius: 4px;
+ background-color: transparent;
+}
+
+.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
+ display: block;
+ float: none;
+}
+
+.tabset-dropdown > .nav-tabs > li {
+ display: none;
+}
+</style>
+
+<!-- code folding -->
- // establish options
- var options = {
- selectors: "h1,h2,h3,h4",
- theme: "bootstrap3",
- context: '.toc-content',
- hashGenerator: function (text) {
- return text.replace(/[.\\/?&!#<>]/g, '').replace(/\s/g, '_').toLowerCase();
- },
- ignoreSelector: ".toc-ignore",
- scrollTo: 0
- };
- options.showAndHide = true;
- options.smoothScroll = true;
- // tocify
- var toc = $("#TOC").tocify(options).data("toc-tocify");
-});
-</script>
<style type="text/css">
@@ -152,6 +188,12 @@ $(document).ready(function () {
}
}
+@media print {
+.toc-content {
+ /* see https://github.com/w3c/csswg-drafts/issues/4434 */
+ float: right;
+}
+}
.toc-content {
padding-left: 30px;
@@ -187,8 +229,6 @@ div.tocify {
.tocify-subheader .tocify-item {
font-size: 0.90em;
- padding-left: 25px;
- text-indent: 0;
}
.tocify .list-group-item {
@@ -198,6 +238,16 @@ div.tocify {
</style>
+
+
+</head>
+
+<body>
+
+
+<div class="container-fluid main-container">
+
+
<!-- setup 3col/9col grid for toc_float and main content -->
<div class="row-fluid">
<div class="col-xs-12 col-sm-4 col-md-3">
@@ -215,8 +265,8 @@ div.tocify {
<h1 class="title toc-ignore">Domestic Water Demand Estimation Using SPRG Survey</h1>
-<h4 class="author"><em>Despina Manouseli & Ben Anderson</em></h4>
-<h4 class="date"><em>Last run at: 2017-06-19 21:38:24</em></h4>
+<h4 class="author">Despina Manouseli & Ben Anderson</h4>
+<h4 class="date">Last run at: 2021-03-11 16:50:37</h4>
</div>
@@ -244,17 +294,31 @@ div.tocify {
<div id="set-directories-and-import-data" class="section level1">
<h1><span class="header-section-number">3</span> Set directories and import data</h1>
<p>First, load the SPRG survey data that is used for the household attributes.</p>
-<pre class="r"><code># dPath <- 'C:/Users/despina/Desktop/ImpetusPackageJan2017/' fpath <-
-# paste0(dPath, '/') opath <- paste0(dPath, '/') print(paste0('Data path:
-# ',dPath)) print(paste0('Data path: ',dPath)) Surveydata <-
-# read.csv('C:/Users/despina/Desktop/ImpetusPackageJan2017/SPRGdata_duplicateDELETED.csv')
+<pre class="r"><code># dPath <- "C:/Users/despina/Desktop/ImpetusPackageJan2017/"
+# fpath <- paste0(dPath, "/")
+# opath <- paste0(dPath, "/")
+# print(paste0("Data path: ",dPath))
+# print(paste0("Data path: ",dPath))
+#Surveydata <- read.csv("C:/Users/despina/Desktop/ImpetusPackageJan2017/SPRGdata_duplicateDELETED.csv")
Surveydata <- read.csv(paste0(iPath, "SPRG dataset/SPRGdata_duplicateDELETED.csv"))
-t <- Surveydata[1:10, 1:8]
+t <- Surveydata[1:10,1:8]
-kable(caption = "Example rows/columns SPRG data table", t)</code></pre>
+kable(caption = "Example rows/columns SPRG data table",
+ t
+)</code></pre>
<table>
<caption>Example rows/columns SPRG data table</caption>
+<colgroup>
+<col width="4%" />
+<col width="9%" />
+<col width="2%" />
+<col width="7%" />
+<col width="6%" />
+<col width="38%" />
+<col width="22%" />
+<col width="8%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">iobs</th>
@@ -372,12 +436,14 @@ kable(caption = "Example rows/columns SPRG data table", t)</code></pre
</table>
<pre class="r"><code>t <- with(Surveydata, table(q2d_1, q2b_1, useNA = "always"))
-kable(caption = "SPRG: age and work status distributions of respondents", t)</code></pre>
+kable(caption = "SPRG: age and work status distributions of respondents",
+ t
+)</code></pre>
<table>
<caption>SPRG: age and work status distributions of respondents</caption>
<thead>
<tr class="header">
-<th></th>
+<th align="left"></th>
<th align="right">16-24</th>
<th align="right">25-34</th>
<th align="right">35-44</th>
@@ -391,7 +457,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
</thead>
<tbody>
<tr class="odd">
-<td>full-time paid work (30+ hrs per week)</td>
+<td align="left">full-time paid work (30+ hrs per week)</td>
<td align="right">39</td>
<td align="right">165</td>
<td align="right">170</td>
@@ -403,7 +469,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>looking after home/family</td>
+<td align="left">looking after home/family</td>
<td align="right">6</td>
<td align="right">33</td>
<td align="right">40</td>
@@ -415,7 +481,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>other</td>
+<td align="left">other</td>
<td align="right">0</td>
<td align="right">14</td>
<td align="right">10</td>
@@ -427,7 +493,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>part-time paid work (8 - 29 hrs per week)</td>
+<td align="left">part-time paid work (8 - 29 hrs per week)</td>
<td align="right">9</td>
<td align="right">38</td>
<td align="right">51</td>
@@ -439,7 +505,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>part-time paid work (under 8 hrs per week)</td>
+<td align="left">part-time paid work (under 8 hrs per week)</td>
<td align="right">0</td>
<td align="right">1</td>
<td align="right">1</td>
@@ -451,7 +517,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>permanently sick/disabled</td>
+<td align="left">permanently sick/disabled</td>
<td align="right">2</td>
<td align="right">2</td>
<td align="right">6</td>
@@ -463,7 +529,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>retired</td>
+<td align="left">retired</td>
<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
@@ -475,7 +541,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>self-employed</td>
+<td align="left">self-employed</td>
<td align="right">2</td>
<td align="right">10</td>
<td align="right">14</td>
@@ -487,7 +553,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>student (16 - 18 years old)</td>
+<td align="left">student (16 - 18 years old)</td>
<td align="right">35</td>
<td align="right">0</td>
<td align="right">0</td>
@@ -499,7 +565,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>student (19 - 24 years old)</td>
+<td align="left">student (19 - 24 years old)</td>
<td align="right">43</td>
<td align="right">0</td>
<td align="right">0</td>
@@ -511,7 +577,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>unemployed (not seeking work)</td>
+<td align="left">unemployed (not seeking work)</td>
<td align="right">3</td>
<td align="right">11</td>
<td align="right">7</td>
@@ -523,7 +589,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="even">
-<td>unemployed (seeking work)</td>
+<td align="left">unemployed (seeking work)</td>
<td align="right">14</td>
<td align="right">20</td>
<td align="right">15</td>
@@ -535,7 +601,7 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>NA</td>
+<td align="left">NA</td>
<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
@@ -550,10 +616,11 @@ kable(caption = "SPRG: age and work status distributions of respondents&quo
</table>
<p>The SPRG Survey dataset has 1800 observations.</p>
<p>Next, load the two EST (2013) data files which give frequencies of use of dishwashers, baths and showers.</p>
-<pre class="r"><code>ESTdata_dish <- read.table(paste0(iPath, "SPRG dataset/DishWashFreq_EST.txt"),
- header = TRUE)
+<pre class="r"><code>ESTdata_dish <- read.table(paste0(iPath, "SPRG dataset/DishWashFreq_EST.txt"), header = TRUE)
-kable(caption = "EST data table for dishwasher frequencies", ESTdata_dish)</code></pre>
+kable(caption = "EST data table for dishwasher frequencies",
+ ESTdata_dish
+)</code></pre>
<table>
<caption>EST data table for dishwasher frequencies</caption>
<thead>
@@ -605,10 +672,11 @@ kable(caption = "EST data table for dishwasher frequencies", ESTdata_d
</tr>
</tbody>
</table>
-<pre class="r"><code>ESTdata_showerBath <- read.table(paste0(iPath, "SPRG dataset/ShowerBathFreq_EST.txt"),
- header = TRUE)
+<pre class="r"><code>ESTdata_showerBath <- read.table(paste0(iPath, "SPRG dataset/ShowerBathFreq_EST.txt"), header = TRUE)
-kable(caption = "EST data table for shower and bath frequencies", ESTdata_showerBath)</code></pre>
+kable(caption = "EST data table for shower and bath frequencies",
+ ESTdata_showerBath
+)</code></pre>
<table>
<caption>EST data table for shower and bath frequencies</caption>
<thead>
@@ -678,17 +746,17 @@ kable(caption = "EST data table for shower and bath frequencies", ESTd
<h2><span class="header-section-number">4.1</span> Bathroom sink use (Teeth brushing and washing of hands)</h2>
<div id="washing-of-hands" class="section level3">
<h3><span class="header-section-number">4.1.1</span> Washing of hands</h3>
-<pre class="r"><code>handdemand <- select(Surveydata, iobs, bmg_id, q2, q4)
-handdemand <- rename(handdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4)
-handdemand_hh <- mutate(handdemand, hands = (10.4 * hhsize * 30)) #Based on: http://avonlakewater.org/for-our-customers/how-much-water-do-i-use-when-i/ hand washing is 0.55 gal/wash. with a frequency of use of 5 times a day this is 2.75 gal/day=10.4 lt/day/person-for a standard faucet.
+<pre class="r"><code>handdemand<-select(Surveydata, iobs,bmg_id, q2, q4)
+handdemand<-rename(handdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4)
+handdemand_hh<-mutate(handdemand,hands= (10.4*hhsize*30)) #Based on: http://avonlakewater.org/for-our-customers/how-much-water-do-i-use-when-i/ hand washing is 0.55 gal/wash. with a frequency of use of 5 times a day this is 2.75 gal/day=10.4 lt/day/person-for a standard faucet.
summary(handdemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
## hands
## Min. : 312.0
## 1st Qu.: 624.0
@@ -696,7 +764,9 @@ summary(handdemand_hh)</code></pre>
## Mean : 828.4
## 3rd Qu.:1248.0
## Max. :3120.0</code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for washing hands", handdemand_hh[1:5, ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for washing hands",
+ handdemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for washing hands</caption>
<thead>
@@ -744,44 +814,26 @@ summary(handdemand_hh)</code></pre>
<td align="left">yes</td>
<td align="right">1248</td>
</tr>
-<tr class="even">
-<td align="right">### Te</td>
-<td align="right">eth brushing</td>
-<td align="right"></td>
-<td align="left"></td>
-<td align="right"></td>
-</tr>
</tbody>
</table>
-<pre class="r"><code>teethdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q36, q37)
-teethdemand1 <- rename(teethdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4,
- wash_freq = q36, teeth_where = q37)
-teethdemand1[, 5] <- ifelse(teethdemand1[, 5] == "after meals", 4, ifelse(teethdemand1[,
- 5] == "after some meals, plus morning and night", 4, ifelse(teethdemand1[,
- 5] == "don't want to answer", NA, ifelse(teethdemand1[, 5] == "just at night",
- 1, ifelse(teethdemand1[, 5] == "just in the morning", 1, ifelse(teethdemand1[,
- 5] == "more than once a day, but not at fixed times", 2, ifelse(teethdemand1[,
- 5] == "morning and night", 2, ifelse(teethdemand1[, 5] == "once a day, but not at a fixed time",
- 1, ifelse(teethdemand1[, 5] == "only have dentures", 0, ifelse(teethdemand1[,
- 5] == "other", NA, NA))))))))))
-teethdemand1[, 6] <- ifelse(teethdemand1[, 6] == "at a sink with a cup of water",
- 1.42, ifelse(teethdemand1[, 6] == "at a sink without a tap running", 1.42,
- ifelse(teethdemand1[, 6] == "at the sink with a tap running", 16.7,
- ifelse(teethdemand1[, 6] == "don't want to answer", NA, ifelse(teethdemand1[,
- 6] == "in the bath", 0, ifelse(teethdemand1[, 6] == "in the shower",
- 0, ifelse(teethdemand1[, 6] == "other", 0, NA)))))))
-
-teethdemand_hh <- mutate(teethdemand1, teethbrush_hh = (wash_freq * hhsize *
- teeth_where * 30))
+</div>
+<div id="teeth-brushing" class="section level3">
+<h3><span class="header-section-number">4.1.2</span> Teeth brushing</h3>
+<pre class="r"><code>teethdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q36,q37)
+teethdemand1<-rename(teethdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, wash_freq=q36, teeth_where=q37)
+teethdemand1[,5] <- ifelse(teethdemand1[,5] == "after meals", 4 ,ifelse(teethdemand1[,5] == "after some meals, plus morning and night", 4, ifelse(teethdemand1[,5] == "don't want to answer", NA ,ifelse(teethdemand1[,5] == "just at night", 1, ifelse(teethdemand1[,5] == "just in the morning", 1,ifelse(teethdemand1[,5] == "more than once a day, but not at fixed times", 2,ifelse(teethdemand1[,5] == "morning and night", 2, ifelse(teethdemand1[,5] == "once a day, but not at a fixed time", 1 , ifelse(teethdemand1[,5] == "only have dentures", 0 ,ifelse(teethdemand1[,5] == "other", NA, NA))))))))))
+teethdemand1[,6]<- ifelse(teethdemand1[,6] == "at a sink with a cup of water", 1.42 ,ifelse(teethdemand1[,6] == "at a sink without a tap running", 1.42, ifelse(teethdemand1[,6] == "at the sink with a tap running", 16.7, ifelse(teethdemand1[,6] == "don't want to answer", NA,ifelse(teethdemand1[,6] == "in the bath", 0,ifelse(teethdemand1[,6] == "in the shower", 0,ifelse(teethdemand1[,6] == "other", 0, NA)))))))
+
+teethdemand_hh<-mutate(teethdemand1,teethbrush_hh= (wash_freq*hhsize*teeth_where*30))
summary(teethdemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## wash_freq teeth_where teethbrush_hh
## Min. :0.000 Min. : 0.000 Min. : 0.0
## 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
@@ -790,8 +842,9 @@ summary(teethdemand_hh)</code></pre>
## 3rd Qu.:2.000 3rd Qu.:16.700 3rd Qu.: 1002.0
## Max. :4.000 Max. :16.700 Max. :12024.0
## NA's :22 NA's :42 NA's :53</code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for teeth brushing", teethdemand_hh[1:5,
- ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for teeth brushing",
+ teethdemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for teeth brushing</caption>
<thead>
@@ -851,32 +904,25 @@ summary(teethdemand_hh)</code></pre>
<td align="right">1.42</td>
<td align="right">340.8</td>
</tr>
-<tr class="even">
-<td align="right">### To</td>
-<td align="right">tal bathroom</td>
-<td align="right">sink use</td>
-<td align="left"></td>
-<td align="right"></td>
-<td align="right"></td>
-<td align="right"></td>
-</tr>
</tbody>
</table>
-<pre class="r"><code>bathsink_hh <- merge(x = teethdemand_hh, y = handdemand_hh, by = "id", all = TRUE)
-bathsink_hh <- mutate(bathsink_hh, monthlyBathroomSinkUse = (teethbrush_hh +
- hands))
+</div>
+<div id="total-bathroom-sink-use" class="section level3">
+<h3><span class="header-section-number">4.1.3</span> Total bathroom sink use</h3>
+<pre class="r"><code>bathsink_hh<-merge(x = teethdemand_hh, y = handdemand_hh, by = "id", all = TRUE)
+bathsink_hh<-mutate(bathsink_hh,monthlyBathroomSinkUse= (teethbrush_hh+hands))
-bathsink_hh <- bathsink_hh[, -(8:10), drop = FALSE] #droping columns I dont need
-bathsink_hh <- mutate(bathsink_hh, dailyBathroomSinkUse = (monthlyBathroomSinkUse/30))
+bathsink_hh<-bathsink_hh[,-(8:10),drop=FALSE]#droping columns I dont need
+bathsink_hh<-mutate(bathsink_hh,dailyBathroomSinkUse= (monthlyBathroomSinkUse/30))
summary(bathsink_hh)</code></pre>
-<pre><code>## id obs.x hhsize.x meter.x
-## Min. :836900048 Min. : 2.0 Min. : 1.000 don't know:167
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 no :864
-## Median :836920637 Median : 905.5 Median : 2.000 yes :769
-## Mean :836919052 Mean : 906.0 Mean : 2.655
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
-## Max. :836965495 Max. :1810.0 Max. :10.000
-##
+<pre><code>## id obs.x hhsize.x meter.x
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :1810.0 Max. :10.000
+##
## wash_freq teeth_where teethbrush_hh hands
## Min. :0.000 Min. : 0.000 Min. : 0.0 Min. : 312.0
## 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4 1st Qu.: 624.0
@@ -893,9 +939,23 @@ summary(bathsink_hh)</code></pre>
## 3rd Qu.: 1986.0 3rd Qu.: 66.20
## Max. :13896.0 Max. :463.20
## NA's :53 NA's :53</code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for washing of hands", bathsink_hh[1:5, ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for washing of hands",
+ bathsink_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for washing of hands</caption>
+<colgroup>
+<col width="8%" />
+<col width="4%" />
+<col width="7%" />
+<col width="9%" />
+<col width="8%" />
+<col width="9%" />
+<col width="11%" />
+<col width="4%" />
+<col width="18%" />
+<col width="17%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">id</th>
@@ -971,78 +1031,54 @@ summary(bathsink_hh)</code></pre>
<td align="right">1588.8</td>
<td align="right">52.96</td>
</tr>
-<tr class="even">
-<td align="right">### Plot of</td>
-<td align="right">bathroom</td>
-<td align="right">sink deman</td>
-<td align="left">d per househo</td>
-<td align="right">ld size</td>
-<td align="right"></td>
-<td align="right"></td>
-<td align="right"></td>
-<td align="right"></td>
-<td align="right"></td>
-</tr>
</tbody>
</table>
-<pre class="r"><code>ggplot(data = bathsink_hh) + aes(y = monthlyBathroomSinkUse, x = factor(hhsize.x)) +
- geom_boxplot() + labs(title = "total bathroom sink use (l/house/month)")</code></pre>
+</div>
+<div id="plot-of-bathroom-sink-demand-per-household-size" class="section level3">
+<h3><span class="header-section-number">4.1.4</span> Plot of bathroom sink demand per household size</h3>
+<pre class="r"><code>ggplot(data=bathsink_hh)+ aes(y = monthlyBathroomSinkUse, x = factor(hhsize.x)) +
+ geom_boxplot() +
+ labs(title = "total bathroom sink use (l/house/month)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bathsink%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(bathsink_hh[bathsink_hh$meter.x == "yes" | bathsink_hh$meter.x == "no",
- ], aes(factor(hhsize.x), monthlyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x)) +
- labs(title = "sink demand (l/household/month)") + xlab("household size") +
- ylab("sink demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(bathsink_hh[bathsink_hh$meter.x == "yes"|bathsink_hh$meter.x == "no",], aes(factor(hhsize.x), monthlyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x))+labs(title = "sink demand (l/household/month)")+ xlab('household size')+ylab('sink demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bathsink%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(bathsink_hh[bathsink_hh$meter.x == "yes" | bathsink_hh$meter.x == "no",
- ], aes(factor(hhsize.x), dailyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x)) +
- labs(title = "sink demand (l/household/day)") + xlab("household size") +
- ylab("sink demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(bathsink_hh[bathsink_hh$meter.x == "yes"|bathsink_hh$meter.x == "no",], aes(factor(hhsize.x), dailyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x))+labs(title = "sink demand (l/household/day)")+ xlab('household size')+ylab('sink demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bathsink%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
</div>
<div id="bathing-water-demand" class="section level2">
<h2><span class="header-section-number">4.2</span> Bathing water demand</h2>
-<pre class="r"><code>bathdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q29_1, q7a_5)
-bathdemand1 <- rename(bathdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4,
- bath_freq = q29_1, baths = q7a_5)
-bathdemand1[, 5] <- ifelse(bathdemand1[, 5] == "once a week", 1, ifelse(bathdemand1[,
- 5] == "twice a week", 2, ifelse(bathdemand1[, 5] == "three times a week",
- 3, ifelse(bathdemand1[, 5] == "four times a week", 4, ifelse(bathdemand1[,
- 5] == "five times a week", 5, ifelse(bathdemand1[, 5] == "six times a week",
- 6, ifelse(bathdemand1[, 5] == "seven times a week", 7, ifelse(bathdemand1[,
- 5] == "more than seven times a week", 9, ifelse(bathdemand1[, 5] ==
- "none", 0, NA)))))))))
+<pre class="r"><code>bathdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q29_1, q7a_5)
+bathdemand1<-rename(bathdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, bath_freq=q29_1, baths=q7a_5)
+bathdemand1[,5] <- ifelse(bathdemand1[,5] == "once a week", 1 ,ifelse(bathdemand1[,5] == "twice a week", 2, ifelse(bathdemand1[,5] == "three times a week", 3 ,ifelse(bathdemand1[,5] == "four times a week", 4, ifelse(bathdemand1[,5] == "five times a week", 5,ifelse(bathdemand1[,5] == "six times a week", 6,ifelse(bathdemand1[,5] == "seven times a week", 7, ifelse(bathdemand1[,5] == "more than seven times a week", 9 , ifelse(bathdemand1[,5] == "none", 0 ,NA)))))))))
# the ones that do not have baths were left out.
-single_occup_bath <- filter(bathdemand1, hhsize == 1)
-mean(single_occup_bath$bath_freq, na.rm = TRUE) # mean frequency of bathing is 1.87 times/week for one-person homes. In the EST sample, it is 1.7 (judging by the graph-Figure 8).</code></pre>
+single_occup_bath<-filter(bathdemand1, hhsize == 1)
+mean (single_occup_bath$bath_freq,na.rm=TRUE) # mean frequency of bathing is 1.87 times/week for one-person homes. In the EST sample, it is 1.7 (judging by the graph-Figure 8).</code></pre>
<pre><code>## [1] 1.871314</code></pre>
-<pre class="r"><code># i want to assume frequencies by household-I only have for the respondent.
-bathdemand1 <- mutate(bathdemand1, housefreq = bath_freq * hhsize)
+<pre class="r"><code>#i want to assume frequencies by household-I only have for the respondent.
+bathdemand1<-mutate(bathdemand1, housefreq=bath_freq*hhsize)
-bathdemand_EST <- merge(x = bathdemand1, y = ESTdata_showerBath, by = "hhsize",
- all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (baths_freq_EST, baths_freq_EST).
+bathdemand_EST<-merge(x = bathdemand1, y = ESTdata_showerBath, by = "hhsize", all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (baths_freq_EST, baths_freq_EST).
-bathdemand_hh <- mutate(bathdemand_EST, monthlyBathUse = (1.87 * baths_freq_EST/1.7) *
- 4 * 80) #monthlyBathUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by bath (80 litres, (EST, 2013)).
+bathdemand_hh<-mutate(bathdemand_EST,monthlyBathUse= (1.87*baths_freq_EST/1.7)*4*80) #monthlyBathUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by bath (80 litres, (EST, 2013)).
-bathdemand_hh$monthlyBathUse <- ifelse(bathdemand_hh$baths == 0, 0, bathdemand_hh$monthlyBathUse)
-bathdemand_hh$dailyBathUse <- bathdemand_hh$monthlyBathUse/30 #'At home with water2' reports 51 l/hh/day for their sample for baths. Our mean is 35.5 l/hh/d. Reasonable but lower than theirs (zero consumption was included in the calculation of mean)
+bathdemand_hh$monthlyBathUse <- ifelse (bathdemand_hh$baths==0, 0, bathdemand_hh$monthlyBathUse)
+bathdemand_hh$dailyBathUse<-bathdemand_hh$monthlyBathUse/30 #'At home with water2' reports 51 l/hh/day for their sample for baths. Our mean is 35.5 l/hh/d. Reasonable but lower than theirs (zero consumption was included in the calculation of mean)
-# households that had no baths in their bathrooms, were assumed as not
-# taking any baths
-summary(bathdemand_hh)</code></pre>
-<pre><code>## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
+# households that had no baths in their bathrooms, were assumed as not taking any baths
+summary(bathdemand_hh) </code></pre>
+<pre><code>## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+##
## bath_freq baths housefreq baths_freq_EST
## Min. :0.000 Min. :0.0000 Min. : 0.000 Min. :1.700
## 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.: 0.000 1st Qu.:2.250
@@ -1059,9 +1095,24 @@ summary(bathdemand_hh)</code></pre>
## 3rd Qu.:14.65 3rd Qu.:1707.2 3rd Qu.:56.91
## Max. :16.05 Max. :2323.2 Max. :77.44
## </code></pre>
-<pre class="r"><code>kable(caption = "Summary of bath demand", bathdemand_hh[1:5, ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of bath demand",
+ bathdemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of bath demand</caption>
+<colgroup>
+<col width="6%" />
+<col width="4%" />
+<col width="8%" />
+<col width="5%" />
+<col width="8%" />
+<col width="5%" />
+<col width="8%" />
+<col width="13%" />
+<col width="14%" />
+<col width="13%" />
+<col width="11%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">hhsize</th>
@@ -1146,52 +1197,39 @@ summary(bathdemand_hh)</code></pre>
</tbody>
</table>
<p>Plot of bath demand per household size</p>
-<pre class="r"><code>ggplot(data = bathdemand_hh) + aes(y = monthlyBathUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total bath use (l/house/day)")</code></pre>
+<pre class="r"><code>ggplot(data=bathdemand_hh)+ aes(y = monthlyBathUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total bath use (l/house/day)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bath%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(bathdemand_hh[bathdemand_hh$meter == "yes" | bathdemand_hh$meter == "no",
- ], aes(factor(hhsize), monthlyBathUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "bath demand (l/household/month)") + xlab("household size") +
- ylab("bath demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(bathdemand_hh[bathdemand_hh$meter == "yes"|bathdemand_hh$meter == "no",], aes(factor(hhsize), monthlyBathUse)) + geom_boxplot(aes(fill = meter))+labs(title = "bath demand (l/household/month)")+ xlab('household size')+ylab('bath demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bath%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(bathdemand_hh[bathdemand_hh$meter == "yes" | bathdemand_hh$meter == "no",
- ], aes(factor(hhsize), dailyBathUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "bath demand (l/household/day)") + xlab("household size") +
- ylab("bath demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(bathdemand_hh[bathdemand_hh$meter == "yes"|bathdemand_hh$meter == "no",], aes(factor(hhsize), dailyBathUse)) + geom_boxplot(aes(fill = meter))+labs(title = "bath demand (l/household/day)")+ xlab('household size')+ylab('bath demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/bath%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="dishwasher-demand" class="section level2">
<h2><span class="header-section-number">4.3</span> Dishwasher demand</h2>
-<pre class="r"><code>DishDemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_13, q44b)
-DishDemand <- rename(DishDemand, obs = iobs, id = bmg_id, hhsize = q2, dishwashers = q7a_13,
- dish_freq = q44b, meter = q4)
+<pre class="r"><code>DishDemand<-select(Surveydata, iobs,bmg_id, q2,q4, q7a_13, q44b)
+DishDemand<-rename(DishDemand, obs =iobs, id=bmg_id, hhsize=q2,dishwashers=q7a_13, dish_freq=q44b, meter=q4 )
summary(DishDemand)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
-## dishwashers dish_freq
-## Min. :0.0000 :1039
-## 1st Qu.:0.0000 once a day : 216
-## Median :0.0000 every couple of days : 195
-## Mean :0.4233 when the dishwasher/sink is full: 167
-## 3rd Qu.:1.0000 never : 62
-## Max. :2.0000 other : 40
-## (Other) : 81</code></pre>
-<pre class="r"><code># 762 h/hs have dishwashers. 167 people use it when it is full (unknown
-# frequency), 62 never use it, and 40 have stated 'other', while 32 use it
-# after every meal (3 times per day?). So only 412 h/hs use it once a day or
-# every couple of days. So no really useful frequencies of use result from
-# the survey. I have used EST's frequencies by household
-# size.(http://www.energysavingtrust.org.uk/sites/default/files/reports/AtHomewithWater(7).pdf
-# Figure 18)
-
-kable(caption = "Summary of EST data for dishwashers frequency of use", ESTdata_dish[1:5,
- ])</code></pre>
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+## dishwashers dish_freq
+## Min. :0.0000 Length:1800
+## 1st Qu.:0.0000 Class :character
+## Median :0.0000 Mode :character
+## Mean :0.4233
+## 3rd Qu.:1.0000
+## Max. :2.0000</code></pre>
+<pre class="r"><code># 762 h/hs have dishwashers. 167 people use it when it is full (unknown frequency), 62 never use it, and 40 have stated 'other', while 32 use it after every meal (3 times per day?). So only 412 h/hs use it once a day or every couple of days. So no really useful frequencies of use result from the survey. I have used EST's frequencies by household size.(http://www.energysavingtrust.org.uk/sites/default/files/reports/AtHomewithWater(7).pdf Figure 18)
+
+kable(caption = "Summary of EST data for dishwashers frequency of use",
+ ESTdata_dish [1:5,]
+)</code></pre>
<table>
<caption>Summary of EST data for dishwashers frequency of use</caption>
<thead>
@@ -1223,45 +1261,52 @@ kable(caption = "Summary of EST data for dishwashers frequency of use"
</tr>
</tbody>
</table>
-<pre class="r"><code>dishdemand_EST <- merge(x = DishDemand, y = ESTdata_dish, by = "hhsize", all.x = TRUE) # a column was added to the dataframe for dishwasher use frequency by household size, according to the EST data (ESTdata_dish).
+<pre class="r"><code>dishdemand_EST<-merge(x = DishDemand, y = ESTdata_dish, by = "hhsize", all.x = TRUE) # a column was added to the dataframe for dishwasher use frequency by household size, according to the EST data (ESTdata_dish).
-monthlyDishwasherUse <- mutate(dishdemand_EST, monthlyDishwasherUse = weeklyDish_freq *
- 4 * 14) # Monthly litres per household consumed by dishwashers (14litres/cycle)
-monthlyDishwasherUse$monthlyDishwasherUse <- ifelse(monthlyDishwasherUse$dishwashers ==
- 0, 0, monthlyDishwasherUse$monthlyDishwasherUse) # calculated only for households with dishwashers
+monthlyDishwasherUse<-mutate(dishdemand_EST,monthlyDishwasherUse= weeklyDish_freq*4*14) # Monthly litres per household consumed by dishwashers (14litres/cycle)
+monthlyDishwasherUse$monthlyDishwasherUse <- ifelse(monthlyDishwasherUse$dishwashers==0, 0,monthlyDishwasherUse$monthlyDishwasherUse) # calculated only for households with dishwashers
monthlyDishwasherUse$dailyDishwasherUse <- monthlyDishwasherUse$monthlyDishwasherUse/30
-summary(monthlyDishwasherUse) #'At home with water2' reports 10 l/hh/day for their sample for taps. Our mean is 2.4 l/hh/d. Reasonable but much lower than theirs. This is probably because zero values are included in the mean calculation).</code></pre>
-<pre><code>## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
-## dishwashers dish_freq weeklyDish_freq
-## Min. :0.0000 :1039 Min. :0.900
-## 1st Qu.:0.0000 once a day : 216 1st Qu.:2.300
-## Median :0.0000 every couple of days : 195 Median :2.300
-## Mean :0.4233 when the dishwasher/sink is full: 167 Mean :2.737
-## 3rd Qu.:1.0000 never : 62 3rd Qu.:4.300
-## Max. :2.0000 other : 40 Max. :4.800
-## (Other) : 81
-## monthlyDishwasherUse dailyDishwasherUse
-## Min. : 0.00 Min. :0.000
-## 1st Qu.: 0.00 1st Qu.:0.000
-## Median : 0.00 Median :0.000
-## Mean : 71.18 Mean :2.373
-## 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :268.80 Max. :8.960
-## </code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for dishwashers", monthlyDishwasherUse[1:5,
- ])</code></pre>
+summary(monthlyDishwasherUse)#'At home with water2' reports 10 l/hh/day for their sample for taps. Our mean is 2.4 l/hh/d. Reasonable but much lower than theirs. This is probably because zero values are included in the mean calculation).</code></pre>
+<pre><code>## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+## dishwashers dish_freq weeklyDish_freq monthlyDishwasherUse
+## Min. :0.0000 Length:1800 Min. :0.900 Min. : 0.00
+## 1st Qu.:0.0000 Class :character 1st Qu.:2.300 1st Qu.: 0.00
+## Median :0.0000 Mode :character Median :2.300 Median : 0.00
+## Mean :0.4233 Mean :2.737 Mean : 71.18
+## 3rd Qu.:1.0000 3rd Qu.:4.300 3rd Qu.:128.80
+## Max. :2.0000 Max. :4.800 Max. :268.80
+## dailyDishwasherUse
+## Min. :0.000
+## 1st Qu.:0.000
+## Median :0.000
+## Mean :2.373
+## 3rd Qu.:4.293
+## Max. :8.960</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for dishwashers",
+ monthlyDishwasherUse [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for dishwashers</caption>
+<colgroup>
+<col width="6%" />
+<col width="4%" />
+<col width="9%" />
+<col width="5%" />
+<col width="11%" />
+<col width="10%" />
+<col width="14%" />
+<col width="19%" />
+<col width="17%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">hhsize</th>
@@ -1334,39 +1379,31 @@ summary(monthlyDishwasherUse) #'At home with water2' reports 10 l/hh/da
</tbody>
</table>
<p>Plot of dishwashers’ demand per household size</p>
-<pre class="r"><code>ggplot(data = monthlyDishwasherUse) + aes(y = monthlyDishwasherUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total dishwashing use (l/house/month)")</code></pre>
+<pre class="r"><code>ggplot(data=monthlyDishwasherUse)+ aes(y = monthlyDishwasherUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total dishwashing use (l/house/month)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/dishwasher%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes" | monthlyDishwasherUse$meter ==
- "no", ], aes(factor(hhsize), monthlyDishwasherUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "dishwasher demand (l/household/month)") + xlab("household size") +
- ylab("dishwasher demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes"|monthlyDishwasherUse$meter == "no",], aes(factor(hhsize), monthlyDishwasherUse)) + geom_boxplot(aes(fill = meter))+labs(title = "dishwasher demand (l/household/month)")+ xlab('household size')+ylab('dishwasher demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/dishwasher%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes" | monthlyDishwasherUse$meter ==
- "no", ], aes(factor(hhsize), dailyDishwasherUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "dishwasher demand (l/household/day)") + xlab("household size") +
- ylab("dishwasher demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes"|monthlyDishwasherUse$meter == "no",], aes(factor(hhsize), dailyDishwasherUse)) + geom_boxplot(aes(fill = meter))+labs(title = "dishwasher demand (l/household/day)")+ xlab('household size')+ylab('dishwasher demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/dishwasher%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="kitchen-sink-use" class="section level2">
<h2><span class="header-section-number">4.4</span> Kitchen sink use</h2>
-<pre class="r"><code># water for cooking and drinking accounts for 2gal per capita/per day=7.57
-# litres per capita per
-# day.http://www.freedrinkingwater.com/water_quality/common-daily-water-usage.htm
-
-kitchen_sink <- select(Surveydata, iobs, bmg_id, q2, q4)
-kitchen_sink <- rename(kitchen_sink, obs = iobs, id = bmg_id, hhsize = q2, meter = q4)
-kitchen_sink_hh <- mutate(kitchen_sink, monthlyKitchenSinkUse = hhsize * 7.57 *
- 30)
-kitchen_sink_hh <- mutate(kitchen_sink_hh, dailyKitchenSinkUse = monthlyKitchenSinkUse/30)
+<pre class="r"><code>#water for cooking and drinking accounts for 2gal per capita/per day=7.57 litres per capita per day.http://www.freedrinkingwater.com/water_quality/common-daily-water-usage.htm
+
+kitchen_sink<-select(Surveydata, iobs,bmg_id, q2, q4)
+kitchen_sink<-rename(kitchen_sink, obs =iobs, id=bmg_id, hhsize=q2, meter=q4)
+kitchen_sink_hh<-mutate(kitchen_sink,monthlyKitchenSinkUse = hhsize*7.57*30)
+kitchen_sink_hh<-mutate(kitchen_sink_hh,dailyKitchenSinkUse = monthlyKitchenSinkUse/30)
summary(kitchen_sink_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
## monthlyKitchenSinkUse dailyKitchenSinkUse
## Min. : 227.1 Min. : 7.57
## 1st Qu.: 454.2 1st Qu.:15.14
@@ -1374,8 +1411,9 @@ summary(kitchen_sink_hh)</code></pre>
## Mean : 603.0 Mean :20.10
## 3rd Qu.: 908.4 3rd Qu.:30.28
## Max. :2271.0 Max. :75.70</code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for kitchen sink uses", kitchen_sink_hh[1:5,
- ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for kitchen sink uses",
+ kitchen_sink_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for kitchen sink uses</caption>
<thead>
@@ -1429,105 +1467,72 @@ summary(kitchen_sink_hh)</code></pre>
<td align="right">908.4</td>
<td align="right">30.28</td>
</tr>
-<tr class="even">
-<td align="right">### Pl</td>
-<td align="right">ot of kitche</td>
-<td align="right">n sink de</td>
-<td align="left">mand per hous</td>
-<td align="right">ehold size</td>
-<td align="right"></td>
-</tr>
</tbody>
</table>
-<pre class="r"><code>ggplot(data = kitchen_sink_hh) + aes(y = monthlyKitchenSinkUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total kitchen sink use (l/house/month)")</code></pre>
+<div id="plot-of-kitchen-sink-demand-per-household-size" class="section level3">
+<h3><span class="header-section-number">4.4.1</span> Plot of kitchen sink demand per household size</h3>
+<pre class="r"><code>ggplot(data=kitchen_sink_hh)+ aes(y = monthlyKitchenSinkUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total kitchen sink use (l/house/month)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/kitchensink%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes" | kitchen_sink_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyKitchenSinkUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "kitchen sink demand (l/household/month)") + xlab("household size") +
- ylab("kitchen sink demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes"|kitchen_sink_hh$meter == "no",], aes(factor(hhsize), monthlyKitchenSinkUse)) + geom_boxplot(aes(fill = meter))+labs(title = "kitchen sink demand (l/household/month)")+ xlab('household size')+ylab('kitchen sink demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/kitchensink%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes" | kitchen_sink_hh$meter ==
- "no", ], aes(factor(hhsize), dailyKitchenSinkUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "kitchen sink demand (l/household/day)") + xlab("household size") +
- ylab("kitchen sink demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes"|kitchen_sink_hh$meter == "no",], aes(factor(hhsize), dailyKitchenSinkUse)) + geom_boxplot(aes(fill = meter))+labs(title = "kitchen sink demand (l/household/day)")+ xlab('household size')+ylab('kitchen sink demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/kitchensink%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
+</div>
<div id="showering-water-demand" class="section level2">
<h2><span class="header-section-number">4.5</span> Showering water demand</h2>
-<pre class="r"><code>showerdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q29_2, q7a_3, q7a_4)
-showerdemand1 <- rename(showerdemand, obs = iobs, id = bmg_id, hhsize = q2,
- meter = q4, showers = q7a_3, powershowers = q7a_4, shower_freq = q29_2)
-showerdemand1[, 5] <- ifelse(showerdemand1[, 5] == "once a week", 1, ifelse(showerdemand1[,
- 5] == "twice a week", 2, ifelse(showerdemand1[, 5] == "three times a week",
- 3, ifelse(showerdemand1[, 5] == "four times a week", 4, ifelse(showerdemand1[,
- 5] == "five times a week", 5, ifelse(showerdemand1[, 5] == "six times a week",
- 6, ifelse(showerdemand1[, 5] == "seven times a week", 7, ifelse(showerdemand1[,
- 5] == "more than seven times a week", 9, ifelse(showerdemand1[,
- 5] == "none", 0, NA)))))))))
-
-# someone can take a shower in the bath as well, so the households that have
-# reported that they do not have showers in the house, are also included
-# (many of them have reported showering frequencies).
-summary(showerdemand1[, 5]) #53 NA's</code></pre>
+<pre class="r"><code>showerdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q29_2, q7a_3,q7a_4 )
+showerdemand1<-rename(showerdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, showers=q7a_3, powershowers=q7a_4, shower_freq=q29_2)
+showerdemand1[,5] <- ifelse(showerdemand1[,5] == "once a week", 1 ,ifelse(showerdemand1[,5] == "twice a week", 2, ifelse(showerdemand1[,5] == "three times a week", 3 ,ifelse(showerdemand1[,5] == "four times a week", 4, ifelse(showerdemand1[,5] == "five times a week", 5,ifelse(showerdemand1[,5] == "six times a week", 6,ifelse(showerdemand1[,5] == "seven times a week", 7, ifelse(showerdemand1[,5] == "more than seven times a week", 9,ifelse(showerdemand1[,5] == "none", 0, NA)))))))))
+
+#someone can take a shower in the bath as well, so the households that have reported that they do not have showers in the house, are also included (many of them have reported showering frequencies).
+summary(showerdemand1[,5]) #53 NA's</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 3.000 7.000 4.969 7.000 9.000 53</code></pre>
-<pre class="r"><code># total number of showers in the house
-showerdemand1 <- mutate(showerdemand1, numberofShowers_hh = showers + powershowers)
-# coeff for normal showers
-showerdemand1 <- mutate(showerdemand1, normalShowerCoeff = showers/(showers +
- powershowers))
-# coeff for power showers
-showerdemand1 <- mutate(showerdemand1, powerShowerCoeff = powershowers/(showers +
- powershowers))
-
-showerdemand1$normalShowerCoeff <- ifelse(is.na(showerdemand1$normalShowerCoeff),
- 0, showerdemand1$normalShowerCoeff)
-showerdemand1$powerShowerCoeff <- ifelse(is.na(showerdemand1$powerShowerCoeff),
- 0, showerdemand1$powerShowerCoeff)
-
-single_occup_sh <- filter(showerdemand1, hhsize == 1)
-mean(single_occup_sh$shower_freq, na.rm = TRUE) # mean frequency of showering is 4.25 times/week for one-person homes. In the EST sample, it is 5.2 (judging by the graph-Figure 8). </code></pre>
+<pre class="r"><code>#total number of showers in the house
+showerdemand1<-mutate(showerdemand1,numberofShowers_hh=showers+powershowers)
+#coeff for normal showers
+showerdemand1<-mutate(showerdemand1,normalShowerCoeff=showers/(showers+powershowers))
+#coeff for power showers
+showerdemand1<-mutate(showerdemand1,powerShowerCoeff=powershowers/(showers+powershowers))
+
+showerdemand1$normalShowerCoeff <- ifelse (is.na (showerdemand1$normalShowerCoeff) , 0 ,showerdemand1$normalShowerCoeff )
+showerdemand1$powerShowerCoeff <- ifelse (is.na (showerdemand1$powerShowerCoeff) , 0 ,showerdemand1$powerShowerCoeff )
+
+single_occup_sh<-filter(showerdemand1, hhsize == 1)
+mean (single_occup_sh$shower_freq,na.rm=TRUE) # mean frequency of showering is 4.25 times/week for one-person homes. In the EST sample, it is 5.2 (judging by the graph-Figure 8). </code></pre>
<pre><code>## [1] 4.252688</code></pre>
-<pre class="r"><code>showerdemand_EST <- merge(x = showerdemand1, y = ESTdata_showerBath, by = "hhsize",
- all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (showers_freq_EST, baths_freq_EST).
+<pre class="r"><code>showerdemand_EST<-merge(x = showerdemand1, y = ESTdata_showerBath, by = "hhsize", all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (showers_freq_EST, baths_freq_EST).
-# I want to take both the reported showering frequencies and the EST
-# frequencies into account. First I calculate showers per person for the EST
-# DATA
-showerdemand_EST <- mutate(showerdemand_EST, EST_freq_perperson = showers_freq_EST/hhsize)
+#I want to take both the reported showering frequencies and the EST frequencies into account. First I calculate showers per person for the EST DATA
+showerdemand_EST<-mutate(showerdemand_EST,EST_freq_perperson=showers_freq_EST/hhsize)
-# final frequencies are calculated as a mean value from EST data and the
-# reported freqs
+#final frequencies are calculated as a mean value from EST data and the reported freqs
-showerdemand_EST <- mutate(showerdemand_EST, final_freq_perperson = (EST_freq_perperson +
- shower_freq)/2)
+showerdemand_EST<-mutate(showerdemand_EST,final_freq_perperson=(EST_freq_perperson+shower_freq)/2)
# frequency of showering by hh size:
-showerdemand_EST <- mutate(showerdemand_EST, final_freq_hh = final_freq_perperson *
- hhsize)
+showerdemand_EST<-mutate(showerdemand_EST,final_freq_hh=final_freq_perperson*hhsize)
-# the average 7,5-minute normal shower uses 60 litres of water while a power
-# shower uses 97,5 litres in 7,5 minutes. (EST-AT HOME WITH WATER)
-showerdemand_hh <- mutate(showerdemand_EST, monthlyShowerUse = (60 * normalShowerCoeff +
- 97.5 * powerShowerCoeff) * 4 * final_freq_hh)
+#the average 7,5-minute normal shower uses 60 litres of water while a power shower uses 97,5 litres in 7,5 minutes. (EST-AT HOME WITH WATER)
+showerdemand_hh<-mutate(showerdemand_EST,monthlyShowerUse=(60*normalShowerCoeff+97.5*powerShowerCoeff)*4*final_freq_hh)
-# monthlyShowerUse is the frequency of showering for each household size,
-# multiplied by 4 weeks in a month and by the mean consumption by shower
-# type.
+#monthlyShowerUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by shower type.
-showerdemand_hh <- mutate(showerdemand_hh, dailyShowerUse = monthlyShowerUse/30) #'At home with water2' reports 86 l/hh/day for their sample for showers. Our mean is 107 l/hh/d. Our results make sense.
+showerdemand_hh<-mutate(showerdemand_hh,dailyShowerUse=monthlyShowerUse/30)#'At home with water2' reports 86 l/hh/day for their sample for showers. Our mean is 107 l/hh/d. Our results make sense.
-showerdemand_hh <- showerdemand_hh[, -(5:15), drop = FALSE]
+showerdemand_hh<-showerdemand_hh[,-(5:15),drop=FALSE]
summary(showerdemand_hh)</code></pre>
-<pre><code>## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
+<pre><code>## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+##
## monthlyShowerUse dailyShowerUse
## Min. : 0 Min. : 0.0
## 1st Qu.: 1464 1st Qu.: 48.8
@@ -1536,7 +1541,9 @@ summary(showerdemand_hh)</code></pre>
## 3rd Qu.: 4638 3rd Qu.:154.6
## Max. :15415 Max. :513.8
## NA's :53 NA's :53</code></pre>
-<pre class="r"><code>kable(caption = "Summary of shower demand", showerdemand_hh[1:5, ])</code></pre>
+<pre class="r"><code>kable(caption = "Summary of shower demand",
+ showerdemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of shower demand</caption>
<thead>
@@ -1593,61 +1600,43 @@ summary(showerdemand_hh)</code></pre>
</tbody>
</table>
<p>Plot of shower demand per household size</p>
-<pre class="r"><code>ggplot(data = showerdemand_hh) + aes(y = dailyShowerUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total shower use (l/house/day)")</code></pre>
+<pre class="r"><code>ggplot(data=showerdemand_hh)+ aes(y = dailyShowerUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total shower use (l/house/day)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/shower%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(showerdemand_hh[showerdemand_hh$meter == "yes" | showerdemand_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyShowerUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "shower demand (l/household/month)") + xlab("household size") +
- ylab("shower demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(showerdemand_hh[showerdemand_hh$meter == "yes"|showerdemand_hh$meter == "no",], aes(factor(hhsize), monthlyShowerUse)) + geom_boxplot(aes(fill = meter))+labs(title = "shower demand (l/household/month)")+ xlab('household size')+ylab('shower demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/shower%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(showerdemand_hh[showerdemand_hh$meter == "yes" | showerdemand_hh$meter ==
- "no", ], aes(factor(hhsize), dailyShowerUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "shower demand (l/household/day)") + xlab("household size") +
- ylab("shower demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(showerdemand_hh[showerdemand_hh$meter == "yes"|showerdemand_hh$meter == "no",], aes(factor(hhsize), dailyShowerUse)) + geom_boxplot(aes(fill = meter))+labs(title = "shower demand (l/household/day)")+ xlab('household size')+ylab('shower demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/shower%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="wc-water-demand" class="section level2">
<h2><span class="header-section-number">4.6</span> WC water demand</h2>
-<pre class="r"><code>## Surveydata <- data.table(read.csv(paste0(fpath,'/SPRGdata.csv')))
-Toiletdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_6, q7a_7, q48)
-toiletdemand1 <- rename(Toiletdemand, obs = iobs, id = bmg_id, hhsize = q2,
- meter = q4, singleflush_wc = q7a_6, dualflush_wc = q7a_7, effective_flush = q48)
-toiletdemand2 <- mutate(toiletdemand1, flushvolume = (singleflush_wc * 7.5 +
- dualflush_wc * 5)/(singleflush_wc + dualflush_wc)) # litres used per flush
+<pre class="r"><code>## Surveydata <- data.table(read.csv(paste0(fpath,"/SPRGdata.csv")))
+Toiletdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q7a_6,q7a_7, q48)
+toiletdemand1<-rename(Toiletdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, singleflush_wc=q7a_6, dualflush_wc=q7a_7,effective_flush=q48)
+toiletdemand2<-mutate (toiletdemand1, flushvolume=(singleflush_wc*7.5 + dualflush_wc*5)/(singleflush_wc+dualflush_wc)) # litres used per flush
# 'At home with water (EST)'suggests a mean 5 flusheS per day per occupant
-# Ignoring economies of scale, toilet consumption in the household should
-# be: each occupant's demand * household size-the resulting consumption will
-# most probably be an overestimation!-This calculation can change.
-toiletdemand_hh <- mutate(toiletdemand2, monthlyWCUse = flushvolume * hhsize *
- 30 * 5)
-
-toiletdemand_hh <- mutate(toiletdemand_hh, dailyWCUse = monthlyWCUse/30) #'At home with water2' reports 74 l/hh/day for their sample for lavatories. Our mean is 91.3 l/hh/d. Our results make sense.
-summary(toiletdemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
-## singleflush_wc dualflush_wc
-## Min. : 0.000 Min. :0.0000
-## 1st Qu.: 1.000 1st Qu.:0.0000
-## Median : 1.000 Median :0.0000
-## Mean : 1.169 Mean :0.4233
-## 3rd Qu.: 2.000 3rd Qu.:1.0000
-## Max. :97.000 Max. :5.0000
-##
-## effective_flush flushvolume
-## always empties the bowl with one flush :1491 Min. :5.000
-## usually empties the bowl with one flush : 210 1st Qu.:6.250
-## refused : 45 Median :7.500
-## empties about half the time with one flush: 32 Mean :6.918
-## usually needs more than one flush : 16 3rd Qu.:7.500
-## don't know : 3 Max. :7.500
-## (Other) : 3 NA's :59
+# Ignoring economies of scale, toilet consumption in the household should be: each occupant's demand * household size-the resulting consumption will most probably be an overestimation!-This calculation can change.
+toiletdemand_hh<-mutate (toiletdemand2, monthlyWCUse=flushvolume*hhsize*30*5)
+
+toiletdemand_hh<-mutate (toiletdemand_hh, dailyWCUse=monthlyWCUse/30) #'At home with water2' reports 74 l/hh/day for their sample for lavatories. Our mean is 91.3 l/hh/d. Our results make sense.
+summary (toiletdemand_hh)</code></pre>
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
+## singleflush_wc dualflush_wc effective_flush flushvolume
+## Min. : 0.000 Min. :0.0000 Length:1800 Min. :5.000
+## 1st Qu.: 1.000 1st Qu.:0.0000 Class :character 1st Qu.:6.250
+## Median : 1.000 Median :0.0000 Mode :character Median :7.500
+## Mean : 1.169 Mean :0.4233 Mean :6.918
+## 3rd Qu.: 2.000 3rd Qu.:1.0000 3rd Qu.:7.500
+## Max. :97.000 Max. :5.0000 Max. :7.500
+## NA's :59
## monthlyWCUse dailyWCUse
## Min. : 750 Min. : 25.00
## 1st Qu.:1500 1st Qu.: 50.00
@@ -1656,12 +1645,14 @@ summary(toiletdemand_hh)</code></pre>
## 3rd Qu.:3375 3rd Qu.:112.50
## Max. :7875 Max. :262.50
## NA's :59 NA's :59</code></pre>
-<pre class="r"><code>sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm = TRUE)</code></pre>
+<pre class="r"><code>sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm=TRUE) </code></pre>
<pre><code>## 1 2 3 4 5 6 7 10
## 1063.670 2067.707 3075.615 4104.235 5189.438 6286.765 7109.375 7500.000</code></pre>
-<pre class="r"><code>toiletdemand_hh <- toiletdemand_hh[, -(5:8), drop = FALSE]
+<pre class="r"><code>toiletdemand_hh<-toiletdemand_hh[,-(5:8),drop=FALSE]
-kable(caption = "Summary of toilet demand table", toiletdemand_hh[1:5, ])</code></pre>
+kable(caption = "Summary of toilet demand table",
+ toiletdemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of toilet demand table</caption>
<thead>
@@ -1718,58 +1709,43 @@ kable(caption = "Summary of toilet demand table", toiletdemand_hh[1:5,
</tbody>
</table>
<p>Plot of toilet demand per household size for metered and unmetered hhs</p>
-<pre class="r"><code>ggplot(data = toiletdemand_hh) + aes(y = dailyWCUse, x = factor(hhsize)) + geom_boxplot() +
- labs(title = "WC use (l/household/day)") + xlab("household size") + ylab("WC demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(data=toiletdemand_hh)+ aes(y = dailyWCUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "WC use (l/household/day)")+ xlab('household size')+ylab('WC demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/toilet%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes" | toiletdemand_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyWCUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "WC use (l/household/month)") + xlab("household size") + ylab("WC demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes"|toiletdemand_hh$meter == "no",], aes(factor(hhsize), monthlyWCUse)) + geom_boxplot(aes(fill = meter))+labs(title = "WC use (l/household/month)")+ xlab('household size')+ylab('WC demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/toilet%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes" | toiletdemand_hh$meter ==
- "no", ], aes(factor(hhsize), dailyWCUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "WC use (l/household/day)") + xlab("household size") + ylab("WC demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes"|toiletdemand_hh$meter == "no",], aes(factor(hhsize), dailyWCUse)) + geom_boxplot(aes(fill = meter))+labs(title = "WC use (l/household/day)")+ xlab('household size')+ylab('WC demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/toilet%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="washing-machine-water-demand" class="section level2">
<h2><span class="header-section-number">4.7</span> Washing machine water demand</h2>
-<pre class="r"><code>washingmachinedemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_11, q20,
- q21)
-washingmachinedemand1 <- rename(washingmachinedemand, obs = iobs, id = bmg_id,
- hhsize = q2, meter = q4, weeklyloads = q20, combinedwash = q21, washingmachine = q7a_11)
+<pre class="r"><code>washingmachinedemand<-select(Surveydata, iobs,bmg_id, q2, q4,q7a_11, q20,q21)
+washingmachinedemand1<-rename(washingmachinedemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, weeklyloads=q20, combinedwash=q21, washingmachine=q7a_11)
# I only kept h/hs that have washing machines at home (1704 homes)
-washingmachinedemand1$washingmachine <- ifelse(washingmachinedemand1$washingmachine ==
- "1", 1, ifelse(washingmachinedemand1$washingmachine == "2", 2, 0))
-
-# 0 for the houses without a machine. the rest assumed to combine washes
-washingmachinedemand1$combinedwash <- ifelse(washingmachinedemand1$combinedwash ==
- "the washing is combined and done for the whole household", 1, ifelse(is.null(washingmachinedemand1$combinedwash) |
- washingmachinedemand1$washingmachine == 1, 1, ifelse(is.null(washingmachinedemand1$combinedwash) |
- washingmachinedemand1$washingmachine == 2, 1, NA)))
-
-washingmachinedemand1[, 6] <- ifelse(washingmachinedemand1[, 6] == "less than one load a week",
- 0.5, ifelse(washingmachinedemand1[, 6] == "about 1 load", 1, ifelse(washingmachinedemand1[,
- 6] == "2-3 loads", 2.5, ifelse(washingmachinedemand1[, 6] == "4-5 loads",
- 4.5, ifelse(washingmachinedemand1[, 6] == "6-10 loads", 8, ifelse(washingmachinedemand1[,
- 6] == "more than 10 loads", 12, ifelse(washingmachinedemand1[, 6] ==
- "don't know", NA, 0)))))))
-
-summary(washingmachinedemand1[, 6]) #145 NA's</code></pre>
+washingmachinedemand1$washingmachine<-ifelse(washingmachinedemand1$washingmachine == "1",1,ifelse(washingmachinedemand1$washingmachine == "2", 2, 0))
+
+ # 0 for the houses without a machine. the rest assumed to combine washes
+washingmachinedemand1$combinedwash<-ifelse(washingmachinedemand1$combinedwash == "the washing is combined and done for the whole household",1, ifelse(is.null (washingmachinedemand1$combinedwash) | washingmachinedemand1$washingmachine==1,1,ifelse(is.null (washingmachinedemand1$combinedwash) | washingmachinedemand1$washingmachine==2,1, NA)))
+
+washingmachinedemand1[,6] <- ifelse(washingmachinedemand1[,6] == "less than one load a week", 0.5,ifelse(washingmachinedemand1[,6] == "about 1 load", 1, ifelse(washingmachinedemand1[,6] == "2-3 loads", 2.5,ifelse(washingmachinedemand1[,6] == "4-5 loads", 4.5, ifelse(washingmachinedemand1[,6] == "6-10 loads", 8,ifelse(washingmachinedemand1[,6] == "more than 10 loads", 12,ifelse(washingmachinedemand1[,6] == "don't know" , NA, 0)))))))
+
+summary (washingmachinedemand1[,6]) #145 NA's</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.000 2.500 2.500 3.542 4.500 12.000 47</code></pre>
-<pre class="r"><code>washingmachine_hh <- mutate(washingmachinedemand1, monthlyWashingMachineUse = weeklyloads *
- 4 * 50) # according to 'At home with water (EST)', an average cycle consumes 50 litres of water.
-washingmachine_hh <- mutate(washingmachine_hh, dailyWashingMachineUse = monthlyWashingMachineUse/30) #'At home with water2' reports 33 l/hh/day for their sample for washing machines. Our mean is 25. Our results make sense.
-
-summary(washingmachine_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+<pre class="r"><code>washingmachine_hh<-mutate(washingmachinedemand1,monthlyWashingMachineUse= weeklyloads*4*50) # according to 'At home with water (EST)', an average cycle consumes 50 litres of water.
+washingmachine_hh<-mutate(washingmachine_hh,dailyWashingMachineUse=monthlyWashingMachineUse/30) #'At home with water2' reports 33 l/hh/day for their sample for washing machines. Our mean is 25. Our results make sense.
+
+summary (washingmachine_hh)</code></pre>
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## washingmachine weeklyloads combinedwash monthlyWashingMachineUse
## Min. :0.0000 Min. : 0.000 Min. :1 Min. : 0.0
## 1st Qu.:1.0000 1st Qu.: 2.500 1st Qu.:1 1st Qu.: 500.0
@@ -1786,10 +1762,11 @@ summary(washingmachine_hh)</code></pre>
## 3rd Qu.:30.00
## Max. :80.00
## NA's :47</code></pre>
-<pre class="r"><code>washingmachine_hh <- washingmachine_hh[, -(5:7), drop = FALSE]
+<pre class="r"><code>washingmachine_hh<-washingmachine_hh[,-(5:7),drop=FALSE]
-kable(caption = "Summary of washing machine demand data table", washingmachine_hh[1:5,
- ])</code></pre>
+kable(caption = "Summary of washing machine demand data table",
+ washingmachine_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of washing machine demand data table</caption>
<thead>
@@ -1846,46 +1823,33 @@ kable(caption = "Summary of washing machine demand data table", washin
</tbody>
</table>
<p>Plot of washingmachine demand per household size for metered and unmetered hhs</p>
-<pre class="r"><code>ggplot(data = washingmachine_hh) + aes(y = dailyWashingMachineUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total washingmachine use (l/house/day)")</code></pre>
+<pre class="r"><code>ggplot(data=washingmachine_hh)+ aes(y = dailyWashingMachineUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total washingmachine use (l/house/day)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/washingmachine%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(washingmachine_hh[washingmachine_hh$meter == "yes" | washingmachine_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyWashingMachineUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "washine machine use (l/household/month)") + xlab("household size") +
- ylab("washing machine demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(washingmachine_hh[washingmachine_hh$meter == "yes"|washingmachine_hh$meter == "no",], aes(factor(hhsize), monthlyWashingMachineUse)) + geom_boxplot(aes(fill = meter))+labs(title = "washine machine use (l/household/month)")+ xlab('household size')+ylab('washing machine demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/washingmachine%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(washingmachine_hh[washingmachine_hh$meter == "yes" | washingmachine_hh$meter ==
- "no", ], aes(factor(hhsize), dailyWashingMachineUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "washine machine use (l/household/day)") + xlab("household size") +
- ylab("washing machine demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(washingmachine_hh[washingmachine_hh$meter == "yes"|washingmachine_hh$meter == "no",], aes(factor(hhsize),dailyWashingMachineUse)) + geom_boxplot(aes(fill = meter))+labs(title = "washine machine use (l/household/day)")+ xlab('household size')+ylab('washing machine demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/washingmachine%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="total-internal-consumption" class="section level2">
<h2><span class="header-section-number">4.8</span> Total internal consumption</h2>
-<pre class="r"><code># total demand
-totalIntDemand_hh <- merge(x = bathdemand_hh, y = showerdemand_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = kitchen_sink_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = monthlyDishwasherUse,
- by = "id", all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = toiletdemand_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = washingmachine_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = bathsink_hh, by = "id",
- all = TRUE)
-
-
-totalIntDemand_hh <- subset(totalIntDemand_hh, select = c("id", "obs.y", "hhsize.x.x",
- "meter.x.x", "monthlyBathUse", "monthlyShowerUse", "monthlyDishwasherUse",
- "monthlyKitchenSinkUse", "monthlyWCUse", "monthlyWashingMachineUse", "monthlyBathroomSinkUse"))
+<pre class="r"><code>#total demand
+totalIntDemand_hh<-merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = kitchen_sink_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = monthlyDishwasherUse, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = toiletdemand_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = washingmachine_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = bathsink_hh, by = "id", all = TRUE)
+
+
+totalIntDemand_hh <- subset(totalIntDemand_hh, select=c("id","obs.y", "hhsize.x.x","meter.x.x","monthlyBathUse", "monthlyShowerUse","monthlyDishwasherUse", "monthlyKitchenSinkUse", "monthlyWCUse","monthlyWashingMachineUse", "monthlyBathroomSinkUse"))
str(totalIntDemand_hh)</code></pre>
<pre><code>## 'data.frame': 1800 obs. of 11 variables:
## $ id : int 836900048 836900071 836900073 836900106 836900117 836900123 836900127 836900128 836900131 836900132 ...
## $ obs.y : int 2 3 4 5 6 179 162 161 181 163 ...
## $ hhsize.x.x : int 2 2 4 1 4 5 5 4 2 6 ...
-## $ meter.x.x : Factor w/ 3 levels "don't know","no",..: 3 1 3 3 3 1 3 3 1 1 ...
+## $ meter.x.x : chr "yes" "don't know" "yes" "yes" ...
## $ monthlyBathUse : num 0 792 1707 0 1707 ...
## $ monthlyShowerUse : num NA NA 5118 2379 NA ...
## $ monthlyDishwasherUse : num 0 129 241 0 241 ...
@@ -1893,43 +1857,42 @@ str(totalIntDemand_hh)</code></pre>
## $ monthlyWCUse : num 2250 1500 3500 750 4500 ...
## $ monthlyWashingMachineUse: num 500 500 NA 500 1600 500 NA 200 0 500 ...
## $ monthlyBathroomSinkUse : num 794 794 1589 397 1589 ...</code></pre>
-<pre class="r"><code>totalIntDemand_hh <- mutate(totalIntDemand_hh, totalMonthlyInHouseDemand = (monthlyBathUse +
- monthlyShowerUse + monthlyKitchenSinkUse + monthlyDishwasherUse + monthlyWCUse +
- monthlyWashingMachineUse + monthlyBathroomSinkUse))
+<pre class="r"><code>totalIntDemand_hh <- mutate(totalIntDemand_hh,totalMonthlyInHouseDemand = (monthlyBathUse + monthlyShowerUse + monthlyKitchenSinkUse + monthlyDishwasherUse +
+ monthlyWCUse + monthlyWashingMachineUse + monthlyBathroomSinkUse) )
summary(totalIntDemand_hh)</code></pre>
-<pre><code>## id obs.y hhsize.x.x meter.x.x
-## Min. :836900048 Min. : 2.0 Min. : 1.000 don't know:167
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 no :864
-## Median :836920637 Median : 905.5 Median : 2.000 yes :769
-## Mean :836919052 Mean : 906.0 Mean : 2.655
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
-## Max. :836965495 Max. :1810.0 Max. :10.000
-##
-## monthlyBathUse monthlyShowerUse monthlyDishwasherUse
-## Min. : 0.0 Min. : 0 Min. : 0.00
-## 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00
-## Median : 792.0 Median : 2808 Median : 0.00
-## Mean :1065.9 Mean : 3210 Mean : 71.18
-## 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80
-## Max. :2323.2 Max. :15415 Max. :268.80
-## NA's :53
-## monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse
-## Min. : 227.1 Min. : 750 Min. : 0.0
-## 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0
-## Median : 454.2 Median :2250 Median : 500.0
-## Mean : 603.0 Mean :2739 Mean : 708.3
-## 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0
-## Max. :2271.0 Max. :7875 Max. :2400.0
-## NA's :59 NA's :47
-## monthlyBathroomSinkUse totalMonthlyInHouseDemand
-## Min. : 312.0 Min. : 1907
-## 1st Qu.: 794.4 1st Qu.: 6043
-## Median : 1191.6 Median : 9167
-## Mean : 1748.0 Mean :10140
-## 3rd Qu.: 1986.0 3rd Qu.:13821
-## Max. :13896.0 Max. :34171
-## NA's :53 NA's :186</code></pre>
+<pre><code>## id obs.y hhsize.x.x meter.x.x
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :1810.0 Max. :10.000
+##
+## monthlyBathUse monthlyShowerUse monthlyDishwasherUse monthlyKitchenSinkUse
+## Min. : 0.0 Min. : 0 Min. : 0.00 Min. : 227.1
+## 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00 1st Qu.: 454.2
+## Median : 792.0 Median : 2808 Median : 0.00 Median : 454.2
+## Mean :1065.9 Mean : 3210 Mean : 71.18 Mean : 603.0
+## 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80 3rd Qu.: 908.4
+## Max. :2323.2 Max. :15415 Max. :268.80 Max. :2271.0
+## NA's :53
+## monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse
+## Min. : 750 Min. : 0.0 Min. : 312.0
+## 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4
+## Median :2250 Median : 500.0 Median : 1191.6
+## Mean :2739 Mean : 708.3 Mean : 1748.0
+## 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0
+## Max. :7875 Max. :2400.0 Max. :13896.0
+## NA's :59 NA's :47 NA's :53
+## totalMonthlyInHouseDemand
+## Min. : 1907
+## 1st Qu.: 6043
+## Median : 9167
+## Mean :10140
+## 3rd Qu.:13821
+## Max. :34171
+## NA's :186</code></pre>
</div>
</div>
<div id="estimate-external-consumption" class="section level1">
@@ -1943,123 +1906,102 @@ gardenNoMeter <- 0.08</code></pre>
<li>10% of total h/h use for metered homes</li>
<li>8% of total h/h use for unmetered homes respectively.</li>
</ul>
-<pre class="r"><code>monthlyGardenUse <- select(Surveydata, iobs, bmg_id, q2, q4, q10a)
-monthlyGardenUse <- rename(monthlyGardenUse, obs = iobs, id = bmg_id, hhsize = q2,
- noplantslawn = q10a, meter = q4)
-monthlyGardenUse$noplantslawn <- ifelse(monthlyGardenUse$noplantslawn == "yes",
- 0, 1) # the houses that do not have garden or lawn to water are modeled as '0'. Have not found garden use data by household size yet so I have used Thames Water's approximation. 10% of total h/h use and 8% of total h/h use for metered and unmetered homes respectively.
-monthlyGardenUse_hh <- merge(x = totalIntDemand_hh, y = monthlyGardenUse, by = "id",
- all = TRUE)
-monthlyGardenUse_hh <- subset(monthlyGardenUse_hh, select = c("id", "hhsize",
- "meter", "noplantslawn", "totalMonthlyInHouseDemand"))
+<pre class="r"><code>monthlyGardenUse<-select(Surveydata, iobs,bmg_id, q2, q4, q10a)
+monthlyGardenUse<-rename(monthlyGardenUse, obs =iobs, id=bmg_id, hhsize=q2,noplantslawn=q10a, meter=q4)
+monthlyGardenUse$noplantslawn <- ifelse(monthlyGardenUse$noplantslawn== "yes", 0, 1) # the houses that do not have garden or lawn to water are modeled as '0'. Have not found garden use data by household size yet so I have used Thames Water's approximation. 10% of total h/h use and 8% of total h/h use for metered and unmetered homes respectively.
+monthlyGardenUse_hh<-merge(x = totalIntDemand_hh, y = monthlyGardenUse, by = "id", all = TRUE)
+monthlyGardenUse_hh<-subset(monthlyGardenUse_hh, select=c("id", "hhsize","meter", "noplantslawn", "totalMonthlyInHouseDemand"))
str(monthlyGardenUse_hh)</code></pre>
<pre><code>## 'data.frame': 1800 obs. of 5 variables:
## $ id : int 836900048 836900071 836900073 836900106 836900117 836900123 836900127 836900128 836900131 836900132 ...
## $ hhsize : int 2 2 4 1 4 5 5 4 2 6 ...
-## $ meter : Factor w/ 3 levels "don't know","no",..: 3 1 3 3 3 1 3 3 1 1 ...
+## $ meter : chr "yes" "don't know" "yes" "yes" ...
## $ noplantslawn : num 1 1 1 1 1 0 1 0 0 0 ...
## $ totalMonthlyInHouseDemand: num NA NA NA 4253 NA ...</code></pre>
-<pre class="r"><code>monthlyGardenUse_hh$monthlyGardenUse <- ifelse(monthlyGardenUse_hh$meter ==
- "yes", monthlyGardenUse_hh$totalMonthlyInHouseDemand * gardenMeter * monthlyGardenUse_hh$noplantslawn,
- ifelse(monthlyGardenUse_hh$meter == "no", monthlyGardenUse_hh$totalMonthlyInHouseDemand *
- gardenNoMeter * monthlyGardenUse_hh$noplantslawn, NA)) #a column with garden use was added
-
-monthlyGardenUse_hh$dailyGardenUse <- monthlyGardenUse_hh$monthlyGardenUse/30
-summary(monthlyGardenUse_hh$dailyGardenUse) #Mean daily garden demand is 32.5 l/hh/day. Seems reasonable</code></pre>
+<pre class="r"><code>monthlyGardenUse_hh$monthlyGardenUse <- ifelse(monthlyGardenUse_hh$meter == "yes",
+ monthlyGardenUse_hh$totalMonthlyInHouseDemand*gardenMeter*monthlyGardenUse_hh$noplantslawn,
+ ifelse (monthlyGardenUse_hh$meter == "no",
+ monthlyGardenUse_hh$totalMonthlyInHouseDemand * gardenNoMeter * monthlyGardenUse_hh$noplantslawn,
+ NA )
+ ) #a column with garden use was added
+
+monthlyGardenUse_hh$dailyGardenUse<-monthlyGardenUse_hh$monthlyGardenUse/30
+summary(monthlyGardenUse_hh$dailyGardenUse) #Mean daily garden demand is 32.5 l/hh/day. Seems reasonable</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.00 0.00 18.72 19.95 31.79 85.44 331</code></pre>
-<pre class="r"><code>sapply(split(monthlyGardenUse_hh$monthlyGardenUse, monthlyGardenUse_hh$hhsize),
- mean, na.rm = TRUE)</code></pre>
-<pre><code>## 1 2 3 4 5 6 7
-## 227.7423 530.5318 726.9288 873.7553 926.8311 886.5356 1270.9766
-## 10
-## 2497.5260</code></pre>
+<pre class="r"><code>sapply(split(monthlyGardenUse_hh$monthlyGardenUse, monthlyGardenUse_hh$hhsize), mean, na.rm=TRUE) </code></pre>
+<pre><code>## 1 2 3 4 5 6 7 10
+## 227.7423 530.5318 726.9288 873.7553 926.8311 886.5356 1270.9766 2497.5260</code></pre>
<p>Plot of garden demand per household size</p>
<pre class="r"><code>monthlyGardenUse_hh$hhsize <- as.integer(monthlyGardenUse_hh$hhsize)
x.sub <- subset(monthlyGardenUse_hh, hhsize <= 6)
-monthlyGardenUse_hh$hhsize <- as.factor(monthlyGardenUse_hh$hhsize)
+monthlyGardenUse_hh$hhsize<- as.factor(monthlyGardenUse_hh$hhsize)
-ggplot(data = x.sub) + aes(y = monthlyGardenUse, x = factor(hhsize)) + geom_boxplot() +
- labs(title = "Garden water use (l/house/month)") + xlab("household size") +
- ylab("garden demand (l/hh/month)")</code></pre>
+ggplot(data=x.sub )+ aes(y = monthlyGardenUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "Garden water use (l/house/month)")+ xlab('household size')+ylab('garden demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/garden%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(x.sub[x.sub$meter == "yes" | x.sub$meter == "no", ], aes(factor(hhsize),
- monthlyGardenUse)) + geom_boxplot(aes(fill = meter)) + labs(title = " garden demand (l/household/month)") +
- xlab("household size") + ylab("garden demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(x.sub[x.sub$meter == "yes"|x.sub$meter == "no",], aes(factor(hhsize), monthlyGardenUse)) + geom_boxplot(aes(fill = meter))+labs(title = " garden demand (l/household/month)")+ xlab('household size')+ylab('garden demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/garden%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(x.sub[x.sub$meter == "yes" | x.sub$meter == "no", ], aes(factor(hhsize),
- dailyGardenUse)) + geom_boxplot(aes(fill = meter)) + labs(title = " garden demand (l/household/day)") +
- xlab("household size") + ylab("garden demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(x.sub[x.sub$meter == "yes"|x.sub$meter == "no",], aes(factor(hhsize), dailyGardenUse)) + geom_boxplot(aes(fill = meter))+labs(title = " garden demand (l/household/day)")+ xlab('household size')+ylab('garden demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/garden%20water%20demand%20plot-3.png" /><!-- --></p>
</div>
<div id="carwashing-demand" class="section level2">
<h2><span class="header-section-number">5.2</span> Carwashing demand</h2>
-<pre class="r"><code># Households with no cars are assigned a ZERO value
-CarDemand_hh <- select(Surveydata, iobs, bmg_id, q2, q4, q13a, q13b, q13c, q14a,
- q15aa, q15ab, q15ac)
-CarDemand_hh <- rename(CarDemand_hh, obs = iobs, id = bmg_id, hhsize = q2, onecar = q13a,
- twocars = q13b, threecars = q13c, carwash_freq = q14a, bucket_wash = q15aa,
- hose_wash = q15ab, pres_wash = q15ac, meter = q4)
+<pre class="r"><code>#Households with no cars are assigned a ZERO value
+CarDemand_hh<-select(Surveydata, iobs,bmg_id, q2, q4, q13a, q13b,q13c, q14a, q15aa,q15ab,q15ac)
+CarDemand_hh<-rename(CarDemand_hh, obs =iobs, id=bmg_id, hhsize=q2,onecar=q13a, twocars=q13b, threecars=q13c, carwash_freq=q14a, bucket_wash=q15aa, hose_wash=q15ab, pres_wash=q15ac, meter=q4 )
CarDemand_hh$onecar <- ifelse(CarDemand_hh$onecar == "yes", 1, 0)
CarDemand_hh$twocars <- ifelse(CarDemand_hh$twocars == "yes", 2, 0)
-CarDemand_hh$threecars <- ifelse(CarDemand_hh$threecars == "yes", 3, 0)
-CarDemand_hh$CarSum <- CarDemand_hh$onecar + CarDemand_hh$twocars + CarDemand_hh$threecars #new column with number of cars per household
+CarDemand_hh$threecars<- ifelse(CarDemand_hh$threecars== "yes", 3, 0)
+CarDemand_hh$CarSum<-CarDemand_hh$onecar+CarDemand_hh$twocars+CarDemand_hh$threecars #new column with number of cars per household
-CarDemand_hh[, 8] <- ifelse(CarDemand_hh[, 8] == "never", 0, ifelse(CarDemand_hh[,
- 8] == "at least once a week", 4, ifelse(CarDemand_hh[, 8] == "less often than every three months",
- 0.25, ifelse(CarDemand_hh[, 8] == "less than once a month, but at least every three months",
- 0.33, ifelse(CarDemand_hh[, 8] == "less than once a week, but at least once a month",
- 1, NA)))))
+CarDemand_hh[,8] <- ifelse(CarDemand_hh[,8] == "never", 0 ,ifelse(CarDemand_hh[,8] == "at least once a week", 4, ifelse(CarDemand_hh[,8] == "less often than every three months", 0.25 ,ifelse(CarDemand_hh[,8] == "less than once a month, but at least every three months", 0.33, ifelse(CarDemand_hh[,8] == "less than once a week, but at least once a month", 1, NA)))))
-CarDemand_hh[, 8] <- ifelse(CarDemand_hh$CarSum == 0, 0, CarDemand_hh[, 8]) #for those not owning a car, frequency of carwashing is zero
+CarDemand_hh[,8]<-ifelse (CarDemand_hh$CarSum==0,0,CarDemand_hh[,8]) #for those not owning a car, frequency of carwashing is zero
-summary(CarDemand_hh[, 8])</code></pre>
+summary(CarDemand_hh[,8])</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.0000 0.0000 0.2500 0.4543 0.3300 4.0000 41</code></pre>
-<pre class="r"><code># a bucket wash uses 30litres/wash while a hose wash uses 250litres/ wash
+<pre class="r"><code>#a bucket wash uses 30litres/wash while a hose wash uses 250litres/ wash
CarDemand_hh$bucket_wash <- ifelse(CarDemand_hh$bucket_wash == "yes", 30, 0)
CarDemand_hh$hose_wash <- ifelse(CarDemand_hh$hose_wash == "yes", 250, 0)
-# a pressure washer uses approximately 35gal/10 minute wash= 132litres/wash
-# (http://www.mde.state.md.us/programs/Water/WaterConservation/Pages/Programs/WaterPrograms/water_conservation/household_tips/carwashing.aspx)
+#a pressure washer uses approximately 35gal/10 minute wash= 132litres/wash (http://www.mde.state.md.us/programs/Water/WaterConservation/Pages/Programs/WaterPrograms/water_conservation/household_tips/carwashing.aspx)
CarDemand_hh$pres_wash <- ifelse(CarDemand_hh$pres_wash == "yes", 132, 0)
-# many households use multiple ways to wash their cars
-CarDemand_hh$Mean_wash <- rowMeans(CarDemand_hh[, 9:11], na.rm = TRUE)
-# most households have not indicated how they wash their cars, so their
-# consumption could not be calculated. Thus, I took the mean of reported
-# bucket wash, hose wash and pressure wash for each household size and I
-# assigned it to each household that has a car but no records for how they
-# wash it.
+#many households use multiple ways to wash their cars
+CarDemand_hh$Mean_wash <- rowMeans(CarDemand_hh[,9:11],na.rm=TRUE)
+#most households have not indicated how they wash their cars, so their consumption could not be calculated. Thus, I took the mean of reported bucket wash, hose wash and pressure wash for each household size and I assigned it to each household that has a car but no records for how they wash it.
CarDemand_hh$Mean_wash[CarDemand_hh$Mean_wash == 0] <- NA
-size1mean_wash <- filter(CarDemand_hh, hhsize == 1 & CarSum >= 1)
-mean1 <- mean(size1mean_wash$Mean_wash, na.rm = TRUE)
-size2mean_wash <- filter(CarDemand_hh, hhsize == 2 & CarSum >= 1)
-mean2 <- mean(size2mean_wash$Mean_wash, na.rm = TRUE)
-size3mean_wash <- filter(CarDemand_hh, hhsize == 3 & CarSum >= 1)
-mean3 <- mean(size3mean_wash$Mean_wash, na.rm = TRUE)
-size4mean_wash <- filter(CarDemand_hh, hhsize == 4 & CarSum >= 1)
-mean4 <- mean(size4mean_wash$Mean_wash, na.rm = TRUE)
-size5mean_wash <- filter(CarDemand_hh, hhsize == 5 & CarSum >= 1)
-mean5 <- mean(size5mean_wash$Mean_wash, na.rm = TRUE)
-size6mean_wash <- filter(CarDemand_hh, hhsize == 6 & CarSum >= 1)
-mean6 <- mean(size6mean_wash$Mean_wash, na.rm = TRUE)
-size7mean_wash <- filter(CarDemand_hh, hhsize == 7 & CarSum >= 1)
-mean7 <- mean(size7mean_wash$Mean_wash, na.rm = TRUE)
+size1mean_wash<-filter(CarDemand_hh, hhsize == 1 & CarSum>=1)
+mean1<-mean (size1mean_wash$Mean_wash,na.rm=TRUE)
+size2mean_wash<-filter(CarDemand_hh, hhsize == 2 & CarSum>=1)
+mean2<-mean (size2mean_wash$Mean_wash,na.rm=TRUE)
+size3mean_wash<-filter(CarDemand_hh, hhsize == 3 &CarSum>=1)
+mean3<-mean (size3mean_wash$Mean_wash,na.rm=TRUE)
+size4mean_wash<-filter(CarDemand_hh, hhsize == 4 &CarSum>=1)
+mean4<-mean (size4mean_wash$Mean_wash,na.rm=TRUE)
+size5mean_wash<-filter(CarDemand_hh, hhsize == 5 &CarSum>=1)
+mean5<-mean (size5mean_wash$Mean_wash,na.rm=TRUE)
+size6mean_wash<-filter(CarDemand_hh, hhsize == 6 &CarSum>=1)
+mean6<-mean (size6mean_wash$Mean_wash,na.rm=TRUE)
+size7mean_wash<-filter(CarDemand_hh, hhsize == 7 &CarSum>=1)
+mean7<-mean (size7mean_wash$Mean_wash,na.rm=TRUE)
summary(CarDemand_hh)</code></pre>
-<pre><code>## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+<pre><code>## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## onecar twocars threecars carwash_freq
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
@@ -2084,60 +2026,42 @@ summary(CarDemand_hh)</code></pre>
## 3rd Qu.: 54.00
## Max. :137.33
## NA's :1296</code></pre>
-<pre class="r"><code>CarDemand_hh$Mean_wash <- ifelse(is.na(CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum >=
- 1 & CarDemand_hh$hhsize == 1, mean1, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 2, mean2, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 3, mean3, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 4, mean4, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 5, mean5, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 6, mean6, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 7, mean7, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum < 1, 0, CarDemand_hh$Mean_wash))))))))
+<pre class="r"><code>CarDemand_hh$Mean_wash <- ifelse(is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 1, mean1, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 2, mean2, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 3, mean3, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 4, mean4,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 5, mean5,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 6, mean6,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 7, mean7,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum<1 ,0, CarDemand_hh$Mean_wash ))))))))
# Now, only households with no cars have a zero value for mean_wash (429).
-# Need to do the same for carwashing frequencies, so that litres (mean_wash)
-# can be multiplied by frequencies and number of cars to produce monthly
-# consumption (monthlyCarWashUse). most households have not indicated how
-# often they wash their cars, so their consumption cannot be calculated.
-# Thus, I took the mean of reported frequencies for each household size and
-# I assigned it to each household that has a car but no records for how
-# often they wash it.
-
-
-size1mean_freq <- filter(CarDemand_hh, hhsize == 1 & CarSum >= 1)
-freq1 <- mean(size1mean_freq$carwash_freq, na.rm = TRUE)
-size2mean_freq <- filter(CarDemand_hh, hhsize == 2 & CarSum >= 1)
-freq2 <- mean(size2mean_freq$carwash_freq, na.rm = TRUE)
-size3mean_freq <- filter(CarDemand_hh, hhsize == 3 & CarSum >= 1)
-freq3 <- mean(size3mean_freq$carwash_freq, na.rm = TRUE)
-size4mean_freq <- filter(CarDemand_hh, hhsize == 4 & CarSum >= 1)
-freq4 <- mean(size4mean_freq$carwash_freq, na.rm = TRUE)
-size5mean_freq <- filter(CarDemand_hh, hhsize == 5 & CarSum >= 1)
-freq5 <- mean(size5mean_freq$carwash_freq, na.rm = TRUE)
-size6mean_freq <- filter(CarDemand_hh, hhsize == 6 & CarSum >= 1)
-freq6 <- mean(size6mean_freq$carwash_freq, na.rm = TRUE)
-
-CarDemand_hh$carwash_freq <- ifelse(is.na(CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum >=
- 1 & CarDemand_hh$hhsize == 1, freq1, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 2, freq2, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 3, freq3, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 4, freq4, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 5, freq5, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 6, freq6, CarDemand_hh$carwash_freq))))))
-
-CarDemand_hh$monthlyCarWashUse <- CarDemand_hh$carwash_freq * CarDemand_hh$CarSum *
- CarDemand_hh$Mean_wash #monthly consumption for car washing
-summary(CarDemand_hh$monthlyCarWashUse)</code></pre>
+#Need to do the same for carwashing frequencies, so that litres (mean_wash) can be multiplied by frequencies and number of cars to produce monthly consumption (monthlyCarWashUse).
+#most households have not indicated how often they wash their cars, so their consumption cannot be calculated. Thus, I took the mean of reported frequencies for each household size and I assigned it to each household that has a car but no records for how often they wash it.
+
+
+size1mean_freq<-filter(CarDemand_hh, hhsize == 1 & CarSum>=1)
+freq1<-mean (size1mean_freq$carwash_freq,na.rm=TRUE)
+size2mean_freq<-filter(CarDemand_hh, hhsize == 2 & CarSum>=1)
+freq2<-mean (size2mean_freq$carwash_freq,na.rm=TRUE)
+size3mean_freq<-filter(CarDemand_hh, hhsize == 3 &CarSum>=1)
+freq3<-mean (size3mean_freq$carwash_freq,na.rm=TRUE)
+size4mean_freq<-filter(CarDemand_hh, hhsize == 4 &CarSum>=1)
+freq4<-mean (size4mean_freq$carwash_freq,na.rm=TRUE)
+size5mean_freq<-filter(CarDemand_hh, hhsize == 5 &CarSum>=1)
+freq5<-mean (size5mean_freq$carwash_freq,na.rm=TRUE)
+size6mean_freq<-filter(CarDemand_hh, hhsize == 6 &CarSum>=1)
+freq6<-mean (size6mean_freq$carwash_freq,na.rm=TRUE)
+
+CarDemand_hh$carwash_freq <- ifelse(is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 1, freq1, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 2, freq2, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 3, freq3, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 4, freq4,ifelse ( is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 5, freq5,ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 6, freq6,CarDemand_hh$carwash_freq ))))))
+
+CarDemand_hh$monthlyCarWashUse<-CarDemand_hh$carwash_freq*CarDemand_hh$CarSum*CarDemand_hh$Mean_wash #monthly consumption for car washing
+summary(CarDemand_hh$monthlyCarWashUse) </code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.00 0.00 7.50 24.12 23.33 746.67 4</code></pre>
<pre class="r"><code>summary(CarDemand_hh$monthlyCarWashUse)</code></pre>
<pre><code>## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 0.00 0.00 7.50 24.12 23.33 746.67 4</code></pre>
-<pre class="r"><code>CarDemand_hh <- CarDemand_hh[, -(5:13), drop = FALSE] #dropping columns i dont need
-CarDemand_hh <- mutate(CarDemand_hh, dailyCarWashUse = monthlyCarWashUse/30)
+<pre class="r"><code>CarDemand_hh<-CarDemand_hh[,-(5:13),drop=FALSE] #dropping columns i dont need
+CarDemand_hh<-mutate(CarDemand_hh,dailyCarWashUse= monthlyCarWashUse/30)
-kable(caption = "Summary of demand for car washing", CarDemand_hh[1:5, ])</code></pre>
+kable(caption = "Summary of demand for car washing",
+ CarDemand_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for car washing</caption>
<thead>
@@ -2194,34 +2118,29 @@ kable(caption = "Summary of demand for car washing", CarDemand_hh[1:5,
</tbody>
</table>
<p>Plot of carwashing demand per household size</p>
-<pre class="r"><code>ggplot(data = CarDemand_hh) + aes(y = monthlyCarWashUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total carwashing use (l/house/month)")</code></pre>
+<pre class="r"><code>ggplot(data=CarDemand_hh)+ aes(y = monthlyCarWashUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total carwashing use (l/house/month)")</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/carwashing%20water%20demand%20plot-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(CarDemand_hh[CarDemand_hh$meter == "yes" | CarDemand_hh$meter == "no",
- ], aes(factor(hhsize), monthlyCarWashUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = " carwashing demand (l/household/month)") + xlab("household size") +
- ylab("carwashing demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(CarDemand_hh[CarDemand_hh$meter == "yes"|CarDemand_hh$meter == "no",], aes(factor(hhsize), monthlyCarWashUse)) + geom_boxplot(aes(fill = meter))+labs(title = " carwashing demand (l/household/month)")+ xlab('household size')+ylab('carwashing demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/carwashing%20water%20demand%20plot-2.png" /><!-- --></p>
-<pre class="r"><code>ggplot(CarDemand_hh[CarDemand_hh$meter == "yes" | CarDemand_hh$meter == "no",
- ], aes(factor(hhsize), dailyCarWashUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "carwashing demand (l/household/day)") + xlab("household size") +
- ylab("carwashing demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(CarDemand_hh[CarDemand_hh$meter == "yes"|CarDemand_hh$meter == "no",], aes(factor(hhsize), dailyCarWashUse)) + geom_boxplot(aes(fill = meter))+labs(title = "carwashing demand (l/household/day)")+ xlab('household size')+ylab('carwashing demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/carwashing%20water%20demand%20plot-3.png" /><!-- --></p>
-<pre class="r"><code>CarDemand_hh <- CarDemand_hh <- subset(CarDemand_hh, select = c("id", "monthlyCarWashUse",
- "dailyCarWashUse"))</code></pre>
+<pre class="r"><code>CarDemand_hh <- CarDemand_hh<-subset(CarDemand_hh, select=c("id","monthlyCarWashUse","dailyCarWashUse" ))</code></pre>
</div>
<div id="washing-of-caravans-and-boats-not-implemented" class="section level2">
<h2><span class="header-section-number">5.3</span> Washing of caravans and boats (not implemented)</h2>
<p>We could not find data on litres per wash etc and it seems quite rare in any case so we have ignored this usage.</p>
-<pre class="r"><code>t <- table(Surveydata$q14b, Surveydata$q14c, useNA = "always")
+<pre class="r"><code>t <- table(Surveydata$q14b,Surveydata$q14c, useNA = "always")
-kable(caption = "Frequency of washing caravans (rows) vs boats", t)</code></pre>
+kable(caption = "Frequency of washing caravans (rows) vs boats",
+ t)</code></pre>
<table>
<caption>Frequency of washing caravans (rows) vs boats</caption>
<thead>
<tr class="header">
-<th></th>
-<th></th>
+<th align="left"></th>
+<th align="right"></th>
<th align="right">less often than every three months</th>
<th align="right">never</th>
<th align="right">NA</th>
@@ -2229,73 +2148,67 @@ kable(caption = "Frequency of washing caravans (rows) vs boats", t)</c
</thead>
<tbody>
<tr class="odd">
-<td></td>
-<td>1782</td>
+<td align="left"></td>
+<td align="right">1782</td>
<td align="right">1</td>
<td align="right">3</td>
<td align="right">0</td>
</tr>
<tr class="even">
-<td>at least once a week</td>
-<td>1</td>
+<td align="left">at least once a week</td>
+<td align="right">1</td>
<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>less often than every three months</td>
-<td>5</td>
+<td align="left">less often than every three months</td>
+<td align="right">5</td>
<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
</tr>
<tr class="even">
-<td>less than once a month, but at least every three months</td>
-<td>4</td>
+<td align="left">less than once a month, but at least every three months</td>
+<td align="right">4</td>
<td align="right">0</td>
<td align="right">1</td>
<td align="right">0</td>
</tr>
<tr class="odd">
-<td>never</td>
-<td>2</td>
+<td align="left">never</td>
+<td align="right">2</td>
<td align="right">0</td>
<td align="right">1</td>
<td align="right">0</td>
</tr>
<tr class="even">
-<td>NA</td>
-<td>0</td>
+<td align="left">NA</td>
+<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
<td align="right">0</td>
</tr>
</tbody>
</table>
-</div>
-</div>
-<div id="total-consumption" class="section level1">
-<h1><span class="header-section-number">6</span> Total consumption</h1>
+<p># Total consumption</p>
<p>Combine the internal and external consumption estimates per household.</p>
<pre class="r"><code>totalExtDemand_hh <- merge(monthlyGardenUse_hh, CarDemand_hh, by = "id")
-# only keep what we need
-totalExtDemand_hh <- subset(totalExtDemand_hh, select = c("id", "monthlyGardenUse",
- "dailyGardenUse", "monthlyCarWashUse", "dailyCarWashUse"))
+# only keep what we need
+totalExtDemand_hh <- subset(totalExtDemand_hh, select=c("id","monthlyGardenUse","dailyGardenUse","monthlyCarWashUse","dailyCarWashUse" ))
# clean up
-totalIntDemand_hh <- rename(totalIntDemand_hh, meter = meter.x.x)
-totalIntDemand_hh <- rename(totalIntDemand_hh, hhsize = hhsize.x.x)
+totalIntDemand_hh <- rename(totalIntDemand_hh, meter = meter.x.x)
+totalIntDemand_hh <- rename(totalIntDemand_hh, hhsize = hhsize.x.x)
# why can't merge combined 3+ data frames?
totalDemand_hh <- merge(totalIntDemand_hh, totalExtDemand_hh, by = "id")
-totalDemand_hh$totalMonthlyHouseDemandFinal <- totalDemand_hh$totalMonthlyInHouseDemand +
- totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
+totalDemand_hh$totalMonthlyHouseDemandFinal <- totalDemand_hh$totalMonthlyInHouseDemand + totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
totalDemand_hh$totalDailyHouseDemandFinal <- totalDemand_hh$totalMonthlyHouseDemandFinal/30
-# construct other daily values that may have been removed during merging
-# process
+# construct other daily values that may have been removed during merging process
totalDemand_hh$dailyBathUse <- totalDemand_hh$monthlyBathUse/30
totalDemand_hh$dailyShowerUse <- totalDemand_hh$monthlyShowerUse/30
totalDemand_hh$dailyDishwasherUse <- totalDemand_hh$monthlyDishwasherUse/30
@@ -2304,22 +2217,41 @@ totalDemand_hh$dailyWCUse <- totalDemand_hh$monthlyWCUse/30
totalDemand_hh$dailyWashingMachineUse <- totalDemand_hh$monthlyWashingMachineUse/30
totalDemand_hh$dailyBathroomSinkUse <- totalDemand_hh$monthlyBathroomSinkUse/30</code></pre>
</div>
+</div>
<div id="summaries" class="section level1">
-<h1><span class="header-section-number">7</span> Summaries</h1>
+<h1><span class="header-section-number">6</span> Summaries</h1>
<pre class="r"><code># I am combining the bath and shower datasets
-bath_sh_hh <- merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all.x = TRUE)
-
-# at this point I got extra observations after merging the datasets. Now has
-# been corrected. The following test revealed the duplicates: n_occur <-
-# data.frame(table(bath_sh_hh$id)) n_occur[n_occur$Freq > 1,]
-# bath_sh_hh[bath_sh_hh$id %in% n_occur$Var1[n_occur$Freq > 1],] id
-# 836900103 appears 4 times in the merged dataframe!!
-
-# i am deleting the columns i dont need
-bath_sh_hh <- subset(bath_sh_hh, select = -c(obs.x, obs.y))
-kable(caption = "Summary of bath and shower demand", bath_sh_hh[1:5, ])</code></pre>
+bath_sh_hh<-merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all.x = TRUE)
+
+#at this point I got extra observations after merging the datasets. Now has been corrected. The following test revealed the duplicates:
+#n_occur <- data.frame(table(bath_sh_hh$id))
+#n_occur[n_occur$Freq > 1,]
+#bath_sh_hh[bath_sh_hh$id %in% n_occur$Var1[n_occur$Freq > 1],]
+#id 836900103 appears 4 times in the merged dataframe!!
+
+#i am deleting the columns i dont need
+bath_sh_hh <- subset(bath_sh_hh, select = -c(obs.x,obs.y))
+kable(caption = "Summary of bath and shower demand",
+ bath_sh_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of bath and shower demand</caption>
+<colgroup>
+<col width="5%" />
+<col width="5%" />
+<col width="6%" />
+<col width="5%" />
+<col width="3%" />
+<col width="5%" />
+<col width="8%" />
+<col width="10%" />
+<col width="8%" />
+<col width="7%" />
+<col width="5%" />
+<col width="6%" />
+<col width="10%" />
+<col width="8%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">id</th>
@@ -2422,35 +2354,38 @@ kable(caption = "Summary of bath and shower demand", bath_sh_hh[1:5, ]
</tbody>
</table>
<pre class="r"><code># combining the dishwashers and kitchen sink datasets
-kitchen_dish_hh <- merge(x = monthlyDishwasherUse, y = kitchen_sink_hh, by = "id",
- all = TRUE)
-kitchen_dish_hh <- kitchen_dish_hh[, -(2:7), drop = FALSE] #dropping columns i dont need
+kitchen_dish_hh<-merge(x = monthlyDishwasherUse, y = kitchen_sink_hh, by = "id", all = TRUE)
+kitchen_dish_hh<-kitchen_dish_hh[,-(2:7),drop=FALSE]#dropping columns i dont need
summary(kitchen_dish_hh)</code></pre>
-<pre><code>## id monthlyDishwasherUse dailyDishwasherUse
-## Min. :836900048 Min. : 0.00 Min. :0.000
-## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000
-## Median :836920637 Median : 0.00 Median :0.000
-## Mean :836919052 Mean : 71.18 Mean :2.373
-## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :836965495 Max. :268.80 Max. :8.960
-## obs.y hhsize.y meter.y monthlyKitchenSinkUse
-## Min. : 2.0 Min. : 1.000 don't know:167 Min. : 227.1
-## 1st Qu.: 454.8 1st Qu.: 2.000 no :864 1st Qu.: 454.2
-## Median : 905.5 Median : 2.000 yes :769 Median : 454.2
-## Mean : 906.0 Mean : 2.655 Mean : 603.0
-## 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.: 908.4
-## Max. :1810.0 Max. :10.000 Max. :2271.0
-## dailyKitchenSinkUse
-## Min. : 7.57
-## 1st Qu.:15.14
-## Median :15.14
-## Mean :20.10
-## 3rd Qu.:30.28
-## Max. :75.70</code></pre>
-<pre class="r"><code>kable(caption = "Summary of demand for dishwashers and kitchen uses", kitchen_dish_hh[1:5,
- ])</code></pre>
+<pre><code>## id monthlyDishwasherUse dailyDishwasherUse obs.y
+## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0
+## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8
+## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5
+## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0
+## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2
+## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0
+## hhsize.y meter.y monthlyKitchenSinkUse dailyKitchenSinkUse
+## Min. : 1.000 Length:1800 Min. : 227.1 Min. : 7.57
+## 1st Qu.: 2.000 Class :character 1st Qu.: 454.2 1st Qu.:15.14
+## Median : 2.000 Mode :character Median : 454.2 Median :15.14
+## Mean : 2.655 Mean : 603.0 Mean :20.10
+## 3rd Qu.: 4.000 3rd Qu.: 908.4 3rd Qu.:30.28
+## Max. :10.000 Max. :2271.0 Max. :75.70</code></pre>
+<pre class="r"><code>kable(caption = "Summary of demand for dishwashers and kitchen uses",
+ kitchen_dish_hh [1:5,]
+)</code></pre>
<table>
<caption>Summary of demand for dishwashers and kitchen uses</caption>
+<colgroup>
+<col width="8%" />
+<col width="17%" />
+<col width="16%" />
+<col width="5%" />
+<col width="7%" />
+<col width="9%" />
+<col width="18%" />
+<col width="16%" />
+</colgroup>
<thead>
<tr class="header">
<th align="right">id</th>
@@ -2517,117 +2452,132 @@ summary(kitchen_dish_hh)</code></pre>
</tbody>
</table>
<div id="daily" class="section level2">
-<h2><span class="header-section-number">7.1</span> Daily</h2>
+<h2><span class="header-section-number">6.1</span> Daily</h2>
<p>What do we do about NAs - are they meaningful or should they be 0 e.g. when summing values where 1 or more is NA?</p>
-<pre class="r"><code>t <- summary(select(totalDemand_hh, contains("daily"))) #
+<pre class="r"><code>t <- summary(select(totalDemand_hh, contains("daily"))) #
-kable(caption = "Summary of daily total household demand values", t)</code></pre>
+kable(caption = "Summary of daily total household demand values",
+ t
+)</code></pre>
<table>
<caption>Summary of daily total household demand values</caption>
+<colgroup>
+<col width="1%" />
+<col width="7%" />
+<col width="8%" />
+<col width="14%" />
+<col width="7%" />
+<col width="7%" />
+<col width="10%" />
+<col width="10%" />
+<col width="7%" />
+<col width="12%" />
+<col width="11%" />
+</colgroup>
<thead>
<tr class="header">
-<th></th>
+<th align="left"></th>
<th align="left">dailyGardenUse</th>
<th align="left">dailyCarWashUse</th>
<th align="left">totalDailyHouseDemandFinal</th>
-<th align="center">dailyBathUse</th>
+<th align="left">dailyBathUse</th>
<th align="left">dailyShowerUse</th>
<th align="left">dailyDishwasherUse</th>
<th align="left">dailyKitchenSinkUse</th>
-<th align="center">dailyWCUse</th>
+<th align="left">dailyWCUse</th>
<th align="left">dailyWashingMachineUse</th>
<th align="left">dailyBathroomSinkUse</th>
</tr>
</thead>
<tbody>
<tr class="odd">
-<td></td>
+<td align="left"></td>
<td align="left">Min. : 0.00</td>
<td align="left">Min. : 0.0000</td>
<td align="left">Min. : 63.56</td>
-<td align="center">Min. : 0.00</td>
+<td align="left">Min. : 0.00</td>
<td align="left">Min. : 0.0</td>
<td align="left">Min. :0.000</td>
<td align="left">Min. : 7.57</td>
-<td align="center">Min. : 25.00</td>
+<td align="left">Min. : 25.00</td>
<td align="left">Min. : 0.00</td>
<td align="left">Min. : 10.40</td>
</tr>
<tr class="even">
-<td></td>
+<td align="left"></td>
<td align="left">1st Qu.: 0.00</td>
<td align="left">1st Qu.: 0.0000</td>
<td align="left">1st Qu.: 211.37</td>
-<td align="center">1st Qu.:19.95</td>
+<td align="left">1st Qu.:19.95</td>
<td align="left">1st Qu.: 48.8</td>
<td align="left">1st Qu.:0.000</td>
<td align="left">1st Qu.:15.14</td>
-<td align="center">1st Qu.: 50.00</td>
+<td align="left">1st Qu.: 50.00</td>
<td align="left">1st Qu.:16.67</td>
<td align="left">1st Qu.: 26.48</td>
</tr>
<tr class="odd">
-<td></td>
+<td align="left"></td>
<td align="left">Median :18.72</td>
<td align="left">Median : 0.2500</td>
<td align="left">Median : 314.64</td>
-<td align="center">Median :26.40</td>
+<td align="left">Median :26.40</td>
<td align="left">Median : 93.6</td>
<td align="left">Median :0.000</td>
<td align="left">Median :15.14</td>
-<td align="center">Median : 75.00</td>
+<td align="left">Median : 75.00</td>
<td align="left">Median :16.67</td>
<td align="left">Median : 39.72</td>
</tr>
<tr class="even">
-<td></td>
+<td align="left"></td>
<td align="left">Mean :19.95</td>
<td align="left">Mean : 0.8041</td>
<td align="left">Mean : 352.75</td>
-<td align="center">Mean :35.53</td>
+<td align="left">Mean :35.53</td>
<td align="left">Mean :107.0</td>
<td align="left">Mean :2.373</td>
<td align="left">Mean :20.10</td>
-<td align="center">Mean : 91.31</td>
+<td align="left">Mean : 91.31</td>
<td align="left">Mean :23.61</td>
<td align="left">Mean : 58.27</td>
</tr>
<tr class="odd">
-<td></td>
+<td align="left"></td>
<td align="left">3rd Qu.:31.79</td>
<td align="left">3rd Qu.: 0.7778</td>
<td align="left">3rd Qu.: 477.91</td>
-<td align="center">3rd Qu.:56.91</td>
+<td align="left">3rd Qu.:56.91</td>
<td align="left">3rd Qu.:154.6</td>
<td align="left">3rd Qu.:4.293</td>
<td align="left">3rd Qu.:30.28</td>
-<td align="center">3rd Qu.:112.50</td>
+<td align="left">3rd Qu.:112.50</td>
<td align="left">3rd Qu.:30.00</td>
<td align="left">3rd Qu.: 66.20</td>
</tr>
<tr class="even">
-<td></td>
+<td align="left"></td>
<td align="left">Max. :85.44</td>
<td align="left">Max. :24.8889</td>
<td align="left">Max. :1154.18</td>
-<td align="center">Max. :77.44</td>
+<td align="left">Max. :77.44</td>
<td align="left">Max. :513.8</td>
<td align="left">Max. :8.960</td>
<td align="left">Max. :75.70</td>
-<td align="center">Max. :262.50</td>
+<td align="left">Max. :262.50</td>
<td align="left">Max. :80.00</td>
<td align="left">Max. :463.20</td>
</tr>
<tr class="odd">
-<td></td>
+<td align="left"></td>
<td align="left">NA’s :331</td>
<td align="left">NA’s :4</td>
<td align="left">NA’s :334</td>
-<td align="center">NA</td>
+<td align="left">NA</td>
<td align="left">NA’s :53</td>
<td align="left">NA</td>
<td align="left">NA</td>
-<td align="center">NA’s :59</td>
+<td align="left">NA’s :59</td>
<td align="left">NA’s :47</td>
<td align="left">NA’s :53</td>
</tr>
@@ -2636,73 +2586,65 @@ kable(caption = "Summary of daily total household demand values", t)</
</div>
</div>
<div id="summary-plots" class="section level1">
-<h1><span class="header-section-number">8</span> Summary plots</h1>
-<pre class="r"><code>ggplot(data = totalDemand_hh) + geom_bar(mapping = aes(x = factor(hhsize))) +
- xlab("household size")</code></pre>
+<h1><span class="header-section-number">7</span> Summary plots</h1>
+<pre class="r"><code>ggplot(data = totalDemand_hh) +
+ geom_bar(mapping = aes(x = factor(hhsize)))+ xlab('household size') </code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Household%20size-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data = totalDemand_hh) + geom_bar(mapping = aes(x = factor(meter))) +
- xlab("metered or not")</code></pre>
+<pre class="r"><code>ggplot(data = totalDemand_hh) +
+ geom_bar(mapping = aes(x = factor(meter)))+xlab('metered or not')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Number%20metered-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data = totalDemand_hh) + aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total use (l/month)") + labs(title = " total demand (l/household/month)") +
- xlab("household size") + ylab("total household demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total use (l/month)")+labs(title = " total demand (l/household/month)")+ xlab('household size')+ylab('total household demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Total%20monthly%20demand%20by%20household%20size-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data = totalDemand_hh) + aes(y = totalMonthlyHouseDemandFinal, x = factor(meter)) +
- geom_boxplot() + labs(title = "Total demand (l/household/month)") + xlab("metered or not") +
- ylab("Total household demand (l/hh/month)")</code></pre>
+<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(meter)) +
+ geom_boxplot() +labs(title = "Total demand (l/household/month)")+ xlab('metered or not')+ylab('Total household demand (l/hh/month)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Total%20monthly%20demand%20by%20metering-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(data = totalDemand_hh) + aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() + labs(title = " Total demand (l/household/day)") + xlab("metered or not") +
- ylab("Total household demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(data=totalDemand_hh)+ aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
+ geom_boxplot() +labs(title = " Total demand (l/household/day)")+ xlab('metered or not')+ylab('Total household demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Total%20monthly%20external%20demand%20by%20household%20size-1.png" /><!-- --></p>
-<pre class="r"><code>ggplot(totalDemand_hh[totalDemand_hh$meter == "yes" | totalDemand_hh$meter ==
- "no", ], aes(factor(hhsize), totalDailyHouseDemandFinal)) + geom_boxplot(aes(fill = meter)) +
- labs(title = " total demand (l/household/day)") + xlab("household size") +
- ylab("total demand (l/hh/day)")</code></pre>
+<pre class="r"><code>ggplot(totalDemand_hh[totalDemand_hh$meter == "yes"|totalDemand_hh$meter == "no",], aes(factor(hhsize), totalDailyHouseDemandFinal)) + geom_boxplot(aes(fill = meter))+labs(title = " total demand (l/household/day)")+ xlab('household size')+ylab('total demand (l/hh/day)')</code></pre>
<p><img src="SPRG_demand_v2.1_BA_files/figure-html/Total%20daily%20demand%20by%20household%20size%20&%20metering-1.png" /><!-- --></p>
<p>Now write out the seasonal values</p>
-<pre class="r"><code># delete columns I dont need
-totalDemand_hh <- subset(totalDemand_hh, select = -c(obs.y)) # remove what we don't want to keep
+<pre class="r"><code>#delete columns I dont need
+totalDemand_hh <- subset(totalDemand_hh, select = -c(obs.y)) # remove what we don't want to keep
# seasonal values are input config file to WDEM. Monthly values are unused
-# tab delimted output file write.csv(hhmonthly,
-# paste(fpath,'output-hh-monthly-consumption',format(Sys.time(), '%Y-%m-%d
-# %I-%p'),'.csv', sep = '')) oFile <-
-# paste0(opath,'output-hh-seasonal-consumption_',format(Sys.time(),
-# '%Y-%m-%d'), 'v2.txt', sep = '') write.table(hhmcSeasonalValuesDT,
-# oFile,sep = '\t')
+# tab delimted output file
+# write.csv(hhmonthly, paste(fpath,"output-hh-monthly-consumption",format(Sys.time(), "%Y-%m-%d %I-%p"),".csv", sep = ""))
+#oFile <- paste0(opath,"output-hh-seasonal-consumption_",format(Sys.time(), "%Y-%m-%d"), "v2.txt", sep = "")
+#write.table(hhmcSeasonalValuesDT, oFile,sep = "\t")
-oFile <- paste0(oPath, "output-SPRG-1800hh-consumption_", format(Sys.time(),
- "%Y-%m-%d"), outputVersion, ".csv")
+oFile <- paste0(oPath,"output-SPRG-1800hh-consumption_",format(Sys.time(), "%Y-%m-%d"), outputVersion, ".csv")
write.csv(totalDemand_hh, oFile)</code></pre>
<p>Data written to:</p>
<blockquote>
-<p>~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2017-06-19v2.1.csv and (possibly) gzipped</p>
+<p>~/University of Southampton/IMPETUS - Documents/data//model_outputs/output-SPRG-1800hh-consumption_2021-03-11v2.1.csv and (possibly) gzipped</p>
</blockquote>
</div>
<div id="about" class="section level1">
-<h1><span class="header-section-number">9</span> About</h1>
+<h1><span class="header-section-number">8</span> About</h1>
<p>This work was supported by the NERC funded IMPETUS (Improving Predictions of Drought for User Decision-Making) project:</p>
<ul>
<li><a href="http://gotw.nerc.ac.uk/list_split.asp?awardref=NE%2FL010216%2F1">http://gotw.nerc.ac.uk/list_split.asp?awardref=NE%2FL010216%2F1</a></li>
</ul>
<div id="code" class="section level2">
-<h2><span class="header-section-number">9.1</span> Code</h2>
+<h2><span class="header-section-number">8.1</span> Code</h2>
<ul>
<li><a href="https://github.com/dataknut/IMPETUS" class="uri">https://github.com/dataknut/IMPETUS</a> (currently private)</li>
</ul>
</div>
<div id="citation" class="section level2">
-<h2><span class="header-section-number">9.2</span> Citation</h2>
+<h2><span class="header-section-number">8.2</span> Citation</h2>
<p>If you wish to use any of the material from this report please cite as:</p>
<ul>
-<li>Manouseli, D., & Anderson, B. (2017) <em>Domestic Water Demand Estimation Using SPRG Survey</em>, University of Southampton: Southampton, UK.</li>
+<li>Manouseli, D., & Anderson, B. (2021) <em>Domestic Water Demand Estimation Using SPRG Survey</em>, University of Southampton: Southampton, UK.</li>
</ul>
</div>
<div id="runtime" class="section level2">
-<h2><span class="header-section-number">9.3</span> Runtime</h2>
-<p>Analysis completed in: 19.16 seconds using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 3.4.0 (2017-04-21) running on x86_64-apple-darwin15.6.0.</p>
+<h2><span class="header-section-number">8.3</span> Runtime</h2>
+<p>Analysis completed in: 15.97 seconds using <a href="https://cran.r-project.org/package=knitr">knitr</a> in <a href="http://www.rstudio.com">RStudio</a> with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.</p>
<p>R packages used:</p>
<ul>
<li>base R - for the basics <span class="citation">(R Core Team 2016)</span></li>
@@ -2719,19 +2661,19 @@ write.csv(totalDemand_hh, oFile)</code></pre>
<h1>References</h1>
<div id="refs" class="references">
<div id="ref-baseR">
-<p>R Core Team. 2016. <em>R: A Language and Environment for Statistical Computing</em>. Vienna, Austria: R Foundation for Statistical Computing. <a href="https://www.R-project.org/" class="uri">https://www.R-project.org/</a>.</p>
+<p>R Core Team. 2016. <em>R: A Language and Environment for Statistical Computing</em>. Vienna, Austria: R Foundation for Statistical Computing. <a href="https://www.R-project.org/">https://www.R-project.org/</a>.</p>
</div>
<div id="ref-ggplot2">
-<p>Wickham, Hadley. 2009. <em>Ggplot2: Elegant Graphics for Data Analysis</em>. Springer-Verlag New York. <a href="http://ggplot2.org" class="uri">http://ggplot2.org</a>.</p>
+<p>Wickham, Hadley. 2009. <em>Ggplot2: Elegant Graphics for Data Analysis</em>. Springer-Verlag New York. <a href="http://ggplot2.org">http://ggplot2.org</a>.</p>
</div>
<div id="ref-tidyverse">
-<p>———. 2017. <em>Tidyverse: Easily Install and Load ’Tidyverse’ Packages</em>. <a href="https://CRAN.R-project.org/package=tidyverse" class="uri">https://CRAN.R-project.org/package=tidyverse</a>.</p>
+<p>———. 2017. <em>Tidyverse: Easily Install and Load ’Tidyverse’ Packages</em>. <a href="https://CRAN.R-project.org/package=tidyverse">https://CRAN.R-project.org/package=tidyverse</a>.</p>
</div>
<div id="ref-dplyr">
-<p>Wickham, Hadley, and Romain Francois. 2016. <em>Dplyr: A Grammar of Data Manipulation</em>. <a href="https://CRAN.R-project.org/package=dplyr" class="uri">https://CRAN.R-project.org/package=dplyr</a>.</p>
+<p>Wickham, Hadley, and Romain Francois. 2016. <em>Dplyr: A Grammar of Data Manipulation</em>. <a href="https://CRAN.R-project.org/package=dplyr">https://CRAN.R-project.org/package=dplyr</a>.</p>
</div>
<div id="ref-knitr">
-<p>Xie, Yihui. 2016. <em>Knitr: A General-Purpose Package for Dynamic Report Generation in R</em>. <a href="https://CRAN.R-project.org/package=knitr" class="uri">https://CRAN.R-project.org/package=knitr</a>.</p>
+<p>Xie, Yihui. 2016. <em>Knitr: A General-Purpose Package for Dynamic Report Generation in R</em>. <a href="https://CRAN.R-project.org/package=knitr">https://CRAN.R-project.org/package=knitr</a>.</p>
</div>
</div>
</div>
@@ -2747,7 +2689,7 @@ write.csv(totalDemand_hh, oFile)</code></pre>
// add bootstrap table styles to pandoc tables
function bootstrapStylePandocTables() {
- $('tr.header').parent('thead').parent('table').addClass('table table-condensed');
+ $('tr.odd').parent('tbody').parent('table').addClass('table table-condensed');
}
$(document).ready(function () {
bootstrapStylePandocTables();
@@ -2756,6 +2698,49 @@ $(document).ready(function () {
</script>
+<!-- tabsets -->
+
+<script>
+$(document).ready(function () {
+ window.buildTabsets("TOC");
+});
+
+$(document).ready(function () {
+ $('.tabset-dropdown > .nav-tabs > li').click(function () {
+ $(this).parent().toggleClass('nav-tabs-open')
+ });
+});
+</script>
+
+<!-- code folding -->
+
+<script>
+$(document).ready(function () {
+
+ // move toc-ignore selectors from section div to header
+ $('div.section.toc-ignore')
+ .removeClass('toc-ignore')
+ .children('h1,h2,h3,h4,h5').addClass('toc-ignore');
+
+ // establish options
+ var options = {
+ selectors: "h1,h2,h3,h4",
+ theme: "bootstrap3",
+ context: '.toc-content',
+ hashGenerator: function (text) {
+ return text.replace(/[.\\/?&!#<>]/g, '').replace(/\s/g, '_');
+ },
+ ignoreSelector: ".toc-ignore",
+ scrollTo: 0
+ };
+ options.showAndHide = true;
+ options.smoothScroll = true;
+
+ // tocify
+ var toc = $("#TOC").tocify(options).data("toc-tocify");
+});
+</script>
+
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
diff --git a/model_v2/SPRG_demand_v2.1_BA.md b/model_v2/SPRG_demand_v2.1_BA.md
index 0c27a3cdbbcdc87aa2fe81724bd8683946d6bbdb..acddb04975a3e42984e5fe9129623a79f38aadb6 100644
--- a/model_v2/SPRG_demand_v2.1_BA.md
+++ b/model_v2/SPRG_demand_v2.1_BA.md
@@ -1,6 +1,22 @@
-# Domestic Water Demand Estimation Using SPRG Survey
-Despina Manouseli & Ben Anderson
-Last run at: `r Sys.time()`
+---
+title: "Domestic Water Demand Estimation Using SPRG Survey"
+author: "Despina Manouseli & Ben Anderson"
+date: 'Last run at: 2021-03-11 16:50:37'
+output:
+ html_document:
+ keep_md: yes
+ number_sections: yes
+ self_contained: no
+ toc: yes
+ toc_depth: 4
+ toc_float: yes
+ pdf_document:
+ number_sections: yes
+ toc: yes
+ toc_depth: 4
+ toc_float: yes
+bibliography: '/Users/ben/OneDrive - University of Southampton/Documents/repos/git.soton/serg/IMPETUS/bibliography.bib'
+---
@@ -31,59 +47,65 @@ First, load the SPRG survey data that is used for the household attributes.
```r
-# dPath <- 'C:/Users/despina/Desktop/ImpetusPackageJan2017/' fpath <-
-# paste0(dPath, '/') opath <- paste0(dPath, '/') print(paste0('Data path:
-# ',dPath)) print(paste0('Data path: ',dPath)) Surveydata <-
-# read.csv('C:/Users/despina/Desktop/ImpetusPackageJan2017/SPRGdata_duplicateDELETED.csv')
+# dPath <- "C:/Users/despina/Desktop/ImpetusPackageJan2017/"
+# fpath <- paste0(dPath, "/")
+# opath <- paste0(dPath, "/")
+# print(paste0("Data path: ",dPath))
+# print(paste0("Data path: ",dPath))
+#Surveydata <- read.csv("C:/Users/despina/Desktop/ImpetusPackageJan2017/SPRGdata_duplicateDELETED.csv")
Surveydata <- read.csv(paste0(iPath, "SPRG dataset/SPRGdata_duplicateDELETED.csv"))
-t <- Surveydata[1:10, 1:8]
+t <- Surveydata[1:10,1:8]
-kable(caption = "Example rows/columns SPRG data table", t)
+kable(caption = "Example rows/columns SPRG data table",
+ t
+)
```
Table: Example rows/columns SPRG data table
- iobs bmg_id q2 q2b_1 q2c_1 q2d_1 q2a_2 q2b_2
------ ---------- --- -------- ------- ------------------------------------------ ------------------------- ---------
- 2 836900048 2 65-74 female retired husband, wife or partner 65-74
- 3 836900071 2 25-34 female other husband, wife or partner 25-34
- 4 836900073 4 16-24 male student (19 - 24 years old) other relative 45-54
- 5 836900106 1 75+ female retired
- 6 836900117 4 45-54 female part-time paid work (8 - 29 hrs per week) husband, wife or partner 35-44
- 8 836900328 2 refused female other other relative refused
- 9 836900330 1 75+ female retired
- 10 836900325 3 16-24 female student (19 - 24 years old) parent 45-54
- 11 836900310 1 55-64 female permanently sick/disabled
- 12 836900313 3 25-34 female looking after home/family son or daughter under 16
+| iobs| bmg_id| q2|q2b_1 |q2c_1 |q2d_1 |q2a_2 |q2b_2 |
+|----:|---------:|--:|:-------|:------|:-----------------------------------------|:------------------------|:--------|
+| 2| 836900048| 2|65-74 |female |retired |husband, wife or partner |65-74 |
+| 3| 836900071| 2|25-34 |female |other |husband, wife or partner |25-34 |
+| 4| 836900073| 4|16-24 |male |student (19 - 24 years old) |other relative |45-54 |
+| 5| 836900106| 1|75+ |female |retired | | |
+| 6| 836900117| 4|45-54 |female |part-time paid work (8 - 29 hrs per week) |husband, wife or partner |35-44 |
+| 8| 836900328| 2|refused |female |other |other relative |refused |
+| 9| 836900330| 1|75+ |female |retired | | |
+| 10| 836900325| 3|16-24 |female |student (19 - 24 years old) |parent |45-54 |
+| 11| 836900310| 1|55-64 |female |permanently sick/disabled | | |
+| 12| 836900313| 3|25-34 |female |looking after home/family |son or daughter |under 16 |
```r
t <- with(Surveydata, table(q2d_1, q2b_1, useNA = "always"))
-kable(caption = "SPRG: age and work status distributions of respondents", t)
+kable(caption = "SPRG: age and work status distributions of respondents",
+ t
+)
```
Table: SPRG: age and work status distributions of respondents
- 16-24 25-34 35-44 45-54 55-64 65-74 75+ refused NA
-------------------------------------------- ------ ------ ------ ------ ------ ------ ---- -------- ---
-full-time paid work (30+ hrs per week) 39 165 170 151 77 9 1 12 0
-looking after home/family 6 33 40 20 18 1 0 1 0
-other 0 14 10 6 1 1 1 7 0
-part-time paid work (8 - 29 hrs per week) 9 38 51 45 34 8 0 1 0
-part-time paid work (under 8 hrs per week) 0 1 1 0 0 1 0 0 0
-permanently sick/disabled 2 2 6 10 13 0 0 1 0
-retired 0 0 0 6 78 244 216 7 0
-self-employed 2 10 14 11 17 3 1 0 0
-student (16 - 18 years old) 35 0 0 0 0 0 0 0 0
-student (19 - 24 years old) 43 0 0 0 0 0 0 0 0
-unemployed (not seeking work) 3 11 7 13 4 0 0 0 0
-unemployed (seeking work) 14 20 15 15 5 0 0 0 0
-NA 0 0 0 0 0 0 0 0 0
+| | 16-24| 25-34| 35-44| 45-54| 55-64| 65-74| 75+| refused| NA|
+|:------------------------------------------|-----:|-----:|-----:|-----:|-----:|-----:|---:|-------:|--:|
+|full-time paid work (30+ hrs per week) | 39| 165| 170| 151| 77| 9| 1| 12| 0|
+|looking after home/family | 6| 33| 40| 20| 18| 1| 0| 1| 0|
+|other | 0| 14| 10| 6| 1| 1| 1| 7| 0|
+|part-time paid work (8 - 29 hrs per week) | 9| 38| 51| 45| 34| 8| 0| 1| 0|
+|part-time paid work (under 8 hrs per week) | 0| 1| 1| 0| 0| 1| 0| 0| 0|
+|permanently sick/disabled | 2| 2| 6| 10| 13| 0| 0| 1| 0|
+|retired | 0| 0| 0| 6| 78| 244| 216| 7| 0|
+|self-employed | 2| 10| 14| 11| 17| 3| 1| 0| 0|
+|student (16 - 18 years old) | 35| 0| 0| 0| 0| 0| 0| 0| 0|
+|student (19 - 24 years old) | 43| 0| 0| 0| 0| 0| 0| 0| 0|
+|unemployed (not seeking work) | 3| 11| 7| 13| 4| 0| 0| 0| 0|
+|unemployed (seeking work) | 14| 20| 15| 15| 5| 0| 0| 0| 0|
+|NA | 0| 0| 0| 0| 0| 0| 0| 0| 0|
The SPRG Survey dataset has 1800 observations.
@@ -91,52 +113,54 @@ Next, load the two EST (2013) data files which give frequencies of use of dishwa
```r
-ESTdata_dish <- read.table(paste0(iPath, "SPRG dataset/DishWashFreq_EST.txt"),
- header = TRUE)
+ESTdata_dish <- read.table(paste0(iPath, "SPRG dataset/DishWashFreq_EST.txt"), header = TRUE)
-kable(caption = "EST data table for dishwasher frequencies", ESTdata_dish)
+kable(caption = "EST data table for dishwasher frequencies",
+ ESTdata_dish
+)
```
Table: EST data table for dishwasher frequencies
- hhsize weeklyDish_freq
-------- ----------------
- 1 0.9
- 2 2.3
- 3 3.1
- 4 4.3
- 5 4.8
- 6 4.4
- 7 4.4
- 8 4.4
- 9 4.4
- 10 4.4
+| hhsize| weeklyDish_freq|
+|------:|---------------:|
+| 1| 0.9|
+| 2| 2.3|
+| 3| 3.1|
+| 4| 4.3|
+| 5| 4.8|
+| 6| 4.4|
+| 7| 4.4|
+| 8| 4.4|
+| 9| 4.4|
+| 10| 4.4|
```r
-ESTdata_showerBath <- read.table(paste0(iPath, "SPRG dataset/ShowerBathFreq_EST.txt"),
- header = TRUE)
+ESTdata_showerBath <- read.table(paste0(iPath, "SPRG dataset/ShowerBathFreq_EST.txt"), header = TRUE)
-kable(caption = "EST data table for shower and bath frequencies", ESTdata_showerBath)
+kable(caption = "EST data table for shower and bath frequencies",
+ ESTdata_showerBath
+)
```
Table: EST data table for shower and bath frequencies
- hhsize baths_freq_EST showers_freq_EST
-------- --------------- -----------------
- 1 1.70 5.20
- 2 2.25 9.40
- 3 4.00 12.05
- 4 4.85 14.65
- 5 5.60 15.95
- 6 6.60 16.05
- 7 6.60 16.05
- 8 6.60 16.05
- 9 6.60 16.05
- 10 6.60 16.05
+| hhsize| baths_freq_EST| showers_freq_EST|
+|------:|--------------:|----------------:|
+| 1| 1.70| 5.20|
+| 2| 2.25| 9.40|
+| 3| 4.00| 12.05|
+| 4| 4.85| 14.65|
+| 5| 5.60| 15.95|
+| 6| 6.60| 16.05|
+| 7| 6.60| 16.05|
+| 8| 6.60| 16.05|
+| 9| 6.60| 16.05|
+| 10| 6.60| 16.05|
# Estimate Internal Consumption
@@ -146,20 +170,20 @@ Table: EST data table for shower and bath frequencies
### Washing of hands
```r
-handdemand <- select(Surveydata, iobs, bmg_id, q2, q4)
-handdemand <- rename(handdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4)
-handdemand_hh <- mutate(handdemand, hands = (10.4 * hhsize * 30)) #Based on: http://avonlakewater.org/for-our-customers/how-much-water-do-i-use-when-i/ hand washing is 0.55 gal/wash. with a frequency of use of 5 times a day this is 2.75 gal/day=10.4 lt/day/person-for a standard faucet.
+handdemand<-select(Surveydata, iobs,bmg_id, q2, q4)
+handdemand<-rename(handdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4)
+handdemand_hh<-mutate(handdemand,hands= (10.4*hhsize*30)) #Based on: http://avonlakewater.org/for-our-customers/how-much-water-do-i-use-when-i/ hand washing is 0.55 gal/wash. with a frequency of use of 5 times a day this is 2.75 gal/day=10.4 lt/day/person-for a standard faucet.
summary(handdemand_hh)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
## hands
## Min. : 312.0
## 1st Qu.: 624.0
@@ -170,56 +194,44 @@ summary(handdemand_hh)
```
```r
-kable(caption = "Summary of demand for washing hands", handdemand_hh[1:5, ])
+kable(caption = "Summary of demand for washing hands",
+ handdemand_hh [1:5,]
+)
```
Table: Summary of demand for washing hands
- obs id hhsize meter hands
----- ---------- ------- ----------- ------
- 2 836900048 2 yes 624
- 3 836900071 2 don't know 624
- 4 836900073 4 yes 1248
- 5 836900106 1 yes 312
- 6 836900117 4 yes 1248
+| obs| id| hhsize|meter | hands|
+|---:|---------:|------:|:----------|-----:|
+| 2| 836900048| 2|yes | 624|
+| 3| 836900071| 2|don't know | 624|
+| 4| 836900073| 4|yes | 1248|
+| 5| 836900106| 1|yes | 312|
+| 6| 836900117| 4|yes | 1248|
### Teeth brushing
```r
-teethdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q36, q37)
-teethdemand1 <- rename(teethdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4,
- wash_freq = q36, teeth_where = q37)
-teethdemand1[, 5] <- ifelse(teethdemand1[, 5] == "after meals", 4, ifelse(teethdemand1[,
- 5] == "after some meals, plus morning and night", 4, ifelse(teethdemand1[,
- 5] == "don't want to answer", NA, ifelse(teethdemand1[, 5] == "just at night",
- 1, ifelse(teethdemand1[, 5] == "just in the morning", 1, ifelse(teethdemand1[,
- 5] == "more than once a day, but not at fixed times", 2, ifelse(teethdemand1[,
- 5] == "morning and night", 2, ifelse(teethdemand1[, 5] == "once a day, but not at a fixed time",
- 1, ifelse(teethdemand1[, 5] == "only have dentures", 0, ifelse(teethdemand1[,
- 5] == "other", NA, NA))))))))))
-teethdemand1[, 6] <- ifelse(teethdemand1[, 6] == "at a sink with a cup of water",
- 1.42, ifelse(teethdemand1[, 6] == "at a sink without a tap running", 1.42,
- ifelse(teethdemand1[, 6] == "at the sink with a tap running", 16.7,
- ifelse(teethdemand1[, 6] == "don't want to answer", NA, ifelse(teethdemand1[,
- 6] == "in the bath", 0, ifelse(teethdemand1[, 6] == "in the shower",
- 0, ifelse(teethdemand1[, 6] == "other", 0, NA)))))))
-
-teethdemand_hh <- mutate(teethdemand1, teethbrush_hh = (wash_freq * hhsize *
- teeth_where * 30))
+teethdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q36,q37)
+teethdemand1<-rename(teethdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, wash_freq=q36, teeth_where=q37)
+teethdemand1[,5] <- ifelse(teethdemand1[,5] == "after meals", 4 ,ifelse(teethdemand1[,5] == "after some meals, plus morning and night", 4, ifelse(teethdemand1[,5] == "don't want to answer", NA ,ifelse(teethdemand1[,5] == "just at night", 1, ifelse(teethdemand1[,5] == "just in the morning", 1,ifelse(teethdemand1[,5] == "more than once a day, but not at fixed times", 2,ifelse(teethdemand1[,5] == "morning and night", 2, ifelse(teethdemand1[,5] == "once a day, but not at a fixed time", 1 , ifelse(teethdemand1[,5] == "only have dentures", 0 ,ifelse(teethdemand1[,5] == "other", NA, NA))))))))))
+teethdemand1[,6]<- ifelse(teethdemand1[,6] == "at a sink with a cup of water", 1.42 ,ifelse(teethdemand1[,6] == "at a sink without a tap running", 1.42, ifelse(teethdemand1[,6] == "at the sink with a tap running", 16.7, ifelse(teethdemand1[,6] == "don't want to answer", NA,ifelse(teethdemand1[,6] == "in the bath", 0,ifelse(teethdemand1[,6] == "in the shower", 0,ifelse(teethdemand1[,6] == "other", 0, NA)))))))
+
+teethdemand_hh<-mutate(teethdemand1,teethbrush_hh= (wash_freq*hhsize*teeth_where*30))
summary(teethdemand_hh)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## wash_freq teeth_where teethbrush_hh
## Min. :0.000 Min. : 0.000 Min. : 0.0
## 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4
@@ -231,42 +243,42 @@ summary(teethdemand_hh)
```
```r
-kable(caption = "Summary of demand for teeth brushing", teethdemand_hh[1:5,
- ])
+kable(caption = "Summary of demand for teeth brushing",
+ teethdemand_hh [1:5,]
+)
```
Table: Summary of demand for teeth brushing
- obs id hhsize meter wash_freq teeth_where teethbrush_hh
----- ---------- ------- ----------- ---------- ------------ --------------
- 2 836900048 2 yes 2 1.42 170.4
- 3 836900071 2 don't know 2 1.42 170.4
- 4 836900073 4 yes 2 1.42 340.8
- 5 836900106 1 yes 2 1.42 85.2
- 6 836900117 4 yes 2 1.42 340.8
+| obs| id| hhsize|meter | wash_freq| teeth_where| teethbrush_hh|
+|---:|---------:|------:|:----------|---------:|-----------:|-------------:|
+| 2| 836900048| 2|yes | 2| 1.42| 170.4|
+| 3| 836900071| 2|don't know | 2| 1.42| 170.4|
+| 4| 836900073| 4|yes | 2| 1.42| 340.8|
+| 5| 836900106| 1|yes | 2| 1.42| 85.2|
+| 6| 836900117| 4|yes | 2| 1.42| 340.8|
### Total bathroom sink use
```r
-bathsink_hh <- merge(x = teethdemand_hh, y = handdemand_hh, by = "id", all = TRUE)
-bathsink_hh <- mutate(bathsink_hh, monthlyBathroomSinkUse = (teethbrush_hh +
- hands))
+bathsink_hh<-merge(x = teethdemand_hh, y = handdemand_hh, by = "id", all = TRUE)
+bathsink_hh<-mutate(bathsink_hh,monthlyBathroomSinkUse= (teethbrush_hh+hands))
-bathsink_hh <- bathsink_hh[, -(8:10), drop = FALSE] #droping columns I dont need
-bathsink_hh <- mutate(bathsink_hh, dailyBathroomSinkUse = (monthlyBathroomSinkUse/30))
+bathsink_hh<-bathsink_hh[,-(8:10),drop=FALSE]#droping columns I dont need
+bathsink_hh<-mutate(bathsink_hh,dailyBathroomSinkUse= (monthlyBathroomSinkUse/30))
summary(bathsink_hh)
```
```
-## id obs.x hhsize.x meter.x
-## Min. :836900048 Min. : 2.0 Min. : 1.000 don't know:167
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 no :864
-## Median :836920637 Median : 905.5 Median : 2.000 yes :769
-## Mean :836919052 Mean : 906.0 Mean : 2.655
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
-## Max. :836965495 Max. :1810.0 Max. :10.000
-##
+## id obs.x hhsize.x meter.x
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :1810.0 Max. :10.000
+##
## wash_freq teeth_where teethbrush_hh hands
## Min. :0.000 Min. : 0.000 Min. : 0.0 Min. : 312.0
## 1st Qu.:2.000 1st Qu.: 1.420 1st Qu.: 170.4 1st Qu.: 624.0
@@ -286,43 +298,40 @@ summary(bathsink_hh)
```
```r
-kable(caption = "Summary of demand for washing of hands", bathsink_hh[1:5, ])
+kable(caption = "Summary of demand for washing of hands",
+ bathsink_hh [1:5,]
+)
```
Table: Summary of demand for washing of hands
- id obs.x hhsize.x meter.x wash_freq teeth_where teethbrush_hh hands monthlyBathroomSinkUse dailyBathroomSinkUse
----------- ------ --------- ----------- ---------- ------------ -------------- ------ ----------------------- ---------------------
- 836900048 2 2 yes 2 1.42 170.4 624 794.4 26.48
- 836900071 3 2 don't know 2 1.42 170.4 624 794.4 26.48
- 836900073 4 4 yes 2 1.42 340.8 1248 1588.8 52.96
- 836900106 5 1 yes 2 1.42 85.2 312 397.2 13.24
- 836900117 6 4 yes 2 1.42 340.8 1248 1588.8 52.96
+| id| obs.x| hhsize.x|meter.x | wash_freq| teeth_where| teethbrush_hh| hands| monthlyBathroomSinkUse| dailyBathroomSinkUse|
+|---------:|-----:|--------:|:----------|---------:|-----------:|-------------:|-----:|----------------------:|--------------------:|
+| 836900048| 2| 2|yes | 2| 1.42| 170.4| 624| 794.4| 26.48|
+| 836900071| 3| 2|don't know | 2| 1.42| 170.4| 624| 794.4| 26.48|
+| 836900073| 4| 4|yes | 2| 1.42| 340.8| 1248| 1588.8| 52.96|
+| 836900106| 5| 1|yes | 2| 1.42| 85.2| 312| 397.2| 13.24|
+| 836900117| 6| 4|yes | 2| 1.42| 340.8| 1248| 1588.8| 52.96|
### Plot of bathroom sink demand per household size
```r
-ggplot(data = bathsink_hh) + aes(y = monthlyBathroomSinkUse, x = factor(hhsize.x)) +
- geom_boxplot() + labs(title = "total bathroom sink use (l/house/month)")
+ggplot(data=bathsink_hh)+ aes(y = monthlyBathroomSinkUse, x = factor(hhsize.x)) +
+ geom_boxplot() +
+ labs(title = "total bathroom sink use (l/house/month)")
```
<!-- -->
```r
-ggplot(bathsink_hh[bathsink_hh$meter.x == "yes" | bathsink_hh$meter.x == "no",
- ], aes(factor(hhsize.x), monthlyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x)) +
- labs(title = "sink demand (l/household/month)") + xlab("household size") +
- ylab("sink demand (l/hh/month)")
+ggplot(bathsink_hh[bathsink_hh$meter.x == "yes"|bathsink_hh$meter.x == "no",], aes(factor(hhsize.x), monthlyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x))+labs(title = "sink demand (l/household/month)")+ xlab('household size')+ylab('sink demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(bathsink_hh[bathsink_hh$meter.x == "yes" | bathsink_hh$meter.x == "no",
- ], aes(factor(hhsize.x), dailyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x)) +
- labs(title = "sink demand (l/household/day)") + xlab("household size") +
- ylab("sink demand (l/hh/day)")
+ggplot(bathsink_hh[bathsink_hh$meter.x == "yes"|bathsink_hh$meter.x == "no",], aes(factor(hhsize.x), dailyBathroomSinkUse)) + geom_boxplot(aes(fill = meter.x))+labs(title = "sink demand (l/household/day)")+ xlab('household size')+ylab('sink demand (l/hh/day)')
```
<!-- -->
@@ -334,21 +343,14 @@ ggplot(bathsink_hh[bathsink_hh$meter.x == "yes" | bathsink_hh$meter.x == "no",
```r
-bathdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q29_1, q7a_5)
-bathdemand1 <- rename(bathdemand, obs = iobs, id = bmg_id, hhsize = q2, meter = q4,
- bath_freq = q29_1, baths = q7a_5)
-bathdemand1[, 5] <- ifelse(bathdemand1[, 5] == "once a week", 1, ifelse(bathdemand1[,
- 5] == "twice a week", 2, ifelse(bathdemand1[, 5] == "three times a week",
- 3, ifelse(bathdemand1[, 5] == "four times a week", 4, ifelse(bathdemand1[,
- 5] == "five times a week", 5, ifelse(bathdemand1[, 5] == "six times a week",
- 6, ifelse(bathdemand1[, 5] == "seven times a week", 7, ifelse(bathdemand1[,
- 5] == "more than seven times a week", 9, ifelse(bathdemand1[, 5] ==
- "none", 0, NA)))))))))
+bathdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q29_1, q7a_5)
+bathdemand1<-rename(bathdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, bath_freq=q29_1, baths=q7a_5)
+bathdemand1[,5] <- ifelse(bathdemand1[,5] == "once a week", 1 ,ifelse(bathdemand1[,5] == "twice a week", 2, ifelse(bathdemand1[,5] == "three times a week", 3 ,ifelse(bathdemand1[,5] == "four times a week", 4, ifelse(bathdemand1[,5] == "five times a week", 5,ifelse(bathdemand1[,5] == "six times a week", 6,ifelse(bathdemand1[,5] == "seven times a week", 7, ifelse(bathdemand1[,5] == "more than seven times a week", 9 , ifelse(bathdemand1[,5] == "none", 0 ,NA)))))))))
# the ones that do not have baths were left out.
-single_occup_bath <- filter(bathdemand1, hhsize == 1)
-mean(single_occup_bath$bath_freq, na.rm = TRUE) # mean frequency of bathing is 1.87 times/week for one-person homes. In the EST sample, it is 1.7 (judging by the graph-Figure 8).
+single_occup_bath<-filter(bathdemand1, hhsize == 1)
+mean (single_occup_bath$bath_freq,na.rm=TRUE) # mean frequency of bathing is 1.87 times/week for one-person homes. In the EST sample, it is 1.7 (judging by the graph-Figure 8).
```
```
@@ -356,34 +358,31 @@ mean(single_occup_bath$bath_freq, na.rm = TRUE) # mean frequency of bathing is
```
```r
-# i want to assume frequencies by household-I only have for the respondent.
-bathdemand1 <- mutate(bathdemand1, housefreq = bath_freq * hhsize)
+#i want to assume frequencies by household-I only have for the respondent.
+bathdemand1<-mutate(bathdemand1, housefreq=bath_freq*hhsize)
-bathdemand_EST <- merge(x = bathdemand1, y = ESTdata_showerBath, by = "hhsize",
- all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (baths_freq_EST, baths_freq_EST).
+bathdemand_EST<-merge(x = bathdemand1, y = ESTdata_showerBath, by = "hhsize", all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (baths_freq_EST, baths_freq_EST).
-bathdemand_hh <- mutate(bathdemand_EST, monthlyBathUse = (1.87 * baths_freq_EST/1.7) *
- 4 * 80) #monthlyBathUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by bath (80 litres, (EST, 2013)).
+bathdemand_hh<-mutate(bathdemand_EST,monthlyBathUse= (1.87*baths_freq_EST/1.7)*4*80) #monthlyBathUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by bath (80 litres, (EST, 2013)).
-bathdemand_hh$monthlyBathUse <- ifelse(bathdemand_hh$baths == 0, 0, bathdemand_hh$monthlyBathUse)
-bathdemand_hh$dailyBathUse <- bathdemand_hh$monthlyBathUse/30 #'At home with water2' reports 51 l/hh/day for their sample for baths. Our mean is 35.5 l/hh/d. Reasonable but lower than theirs (zero consumption was included in the calculation of mean)
+bathdemand_hh$monthlyBathUse <- ifelse (bathdemand_hh$baths==0, 0, bathdemand_hh$monthlyBathUse)
+bathdemand_hh$dailyBathUse<-bathdemand_hh$monthlyBathUse/30 #'At home with water2' reports 51 l/hh/day for their sample for baths. Our mean is 35.5 l/hh/d. Reasonable but lower than theirs (zero consumption was included in the calculation of mean)
-# households that had no baths in their bathrooms, were assumed as not
-# taking any baths
-summary(bathdemand_hh)
+# households that had no baths in their bathrooms, were assumed as not taking any baths
+summary(bathdemand_hh)
```
```
-## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
+## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+##
## bath_freq baths housefreq baths_freq_EST
## Min. :0.000 Min. :0.0000 Min. : 0.000 Min. :1.700
## 1st Qu.:0.000 1st Qu.:1.0000 1st Qu.: 0.000 1st Qu.:2.250
@@ -403,45 +402,42 @@ summary(bathdemand_hh)
```
```r
-kable(caption = "Summary of bath demand", bathdemand_hh[1:5, ])
+kable(caption = "Summary of bath demand",
+ bathdemand_hh [1:5,]
+)
```
Table: Summary of bath demand
- hhsize obs id meter bath_freq baths housefreq baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse
-------- ----- ---------- ------ ---------- ------ ---------- --------------- ----------------- --------------- -------------
- 1 1470 836911007 no 0 0 0 1.7 5.2 0.0 0.00000
- 1 185 836900601 yes 0 1 0 1.7 5.2 598.4 19.94667
- 1 240 836910831 yes 0 1 0 1.7 5.2 598.4 19.94667
- 1 362 836921073 no 0 0 0 1.7 5.2 0.0 0.00000
- 1 406 836921608 no 0 1 0 1.7 5.2 598.4 19.94667
+| hhsize| obs| id|meter | bath_freq| baths| housefreq| baths_freq_EST| showers_freq_EST| monthlyBathUse| dailyBathUse|
+|------:|----:|---------:|:-----|---------:|-----:|---------:|--------------:|----------------:|--------------:|------------:|
+| 1| 1470| 836911007|no | 0| 0| 0| 1.7| 5.2| 0.0| 0.00000|
+| 1| 185| 836900601|yes | 0| 1| 0| 1.7| 5.2| 598.4| 19.94667|
+| 1| 240| 836910831|yes | 0| 1| 0| 1.7| 5.2| 598.4| 19.94667|
+| 1| 362| 836921073|no | 0| 0| 0| 1.7| 5.2| 0.0| 0.00000|
+| 1| 406| 836921608|no | 0| 1| 0| 1.7| 5.2| 598.4| 19.94667|
Plot of bath demand per household size
```r
-ggplot(data = bathdemand_hh) + aes(y = monthlyBathUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total bath use (l/house/day)")
+ggplot(data=bathdemand_hh)+ aes(y = monthlyBathUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total bath use (l/house/day)")
```
<!-- -->
```r
-ggplot(bathdemand_hh[bathdemand_hh$meter == "yes" | bathdemand_hh$meter == "no",
- ], aes(factor(hhsize), monthlyBathUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "bath demand (l/household/month)") + xlab("household size") +
- ylab("bath demand (l/hh/month)")
+ggplot(bathdemand_hh[bathdemand_hh$meter == "yes"|bathdemand_hh$meter == "no",], aes(factor(hhsize), monthlyBathUse)) + geom_boxplot(aes(fill = meter))+labs(title = "bath demand (l/household/month)")+ xlab('household size')+ylab('bath demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(bathdemand_hh[bathdemand_hh$meter == "yes" | bathdemand_hh$meter == "no",
- ], aes(factor(hhsize), dailyBathUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "bath demand (l/household/day)") + xlab("household size") +
- ylab("bath demand (l/hh/day)")
+ggplot(bathdemand_hh[bathdemand_hh$meter == "yes"|bathdemand_hh$meter == "no",], aes(factor(hhsize), dailyBathUse)) + geom_boxplot(aes(fill = meter))+labs(title = "bath demand (l/household/day)")+ xlab('household size')+ylab('bath demand (l/hh/day)')
```
<!-- -->
@@ -450,137 +446,120 @@ ggplot(bathdemand_hh[bathdemand_hh$meter == "yes" | bathdemand_hh$meter == "no",
## Dishwasher demand
```r
-DishDemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_13, q44b)
-DishDemand <- rename(DishDemand, obs = iobs, id = bmg_id, hhsize = q2, dishwashers = q7a_13,
- dish_freq = q44b, meter = q4)
+DishDemand<-select(Surveydata, iobs,bmg_id, q2,q4, q7a_13, q44b)
+DishDemand<-rename(DishDemand, obs =iobs, id=bmg_id, hhsize=q2,dishwashers=q7a_13, dish_freq=q44b, meter=q4 )
summary(DishDemand)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
-## dishwashers dish_freq
-## Min. :0.0000 :1039
-## 1st Qu.:0.0000 once a day : 216
-## Median :0.0000 every couple of days : 195
-## Mean :0.4233 when the dishwasher/sink is full: 167
-## 3rd Qu.:1.0000 never : 62
-## Max. :2.0000 other : 40
-## (Other) : 81
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+## dishwashers dish_freq
+## Min. :0.0000 Length:1800
+## 1st Qu.:0.0000 Class :character
+## Median :0.0000 Mode :character
+## Mean :0.4233
+## 3rd Qu.:1.0000
+## Max. :2.0000
```
```r
-# 762 h/hs have dishwashers. 167 people use it when it is full (unknown
-# frequency), 62 never use it, and 40 have stated 'other', while 32 use it
-# after every meal (3 times per day?). So only 412 h/hs use it once a day or
-# every couple of days. So no really useful frequencies of use result from
-# the survey. I have used EST's frequencies by household
-# size.(http://www.energysavingtrust.org.uk/sites/default/files/reports/AtHomewithWater(7).pdf
-# Figure 18)
+# 762 h/hs have dishwashers. 167 people use it when it is full (unknown frequency), 62 never use it, and 40 have stated 'other', while 32 use it after every meal (3 times per day?). So only 412 h/hs use it once a day or every couple of days. So no really useful frequencies of use result from the survey. I have used EST's frequencies by household size.(http://www.energysavingtrust.org.uk/sites/default/files/reports/AtHomewithWater(7).pdf Figure 18)
-kable(caption = "Summary of EST data for dishwashers frequency of use", ESTdata_dish[1:5,
- ])
+kable(caption = "Summary of EST data for dishwashers frequency of use",
+ ESTdata_dish [1:5,]
+)
```
Table: Summary of EST data for dishwashers frequency of use
- hhsize weeklyDish_freq
-------- ----------------
- 1 0.9
- 2 2.3
- 3 3.1
- 4 4.3
- 5 4.8
+| hhsize| weeklyDish_freq|
+|------:|---------------:|
+| 1| 0.9|
+| 2| 2.3|
+| 3| 3.1|
+| 4| 4.3|
+| 5| 4.8|
```r
-dishdemand_EST <- merge(x = DishDemand, y = ESTdata_dish, by = "hhsize", all.x = TRUE) # a column was added to the dataframe for dishwasher use frequency by household size, according to the EST data (ESTdata_dish).
+dishdemand_EST<-merge(x = DishDemand, y = ESTdata_dish, by = "hhsize", all.x = TRUE) # a column was added to the dataframe for dishwasher use frequency by household size, according to the EST data (ESTdata_dish).
-monthlyDishwasherUse <- mutate(dishdemand_EST, monthlyDishwasherUse = weeklyDish_freq *
- 4 * 14) # Monthly litres per household consumed by dishwashers (14litres/cycle)
-monthlyDishwasherUse$monthlyDishwasherUse <- ifelse(monthlyDishwasherUse$dishwashers ==
- 0, 0, monthlyDishwasherUse$monthlyDishwasherUse) # calculated only for households with dishwashers
+monthlyDishwasherUse<-mutate(dishdemand_EST,monthlyDishwasherUse= weeklyDish_freq*4*14) # Monthly litres per household consumed by dishwashers (14litres/cycle)
+monthlyDishwasherUse$monthlyDishwasherUse <- ifelse(monthlyDishwasherUse$dishwashers==0, 0,monthlyDishwasherUse$monthlyDishwasherUse) # calculated only for households with dishwashers
monthlyDishwasherUse$dailyDishwasherUse <- monthlyDishwasherUse$monthlyDishwasherUse/30
-summary(monthlyDishwasherUse) #'At home with water2' reports 10 l/hh/day for their sample for taps. Our mean is 2.4 l/hh/d. Reasonable but much lower than theirs. This is probably because zero values are included in the mean calculation).
-```
-
-```
-## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
-## dishwashers dish_freq weeklyDish_freq
-## Min. :0.0000 :1039 Min. :0.900
-## 1st Qu.:0.0000 once a day : 216 1st Qu.:2.300
-## Median :0.0000 every couple of days : 195 Median :2.300
-## Mean :0.4233 when the dishwasher/sink is full: 167 Mean :2.737
-## 3rd Qu.:1.0000 never : 62 3rd Qu.:4.300
-## Max. :2.0000 other : 40 Max. :4.800
-## (Other) : 81
-## monthlyDishwasherUse dailyDishwasherUse
-## Min. : 0.00 Min. :0.000
-## 1st Qu.: 0.00 1st Qu.:0.000
-## Median : 0.00 Median :0.000
-## Mean : 71.18 Mean :2.373
-## 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :268.80 Max. :8.960
-##
+summary(monthlyDishwasherUse)#'At home with water2' reports 10 l/hh/day for their sample for taps. Our mean is 2.4 l/hh/d. Reasonable but much lower than theirs. This is probably because zero values are included in the mean calculation).
+```
+
+```
+## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+## dishwashers dish_freq weeklyDish_freq monthlyDishwasherUse
+## Min. :0.0000 Length:1800 Min. :0.900 Min. : 0.00
+## 1st Qu.:0.0000 Class :character 1st Qu.:2.300 1st Qu.: 0.00
+## Median :0.0000 Mode :character Median :2.300 Median : 0.00
+## Mean :0.4233 Mean :2.737 Mean : 71.18
+## 3rd Qu.:1.0000 3rd Qu.:4.300 3rd Qu.:128.80
+## Max. :2.0000 Max. :4.800 Max. :268.80
+## dailyDishwasherUse
+## Min. :0.000
+## 1st Qu.:0.000
+## Median :0.000
+## Mean :2.373
+## 3rd Qu.:4.293
+## Max. :8.960
```
```r
-kable(caption = "Summary of demand for dishwashers", monthlyDishwasherUse[1:5,
- ])
+kable(caption = "Summary of demand for dishwashers",
+ monthlyDishwasherUse [1:5,]
+)
```
Table: Summary of demand for dishwashers
- hhsize obs id meter dishwashers dish_freq weeklyDish_freq monthlyDishwasherUse dailyDishwasherUse
-------- ----- ---------- ------ ------------ ----------- ---------------- --------------------- -------------------
- 1 1470 836911007 no 0 0.9 0.0 0.00
- 1 185 836900601 yes 0 0.9 0.0 0.00
- 1 240 836910831 yes 1 once a day 0.9 50.4 1.68
- 1 362 836921073 no 1 once a day 0.9 50.4 1.68
- 1 406 836921608 no 0 0.9 0.0 0.00
+| hhsize| obs| id|meter | dishwashers|dish_freq | weeklyDish_freq| monthlyDishwasherUse| dailyDishwasherUse|
+|------:|----:|---------:|:-----|-----------:|:----------|---------------:|--------------------:|------------------:|
+| 1| 1470| 836911007|no | 0| | 0.9| 0.0| 0.00|
+| 1| 185| 836900601|yes | 0| | 0.9| 0.0| 0.00|
+| 1| 240| 836910831|yes | 1|once a day | 0.9| 50.4| 1.68|
+| 1| 362| 836921073|no | 1|once a day | 0.9| 50.4| 1.68|
+| 1| 406| 836921608|no | 0| | 0.9| 0.0| 0.00|
Plot of dishwashers' demand per household size
```r
-ggplot(data = monthlyDishwasherUse) + aes(y = monthlyDishwasherUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total dishwashing use (l/house/month)")
+ggplot(data=monthlyDishwasherUse)+ aes(y = monthlyDishwasherUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total dishwashing use (l/house/month)")
```
<!-- -->
```r
-ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes" | monthlyDishwasherUse$meter ==
- "no", ], aes(factor(hhsize), monthlyDishwasherUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "dishwasher demand (l/household/month)") + xlab("household size") +
- ylab("dishwasher demand (l/hh/month)")
+ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes"|monthlyDishwasherUse$meter == "no",], aes(factor(hhsize), monthlyDishwasherUse)) + geom_boxplot(aes(fill = meter))+labs(title = "dishwasher demand (l/household/month)")+ xlab('household size')+ylab('dishwasher demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes" | monthlyDishwasherUse$meter ==
- "no", ], aes(factor(hhsize), dailyDishwasherUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "dishwasher demand (l/household/day)") + xlab("household size") +
- ylab("dishwasher demand (l/hh/day)")
+ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes"|monthlyDishwasherUse$meter == "no",], aes(factor(hhsize), dailyDishwasherUse)) + geom_boxplot(aes(fill = meter))+labs(title = "dishwasher demand (l/household/day)")+ xlab('household size')+ylab('dishwasher demand (l/hh/day)')
```
<!-- -->
@@ -589,26 +568,23 @@ ggplot(monthlyDishwasherUse[monthlyDishwasherUse$meter == "yes" | monthlyDishwas
## Kitchen sink use
```r
-# water for cooking and drinking accounts for 2gal per capita/per day=7.57
-# litres per capita per
-# day.http://www.freedrinkingwater.com/water_quality/common-daily-water-usage.htm
+#water for cooking and drinking accounts for 2gal per capita/per day=7.57 litres per capita per day.http://www.freedrinkingwater.com/water_quality/common-daily-water-usage.htm
-kitchen_sink <- select(Surveydata, iobs, bmg_id, q2, q4)
-kitchen_sink <- rename(kitchen_sink, obs = iobs, id = bmg_id, hhsize = q2, meter = q4)
-kitchen_sink_hh <- mutate(kitchen_sink, monthlyKitchenSinkUse = hhsize * 7.57 *
- 30)
-kitchen_sink_hh <- mutate(kitchen_sink_hh, dailyKitchenSinkUse = monthlyKitchenSinkUse/30)
+kitchen_sink<-select(Surveydata, iobs,bmg_id, q2, q4)
+kitchen_sink<-rename(kitchen_sink, obs =iobs, id=bmg_id, hhsize=q2, meter=q4)
+kitchen_sink_hh<-mutate(kitchen_sink,monthlyKitchenSinkUse = hhsize*7.57*30)
+kitchen_sink_hh<-mutate(kitchen_sink_hh,dailyKitchenSinkUse = monthlyKitchenSinkUse/30)
summary(kitchen_sink_hh)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
## monthlyKitchenSinkUse dailyKitchenSinkUse
## Min. : 227.1 Min. : 7.57
## 1st Qu.: 454.2 1st Qu.:15.14
@@ -619,44 +595,40 @@ summary(kitchen_sink_hh)
```
```r
-kable(caption = "Summary of demand for kitchen sink uses", kitchen_sink_hh[1:5,
- ])
+kable(caption = "Summary of demand for kitchen sink uses",
+ kitchen_sink_hh [1:5,]
+)
```
Table: Summary of demand for kitchen sink uses
- obs id hhsize meter monthlyKitchenSinkUse dailyKitchenSinkUse
----- ---------- ------- ----------- ---------------------- --------------------
- 2 836900048 2 yes 454.2 15.14
- 3 836900071 2 don't know 454.2 15.14
- 4 836900073 4 yes 908.4 30.28
- 5 836900106 1 yes 227.1 7.57
- 6 836900117 4 yes 908.4 30.28
+| obs| id| hhsize|meter | monthlyKitchenSinkUse| dailyKitchenSinkUse|
+|---:|---------:|------:|:----------|---------------------:|-------------------:|
+| 2| 836900048| 2|yes | 454.2| 15.14|
+| 3| 836900071| 2|don't know | 454.2| 15.14|
+| 4| 836900073| 4|yes | 908.4| 30.28|
+| 5| 836900106| 1|yes | 227.1| 7.57|
+| 6| 836900117| 4|yes | 908.4| 30.28|
### Plot of kitchen sink demand per household size
```r
-ggplot(data = kitchen_sink_hh) + aes(y = monthlyKitchenSinkUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total kitchen sink use (l/house/month)")
+ggplot(data=kitchen_sink_hh)+ aes(y = monthlyKitchenSinkUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total kitchen sink use (l/house/month)")
```
<!-- -->
```r
-ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes" | kitchen_sink_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyKitchenSinkUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "kitchen sink demand (l/household/month)") + xlab("household size") +
- ylab("kitchen sink demand (l/hh/month)")
+ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes"|kitchen_sink_hh$meter == "no",], aes(factor(hhsize), monthlyKitchenSinkUse)) + geom_boxplot(aes(fill = meter))+labs(title = "kitchen sink demand (l/household/month)")+ xlab('household size')+ylab('kitchen sink demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes" | kitchen_sink_hh$meter ==
- "no", ], aes(factor(hhsize), dailyKitchenSinkUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "kitchen sink demand (l/household/day)") + xlab("household size") +
- ylab("kitchen sink demand (l/hh/day)")
+ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes"|kitchen_sink_hh$meter == "no",], aes(factor(hhsize), dailyKitchenSinkUse)) + geom_boxplot(aes(fill = meter))+labs(title = "kitchen sink demand (l/household/day)")+ xlab('household size')+ylab('kitchen sink demand (l/hh/day)')
```
<!-- -->
@@ -670,21 +642,12 @@ ggplot(kitchen_sink_hh[kitchen_sink_hh$meter == "yes" | kitchen_sink_hh$meter ==
```r
-showerdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q29_2, q7a_3, q7a_4)
-showerdemand1 <- rename(showerdemand, obs = iobs, id = bmg_id, hhsize = q2,
- meter = q4, showers = q7a_3, powershowers = q7a_4, shower_freq = q29_2)
-showerdemand1[, 5] <- ifelse(showerdemand1[, 5] == "once a week", 1, ifelse(showerdemand1[,
- 5] == "twice a week", 2, ifelse(showerdemand1[, 5] == "three times a week",
- 3, ifelse(showerdemand1[, 5] == "four times a week", 4, ifelse(showerdemand1[,
- 5] == "five times a week", 5, ifelse(showerdemand1[, 5] == "six times a week",
- 6, ifelse(showerdemand1[, 5] == "seven times a week", 7, ifelse(showerdemand1[,
- 5] == "more than seven times a week", 9, ifelse(showerdemand1[,
- 5] == "none", 0, NA)))))))))
+showerdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q29_2, q7a_3,q7a_4 )
+showerdemand1<-rename(showerdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, showers=q7a_3, powershowers=q7a_4, shower_freq=q29_2)
+showerdemand1[,5] <- ifelse(showerdemand1[,5] == "once a week", 1 ,ifelse(showerdemand1[,5] == "twice a week", 2, ifelse(showerdemand1[,5] == "three times a week", 3 ,ifelse(showerdemand1[,5] == "four times a week", 4, ifelse(showerdemand1[,5] == "five times a week", 5,ifelse(showerdemand1[,5] == "six times a week", 6,ifelse(showerdemand1[,5] == "seven times a week", 7, ifelse(showerdemand1[,5] == "more than seven times a week", 9,ifelse(showerdemand1[,5] == "none", 0, NA)))))))))
-# someone can take a shower in the bath as well, so the households that have
-# reported that they do not have showers in the house, are also included
-# (many of them have reported showering frequencies).
-summary(showerdemand1[, 5]) #53 NA's
+#someone can take a shower in the bath as well, so the households that have reported that they do not have showers in the house, are also included (many of them have reported showering frequencies).
+summary(showerdemand1[,5]) #53 NA's
```
```
@@ -693,22 +656,18 @@ summary(showerdemand1[, 5]) #53 NA's
```
```r
-# total number of showers in the house
-showerdemand1 <- mutate(showerdemand1, numberofShowers_hh = showers + powershowers)
-# coeff for normal showers
-showerdemand1 <- mutate(showerdemand1, normalShowerCoeff = showers/(showers +
- powershowers))
-# coeff for power showers
-showerdemand1 <- mutate(showerdemand1, powerShowerCoeff = powershowers/(showers +
- powershowers))
+#total number of showers in the house
+showerdemand1<-mutate(showerdemand1,numberofShowers_hh=showers+powershowers)
+#coeff for normal showers
+showerdemand1<-mutate(showerdemand1,normalShowerCoeff=showers/(showers+powershowers))
+#coeff for power showers
+showerdemand1<-mutate(showerdemand1,powerShowerCoeff=powershowers/(showers+powershowers))
-showerdemand1$normalShowerCoeff <- ifelse(is.na(showerdemand1$normalShowerCoeff),
- 0, showerdemand1$normalShowerCoeff)
-showerdemand1$powerShowerCoeff <- ifelse(is.na(showerdemand1$powerShowerCoeff),
- 0, showerdemand1$powerShowerCoeff)
+showerdemand1$normalShowerCoeff <- ifelse (is.na (showerdemand1$normalShowerCoeff) , 0 ,showerdemand1$normalShowerCoeff )
+showerdemand1$powerShowerCoeff <- ifelse (is.na (showerdemand1$powerShowerCoeff) , 0 ,showerdemand1$powerShowerCoeff )
-single_occup_sh <- filter(showerdemand1, hhsize == 1)
-mean(single_occup_sh$shower_freq, na.rm = TRUE) # mean frequency of showering is 4.25 times/week for one-person homes. In the EST sample, it is 5.2 (judging by the graph-Figure 8).
+single_occup_sh<-filter(showerdemand1, hhsize == 1)
+mean (single_occup_sh$shower_freq,na.rm=TRUE) # mean frequency of showering is 4.25 times/week for one-person homes. In the EST sample, it is 5.2 (judging by the graph-Figure 8).
```
```
@@ -716,48 +675,38 @@ mean(single_occup_sh$shower_freq, na.rm = TRUE) # mean frequency of showering i
```
```r
-showerdemand_EST <- merge(x = showerdemand1, y = ESTdata_showerBath, by = "hhsize",
- all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (showers_freq_EST, baths_freq_EST).
+showerdemand_EST<-merge(x = showerdemand1, y = ESTdata_showerBath, by = "hhsize", all.x = TRUE) # two columns were added to the dataframe. one for shower frequency and one for bathing frequency, according to the EST data (showers_freq_EST, baths_freq_EST).
-# I want to take both the reported showering frequencies and the EST
-# frequencies into account. First I calculate showers per person for the EST
-# DATA
-showerdemand_EST <- mutate(showerdemand_EST, EST_freq_perperson = showers_freq_EST/hhsize)
+#I want to take both the reported showering frequencies and the EST frequencies into account. First I calculate showers per person for the EST DATA
+showerdemand_EST<-mutate(showerdemand_EST,EST_freq_perperson=showers_freq_EST/hhsize)
-# final frequencies are calculated as a mean value from EST data and the
-# reported freqs
+#final frequencies are calculated as a mean value from EST data and the reported freqs
-showerdemand_EST <- mutate(showerdemand_EST, final_freq_perperson = (EST_freq_perperson +
- shower_freq)/2)
+showerdemand_EST<-mutate(showerdemand_EST,final_freq_perperson=(EST_freq_perperson+shower_freq)/2)
# frequency of showering by hh size:
-showerdemand_EST <- mutate(showerdemand_EST, final_freq_hh = final_freq_perperson *
- hhsize)
+showerdemand_EST<-mutate(showerdemand_EST,final_freq_hh=final_freq_perperson*hhsize)
-# the average 7,5-minute normal shower uses 60 litres of water while a power
-# shower uses 97,5 litres in 7,5 minutes. (EST-AT HOME WITH WATER)
-showerdemand_hh <- mutate(showerdemand_EST, monthlyShowerUse = (60 * normalShowerCoeff +
- 97.5 * powerShowerCoeff) * 4 * final_freq_hh)
+#the average 7,5-minute normal shower uses 60 litres of water while a power shower uses 97,5 litres in 7,5 minutes. (EST-AT HOME WITH WATER)
+showerdemand_hh<-mutate(showerdemand_EST,monthlyShowerUse=(60*normalShowerCoeff+97.5*powerShowerCoeff)*4*final_freq_hh)
-# monthlyShowerUse is the frequency of showering for each household size,
-# multiplied by 4 weeks in a month and by the mean consumption by shower
-# type.
+#monthlyShowerUse is the frequency of showering for each household size, multiplied by 4 weeks in a month and by the mean consumption by shower type.
-showerdemand_hh <- mutate(showerdemand_hh, dailyShowerUse = monthlyShowerUse/30) #'At home with water2' reports 86 l/hh/day for their sample for showers. Our mean is 107 l/hh/d. Our results make sense.
+showerdemand_hh<-mutate(showerdemand_hh,dailyShowerUse=monthlyShowerUse/30)#'At home with water2' reports 86 l/hh/day for their sample for showers. Our mean is 107 l/hh/d. Our results make sense.
-showerdemand_hh <- showerdemand_hh[, -(5:15), drop = FALSE]
+showerdemand_hh<-showerdemand_hh[,-(5:15),drop=FALSE]
summary(showerdemand_hh)
```
```
-## hhsize obs id meter
-## Min. : 1.000 Min. : 2.0 Min. :836900048 don't know:167
-## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 no :864
-## Median : 2.000 Median : 905.5 Median :836920637 yes :769
-## Mean : 2.655 Mean : 906.0 Mean :836919052
-## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
-## Max. :10.000 Max. :1810.0 Max. :836965495
-##
+## hhsize obs id meter
+## Min. : 1.000 Min. : 2.0 Min. :836900048 Length:1800
+## 1st Qu.: 2.000 1st Qu.: 454.8 1st Qu.:836910532 Class :character
+## Median : 2.000 Median : 905.5 Median :836920637 Mode :character
+## Mean : 2.655 Mean : 906.0 Mean :836919052
+## 3rd Qu.: 4.000 3rd Qu.:1356.2 3rd Qu.:836922574
+## Max. :10.000 Max. :1810.0 Max. :836965495
+##
## monthlyShowerUse dailyShowerUse
## Min. : 0 Min. : 0.0
## 1st Qu.: 1464 1st Qu.: 48.8
@@ -769,44 +718,41 @@ summary(showerdemand_hh)
```
```r
-kable(caption = "Summary of shower demand", showerdemand_hh[1:5, ])
+kable(caption = "Summary of shower demand",
+ showerdemand_hh [1:5,]
+)
```
Table: Summary of shower demand
- hhsize obs id meter monthlyShowerUse dailyShowerUse
-------- ----- ---------- ------ ----------------- ---------------
- 1 1470 836911007 no 984 32.8
- 1 185 836900601 yes 1599 53.3
- 1 240 836910831 yes 1464 48.8
- 1 362 836921073 no 2379 79.3
- 1 406 836921608 no 0 0.0
+| hhsize| obs| id|meter | monthlyShowerUse| dailyShowerUse|
+|------:|----:|---------:|:-----|----------------:|--------------:|
+| 1| 1470| 836911007|no | 984| 32.8|
+| 1| 185| 836900601|yes | 1599| 53.3|
+| 1| 240| 836910831|yes | 1464| 48.8|
+| 1| 362| 836921073|no | 2379| 79.3|
+| 1| 406| 836921608|no | 0| 0.0|
Plot of shower demand per household size
```r
-ggplot(data = showerdemand_hh) + aes(y = dailyShowerUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total shower use (l/house/day)")
+ggplot(data=showerdemand_hh)+ aes(y = dailyShowerUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total shower use (l/house/day)")
```
<!-- -->
```r
-ggplot(showerdemand_hh[showerdemand_hh$meter == "yes" | showerdemand_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyShowerUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "shower demand (l/household/month)") + xlab("household size") +
- ylab("shower demand (l/hh/month)")
+ggplot(showerdemand_hh[showerdemand_hh$meter == "yes"|showerdemand_hh$meter == "no",], aes(factor(hhsize), monthlyShowerUse)) + geom_boxplot(aes(fill = meter))+labs(title = "shower demand (l/household/month)")+ xlab('household size')+ylab('shower demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(showerdemand_hh[showerdemand_hh$meter == "yes" | showerdemand_hh$meter ==
- "no", ], aes(factor(hhsize), dailyShowerUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "shower demand (l/household/day)") + xlab("household size") +
- ylab("shower demand (l/hh/day)")
+ggplot(showerdemand_hh[showerdemand_hh$meter == "yes"|showerdemand_hh$meter == "no",], aes(factor(hhsize), dailyShowerUse)) + geom_boxplot(aes(fill = meter))+labs(title = "shower demand (l/household/day)")+ xlab('household size')+ylab('shower demand (l/hh/day)')
```
<!-- -->
@@ -818,48 +764,35 @@ ggplot(showerdemand_hh[showerdemand_hh$meter == "yes" | showerdemand_hh$meter ==
```r
-## Surveydata <- data.table(read.csv(paste0(fpath,'/SPRGdata.csv')))
-Toiletdemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_6, q7a_7, q48)
-toiletdemand1 <- rename(Toiletdemand, obs = iobs, id = bmg_id, hhsize = q2,
- meter = q4, singleflush_wc = q7a_6, dualflush_wc = q7a_7, effective_flush = q48)
-toiletdemand2 <- mutate(toiletdemand1, flushvolume = (singleflush_wc * 7.5 +
- dualflush_wc * 5)/(singleflush_wc + dualflush_wc)) # litres used per flush
+## Surveydata <- data.table(read.csv(paste0(fpath,"/SPRGdata.csv")))
+Toiletdemand<-select(Surveydata, iobs,bmg_id, q2, q4,q7a_6,q7a_7, q48)
+toiletdemand1<-rename(Toiletdemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, singleflush_wc=q7a_6, dualflush_wc=q7a_7,effective_flush=q48)
+toiletdemand2<-mutate (toiletdemand1, flushvolume=(singleflush_wc*7.5 + dualflush_wc*5)/(singleflush_wc+dualflush_wc)) # litres used per flush
# 'At home with water (EST)'suggests a mean 5 flusheS per day per occupant
-# Ignoring economies of scale, toilet consumption in the household should
-# be: each occupant's demand * household size-the resulting consumption will
-# most probably be an overestimation!-This calculation can change.
-toiletdemand_hh <- mutate(toiletdemand2, monthlyWCUse = flushvolume * hhsize *
- 30 * 5)
-
-toiletdemand_hh <- mutate(toiletdemand_hh, dailyWCUse = monthlyWCUse/30) #'At home with water2' reports 74 l/hh/day for their sample for lavatories. Our mean is 91.3 l/hh/d. Our results make sense.
-summary(toiletdemand_hh)
-```
-
-```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
-## singleflush_wc dualflush_wc
-## Min. : 0.000 Min. :0.0000
-## 1st Qu.: 1.000 1st Qu.:0.0000
-## Median : 1.000 Median :0.0000
-## Mean : 1.169 Mean :0.4233
-## 3rd Qu.: 2.000 3rd Qu.:1.0000
-## Max. :97.000 Max. :5.0000
-##
-## effective_flush flushvolume
-## always empties the bowl with one flush :1491 Min. :5.000
-## usually empties the bowl with one flush : 210 1st Qu.:6.250
-## refused : 45 Median :7.500
-## empties about half the time with one flush: 32 Mean :6.918
-## usually needs more than one flush : 16 3rd Qu.:7.500
-## don't know : 3 Max. :7.500
-## (Other) : 3 NA's :59
+# Ignoring economies of scale, toilet consumption in the household should be: each occupant's demand * household size-the resulting consumption will most probably be an overestimation!-This calculation can change.
+toiletdemand_hh<-mutate (toiletdemand2, monthlyWCUse=flushvolume*hhsize*30*5)
+
+toiletdemand_hh<-mutate (toiletdemand_hh, dailyWCUse=monthlyWCUse/30) #'At home with water2' reports 74 l/hh/day for their sample for lavatories. Our mean is 91.3 l/hh/d. Our results make sense.
+summary (toiletdemand_hh)
+```
+
+```
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
+## singleflush_wc dualflush_wc effective_flush flushvolume
+## Min. : 0.000 Min. :0.0000 Length:1800 Min. :5.000
+## 1st Qu.: 1.000 1st Qu.:0.0000 Class :character 1st Qu.:6.250
+## Median : 1.000 Median :0.0000 Mode :character Median :7.500
+## Mean : 1.169 Mean :0.4233 Mean :6.918
+## 3rd Qu.: 2.000 3rd Qu.:1.0000 3rd Qu.:7.500
+## Max. :97.000 Max. :5.0000 Max. :7.500
+## NA's :59
## monthlyWCUse dailyWCUse
## Min. : 750 Min. : 25.00
## 1st Qu.:1500 1st Qu.: 50.00
@@ -871,7 +804,7 @@ summary(toiletdemand_hh)
```
```r
-sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm = TRUE)
+sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm=TRUE)
```
```
@@ -880,44 +813,43 @@ sapply(split(toiletdemand_hh$monthlyWCUse, toiletdemand_hh$hhsize), mean, na.rm
```
```r
-toiletdemand_hh <- toiletdemand_hh[, -(5:8), drop = FALSE]
+toiletdemand_hh<-toiletdemand_hh[,-(5:8),drop=FALSE]
-kable(caption = "Summary of toilet demand table", toiletdemand_hh[1:5, ])
+kable(caption = "Summary of toilet demand table",
+ toiletdemand_hh [1:5,]
+)
```
Table: Summary of toilet demand table
- obs id hhsize meter monthlyWCUse dailyWCUse
----- ---------- ------- ----------- ------------- -----------
- 2 836900048 2 yes 2250 75.0000
- 3 836900071 2 don't know 1500 50.0000
- 4 836900073 4 yes 3500 116.6667
- 5 836900106 1 yes 750 25.0000
- 6 836900117 4 yes 4500 150.0000
+| obs| id| hhsize|meter | monthlyWCUse| dailyWCUse|
+|---:|---------:|------:|:----------|------------:|----------:|
+| 2| 836900048| 2|yes | 2250| 75.0000|
+| 3| 836900071| 2|don't know | 1500| 50.0000|
+| 4| 836900073| 4|yes | 3500| 116.6667|
+| 5| 836900106| 1|yes | 750| 25.0000|
+| 6| 836900117| 4|yes | 4500| 150.0000|
Plot of toilet demand per household size for metered and unmetered hhs
```r
-ggplot(data = toiletdemand_hh) + aes(y = dailyWCUse, x = factor(hhsize)) + geom_boxplot() +
- labs(title = "WC use (l/household/day)") + xlab("household size") + ylab("WC demand (l/hh/day)")
+ggplot(data=toiletdemand_hh)+ aes(y = dailyWCUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "WC use (l/household/day)")+ xlab('household size')+ylab('WC demand (l/hh/day)')
```
<!-- -->
```r
-ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes" | toiletdemand_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyWCUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "WC use (l/household/month)") + xlab("household size") + ylab("WC demand (l/hh/month)")
+ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes"|toiletdemand_hh$meter == "no",], aes(factor(hhsize), monthlyWCUse)) + geom_boxplot(aes(fill = meter))+labs(title = "WC use (l/household/month)")+ xlab('household size')+ylab('WC demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes" | toiletdemand_hh$meter ==
- "no", ], aes(factor(hhsize), dailyWCUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "WC use (l/household/day)") + xlab("household size") + ylab("WC demand (l/hh/day)")
+ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes"|toiletdemand_hh$meter == "no",], aes(factor(hhsize), dailyWCUse)) + geom_boxplot(aes(fill = meter))+labs(title = "WC use (l/household/day)")+ xlab('household size')+ylab('WC demand (l/hh/day)')
```
<!-- -->
@@ -927,29 +859,18 @@ ggplot(toiletdemand_hh[toiletdemand_hh$meter == "yes" | toiletdemand_hh$meter ==
```r
-washingmachinedemand <- select(Surveydata, iobs, bmg_id, q2, q4, q7a_11, q20,
- q21)
-washingmachinedemand1 <- rename(washingmachinedemand, obs = iobs, id = bmg_id,
- hhsize = q2, meter = q4, weeklyloads = q20, combinedwash = q21, washingmachine = q7a_11)
+washingmachinedemand<-select(Surveydata, iobs,bmg_id, q2, q4,q7a_11, q20,q21)
+washingmachinedemand1<-rename(washingmachinedemand, obs =iobs, id=bmg_id, hhsize=q2, meter=q4, weeklyloads=q20, combinedwash=q21, washingmachine=q7a_11)
# I only kept h/hs that have washing machines at home (1704 homes)
-washingmachinedemand1$washingmachine <- ifelse(washingmachinedemand1$washingmachine ==
- "1", 1, ifelse(washingmachinedemand1$washingmachine == "2", 2, 0))
+washingmachinedemand1$washingmachine<-ifelse(washingmachinedemand1$washingmachine == "1",1,ifelse(washingmachinedemand1$washingmachine == "2", 2, 0))
-# 0 for the houses without a machine. the rest assumed to combine washes
-washingmachinedemand1$combinedwash <- ifelse(washingmachinedemand1$combinedwash ==
- "the washing is combined and done for the whole household", 1, ifelse(is.null(washingmachinedemand1$combinedwash) |
- washingmachinedemand1$washingmachine == 1, 1, ifelse(is.null(washingmachinedemand1$combinedwash) |
- washingmachinedemand1$washingmachine == 2, 1, NA)))
+ # 0 for the houses without a machine. the rest assumed to combine washes
+washingmachinedemand1$combinedwash<-ifelse(washingmachinedemand1$combinedwash == "the washing is combined and done for the whole household",1, ifelse(is.null (washingmachinedemand1$combinedwash) | washingmachinedemand1$washingmachine==1,1,ifelse(is.null (washingmachinedemand1$combinedwash) | washingmachinedemand1$washingmachine==2,1, NA)))
-washingmachinedemand1[, 6] <- ifelse(washingmachinedemand1[, 6] == "less than one load a week",
- 0.5, ifelse(washingmachinedemand1[, 6] == "about 1 load", 1, ifelse(washingmachinedemand1[,
- 6] == "2-3 loads", 2.5, ifelse(washingmachinedemand1[, 6] == "4-5 loads",
- 4.5, ifelse(washingmachinedemand1[, 6] == "6-10 loads", 8, ifelse(washingmachinedemand1[,
- 6] == "more than 10 loads", 12, ifelse(washingmachinedemand1[, 6] ==
- "don't know", NA, 0)))))))
+washingmachinedemand1[,6] <- ifelse(washingmachinedemand1[,6] == "less than one load a week", 0.5,ifelse(washingmachinedemand1[,6] == "about 1 load", 1, ifelse(washingmachinedemand1[,6] == "2-3 loads", 2.5,ifelse(washingmachinedemand1[,6] == "4-5 loads", 4.5, ifelse(washingmachinedemand1[,6] == "6-10 loads", 8,ifelse(washingmachinedemand1[,6] == "more than 10 loads", 12,ifelse(washingmachinedemand1[,6] == "don't know" , NA, 0)))))))
-summary(washingmachinedemand1[, 6]) #145 NA's
+summary (washingmachinedemand1[,6]) #145 NA's
```
```
@@ -958,22 +879,21 @@ summary(washingmachinedemand1[, 6]) #145 NA's
```
```r
-washingmachine_hh <- mutate(washingmachinedemand1, monthlyWashingMachineUse = weeklyloads *
- 4 * 50) # according to 'At home with water (EST)', an average cycle consumes 50 litres of water.
-washingmachine_hh <- mutate(washingmachine_hh, dailyWashingMachineUse = monthlyWashingMachineUse/30) #'At home with water2' reports 33 l/hh/day for their sample for washing machines. Our mean is 25. Our results make sense.
+washingmachine_hh<-mutate(washingmachinedemand1,monthlyWashingMachineUse= weeklyloads*4*50) # according to 'At home with water (EST)', an average cycle consumes 50 litres of water.
+washingmachine_hh<-mutate(washingmachine_hh,dailyWashingMachineUse=monthlyWashingMachineUse/30) #'At home with water2' reports 33 l/hh/day for their sample for washing machines. Our mean is 25. Our results make sense.
-summary(washingmachine_hh)
+summary (washingmachine_hh)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## washingmachine weeklyloads combinedwash monthlyWashingMachineUse
## Min. :0.0000 Min. : 0.000 Min. :1 Min. : 0.0
## 1st Qu.:1.0000 1st Qu.: 2.500 1st Qu.:1 1st Qu.: 500.0
@@ -993,47 +913,43 @@ summary(washingmachine_hh)
```
```r
-washingmachine_hh <- washingmachine_hh[, -(5:7), drop = FALSE]
+washingmachine_hh<-washingmachine_hh[,-(5:7),drop=FALSE]
-kable(caption = "Summary of washing machine demand data table", washingmachine_hh[1:5,
- ])
+kable(caption = "Summary of washing machine demand data table",
+ washingmachine_hh [1:5,]
+)
```
Table: Summary of washing machine demand data table
- obs id hhsize meter monthlyWashingMachineUse dailyWashingMachineUse
----- ---------- ------- ----------- ------------------------- -----------------------
- 2 836900048 2 yes 500 16.66667
- 3 836900071 2 don't know 500 16.66667
- 4 836900073 4 yes NA NA
- 5 836900106 1 yes 500 16.66667
- 6 836900117 4 yes 1600 53.33333
+| obs| id| hhsize|meter | monthlyWashingMachineUse| dailyWashingMachineUse|
+|---:|---------:|------:|:----------|------------------------:|----------------------:|
+| 2| 836900048| 2|yes | 500| 16.66667|
+| 3| 836900071| 2|don't know | 500| 16.66667|
+| 4| 836900073| 4|yes | NA| NA|
+| 5| 836900106| 1|yes | 500| 16.66667|
+| 6| 836900117| 4|yes | 1600| 53.33333|
Plot of washingmachine demand per household size for metered and unmetered hhs
```r
-ggplot(data = washingmachine_hh) + aes(y = dailyWashingMachineUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total washingmachine use (l/house/day)")
+ggplot(data=washingmachine_hh)+ aes(y = dailyWashingMachineUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total washingmachine use (l/house/day)")
```
<!-- -->
```r
-ggplot(washingmachine_hh[washingmachine_hh$meter == "yes" | washingmachine_hh$meter ==
- "no", ], aes(factor(hhsize), monthlyWashingMachineUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "washine machine use (l/household/month)") + xlab("household size") +
- ylab("washing machine demand (l/hh/month)")
+ggplot(washingmachine_hh[washingmachine_hh$meter == "yes"|washingmachine_hh$meter == "no",], aes(factor(hhsize), monthlyWashingMachineUse)) + geom_boxplot(aes(fill = meter))+labs(title = "washine machine use (l/household/month)")+ xlab('household size')+ylab('washing machine demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(washingmachine_hh[washingmachine_hh$meter == "yes" | washingmachine_hh$meter ==
- "no", ], aes(factor(hhsize), dailyWashingMachineUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "washine machine use (l/household/day)") + xlab("household size") +
- ylab("washing machine demand (l/hh/day)")
+ggplot(washingmachine_hh[washingmachine_hh$meter == "yes"|washingmachine_hh$meter == "no",], aes(factor(hhsize),dailyWashingMachineUse)) + geom_boxplot(aes(fill = meter))+labs(title = "washine machine use (l/household/day)")+ xlab('household size')+ylab('washing machine demand (l/hh/day)')
```
<!-- -->
@@ -1042,24 +958,16 @@ ggplot(washingmachine_hh[washingmachine_hh$meter == "yes" | washingmachine_hh$me
```r
-# total demand
-totalIntDemand_hh <- merge(x = bathdemand_hh, y = showerdemand_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = kitchen_sink_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = monthlyDishwasherUse,
- by = "id", all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = toiletdemand_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = washingmachine_hh, by = "id",
- all = TRUE)
-totalIntDemand_hh <- merge(x = totalIntDemand_hh, y = bathsink_hh, by = "id",
- all = TRUE)
+#total demand
+totalIntDemand_hh<-merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = kitchen_sink_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = monthlyDishwasherUse, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = toiletdemand_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = washingmachine_hh, by = "id", all = TRUE)
+totalIntDemand_hh<-merge(x = totalIntDemand_hh, y = bathsink_hh, by = "id", all = TRUE)
-totalIntDemand_hh <- subset(totalIntDemand_hh, select = c("id", "obs.y", "hhsize.x.x",
- "meter.x.x", "monthlyBathUse", "monthlyShowerUse", "monthlyDishwasherUse",
- "monthlyKitchenSinkUse", "monthlyWCUse", "monthlyWashingMachineUse", "monthlyBathroomSinkUse"))
+totalIntDemand_hh <- subset(totalIntDemand_hh, select=c("id","obs.y", "hhsize.x.x","meter.x.x","monthlyBathUse", "monthlyShowerUse","monthlyDishwasherUse", "monthlyKitchenSinkUse", "monthlyWCUse","monthlyWashingMachineUse", "monthlyBathroomSinkUse"))
str(totalIntDemand_hh)
```
@@ -1068,7 +976,7 @@ str(totalIntDemand_hh)
## $ id : int 836900048 836900071 836900073 836900106 836900117 836900123 836900127 836900128 836900131 836900132 ...
## $ obs.y : int 2 3 4 5 6 179 162 161 181 163 ...
## $ hhsize.x.x : int 2 2 4 1 4 5 5 4 2 6 ...
-## $ meter.x.x : Factor w/ 3 levels "don't know","no",..: 3 1 3 3 3 1 3 3 1 1 ...
+## $ meter.x.x : chr "yes" "don't know" "yes" "yes" ...
## $ monthlyBathUse : num 0 792 1707 0 1707 ...
## $ monthlyShowerUse : num NA NA 5118 2379 NA ...
## $ monthlyDishwasherUse : num 0 129 241 0 241 ...
@@ -1079,46 +987,45 @@ str(totalIntDemand_hh)
```
```r
-totalIntDemand_hh <- mutate(totalIntDemand_hh, totalMonthlyInHouseDemand = (monthlyBathUse +
- monthlyShowerUse + monthlyKitchenSinkUse + monthlyDishwasherUse + monthlyWCUse +
- monthlyWashingMachineUse + monthlyBathroomSinkUse))
+totalIntDemand_hh <- mutate(totalIntDemand_hh,totalMonthlyInHouseDemand = (monthlyBathUse + monthlyShowerUse + monthlyKitchenSinkUse + monthlyDishwasherUse +
+ monthlyWCUse + monthlyWashingMachineUse + monthlyBathroomSinkUse) )
summary(totalIntDemand_hh)
```
```
-## id obs.y hhsize.x.x meter.x.x
-## Min. :836900048 Min. : 2.0 Min. : 1.000 don't know:167
-## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 no :864
-## Median :836920637 Median : 905.5 Median : 2.000 yes :769
-## Mean :836919052 Mean : 906.0 Mean : 2.655
-## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
-## Max. :836965495 Max. :1810.0 Max. :10.000
-##
-## monthlyBathUse monthlyShowerUse monthlyDishwasherUse
-## Min. : 0.0 Min. : 0 Min. : 0.00
-## 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00
-## Median : 792.0 Median : 2808 Median : 0.00
-## Mean :1065.9 Mean : 3210 Mean : 71.18
-## 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80
-## Max. :2323.2 Max. :15415 Max. :268.80
-## NA's :53
-## monthlyKitchenSinkUse monthlyWCUse monthlyWashingMachineUse
-## Min. : 227.1 Min. : 750 Min. : 0.0
-## 1st Qu.: 454.2 1st Qu.:1500 1st Qu.: 500.0
-## Median : 454.2 Median :2250 Median : 500.0
-## Mean : 603.0 Mean :2739 Mean : 708.3
-## 3rd Qu.: 908.4 3rd Qu.:3375 3rd Qu.: 900.0
-## Max. :2271.0 Max. :7875 Max. :2400.0
-## NA's :59 NA's :47
-## monthlyBathroomSinkUse totalMonthlyInHouseDemand
-## Min. : 312.0 Min. : 1907
-## 1st Qu.: 794.4 1st Qu.: 6043
-## Median : 1191.6 Median : 9167
-## Mean : 1748.0 Mean :10140
-## 3rd Qu.: 1986.0 3rd Qu.:13821
-## Max. :13896.0 Max. :34171
-## NA's :53 NA's :186
+## id obs.y hhsize.x.x meter.x.x
+## Min. :836900048 Min. : 2.0 Min. : 1.000 Length:1800
+## 1st Qu.:836910532 1st Qu.: 454.8 1st Qu.: 2.000 Class :character
+## Median :836920637 Median : 905.5 Median : 2.000 Mode :character
+## Mean :836919052 Mean : 906.0 Mean : 2.655
+## 3rd Qu.:836922574 3rd Qu.:1356.2 3rd Qu.: 4.000
+## Max. :836965495 Max. :1810.0 Max. :10.000
+##
+## monthlyBathUse monthlyShowerUse monthlyDishwasherUse monthlyKitchenSinkUse
+## Min. : 0.0 Min. : 0 Min. : 0.00 Min. : 227.1
+## 1st Qu.: 598.4 1st Qu.: 1464 1st Qu.: 0.00 1st Qu.: 454.2
+## Median : 792.0 Median : 2808 Median : 0.00 Median : 454.2
+## Mean :1065.9 Mean : 3210 Mean : 71.18 Mean : 603.0
+## 3rd Qu.:1707.2 3rd Qu.: 4638 3rd Qu.:128.80 3rd Qu.: 908.4
+## Max. :2323.2 Max. :15415 Max. :268.80 Max. :2271.0
+## NA's :53
+## monthlyWCUse monthlyWashingMachineUse monthlyBathroomSinkUse
+## Min. : 750 Min. : 0.0 Min. : 312.0
+## 1st Qu.:1500 1st Qu.: 500.0 1st Qu.: 794.4
+## Median :2250 Median : 500.0 Median : 1191.6
+## Mean :2739 Mean : 708.3 Mean : 1748.0
+## 3rd Qu.:3375 3rd Qu.: 900.0 3rd Qu.: 1986.0
+## Max. :7875 Max. :2400.0 Max. :13896.0
+## NA's :59 NA's :47 NA's :53
+## totalMonthlyInHouseDemand
+## Min. : 1907
+## 1st Qu.: 6043
+## Median : 9167
+## Mean :10140
+## 3rd Qu.:13821
+## Max. :34171
+## NA's :186
```
# Estimate External Consumption
@@ -1137,15 +1044,11 @@ gardenNoMeter <- 0.08
```r
-monthlyGardenUse <- select(Surveydata, iobs, bmg_id, q2, q4, q10a)
-monthlyGardenUse <- rename(monthlyGardenUse, obs = iobs, id = bmg_id, hhsize = q2,
- noplantslawn = q10a, meter = q4)
-monthlyGardenUse$noplantslawn <- ifelse(monthlyGardenUse$noplantslawn == "yes",
- 0, 1) # the houses that do not have garden or lawn to water are modeled as '0'. Have not found garden use data by household size yet so I have used Thames Water's approximation. 10% of total h/h use and 8% of total h/h use for metered and unmetered homes respectively.
-monthlyGardenUse_hh <- merge(x = totalIntDemand_hh, y = monthlyGardenUse, by = "id",
- all = TRUE)
-monthlyGardenUse_hh <- subset(monthlyGardenUse_hh, select = c("id", "hhsize",
- "meter", "noplantslawn", "totalMonthlyInHouseDemand"))
+monthlyGardenUse<-select(Surveydata, iobs,bmg_id, q2, q4, q10a)
+monthlyGardenUse<-rename(monthlyGardenUse, obs =iobs, id=bmg_id, hhsize=q2,noplantslawn=q10a, meter=q4)
+monthlyGardenUse$noplantslawn <- ifelse(monthlyGardenUse$noplantslawn== "yes", 0, 1) # the houses that do not have garden or lawn to water are modeled as '0'. Have not found garden use data by household size yet so I have used Thames Water's approximation. 10% of total h/h use and 8% of total h/h use for metered and unmetered homes respectively.
+monthlyGardenUse_hh<-merge(x = totalIntDemand_hh, y = monthlyGardenUse, by = "id", all = TRUE)
+monthlyGardenUse_hh<-subset(monthlyGardenUse_hh, select=c("id", "hhsize","meter", "noplantslawn", "totalMonthlyInHouseDemand"))
str(monthlyGardenUse_hh)
```
@@ -1154,19 +1057,21 @@ str(monthlyGardenUse_hh)
## 'data.frame': 1800 obs. of 5 variables:
## $ id : int 836900048 836900071 836900073 836900106 836900117 836900123 836900127 836900128 836900131 836900132 ...
## $ hhsize : int 2 2 4 1 4 5 5 4 2 6 ...
-## $ meter : Factor w/ 3 levels "don't know","no",..: 3 1 3 3 3 1 3 3 1 1 ...
+## $ meter : chr "yes" "don't know" "yes" "yes" ...
## $ noplantslawn : num 1 1 1 1 1 0 1 0 0 0 ...
## $ totalMonthlyInHouseDemand: num NA NA NA 4253 NA ...
```
```r
-monthlyGardenUse_hh$monthlyGardenUse <- ifelse(monthlyGardenUse_hh$meter ==
- "yes", monthlyGardenUse_hh$totalMonthlyInHouseDemand * gardenMeter * monthlyGardenUse_hh$noplantslawn,
- ifelse(monthlyGardenUse_hh$meter == "no", monthlyGardenUse_hh$totalMonthlyInHouseDemand *
- gardenNoMeter * monthlyGardenUse_hh$noplantslawn, NA)) #a column with garden use was added
+monthlyGardenUse_hh$monthlyGardenUse <- ifelse(monthlyGardenUse_hh$meter == "yes",
+ monthlyGardenUse_hh$totalMonthlyInHouseDemand*gardenMeter*monthlyGardenUse_hh$noplantslawn,
+ ifelse (monthlyGardenUse_hh$meter == "no",
+ monthlyGardenUse_hh$totalMonthlyInHouseDemand * gardenNoMeter * monthlyGardenUse_hh$noplantslawn,
+ NA )
+ ) #a column with garden use was added
-monthlyGardenUse_hh$dailyGardenUse <- monthlyGardenUse_hh$monthlyGardenUse/30
-summary(monthlyGardenUse_hh$dailyGardenUse) #Mean daily garden demand is 32.5 l/hh/day. Seems reasonable
+monthlyGardenUse_hh$dailyGardenUse<-monthlyGardenUse_hh$monthlyGardenUse/30
+summary(monthlyGardenUse_hh$dailyGardenUse) #Mean daily garden demand is 32.5 l/hh/day. Seems reasonable
```
```
@@ -1175,15 +1080,12 @@ summary(monthlyGardenUse_hh$dailyGardenUse) #Mean daily garden demand is 32.5 l
```
```r
-sapply(split(monthlyGardenUse_hh$monthlyGardenUse, monthlyGardenUse_hh$hhsize),
- mean, na.rm = TRUE)
+sapply(split(monthlyGardenUse_hh$monthlyGardenUse, monthlyGardenUse_hh$hhsize), mean, na.rm=TRUE)
```
```
-## 1 2 3 4 5 6 7
-## 227.7423 530.5318 726.9288 873.7553 926.8311 886.5356 1270.9766
-## 10
-## 2497.5260
+## 1 2 3 4 5 6 7 10
+## 227.7423 530.5318 726.9288 873.7553 926.8311 886.5356 1270.9766 2497.5260
```
Plot of garden demand per household size
@@ -1193,27 +1095,23 @@ monthlyGardenUse_hh$hhsize <- as.integer(monthlyGardenUse_hh$hhsize)
x.sub <- subset(monthlyGardenUse_hh, hhsize <= 6)
-monthlyGardenUse_hh$hhsize <- as.factor(monthlyGardenUse_hh$hhsize)
+monthlyGardenUse_hh$hhsize<- as.factor(monthlyGardenUse_hh$hhsize)
-ggplot(data = x.sub) + aes(y = monthlyGardenUse, x = factor(hhsize)) + geom_boxplot() +
- labs(title = "Garden water use (l/house/month)") + xlab("household size") +
- ylab("garden demand (l/hh/month)")
+ggplot(data=x.sub )+ aes(y = monthlyGardenUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "Garden water use (l/house/month)")+ xlab('household size')+ylab('garden demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(x.sub[x.sub$meter == "yes" | x.sub$meter == "no", ], aes(factor(hhsize),
- monthlyGardenUse)) + geom_boxplot(aes(fill = meter)) + labs(title = " garden demand (l/household/month)") +
- xlab("household size") + ylab("garden demand (l/hh/month)")
+ggplot(x.sub[x.sub$meter == "yes"|x.sub$meter == "no",], aes(factor(hhsize), monthlyGardenUse)) + geom_boxplot(aes(fill = meter))+labs(title = " garden demand (l/household/month)")+ xlab('household size')+ylab('garden demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(x.sub[x.sub$meter == "yes" | x.sub$meter == "no", ], aes(factor(hhsize),
- dailyGardenUse)) + geom_boxplot(aes(fill = meter)) + labs(title = " garden demand (l/household/day)") +
- xlab("household size") + ylab("garden demand (l/hh/day)")
+ggplot(x.sub[x.sub$meter == "yes"|x.sub$meter == "no",], aes(factor(hhsize), dailyGardenUse)) + geom_boxplot(aes(fill = meter))+labs(title = " garden demand (l/household/day)")+ xlab('household size')+ylab('garden demand (l/hh/day)')
```
<!-- -->
@@ -1221,26 +1119,19 @@ ggplot(x.sub[x.sub$meter == "yes" | x.sub$meter == "no", ], aes(factor(hhsize),
## Carwashing demand
```r
-# Households with no cars are assigned a ZERO value
-CarDemand_hh <- select(Surveydata, iobs, bmg_id, q2, q4, q13a, q13b, q13c, q14a,
- q15aa, q15ab, q15ac)
-CarDemand_hh <- rename(CarDemand_hh, obs = iobs, id = bmg_id, hhsize = q2, onecar = q13a,
- twocars = q13b, threecars = q13c, carwash_freq = q14a, bucket_wash = q15aa,
- hose_wash = q15ab, pres_wash = q15ac, meter = q4)
+#Households with no cars are assigned a ZERO value
+CarDemand_hh<-select(Surveydata, iobs,bmg_id, q2, q4, q13a, q13b,q13c, q14a, q15aa,q15ab,q15ac)
+CarDemand_hh<-rename(CarDemand_hh, obs =iobs, id=bmg_id, hhsize=q2,onecar=q13a, twocars=q13b, threecars=q13c, carwash_freq=q14a, bucket_wash=q15aa, hose_wash=q15ab, pres_wash=q15ac, meter=q4 )
CarDemand_hh$onecar <- ifelse(CarDemand_hh$onecar == "yes", 1, 0)
CarDemand_hh$twocars <- ifelse(CarDemand_hh$twocars == "yes", 2, 0)
-CarDemand_hh$threecars <- ifelse(CarDemand_hh$threecars == "yes", 3, 0)
-CarDemand_hh$CarSum <- CarDemand_hh$onecar + CarDemand_hh$twocars + CarDemand_hh$threecars #new column with number of cars per household
+CarDemand_hh$threecars<- ifelse(CarDemand_hh$threecars== "yes", 3, 0)
+CarDemand_hh$CarSum<-CarDemand_hh$onecar+CarDemand_hh$twocars+CarDemand_hh$threecars #new column with number of cars per household
-CarDemand_hh[, 8] <- ifelse(CarDemand_hh[, 8] == "never", 0, ifelse(CarDemand_hh[,
- 8] == "at least once a week", 4, ifelse(CarDemand_hh[, 8] == "less often than every three months",
- 0.25, ifelse(CarDemand_hh[, 8] == "less than once a month, but at least every three months",
- 0.33, ifelse(CarDemand_hh[, 8] == "less than once a week, but at least once a month",
- 1, NA)))))
+CarDemand_hh[,8] <- ifelse(CarDemand_hh[,8] == "never", 0 ,ifelse(CarDemand_hh[,8] == "at least once a week", 4, ifelse(CarDemand_hh[,8] == "less often than every three months", 0.25 ,ifelse(CarDemand_hh[,8] == "less than once a month, but at least every three months", 0.33, ifelse(CarDemand_hh[,8] == "less than once a week, but at least once a month", 1, NA)))))
-CarDemand_hh[, 8] <- ifelse(CarDemand_hh$CarSum == 0, 0, CarDemand_hh[, 8]) #for those not owning a car, frequency of carwashing is zero
+CarDemand_hh[,8]<-ifelse (CarDemand_hh$CarSum==0,0,CarDemand_hh[,8]) #for those not owning a car, frequency of carwashing is zero
-summary(CarDemand_hh[, 8])
+summary(CarDemand_hh[,8])
```
```
@@ -1249,50 +1140,45 @@ summary(CarDemand_hh[, 8])
```
```r
-# a bucket wash uses 30litres/wash while a hose wash uses 250litres/ wash
+#a bucket wash uses 30litres/wash while a hose wash uses 250litres/ wash
CarDemand_hh$bucket_wash <- ifelse(CarDemand_hh$bucket_wash == "yes", 30, 0)
CarDemand_hh$hose_wash <- ifelse(CarDemand_hh$hose_wash == "yes", 250, 0)
-# a pressure washer uses approximately 35gal/10 minute wash= 132litres/wash
-# (http://www.mde.state.md.us/programs/Water/WaterConservation/Pages/Programs/WaterPrograms/water_conservation/household_tips/carwashing.aspx)
+#a pressure washer uses approximately 35gal/10 minute wash= 132litres/wash (http://www.mde.state.md.us/programs/Water/WaterConservation/Pages/Programs/WaterPrograms/water_conservation/household_tips/carwashing.aspx)
CarDemand_hh$pres_wash <- ifelse(CarDemand_hh$pres_wash == "yes", 132, 0)
-# many households use multiple ways to wash their cars
-CarDemand_hh$Mean_wash <- rowMeans(CarDemand_hh[, 9:11], na.rm = TRUE)
-# most households have not indicated how they wash their cars, so their
-# consumption could not be calculated. Thus, I took the mean of reported
-# bucket wash, hose wash and pressure wash for each household size and I
-# assigned it to each household that has a car but no records for how they
-# wash it.
+#many households use multiple ways to wash their cars
+CarDemand_hh$Mean_wash <- rowMeans(CarDemand_hh[,9:11],na.rm=TRUE)
+#most households have not indicated how they wash their cars, so their consumption could not be calculated. Thus, I took the mean of reported bucket wash, hose wash and pressure wash for each household size and I assigned it to each household that has a car but no records for how they wash it.
CarDemand_hh$Mean_wash[CarDemand_hh$Mean_wash == 0] <- NA
-size1mean_wash <- filter(CarDemand_hh, hhsize == 1 & CarSum >= 1)
-mean1 <- mean(size1mean_wash$Mean_wash, na.rm = TRUE)
-size2mean_wash <- filter(CarDemand_hh, hhsize == 2 & CarSum >= 1)
-mean2 <- mean(size2mean_wash$Mean_wash, na.rm = TRUE)
-size3mean_wash <- filter(CarDemand_hh, hhsize == 3 & CarSum >= 1)
-mean3 <- mean(size3mean_wash$Mean_wash, na.rm = TRUE)
-size4mean_wash <- filter(CarDemand_hh, hhsize == 4 & CarSum >= 1)
-mean4 <- mean(size4mean_wash$Mean_wash, na.rm = TRUE)
-size5mean_wash <- filter(CarDemand_hh, hhsize == 5 & CarSum >= 1)
-mean5 <- mean(size5mean_wash$Mean_wash, na.rm = TRUE)
-size6mean_wash <- filter(CarDemand_hh, hhsize == 6 & CarSum >= 1)
-mean6 <- mean(size6mean_wash$Mean_wash, na.rm = TRUE)
-size7mean_wash <- filter(CarDemand_hh, hhsize == 7 & CarSum >= 1)
-mean7 <- mean(size7mean_wash$Mean_wash, na.rm = TRUE)
+size1mean_wash<-filter(CarDemand_hh, hhsize == 1 & CarSum>=1)
+mean1<-mean (size1mean_wash$Mean_wash,na.rm=TRUE)
+size2mean_wash<-filter(CarDemand_hh, hhsize == 2 & CarSum>=1)
+mean2<-mean (size2mean_wash$Mean_wash,na.rm=TRUE)
+size3mean_wash<-filter(CarDemand_hh, hhsize == 3 &CarSum>=1)
+mean3<-mean (size3mean_wash$Mean_wash,na.rm=TRUE)
+size4mean_wash<-filter(CarDemand_hh, hhsize == 4 &CarSum>=1)
+mean4<-mean (size4mean_wash$Mean_wash,na.rm=TRUE)
+size5mean_wash<-filter(CarDemand_hh, hhsize == 5 &CarSum>=1)
+mean5<-mean (size5mean_wash$Mean_wash,na.rm=TRUE)
+size6mean_wash<-filter(CarDemand_hh, hhsize == 6 &CarSum>=1)
+mean6<-mean (size6mean_wash$Mean_wash,na.rm=TRUE)
+size7mean_wash<-filter(CarDemand_hh, hhsize == 7 &CarSum>=1)
+mean7<-mean (size7mean_wash$Mean_wash,na.rm=TRUE)
summary(CarDemand_hh)
```
```
-## obs id hhsize meter
-## Min. : 2.0 Min. :836900048 Min. : 1.000 don't know:167
-## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 no :864
-## Median : 905.5 Median :836920637 Median : 2.000 yes :769
-## Mean : 906.0 Mean :836919052 Mean : 2.655
-## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
-## Max. :1810.0 Max. :836965495 Max. :10.000
-##
+## obs id hhsize meter
+## Min. : 2.0 Min. :836900048 Min. : 1.000 Length:1800
+## 1st Qu.: 454.8 1st Qu.:836910532 1st Qu.: 2.000 Class :character
+## Median : 905.5 Median :836920637 Median : 2.000 Mode :character
+## Mean : 906.0 Mean :836919052 Mean : 2.655
+## 3rd Qu.:1356.2 3rd Qu.:836922574 3rd Qu.: 4.000
+## Max. :1810.0 Max. :836965495 Max. :10.000
+##
## onecar twocars threecars carwash_freq
## Min. :0.0000 Min. :0.0000 Min. :0.0000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000 1st Qu.:0.0000
@@ -1320,50 +1206,30 @@ summary(CarDemand_hh)
```
```r
-CarDemand_hh$Mean_wash <- ifelse(is.na(CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum >=
- 1 & CarDemand_hh$hhsize == 1, mean1, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 2, mean2, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 3, mean3, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 4, mean4, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 5, mean5, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 6, mean6, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 7, mean7, ifelse(is.na(CarDemand_hh$Mean_wash) &
- CarDemand_hh$CarSum < 1, 0, CarDemand_hh$Mean_wash))))))))
+CarDemand_hh$Mean_wash <- ifelse(is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 1, mean1, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 2, mean2, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 3, mean3, ifelse (is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 4, mean4,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 5, mean5,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 6, mean6,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 7, mean7,ifelse ( is.na (CarDemand_hh$Mean_wash) & CarDemand_hh$CarSum<1 ,0, CarDemand_hh$Mean_wash ))))))))
# Now, only households with no cars have a zero value for mean_wash (429).
-# Need to do the same for carwashing frequencies, so that litres (mean_wash)
-# can be multiplied by frequencies and number of cars to produce monthly
-# consumption (monthlyCarWashUse). most households have not indicated how
-# often they wash their cars, so their consumption cannot be calculated.
-# Thus, I took the mean of reported frequencies for each household size and
-# I assigned it to each household that has a car but no records for how
-# often they wash it.
-
-
-size1mean_freq <- filter(CarDemand_hh, hhsize == 1 & CarSum >= 1)
-freq1 <- mean(size1mean_freq$carwash_freq, na.rm = TRUE)
-size2mean_freq <- filter(CarDemand_hh, hhsize == 2 & CarSum >= 1)
-freq2 <- mean(size2mean_freq$carwash_freq, na.rm = TRUE)
-size3mean_freq <- filter(CarDemand_hh, hhsize == 3 & CarSum >= 1)
-freq3 <- mean(size3mean_freq$carwash_freq, na.rm = TRUE)
-size4mean_freq <- filter(CarDemand_hh, hhsize == 4 & CarSum >= 1)
-freq4 <- mean(size4mean_freq$carwash_freq, na.rm = TRUE)
-size5mean_freq <- filter(CarDemand_hh, hhsize == 5 & CarSum >= 1)
-freq5 <- mean(size5mean_freq$carwash_freq, na.rm = TRUE)
-size6mean_freq <- filter(CarDemand_hh, hhsize == 6 & CarSum >= 1)
-freq6 <- mean(size6mean_freq$carwash_freq, na.rm = TRUE)
-
-CarDemand_hh$carwash_freq <- ifelse(is.na(CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum >=
- 1 & CarDemand_hh$hhsize == 1, freq1, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 2, freq2, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 3, freq3, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 4, freq4, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 5, freq5, ifelse(is.na(CarDemand_hh$carwash_freq) &
- CarDemand_hh$CarSum >= 1 & CarDemand_hh$hhsize == 6, freq6, CarDemand_hh$carwash_freq))))))
-
-CarDemand_hh$monthlyCarWashUse <- CarDemand_hh$carwash_freq * CarDemand_hh$CarSum *
- CarDemand_hh$Mean_wash #monthly consumption for car washing
-summary(CarDemand_hh$monthlyCarWashUse)
+#Need to do the same for carwashing frequencies, so that litres (mean_wash) can be multiplied by frequencies and number of cars to produce monthly consumption (monthlyCarWashUse).
+#most households have not indicated how often they wash their cars, so their consumption cannot be calculated. Thus, I took the mean of reported frequencies for each household size and I assigned it to each household that has a car but no records for how often they wash it.
+
+
+size1mean_freq<-filter(CarDemand_hh, hhsize == 1 & CarSum>=1)
+freq1<-mean (size1mean_freq$carwash_freq,na.rm=TRUE)
+size2mean_freq<-filter(CarDemand_hh, hhsize == 2 & CarSum>=1)
+freq2<-mean (size2mean_freq$carwash_freq,na.rm=TRUE)
+size3mean_freq<-filter(CarDemand_hh, hhsize == 3 &CarSum>=1)
+freq3<-mean (size3mean_freq$carwash_freq,na.rm=TRUE)
+size4mean_freq<-filter(CarDemand_hh, hhsize == 4 &CarSum>=1)
+freq4<-mean (size4mean_freq$carwash_freq,na.rm=TRUE)
+size5mean_freq<-filter(CarDemand_hh, hhsize == 5 &CarSum>=1)
+freq5<-mean (size5mean_freq$carwash_freq,na.rm=TRUE)
+size6mean_freq<-filter(CarDemand_hh, hhsize == 6 &CarSum>=1)
+freq6<-mean (size6mean_freq$carwash_freq,na.rm=TRUE)
+
+CarDemand_hh$carwash_freq <- ifelse(is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 1, freq1, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 2, freq2, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 3, freq3, ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 4, freq4,ifelse ( is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 5, freq5,ifelse (is.na (CarDemand_hh$carwash_freq) & CarDemand_hh$CarSum>=1 & CarDemand_hh$hhsize == 6, freq6,CarDemand_hh$carwash_freq ))))))
+
+CarDemand_hh$monthlyCarWashUse<-CarDemand_hh$carwash_freq*CarDemand_hh$CarSum*CarDemand_hh$Mean_wash #monthly consumption for car washing
+summary(CarDemand_hh$monthlyCarWashUse)
```
```
@@ -1381,55 +1247,51 @@ summary(CarDemand_hh$monthlyCarWashUse)
```
```r
-CarDemand_hh <- CarDemand_hh[, -(5:13), drop = FALSE] #dropping columns i dont need
-CarDemand_hh <- mutate(CarDemand_hh, dailyCarWashUse = monthlyCarWashUse/30)
+CarDemand_hh<-CarDemand_hh[,-(5:13),drop=FALSE] #dropping columns i dont need
+CarDemand_hh<-mutate(CarDemand_hh,dailyCarWashUse= monthlyCarWashUse/30)
-kable(caption = "Summary of demand for car washing", CarDemand_hh[1:5, ])
+kable(caption = "Summary of demand for car washing",
+ CarDemand_hh [1:5,]
+)
```
Table: Summary of demand for car washing
- obs id hhsize meter monthlyCarWashUse dailyCarWashUse
----- ---------- ------- ----------- ------------------ ----------------
- 2 836900048 2 yes 2.500000 0.0833333
- 3 836900071 2 don't know 6.419628 0.2139876
- 4 836900073 4 yes 38.639731 1.2879910
- 5 836900106 1 yes 30.800000 1.0266667
- 6 836900117 4 yes 3.300000 0.1100000
+| obs| id| hhsize|meter | monthlyCarWashUse| dailyCarWashUse|
+|---:|---------:|------:|:----------|-----------------:|---------------:|
+| 2| 836900048| 2|yes | 2.500000| 0.0833333|
+| 3| 836900071| 2|don't know | 6.419628| 0.2139876|
+| 4| 836900073| 4|yes | 38.639731| 1.2879910|
+| 5| 836900106| 1|yes | 30.800000| 1.0266667|
+| 6| 836900117| 4|yes | 3.300000| 0.1100000|
Plot of carwashing demand per household size
```r
-ggplot(data = CarDemand_hh) + aes(y = monthlyCarWashUse, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total carwashing use (l/house/month)")
+ggplot(data=CarDemand_hh)+ aes(y = monthlyCarWashUse, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total carwashing use (l/house/month)")
```
<!-- -->
```r
-ggplot(CarDemand_hh[CarDemand_hh$meter == "yes" | CarDemand_hh$meter == "no",
- ], aes(factor(hhsize), monthlyCarWashUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = " carwashing demand (l/household/month)") + xlab("household size") +
- ylab("carwashing demand (l/hh/month)")
+ggplot(CarDemand_hh[CarDemand_hh$meter == "yes"|CarDemand_hh$meter == "no",], aes(factor(hhsize), monthlyCarWashUse)) + geom_boxplot(aes(fill = meter))+labs(title = " carwashing demand (l/household/month)")+ xlab('household size')+ylab('carwashing demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(CarDemand_hh[CarDemand_hh$meter == "yes" | CarDemand_hh$meter == "no",
- ], aes(factor(hhsize), dailyCarWashUse)) + geom_boxplot(aes(fill = meter)) +
- labs(title = "carwashing demand (l/household/day)") + xlab("household size") +
- ylab("carwashing demand (l/hh/day)")
+ggplot(CarDemand_hh[CarDemand_hh$meter == "yes"|CarDemand_hh$meter == "no",], aes(factor(hhsize), dailyCarWashUse)) + geom_boxplot(aes(fill = meter))+labs(title = "carwashing demand (l/household/day)")+ xlab('household size')+ylab('carwashing demand (l/hh/day)')
```
<!-- -->
```r
-CarDemand_hh <- CarDemand_hh <- subset(CarDemand_hh, select = c("id", "monthlyCarWashUse",
- "dailyCarWashUse"))
+CarDemand_hh <- CarDemand_hh<-subset(CarDemand_hh, select=c("id","monthlyCarWashUse","dailyCarWashUse" ))
```
## Washing of caravans and boats (not implemented)
@@ -1438,23 +1300,24 @@ We could not find data on litres per wash etc and it seems quite rare in any cas
```r
-t <- table(Surveydata$q14b, Surveydata$q14c, useNA = "always")
+t <- table(Surveydata$q14b,Surveydata$q14c, useNA = "always")
-kable(caption = "Frequency of washing caravans (rows) vs boats", t)
+kable(caption = "Frequency of washing caravans (rows) vs boats",
+ t)
```
Table: Frequency of washing caravans (rows) vs boats
- less often than every three months never NA
--------------------------------------------------------- ----- ----------------------------------- ------ ---
- 1782 1 3 0
-at least once a week 1 0 0 0
-less often than every three months 5 0 0 0
-less than once a month, but at least every three months 4 0 1 0
-never 2 0 1 0
-NA 0 0 0 0
+| | | less often than every three months| never| NA|
+|:-------------------------------------------------------|----:|----------------------------------:|-----:|--:|
+| | 1782| 1| 3| 0|
+|at least once a week | 1| 0| 0| 0|
+|less often than every three months | 5| 0| 0| 0|
+|less than once a month, but at least every three months | 4| 0| 1| 0|
+|never | 2| 0| 1| 0|
+|NA | 0| 0| 0| 0|
# Total consumption
@@ -1464,23 +1327,20 @@ Combine the internal and external consumption estimates per household.
```r
totalExtDemand_hh <- merge(monthlyGardenUse_hh, CarDemand_hh, by = "id")
-# only keep what we need
-totalExtDemand_hh <- subset(totalExtDemand_hh, select = c("id", "monthlyGardenUse",
- "dailyGardenUse", "monthlyCarWashUse", "dailyCarWashUse"))
+# only keep what we need
+totalExtDemand_hh <- subset(totalExtDemand_hh, select=c("id","monthlyGardenUse","dailyGardenUse","monthlyCarWashUse","dailyCarWashUse" ))
# clean up
-totalIntDemand_hh <- rename(totalIntDemand_hh, meter = meter.x.x)
-totalIntDemand_hh <- rename(totalIntDemand_hh, hhsize = hhsize.x.x)
+totalIntDemand_hh <- rename(totalIntDemand_hh, meter = meter.x.x)
+totalIntDemand_hh <- rename(totalIntDemand_hh, hhsize = hhsize.x.x)
# why can't merge combined 3+ data frames?
totalDemand_hh <- merge(totalIntDemand_hh, totalExtDemand_hh, by = "id")
-totalDemand_hh$totalMonthlyHouseDemandFinal <- totalDemand_hh$totalMonthlyInHouseDemand +
- totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
+totalDemand_hh$totalMonthlyHouseDemandFinal <- totalDemand_hh$totalMonthlyInHouseDemand + totalDemand_hh$monthlyCarWashUse + totalDemand_hh$monthlyGardenUse
totalDemand_hh$totalDailyHouseDemandFinal <- totalDemand_hh$totalMonthlyHouseDemandFinal/30
-# construct other daily values that may have been removed during merging
-# process
+# construct other daily values that may have been removed during merging process
totalDemand_hh$dailyBathUse <- totalDemand_hh$monthlyBathUse/30
totalDemand_hh$dailyShowerUse <- totalDemand_hh$monthlyShowerUse/30
totalDemand_hh$dailyDishwasherUse <- totalDemand_hh$monthlyDishwasherUse/30
@@ -1496,80 +1356,75 @@ totalDemand_hh$dailyBathroomSinkUse <- totalDemand_hh$monthlyBathroomSinkUse/30
```r
# I am combining the bath and shower datasets
-bath_sh_hh <- merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all.x = TRUE)
+bath_sh_hh<-merge(x = bathdemand_hh, y = showerdemand_hh, by = "id", all.x = TRUE)
-# at this point I got extra observations after merging the datasets. Now has
-# been corrected. The following test revealed the duplicates: n_occur <-
-# data.frame(table(bath_sh_hh$id)) n_occur[n_occur$Freq > 1,]
-# bath_sh_hh[bath_sh_hh$id %in% n_occur$Var1[n_occur$Freq > 1],] id
-# 836900103 appears 4 times in the merged dataframe!!
+#at this point I got extra observations after merging the datasets. Now has been corrected. The following test revealed the duplicates:
+#n_occur <- data.frame(table(bath_sh_hh$id))
+#n_occur[n_occur$Freq > 1,]
+#bath_sh_hh[bath_sh_hh$id %in% n_occur$Var1[n_occur$Freq > 1],]
+#id 836900103 appears 4 times in the merged dataframe!!
-# i am deleting the columns i dont need
-bath_sh_hh <- subset(bath_sh_hh, select = -c(obs.x, obs.y))
-kable(caption = "Summary of bath and shower demand", bath_sh_hh[1:5, ])
+#i am deleting the columns i dont need
+bath_sh_hh <- subset(bath_sh_hh, select = -c(obs.x,obs.y))
+kable(caption = "Summary of bath and shower demand",
+ bath_sh_hh [1:5,]
+)
```
Table: Summary of bath and shower demand
- id hhsize.x meter.x bath_freq baths housefreq baths_freq_EST showers_freq_EST monthlyBathUse dailyBathUse hhsize.y meter.y monthlyShowerUse dailyShowerUse
----------- --------- ----------- ---------- ------ ---------- --------------- ----------------- --------------- ------------- --------- ----------- ----------------- ---------------
- 836900048 2 yes NA 0 NA 2.25 9.40 0.0 0.00000 2 yes NA NA
- 836900071 2 don't know NA 1 NA 2.25 9.40 792.0 26.40000 2 don't know NA NA
- 836900073 4 yes 2 2 8 4.85 14.65 1707.2 56.90667 4 yes 5118 170.6
- 836900106 1 yes NA 0 NA 1.70 5.20 0.0 0.00000 1 yes 2379 79.3
- 836900117 4 yes 5 1 20 4.85 14.65 1707.2 56.90667 4 yes NA NA
+| id| hhsize.x|meter.x | bath_freq| baths| housefreq| baths_freq_EST| showers_freq_EST| monthlyBathUse| dailyBathUse| hhsize.y|meter.y | monthlyShowerUse| dailyShowerUse|
+|---------:|--------:|:----------|---------:|-----:|---------:|--------------:|----------------:|--------------:|------------:|--------:|:----------|----------------:|--------------:|
+| 836900048| 2|yes | NA| 0| NA| 2.25| 9.40| 0.0| 0.00000| 2|yes | NA| NA|
+| 836900071| 2|don't know | NA| 1| NA| 2.25| 9.40| 792.0| 26.40000| 2|don't know | NA| NA|
+| 836900073| 4|yes | 2| 2| 8| 4.85| 14.65| 1707.2| 56.90667| 4|yes | 5118| 170.6|
+| 836900106| 1|yes | NA| 0| NA| 1.70| 5.20| 0.0| 0.00000| 1|yes | 2379| 79.3|
+| 836900117| 4|yes | 5| 1| 20| 4.85| 14.65| 1707.2| 56.90667| 4|yes | NA| NA|
```r
# combining the dishwashers and kitchen sink datasets
-kitchen_dish_hh <- merge(x = monthlyDishwasherUse, y = kitchen_sink_hh, by = "id",
- all = TRUE)
-kitchen_dish_hh <- kitchen_dish_hh[, -(2:7), drop = FALSE] #dropping columns i dont need
+kitchen_dish_hh<-merge(x = monthlyDishwasherUse, y = kitchen_sink_hh, by = "id", all = TRUE)
+kitchen_dish_hh<-kitchen_dish_hh[,-(2:7),drop=FALSE]#dropping columns i dont need
summary(kitchen_dish_hh)
```
```
-## id monthlyDishwasherUse dailyDishwasherUse
-## Min. :836900048 Min. : 0.00 Min. :0.000
-## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000
-## Median :836920637 Median : 0.00 Median :0.000
-## Mean :836919052 Mean : 71.18 Mean :2.373
-## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293
-## Max. :836965495 Max. :268.80 Max. :8.960
-## obs.y hhsize.y meter.y monthlyKitchenSinkUse
-## Min. : 2.0 Min. : 1.000 don't know:167 Min. : 227.1
-## 1st Qu.: 454.8 1st Qu.: 2.000 no :864 1st Qu.: 454.2
-## Median : 905.5 Median : 2.000 yes :769 Median : 454.2
-## Mean : 906.0 Mean : 2.655 Mean : 603.0
-## 3rd Qu.:1356.2 3rd Qu.: 4.000 3rd Qu.: 908.4
-## Max. :1810.0 Max. :10.000 Max. :2271.0
-## dailyKitchenSinkUse
-## Min. : 7.57
-## 1st Qu.:15.14
-## Median :15.14
-## Mean :20.10
-## 3rd Qu.:30.28
-## Max. :75.70
+## id monthlyDishwasherUse dailyDishwasherUse obs.y
+## Min. :836900048 Min. : 0.00 Min. :0.000 Min. : 2.0
+## 1st Qu.:836910532 1st Qu.: 0.00 1st Qu.:0.000 1st Qu.: 454.8
+## Median :836920637 Median : 0.00 Median :0.000 Median : 905.5
+## Mean :836919052 Mean : 71.18 Mean :2.373 Mean : 906.0
+## 3rd Qu.:836922574 3rd Qu.:128.80 3rd Qu.:4.293 3rd Qu.:1356.2
+## Max. :836965495 Max. :268.80 Max. :8.960 Max. :1810.0
+## hhsize.y meter.y monthlyKitchenSinkUse dailyKitchenSinkUse
+## Min. : 1.000 Length:1800 Min. : 227.1 Min. : 7.57
+## 1st Qu.: 2.000 Class :character 1st Qu.: 454.2 1st Qu.:15.14
+## Median : 2.000 Mode :character Median : 454.2 Median :15.14
+## Mean : 2.655 Mean : 603.0 Mean :20.10
+## 3rd Qu.: 4.000 3rd Qu.: 908.4 3rd Qu.:30.28
+## Max. :10.000 Max. :2271.0 Max. :75.70
```
```r
-kable(caption = "Summary of demand for dishwashers and kitchen uses", kitchen_dish_hh[1:5,
- ])
+kable(caption = "Summary of demand for dishwashers and kitchen uses",
+ kitchen_dish_hh [1:5,]
+)
```
Table: Summary of demand for dishwashers and kitchen uses
- id monthlyDishwasherUse dailyDishwasherUse obs.y hhsize.y meter.y monthlyKitchenSinkUse dailyKitchenSinkUse
----------- --------------------- ------------------- ------ --------- ----------- ---------------------- --------------------
- 836900048 0.0 0.000000 2 2 yes 454.2 15.14
- 836900071 128.8 4.293333 3 2 don't know 454.2 15.14
- 836900073 240.8 8.026667 4 4 yes 908.4 30.28
- 836900106 0.0 0.000000 5 1 yes 227.1 7.57
- 836900117 240.8 8.026667 6 4 yes 908.4 30.28
+| id| monthlyDishwasherUse| dailyDishwasherUse| obs.y| hhsize.y|meter.y | monthlyKitchenSinkUse| dailyKitchenSinkUse|
+|---------:|--------------------:|------------------:|-----:|--------:|:----------|---------------------:|-------------------:|
+| 836900048| 0.0| 0.000000| 2| 2|yes | 454.2| 15.14|
+| 836900071| 128.8| 4.293333| 3| 2|don't know | 454.2| 15.14|
+| 836900073| 240.8| 8.026667| 4| 4|yes | 908.4| 30.28|
+| 836900106| 0.0| 0.000000| 5| 1|yes | 227.1| 7.57|
+| 836900117| 240.8| 8.026667| 6| 4|yes | 908.4| 30.28|
@@ -1579,39 +1434,41 @@ What do we do about NAs - are they meaningful or should they be 0 e.g. when summ
```r
-t <- summary(select(totalDemand_hh, contains("daily"))) #
+t <- summary(select(totalDemand_hh, contains("daily"))) #
-kable(caption = "Summary of daily total household demand values", t)
+kable(caption = "Summary of daily total household demand values",
+ t
+)
```
Table: Summary of daily total household demand values
- dailyGardenUse dailyCarWashUse totalDailyHouseDemandFinal dailyBathUse dailyShowerUse dailyDishwasherUse dailyKitchenSinkUse dailyWCUse dailyWashingMachineUse dailyBathroomSinkUse
---- --------------- ---------------- --------------------------- -------------- --------------- ------------------- -------------------- --------------- ----------------------- ---------------------
- Min. : 0.00 Min. : 0.0000 Min. : 63.56 Min. : 0.00 Min. : 0.0 Min. :0.000 Min. : 7.57 Min. : 25.00 Min. : 0.00 Min. : 10.40
- 1st Qu.: 0.00 1st Qu.: 0.0000 1st Qu.: 211.37 1st Qu.:19.95 1st Qu.: 48.8 1st Qu.:0.000 1st Qu.:15.14 1st Qu.: 50.00 1st Qu.:16.67 1st Qu.: 26.48
- Median :18.72 Median : 0.2500 Median : 314.64 Median :26.40 Median : 93.6 Median :0.000 Median :15.14 Median : 75.00 Median :16.67 Median : 39.72
- Mean :19.95 Mean : 0.8041 Mean : 352.75 Mean :35.53 Mean :107.0 Mean :2.373 Mean :20.10 Mean : 91.31 Mean :23.61 Mean : 58.27
- 3rd Qu.:31.79 3rd Qu.: 0.7778 3rd Qu.: 477.91 3rd Qu.:56.91 3rd Qu.:154.6 3rd Qu.:4.293 3rd Qu.:30.28 3rd Qu.:112.50 3rd Qu.:30.00 3rd Qu.: 66.20
- Max. :85.44 Max. :24.8889 Max. :1154.18 Max. :77.44 Max. :513.8 Max. :8.960 Max. :75.70 Max. :262.50 Max. :80.00 Max. :463.20
- NA's :331 NA's :4 NA's :334 NA NA's :53 NA NA NA's :59 NA's :47 NA's :53
+| |dailyGardenUse |dailyCarWashUse |totalDailyHouseDemandFinal | dailyBathUse |dailyShowerUse |dailyDishwasherUse |dailyKitchenSinkUse | dailyWCUse |dailyWashingMachineUse |dailyBathroomSinkUse |
+|:--|:--------------|:---------------|:--------------------------|:-------------|:--------------|:------------------|:-------------------|:--------------|:----------------------|:--------------------|
+| |Min. : 0.00 |Min. : 0.0000 |Min. : 63.56 |Min. : 0.00 |Min. : 0.0 |Min. :0.000 |Min. : 7.57 |Min. : 25.00 |Min. : 0.00 |Min. : 10.40 |
+| |1st Qu.: 0.00 |1st Qu.: 0.0000 |1st Qu.: 211.37 |1st Qu.:19.95 |1st Qu.: 48.8 |1st Qu.:0.000 |1st Qu.:15.14 |1st Qu.: 50.00 |1st Qu.:16.67 |1st Qu.: 26.48 |
+| |Median :18.72 |Median : 0.2500 |Median : 314.64 |Median :26.40 |Median : 93.6 |Median :0.000 |Median :15.14 |Median : 75.00 |Median :16.67 |Median : 39.72 |
+| |Mean :19.95 |Mean : 0.8041 |Mean : 352.75 |Mean :35.53 |Mean :107.0 |Mean :2.373 |Mean :20.10 |Mean : 91.31 |Mean :23.61 |Mean : 58.27 |
+| |3rd Qu.:31.79 |3rd Qu.: 0.7778 |3rd Qu.: 477.91 |3rd Qu.:56.91 |3rd Qu.:154.6 |3rd Qu.:4.293 |3rd Qu.:30.28 |3rd Qu.:112.50 |3rd Qu.:30.00 |3rd Qu.: 66.20 |
+| |Max. :85.44 |Max. :24.8889 |Max. :1154.18 |Max. :77.44 |Max. :513.8 |Max. :8.960 |Max. :75.70 |Max. :262.50 |Max. :80.00 |Max. :463.20 |
+| |NA's :331 |NA's :4 |NA's :334 |NA |NA's :53 |NA |NA |NA's :59 |NA's :47 |NA's :53 |
# Summary plots
```r
-ggplot(data = totalDemand_hh) + geom_bar(mapping = aes(x = factor(hhsize))) +
- xlab("household size")
+ggplot(data = totalDemand_hh) +
+ geom_bar(mapping = aes(x = factor(hhsize)))+ xlab('household size')
```
<!-- -->
```r
-ggplot(data = totalDemand_hh) + geom_bar(mapping = aes(x = factor(meter))) +
- xlab("metered or not")
+ggplot(data = totalDemand_hh) +
+ geom_bar(mapping = aes(x = factor(meter)))+xlab('metered or not')
```
<!-- -->
@@ -1619,37 +1476,32 @@ ggplot(data = totalDemand_hh) + geom_bar(mapping = aes(x = factor(meter))) +
```r
-ggplot(data = totalDemand_hh) + aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() + labs(title = "total use (l/month)") + labs(title = " total demand (l/household/month)") +
- xlab("household size") + ylab("total household demand (l/hh/month)")
+ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(hhsize)) +
+ geom_boxplot() +
+ labs(title = "total use (l/month)")+labs(title = " total demand (l/household/month)")+ xlab('household size')+ylab('total household demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(data = totalDemand_hh) + aes(y = totalMonthlyHouseDemandFinal, x = factor(meter)) +
- geom_boxplot() + labs(title = "Total demand (l/household/month)") + xlab("metered or not") +
- ylab("Total household demand (l/hh/month)")
+ggplot(data=totalDemand_hh)+ aes(y = totalMonthlyHouseDemandFinal, x = factor(meter)) +
+ geom_boxplot() +labs(title = "Total demand (l/household/month)")+ xlab('metered or not')+ylab('Total household demand (l/hh/month)')
```
<!-- -->
```r
-ggplot(data = totalDemand_hh) + aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
- geom_boxplot() + labs(title = " Total demand (l/household/day)") + xlab("metered or not") +
- ylab("Total household demand (l/hh/day)")
+ggplot(data=totalDemand_hh)+ aes(y = totalDailyHouseDemandFinal, x = factor(hhsize)) +
+ geom_boxplot() +labs(title = " Total demand (l/household/day)")+ xlab('metered or not')+ylab('Total household demand (l/hh/day)')
```
<!-- -->
```r
-ggplot(totalDemand_hh[totalDemand_hh$meter == "yes" | totalDemand_hh$meter ==
- "no", ], aes(factor(hhsize), totalDailyHouseDemandFinal)) + geom_boxplot(aes(fill = meter)) +
- labs(title = " total demand (l/household/day)") + xlab("household size") +
- ylab("total demand (l/hh/day)")
+ggplot(totalDemand_hh[totalDemand_hh$meter == "yes"|totalDemand_hh$meter == "no",], aes(factor(hhsize), totalDailyHouseDemandFinal)) + geom_boxplot(aes(fill = meter))+labs(title = " total demand (l/household/day)")+ xlab('household size')+ylab('total demand (l/hh/day)')
```
<!-- -->
@@ -1659,26 +1511,23 @@ ggplot(totalDemand_hh[totalDemand_hh$meter == "yes" | totalDemand_hh$meter ==
```r
-# delete columns I dont need
-totalDemand_hh <- subset(totalDemand_hh, select = -c(obs.y)) # remove what we don't want to keep
+#delete columns I dont need
+totalDemand_hh <- subset(totalDemand_hh, select = -c(obs.y)) # remove what we don't want to keep
# seasonal values are input config file to WDEM. Monthly values are unused
-# tab delimted output file write.csv(hhmonthly,
-# paste(fpath,'output-hh-monthly-consumption',format(Sys.time(), '%Y-%m-%d
-# %I-%p'),'.csv', sep = '')) oFile <-
-# paste0(opath,'output-hh-seasonal-consumption_',format(Sys.time(),
-# '%Y-%m-%d'), 'v2.txt', sep = '') write.table(hhmcSeasonalValuesDT,
-# oFile,sep = '\t')
+# tab delimted output file
+# write.csv(hhmonthly, paste(fpath,"output-hh-monthly-consumption",format(Sys.time(), "%Y-%m-%d %I-%p"),".csv", sep = ""))
+#oFile <- paste0(opath,"output-hh-seasonal-consumption_",format(Sys.time(), "%Y-%m-%d"), "v2.txt", sep = "")
+#write.table(hhmcSeasonalValuesDT, oFile,sep = "\t")
-oFile <- paste0(oPath, "output-SPRG-1800hh-consumption_", format(Sys.time(),
- "%Y-%m-%d"), outputVersion, ".csv")
+oFile <- paste0(oPath,"output-SPRG-1800hh-consumption_",format(Sys.time(), "%Y-%m-%d"), outputVersion, ".csv")
write.csv(totalDemand_hh, oFile)
```
Data written to:
-> ~/Data/IMPETUS/outputs/model_v2/output-SPRG-1800hh-consumption_2017-06-19v2.1.csv and (possibly) gzipped
+> ~/University of Southampton/IMPETUS - Documents/data//model_outputs/output-SPRG-1800hh-consumption_2021-03-11v2.1.csv and (possibly) gzipped
# About
@@ -1694,11 +1543,11 @@ This work was supported by the NERC funded IMPETUS (Improving Predictions of Dro
If you wish to use any of the material from this report please cite as:
- * Manouseli, D., & Anderson, B. (2017) _Domestic Water Demand Estimation Using SPRG Survey_, University of Southampton: Southampton, UK.
+ * Manouseli, D., & Anderson, B. (2021) _Domestic Water Demand Estimation Using SPRG Survey_, University of Southampton: Southampton, UK.
## Runtime
-Analysis completed in: 19.16 seconds using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 3.4.0 (2017-04-21) running on x86_64-apple-darwin15.6.0.
+Analysis completed in: 15.97 seconds using [knitr](https://cran.r-project.org/package=knitr) in [RStudio](http://www.rstudio.com) with R version 4.0.2 (2020-06-22) running on x86_64-apple-darwin17.0.
R packages used:
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.css b/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 0000000000000000000000000000000000000000..07aee5fcb8398a53ea2189cff95cbe6504116d96
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.css
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.js b/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 0000000000000000000000000000000000000000..570f99a0a8775e26c9dac3b1dd7b82cbe6dbfae3
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/anchor-sections-1.0/anchor-sections.js
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+ // Do nothing if AnchorJS is used
+ if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+ return;
+ }
+
+ const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+ // Do nothing if sections are already anchored
+ if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+ return null;
+ }
+
+ // Use section id when pandoc runs with --section-divs
+ const section_id = function(x) {
+ return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+ ? x.id : '');
+ };
+
+ // Add anchors
+ h.forEach(function(x) {
+ const id = x.id || section_id(x.parentElement);
+ if (id === '') {
+ return null;
+ }
+ let anchor = document.createElement('a');
+ anchor.href = '#' + id;
+ anchor.classList = ['anchor-section'];
+ x.classList.add('hasAnchor');
+ x.appendChild(anchor);
+ });
+});
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/bootstrap-3.3.5/css/darkly.min.css b/model_v2/SPRG_demand_v2.1_BA_files/bootstrap-3.3.5/css/darkly.min.css
new file mode 100644
index 0000000000000000000000000000000000000000..aaf0ab5af433e86669c01af0158e73e43d0fdcea
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/bootstrap-3.3.5/css/darkly.min.css
@@ -0,0 +1,30 @@
+@font-face {
+ font-family: 'Lato';
+ font-style: normal;
+ font-weight: 400;
+ src: url(fonts/Lato.ttf) format('truetype');
+}
+@font-face {
+ font-family: 'Lato';
+ font-style: normal;
+ font-weight: 700;
+ src: url(fonts/LatoBold.ttf) format('truetype');
+}
+@font-face {
+ font-family: 'Lato';
+ font-style: italic;
+ font-weight: 400;
+ src: url(fonts/LatoItalic.ttf) format('truetype');
+}
+
+/*!
+ * bootswatch v3.3.7
+ * Homepage: http://bootswatch.com
+ * Copyright 2012-2016 Thomas Park
+ * Licensed under MIT
+ * Based on Bootstrap
+*//*!
+ * Bootstrap v3.3.7 (http://getbootstrap.com)
+ * Copyright 2011-2016 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ *//*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */html{font-family:sans-serif;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%}body{margin:0}article,aside,details,figcaption,figure,footer,header,hgroup,main,menu,nav,section,summary{display:block}audio,canvas,progress,video{display:inline-block;vertical-align:baseline}audio:not([controls]){display:none;height:0}[hidden],template{display:none}a{background-color:transparent}a:active,a:hover{outline:0}abbr[title]{border-bottom:1px dotted}b,strong{font-weight:bold}dfn{font-style:italic}h1{font-size:2em;margin:0.67em 0}mark{background:#ff0;color:#000}small{font-size:80%}sub,sup{font-size:75%;line-height:0;position:relative;vertical-align:baseline}sup{top:-0.5em}sub{bottom:-0.25em}img{border:0}svg:not(:root){overflow:hidden}figure{margin:1em 40px}hr{-webkit-box-sizing:content-box;-moz-box-sizing:content-box;box-sizing:content-box;height:0}pre{overflow:auto}code,kbd,pre,samp{font-family:monospace, monospace;font-size:1em}button,input,optgroup,select,textarea{color:inherit;font:inherit;margin:0}button{overflow:visible}button,select{text-transform:none}button,html input[type="button"],input[type="reset"],input[type="submit"]{-webkit-appearance:button;cursor:pointer}button[disabled],html input[disabled]{cursor:default}button::-moz-focus-inner,input::-moz-focus-inner{border:0;padding:0}input{line-height:normal}input[type="checkbox"],input[type="radio"]{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box;padding:0}input[type="number"]::-webkit-inner-spin-button,input[type="number"]::-webkit-outer-spin-button{height:auto}input[type="search"]{-webkit-appearance:textfield;-webkit-box-sizing:content-box;-moz-box-sizing:content-box;box-sizing:content-box}input[type="search"]::-webkit-search-cancel-button,input[type="search"]::-webkit-search-decoration{-webkit-appearance:none}fieldset{border:1px solid #c0c0c0;margin:0 2px;padding:0.35em 0.625em 0.75em}legend{border:0;padding:0}textarea{overflow:auto}optgroup{font-weight:bold}table{border-collapse:collapse;border-spacing:0}td,th{padding:0}/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */@media print{*,*:before,*:after{background:transparent !important;color:#000 !important;-webkit-box-shadow:none !important;box-shadow:none !important;text-shadow:none !important}a,a:visited{text-decoration:underline}a[href]:after{content:" (" attr(href) ")"}abbr[title]:after{content:" (" attr(title) ")"}a[href^="#"]:after,a[href^="javascript:"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}p,h2,h3{orphans:3;widows:3}h2,h3{page-break-after:avoid}.navbar{display:none}.btn>.caret,.dropup>.btn>.caret{border-top-color:#000 !important}.label{border:1px solid #000}.table{border-collapse:collapse !important}.table td,.table th{background-color:#fff !important}.table-bordered th,.table-bordered td{border:1px solid #ddd !important}}@font-face{font-family:'Glyphicons Halflings';src:url('../fonts/glyphicons-halflings-regular.eot');src:url('../fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'),url('../fonts/glyphicons-halflings-regular.woff2') format('woff2'),url('../fonts/glyphicons-halflings-regular.woff') format('woff'),url('../fonts/glyphicons-halflings-regular.ttf') format('truetype'),url('../fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg')}.glyphicon{position:relative;top:1px;display:inline-block;font-family:'Glyphicons Halflings';font-style:normal;font-weight:normal;line-height:1;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale}.glyphicon-asterisk:before{content:"\002a"}.glyphicon-plus:before{content:"\002b"}.glyphicon-euro:before,.glyphicon-eur:before{content:"\20ac"}.glyphicon-minus:before{content:"\2212"}.glyphicon-cloud:before{content:"\2601"}.glyphicon-envelope:before{content:"\2709"}.glyphicon-pencil:before{content:"\270f"}.glyphicon-glass:before{content:"\e001"}.glyphicon-music:before{content:"\e002"}.glyphicon-search:before{content:"\e003"}.glyphicon-heart:before{content:"\e005"}.glyphicon-star:before{content:"\e006"}.glyphicon-star-empty:before{content:"\e007"}.glyphicon-user:before{content:"\e008"}.glyphicon-film:before{content:"\e009"}.glyphicon-th-large:before{content:"\e010"}.glyphicon-th:before{content:"\e011"}.glyphicon-th-list:before{content:"\e012"}.glyphicon-ok:before{content:"\e013"}.glyphicon-remove:before{content:"\e014"}.glyphicon-zoom-in:before{content:"\e015"}.glyphicon-zoom-out:before{content:"\e016"}.glyphicon-off:before{content:"\e017"}.glyphicon-signal:before{content:"\e018"}.glyphicon-cog:before{content:"\e019"}.glyphicon-trash:before{content:"\e020"}.glyphicon-home:before{content:"\e021"}.glyphicon-file:before{content:"\e022"}.glyphicon-time:before{content:"\e023"}.glyphicon-road:before{content:"\e024"}.glyphicon-download-alt:before{content:"\e025"}.glyphicon-download:before{content:"\e026"}.glyphicon-upload:before{content:"\e027"}.glyphicon-inbox:before{content:"\e028"}.glyphicon-play-circle:before{content:"\e029"}.glyphicon-repeat:before{content:"\e030"}.glyphicon-refresh:before{content:"\e031"}.glyphicon-list-alt:before{content:"\e032"}.glyphicon-lock:before{content:"\e033"}.glyphicon-flag:before{content:"\e034"}.glyphicon-headphones:before{content:"\e035"}.glyphicon-volume-off:before{content:"\e036"}.glyphicon-volume-down:before{content:"\e037"}.glyphicon-volume-up:before{content:"\e038"}.glyphicon-qrcode:before{content:"\e039"}.glyphicon-barcode:before{content:"\e040"}.glyphicon-tag:before{content:"\e041"}.glyphicon-tags:before{content:"\e042"}.glyphicon-book:before{content:"\e043"}.glyphicon-bookmark:before{content:"\e044"}.glyphicon-print:before{content:"\e045"}.glyphicon-camera:before{content:"\e046"}.glyphicon-font:before{content:"\e047"}.glyphicon-bold:before{content:"\e048"}.glyphicon-italic:before{content:"\e049"}.glyphicon-text-height:before{content:"\e050"}.glyphicon-text-width:before{content:"\e051"}.glyphicon-align-left:before{content:"\e052"}.glyphicon-align-center:before{content:"\e053"}.glyphicon-align-right:before{content:"\e054"}.glyphicon-align-justify:before{content:"\e055"}.glyphicon-list:before{content:"\e056"}.glyphicon-indent-left:before{content:"\e057"}.glyphicon-indent-right:before{content:"\e058"}.glyphicon-facetime-video:before{content:"\e059"}.glyphicon-picture:before{content:"\e060"}.glyphicon-map-marker:before{content:"\e062"}.glyphicon-adjust:before{content:"\e063"}.glyphicon-tint:before{content:"\e064"}.glyphicon-edit:before{content:"\e065"}.glyphicon-share:before{content:"\e066"}.glyphicon-check:before{content:"\e067"}.glyphicon-move:before{content:"\e068"}.glyphicon-step-backward:before{content:"\e069"}.glyphicon-fast-backward:before{content:"\e070"}.glyphicon-backward:before{content:"\e071"}.glyphicon-play:before{content:"\e072"}.glyphicon-pause:before{content:"\e073"}.glyphicon-stop:before{content:"\e074"}.glyphicon-forward:before{content:"\e075"}.glyphicon-fast-forward:before{content:"\e076"}.glyphicon-step-forward:before{content:"\e077"}.glyphicon-eject:before{content:"\e078"}.glyphicon-chevron-left:before{content:"\e079"}.glyphicon-chevron-right:before{content:"\e080"}.glyphicon-plus-sign:before{content:"\e081"}.glyphicon-minus-sign:before{content:"\e082"}.glyphicon-remove-sign:before{content:"\e083"}.glyphicon-ok-sign:before{content:"\e084"}.glyphicon-question-sign:before{content:"\e085"}.glyphicon-info-sign:before{content:"\e086"}.glyphicon-screenshot:before{content:"\e087"}.glyphicon-remove-circle:before{content:"\e088"}.glyphicon-ok-circle:before{content:"\e089"}.glyphicon-ban-circle:before{content:"\e090"}.glyphicon-arrow-left:before{content:"\e091"}.glyphicon-arrow-right:before{content:"\e092"}.glyphicon-arrow-up:before{content:"\e093"}.glyphicon-arrow-down:before{content:"\e094"}.glyphicon-share-alt:before{content:"\e095"}.glyphicon-resize-full:before{content:"\e096"}.glyphicon-resize-small:before{content:"\e097"}.glyphicon-exclamation-sign:before{content:"\e101"}.glyphicon-gift:before{content:"\e102"}.glyphicon-leaf:before{content:"\e103"}.glyphicon-fire:before{content:"\e104"}.glyphicon-eye-open:before{content:"\e105"}.glyphicon-eye-close:before{content:"\e106"}.glyphicon-warning-sign:before{content:"\e107"}.glyphicon-plane:before{content:"\e108"}.glyphicon-calendar:before{content:"\e109"}.glyphicon-random:before{content:"\e110"}.glyphicon-comment:before{content:"\e111"}.glyphicon-magnet:before{content:"\e112"}.glyphicon-chevron-up:before{content:"\e113"}.glyphicon-chevron-down:before{content:"\e114"}.glyphicon-retweet:before{content:"\e115"}.glyphicon-shopping-cart:before{content:"\e116"}.glyphicon-folder-close:before{content:"\e117"}.glyphicon-folder-open:before{content:"\e118"}.glyphicon-resize-vertical:before{content:"\e119"}.glyphicon-resize-horizontal:before{content:"\e120"}.glyphicon-hdd:before{content:"\e121"}.glyphicon-bullhorn:before{content:"\e122"}.glyphicon-bell:before{content:"\e123"}.glyphicon-certificate:before{content:"\e124"}.glyphicon-thumbs-up:before{content:"\e125"}.glyphicon-thumbs-down:before{content:"\e126"}.glyphicon-hand-right:before{content:"\e127"}.glyphicon-hand-left:before{content:"\e128"}.glyphicon-hand-up:before{content:"\e129"}.glyphicon-hand-down:before{content:"\e130"}.glyphicon-circle-arrow-right:before{content:"\e131"}.glyphicon-circle-arrow-left:before{content:"\e132"}.glyphicon-circle-arrow-up:before{content:"\e133"}.glyphicon-circle-arrow-down:before{content:"\e134"}.glyphicon-globe:before{content:"\e135"}.glyphicon-wrench:before{content:"\e136"}.glyphicon-tasks:before{content:"\e137"}.glyphicon-filter:before{content:"\e138"}.glyphicon-briefcase:before{content:"\e139"}.glyphicon-fullscreen:before{content:"\e140"}.glyphicon-dashboard:before{content:"\e141"}.glyphicon-paperclip:before{content:"\e142"}.glyphicon-heart-empty:before{content:"\e143"}.glyphicon-link:before{content:"\e144"}.glyphicon-phone:before{content:"\e145"}.glyphicon-pushpin:before{content:"\e146"}.glyphicon-usd:before{content:"\e148"}.glyphicon-gbp:before{content:"\e149"}.glyphicon-sort:before{content:"\e150"}.glyphicon-sort-by-alphabet:before{content:"\e151"}.glyphicon-sort-by-alphabet-alt:before{content:"\e152"}.glyphicon-sort-by-order:before{content:"\e153"}.glyphicon-sort-by-order-alt:before{content:"\e154"}.glyphicon-sort-by-attributes:before{content:"\e155"}.glyphicon-sort-by-attributes-alt:before{content:"\e156"}.glyphicon-unchecked:before{content:"\e157"}.glyphicon-expand:before{content:"\e158"}.glyphicon-collapse-down:before{content:"\e159"}.glyphicon-collapse-up:before{content:"\e160"}.glyphicon-log-in:before{content:"\e161"}.glyphicon-flash:before{content:"\e162"}.glyphicon-log-out:before{content:"\e163"}.glyphicon-new-window:before{content:"\e164"}.glyphicon-record:before{content:"\e165"}.glyphicon-save:before{content:"\e166"}.glyphicon-open:before{content:"\e167"}.glyphicon-saved:before{content:"\e168"}.glyphicon-import:before{content:"\e169"}.glyphicon-export:before{content:"\e170"}.glyphicon-send:before{content:"\e171"}.glyphicon-floppy-disk:before{content:"\e172"}.glyphicon-floppy-saved:before{content:"\e173"}.glyphicon-floppy-remove:before{content:"\e174"}.glyphicon-floppy-save:before{content:"\e175"}.glyphicon-floppy-open:before{content:"\e176"}.glyphicon-credit-card:before{content:"\e177"}.glyphicon-transfer:before{content:"\e178"}.glyphicon-cutlery:before{content:"\e179"}.glyphicon-header:before{content:"\e180"}.glyphicon-compressed:before{content:"\e181"}.glyphicon-earphone:before{content:"\e182"}.glyphicon-phone-alt:before{content:"\e183"}.glyphicon-tower:before{content:"\e184"}.glyphicon-stats:before{content:"\e185"}.glyphicon-sd-video:before{content:"\e186"}.glyphicon-hd-video:before{content:"\e187"}.glyphicon-subtitles:before{content:"\e188"}.glyphicon-sound-stereo:before{content:"\e189"}.glyphicon-sound-dolby:before{content:"\e190"}.glyphicon-sound-5-1:before{content:"\e191"}.glyphicon-sound-6-1:before{content:"\e192"}.glyphicon-sound-7-1:before{content:"\e193"}.glyphicon-copyright-mark:before{content:"\e194"}.glyphicon-registration-mark:before{content:"\e195"}.glyphicon-cloud-download:before{content:"\e197"}.glyphicon-cloud-upload:before{content:"\e198"}.glyphicon-tree-conifer:before{content:"\e199"}.glyphicon-tree-deciduous:before{content:"\e200"}.glyphicon-cd:before{content:"\e201"}.glyphicon-save-file:before{content:"\e202"}.glyphicon-open-file:before{content:"\e203"}.glyphicon-level-up:before{content:"\e204"}.glyphicon-copy:before{content:"\e205"}.glyphicon-paste:before{content:"\e206"}.glyphicon-alert:before{content:"\e209"}.glyphicon-equalizer:before{content:"\e210"}.glyphicon-king:before{content:"\e211"}.glyphicon-queen:before{content:"\e212"}.glyphicon-pawn:before{content:"\e213"}.glyphicon-bishop:before{content:"\e214"}.glyphicon-knight:before{content:"\e215"}.glyphicon-baby-formula:before{content:"\e216"}.glyphicon-tent:before{content:"\26fa"}.glyphicon-blackboard:before{content:"\e218"}.glyphicon-bed:before{content:"\e219"}.glyphicon-apple:before{content:"\f8ff"}.glyphicon-erase:before{content:"\e221"}.glyphicon-hourglass:before{content:"\231b"}.glyphicon-lamp:before{content:"\e223"}.glyphicon-duplicate:before{content:"\e224"}.glyphicon-piggy-bank:before{content:"\e225"}.glyphicon-scissors:before{content:"\e226"}.glyphicon-bitcoin:before{content:"\e227"}.glyphicon-btc:before{content:"\e227"}.glyphicon-xbt:before{content:"\e227"}.glyphicon-yen:before{content:"\00a5"}.glyphicon-jpy:before{content:"\00a5"}.glyphicon-ruble:before{content:"\20bd"}.glyphicon-rub:before{content:"\20bd"}.glyphicon-scale:before{content:"\e230"}.glyphicon-ice-lolly:before{content:"\e231"}.glyphicon-ice-lolly-tasted:before{content:"\e232"}.glyphicon-education:before{content:"\e233"}.glyphicon-option-horizontal:before{content:"\e234"}.glyphicon-option-vertical:before{content:"\e235"}.glyphicon-menu-hamburger:before{content:"\e236"}.glyphicon-modal-window:before{content:"\e237"}.glyphicon-oil:before{content:"\e238"}.glyphicon-grain:before{content:"\e239"}.glyphicon-sunglasses:before{content:"\e240"}.glyphicon-text-size:before{content:"\e241"}.glyphicon-text-color:before{content:"\e242"}.glyphicon-text-background:before{content:"\e243"}.glyphicon-object-align-top:before{content:"\e244"}.glyphicon-object-align-bottom:before{content:"\e245"}.glyphicon-object-align-horizontal:before{content:"\e246"}.glyphicon-object-align-left:before{content:"\e247"}.glyphicon-object-align-vertical:before{content:"\e248"}.glyphicon-object-align-right:before{content:"\e249"}.glyphicon-triangle-right:before{content:"\e250"}.glyphicon-triangle-left:before{content:"\e251"}.glyphicon-triangle-bottom:before{content:"\e252"}.glyphicon-triangle-top:before{content:"\e253"}.glyphicon-console:before{content:"\e254"}.glyphicon-superscript:before{content:"\e255"}.glyphicon-subscript:before{content:"\e256"}.glyphicon-menu-left:before{content:"\e257"}.glyphicon-menu-right:before{content:"\e258"}.glyphicon-menu-down:before{content:"\e259"}.glyphicon-menu-up:before{content:"\e260"}*{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}*:before,*:after{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}html{font-size:10px;-webkit-tap-highlight-color:rgba(0,0,0,0)}body{font-family:"Lato","Helvetica Neue",Helvetica,Arial,sans-serif;font-size:15px;line-height:1.42857143;color:#ffffff;background-color:#222222}input,button,select,textarea{font-family:inherit;font-size:inherit;line-height:inherit}a{color:#0ce3ac;text-decoration:none}a:hover,a:focus{color:#0ce3ac;text-decoration:underline}a:focus{outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}figure{margin:0}img{vertical-align:middle}.img-responsive,.thumbnail>img,.thumbnail a>img,.carousel-inner>.item>img,.carousel-inner>.item>a>img{display:block;max-width:100%;height:auto}.img-rounded{border-radius:6px}.img-thumbnail{padding:2px;line-height:1.42857143;background-color:#222222;border:1px solid #464545;border-radius:4px;-webkit-transition:all .2s ease-in-out;-o-transition:all .2s ease-in-out;transition:all .2s ease-in-out;display:inline-block;max-width:100%;height:auto}.img-circle{border-radius:50%}hr{margin-top:21px;margin-bottom:21px;border:0;border-top:1px solid #464545}.sr-only{position:absolute;width:1px;height:1px;margin:-1px;padding:0;overflow:hidden;clip:rect(0, 0, 0, 0);border:0}.sr-only-focusable:active,.sr-only-focusable:focus{position:static;width:auto;height:auto;margin:0;overflow:visible;clip:auto}[role="button"]{cursor:pointer}h1,h2,h3,h4,h5,h6,.h1,.h2,.h3,.h4,.h5,.h6{font-family:"Lato","Helvetica Neue",Helvetica,Arial,sans-serif;font-weight:400;line-height:1.1;color:inherit}h1 small,h2 small,h3 small,h4 small,h5 small,h6 small,.h1 small,.h2 small,.h3 small,.h4 small,.h5 small,.h6 small,h1 .small,h2 .small,h3 .small,h4 .small,h5 .small,h6 .small,.h1 .small,.h2 .small,.h3 .small,.h4 .small,.h5 .small,.h6 .small{font-weight:normal;line-height:1;color:#999999}h1,.h1,h2,.h2,h3,.h3{margin-top:21px;margin-bottom:10.5px}h1 small,.h1 small,h2 small,.h2 small,h3 small,.h3 small,h1 .small,.h1 .small,h2 .small,.h2 .small,h3 .small,.h3 .small{font-size:65%}h4,.h4,h5,.h5,h6,.h6{margin-top:10.5px;margin-bottom:10.5px}h4 small,.h4 small,h5 small,.h5 small,h6 small,.h6 small,h4 .small,.h4 .small,h5 .small,.h5 .small,h6 .small,.h6 .small{font-size:75%}h1,.h1{font-size:39px}h2,.h2{font-size:32px}h3,.h3{font-size:26px}h4,.h4{font-size:19px}h5,.h5{font-size:15px}h6,.h6{font-size:13px}p{margin:0 0 10.5px}.lead{margin-bottom:21px;font-size:17px;font-weight:300;line-height:1.4}@media (min-width:768px){.lead{font-size:22.5px}}small,.small{font-size:86%}mark,.mark{background-color:#f39c12;padding:.2em}.text-left{text-align:left}.text-right{text-align:right}.text-center{text-align:center}.text-justify{text-align:justify}.text-nowrap{white-space:nowrap}.text-lowercase{text-transform:lowercase}.text-uppercase{text-transform:uppercase}.text-capitalize{text-transform:capitalize}.text-muted{color:#999999}.text-primary{color:#375a7f}a.text-primary:hover,a.text-primary:focus{color:#28415b}.text-success{color:#ffffff}a.text-success:hover,a.text-success:focus{color:#e6e6e6}.text-info{color:#ffffff}a.text-info:hover,a.text-info:focus{color:#e6e6e6}.text-warning{color:#ffffff}a.text-warning:hover,a.text-warning:focus{color:#e6e6e6}.text-danger{color:#ffffff}a.text-danger:hover,a.text-danger:focus{color:#e6e6e6}.bg-primary{color:#fff;background-color:#375a7f}a.bg-primary:hover,a.bg-primary:focus{background-color:#28415b}.bg-success{background-color:#00bc8c}a.bg-success:hover,a.bg-success:focus{background-color:#008966}.bg-info{background-color:#3498db}a.bg-info:hover,a.bg-info:focus{background-color:#217dbb}.bg-warning{background-color:#f39c12}a.bg-warning:hover,a.bg-warning:focus{background-color:#c87f0a}.bg-danger{background-color:#e74c3c}a.bg-danger:hover,a.bg-danger:focus{background-color:#d62c1a}.page-header{padding-bottom:9.5px;margin:42px 0 21px;border-bottom:1px solid transparent}ul,ol{margin-top:0;margin-bottom:10.5px}ul ul,ol ul,ul ol,ol ol{margin-bottom:0}.list-unstyled{padding-left:0;list-style:none}.list-inline{padding-left:0;list-style:none;margin-left:-5px}.list-inline>li{display:inline-block;padding-left:5px;padding-right:5px}dl{margin-top:0;margin-bottom:21px}dt,dd{line-height:1.42857143}dt{font-weight:bold}dd{margin-left:0}@media (min-width:768px){.dl-horizontal dt{float:left;width:160px;clear:left;text-align:right;overflow:hidden;text-overflow:ellipsis;white-space:nowrap}.dl-horizontal dd{margin-left:180px}}abbr[title],abbr[data-original-title]{cursor:help;border-bottom:1px dotted #999999}.initialism{font-size:90%;text-transform:uppercase}blockquote{padding:10.5px 21px;margin:0 0 21px;font-size:18.75px;border-left:5px solid #464545}blockquote p:last-child,blockquote ul:last-child,blockquote ol:last-child{margin-bottom:0}blockquote footer,blockquote small,blockquote .small{display:block;font-size:80%;line-height:1.42857143;color:#999999}blockquote footer:before,blockquote small:before,blockquote .small:before{content:'\2014 \00A0'}.blockquote-reverse,blockquote.pull-right{padding-right:15px;padding-left:0;border-right:5px solid #464545;border-left:0;text-align:right}.blockquote-reverse footer:before,blockquote.pull-right footer:before,.blockquote-reverse small:before,blockquote.pull-right small:before,.blockquote-reverse .small:before,blockquote.pull-right .small:before{content:''}.blockquote-reverse footer:after,blockquote.pull-right footer:after,.blockquote-reverse small:after,blockquote.pull-right small:after,.blockquote-reverse .small:after,blockquote.pull-right .small:after{content:'\00A0 \2014'}address{margin-bottom:21px;font-style:normal;line-height:1.42857143}code,kbd,pre,samp{font-family:Menlo,Monaco,Consolas,"Courier New",monospace}code{padding:2px 4px;font-size:90%;color:#c7254e;background-color:#f9f2f4;border-radius:4px}kbd{padding:2px 4px;font-size:90%;color:#ffffff;background-color:#333333;border-radius:3px;-webkit-box-shadow:inset 0 -1px 0 rgba(0,0,0,0.25);box-shadow:inset 0 -1px 0 rgba(0,0,0,0.25)}kbd kbd{padding:0;font-size:100%;font-weight:bold;-webkit-box-shadow:none;box-shadow:none}pre{display:block;padding:10px;margin:0 0 10.5px;font-size:14px;line-height:1.42857143;word-break:break-all;word-wrap:break-word;color:#303030;background-color:#ebebeb;border:1px solid #cccccc;border-radius:4px}pre code{padding:0;font-size:inherit;color:inherit;white-space:pre-wrap;background-color:transparent;border-radius:0}.pre-scrollable{max-height:340px;overflow-y:scroll}.container{margin-right:auto;margin-left:auto;padding-left:15px;padding-right:15px}@media (min-width:768px){.container{width:750px}}@media (min-width:992px){.container{width:970px}}@media (min-width:1200px){.container{width:1170px}}.container-fluid{margin-right:auto;margin-left:auto;padding-left:15px;padding-right:15px}.row{margin-left:-15px;margin-right:-15px}.col-xs-1,.col-sm-1,.col-md-1,.col-lg-1,.col-xs-2,.col-sm-2,.col-md-2,.col-lg-2,.col-xs-3,.col-sm-3,.col-md-3,.col-lg-3,.col-xs-4,.col-sm-4,.col-md-4,.col-lg-4,.col-xs-5,.col-sm-5,.col-md-5,.col-lg-5,.col-xs-6,.col-sm-6,.col-md-6,.col-lg-6,.col-xs-7,.col-sm-7,.col-md-7,.col-lg-7,.col-xs-8,.col-sm-8,.col-md-8,.col-lg-8,.col-xs-9,.col-sm-9,.col-md-9,.col-lg-9,.col-xs-10,.col-sm-10,.col-md-10,.col-lg-10,.col-xs-11,.col-sm-11,.col-md-11,.col-lg-11,.col-xs-12,.col-sm-12,.col-md-12,.col-lg-12{position:relative;min-height:1px;padding-left:15px;padding-right:15px}.col-xs-1,.col-xs-2,.col-xs-3,.col-xs-4,.col-xs-5,.col-xs-6,.col-xs-7,.col-xs-8,.col-xs-9,.col-xs-10,.col-xs-11,.col-xs-12{float:left}.col-xs-12{width:100%}.col-xs-11{width:91.66666667%}.col-xs-10{width:83.33333333%}.col-xs-9{width:75%}.col-xs-8{width:66.66666667%}.col-xs-7{width:58.33333333%}.col-xs-6{width:50%}.col-xs-5{width:41.66666667%}.col-xs-4{width:33.33333333%}.col-xs-3{width:25%}.col-xs-2{width:16.66666667%}.col-xs-1{width:8.33333333%}.col-xs-pull-12{right:100%}.col-xs-pull-11{right:91.66666667%}.col-xs-pull-10{right:83.33333333%}.col-xs-pull-9{right:75%}.col-xs-pull-8{right:66.66666667%}.col-xs-pull-7{right:58.33333333%}.col-xs-pull-6{right:50%}.col-xs-pull-5{right:41.66666667%}.col-xs-pull-4{right:33.33333333%}.col-xs-pull-3{right:25%}.col-xs-pull-2{right:16.66666667%}.col-xs-pull-1{right:8.33333333%}.col-xs-pull-0{right:auto}.col-xs-push-12{left:100%}.col-xs-push-11{left:91.66666667%}.col-xs-push-10{left:83.33333333%}.col-xs-push-9{left:75%}.col-xs-push-8{left:66.66666667%}.col-xs-push-7{left:58.33333333%}.col-xs-push-6{left:50%}.col-xs-push-5{left:41.66666667%}.col-xs-push-4{left:33.33333333%}.col-xs-push-3{left:25%}.col-xs-push-2{left:16.66666667%}.col-xs-push-1{left:8.33333333%}.col-xs-push-0{left:auto}.col-xs-offset-12{margin-left:100%}.col-xs-offset-11{margin-left:91.66666667%}.col-xs-offset-10{margin-left:83.33333333%}.col-xs-offset-9{margin-left:75%}.col-xs-offset-8{margin-left:66.66666667%}.col-xs-offset-7{margin-left:58.33333333%}.col-xs-offset-6{margin-left:50%}.col-xs-offset-5{margin-left:41.66666667%}.col-xs-offset-4{margin-left:33.33333333%}.col-xs-offset-3{margin-left:25%}.col-xs-offset-2{margin-left:16.66666667%}.col-xs-offset-1{margin-left:8.33333333%}.col-xs-offset-0{margin-left:0%}@media (min-width:768px){.col-sm-1,.col-sm-2,.col-sm-3,.col-sm-4,.col-sm-5,.col-sm-6,.col-sm-7,.col-sm-8,.col-sm-9,.col-sm-10,.col-sm-11,.col-sm-12{float:left}.col-sm-12{width:100%}.col-sm-11{width:91.66666667%}.col-sm-10{width:83.33333333%}.col-sm-9{width:75%}.col-sm-8{width:66.66666667%}.col-sm-7{width:58.33333333%}.col-sm-6{width:50%}.col-sm-5{width:41.66666667%}.col-sm-4{width:33.33333333%}.col-sm-3{width:25%}.col-sm-2{width:16.66666667%}.col-sm-1{width:8.33333333%}.col-sm-pull-12{right:100%}.col-sm-pull-11{right:91.66666667%}.col-sm-pull-10{right:83.33333333%}.col-sm-pull-9{right:75%}.col-sm-pull-8{right:66.66666667%}.col-sm-pull-7{right:58.33333333%}.col-sm-pull-6{right:50%}.col-sm-pull-5{right:41.66666667%}.col-sm-pull-4{right:33.33333333%}.col-sm-pull-3{right:25%}.col-sm-pull-2{right:16.66666667%}.col-sm-pull-1{right:8.33333333%}.col-sm-pull-0{right:auto}.col-sm-push-12{left:100%}.col-sm-push-11{left:91.66666667%}.col-sm-push-10{left:83.33333333%}.col-sm-push-9{left:75%}.col-sm-push-8{left:66.66666667%}.col-sm-push-7{left:58.33333333%}.col-sm-push-6{left:50%}.col-sm-push-5{left:41.66666667%}.col-sm-push-4{left:33.33333333%}.col-sm-push-3{left:25%}.col-sm-push-2{left:16.66666667%}.col-sm-push-1{left:8.33333333%}.col-sm-push-0{left:auto}.col-sm-offset-12{margin-left:100%}.col-sm-offset-11{margin-left:91.66666667%}.col-sm-offset-10{margin-left:83.33333333%}.col-sm-offset-9{margin-left:75%}.col-sm-offset-8{margin-left:66.66666667%}.col-sm-offset-7{margin-left:58.33333333%}.col-sm-offset-6{margin-left:50%}.col-sm-offset-5{margin-left:41.66666667%}.col-sm-offset-4{margin-left:33.33333333%}.col-sm-offset-3{margin-left:25%}.col-sm-offset-2{margin-left:16.66666667%}.col-sm-offset-1{margin-left:8.33333333%}.col-sm-offset-0{margin-left:0%}}@media (min-width:992px){.col-md-1,.col-md-2,.col-md-3,.col-md-4,.col-md-5,.col-md-6,.col-md-7,.col-md-8,.col-md-9,.col-md-10,.col-md-11,.col-md-12{float:left}.col-md-12{width:100%}.col-md-11{width:91.66666667%}.col-md-10{width:83.33333333%}.col-md-9{width:75%}.col-md-8{width:66.66666667%}.col-md-7{width:58.33333333%}.col-md-6{width:50%}.col-md-5{width:41.66666667%}.col-md-4{width:33.33333333%}.col-md-3{width:25%}.col-md-2{width:16.66666667%}.col-md-1{width:8.33333333%}.col-md-pull-12{right:100%}.col-md-pull-11{right:91.66666667%}.col-md-pull-10{right:83.33333333%}.col-md-pull-9{right:75%}.col-md-pull-8{right:66.66666667%}.col-md-pull-7{right:58.33333333%}.col-md-pull-6{right:50%}.col-md-pull-5{right:41.66666667%}.col-md-pull-4{right:33.33333333%}.col-md-pull-3{right:25%}.col-md-pull-2{right:16.66666667%}.col-md-pull-1{right:8.33333333%}.col-md-pull-0{right:auto}.col-md-push-12{left:100%}.col-md-push-11{left:91.66666667%}.col-md-push-10{left:83.33333333%}.col-md-push-9{left:75%}.col-md-push-8{left:66.66666667%}.col-md-push-7{left:58.33333333%}.col-md-push-6{left:50%}.col-md-push-5{left:41.66666667%}.col-md-push-4{left:33.33333333%}.col-md-push-3{left:25%}.col-md-push-2{left:16.66666667%}.col-md-push-1{left:8.33333333%}.col-md-push-0{left:auto}.col-md-offset-12{margin-left:100%}.col-md-offset-11{margin-left:91.66666667%}.col-md-offset-10{margin-left:83.33333333%}.col-md-offset-9{margin-left:75%}.col-md-offset-8{margin-left:66.66666667%}.col-md-offset-7{margin-left:58.33333333%}.col-md-offset-6{margin-left:50%}.col-md-offset-5{margin-left:41.66666667%}.col-md-offset-4{margin-left:33.33333333%}.col-md-offset-3{margin-left:25%}.col-md-offset-2{margin-left:16.66666667%}.col-md-offset-1{margin-left:8.33333333%}.col-md-offset-0{margin-left:0%}}@media (min-width:1200px){.col-lg-1,.col-lg-2,.col-lg-3,.col-lg-4,.col-lg-5,.col-lg-6,.col-lg-7,.col-lg-8,.col-lg-9,.col-lg-10,.col-lg-11,.col-lg-12{float:left}.col-lg-12{width:100%}.col-lg-11{width:91.66666667%}.col-lg-10{width:83.33333333%}.col-lg-9{width:75%}.col-lg-8{width:66.66666667%}.col-lg-7{width:58.33333333%}.col-lg-6{width:50%}.col-lg-5{width:41.66666667%}.col-lg-4{width:33.33333333%}.col-lg-3{width:25%}.col-lg-2{width:16.66666667%}.col-lg-1{width:8.33333333%}.col-lg-pull-12{right:100%}.col-lg-pull-11{right:91.66666667%}.col-lg-pull-10{right:83.33333333%}.col-lg-pull-9{right:75%}.col-lg-pull-8{right:66.66666667%}.col-lg-pull-7{right:58.33333333%}.col-lg-pull-6{right:50%}.col-lg-pull-5{right:41.66666667%}.col-lg-pull-4{right:33.33333333%}.col-lg-pull-3{right:25%}.col-lg-pull-2{right:16.66666667%}.col-lg-pull-1{right:8.33333333%}.col-lg-pull-0{right:auto}.col-lg-push-12{left:100%}.col-lg-push-11{left:91.66666667%}.col-lg-push-10{left:83.33333333%}.col-lg-push-9{left:75%}.col-lg-push-8{left:66.66666667%}.col-lg-push-7{left:58.33333333%}.col-lg-push-6{left:50%}.col-lg-push-5{left:41.66666667%}.col-lg-push-4{left:33.33333333%}.col-lg-push-3{left:25%}.col-lg-push-2{left:16.66666667%}.col-lg-push-1{left:8.33333333%}.col-lg-push-0{left:auto}.col-lg-offset-12{margin-left:100%}.col-lg-offset-11{margin-left:91.66666667%}.col-lg-offset-10{margin-left:83.33333333%}.col-lg-offset-9{margin-left:75%}.col-lg-offset-8{margin-left:66.66666667%}.col-lg-offset-7{margin-left:58.33333333%}.col-lg-offset-6{margin-left:50%}.col-lg-offset-5{margin-left:41.66666667%}.col-lg-offset-4{margin-left:33.33333333%}.col-lg-offset-3{margin-left:25%}.col-lg-offset-2{margin-left:16.66666667%}.col-lg-offset-1{margin-left:8.33333333%}.col-lg-offset-0{margin-left:0%}}table{background-color:transparent}caption{padding-top:8px;padding-bottom:8px;color:#999999;text-align:left}th{text-align:left}.table{width:100%;max-width:100%;margin-bottom:21px}.table>thead>tr>th,.table>tbody>tr>th,.table>tfoot>tr>th,.table>thead>tr>td,.table>tbody>tr>td,.table>tfoot>tr>td{padding:8px;line-height:1.42857143;vertical-align:top;border-top:1px solid #464545}.table>thead>tr>th{vertical-align:bottom;border-bottom:2px solid #464545}.table>caption+thead>tr:first-child>th,.table>colgroup+thead>tr:first-child>th,.table>thead:first-child>tr:first-child>th,.table>caption+thead>tr:first-child>td,.table>colgroup+thead>tr:first-child>td,.table>thead:first-child>tr:first-child>td{border-top:0}.table>tbody+tbody{border-top:2px solid #464545}.table .table{background-color:#222222}.table-condensed>thead>tr>th,.table-condensed>tbody>tr>th,.table-condensed>tfoot>tr>th,.table-condensed>thead>tr>td,.table-condensed>tbody>tr>td,.table-condensed>tfoot>tr>td{padding:5px}.table-bordered{border:1px solid #464545}.table-bordered>thead>tr>th,.table-bordered>tbody>tr>th,.table-bordered>tfoot>tr>th,.table-bordered>thead>tr>td,.table-bordered>tbody>tr>td,.table-bordered>tfoot>tr>td{border:1px solid #464545}.table-bordered>thead>tr>th,.table-bordered>thead>tr>td{border-bottom-width:2px}.table-striped>tbody>tr:nth-of-type(odd){background-color:#3d3d3d}.table-hover>tbody>tr:hover{background-color:#464545}table col[class*="col-"]{position:static;float:none;display:table-column}table td[class*="col-"],table th[class*="col-"]{position:static;float:none;display:table-cell}.table>thead>tr>td.active,.table>tbody>tr>td.active,.table>tfoot>tr>td.active,.table>thead>tr>th.active,.table>tbody>tr>th.active,.table>tfoot>tr>th.active,.table>thead>tr.active>td,.table>tbody>tr.active>td,.table>tfoot>tr.active>td,.table>thead>tr.active>th,.table>tbody>tr.active>th,.table>tfoot>tr.active>th{background-color:#464545}.table-hover>tbody>tr>td.active:hover,.table-hover>tbody>tr>th.active:hover,.table-hover>tbody>tr.active:hover>td,.table-hover>tbody>tr:hover>.active,.table-hover>tbody>tr.active:hover>th{background-color:#393838}.table>thead>tr>td.success,.table>tbody>tr>td.success,.table>tfoot>tr>td.success,.table>thead>tr>th.success,.table>tbody>tr>th.success,.table>tfoot>tr>th.success,.table>thead>tr.success>td,.table>tbody>tr.success>td,.table>tfoot>tr.success>td,.table>thead>tr.success>th,.table>tbody>tr.success>th,.table>tfoot>tr.success>th{background-color:#00bc8c}.table-hover>tbody>tr>td.success:hover,.table-hover>tbody>tr>th.success:hover,.table-hover>tbody>tr.success:hover>td,.table-hover>tbody>tr:hover>.success,.table-hover>tbody>tr.success:hover>th{background-color:#00a379}.table>thead>tr>td.info,.table>tbody>tr>td.info,.table>tfoot>tr>td.info,.table>thead>tr>th.info,.table>tbody>tr>th.info,.table>tfoot>tr>th.info,.table>thead>tr.info>td,.table>tbody>tr.info>td,.table>tfoot>tr.info>td,.table>thead>tr.info>th,.table>tbody>tr.info>th,.table>tfoot>tr.info>th{background-color:#3498db}.table-hover>tbody>tr>td.info:hover,.table-hover>tbody>tr>th.info:hover,.table-hover>tbody>tr.info:hover>td,.table-hover>tbody>tr:hover>.info,.table-hover>tbody>tr.info:hover>th{background-color:#258cd1}.table>thead>tr>td.warning,.table>tbody>tr>td.warning,.table>tfoot>tr>td.warning,.table>thead>tr>th.warning,.table>tbody>tr>th.warning,.table>tfoot>tr>th.warning,.table>thead>tr.warning>td,.table>tbody>tr.warning>td,.table>tfoot>tr.warning>td,.table>thead>tr.warning>th,.table>tbody>tr.warning>th,.table>tfoot>tr.warning>th{background-color:#f39c12}.table-hover>tbody>tr>td.warning:hover,.table-hover>tbody>tr>th.warning:hover,.table-hover>tbody>tr.warning:hover>td,.table-hover>tbody>tr:hover>.warning,.table-hover>tbody>tr.warning:hover>th{background-color:#e08e0b}.table>thead>tr>td.danger,.table>tbody>tr>td.danger,.table>tfoot>tr>td.danger,.table>thead>tr>th.danger,.table>tbody>tr>th.danger,.table>tfoot>tr>th.danger,.table>thead>tr.danger>td,.table>tbody>tr.danger>td,.table>tfoot>tr.danger>td,.table>thead>tr.danger>th,.table>tbody>tr.danger>th,.table>tfoot>tr.danger>th{background-color:#e74c3c}.table-hover>tbody>tr>td.danger:hover,.table-hover>tbody>tr>th.danger:hover,.table-hover>tbody>tr.danger:hover>td,.table-hover>tbody>tr:hover>.danger,.table-hover>tbody>tr.danger:hover>th{background-color:#e43725}.table-responsive{overflow-x:auto;min-height:0.01%}@media screen and (max-width:767px){.table-responsive{width:100%;margin-bottom:15.75px;overflow-y:hidden;-ms-overflow-style:-ms-autohiding-scrollbar;border:1px solid #464545}.table-responsive>.table{margin-bottom:0}.table-responsive>.table>thead>tr>th,.table-responsive>.table>tbody>tr>th,.table-responsive>.table>tfoot>tr>th,.table-responsive>.table>thead>tr>td,.table-responsive>.table>tbody>tr>td,.table-responsive>.table>tfoot>tr>td{white-space:nowrap}.table-responsive>.table-bordered{border:0}.table-responsive>.table-bordered>thead>tr>th:first-child,.table-responsive>.table-bordered>tbody>tr>th:first-child,.table-responsive>.table-bordered>tfoot>tr>th:first-child,.table-responsive>.table-bordered>thead>tr>td:first-child,.table-responsive>.table-bordered>tbody>tr>td:first-child,.table-responsive>.table-bordered>tfoot>tr>td:first-child{border-left:0}.table-responsive>.table-bordered>thead>tr>th:last-child,.table-responsive>.table-bordered>tbody>tr>th:last-child,.table-responsive>.table-bordered>tfoot>tr>th:last-child,.table-responsive>.table-bordered>thead>tr>td:last-child,.table-responsive>.table-bordered>tbody>tr>td:last-child,.table-responsive>.table-bordered>tfoot>tr>td:last-child{border-right:0}.table-responsive>.table-bordered>tbody>tr:last-child>th,.table-responsive>.table-bordered>tfoot>tr:last-child>th,.table-responsive>.table-bordered>tbody>tr:last-child>td,.table-responsive>.table-bordered>tfoot>tr:last-child>td{border-bottom:0}}fieldset{padding:0;margin:0;border:0;min-width:0}legend{display:block;width:100%;padding:0;margin-bottom:21px;font-size:22.5px;line-height:inherit;color:#ffffff;border:0;border-bottom:1px solid transparent}label{display:inline-block;max-width:100%;margin-bottom:5px;font-weight:bold}input[type="search"]{-webkit-box-sizing:border-box;-moz-box-sizing:border-box;box-sizing:border-box}input[type="radio"],input[type="checkbox"]{margin:4px 0 0;margin-top:1px \9;line-height:normal}input[type="file"]{display:block}input[type="range"]{display:block;width:100%}select[multiple],select[size]{height:auto}input[type="file"]:focus,input[type="radio"]:focus,input[type="checkbox"]:focus{outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}output{display:block;padding-top:11px;font-size:15px;line-height:1.42857143;color:#464545}.form-control{display:block;width:100%;height:45px;padding:10px 15px;font-size:15px;line-height:1.42857143;color:#464545;background-color:#ffffff;background-image:none;border:1px solid #f1f1f1;border-radius:4px;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075);box-shadow:inset 0 1px 1px rgba(0,0,0,0.075);-webkit-transition:border-color ease-in-out .15s,-webkit-box-shadow ease-in-out .15s;-o-transition:border-color ease-in-out .15s,box-shadow ease-in-out .15s;transition:border-color ease-in-out .15s,box-shadow ease-in-out .15s}.form-control:focus{border-color:#ffffff;outline:0;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 8px rgba(255,255,255,0.6);box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 8px rgba(255,255,255,0.6)}.form-control::-moz-placeholder{color:#999999;opacity:1}.form-control:-ms-input-placeholder{color:#999999}.form-control::-webkit-input-placeholder{color:#999999}.form-control::-ms-expand{border:0;background-color:transparent}.form-control[disabled],.form-control[readonly],fieldset[disabled] .form-control{background-color:#ebebeb;opacity:1}.form-control[disabled],fieldset[disabled] .form-control{cursor:not-allowed}textarea.form-control{height:auto}input[type="search"]{-webkit-appearance:none}@media screen and (-webkit-min-device-pixel-ratio:0){input[type="date"].form-control,input[type="time"].form-control,input[type="datetime-local"].form-control,input[type="month"].form-control{line-height:45px}input[type="date"].input-sm,input[type="time"].input-sm,input[type="datetime-local"].input-sm,input[type="month"].input-sm,.input-group-sm input[type="date"],.input-group-sm input[type="time"],.input-group-sm input[type="datetime-local"],.input-group-sm input[type="month"]{line-height:35px}input[type="date"].input-lg,input[type="time"].input-lg,input[type="datetime-local"].input-lg,input[type="month"].input-lg,.input-group-lg input[type="date"],.input-group-lg input[type="time"],.input-group-lg input[type="datetime-local"],.input-group-lg input[type="month"]{line-height:66px}}.form-group{margin-bottom:15px}.radio,.checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.radio label,.checkbox label{min-height:21px;padding-left:20px;margin-bottom:0;font-weight:normal;cursor:pointer}.radio input[type="radio"],.radio-inline input[type="radio"],.checkbox input[type="checkbox"],.checkbox-inline input[type="checkbox"]{position:absolute;margin-left:-20px;margin-top:4px \9}.radio+.radio,.checkbox+.checkbox{margin-top:-5px}.radio-inline,.checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;vertical-align:middle;font-weight:normal;cursor:pointer}.radio-inline+.radio-inline,.checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px}input[type="radio"][disabled],input[type="checkbox"][disabled],input[type="radio"].disabled,input[type="checkbox"].disabled,fieldset[disabled] input[type="radio"],fieldset[disabled] input[type="checkbox"]{cursor:not-allowed}.radio-inline.disabled,.checkbox-inline.disabled,fieldset[disabled] .radio-inline,fieldset[disabled] .checkbox-inline{cursor:not-allowed}.radio.disabled label,.checkbox.disabled label,fieldset[disabled] .radio label,fieldset[disabled] .checkbox label{cursor:not-allowed}.form-control-static{padding-top:11px;padding-bottom:11px;margin-bottom:0;min-height:36px}.form-control-static.input-lg,.form-control-static.input-sm{padding-left:0;padding-right:0}.input-sm{height:35px;padding:6px 9px;font-size:13px;line-height:1.5;border-radius:3px}select.input-sm{height:35px;line-height:35px}textarea.input-sm,select[multiple].input-sm{height:auto}.form-group-sm .form-control{height:35px;padding:6px 9px;font-size:13px;line-height:1.5;border-radius:3px}.form-group-sm select.form-control{height:35px;line-height:35px}.form-group-sm textarea.form-control,.form-group-sm select[multiple].form-control{height:auto}.form-group-sm .form-control-static{height:35px;min-height:34px;padding:7px 9px;font-size:13px;line-height:1.5}.input-lg{height:66px;padding:18px 27px;font-size:19px;line-height:1.3333333;border-radius:6px}select.input-lg{height:66px;line-height:66px}textarea.input-lg,select[multiple].input-lg{height:auto}.form-group-lg .form-control{height:66px;padding:18px 27px;font-size:19px;line-height:1.3333333;border-radius:6px}.form-group-lg select.form-control{height:66px;line-height:66px}.form-group-lg textarea.form-control,.form-group-lg select[multiple].form-control{height:auto}.form-group-lg .form-control-static{height:66px;min-height:40px;padding:19px 27px;font-size:19px;line-height:1.3333333}.has-feedback{position:relative}.has-feedback .form-control{padding-right:56.25px}.form-control-feedback{position:absolute;top:0;right:0;z-index:2;display:block;width:45px;height:45px;line-height:45px;text-align:center;pointer-events:none}.input-lg+.form-control-feedback,.input-group-lg+.form-control-feedback,.form-group-lg .form-control+.form-control-feedback{width:66px;height:66px;line-height:66px}.input-sm+.form-control-feedback,.input-group-sm+.form-control-feedback,.form-group-sm .form-control+.form-control-feedback{width:35px;height:35px;line-height:35px}.has-success .help-block,.has-success .control-label,.has-success .radio,.has-success .checkbox,.has-success .radio-inline,.has-success .checkbox-inline,.has-success.radio label,.has-success.checkbox label,.has-success.radio-inline label,.has-success.checkbox-inline label{color:#ffffff}.has-success .form-control{border-color:#ffffff;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075);box-shadow:inset 0 1px 1px rgba(0,0,0,0.075)}.has-success .form-control:focus{border-color:#e6e6e6;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff;box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff}.has-success .input-group-addon{color:#ffffff;border-color:#ffffff;background-color:#00bc8c}.has-success .form-control-feedback{color:#ffffff}.has-warning .help-block,.has-warning .control-label,.has-warning .radio,.has-warning .checkbox,.has-warning .radio-inline,.has-warning .checkbox-inline,.has-warning.radio label,.has-warning.checkbox label,.has-warning.radio-inline label,.has-warning.checkbox-inline label{color:#ffffff}.has-warning .form-control{border-color:#ffffff;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075);box-shadow:inset 0 1px 1px rgba(0,0,0,0.075)}.has-warning .form-control:focus{border-color:#e6e6e6;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff;box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff}.has-warning .input-group-addon{color:#ffffff;border-color:#ffffff;background-color:#f39c12}.has-warning .form-control-feedback{color:#ffffff}.has-error .help-block,.has-error .control-label,.has-error .radio,.has-error .checkbox,.has-error .radio-inline,.has-error .checkbox-inline,.has-error.radio label,.has-error.checkbox label,.has-error.radio-inline label,.has-error.checkbox-inline label{color:#ffffff}.has-error .form-control{border-color:#ffffff;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075);box-shadow:inset 0 1px 1px rgba(0,0,0,0.075)}.has-error .form-control:focus{border-color:#e6e6e6;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff;box-shadow:inset 0 1px 1px rgba(0,0,0,0.075),0 0 6px #fff}.has-error .input-group-addon{color:#ffffff;border-color:#ffffff;background-color:#e74c3c}.has-error .form-control-feedback{color:#ffffff}.has-feedback label~.form-control-feedback{top:26px}.has-feedback label.sr-only~.form-control-feedback{top:0}.help-block{display:block;margin-top:5px;margin-bottom:10px;color:#ffffff}@media (min-width:768px){.form-inline .form-group{display:inline-block;margin-bottom:0;vertical-align:middle}.form-inline .form-control{display:inline-block;width:auto;vertical-align:middle}.form-inline .form-control-static{display:inline-block}.form-inline .input-group{display:inline-table;vertical-align:middle}.form-inline .input-group .input-group-addon,.form-inline .input-group .input-group-btn,.form-inline .input-group .form-control{width:auto}.form-inline .input-group>.form-control{width:100%}.form-inline .control-label{margin-bottom:0;vertical-align:middle}.form-inline .radio,.form-inline .checkbox{display:inline-block;margin-top:0;margin-bottom:0;vertical-align:middle}.form-inline .radio label,.form-inline .checkbox label{padding-left:0}.form-inline .radio input[type="radio"],.form-inline .checkbox input[type="checkbox"]{position:relative;margin-left:0}.form-inline .has-feedback .form-control-feedback{top:0}}.form-horizontal .radio,.form-horizontal .checkbox,.form-horizontal .radio-inline,.form-horizontal .checkbox-inline{margin-top:0;margin-bottom:0;padding-top:11px}.form-horizontal .radio,.form-horizontal .checkbox{min-height:32px}.form-horizontal .form-group{margin-left:-15px;margin-right:-15px}@media (min-width:768px){.form-horizontal .control-label{text-align:right;margin-bottom:0;padding-top:11px}}.form-horizontal .has-feedback .form-control-feedback{right:15px}@media (min-width:768px){.form-horizontal .form-group-lg .control-label{padding-top:19px;font-size:19px}}@media (min-width:768px){.form-horizontal .form-group-sm .control-label{padding-top:7px;font-size:13px}}.btn{display:inline-block;margin-bottom:0;font-weight:normal;text-align:center;vertical-align:middle;-ms-touch-action:manipulation;touch-action:manipulation;cursor:pointer;background-image:none;border:1px solid transparent;white-space:nowrap;padding:10px 15px;font-size:15px;line-height:1.42857143;border-radius:4px;-webkit-user-select:none;-moz-user-select:none;-ms-user-select:none;user-select:none}.btn:focus,.btn:active:focus,.btn.active:focus,.btn.focus,.btn:active.focus,.btn.active.focus{outline:5px auto -webkit-focus-ring-color;outline-offset:-2px}.btn:hover,.btn:focus,.btn.focus{color:#ffffff;text-decoration:none}.btn:active,.btn.active{outline:0;background-image:none;-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,0.125);box-shadow:inset 0 3px 5px rgba(0,0,0,0.125)}.btn.disabled,.btn[disabled],fieldset[disabled] .btn{cursor:not-allowed;opacity:0.65;filter:alpha(opacity=65);-webkit-box-shadow:none;box-shadow:none}a.btn.disabled,fieldset[disabled] a.btn{pointer-events:none}.btn-default{color:#ffffff;background-color:#464545;border-color:#464545}.btn-default:focus,.btn-default.focus{color:#ffffff;background-color:#2c2c2c;border-color:#060606}.btn-default:hover{color:#ffffff;background-color:#2c2c2c;border-color:#272727}.btn-default:active,.btn-default.active,.open>.dropdown-toggle.btn-default{color:#ffffff;background-color:#2c2c2c;border-color:#272727}.btn-default:active:hover,.btn-default.active:hover,.open>.dropdown-toggle.btn-default:hover,.btn-default:active:focus,.btn-default.active:focus,.open>.dropdown-toggle.btn-default:focus,.btn-default:active.focus,.btn-default.active.focus,.open>.dropdown-toggle.btn-default.focus{color:#ffffff;background-color:#1a1a1a;border-color:#060606}.btn-default:active,.btn-default.active,.open>.dropdown-toggle.btn-default{background-image:none}.btn-default.disabled:hover,.btn-default[disabled]:hover,fieldset[disabled] .btn-default:hover,.btn-default.disabled:focus,.btn-default[disabled]:focus,fieldset[disabled] .btn-default:focus,.btn-default.disabled.focus,.btn-default[disabled].focus,fieldset[disabled] .btn-default.focus{background-color:#464545;border-color:#464545}.btn-default .badge{color:#464545;background-color:#ffffff}.btn-primary{color:#ffffff;background-color:#375a7f;border-color:#375a7f}.btn-primary:focus,.btn-primary.focus{color:#ffffff;background-color:#28415b;border-color:#101b26}.btn-primary:hover{color:#ffffff;background-color:#28415b;border-color:#253c54}.btn-primary:active,.btn-primary.active,.open>.dropdown-toggle.btn-primary{color:#ffffff;background-color:#28415b;border-color:#253c54}.btn-primary:active:hover,.btn-primary.active:hover,.open>.dropdown-toggle.btn-primary:hover,.btn-primary:active:focus,.btn-primary.active:focus,.open>.dropdown-toggle.btn-primary:focus,.btn-primary:active.focus,.btn-primary.active.focus,.open>.dropdown-toggle.btn-primary.focus{color:#ffffff;background-color:#1d2f43;border-color:#101b26}.btn-primary:active,.btn-primary.active,.open>.dropdown-toggle.btn-primary{background-image:none}.btn-primary.disabled:hover,.btn-primary[disabled]:hover,fieldset[disabled] .btn-primary:hover,.btn-primary.disabled:focus,.btn-primary[disabled]:focus,fieldset[disabled] .btn-primary:focus,.btn-primary.disabled.focus,.btn-primary[disabled].focus,fieldset[disabled] .btn-primary.focus{background-color:#375a7f;border-color:#375a7f}.btn-primary .badge{color:#375a7f;background-color:#ffffff}.btn-success{color:#ffffff;background-color:#00bc8c;border-color:#00bc8c}.btn-success:focus,.btn-success.focus{color:#ffffff;background-color:#008966;border-color:#003d2d}.btn-success:hover{color:#ffffff;background-color:#008966;border-color:#007f5e}.btn-success:active,.btn-success.active,.open>.dropdown-toggle.btn-success{color:#ffffff;background-color:#008966;border-color:#007f5e}.btn-success:active:hover,.btn-success.active:hover,.open>.dropdown-toggle.btn-success:hover,.btn-success:active:focus,.btn-success.active:focus,.open>.dropdown-toggle.btn-success:focus,.btn-success:active.focus,.btn-success.active.focus,.open>.dropdown-toggle.btn-success.focus{color:#ffffff;background-color:#00654b;border-color:#003d2d}.btn-success:active,.btn-success.active,.open>.dropdown-toggle.btn-success{background-image:none}.btn-success.disabled:hover,.btn-success[disabled]:hover,fieldset[disabled] .btn-success:hover,.btn-success.disabled:focus,.btn-success[disabled]:focus,fieldset[disabled] .btn-success:focus,.btn-success.disabled.focus,.btn-success[disabled].focus,fieldset[disabled] .btn-success.focus{background-color:#00bc8c;border-color:#00bc8c}.btn-success .badge{color:#00bc8c;background-color:#ffffff}.btn-info{color:#ffffff;background-color:#3498db;border-color:#3498db}.btn-info:focus,.btn-info.focus{color:#ffffff;background-color:#217dbb;border-color:#16527a}.btn-info:hover{color:#ffffff;background-color:#217dbb;border-color:#2077b2}.btn-info:active,.btn-info.active,.open>.dropdown-toggle.btn-info{color:#ffffff;background-color:#217dbb;border-color:#2077b2}.btn-info:active:hover,.btn-info.active:hover,.open>.dropdown-toggle.btn-info:hover,.btn-info:active:focus,.btn-info.active:focus,.open>.dropdown-toggle.btn-info:focus,.btn-info:active.focus,.btn-info.active.focus,.open>.dropdown-toggle.btn-info.focus{color:#ffffff;background-color:#1c699d;border-color:#16527a}.btn-info:active,.btn-info.active,.open>.dropdown-toggle.btn-info{background-image:none}.btn-info.disabled:hover,.btn-info[disabled]:hover,fieldset[disabled] .btn-info:hover,.btn-info.disabled:focus,.btn-info[disabled]:focus,fieldset[disabled] .btn-info:focus,.btn-info.disabled.focus,.btn-info[disabled].focus,fieldset[disabled] .btn-info.focus{background-color:#3498db;border-color:#3498db}.btn-info .badge{color:#3498db;background-color:#ffffff}.btn-warning{color:#ffffff;background-color:#f39c12;border-color:#f39c12}.btn-warning:focus,.btn-warning.focus{color:#ffffff;background-color:#c87f0a;border-color:#7f5006}.btn-warning:hover{color:#ffffff;background-color:#c87f0a;border-color:#be780a}.btn-warning:active,.btn-warning.active,.open>.dropdown-toggle.btn-warning{color:#ffffff;background-color:#c87f0a;border-color:#be780a}.btn-warning:active:hover,.btn-warning.active:hover,.open>.dropdown-toggle.btn-warning:hover,.btn-warning:active:focus,.btn-warning.active:focus,.open>.dropdown-toggle.btn-warning:focus,.btn-warning:active.focus,.btn-warning.active.focus,.open>.dropdown-toggle.btn-warning.focus{color:#ffffff;background-color:#a66908;border-color:#7f5006}.btn-warning:active,.btn-warning.active,.open>.dropdown-toggle.btn-warning{background-image:none}.btn-warning.disabled:hover,.btn-warning[disabled]:hover,fieldset[disabled] .btn-warning:hover,.btn-warning.disabled:focus,.btn-warning[disabled]:focus,fieldset[disabled] .btn-warning:focus,.btn-warning.disabled.focus,.btn-warning[disabled].focus,fieldset[disabled] .btn-warning.focus{background-color:#f39c12;border-color:#f39c12}.btn-warning .badge{color:#f39c12;background-color:#ffffff}.btn-danger{color:#ffffff;background-color:#e74c3c;border-color:#e74c3c}.btn-danger:focus,.btn-danger.focus{color:#ffffff;background-color:#d62c1a;border-color:#921e12}.btn-danger:hover{color:#ffffff;background-color:#d62c1a;border-color:#cd2a19}.btn-danger:active,.btn-danger.active,.open>.dropdown-toggle.btn-danger{color:#ffffff;background-color:#d62c1a;border-color:#cd2a19}.btn-danger:active:hover,.btn-danger.active:hover,.open>.dropdown-toggle.btn-danger:hover,.btn-danger:active:focus,.btn-danger.active:focus,.open>.dropdown-toggle.btn-danger:focus,.btn-danger:active.focus,.btn-danger.active.focus,.open>.dropdown-toggle.btn-danger.focus{color:#ffffff;background-color:#b62516;border-color:#921e12}.btn-danger:active,.btn-danger.active,.open>.dropdown-toggle.btn-danger{background-image:none}.btn-danger.disabled:hover,.btn-danger[disabled]:hover,fieldset[disabled] .btn-danger:hover,.btn-danger.disabled:focus,.btn-danger[disabled]:focus,fieldset[disabled] .btn-danger:focus,.btn-danger.disabled.focus,.btn-danger[disabled].focus,fieldset[disabled] .btn-danger.focus{background-color:#e74c3c;border-color:#e74c3c}.btn-danger .badge{color:#e74c3c;background-color:#ffffff}.btn-link{color:#0ce3ac;font-weight:normal;border-radius:0}.btn-link,.btn-link:active,.btn-link.active,.btn-link[disabled],fieldset[disabled] .btn-link{background-color:transparent;-webkit-box-shadow:none;box-shadow:none}.btn-link,.btn-link:hover,.btn-link:focus,.btn-link:active{border-color:transparent}.btn-link:hover,.btn-link:focus{color:#0ce3ac;text-decoration:underline;background-color:transparent}.btn-link[disabled]:hover,fieldset[disabled] .btn-link:hover,.btn-link[disabled]:focus,fieldset[disabled] .btn-link:focus{color:#999999;text-decoration:none}.btn-lg,.btn-group-lg>.btn{padding:18px 27px;font-size:19px;line-height:1.3333333;border-radius:6px}.btn-sm,.btn-group-sm>.btn{padding:6px 9px;font-size:13px;line-height:1.5;border-radius:3px}.btn-xs,.btn-group-xs>.btn{padding:1px 5px;font-size:13px;line-height:1.5;border-radius:3px}.btn-block{display:block;width:100%}.btn-block+.btn-block{margin-top:5px}input[type="submit"].btn-block,input[type="reset"].btn-block,input[type="button"].btn-block{width:100%}.fade{opacity:0;-webkit-transition:opacity 0.15s linear;-o-transition:opacity 0.15s linear;transition:opacity 0.15s linear}.fade.in{opacity:1}.collapse{display:none}.collapse.in{display:block}tr.collapse.in{display:table-row}tbody.collapse.in{display:table-row-group}.collapsing{position:relative;height:0;overflow:hidden;-webkit-transition-property:height, visibility;-o-transition-property:height, visibility;transition-property:height, visibility;-webkit-transition-duration:0.35s;-o-transition-duration:0.35s;transition-duration:0.35s;-webkit-transition-timing-function:ease;-o-transition-timing-function:ease;transition-timing-function:ease}.caret{display:inline-block;width:0;height:0;margin-left:2px;vertical-align:middle;border-top:4px dashed;border-top:4px solid \9;border-right:4px solid transparent;border-left:4px solid transparent}.dropup,.dropdown{position:relative}.dropdown-toggle:focus{outline:0}.dropdown-menu{position:absolute;top:100%;left:0;z-index:1000;display:none;float:left;min-width:160px;padding:5px 0;margin:2px 0 0;list-style:none;font-size:15px;text-align:left;background-color:#303030;border:1px solid #cccccc;border:1px solid rgba(0,0,0,0.15);border-radius:4px;-webkit-box-shadow:0 6px 12px rgba(0,0,0,0.175);box-shadow:0 6px 12px rgba(0,0,0,0.175);-webkit-background-clip:padding-box;background-clip:padding-box}.dropdown-menu.pull-right{right:0;left:auto}.dropdown-menu .divider{height:1px;margin:9.5px 0;overflow:hidden;background-color:#464545}.dropdown-menu>li>a{display:block;padding:3px 20px;clear:both;font-weight:normal;line-height:1.42857143;color:#ebebeb;white-space:nowrap}.dropdown-menu>li>a:hover,.dropdown-menu>li>a:focus{text-decoration:none;color:#ffffff;background-color:#375a7f}.dropdown-menu>.active>a,.dropdown-menu>.active>a:hover,.dropdown-menu>.active>a:focus{color:#ffffff;text-decoration:none;outline:0;background-color:#375a7f}.dropdown-menu>.disabled>a,.dropdown-menu>.disabled>a:hover,.dropdown-menu>.disabled>a:focus{color:#999999}.dropdown-menu>.disabled>a:hover,.dropdown-menu>.disabled>a:focus{text-decoration:none;background-color:transparent;background-image:none;filter:progid:DXImageTransform.Microsoft.gradient(enabled=false);cursor:not-allowed}.open>.dropdown-menu{display:block}.open>a{outline:0}.dropdown-menu-right{left:auto;right:0}.dropdown-menu-left{left:0;right:auto}.dropdown-header{display:block;padding:3px 20px;font-size:13px;line-height:1.42857143;color:#999999;white-space:nowrap}.dropdown-backdrop{position:fixed;left:0;right:0;bottom:0;top:0;z-index:990}.pull-right>.dropdown-menu{right:0;left:auto}.dropup .caret,.navbar-fixed-bottom .dropdown .caret{border-top:0;border-bottom:4px dashed;border-bottom:4px solid \9;content:""}.dropup .dropdown-menu,.navbar-fixed-bottom .dropdown .dropdown-menu{top:auto;bottom:100%;margin-bottom:2px}@media (min-width:768px){.navbar-right .dropdown-menu{left:auto;right:0}.navbar-right .dropdown-menu-left{left:0;right:auto}}.btn-group,.btn-group-vertical{position:relative;display:inline-block;vertical-align:middle}.btn-group>.btn,.btn-group-vertical>.btn{position:relative;float:left}.btn-group>.btn:hover,.btn-group-vertical>.btn:hover,.btn-group>.btn:focus,.btn-group-vertical>.btn:focus,.btn-group>.btn:active,.btn-group-vertical>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn.active{z-index:2}.btn-group .btn+.btn,.btn-group .btn+.btn-group,.btn-group .btn-group+.btn,.btn-group .btn-group+.btn-group{margin-left:-1px}.btn-toolbar{margin-left:-5px}.btn-toolbar .btn,.btn-toolbar .btn-group,.btn-toolbar .input-group{float:left}.btn-toolbar>.btn,.btn-toolbar>.btn-group,.btn-toolbar>.input-group{margin-left:5px}.btn-group>.btn:not(:first-child):not(:last-child):not(.dropdown-toggle){border-radius:0}.btn-group>.btn:first-child{margin-left:0}.btn-group>.btn:first-child:not(:last-child):not(.dropdown-toggle){border-bottom-right-radius:0;border-top-right-radius:0}.btn-group>.btn:last-child:not(:first-child),.btn-group>.dropdown-toggle:not(:first-child){border-bottom-left-radius:0;border-top-left-radius:0}.btn-group>.btn-group{float:left}.btn-group>.btn-group:not(:first-child):not(:last-child)>.btn{border-radius:0}.btn-group>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group>.btn-group:first-child:not(:last-child)>.dropdown-toggle{border-bottom-right-radius:0;border-top-right-radius:0}.btn-group>.btn-group:last-child:not(:first-child)>.btn:first-child{border-bottom-left-radius:0;border-top-left-radius:0}.btn-group .dropdown-toggle:active,.btn-group.open .dropdown-toggle{outline:0}.btn-group>.btn+.dropdown-toggle{padding-left:8px;padding-right:8px}.btn-group>.btn-lg+.dropdown-toggle{padding-left:12px;padding-right:12px}.btn-group.open .dropdown-toggle{-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,0.125);box-shadow:inset 0 3px 5px rgba(0,0,0,0.125)}.btn-group.open .dropdown-toggle.btn-link{-webkit-box-shadow:none;box-shadow:none}.btn .caret{margin-left:0}.btn-lg .caret{border-width:5px 5px 0;border-bottom-width:0}.dropup .btn-lg .caret{border-width:0 5px 5px}.btn-group-vertical>.btn,.btn-group-vertical>.btn-group,.btn-group-vertical>.btn-group>.btn{display:block;float:none;width:100%;max-width:100%}.btn-group-vertical>.btn-group>.btn{float:none}.btn-group-vertical>.btn+.btn,.btn-group-vertical>.btn+.btn-group,.btn-group-vertical>.btn-group+.btn,.btn-group-vertical>.btn-group+.btn-group{margin-top:-1px;margin-left:0}.btn-group-vertical>.btn:not(:first-child):not(:last-child){border-radius:0}.btn-group-vertical>.btn:first-child:not(:last-child){border-top-right-radius:4px;border-top-left-radius:4px;border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn:last-child:not(:first-child){border-top-right-radius:0;border-top-left-radius:0;border-bottom-right-radius:4px;border-bottom-left-radius:4px}.btn-group-vertical>.btn-group:not(:first-child):not(:last-child)>.btn{border-radius:0}.btn-group-vertical>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group-vertical>.btn-group:first-child:not(:last-child)>.dropdown-toggle{border-bottom-right-radius:0;border-bottom-left-radius:0}.btn-group-vertical>.btn-group:last-child:not(:first-child)>.btn:first-child{border-top-right-radius:0;border-top-left-radius:0}.btn-group-justified{display:table;width:100%;table-layout:fixed;border-collapse:separate}.btn-group-justified>.btn,.btn-group-justified>.btn-group{float:none;display:table-cell;width:1%}.btn-group-justified>.btn-group .btn{width:100%}.btn-group-justified>.btn-group .dropdown-menu{left:auto}[data-toggle="buttons"]>.btn input[type="radio"],[data-toggle="buttons"]>.btn-group>.btn input[type="radio"],[data-toggle="buttons"]>.btn input[type="checkbox"],[data-toggle="buttons"]>.btn-group>.btn input[type="checkbox"]{position:absolute;clip:rect(0, 0, 0, 0);pointer-events:none}.input-group{position:relative;display:table;border-collapse:separate}.input-group[class*="col-"]{float:none;padding-left:0;padding-right:0}.input-group .form-control{position:relative;z-index:2;float:left;width:100%;margin-bottom:0}.input-group .form-control:focus{z-index:3}.input-group-lg>.form-control,.input-group-lg>.input-group-addon,.input-group-lg>.input-group-btn>.btn{height:66px;padding:18px 27px;font-size:19px;line-height:1.3333333;border-radius:6px}select.input-group-lg>.form-control,select.input-group-lg>.input-group-addon,select.input-group-lg>.input-group-btn>.btn{height:66px;line-height:66px}textarea.input-group-lg>.form-control,textarea.input-group-lg>.input-group-addon,textarea.input-group-lg>.input-group-btn>.btn,select[multiple].input-group-lg>.form-control,select[multiple].input-group-lg>.input-group-addon,select[multiple].input-group-lg>.input-group-btn>.btn{height:auto}.input-group-sm>.form-control,.input-group-sm>.input-group-addon,.input-group-sm>.input-group-btn>.btn{height:35px;padding:6px 9px;font-size:13px;line-height:1.5;border-radius:3px}select.input-group-sm>.form-control,select.input-group-sm>.input-group-addon,select.input-group-sm>.input-group-btn>.btn{height:35px;line-height:35px}textarea.input-group-sm>.form-control,textarea.input-group-sm>.input-group-addon,textarea.input-group-sm>.input-group-btn>.btn,select[multiple].input-group-sm>.form-control,select[multiple].input-group-sm>.input-group-addon,select[multiple].input-group-sm>.input-group-btn>.btn{height:auto}.input-group-addon,.input-group-btn,.input-group .form-control{display:table-cell}.input-group-addon:not(:first-child):not(:last-child),.input-group-btn:not(:first-child):not(:last-child),.input-group .form-control:not(:first-child):not(:last-child){border-radius:0}.input-group-addon,.input-group-btn{width:1%;white-space:nowrap;vertical-align:middle}.input-group-addon{padding:10px 15px;font-size:15px;font-weight:normal;line-height:1;color:#464545;text-align:center;background-color:#464545;border:1px solid transparent;border-radius:4px}.input-group-addon.input-sm{padding:6px 9px;font-size:13px;border-radius:3px}.input-group-addon.input-lg{padding:18px 27px;font-size:19px;border-radius:6px}.input-group-addon input[type="radio"],.input-group-addon input[type="checkbox"]{margin-top:0}.input-group .form-control:first-child,.input-group-addon:first-child,.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group>.btn,.input-group-btn:first-child>.dropdown-toggle,.input-group-btn:last-child>.btn:not(:last-child):not(.dropdown-toggle),.input-group-btn:last-child>.btn-group:not(:last-child)>.btn{border-bottom-right-radius:0;border-top-right-radius:0}.input-group-addon:first-child{border-right:0}.input-group .form-control:last-child,.input-group-addon:last-child,.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group>.btn,.input-group-btn:last-child>.dropdown-toggle,.input-group-btn:first-child>.btn:not(:first-child),.input-group-btn:first-child>.btn-group:not(:first-child)>.btn{border-bottom-left-radius:0;border-top-left-radius:0}.input-group-addon:last-child{border-left:0}.input-group-btn{position:relative;font-size:0;white-space:nowrap}.input-group-btn>.btn{position:relative}.input-group-btn>.btn+.btn{margin-left:-1px}.input-group-btn>.btn:hover,.input-group-btn>.btn:focus,.input-group-btn>.btn:active{z-index:2}.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group{margin-right:-1px}.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group{z-index:2;margin-left:-1px}.nav{margin-bottom:0;padding-left:0;list-style:none}.nav>li{position:relative;display:block}.nav>li>a{position:relative;display:block;padding:10px 15px}.nav>li>a:hover,.nav>li>a:focus{text-decoration:none;background-color:#303030}.nav>li.disabled>a{color:#605e5e}.nav>li.disabled>a:hover,.nav>li.disabled>a:focus{color:#605e5e;text-decoration:none;background-color:transparent;cursor:not-allowed}.nav .open>a,.nav .open>a:hover,.nav .open>a:focus{background-color:#303030;border-color:#0ce3ac}.nav .nav-divider{height:1px;margin:9.5px 0;overflow:hidden;background-color:#e5e5e5}.nav>li>a>img{max-width:none}.nav-tabs{border-bottom:1px solid #464545}.nav-tabs>li{float:left;margin-bottom:-1px}.nav-tabs>li>a{margin-right:2px;line-height:1.42857143;border:1px solid transparent;border-radius:4px 4px 0 0}.nav-tabs>li>a:hover{border-color:#464545 #464545 #464545}.nav-tabs>li.active>a,.nav-tabs>li.active>a:hover,.nav-tabs>li.active>a:focus{color:#00bc8c;background-color:#222222;border:1px solid #464545;border-bottom-color:transparent;cursor:default}.nav-tabs.nav-justified{width:100%;border-bottom:0}.nav-tabs.nav-justified>li{float:none}.nav-tabs.nav-justified>li>a{text-align:center;margin-bottom:5px}.nav-tabs.nav-justified>.dropdown .dropdown-menu{top:auto;left:auto}@media (min-width:768px){.nav-tabs.nav-justified>li{display:table-cell;width:1%}.nav-tabs.nav-justified>li>a{margin-bottom:0}}.nav-tabs.nav-justified>li>a{margin-right:0;border-radius:4px}.nav-tabs.nav-justified>.active>a,.nav-tabs.nav-justified>.active>a:hover,.nav-tabs.nav-justified>.active>a:focus{border:1px solid #ebebeb}@media (min-width:768px){.nav-tabs.nav-justified>li>a{border-bottom:1px solid #ebebeb;border-radius:4px 4px 0 0}.nav-tabs.nav-justified>.active>a,.nav-tabs.nav-justified>.active>a:hover,.nav-tabs.nav-justified>.active>a:focus{border-bottom-color:#222222}}.nav-pills>li{float:left}.nav-pills>li>a{border-radius:4px}.nav-pills>li+li{margin-left:2px}.nav-pills>li.active>a,.nav-pills>li.active>a:hover,.nav-pills>li.active>a:focus{color:#ffffff;background-color:#375a7f}.nav-stacked>li{float:none}.nav-stacked>li+li{margin-top:2px;margin-left:0}.nav-justified{width:100%}.nav-justified>li{float:none}.nav-justified>li>a{text-align:center;margin-bottom:5px}.nav-justified>.dropdown .dropdown-menu{top:auto;left:auto}@media (min-width:768px){.nav-justified>li{display:table-cell;width:1%}.nav-justified>li>a{margin-bottom:0}}.nav-tabs-justified{border-bottom:0}.nav-tabs-justified>li>a{margin-right:0;border-radius:4px}.nav-tabs-justified>.active>a,.nav-tabs-justified>.active>a:hover,.nav-tabs-justified>.active>a:focus{border:1px solid #ebebeb}@media (min-width:768px){.nav-tabs-justified>li>a{border-bottom:1px solid #ebebeb;border-radius:4px 4px 0 0}.nav-tabs-justified>.active>a,.nav-tabs-justified>.active>a:hover,.nav-tabs-justified>.active>a:focus{border-bottom-color:#222222}}.tab-content>.tab-pane{display:none}.tab-content>.active{display:block}.nav-tabs .dropdown-menu{margin-top:-1px;border-top-right-radius:0;border-top-left-radius:0}.navbar{position:relative;min-height:60px;margin-bottom:21px;border:1px solid transparent}@media (min-width:768px){.navbar{border-radius:4px}}@media (min-width:768px){.navbar-header{float:left}}.navbar-collapse{overflow-x:visible;padding-right:15px;padding-left:15px;border-top:1px solid transparent;-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,0.1);box-shadow:inset 0 1px 0 rgba(255,255,255,0.1);-webkit-overflow-scrolling:touch}.navbar-collapse.in{overflow-y:auto}@media (min-width:768px){.navbar-collapse{width:auto;border-top:0;-webkit-box-shadow:none;box-shadow:none}.navbar-collapse.collapse{display:block !important;height:auto !important;padding-bottom:0;overflow:visible !important}.navbar-collapse.in{overflow-y:visible}.navbar-fixed-top .navbar-collapse,.navbar-static-top .navbar-collapse,.navbar-fixed-bottom .navbar-collapse{padding-left:0;padding-right:0}}.navbar-fixed-top .navbar-collapse,.navbar-fixed-bottom .navbar-collapse{max-height:340px}@media (max-device-width:480px) and (orientation:landscape){.navbar-fixed-top .navbar-collapse,.navbar-fixed-bottom .navbar-collapse{max-height:200px}}.container>.navbar-header,.container-fluid>.navbar-header,.container>.navbar-collapse,.container-fluid>.navbar-collapse{margin-right:-15px;margin-left:-15px}@media (min-width:768px){.container>.navbar-header,.container-fluid>.navbar-header,.container>.navbar-collapse,.container-fluid>.navbar-collapse{margin-right:0;margin-left:0}}.navbar-static-top{z-index:1000;border-width:0 0 1px}@media (min-width:768px){.navbar-static-top{border-radius:0}}.navbar-fixed-top,.navbar-fixed-bottom{position:fixed;right:0;left:0;z-index:1030}@media (min-width:768px){.navbar-fixed-top,.navbar-fixed-bottom{border-radius:0}}.navbar-fixed-top{top:0;border-width:0 0 1px}.navbar-fixed-bottom{bottom:0;margin-bottom:0;border-width:1px 0 0}.navbar-brand{float:left;padding:19.5px 15px;font-size:19px;line-height:21px;height:60px}.navbar-brand:hover,.navbar-brand:focus{text-decoration:none}.navbar-brand>img{display:block}@media (min-width:768px){.navbar>.container .navbar-brand,.navbar>.container-fluid .navbar-brand{margin-left:-15px}}.navbar-toggle{position:relative;float:right;margin-right:15px;padding:9px 10px;margin-top:13px;margin-bottom:13px;background-color:transparent;background-image:none;border:1px solid transparent;border-radius:4px}.navbar-toggle:focus{outline:0}.navbar-toggle .icon-bar{display:block;width:22px;height:2px;border-radius:1px}.navbar-toggle .icon-bar+.icon-bar{margin-top:4px}@media (min-width:768px){.navbar-toggle{display:none}}.navbar-nav{margin:9.75px -15px}.navbar-nav>li>a{padding-top:10px;padding-bottom:10px;line-height:21px}@media (max-width:767px){.navbar-nav .open .dropdown-menu{position:static;float:none;width:auto;margin-top:0;background-color:transparent;border:0;-webkit-box-shadow:none;box-shadow:none}.navbar-nav .open .dropdown-menu>li>a,.navbar-nav .open .dropdown-menu .dropdown-header{padding:5px 15px 5px 25px}.navbar-nav .open .dropdown-menu>li>a{line-height:21px}.navbar-nav .open .dropdown-menu>li>a:hover,.navbar-nav .open .dropdown-menu>li>a:focus{background-image:none}}@media (min-width:768px){.navbar-nav{float:left;margin:0}.navbar-nav>li{float:left}.navbar-nav>li>a{padding-top:19.5px;padding-bottom:19.5px}}.navbar-form{margin-left:-15px;margin-right:-15px;padding:10px 15px;border-top:1px solid transparent;border-bottom:1px solid transparent;-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,0.1),0 1px 0 rgba(255,255,255,0.1);box-shadow:inset 0 1px 0 rgba(255,255,255,0.1),0 1px 0 rgba(255,255,255,0.1);margin-top:7.5px;margin-bottom:7.5px}@media (min-width:768px){.navbar-form .form-group{display:inline-block;margin-bottom:0;vertical-align:middle}.navbar-form .form-control{display:inline-block;width:auto;vertical-align:middle}.navbar-form .form-control-static{display:inline-block}.navbar-form .input-group{display:inline-table;vertical-align:middle}.navbar-form .input-group .input-group-addon,.navbar-form .input-group .input-group-btn,.navbar-form .input-group .form-control{width:auto}.navbar-form .input-group>.form-control{width:100%}.navbar-form .control-label{margin-bottom:0;vertical-align:middle}.navbar-form .radio,.navbar-form .checkbox{display:inline-block;margin-top:0;margin-bottom:0;vertical-align:middle}.navbar-form .radio label,.navbar-form .checkbox label{padding-left:0}.navbar-form .radio input[type="radio"],.navbar-form .checkbox input[type="checkbox"]{position:relative;margin-left:0}.navbar-form .has-feedback .form-control-feedback{top:0}}@media (max-width:767px){.navbar-form .form-group{margin-bottom:5px}.navbar-form .form-group:last-child{margin-bottom:0}}@media (min-width:768px){.navbar-form{width:auto;border:0;margin-left:0;margin-right:0;padding-top:0;padding-bottom:0;-webkit-box-shadow:none;box-shadow:none}}.navbar-nav>li>.dropdown-menu{margin-top:0;border-top-right-radius:0;border-top-left-radius:0}.navbar-fixed-bottom .navbar-nav>li>.dropdown-menu{margin-bottom:0;border-top-right-radius:4px;border-top-left-radius:4px;border-bottom-right-radius:0;border-bottom-left-radius:0}.navbar-btn{margin-top:7.5px;margin-bottom:7.5px}.navbar-btn.btn-sm{margin-top:12.5px;margin-bottom:12.5px}.navbar-btn.btn-xs{margin-top:19px;margin-bottom:19px}.navbar-text{margin-top:19.5px;margin-bottom:19.5px}@media (min-width:768px){.navbar-text{float:left;margin-left:15px;margin-right:15px}}@media (min-width:768px){.navbar-left{float:left !important}.navbar-right{float:right !important;margin-right:-15px}.navbar-right~.navbar-right{margin-right:0}}.navbar-default{background-color:#375a7f;border-color:transparent}.navbar-default .navbar-brand{color:#ffffff}.navbar-default .navbar-brand:hover,.navbar-default .navbar-brand:focus{color:#00bc8c;background-color:transparent}.navbar-default .navbar-text{color:#ffffff}.navbar-default .navbar-nav>li>a{color:#ffffff}.navbar-default .navbar-nav>li>a:hover,.navbar-default .navbar-nav>li>a:focus{color:#00bc8c;background-color:transparent}.navbar-default .navbar-nav>.active>a,.navbar-default .navbar-nav>.active>a:hover,.navbar-default .navbar-nav>.active>a:focus{color:#ffffff;background-color:#28415b}.navbar-default .navbar-nav>.disabled>a,.navbar-default .navbar-nav>.disabled>a:hover,.navbar-default .navbar-nav>.disabled>a:focus{color:#cccccc;background-color:transparent}.navbar-default .navbar-toggle{border-color:#28415b}.navbar-default .navbar-toggle:hover,.navbar-default .navbar-toggle:focus{background-color:#28415b}.navbar-default .navbar-toggle .icon-bar{background-color:#ffffff}.navbar-default .navbar-collapse,.navbar-default .navbar-form{border-color:transparent}.navbar-default .navbar-nav>.open>a,.navbar-default .navbar-nav>.open>a:hover,.navbar-default .navbar-nav>.open>a:focus{background-color:#28415b;color:#ffffff}@media (max-width:767px){.navbar-default .navbar-nav .open .dropdown-menu>li>a{color:#ffffff}.navbar-default .navbar-nav .open .dropdown-menu>li>a:hover,.navbar-default .navbar-nav .open .dropdown-menu>li>a:focus{color:#00bc8c;background-color:transparent}.navbar-default .navbar-nav .open .dropdown-menu>.active>a,.navbar-default .navbar-nav .open .dropdown-menu>.active>a:hover,.navbar-default .navbar-nav .open .dropdown-menu>.active>a:focus{color:#ffffff;background-color:#28415b}.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a,.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a:hover,.navbar-default .navbar-nav .open .dropdown-menu>.disabled>a:focus{color:#cccccc;background-color:transparent}}.navbar-default .navbar-link{color:#ffffff}.navbar-default .navbar-link:hover{color:#00bc8c}.navbar-default .btn-link{color:#ffffff}.navbar-default .btn-link:hover,.navbar-default .btn-link:focus{color:#00bc8c}.navbar-default .btn-link[disabled]:hover,fieldset[disabled] .navbar-default .btn-link:hover,.navbar-default .btn-link[disabled]:focus,fieldset[disabled] .navbar-default .btn-link:focus{color:#cccccc}.navbar-inverse{background-color:#00bc8c;border-color:transparent}.navbar-inverse .navbar-brand{color:#ffffff}.navbar-inverse .navbar-brand:hover,.navbar-inverse .navbar-brand:focus{color:#375a7f;background-color:transparent}.navbar-inverse .navbar-text{color:#ffffff}.navbar-inverse .navbar-nav>li>a{color:#ffffff}.navbar-inverse .navbar-nav>li>a:hover,.navbar-inverse .navbar-nav>li>a:focus{color:#375a7f;background-color:transparent}.navbar-inverse .navbar-nav>.active>a,.navbar-inverse .navbar-nav>.active>a:hover,.navbar-inverse .navbar-nav>.active>a:focus{color:#ffffff;background-color:#00a379}.navbar-inverse .navbar-nav>.disabled>a,.navbar-inverse .navbar-nav>.disabled>a:hover,.navbar-inverse .navbar-nav>.disabled>a:focus{color:#aaaaaa;background-color:transparent}.navbar-inverse .navbar-toggle{border-color:#008966}.navbar-inverse .navbar-toggle:hover,.navbar-inverse .navbar-toggle:focus{background-color:#008966}.navbar-inverse .navbar-toggle .icon-bar{background-color:#ffffff}.navbar-inverse .navbar-collapse,.navbar-inverse .navbar-form{border-color:#009871}.navbar-inverse .navbar-nav>.open>a,.navbar-inverse .navbar-nav>.open>a:hover,.navbar-inverse .navbar-nav>.open>a:focus{background-color:#00a379;color:#ffffff}@media (max-width:767px){.navbar-inverse .navbar-nav .open .dropdown-menu>.dropdown-header{border-color:transparent}.navbar-inverse .navbar-nav .open .dropdown-menu .divider{background-color:transparent}.navbar-inverse .navbar-nav .open .dropdown-menu>li>a{color:#ffffff}.navbar-inverse .navbar-nav .open .dropdown-menu>li>a:hover,.navbar-inverse .navbar-nav .open .dropdown-menu>li>a:focus{color:#375a7f;background-color:transparent}.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a,.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a:hover,.navbar-inverse .navbar-nav .open .dropdown-menu>.active>a:focus{color:#ffffff;background-color:#00a379}.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a,.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a:hover,.navbar-inverse .navbar-nav .open .dropdown-menu>.disabled>a:focus{color:#aaaaaa;background-color:transparent}}.navbar-inverse .navbar-link{color:#ffffff}.navbar-inverse .navbar-link:hover{color:#375a7f}.navbar-inverse .btn-link{color:#ffffff}.navbar-inverse .btn-link:hover,.navbar-inverse .btn-link:focus{color:#375a7f}.navbar-inverse .btn-link[disabled]:hover,fieldset[disabled] .navbar-inverse .btn-link:hover,.navbar-inverse .btn-link[disabled]:focus,fieldset[disabled] .navbar-inverse .btn-link:focus{color:#aaaaaa}.breadcrumb{padding:8px 15px;margin-bottom:21px;list-style:none;background-color:#464545;border-radius:4px}.breadcrumb>li{display:inline-block}.breadcrumb>li+li:before{content:"/\00a0";padding:0 5px;color:#ffffff}.breadcrumb>.active{color:#999999}.pagination{display:inline-block;padding-left:0;margin:21px 0;border-radius:4px}.pagination>li{display:inline}.pagination>li>a,.pagination>li>span{position:relative;float:left;padding:10px 15px;line-height:1.42857143;text-decoration:none;color:#ffffff;background-color:#00bc8c;border:1px solid transparent;margin-left:-1px}.pagination>li:first-child>a,.pagination>li:first-child>span{margin-left:0;border-bottom-left-radius:4px;border-top-left-radius:4px}.pagination>li:last-child>a,.pagination>li:last-child>span{border-bottom-right-radius:4px;border-top-right-radius:4px}.pagination>li>a:hover,.pagination>li>span:hover,.pagination>li>a:focus,.pagination>li>span:focus{z-index:2;color:#ffffff;background-color:#00dba3;border-color:transparent}.pagination>.active>a,.pagination>.active>span,.pagination>.active>a:hover,.pagination>.active>span:hover,.pagination>.active>a:focus,.pagination>.active>span:focus{z-index:3;color:#ffffff;background-color:#00dba3;border-color:transparent;cursor:default}.pagination>.disabled>span,.pagination>.disabled>span:hover,.pagination>.disabled>span:focus,.pagination>.disabled>a,.pagination>.disabled>a:hover,.pagination>.disabled>a:focus{color:#ffffff;background-color:#007053;border-color:transparent;cursor:not-allowed}.pagination-lg>li>a,.pagination-lg>li>span{padding:18px 27px;font-size:19px;line-height:1.3333333}.pagination-lg>li:first-child>a,.pagination-lg>li:first-child>span{border-bottom-left-radius:6px;border-top-left-radius:6px}.pagination-lg>li:last-child>a,.pagination-lg>li:last-child>span{border-bottom-right-radius:6px;border-top-right-radius:6px}.pagination-sm>li>a,.pagination-sm>li>span{padding:6px 9px;font-size:13px;line-height:1.5}.pagination-sm>li:first-child>a,.pagination-sm>li:first-child>span{border-bottom-left-radius:3px;border-top-left-radius:3px}.pagination-sm>li:last-child>a,.pagination-sm>li:last-child>span{border-bottom-right-radius:3px;border-top-right-radius:3px}.pager{padding-left:0;margin:21px 0;list-style:none;text-align:center}.pager li{display:inline}.pager li>a,.pager li>span{display:inline-block;padding:5px 14px;background-color:#00bc8c;border:1px solid transparent;border-radius:15px}.pager li>a:hover,.pager li>a:focus{text-decoration:none;background-color:#00dba3}.pager .next>a,.pager .next>span{float:right}.pager .previous>a,.pager .previous>span{float:left}.pager .disabled>a,.pager .disabled>a:hover,.pager .disabled>a:focus,.pager .disabled>span{color:#dddddd;background-color:#00bc8c;cursor:not-allowed}.label{display:inline;padding:.2em .6em .3em;font-size:75%;font-weight:bold;line-height:1;color:#ffffff;text-align:center;white-space:nowrap;vertical-align:baseline;border-radius:.25em}a.label:hover,a.label:focus{color:#ffffff;text-decoration:none;cursor:pointer}.label:empty{display:none}.btn .label{position:relative;top:-1px}.label-default{background-color:#464545}.label-default[href]:hover,.label-default[href]:focus{background-color:#2c2c2c}.label-primary{background-color:#375a7f}.label-primary[href]:hover,.label-primary[href]:focus{background-color:#28415b}.label-success{background-color:#00bc8c}.label-success[href]:hover,.label-success[href]:focus{background-color:#008966}.label-info{background-color:#3498db}.label-info[href]:hover,.label-info[href]:focus{background-color:#217dbb}.label-warning{background-color:#f39c12}.label-warning[href]:hover,.label-warning[href]:focus{background-color:#c87f0a}.label-danger{background-color:#e74c3c}.label-danger[href]:hover,.label-danger[href]:focus{background-color:#d62c1a}.badge{display:inline-block;min-width:10px;padding:3px 7px;font-size:13px;font-weight:bold;color:#ffffff;line-height:1;vertical-align:middle;white-space:nowrap;text-align:center;background-color:#464545;border-radius:10px}.badge:empty{display:none}.btn .badge{position:relative;top:-1px}.btn-xs .badge,.btn-group-xs>.btn .badge{top:0;padding:1px 5px}a.badge:hover,a.badge:focus{color:#ffffff;text-decoration:none;cursor:pointer}.list-group-item.active>.badge,.nav-pills>.active>a>.badge{color:#375a7f;background-color:#ffffff}.list-group-item>.badge{float:right}.list-group-item>.badge+.badge{margin-right:5px}.nav-pills>li>a>.badge{margin-left:3px}.jumbotron{padding-top:30px;padding-bottom:30px;margin-bottom:30px;color:inherit;background-color:#303030}.jumbotron h1,.jumbotron .h1{color:inherit}.jumbotron p{margin-bottom:15px;font-size:23px;font-weight:200}.jumbotron>hr{border-top-color:#161616}.container .jumbotron,.container-fluid .jumbotron{border-radius:6px;padding-left:15px;padding-right:15px}.jumbotron .container{max-width:100%}@media screen and (min-width:768px){.jumbotron{padding-top:48px;padding-bottom:48px}.container .jumbotron,.container-fluid .jumbotron{padding-left:60px;padding-right:60px}.jumbotron h1,.jumbotron .h1{font-size:68px}}.thumbnail{display:block;padding:2px;margin-bottom:21px;line-height:1.42857143;background-color:#222222;border:1px solid #464545;border-radius:4px;-webkit-transition:border .2s ease-in-out;-o-transition:border .2s ease-in-out;transition:border .2s ease-in-out}.thumbnail>img,.thumbnail a>img{margin-left:auto;margin-right:auto}a.thumbnail:hover,a.thumbnail:focus,a.thumbnail.active{border-color:#0ce3ac}.thumbnail .caption{padding:9px;color:#ffffff}.alert{padding:15px;margin-bottom:21px;border:1px solid transparent;border-radius:4px}.alert h4{margin-top:0;color:inherit}.alert .alert-link{font-weight:bold}.alert>p,.alert>ul{margin-bottom:0}.alert>p+p{margin-top:5px}.alert-dismissable,.alert-dismissible{padding-right:35px}.alert-dismissable .close,.alert-dismissible .close{position:relative;top:-2px;right:-21px;color:inherit}.alert-success{background-color:#00bc8c;border-color:#00bc8c;color:#ffffff}.alert-success hr{border-top-color:#00a379}.alert-success .alert-link{color:#e6e6e6}.alert-info{background-color:#3498db;border-color:#3498db;color:#ffffff}.alert-info hr{border-top-color:#258cd1}.alert-info .alert-link{color:#e6e6e6}.alert-warning{background-color:#f39c12;border-color:#f39c12;color:#ffffff}.alert-warning hr{border-top-color:#e08e0b}.alert-warning .alert-link{color:#e6e6e6}.alert-danger{background-color:#e74c3c;border-color:#e74c3c;color:#ffffff}.alert-danger hr{border-top-color:#e43725}.alert-danger .alert-link{color:#e6e6e6}@-webkit-keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}@-o-keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}@keyframes progress-bar-stripes{from{background-position:40px 0}to{background-position:0 0}}.progress{overflow:hidden;height:21px;margin-bottom:21px;background-color:#ebebeb;border-radius:4px;-webkit-box-shadow:inset 0 1px 2px rgba(0,0,0,0.1);box-shadow:inset 0 1px 2px rgba(0,0,0,0.1)}.progress-bar{float:left;width:0%;height:100%;font-size:13px;line-height:21px;color:#ffffff;text-align:center;background-color:#375a7f;-webkit-box-shadow:inset 0 -1px 0 rgba(0,0,0,0.15);box-shadow:inset 0 -1px 0 rgba(0,0,0,0.15);-webkit-transition:width 0.6s ease;-o-transition:width 0.6s ease;transition:width 0.6s ease}.progress-striped .progress-bar,.progress-bar-striped{background-image:-webkit-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);-webkit-background-size:40px 40px;background-size:40px 40px}.progress.active .progress-bar,.progress-bar.active{-webkit-animation:progress-bar-stripes 2s linear infinite;-o-animation:progress-bar-stripes 2s linear infinite;animation:progress-bar-stripes 2s linear infinite}.progress-bar-success{background-color:#00bc8c}.progress-striped .progress-bar-success{background-image:-webkit-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent)}.progress-bar-info{background-color:#3498db}.progress-striped .progress-bar-info{background-image:-webkit-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent)}.progress-bar-warning{background-color:#f39c12}.progress-striped .progress-bar-warning{background-image:-webkit-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent)}.progress-bar-danger{background-color:#e74c3c}.progress-striped .progress-bar-danger{background-image:-webkit-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:-o-linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent);background-image:linear-gradient(45deg, rgba(255,255,255,0.15) 25%, transparent 25%, transparent 50%, rgba(255,255,255,0.15) 50%, rgba(255,255,255,0.15) 75%, transparent 75%, transparent)}.media{margin-top:15px}.media:first-child{margin-top:0}.media,.media-body{zoom:1;overflow:hidden}.media-body{width:10000px}.media-object{display:block}.media-object.img-thumbnail{max-width:none}.media-right,.media>.pull-right{padding-left:10px}.media-left,.media>.pull-left{padding-right:10px}.media-left,.media-right,.media-body{display:table-cell;vertical-align:top}.media-middle{vertical-align:middle}.media-bottom{vertical-align:bottom}.media-heading{margin-top:0;margin-bottom:5px}.media-list{padding-left:0;list-style:none}.list-group{margin-bottom:20px;padding-left:0}.list-group-item{position:relative;display:block;padding:10px 15px;margin-bottom:-1px;background-color:#303030;border:1px solid #464545}.list-group-item:first-child{border-top-right-radius:4px;border-top-left-radius:4px}.list-group-item:last-child{margin-bottom:0;border-bottom-right-radius:4px;border-bottom-left-radius:4px}a.list-group-item,button.list-group-item{color:#0ce3ac}a.list-group-item .list-group-item-heading,button.list-group-item .list-group-item-heading{color:#0bcb9a}a.list-group-item:hover,button.list-group-item:hover,a.list-group-item:focus,button.list-group-item:focus{text-decoration:none;color:#0ce3ac;background-color:transparent}button.list-group-item{width:100%;text-align:left}.list-group-item.disabled,.list-group-item.disabled:hover,.list-group-item.disabled:focus{background-color:#ebebeb;color:#999999;cursor:not-allowed}.list-group-item.disabled .list-group-item-heading,.list-group-item.disabled:hover .list-group-item-heading,.list-group-item.disabled:focus .list-group-item-heading{color:inherit}.list-group-item.disabled .list-group-item-text,.list-group-item.disabled:hover .list-group-item-text,.list-group-item.disabled:focus .list-group-item-text{color:#999999}.list-group-item.active,.list-group-item.active:hover,.list-group-item.active:focus{z-index:2;color:#ffffff;background-color:#375a7f;border-color:#375a7f}.list-group-item.active .list-group-item-heading,.list-group-item.active:hover .list-group-item-heading,.list-group-item.active:focus .list-group-item-heading,.list-group-item.active .list-group-item-heading>small,.list-group-item.active:hover .list-group-item-heading>small,.list-group-item.active:focus .list-group-item-heading>small,.list-group-item.active .list-group-item-heading>.small,.list-group-item.active:hover .list-group-item-heading>.small,.list-group-item.active:focus .list-group-item-heading>.small{color:inherit}.list-group-item.active .list-group-item-text,.list-group-item.active:hover .list-group-item-text,.list-group-item.active:focus .list-group-item-text{color:#a8c0da}.list-group-item-success{color:#ffffff;background-color:#00bc8c}a.list-group-item-success,button.list-group-item-success{color:#ffffff}a.list-group-item-success .list-group-item-heading,button.list-group-item-success .list-group-item-heading{color:inherit}a.list-group-item-success:hover,button.list-group-item-success:hover,a.list-group-item-success:focus,button.list-group-item-success:focus{color:#ffffff;background-color:#00a379}a.list-group-item-success.active,button.list-group-item-success.active,a.list-group-item-success.active:hover,button.list-group-item-success.active:hover,a.list-group-item-success.active:focus,button.list-group-item-success.active:focus{color:#fff;background-color:#ffffff;border-color:#ffffff}.list-group-item-info{color:#ffffff;background-color:#3498db}a.list-group-item-info,button.list-group-item-info{color:#ffffff}a.list-group-item-info .list-group-item-heading,button.list-group-item-info .list-group-item-heading{color:inherit}a.list-group-item-info:hover,button.list-group-item-info:hover,a.list-group-item-info:focus,button.list-group-item-info:focus{color:#ffffff;background-color:#258cd1}a.list-group-item-info.active,button.list-group-item-info.active,a.list-group-item-info.active:hover,button.list-group-item-info.active:hover,a.list-group-item-info.active:focus,button.list-group-item-info.active:focus{color:#fff;background-color:#ffffff;border-color:#ffffff}.list-group-item-warning{color:#ffffff;background-color:#f39c12}a.list-group-item-warning,button.list-group-item-warning{color:#ffffff}a.list-group-item-warning .list-group-item-heading,button.list-group-item-warning .list-group-item-heading{color:inherit}a.list-group-item-warning:hover,button.list-group-item-warning:hover,a.list-group-item-warning:focus,button.list-group-item-warning:focus{color:#ffffff;background-color:#e08e0b}a.list-group-item-warning.active,button.list-group-item-warning.active,a.list-group-item-warning.active:hover,button.list-group-item-warning.active:hover,a.list-group-item-warning.active:focus,button.list-group-item-warning.active:focus{color:#fff;background-color:#ffffff;border-color:#ffffff}.list-group-item-danger{color:#ffffff;background-color:#e74c3c}a.list-group-item-danger,button.list-group-item-danger{color:#ffffff}a.list-group-item-danger .list-group-item-heading,button.list-group-item-danger .list-group-item-heading{color:inherit}a.list-group-item-danger:hover,button.list-group-item-danger:hover,a.list-group-item-danger:focus,button.list-group-item-danger:focus{color:#ffffff;background-color:#e43725}a.list-group-item-danger.active,button.list-group-item-danger.active,a.list-group-item-danger.active:hover,button.list-group-item-danger.active:hover,a.list-group-item-danger.active:focus,button.list-group-item-danger.active:focus{color:#fff;background-color:#ffffff;border-color:#ffffff}.list-group-item-heading{margin-top:0;margin-bottom:5px}.list-group-item-text{margin-bottom:0;line-height:1.3}.panel{margin-bottom:21px;background-color:#303030;border:1px solid transparent;border-radius:4px;-webkit-box-shadow:0 1px 1px rgba(0,0,0,0.05);box-shadow:0 1px 1px rgba(0,0,0,0.05)}.panel-body{padding:15px}.panel-heading{padding:10px 15px;border-bottom:1px solid transparent;border-top-right-radius:3px;border-top-left-radius:3px}.panel-heading>.dropdown .dropdown-toggle{color:inherit}.panel-title{margin-top:0;margin-bottom:0;font-size:17px;color:inherit}.panel-title>a,.panel-title>small,.panel-title>.small,.panel-title>small>a,.panel-title>.small>a{color:inherit}.panel-footer{padding:10px 15px;background-color:#464545;border-top:1px solid #464545;border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.list-group,.panel>.panel-collapse>.list-group{margin-bottom:0}.panel>.list-group .list-group-item,.panel>.panel-collapse>.list-group .list-group-item{border-width:1px 0;border-radius:0}.panel>.list-group:first-child .list-group-item:first-child,.panel>.panel-collapse>.list-group:first-child .list-group-item:first-child{border-top:0;border-top-right-radius:3px;border-top-left-radius:3px}.panel>.list-group:last-child .list-group-item:last-child,.panel>.panel-collapse>.list-group:last-child .list-group-item:last-child{border-bottom:0;border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.panel-heading+.panel-collapse>.list-group .list-group-item:first-child{border-top-right-radius:0;border-top-left-radius:0}.panel-heading+.list-group .list-group-item:first-child{border-top-width:0}.list-group+.panel-footer{border-top-width:0}.panel>.table,.panel>.table-responsive>.table,.panel>.panel-collapse>.table{margin-bottom:0}.panel>.table caption,.panel>.table-responsive>.table caption,.panel>.panel-collapse>.table caption{padding-left:15px;padding-right:15px}.panel>.table:first-child,.panel>.table-responsive:first-child>.table:first-child{border-top-right-radius:3px;border-top-left-radius:3px}.panel>.table:first-child>thead:first-child>tr:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child{border-top-left-radius:3px;border-top-right-radius:3px}.panel>.table:first-child>thead:first-child>tr:first-child td:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child td:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child td:first-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child td:first-child,.panel>.table:first-child>thead:first-child>tr:first-child th:first-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child th:first-child,.panel>.table:first-child>tbody:first-child>tr:first-child th:first-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child th:first-child{border-top-left-radius:3px}.panel>.table:first-child>thead:first-child>tr:first-child td:last-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child td:last-child,.panel>.table:first-child>tbody:first-child>tr:first-child td:last-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child td:last-child,.panel>.table:first-child>thead:first-child>tr:first-child th:last-child,.panel>.table-responsive:first-child>.table:first-child>thead:first-child>tr:first-child th:last-child,.panel>.table:first-child>tbody:first-child>tr:first-child th:last-child,.panel>.table-responsive:first-child>.table:first-child>tbody:first-child>tr:first-child th:last-child{border-top-right-radius:3px}.panel>.table:last-child,.panel>.table-responsive:last-child>.table:last-child{border-bottom-right-radius:3px;border-bottom-left-radius:3px}.panel>.table:last-child>tbody:last-child>tr:last-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child{border-bottom-left-radius:3px;border-bottom-right-radius:3px}.panel>.table:last-child>tbody:last-child>tr:last-child td:first-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child td:first-child,.panel>.table:last-child>tfoot:last-child>tr:last-child td:first-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child td:first-child,.panel>.table:last-child>tbody:last-child>tr:last-child th:first-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child th:first-child,.panel>.table:last-child>tfoot:last-child>tr:last-child th:first-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child th:first-child{border-bottom-left-radius:3px}.panel>.table:last-child>tbody:last-child>tr:last-child td:last-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child td:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child td:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child td:last-child,.panel>.table:last-child>tbody:last-child>tr:last-child th:last-child,.panel>.table-responsive:last-child>.table:last-child>tbody:last-child>tr:last-child th:last-child,.panel>.table:last-child>tfoot:last-child>tr:last-child th:last-child,.panel>.table-responsive:last-child>.table:last-child>tfoot:last-child>tr:last-child th:last-child{border-bottom-right-radius:3px}.panel>.panel-body+.table,.panel>.panel-body+.table-responsive,.panel>.table+.panel-body,.panel>.table-responsive+.panel-body{border-top:1px solid #464545}.panel>.table>tbody:first-child>tr:first-child th,.panel>.table>tbody:first-child>tr:first-child td{border-top:0}.panel>.table-bordered,.panel>.table-responsive>.table-bordered{border:0}.panel>.table-bordered>thead>tr>th:first-child,.panel>.table-responsive>.table-bordered>thead>tr>th:first-child,.panel>.table-bordered>tbody>tr>th:first-child,.panel>.table-responsive>.table-bordered>tbody>tr>th:first-child,.panel>.table-bordered>tfoot>tr>th:first-child,.panel>.table-responsive>.table-bordered>tfoot>tr>th:first-child,.panel>.table-bordered>thead>tr>td:first-child,.panel>.table-responsive>.table-bordered>thead>tr>td:first-child,.panel>.table-bordered>tbody>tr>td:first-child,.panel>.table-responsive>.table-bordered>tbody>tr>td:first-child,.panel>.table-bordered>tfoot>tr>td:first-child,.panel>.table-responsive>.table-bordered>tfoot>tr>td:first-child{border-left:0}.panel>.table-bordered>thead>tr>th:last-child,.panel>.table-responsive>.table-bordered>thead>tr>th:last-child,.panel>.table-bordered>tbody>tr>th:last-child,.panel>.table-responsive>.table-bordered>tbody>tr>th:last-child,.panel>.table-bordered>tfoot>tr>th:last-child,.panel>.table-responsive>.table-bordered>tfoot>tr>th:last-child,.panel>.table-bordered>thead>tr>td:last-child,.panel>.table-responsive>.table-bordered>thead>tr>td:last-child,.panel>.table-bordered>tbody>tr>td:last-child,.panel>.table-responsive>.table-bordered>tbody>tr>td:last-child,.panel>.table-bordered>tfoot>tr>td:last-child,.panel>.table-responsive>.table-bordered>tfoot>tr>td:last-child{border-right:0}.panel>.table-bordered>thead>tr:first-child>td,.panel>.table-responsive>.table-bordered>thead>tr:first-child>td,.panel>.table-bordered>tbody>tr:first-child>td,.panel>.table-responsive>.table-bordered>tbody>tr:first-child>td,.panel>.table-bordered>thead>tr:first-child>th,.panel>.table-responsive>.table-bordered>thead>tr:first-child>th,.panel>.table-bordered>tbody>tr:first-child>th,.panel>.table-responsive>.table-bordered>tbody>tr:first-child>th{border-bottom:0}.panel>.table-bordered>tbody>tr:last-child>td,.panel>.table-responsive>.table-bordered>tbody>tr:last-child>td,.panel>.table-bordered>tfoot>tr:last-child>td,.panel>.table-responsive>.table-bordered>tfoot>tr:last-child>td,.panel>.table-bordered>tbody>tr:last-child>th,.panel>.table-responsive>.table-bordered>tbody>tr:last-child>th,.panel>.table-bordered>tfoot>tr:last-child>th,.panel>.table-responsive>.table-bordered>tfoot>tr:last-child>th{border-bottom:0}.panel>.table-responsive{border:0;margin-bottom:0}.panel-group{margin-bottom:21px}.panel-group .panel{margin-bottom:0;border-radius:4px}.panel-group .panel+.panel{margin-top:5px}.panel-group .panel-heading{border-bottom:0}.panel-group .panel-heading+.panel-collapse>.panel-body,.panel-group .panel-heading+.panel-collapse>.list-group{border-top:1px solid #464545}.panel-group .panel-footer{border-top:0}.panel-group .panel-footer+.panel-collapse .panel-body{border-bottom:1px solid #464545}.panel-default{border-color:#464545}.panel-default>.panel-heading{color:#ffffff;background-color:#303030;border-color:#464545}.panel-default>.panel-heading+.panel-collapse>.panel-body{border-top-color:#464545}.panel-default>.panel-heading .badge{color:#303030;background-color:#ffffff}.panel-default>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#464545}.panel-primary{border-color:#375a7f}.panel-primary>.panel-heading{color:#ffffff;background-color:#375a7f;border-color:#375a7f}.panel-primary>.panel-heading+.panel-collapse>.panel-body{border-top-color:#375a7f}.panel-primary>.panel-heading .badge{color:#375a7f;background-color:#ffffff}.panel-primary>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#375a7f}.panel-success{border-color:#00bc8c}.panel-success>.panel-heading{color:#ffffff;background-color:#00bc8c;border-color:#00bc8c}.panel-success>.panel-heading+.panel-collapse>.panel-body{border-top-color:#00bc8c}.panel-success>.panel-heading .badge{color:#00bc8c;background-color:#ffffff}.panel-success>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#00bc8c}.panel-info{border-color:#3498db}.panel-info>.panel-heading{color:#ffffff;background-color:#3498db;border-color:#3498db}.panel-info>.panel-heading+.panel-collapse>.panel-body{border-top-color:#3498db}.panel-info>.panel-heading .badge{color:#3498db;background-color:#ffffff}.panel-info>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#3498db}.panel-warning{border-color:#f39c12}.panel-warning>.panel-heading{color:#ffffff;background-color:#f39c12;border-color:#f39c12}.panel-warning>.panel-heading+.panel-collapse>.panel-body{border-top-color:#f39c12}.panel-warning>.panel-heading .badge{color:#f39c12;background-color:#ffffff}.panel-warning>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#f39c12}.panel-danger{border-color:#e74c3c}.panel-danger>.panel-heading{color:#ffffff;background-color:#e74c3c;border-color:#e74c3c}.panel-danger>.panel-heading+.panel-collapse>.panel-body{border-top-color:#e74c3c}.panel-danger>.panel-heading .badge{color:#e74c3c;background-color:#ffffff}.panel-danger>.panel-footer+.panel-collapse>.panel-body{border-bottom-color:#e74c3c}.embed-responsive{position:relative;display:block;height:0;padding:0;overflow:hidden}.embed-responsive .embed-responsive-item,.embed-responsive iframe,.embed-responsive embed,.embed-responsive object,.embed-responsive video{position:absolute;top:0;left:0;bottom:0;height:100%;width:100%;border:0}.embed-responsive-16by9{padding-bottom:56.25%}.embed-responsive-4by3{padding-bottom:75%}.well{min-height:20px;padding:19px;margin-bottom:20px;background-color:#303030;border:1px solid transparent;border-radius:4px;-webkit-box-shadow:inset 0 1px 1px rgba(0,0,0,0.05);box-shadow:inset 0 1px 1px rgba(0,0,0,0.05)}.well blockquote{border-color:#ddd;border-color:rgba(0,0,0,0.15)}.well-lg{padding:24px;border-radius:6px}.well-sm{padding:9px;border-radius:3px}.close{float:right;font-size:22.5px;font-weight:bold;line-height:1;color:#ffffff;text-shadow:none;opacity:0.2;filter:alpha(opacity=20)}.close:hover,.close:focus{color:#ffffff;text-decoration:none;cursor:pointer;opacity:0.5;filter:alpha(opacity=50)}button.close{padding:0;cursor:pointer;background:transparent;border:0;-webkit-appearance:none}.modal-open{overflow:hidden}.modal{display:none;overflow:hidden;position:fixed;top:0;right:0;bottom:0;left:0;z-index:1050;-webkit-overflow-scrolling:touch;outline:0}.modal.fade .modal-dialog{-webkit-transform:translate(0, -25%);-ms-transform:translate(0, -25%);-o-transform:translate(0, -25%);transform:translate(0, -25%);-webkit-transition:-webkit-transform .3s ease-out;-o-transition:-o-transform .3s ease-out;transition:transform .3s ease-out}.modal.in .modal-dialog{-webkit-transform:translate(0, 0);-ms-transform:translate(0, 0);-o-transform:translate(0, 0);transform:translate(0, 0)}.modal-open .modal{overflow-x:hidden;overflow-y:auto}.modal-dialog{position:relative;width:auto;margin:10px}.modal-content{position:relative;background-color:#303030;border:1px solid #999999;border:1px solid rgba(0,0,0,0.2);border-radius:6px;-webkit-box-shadow:0 3px 9px rgba(0,0,0,0.5);box-shadow:0 3px 9px rgba(0,0,0,0.5);-webkit-background-clip:padding-box;background-clip:padding-box;outline:0}.modal-backdrop{position:fixed;top:0;right:0;bottom:0;left:0;z-index:1040;background-color:#000000}.modal-backdrop.fade{opacity:0;filter:alpha(opacity=0)}.modal-backdrop.in{opacity:0.7;filter:alpha(opacity=70)}.modal-header{padding:15px;border-bottom:1px solid #464545}.modal-header .close{margin-top:-2px}.modal-title{margin:0;line-height:1.42857143}.modal-body{position:relative;padding:20px}.modal-footer{padding:20px;text-align:right;border-top:1px solid #464545}.modal-footer .btn+.btn{margin-left:5px;margin-bottom:0}.modal-footer .btn-group .btn+.btn{margin-left:-1px}.modal-footer .btn-block+.btn-block{margin-left:0}.modal-scrollbar-measure{position:absolute;top:-9999px;width:50px;height:50px;overflow:scroll}@media (min-width:768px){.modal-dialog{width:600px;margin:30px auto}.modal-content{-webkit-box-shadow:0 5px 15px rgba(0,0,0,0.5);box-shadow:0 5px 15px rgba(0,0,0,0.5)}.modal-sm{width:300px}}@media (min-width:992px){.modal-lg{width:900px}}.tooltip{position:absolute;z-index:1070;display:block;font-family:"Lato","Helvetica Neue",Helvetica,Arial,sans-serif;font-style:normal;font-weight:normal;letter-spacing:normal;line-break:auto;line-height:1.42857143;text-align:left;text-align:start;text-decoration:none;text-shadow:none;text-transform:none;white-space:normal;word-break:normal;word-spacing:normal;word-wrap:normal;font-size:13px;opacity:0;filter:alpha(opacity=0)}.tooltip.in{opacity:0.9;filter:alpha(opacity=90)}.tooltip.top{margin-top:-3px;padding:5px 0}.tooltip.right{margin-left:3px;padding:0 5px}.tooltip.bottom{margin-top:3px;padding:5px 0}.tooltip.left{margin-left:-3px;padding:0 5px}.tooltip-inner{max-width:200px;padding:3px 8px;color:#ffffff;text-align:center;background-color:#000000;border-radius:4px}.tooltip-arrow{position:absolute;width:0;height:0;border-color:transparent;border-style:solid}.tooltip.top .tooltip-arrow{bottom:0;left:50%;margin-left:-5px;border-width:5px 5px 0;border-top-color:#000000}.tooltip.top-left .tooltip-arrow{bottom:0;right:5px;margin-bottom:-5px;border-width:5px 5px 0;border-top-color:#000000}.tooltip.top-right .tooltip-arrow{bottom:0;left:5px;margin-bottom:-5px;border-width:5px 5px 0;border-top-color:#000000}.tooltip.right .tooltip-arrow{top:50%;left:0;margin-top:-5px;border-width:5px 5px 5px 0;border-right-color:#000000}.tooltip.left .tooltip-arrow{top:50%;right:0;margin-top:-5px;border-width:5px 0 5px 5px;border-left-color:#000000}.tooltip.bottom .tooltip-arrow{top:0;left:50%;margin-left:-5px;border-width:0 5px 5px;border-bottom-color:#000000}.tooltip.bottom-left .tooltip-arrow{top:0;right:5px;margin-top:-5px;border-width:0 5px 5px;border-bottom-color:#000000}.tooltip.bottom-right .tooltip-arrow{top:0;left:5px;margin-top:-5px;border-width:0 5px 5px;border-bottom-color:#000000}.popover{position:absolute;top:0;left:0;z-index:1060;display:none;max-width:276px;padding:1px;font-family:"Lato","Helvetica Neue",Helvetica,Arial,sans-serif;font-style:normal;font-weight:normal;letter-spacing:normal;line-break:auto;line-height:1.42857143;text-align:left;text-align:start;text-decoration:none;text-shadow:none;text-transform:none;white-space:normal;word-break:normal;word-spacing:normal;word-wrap:normal;font-size:15px;background-color:#303030;-webkit-background-clip:padding-box;background-clip:padding-box;border:1px solid #999999;border:1px solid rgba(0,0,0,0.2);border-radius:6px;-webkit-box-shadow:0 5px 10px rgba(0,0,0,0.2);box-shadow:0 5px 10px rgba(0,0,0,0.2)}.popover.top{margin-top:-10px}.popover.right{margin-left:10px}.popover.bottom{margin-top:10px}.popover.left{margin-left:-10px}.popover-title{margin:0;padding:8px 14px;font-size:15px;background-color:#282828;border-bottom:1px solid #1c1c1c;border-radius:5px 5px 0 0}.popover-content{padding:9px 14px}.popover>.arrow,.popover>.arrow:after{position:absolute;display:block;width:0;height:0;border-color:transparent;border-style:solid}.popover>.arrow{border-width:11px}.popover>.arrow:after{border-width:10px;content:""}.popover.top>.arrow{left:50%;margin-left:-11px;border-bottom-width:0;border-top-color:#666666;border-top-color:rgba(0,0,0,0.25);bottom:-11px}.popover.top>.arrow:after{content:" ";bottom:1px;margin-left:-10px;border-bottom-width:0;border-top-color:#303030}.popover.right>.arrow{top:50%;left:-11px;margin-top:-11px;border-left-width:0;border-right-color:#666666;border-right-color:rgba(0,0,0,0.25)}.popover.right>.arrow:after{content:" ";left:1px;bottom:-10px;border-left-width:0;border-right-color:#303030}.popover.bottom>.arrow{left:50%;margin-left:-11px;border-top-width:0;border-bottom-color:#666666;border-bottom-color:rgba(0,0,0,0.25);top:-11px}.popover.bottom>.arrow:after{content:" ";top:1px;margin-left:-10px;border-top-width:0;border-bottom-color:#303030}.popover.left>.arrow{top:50%;right:-11px;margin-top:-11px;border-right-width:0;border-left-color:#666666;border-left-color:rgba(0,0,0,0.25)}.popover.left>.arrow:after{content:" ";right:1px;border-right-width:0;border-left-color:#303030;bottom:-10px}.carousel{position:relative}.carousel-inner{position:relative;overflow:hidden;width:100%}.carousel-inner>.item{display:none;position:relative;-webkit-transition:.6s ease-in-out left;-o-transition:.6s ease-in-out left;transition:.6s ease-in-out left}.carousel-inner>.item>img,.carousel-inner>.item>a>img{line-height:1}@media all and (transform-3d),(-webkit-transform-3d){.carousel-inner>.item{-webkit-transition:-webkit-transform .6s ease-in-out;-o-transition:-o-transform .6s ease-in-out;transition:transform .6s ease-in-out;-webkit-backface-visibility:hidden;backface-visibility:hidden;-webkit-perspective:1000px;perspective:1000px}.carousel-inner>.item.next,.carousel-inner>.item.active.right{-webkit-transform:translate3d(100%, 0, 0);transform:translate3d(100%, 0, 0);left:0}.carousel-inner>.item.prev,.carousel-inner>.item.active.left{-webkit-transform:translate3d(-100%, 0, 0);transform:translate3d(-100%, 0, 0);left:0}.carousel-inner>.item.next.left,.carousel-inner>.item.prev.right,.carousel-inner>.item.active{-webkit-transform:translate3d(0, 0, 0);transform:translate3d(0, 0, 0);left:0}}.carousel-inner>.active,.carousel-inner>.next,.carousel-inner>.prev{display:block}.carousel-inner>.active{left:0}.carousel-inner>.next,.carousel-inner>.prev{position:absolute;top:0;width:100%}.carousel-inner>.next{left:100%}.carousel-inner>.prev{left:-100%}.carousel-inner>.next.left,.carousel-inner>.prev.right{left:0}.carousel-inner>.active.left{left:-100%}.carousel-inner>.active.right{left:100%}.carousel-control{position:absolute;top:0;left:0;bottom:0;width:15%;opacity:0.5;filter:alpha(opacity=50);font-size:20px;color:#ffffff;text-align:center;text-shadow:0 1px 2px rgba(0,0,0,0.6);background-color:rgba(0,0,0,0)}.carousel-control.left{background-image:-webkit-linear-gradient(left, rgba(0,0,0,0.5) 0, rgba(0,0,0,0.0001) 100%);background-image:-o-linear-gradient(left, rgba(0,0,0,0.5) 0, rgba(0,0,0,0.0001) 100%);background-image:-webkit-gradient(linear, left top, right top, from(rgba(0,0,0,0.5)), to(rgba(0,0,0,0.0001)));background-image:linear-gradient(to right, rgba(0,0,0,0.5) 0, rgba(0,0,0,0.0001) 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1)}.carousel-control.right{left:auto;right:0;background-image:-webkit-linear-gradient(left, rgba(0,0,0,0.0001) 0, rgba(0,0,0,0.5) 100%);background-image:-o-linear-gradient(left, rgba(0,0,0,0.0001) 0, rgba(0,0,0,0.5) 100%);background-image:-webkit-gradient(linear, left top, right top, from(rgba(0,0,0,0.0001)), to(rgba(0,0,0,0.5)));background-image:linear-gradient(to right, rgba(0,0,0,0.0001) 0, rgba(0,0,0,0.5) 100%);background-repeat:repeat-x;filter:progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1)}.carousel-control:hover,.carousel-control:focus{outline:0;color:#ffffff;text-decoration:none;opacity:0.9;filter:alpha(opacity=90)}.carousel-control .icon-prev,.carousel-control .icon-next,.carousel-control .glyphicon-chevron-left,.carousel-control .glyphicon-chevron-right{position:absolute;top:50%;margin-top:-10px;z-index:5;display:inline-block}.carousel-control .icon-prev,.carousel-control .glyphicon-chevron-left{left:50%;margin-left:-10px}.carousel-control .icon-next,.carousel-control .glyphicon-chevron-right{right:50%;margin-right:-10px}.carousel-control .icon-prev,.carousel-control .icon-next{width:20px;height:20px;line-height:1;font-family:serif}.carousel-control .icon-prev:before{content:'\2039'}.carousel-control .icon-next:before{content:'\203a'}.carousel-indicators{position:absolute;bottom:10px;left:50%;z-index:15;width:60%;margin-left:-30%;padding-left:0;list-style:none;text-align:center}.carousel-indicators li{display:inline-block;width:10px;height:10px;margin:1px;text-indent:-999px;border:1px solid #ffffff;border-radius:10px;cursor:pointer;background-color:#000 \9;background-color:rgba(0,0,0,0)}.carousel-indicators .active{margin:0;width:12px;height:12px;background-color:#ffffff}.carousel-caption{position:absolute;left:15%;right:15%;bottom:20px;z-index:10;padding-top:20px;padding-bottom:20px;color:#ffffff;text-align:center;text-shadow:0 1px 2px rgba(0,0,0,0.6)}.carousel-caption .btn{text-shadow:none}@media screen and (min-width:768px){.carousel-control .glyphicon-chevron-left,.carousel-control .glyphicon-chevron-right,.carousel-control .icon-prev,.carousel-control .icon-next{width:30px;height:30px;margin-top:-10px;font-size:30px}.carousel-control .glyphicon-chevron-left,.carousel-control .icon-prev{margin-left:-10px}.carousel-control .glyphicon-chevron-right,.carousel-control .icon-next{margin-right:-10px}.carousel-caption{left:20%;right:20%;padding-bottom:30px}.carousel-indicators{bottom:20px}}.clearfix:before,.clearfix:after,.dl-horizontal dd:before,.dl-horizontal dd:after,.container:before,.container:after,.container-fluid:before,.container-fluid:after,.row:before,.row:after,.form-horizontal .form-group:before,.form-horizontal .form-group:after,.btn-toolbar:before,.btn-toolbar:after,.btn-group-vertical>.btn-group:before,.btn-group-vertical>.btn-group:after,.nav:before,.nav:after,.navbar:before,.navbar:after,.navbar-header:before,.navbar-header:after,.navbar-collapse:before,.navbar-collapse:after,.pager:before,.pager:after,.panel-body:before,.panel-body:after,.modal-header:before,.modal-header:after,.modal-footer:before,.modal-footer:after{content:" ";display:table}.clearfix:after,.dl-horizontal dd:after,.container:after,.container-fluid:after,.row:after,.form-horizontal .form-group:after,.btn-toolbar:after,.btn-group-vertical>.btn-group:after,.nav:after,.navbar:after,.navbar-header:after,.navbar-collapse:after,.pager:after,.panel-body:after,.modal-header:after,.modal-footer:after{clear:both}.center-block{display:block;margin-left:auto;margin-right:auto}.pull-right{float:right !important}.pull-left{float:left !important}.hide{display:none !important}.show{display:block !important}.invisible{visibility:hidden}.text-hide{font:0/0 a;color:transparent;text-shadow:none;background-color:transparent;border:0}.hidden{display:none !important}.affix{position:fixed}@-ms-viewport{width:device-width}.visible-xs,.visible-sm,.visible-md,.visible-lg{display:none !important}.visible-xs-block,.visible-xs-inline,.visible-xs-inline-block,.visible-sm-block,.visible-sm-inline,.visible-sm-inline-block,.visible-md-block,.visible-md-inline,.visible-md-inline-block,.visible-lg-block,.visible-lg-inline,.visible-lg-inline-block{display:none !important}@media (max-width:767px){.visible-xs{display:block !important}table.visible-xs{display:table !important}tr.visible-xs{display:table-row !important}th.visible-xs,td.visible-xs{display:table-cell !important}}@media (max-width:767px){.visible-xs-block{display:block !important}}@media (max-width:767px){.visible-xs-inline{display:inline !important}}@media (max-width:767px){.visible-xs-inline-block{display:inline-block !important}}@media (min-width:768px) and (max-width:991px){.visible-sm{display:block !important}table.visible-sm{display:table !important}tr.visible-sm{display:table-row !important}th.visible-sm,td.visible-sm{display:table-cell !important}}@media (min-width:768px) and (max-width:991px){.visible-sm-block{display:block !important}}@media (min-width:768px) and (max-width:991px){.visible-sm-inline{display:inline !important}}@media (min-width:768px) and (max-width:991px){.visible-sm-inline-block{display:inline-block !important}}@media (min-width:992px) and (max-width:1199px){.visible-md{display:block !important}table.visible-md{display:table !important}tr.visible-md{display:table-row !important}th.visible-md,td.visible-md{display:table-cell !important}}@media (min-width:992px) and (max-width:1199px){.visible-md-block{display:block !important}}@media (min-width:992px) and (max-width:1199px){.visible-md-inline{display:inline !important}}@media (min-width:992px) and (max-width:1199px){.visible-md-inline-block{display:inline-block !important}}@media (min-width:1200px){.visible-lg{display:block !important}table.visible-lg{display:table !important}tr.visible-lg{display:table-row !important}th.visible-lg,td.visible-lg{display:table-cell !important}}@media (min-width:1200px){.visible-lg-block{display:block !important}}@media (min-width:1200px){.visible-lg-inline{display:inline !important}}@media (min-width:1200px){.visible-lg-inline-block{display:inline-block !important}}@media (max-width:767px){.hidden-xs{display:none !important}}@media (min-width:768px) and (max-width:991px){.hidden-sm{display:none !important}}@media (min-width:992px) and (max-width:1199px){.hidden-md{display:none !important}}@media (min-width:1200px){.hidden-lg{display:none !important}}.visible-print{display:none !important}@media print{.visible-print{display:block !important}table.visible-print{display:table !important}tr.visible-print{display:table-row !important}th.visible-print,td.visible-print{display:table-cell !important}}.visible-print-block{display:none !important}@media print{.visible-print-block{display:block !important}}.visible-print-inline{display:none !important}@media print{.visible-print-inline{display:inline !important}}.visible-print-inline-block{display:none !important}@media print{.visible-print-inline-block{display:inline-block !important}}@media print{.hidden-print{display:none !important}}.navbar{border-width:0}.navbar-default .badge{background-color:#fff;color:#375a7f}.navbar-inverse .badge{background-color:#fff;color:#00bc8c}.navbar-brand{line-height:1}.navbar-form .form-control{background-color:white}.navbar-form .form-control:focus{border-color:white}.btn{border-width:2px}.btn:active{-webkit-box-shadow:none;box-shadow:none}.btn-group.open .dropdown-toggle{-webkit-box-shadow:none;box-shadow:none}.text-primary,.text-primary:hover{color:#4673a3}.text-success,.text-success:hover{color:#00bc8c}.text-danger,.text-danger:hover{color:#e74c3c}.text-warning,.text-warning:hover{color:#f39c12}.text-info,.text-info:hover{color:#3498db}table a:not(.btn),.table a:not(.btn){text-decoration:underline}table .dropdown-menu a,.table .dropdown-menu a{text-decoration:none}table .success,.table .success,table .warning,.table .warning,table .danger,.table .danger,table .info,.table .info{color:#fff}table .success>th>a,.table .success>th>a,table .warning>th>a,.table .warning>th>a,table .danger>th>a,.table .danger>th>a,table .info>th>a,.table .info>th>a,table .success>td>a,.table .success>td>a,table .warning>td>a,.table .warning>td>a,table .danger>td>a,.table .danger>td>a,table .info>td>a,.table .info>td>a,table .success>a,.table .success>a,table .warning>a,.table .warning>a,table .danger>a,.table .danger>a,table .info>a,.table .info>a{color:#fff}table>thead>tr>th,.table>thead>tr>th,table>tbody>tr>th,.table>tbody>tr>th,table>tfoot>tr>th,.table>tfoot>tr>th,table>thead>tr>td,.table>thead>tr>td,table>tbody>tr>td,.table>tbody>tr>td,table>tfoot>tr>td,.table>tfoot>tr>td{border:none}table-bordered>thead>tr>th,.table-bordered>thead>tr>th,table-bordered>tbody>tr>th,.table-bordered>tbody>tr>th,table-bordered>tfoot>tr>th,.table-bordered>tfoot>tr>th,table-bordered>thead>tr>td,.table-bordered>thead>tr>td,table-bordered>tbody>tr>td,.table-bordered>tbody>tr>td,table-bordered>tfoot>tr>td,.table-bordered>tfoot>tr>td{border:1px solid #464545}input,textarea{color:#464545}.form-control,input,textarea{border:2px hidden transparent;-webkit-box-shadow:none;box-shadow:none}.form-control:focus,input:focus,textarea:focus{-webkit-box-shadow:none;box-shadow:none}.form-control-feedback{color:#464545}.has-warning .help-block,.has-warning .control-label,.has-warning .radio,.has-warning .checkbox,.has-warning .radio-inline,.has-warning .checkbox-inline,.has-warning.radio label,.has-warning.checkbox label,.has-warning.radio-inline label,.has-warning.checkbox-inline label,.has-warning .form-control-feedback{color:#f39c12}.has-warning .form-control,.has-warning .form-control:focus{-webkit-box-shadow:none;box-shadow:none}.has-warning .input-group-addon{border-color:#f39c12}.has-error .help-block,.has-error .control-label,.has-error .radio,.has-error .checkbox,.has-error .radio-inline,.has-error .checkbox-inline,.has-error.radio label,.has-error.checkbox label,.has-error.radio-inline label,.has-error.checkbox-inline label,.has-error .form-control-feedback{color:#e74c3c}.has-error .form-control,.has-error .form-control:focus{-webkit-box-shadow:none;box-shadow:none}.has-error .input-group-addon{border-color:#e74c3c}.has-success .help-block,.has-success .control-label,.has-success .radio,.has-success .checkbox,.has-success .radio-inline,.has-success .checkbox-inline,.has-success.radio label,.has-success.checkbox label,.has-success.radio-inline label,.has-success.checkbox-inline label,.has-success .form-control-feedback{color:#00bc8c}.has-success .form-control,.has-success .form-control:focus{-webkit-box-shadow:none;box-shadow:none}.has-success .input-group-addon{border-color:#00bc8c}.input-group-addon{color:#ffffff}.nav .open>a,.nav .open>a:hover,.nav .open>a:focus{border-color:#464545}.nav-tabs>li>a,.nav-pills>li>a{color:#fff}.pager a,.pager a:hover{color:#fff}.pager .disabled>a,.pager .disabled>a:hover,.pager .disabled>a:focus,.pager .disabled>span{background-color:#007053}.breadcrumb a{color:#fff}.close{text-decoration:none;text-shadow:none;opacity:0.4}.close:hover,.close:focus{opacity:1}.alert .alert-link{color:#fff;text-decoration:underline}.progress{height:10px;-webkit-box-shadow:none;box-shadow:none}.progress .progress-bar{font-size:10px;line-height:10px}.well{-webkit-box-shadow:none;box-shadow:none}a.list-group-item.active,a.list-group-item.active:hover,a.list-group-item.active:focus{border-color:#464545}a.list-group-item-success.active{background-color:#00bc8c}a.list-group-item-success.active:hover,a.list-group-item-success.active:focus{background-color:#00a379}a.list-group-item-warning.active{background-color:#f39c12}a.list-group-item-warning.active:hover,a.list-group-item-warning.active:focus{background-color:#e08e0b}a.list-group-item-danger.active{background-color:#e74c3c}a.list-group-item-danger.active:hover,a.list-group-item-danger.active:focus{background-color:#e43725}.popover{color:#ffffff}.panel-default>.panel-heading{background-color:#464545}
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Household size-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Household size-1.png
index 0556204e4120b4fde5b788fd956a028b1b112d7a..3cb290a7cb5bded6a17e3a03fe5c7bf5efd28249 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Household size-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Household size-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Number metered-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Number metered-1.png
index d2c25376e04ab0044906947b639b4c7cfd32adea..93acaf4c8f28e1c2945243790f38f74dd55ad46f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Number metered-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Number metered-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total daily demand by household size & metering-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total daily demand by household size & metering-1.png
index 1fe679fc3bf66171c178289445a2a37a730928ad..ca22e98c680c4b3cb4a98e4e781686465c89611b 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total daily demand by household size & metering-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total daily demand by household size & metering-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by household size-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by household size-1.png
index 2e1cfe717a9da4b09c57078248a2dd642da65bf0..738d300f2fb14ae91b16c36a628f753ea4c2b659 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by household size-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by household size-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by metering-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by metering-1.png
index af4463e6ff43c0ebde2b7cf08512dbc435bd59b9..79b7794ac853b04418fddea1182be312ec62afd7 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by metering-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly demand by metering-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly external demand by household size-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly external demand by household size-1.png
index 9c09d4744377a472db38a5566c24186500c65d15..07f8983c1bf6056d73839424d64cebfc898a856e 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly external demand by household size-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/Total monthly external demand by household size-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-1.png
index ea0955223c2a21eb6552517bf1152e7eff860915..a59d68446409e4326aaae2d3479aba5769224d06 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-2.png
index ebf20c0e8ee10aa209243cbde90c2e9325e3e2dd..91163ae7a34d39056fe63fd0b31cf7a5e424cdd6 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-3.png
index bf943041a38c9b6c1c39268b0ff45fe2597b173b..d0db7cc05e221f57b7d9e3d36b05b3fbafb8666f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bath water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-1.png
index d1682fe8bffce808ab9cce02a985077bc37abbcf..84285c694c29229fda34011b19c8637a1460bfb1 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-2.png
index 17d278fb5bc01e5dcf1fe96dfca1afa6f00a65b0..2788e0655bac16e137cfd1823a080620622ac46c 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-3.png
index 460bae96d00bed64e023e4279a589900171597a7..80a3c0801362d31b4ea99b691472eb656e554e30 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/bathsink water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-1.png
index 67432954ff09ab42942ca478de714fef68185441..fde9ca0144456e621f4a1c6273dca14eb903c912 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-2.png
index 74a5e12e3fcb2fbbf9520e93c057cb6e152aca8b..a96f503b9d3b12b8ab6716577d1503f187bd42b9 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-3.png
index bab71273eabde4f4dadecbd368457649640c5556..8fe78c19af4223674930a9aba7360b9bce9c02e2 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/carwashing water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-1.png
index 27a7950f4c23b5a2e6e0b573f3b6475c8dd6a109..832e380974eb4dd18607a6090266e1472f47eb72 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-2.png
index 0494031dd1f41c0daafc36cbc7622cf95d41b878..37c8f0e1abd4090d981b93a58960fe339b94c97f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-3.png
index 87ba39c9f761edb4a9af8624bb14548aa93aea5f..ee3d7fd6062b6cd1c09e609a833b75e944d2e67f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/dishwasher water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-1.png
index 28424a088d00fd19263c8b7681fea9565abbd4bd..0bd6009f09721a15077cd2028e95cd9dce89951f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-2.png
index b775b5be6c3e3c45754a1947e50fbac3b8988f8f..7184faabe1380356929f29912ba3aa4103148c24 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-3.png
index 80b99a45f88cb810ed94c53f3085fa4c2d66f609..7b1469bd52c2dc0091ece953907b70f7ab732d7e 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/garden water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-1.png
index 82ecdbf4fd641d88e35769c97dbb7387de1667ff..c3b2e1177d8c203a675297b3f69419d98ea347f4 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-2.png
index cdc9fe043e298a5a4402345540fba01de2f3f17a..51ce6e474d27d259b31906ce3082c5ac143bf21f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-3.png
index 48e160703a8986f62f43a92b5314dba6d2fa6544..3fc95051a670abb0c818eac3f2f655568581d536 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/kitchensink water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-1.png
index af5016a4a91097d83c4ccf9fedd4510c13075778..50cb9175b51a129eff1898d2ac0f163ea8dd4e2f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-2.png
index 5bec9253fa702b0afbdc1a2130ba1bb87a8ef49b..a40d03bb19deababe51dcdd0e247090bd725590f 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-3.png
index d7eaf4e2b75a1dbea67204a3a4684d38cf2ec1fa..0dd49407cbba76b2ca9ee28b0225e5dae209bb2b 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/shower water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-1.png
index 45c6a04d28aeb9ae042cd1e3b433f973cf3da6f6..455718858d38f5e424a6cce19407335467bcecc1 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-2.png
index eb9a42788445c3798287108cd8df9b686d90e31c..49a21be471a1fa21a1172fba52f4b58476aa20a7 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-3.png
index e7d532aa65b67d3c9883af7468ee0cdc11cd8b0d..db3bfc87028fd188111e59adb3407fb5e2b278ad 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/toilet water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-1.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-1.png
index b4000941a10adb0d6bf0c223749b9da8b8dc717e..e61a7d7a00f7bb627e1851e5f55595a7c3099646 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-1.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-1.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-2.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-2.png
index 05a122c5155d366e5a13f4ccc8f5d71cec04b59c..4be39c0a6365b4caefef19257af4b2cc39d87b3d 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-2.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-2.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-3.png b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-3.png
index a20c20fe73430285e33c02d75811004afd73be56..1cb6d6c968697d2ca5c4f3cc66588ee81fb5369d 100644
Binary files a/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-3.png and b/model_v2/SPRG_demand_v2.1_BA_files/figure-html/washingmachine water demand plot-3.png differ
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/default.css b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/default.css
new file mode 100644
index 0000000000000000000000000000000000000000..6e7234a164fd83e8760ad05843fc7208deef6643
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/default.css
@@ -0,0 +1,21 @@
+.hljs-literal {
+ color: #990073;
+}
+
+.hljs-number {
+ color: #099;
+}
+
+.hljs-comment {
+ color: #998;
+ font-style: italic;
+}
+
+.hljs-keyword {
+ color: #900;
+ font-weight: bold;
+}
+
+.hljs-string {
+ color: #d14;
+}
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/highlight.js b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/highlight.js
new file mode 100644
index 0000000000000000000000000000000000000000..c1a8f62b937975ef03f96cc624bba0ab0f17332e
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/highlight.js
@@ -0,0 +1,2 @@
+/*! highlight.js v9.12.0 | BSD3 License | git.io/hljslicense */
+!function(e){var n="object"==typeof window&&window||"object"==typeof self&&self;"undefined"!=typeof exports?e(exports):n&&(n.hljs=e({}),"function"==typeof define&&define.amd&&define([],function(){return n.hljs}))}(function(e){function n(e){return e.replace(/&/g,"&").replace(/</g,"<").replace(/>/g,">")}function t(e){return e.nodeName.toLowerCase()}function r(e,n){var t=e&&e.exec(n);return t&&0===t.index}function a(e){return k.test(e)}function i(e){var n,t,r,i,o=e.className+" ";if(o+=e.parentNode?e.parentNode.className:"",t=B.exec(o))return w(t[1])?t[1]:"no-highlight";for(o=o.split(/\s+/),n=0,r=o.length;r>n;n++)if(i=o[n],a(i)||w(i))return i}function o(e){var n,t={},r=Array.prototype.slice.call(arguments,1);for(n in e)t[n]=e[n];return r.forEach(function(e){for(n in e)t[n]=e[n]}),t}function u(e){var n=[];return function r(e,a){for(var i=e.firstChild;i;i=i.nextSibling)3===i.nodeType?a+=i.nodeValue.length:1===i.nodeType&&(n.push({event:"start",offset:a,node:i}),a=r(i,a),t(i).match(/br|hr|img|input/)||n.push({event:"stop",offset:a,node:i}));return a}(e,0),n}function c(e,r,a){function i(){return e.length&&r.length?e[0].offset!==r[0].offset?e[0].offset<r[0].offset?e:r:"start"===r[0].event?e:r:e.length?e:r}function o(e){function r(e){return" "+e.nodeName+'="'+n(e.value).replace('"',""")+'"'}s+="<"+t(e)+E.map.call(e.attributes,r).join("")+">"}function u(e){s+="</"+t(e)+">"}function c(e){("start"===e.event?o:u)(e.node)}for(var l=0,s="",f=[];e.length||r.length;){var g=i();if(s+=n(a.substring(l,g[0].offset)),l=g[0].offset,g===e){f.reverse().forEach(u);do c(g.splice(0,1)[0]),g=i();while(g===e&&g.length&&g[0].offset===l);f.reverse().forEach(o)}else"start"===g[0].event?f.push(g[0].node):f.pop(),c(g.splice(0,1)[0])}return s+n(a.substr(l))}function l(e){return e.v&&!e.cached_variants&&(e.cached_variants=e.v.map(function(n){return o(e,{v:null},n)})),e.cached_variants||e.eW&&[o(e)]||[e]}function s(e){function n(e){return e&&e.source||e}function t(t,r){return new RegExp(n(t),"m"+(e.cI?"i":"")+(r?"g":""))}function r(a,i){if(!a.compiled){if(a.compiled=!0,a.k=a.k||a.bK,a.k){var o={},u=function(n,t){e.cI&&(t=t.toLowerCase()),t.split(" ").forEach(function(e){var t=e.split("|");o[t[0]]=[n,t[1]?Number(t[1]):1]})};"string"==typeof a.k?u("keyword",a.k):x(a.k).forEach(function(e){u(e,a.k[e])}),a.k=o}a.lR=t(a.l||/\w+/,!0),i&&(a.bK&&(a.b="\\b("+a.bK.split(" ").join("|")+")\\b"),a.b||(a.b=/\B|\b/),a.bR=t(a.b),a.e||a.eW||(a.e=/\B|\b/),a.e&&(a.eR=t(a.e)),a.tE=n(a.e)||"",a.eW&&i.tE&&(a.tE+=(a.e?"|":"")+i.tE)),a.i&&(a.iR=t(a.i)),null==a.r&&(a.r=1),a.c||(a.c=[]),a.c=Array.prototype.concat.apply([],a.c.map(function(e){return l("self"===e?a:e)})),a.c.forEach(function(e){r(e,a)}),a.starts&&r(a.starts,i);var c=a.c.map(function(e){return e.bK?"\\.?("+e.b+")\\.?":e.b}).concat([a.tE,a.i]).map(n).filter(Boolean);a.t=c.length?t(c.join("|"),!0):{exec:function(){return null}}}}r(e)}function f(e,t,a,i){function o(e,n){var t,a;for(t=0,a=n.c.length;a>t;t++)if(r(n.c[t].bR,e))return n.c[t]}function u(e,n){if(r(e.eR,n)){for(;e.endsParent&&e.parent;)e=e.parent;return e}return e.eW?u(e.parent,n):void 0}function c(e,n){return!a&&r(n.iR,e)}function l(e,n){var t=N.cI?n[0].toLowerCase():n[0];return e.k.hasOwnProperty(t)&&e.k[t]}function p(e,n,t,r){var a=r?"":I.classPrefix,i='<span class="'+a,o=t?"":C;return i+=e+'">',i+n+o}function h(){var e,t,r,a;if(!E.k)return n(k);for(a="",t=0,E.lR.lastIndex=0,r=E.lR.exec(k);r;)a+=n(k.substring(t,r.index)),e=l(E,r),e?(B+=e[1],a+=p(e[0],n(r[0]))):a+=n(r[0]),t=E.lR.lastIndex,r=E.lR.exec(k);return a+n(k.substr(t))}function d(){var e="string"==typeof E.sL;if(e&&!y[E.sL])return n(k);var t=e?f(E.sL,k,!0,x[E.sL]):g(k,E.sL.length?E.sL:void 0);return E.r>0&&(B+=t.r),e&&(x[E.sL]=t.top),p(t.language,t.value,!1,!0)}function b(){L+=null!=E.sL?d():h(),k=""}function v(e){L+=e.cN?p(e.cN,"",!0):"",E=Object.create(e,{parent:{value:E}})}function m(e,n){if(k+=e,null==n)return b(),0;var t=o(n,E);if(t)return t.skip?k+=n:(t.eB&&(k+=n),b(),t.rB||t.eB||(k=n)),v(t,n),t.rB?0:n.length;var r=u(E,n);if(r){var a=E;a.skip?k+=n:(a.rE||a.eE||(k+=n),b(),a.eE&&(k=n));do E.cN&&(L+=C),E.skip||(B+=E.r),E=E.parent;while(E!==r.parent);return r.starts&&v(r.starts,""),a.rE?0:n.length}if(c(n,E))throw new Error('Illegal lexeme "'+n+'" for mode "'+(E.cN||"<unnamed>")+'"');return k+=n,n.length||1}var N=w(e);if(!N)throw new Error('Unknown language: "'+e+'"');s(N);var R,E=i||N,x={},L="";for(R=E;R!==N;R=R.parent)R.cN&&(L=p(R.cN,"",!0)+L);var k="",B=0;try{for(var M,j,O=0;;){if(E.t.lastIndex=O,M=E.t.exec(t),!M)break;j=m(t.substring(O,M.index),M[0]),O=M.index+j}for(m(t.substr(O)),R=E;R.parent;R=R.parent)R.cN&&(L+=C);return{r:B,value:L,language:e,top:E}}catch(T){if(T.message&&-1!==T.message.indexOf("Illegal"))return{r:0,value:n(t)};throw T}}function g(e,t){t=t||I.languages||x(y);var r={r:0,value:n(e)},a=r;return t.filter(w).forEach(function(n){var t=f(n,e,!1);t.language=n,t.r>a.r&&(a=t),t.r>r.r&&(a=r,r=t)}),a.language&&(r.second_best=a),r}function p(e){return I.tabReplace||I.useBR?e.replace(M,function(e,n){return I.useBR&&"\n"===e?"<br>":I.tabReplace?n.replace(/\t/g,I.tabReplace):""}):e}function h(e,n,t){var r=n?L[n]:t,a=[e.trim()];return e.match(/\bhljs\b/)||a.push("hljs"),-1===e.indexOf(r)&&a.push(r),a.join(" ").trim()}function d(e){var n,t,r,o,l,s=i(e);a(s)||(I.useBR?(n=document.createElementNS("http://www.w3.org/1999/xhtml","div"),n.innerHTML=e.innerHTML.replace(/\n/g,"").replace(/<br[ \/]*>/g,"\n")):n=e,l=n.textContent,r=s?f(s,l,!0):g(l),t=u(n),t.length&&(o=document.createElementNS("http://www.w3.org/1999/xhtml","div"),o.innerHTML=r.value,r.value=c(t,u(o),l)),r.value=p(r.value),e.innerHTML=r.value,e.className=h(e.className,s,r.language),e.result={language:r.language,re:r.r},r.second_best&&(e.second_best={language:r.second_best.language,re:r.second_best.r}))}function b(e){I=o(I,e)}function v(){if(!v.called){v.called=!0;var e=document.querySelectorAll("pre code");E.forEach.call(e,d)}}function m(){addEventListener("DOMContentLoaded",v,!1),addEventListener("load",v,!1)}function N(n,t){var r=y[n]=t(e);r.aliases&&r.aliases.forEach(function(e){L[e]=n})}function R(){return x(y)}function w(e){return e=(e||"").toLowerCase(),y[e]||y[L[e]]}var E=[],x=Object.keys,y={},L={},k=/^(no-?highlight|plain|text)$/i,B=/\blang(?:uage)?-([\w-]+)\b/i,M=/((^(<[^>]+>|\t|)+|(?:\n)))/gm,C="</span>",I={classPrefix:"hljs-",tabReplace:null,useBR:!1,languages:void 0};return e.highlight=f,e.highlightAuto=g,e.fixMarkup=p,e.highlightBlock=d,e.configure=b,e.initHighlighting=v,e.initHighlightingOnLoad=m,e.registerLanguage=N,e.listLanguages=R,e.getLanguage=w,e.inherit=o,e.IR="[a-zA-Z]\\w*",e.UIR="[a-zA-Z_]\\w*",e.NR="\\b\\d+(\\.\\d+)?",e.CNR="(-?)(\\b0[xX][a-fA-F0-9]+|(\\b\\d+(\\.\\d*)?|\\.\\d+)([eE][-+]?\\d+)?)",e.BNR="\\b(0b[01]+)",e.RSR="!|!=|!==|%|%=|&|&&|&=|\\*|\\*=|\\+|\\+=|,|-|-=|/=|/|:|;|<<|<<=|<=|<|===|==|=|>>>=|>>=|>=|>>>|>>|>|\\?|\\[|\\{|\\(|\\^|\\^=|\\||\\|=|\\|\\||~",e.BE={b:"\\\\[\\s\\S]",r:0},e.ASM={cN:"string",b:"'",e:"'",i:"\\n",c:[e.BE]},e.QSM={cN:"string",b:'"',e:'"',i:"\\n",c:[e.BE]},e.PWM={b:/\b(a|an|the|are|I'm|isn't|don't|doesn't|won't|but|just|should|pretty|simply|enough|gonna|going|wtf|so|such|will|you|your|they|like|more)\b/},e.C=function(n,t,r){var a=e.inherit({cN:"comment",b:n,e:t,c:[]},r||{});return a.c.push(e.PWM),a.c.push({cN:"doctag",b:"(?:TODO|FIXME|NOTE|BUG|XXX):",r:0}),a},e.CLCM=e.C("//","$"),e.CBCM=e.C("/\\*","\\*/"),e.HCM=e.C("#","$"),e.NM={cN:"number",b:e.NR,r:0},e.CNM={cN:"number",b:e.CNR,r:0},e.BNM={cN:"number",b:e.BNR,r:0},e.CSSNM={cN:"number",b:e.NR+"(%|em|ex|ch|rem|vw|vh|vmin|vmax|cm|mm|in|pt|pc|px|deg|grad|rad|turn|s|ms|Hz|kHz|dpi|dpcm|dppx)?",r:0},e.RM={cN:"regexp",b:/\//,e:/\/[gimuy]*/,i:/\n/,c:[e.BE,{b:/\[/,e:/\]/,r:0,c:[e.BE]}]},e.TM={cN:"title",b:e.IR,r:0},e.UTM={cN:"title",b:e.UIR,r:0},e.METHOD_GUARD={b:"\\.\\s*"+e.UIR,r:0},e});hljs.registerLanguage("sql",function(e){var t=e.C("--","$");return{cI:!0,i:/[<>{}*#]/,c:[{bK:"begin end start commit rollback savepoint lock alter create drop rename call delete do handler insert load replace select truncate update set show pragma grant merge describe use explain help declare prepare execute deallocate release unlock purge reset change stop analyze cache flush optimize repair kill install uninstall checksum restore check backup revoke comment",e:/;/,eW:!0,l:/[\w\.]+/,k:{keyword:"abort abs absolute acc acce accep accept access accessed accessible account acos action activate add addtime admin administer advanced advise aes_decrypt aes_encrypt after agent aggregate ali alia alias allocate allow alter always analyze ancillary and any anydata anydataset anyschema anytype apply archive archived archivelog are as asc ascii asin assembly assertion associate asynchronous at atan atn2 attr attri attrib attribu attribut attribute attributes audit authenticated authentication authid authors auto autoallocate autodblink autoextend automatic availability avg backup badfile basicfile before begin beginning benchmark between bfile bfile_base big bigfile bin binary_double binary_float binlog bit_and bit_count bit_length bit_or bit_xor bitmap blob_base block blocksize body both bound buffer_cache buffer_pool build bulk by byte byteordermark bytes cache caching call calling cancel capacity cascade cascaded case cast catalog category ceil ceiling chain change changed char_base char_length character_length characters characterset charindex charset charsetform charsetid check checksum checksum_agg child choose chr chunk class cleanup clear client clob clob_base clone close cluster_id cluster_probability cluster_set clustering coalesce coercibility col collate collation collect colu colum column column_value columns columns_updated comment commit compact compatibility compiled complete composite_limit compound compress compute concat concat_ws concurrent confirm conn connec connect connect_by_iscycle connect_by_isleaf connect_by_root connect_time connection consider consistent constant constraint constraints constructor container content contents context contributors controlfile conv convert convert_tz corr corr_k corr_s corresponding corruption cos cost count count_big counted covar_pop covar_samp cpu_per_call cpu_per_session crc32 create creation critical cross cube cume_dist curdate current current_date current_time current_timestamp current_user cursor curtime customdatum cycle data database databases datafile datafiles datalength date_add date_cache date_format date_sub dateadd datediff datefromparts datename datepart datetime2fromparts day day_to_second dayname dayofmonth dayofweek dayofyear days db_role_change dbtimezone ddl deallocate declare decode decompose decrement decrypt deduplicate def defa defau defaul default defaults deferred defi defin define degrees delayed delegate delete delete_all delimited demand dense_rank depth dequeue des_decrypt des_encrypt des_key_file desc descr descri describ describe descriptor deterministic diagnostics difference dimension direct_load directory disable disable_all disallow disassociate discardfile disconnect diskgroup distinct distinctrow distribute distributed div do document domain dotnet double downgrade drop dumpfile duplicate duration each edition editionable editions element ellipsis else elsif elt empty enable enable_all enclosed encode encoding encrypt end end-exec endian enforced engine engines enqueue enterprise entityescaping eomonth error errors escaped evalname evaluate event eventdata events except exception exceptions exchange exclude excluding execu execut execute exempt exists exit exp expire explain export export_set extended extent external external_1 external_2 externally extract failed failed_login_attempts failover failure far fast feature_set feature_value fetch field fields file file_name_convert filesystem_like_logging final finish first first_value fixed flash_cache flashback floor flush following follows for forall force form forma format found found_rows freelist freelists freepools fresh from from_base64 from_days ftp full function general generated get get_format get_lock getdate getutcdate global global_name globally go goto grant grants greatest group group_concat group_id grouping grouping_id groups gtid_subtract guarantee guard handler hash hashkeys having hea head headi headin heading heap help hex hierarchy high high_priority hosts hour http id ident_current ident_incr ident_seed identified identity idle_time if ifnull ignore iif ilike ilm immediate import in include including increment index indexes indexing indextype indicator indices inet6_aton inet6_ntoa inet_aton inet_ntoa infile initial initialized initially initrans inmemory inner innodb input insert install instance instantiable instr interface interleaved intersect into invalidate invisible is is_free_lock is_ipv4 is_ipv4_compat is_not is_not_null is_used_lock isdate isnull isolation iterate java join json json_exists keep keep_duplicates key keys kill language large last last_day last_insert_id last_value lax lcase lead leading least leaves left len lenght length less level levels library like like2 like4 likec limit lines link list listagg little ln load load_file lob lobs local localtime localtimestamp locate locator lock locked log log10 log2 logfile logfiles logging logical logical_reads_per_call logoff logon logs long loop low low_priority lower lpad lrtrim ltrim main make_set makedate maketime managed management manual map mapping mask master master_pos_wait match matched materialized max maxextents maximize maxinstances maxlen maxlogfiles maxloghistory maxlogmembers maxsize maxtrans md5 measures median medium member memcompress memory merge microsecond mid migration min minextents minimum mining minus minute minvalue missing mod mode model modification modify module monitoring month months mount move movement multiset mutex name name_const names nan national native natural nav nchar nclob nested never new newline next nextval no no_write_to_binlog noarchivelog noaudit nobadfile nocheck nocompress nocopy nocycle nodelay nodiscardfile noentityescaping noguarantee nokeep nologfile nomapping nomaxvalue nominimize nominvalue nomonitoring none noneditionable nonschema noorder nopr nopro noprom nopromp noprompt norely noresetlogs noreverse normal norowdependencies noschemacheck noswitch not nothing notice notrim novalidate now nowait nth_value nullif nulls num numb numbe nvarchar nvarchar2 object ocicoll ocidate ocidatetime ociduration ociinterval ociloblocator ocinumber ociref ocirefcursor ocirowid ocistring ocitype oct octet_length of off offline offset oid oidindex old on online only opaque open operations operator optimal optimize option optionally or oracle oracle_date oradata ord ordaudio orddicom orddoc order ordimage ordinality ordvideo organization orlany orlvary out outer outfile outline output over overflow overriding package pad parallel parallel_enable parameters parent parse partial partition partitions pascal passing password password_grace_time password_lock_time password_reuse_max password_reuse_time password_verify_function patch path patindex pctincrease pctthreshold pctused pctversion percent percent_rank percentile_cont percentile_disc performance period period_add period_diff permanent physical pi pipe pipelined pivot pluggable plugin policy position post_transaction pow power pragma prebuilt precedes preceding precision prediction prediction_cost prediction_details prediction_probability prediction_set prepare present preserve prior priority private private_sga privileges procedural procedure procedure_analyze processlist profiles project prompt protection public publishingservername purge quarter query quick quiesce quota quotename radians raise rand range rank raw read reads readsize rebuild record records recover recovery recursive recycle redo reduced ref reference referenced references referencing refresh regexp_like register regr_avgx regr_avgy regr_count regr_intercept regr_r2 regr_slope regr_sxx regr_sxy reject rekey relational relative relaylog release release_lock relies_on relocate rely rem remainder rename repair repeat replace replicate replication required reset resetlogs resize resource respect restore restricted result result_cache resumable resume retention return returning returns reuse reverse revoke right rlike role roles rollback rolling rollup round row row_count rowdependencies rowid rownum rows rtrim rules safe salt sample save savepoint sb1 sb2 sb4 scan schema schemacheck scn scope scroll sdo_georaster sdo_topo_geometry search sec_to_time second section securefile security seed segment select self sequence sequential serializable server servererror session session_user sessions_per_user set sets settings sha sha1 sha2 share shared shared_pool short show shrink shutdown si_averagecolor si_colorhistogram si_featurelist si_positionalcolor si_stillimage si_texture siblings sid sign sin size size_t sizes skip slave sleep smalldatetimefromparts smallfile snapshot some soname sort soundex source space sparse spfile split sql sql_big_result sql_buffer_result sql_cache sql_calc_found_rows sql_small_result sql_variant_property sqlcode sqldata sqlerror sqlname sqlstate sqrt square standalone standby start starting startup statement static statistics stats_binomial_test stats_crosstab stats_ks_test stats_mode stats_mw_test stats_one_way_anova stats_t_test_ stats_t_test_indep stats_t_test_one stats_t_test_paired stats_wsr_test status std stddev stddev_pop stddev_samp stdev stop storage store stored str str_to_date straight_join strcmp strict string struct stuff style subdate subpartition subpartitions substitutable substr substring subtime subtring_index subtype success sum suspend switch switchoffset switchover sync synchronous synonym sys sys_xmlagg sysasm sysaux sysdate sysdatetimeoffset sysdba sysoper system system_user sysutcdatetime table tables tablespace tan tdo template temporary terminated tertiary_weights test than then thread through tier ties time time_format time_zone timediff timefromparts timeout timestamp timestampadd timestampdiff timezone_abbr timezone_minute timezone_region to to_base64 to_date to_days to_seconds todatetimeoffset trace tracking transaction transactional translate translation treat trigger trigger_nestlevel triggers trim truncate try_cast try_convert try_parse type ub1 ub2 ub4 ucase unarchived unbounded uncompress under undo unhex unicode uniform uninstall union unique unix_timestamp unknown unlimited unlock unpivot unrecoverable unsafe unsigned until untrusted unusable unused update updated upgrade upped upper upsert url urowid usable usage use use_stored_outlines user user_data user_resources users using utc_date utc_timestamp uuid uuid_short validate validate_password_strength validation valist value values var var_samp varcharc vari varia variab variabl variable variables variance varp varraw varrawc varray verify version versions view virtual visible void wait wallet warning warnings week weekday weekofyear wellformed when whene whenev wheneve whenever where while whitespace with within without work wrapped xdb xml xmlagg xmlattributes xmlcast xmlcolattval xmlelement xmlexists xmlforest xmlindex xmlnamespaces xmlpi xmlquery xmlroot xmlschema xmlserialize xmltable xmltype xor year year_to_month years yearweek",literal:"true false null",built_in:"array bigint binary bit blob boolean char character date dec decimal float int int8 integer interval number numeric real record serial serial8 smallint text varchar varying void"},c:[{cN:"string",b:"'",e:"'",c:[e.BE,{b:"''"}]},{cN:"string",b:'"',e:'"',c:[e.BE,{b:'""'}]},{cN:"string",b:"`",e:"`",c:[e.BE]},e.CNM,e.CBCM,t]},e.CBCM,t]}});hljs.registerLanguage("r",function(e){var r="([a-zA-Z]|\\.[a-zA-Z.])[a-zA-Z0-9._]*";return{c:[e.HCM,{b:r,l:r,k:{keyword:"function if in break next repeat else for return switch while try tryCatch stop warning require library attach detach source setMethod setGeneric setGroupGeneric setClass ...",literal:"NULL NA TRUE FALSE T F Inf NaN NA_integer_|10 NA_real_|10 NA_character_|10 NA_complex_|10"},r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"\\d+(?:[eE][+\\-]?\\d*)?L\\b",r:0},{cN:"number",b:"\\d+\\.(?!\\d)(?:i\\b)?",r:0},{cN:"number",b:"\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{b:"`",e:"`",r:0},{cN:"string",c:[e.BE],v:[{b:'"',e:'"'},{b:"'",e:"'"}]}]}});hljs.registerLanguage("perl",function(e){var t="getpwent getservent quotemeta msgrcv scalar kill dbmclose undef lc ma syswrite tr send umask sysopen shmwrite vec qx utime local oct semctl localtime readpipe do return format read sprintf dbmopen pop getpgrp not getpwnam rewinddir qqfileno qw endprotoent wait sethostent bless s|0 opendir continue each sleep endgrent shutdown dump chomp connect getsockname die socketpair close flock exists index shmgetsub for endpwent redo lstat msgctl setpgrp abs exit select print ref gethostbyaddr unshift fcntl syscall goto getnetbyaddr join gmtime symlink semget splice x|0 getpeername recv log setsockopt cos last reverse gethostbyname getgrnam study formline endhostent times chop length gethostent getnetent pack getprotoent getservbyname rand mkdir pos chmod y|0 substr endnetent printf next open msgsnd readdir use unlink getsockopt getpriority rindex wantarray hex system getservbyport endservent int chr untie rmdir prototype tell listen fork shmread ucfirst setprotoent else sysseek link getgrgid shmctl waitpid unpack getnetbyname reset chdir grep split require caller lcfirst until warn while values shift telldir getpwuid my getprotobynumber delete and sort uc defined srand accept package seekdir getprotobyname semop our rename seek if q|0 chroot sysread setpwent no crypt getc chown sqrt write setnetent setpriority foreach tie sin msgget map stat getlogin unless elsif truncate exec keys glob tied closedirioctl socket readlink eval xor readline binmode setservent eof ord bind alarm pipe atan2 getgrent exp time push setgrent gt lt or ne m|0 break given say state when",r={cN:"subst",b:"[$@]\\{",e:"\\}",k:t},s={b:"->{",e:"}"},n={v:[{b:/\$\d/},{b:/[\$%@](\^\w\b|#\w+(::\w+)*|{\w+}|\w+(::\w*)*)/},{b:/[\$%@][^\s\w{]/,r:0}]},i=[e.BE,r,n],o=[n,e.HCM,e.C("^\\=\\w","\\=cut",{eW:!0}),s,{cN:"string",c:i,v:[{b:"q[qwxr]?\\s*\\(",e:"\\)",r:5},{b:"q[qwxr]?\\s*\\[",e:"\\]",r:5},{b:"q[qwxr]?\\s*\\{",e:"\\}",r:5},{b:"q[qwxr]?\\s*\\|",e:"\\|",r:5},{b:"q[qwxr]?\\s*\\<",e:"\\>",r:5},{b:"qw\\s+q",e:"q",r:5},{b:"'",e:"'",c:[e.BE]},{b:'"',e:'"'},{b:"`",e:"`",c:[e.BE]},{b:"{\\w+}",c:[],r:0},{b:"-?\\w+\\s*\\=\\>",c:[],r:0}]},{cN:"number",b:"(\\b0[0-7_]+)|(\\b0x[0-9a-fA-F_]+)|(\\b[1-9][0-9_]*(\\.[0-9_]+)?)|[0_]\\b",r:0},{b:"(\\/\\/|"+e.RSR+"|\\b(split|return|print|reverse|grep)\\b)\\s*",k:"split return print reverse grep",r:0,c:[e.HCM,{cN:"regexp",b:"(s|tr|y)/(\\\\.|[^/])*/(\\\\.|[^/])*/[a-z]*",r:10},{cN:"regexp",b:"(m|qr)?/",e:"/[a-z]*",c:[e.BE],r:0}]},{cN:"function",bK:"sub",e:"(\\s*\\(.*?\\))?[;{]",eE:!0,r:5,c:[e.TM]},{b:"-\\w\\b",r:0},{b:"^__DATA__$",e:"^__END__$",sL:"mojolicious",c:[{b:"^@@.*",e:"$",cN:"comment"}]}];return r.c=o,s.c=o,{aliases:["pl","pm"],l:/[\w\.]+/,k:t,c:o}});hljs.registerLanguage("ini",function(e){var b={cN:"string",c:[e.BE],v:[{b:"'''",e:"'''",r:10},{b:'"""',e:'"""',r:10},{b:'"',e:'"'},{b:"'",e:"'"}]};return{aliases:["toml"],cI:!0,i:/\S/,c:[e.C(";","$"),e.HCM,{cN:"section",b:/^\s*\[+/,e:/\]+/},{b:/^[a-z0-9\[\]_-]+\s*=\s*/,e:"$",rB:!0,c:[{cN:"attr",b:/[a-z0-9\[\]_-]+/},{b:/=/,eW:!0,r:0,c:[{cN:"literal",b:/\bon|off|true|false|yes|no\b/},{cN:"variable",v:[{b:/\$[\w\d"][\w\d_]*/},{b:/\$\{(.*?)}/}]},b,{cN:"number",b:/([\+\-]+)?[\d]+_[\d_]+/},e.NM]}]}]}});hljs.registerLanguage("diff",function(e){return{aliases:["patch"],c:[{cN:"meta",r:10,v:[{b:/^@@ +\-\d+,\d+ +\+\d+,\d+ +@@$/},{b:/^\*\*\* +\d+,\d+ +\*\*\*\*$/},{b:/^\-\-\- +\d+,\d+ +\-\-\-\-$/}]},{cN:"comment",v:[{b:/Index: /,e:/$/},{b:/={3,}/,e:/$/},{b:/^\-{3}/,e:/$/},{b:/^\*{3} /,e:/$/},{b:/^\+{3}/,e:/$/},{b:/\*{5}/,e:/\*{5}$/}]},{cN:"addition",b:"^\\+",e:"$"},{cN:"deletion",b:"^\\-",e:"$"},{cN:"addition",b:"^\\!",e:"$"}]}});hljs.registerLanguage("go",function(e){var t={keyword:"break default func interface select case map struct chan else goto package switch const fallthrough if range type continue for import return var go defer bool byte complex64 complex128 float32 float64 int8 int16 int32 int64 string uint8 uint16 uint32 uint64 int uint uintptr rune",literal:"true false iota nil",built_in:"append cap close complex copy imag len make new panic print println real recover delete"};return{aliases:["golang"],k:t,i:"</",c:[e.CLCM,e.CBCM,{cN:"string",v:[e.QSM,{b:"'",e:"[^\\\\]'"},{b:"`",e:"`"}]},{cN:"number",v:[{b:e.CNR+"[dflsi]",r:1},e.CNM]},{b:/:=/},{cN:"function",bK:"func",e:/\s*\{/,eE:!0,c:[e.TM,{cN:"params",b:/\(/,e:/\)/,k:t,i:/["']/}]}]}});hljs.registerLanguage("bash",function(e){var t={cN:"variable",v:[{b:/\$[\w\d#@][\w\d_]*/},{b:/\$\{(.*?)}/}]},s={cN:"string",b:/"/,e:/"/,c:[e.BE,t,{cN:"variable",b:/\$\(/,e:/\)/,c:[e.BE]}]},a={cN:"string",b:/'/,e:/'/};return{aliases:["sh","zsh"],l:/\b-?[a-z\._]+\b/,k:{keyword:"if then else elif fi for while in do done case esac function",literal:"true false",built_in:"break cd continue eval exec exit export getopts hash pwd readonly return shift test times trap umask unset alias bind builtin caller command declare echo enable help let local logout mapfile printf read readarray source type typeset ulimit unalias set shopt autoload bg bindkey bye cap chdir clone comparguments compcall compctl compdescribe compfiles compgroups compquote comptags comptry compvalues dirs disable disown echotc echoti emulate fc fg float functions getcap getln history integer jobs kill limit log noglob popd print pushd pushln rehash sched setcap setopt stat suspend ttyctl unfunction unhash unlimit unsetopt vared wait whence where which zcompile zformat zftp zle zmodload zparseopts zprof zpty zregexparse zsocket zstyle ztcp",_:"-ne -eq -lt -gt -f -d -e -s -l -a"},c:[{cN:"meta",b:/^#![^\n]+sh\s*$/,r:10},{cN:"function",b:/\w[\w\d_]*\s*\(\s*\)\s*\{/,rB:!0,c:[e.inherit(e.TM,{b:/\w[\w\d_]*/})],r:0},e.HCM,s,a,t]}});hljs.registerLanguage("python",function(e){var r={keyword:"and elif is global as in if from raise for except finally print import pass return exec else break not with class assert yield try while continue del or def lambda async await nonlocal|10 None True False",built_in:"Ellipsis NotImplemented"},b={cN:"meta",b:/^(>>>|\.\.\.) /},c={cN:"subst",b:/\{/,e:/\}/,k:r,i:/#/},a={cN:"string",c:[e.BE],v:[{b:/(u|b)?r?'''/,e:/'''/,c:[b],r:10},{b:/(u|b)?r?"""/,e:/"""/,c:[b],r:10},{b:/(fr|rf|f)'''/,e:/'''/,c:[b,c]},{b:/(fr|rf|f)"""/,e:/"""/,c:[b,c]},{b:/(u|r|ur)'/,e:/'/,r:10},{b:/(u|r|ur)"/,e:/"/,r:10},{b:/(b|br)'/,e:/'/},{b:/(b|br)"/,e:/"/},{b:/(fr|rf|f)'/,e:/'/,c:[c]},{b:/(fr|rf|f)"/,e:/"/,c:[c]},e.ASM,e.QSM]},s={cN:"number",r:0,v:[{b:e.BNR+"[lLjJ]?"},{b:"\\b(0o[0-7]+)[lLjJ]?"},{b:e.CNR+"[lLjJ]?"}]},i={cN:"params",b:/\(/,e:/\)/,c:["self",b,s,a]};return c.c=[a,s,b],{aliases:["py","gyp"],k:r,i:/(<\/|->|\?)|=>/,c:[b,s,a,e.HCM,{v:[{cN:"function",bK:"def"},{cN:"class",bK:"class"}],e:/:/,i:/[${=;\n,]/,c:[e.UTM,i,{b:/->/,eW:!0,k:"None"}]},{cN:"meta",b:/^[\t ]*@/,e:/$/},{b:/\b(print|exec)\(/}]}});hljs.registerLanguage("julia",function(e){var r={keyword:"in isa where baremodule begin break catch ccall const continue do else elseif end export false finally for function global if import importall let local macro module quote return true try using while type immutable abstract bitstype typealias ",literal:"true false ARGS C_NULL DevNull ENDIAN_BOM ENV I Inf Inf16 Inf32 Inf64 InsertionSort JULIA_HOME LOAD_PATH MergeSort NaN NaN16 NaN32 NaN64 PROGRAM_FILE QuickSort RoundDown RoundFromZero RoundNearest RoundNearestTiesAway RoundNearestTiesUp RoundToZero RoundUp STDERR STDIN STDOUT VERSION catalan e|0 eu|0 eulergamma golden im nothing pi γ π φ ",built_in:"ANY AbstractArray AbstractChannel AbstractFloat AbstractMatrix AbstractRNG AbstractSerializer AbstractSet AbstractSparseArray AbstractSparseMatrix AbstractSparseVector AbstractString AbstractUnitRange AbstractVecOrMat AbstractVector Any ArgumentError Array AssertionError Associative Base64DecodePipe Base64EncodePipe Bidiagonal BigFloat BigInt BitArray BitMatrix BitVector Bool BoundsError BufferStream CachingPool CapturedException CartesianIndex CartesianRange Cchar Cdouble Cfloat Channel Char Cint Cintmax_t Clong Clonglong ClusterManager Cmd CodeInfo Colon Complex Complex128 Complex32 Complex64 CompositeException Condition ConjArray ConjMatrix ConjVector Cptrdiff_t Cshort Csize_t Cssize_t Cstring Cuchar Cuint Cuintmax_t Culong Culonglong Cushort Cwchar_t Cwstring DataType Date DateFormat DateTime DenseArray DenseMatrix DenseVecOrMat DenseVector Diagonal Dict DimensionMismatch Dims DirectIndexString Display DivideError DomainError EOFError EachLine Enum Enumerate ErrorException Exception ExponentialBackOff Expr Factorization FileMonitor Float16 Float32 Float64 Function Future GlobalRef GotoNode HTML Hermitian IO IOBuffer IOContext IOStream IPAddr IPv4 IPv6 IndexCartesian IndexLinear IndexStyle InexactError InitError Int Int128 Int16 Int32 Int64 Int8 IntSet Integer InterruptException InvalidStateException Irrational KeyError LabelNode LinSpace LineNumberNode LoadError LowerTriangular MIME Matrix MersenneTwister Method MethodError MethodTable Module NTuple NewvarNode NullException Nullable Number ObjectIdDict OrdinalRange OutOfMemoryError OverflowError Pair ParseError PartialQuickSort PermutedDimsArray Pipe PollingFileWatcher ProcessExitedException Ptr QuoteNode RandomDevice Range RangeIndex Rational RawFD ReadOnlyMemoryError Real ReentrantLock Ref Regex RegexMatch RemoteChannel RemoteException RevString RoundingMode RowVector SSAValue SegmentationFault SerializationState Set SharedArray SharedMatrix SharedVector Signed SimpleVector Slot SlotNumber SparseMatrixCSC SparseVector StackFrame StackOverflowError StackTrace StepRange StepRangeLen StridedArray StridedMatrix StridedVecOrMat StridedVector String SubArray SubString SymTridiagonal Symbol Symmetric SystemError TCPSocket Task Text TextDisplay Timer Tridiagonal Tuple Type TypeError TypeMapEntry TypeMapLevel TypeName TypeVar TypedSlot UDPSocket UInt UInt128 UInt16 UInt32 UInt64 UInt8 UndefRefError UndefVarError UnicodeError UniformScaling Union UnionAll UnitRange Unsigned UpperTriangular Val Vararg VecElement VecOrMat Vector VersionNumber Void WeakKeyDict WeakRef WorkerConfig WorkerPool "},t="[A-Za-z_\\u00A1-\\uFFFF][A-Za-z_0-9\\u00A1-\\uFFFF]*",a={l:t,k:r,i:/<\//},n={cN:"number",b:/(\b0x[\d_]*(\.[\d_]*)?|0x\.\d[\d_]*)p[-+]?\d+|\b0[box][a-fA-F0-9][a-fA-F0-9_]*|(\b\d[\d_]*(\.[\d_]*)?|\.\d[\d_]*)([eEfF][-+]?\d+)?/,r:0},o={cN:"string",b:/'(.|\\[xXuU][a-zA-Z0-9]+)'/},i={cN:"subst",b:/\$\(/,e:/\)/,k:r},l={cN:"variable",b:"\\$"+t},c={cN:"string",c:[e.BE,i,l],v:[{b:/\w*"""/,e:/"""\w*/,r:10},{b:/\w*"/,e:/"\w*/}]},s={cN:"string",c:[e.BE,i,l],b:"`",e:"`"},d={cN:"meta",b:"@"+t},u={cN:"comment",v:[{b:"#=",e:"=#",r:10},{b:"#",e:"$"}]};return a.c=[n,o,c,s,d,u,e.HCM,{cN:"keyword",b:"\\b(((abstract|primitive)\\s+)type|(mutable\\s+)?struct)\\b"},{b:/<:/}],i.c=a.c,a});hljs.registerLanguage("coffeescript",function(e){var c={keyword:"in if for while finally new do return else break catch instanceof throw try this switch continue typeof delete debugger super yield import export from as default await then unless until loop of by when and or is isnt not",literal:"true false null undefined yes no on off",built_in:"npm require console print module global window document"},n="[A-Za-z$_][0-9A-Za-z$_]*",r={cN:"subst",b:/#\{/,e:/}/,k:c},i=[e.BNM,e.inherit(e.CNM,{starts:{e:"(\\s*/)?",r:0}}),{cN:"string",v:[{b:/'''/,e:/'''/,c:[e.BE]},{b:/'/,e:/'/,c:[e.BE]},{b:/"""/,e:/"""/,c:[e.BE,r]},{b:/"/,e:/"/,c:[e.BE,r]}]},{cN:"regexp",v:[{b:"///",e:"///",c:[r,e.HCM]},{b:"//[gim]*",r:0},{b:/\/(?![ *])(\\\/|.)*?\/[gim]*(?=\W|$)/}]},{b:"@"+n},{sL:"javascript",eB:!0,eE:!0,v:[{b:"```",e:"```"},{b:"`",e:"`"}]}];r.c=i;var s=e.inherit(e.TM,{b:n}),t="(\\(.*\\))?\\s*\\B[-=]>",o={cN:"params",b:"\\([^\\(]",rB:!0,c:[{b:/\(/,e:/\)/,k:c,c:["self"].concat(i)}]};return{aliases:["coffee","cson","iced"],k:c,i:/\/\*/,c:i.concat([e.C("###","###"),e.HCM,{cN:"function",b:"^\\s*"+n+"\\s*=\\s*"+t,e:"[-=]>",rB:!0,c:[s,o]},{b:/[:\(,=]\s*/,r:0,c:[{cN:"function",b:t,e:"[-=]>",rB:!0,c:[o]}]},{cN:"class",bK:"class",e:"$",i:/[:="\[\]]/,c:[{bK:"extends",eW:!0,i:/[:="\[\]]/,c:[s]},s]},{b:n+":",e:":",rB:!0,rE:!0,r:0}])}});hljs.registerLanguage("cpp",function(t){var e={cN:"keyword",b:"\\b[a-z\\d_]*_t\\b"},r={cN:"string",v:[{b:'(u8?|U)?L?"',e:'"',i:"\\n",c:[t.BE]},{b:'(u8?|U)?R"',e:'"',c:[t.BE]},{b:"'\\\\?.",e:"'",i:"."}]},s={cN:"number",v:[{b:"\\b(0b[01']+)"},{b:"(-?)\\b([\\d']+(\\.[\\d']*)?|\\.[\\d']+)(u|U|l|L|ul|UL|f|F|b|B)"},{b:"(-?)(\\b0[xX][a-fA-F0-9']+|(\\b[\\d']+(\\.[\\d']*)?|\\.[\\d']+)([eE][-+]?[\\d']+)?)"}],r:0},i={cN:"meta",b:/#\s*[a-z]+\b/,e:/$/,k:{"meta-keyword":"if else elif endif define undef warning error line pragma ifdef ifndef include"},c:[{b:/\\\n/,r:0},t.inherit(r,{cN:"meta-string"}),{cN:"meta-string",b:/<[^\n>]*>/,e:/$/,i:"\\n"},t.CLCM,t.CBCM]},a=t.IR+"\\s*\\(",c={keyword:"int float while private char catch import module export virtual operator sizeof dynamic_cast|10 typedef const_cast|10 const for static_cast|10 union namespace unsigned long volatile static protected bool template mutable if public friend do goto auto void enum else break extern using asm case typeid short reinterpret_cast|10 default double register explicit signed typename try this switch continue inline delete alignof constexpr decltype noexcept static_assert thread_local restrict _Bool complex _Complex _Imaginary atomic_bool atomic_char atomic_schar atomic_uchar atomic_short atomic_ushort atomic_int atomic_uint atomic_long atomic_ulong atomic_llong atomic_ullong new throw return and or not",built_in:"std string cin cout cerr clog stdin stdout stderr stringstream istringstream ostringstream auto_ptr deque list queue stack vector map set bitset multiset multimap unordered_set unordered_map unordered_multiset unordered_multimap array shared_ptr abort abs acos asin atan2 atan calloc ceil cosh cos exit exp fabs floor fmod fprintf fputs free frexp fscanf isalnum isalpha iscntrl isdigit isgraph islower isprint ispunct isspace isupper isxdigit tolower toupper labs ldexp log10 log malloc realloc memchr memcmp memcpy memset modf pow printf putchar puts scanf sinh sin snprintf sprintf sqrt sscanf strcat strchr strcmp strcpy strcspn strlen strncat strncmp strncpy strpbrk strrchr strspn strstr tanh tan vfprintf vprintf vsprintf endl initializer_list unique_ptr",literal:"true false nullptr NULL"},n=[e,t.CLCM,t.CBCM,s,r];return{aliases:["c","cc","h","c++","h++","hpp"],k:c,i:"</",c:n.concat([i,{b:"\\b(deque|list|queue|stack|vector|map|set|bitset|multiset|multimap|unordered_map|unordered_set|unordered_multiset|unordered_multimap|array)\\s*<",e:">",k:c,c:["self",e]},{b:t.IR+"::",k:c},{v:[{b:/=/,e:/;/},{b:/\(/,e:/\)/},{bK:"new throw return else",e:/;/}],k:c,c:n.concat([{b:/\(/,e:/\)/,k:c,c:n.concat(["self"]),r:0}]),r:0},{cN:"function",b:"("+t.IR+"[\\*&\\s]+)+"+a,rB:!0,e:/[{;=]/,eE:!0,k:c,i:/[^\w\s\*&]/,c:[{b:a,rB:!0,c:[t.TM],r:0},{cN:"params",b:/\(/,e:/\)/,k:c,r:0,c:[t.CLCM,t.CBCM,r,s,e]},t.CLCM,t.CBCM,i]},{cN:"class",bK:"class struct",e:/[{;:]/,c:[{b:/</,e:/>/,c:["self"]},t.TM]}]),exports:{preprocessor:i,strings:r,k:c}}});hljs.registerLanguage("ruby",function(e){var b="[a-zA-Z_]\\w*[!?=]?|[-+~]\\@|<<|>>|=~|===?|<=>|[<>]=?|\\*\\*|[-/+%^&*~`|]|\\[\\]=?",r={keyword:"and then defined module in return redo if BEGIN retry end for self when next until do begin unless END rescue else break undef not super class case require yield alias while ensure elsif or include attr_reader attr_writer attr_accessor",literal:"true false nil"},c={cN:"doctag",b:"@[A-Za-z]+"},a={b:"#<",e:">"},s=[e.C("#","$",{c:[c]}),e.C("^\\=begin","^\\=end",{c:[c],r:10}),e.C("^__END__","\\n$")],n={cN:"subst",b:"#\\{",e:"}",k:r},t={cN:"string",c:[e.BE,n],v:[{b:/'/,e:/'/},{b:/"/,e:/"/},{b:/`/,e:/`/},{b:"%[qQwWx]?\\(",e:"\\)"},{b:"%[qQwWx]?\\[",e:"\\]"},{b:"%[qQwWx]?{",e:"}"},{b:"%[qQwWx]?<",e:">"},{b:"%[qQwWx]?/",e:"/"},{b:"%[qQwWx]?%",e:"%"},{b:"%[qQwWx]?-",e:"-"},{b:"%[qQwWx]?\\|",e:"\\|"},{b:/\B\?(\\\d{1,3}|\\x[A-Fa-f0-9]{1,2}|\\u[A-Fa-f0-9]{4}|\\?\S)\b/},{b:/<<(-?)\w+$/,e:/^\s*\w+$/}]},i={cN:"params",b:"\\(",e:"\\)",endsParent:!0,k:r},d=[t,a,{cN:"class",bK:"class module",e:"$|;",i:/=/,c:[e.inherit(e.TM,{b:"[A-Za-z_]\\w*(::\\w+)*(\\?|\\!)?"}),{b:"<\\s*",c:[{b:"("+e.IR+"::)?"+e.IR}]}].concat(s)},{cN:"function",bK:"def",e:"$|;",c:[e.inherit(e.TM,{b:b}),i].concat(s)},{b:e.IR+"::"},{cN:"symbol",b:e.UIR+"(\\!|\\?)?:",r:0},{cN:"symbol",b:":(?!\\s)",c:[t,{b:b}],r:0},{cN:"number",b:"(\\b0[0-7_]+)|(\\b0x[0-9a-fA-F_]+)|(\\b[1-9][0-9_]*(\\.[0-9_]+)?)|[0_]\\b",r:0},{b:"(\\$\\W)|((\\$|\\@\\@?)(\\w+))"},{cN:"params",b:/\|/,e:/\|/,k:r},{b:"("+e.RSR+"|unless)\\s*",k:"unless",c:[a,{cN:"regexp",c:[e.BE,n],i:/\n/,v:[{b:"/",e:"/[a-z]*"},{b:"%r{",e:"}[a-z]*"},{b:"%r\\(",e:"\\)[a-z]*"},{b:"%r!",e:"![a-z]*"},{b:"%r\\[",e:"\\][a-z]*"}]}].concat(s),r:0}].concat(s);n.c=d,i.c=d;var l="[>?]>",o="[\\w#]+\\(\\w+\\):\\d+:\\d+>",u="(\\w+-)?\\d+\\.\\d+\\.\\d(p\\d+)?[^>]+>",w=[{b:/^\s*=>/,starts:{e:"$",c:d}},{cN:"meta",b:"^("+l+"|"+o+"|"+u+")",starts:{e:"$",c:d}}];return{aliases:["rb","gemspec","podspec","thor","irb"],k:r,i:/\/\*/,c:s.concat(w).concat(d)}});hljs.registerLanguage("yaml",function(e){var b="true false yes no null",a="^[ \\-]*",r="[a-zA-Z_][\\w\\-]*",t={cN:"attr",v:[{b:a+r+":"},{b:a+'"'+r+'":'},{b:a+"'"+r+"':"}]},c={cN:"template-variable",v:[{b:"{{",e:"}}"},{b:"%{",e:"}"}]},l={cN:"string",r:0,v:[{b:/'/,e:/'/},{b:/"/,e:/"/},{b:/\S+/}],c:[e.BE,c]};return{cI:!0,aliases:["yml","YAML","yaml"],c:[t,{cN:"meta",b:"^---s*$",r:10},{cN:"string",b:"[\\|>] *$",rE:!0,c:l.c,e:t.v[0].b},{b:"<%[%=-]?",e:"[%-]?%>",sL:"ruby",eB:!0,eE:!0,r:0},{cN:"type",b:"!!"+e.UIR},{cN:"meta",b:"&"+e.UIR+"$"},{cN:"meta",b:"\\*"+e.UIR+"$"},{cN:"bullet",b:"^ *-",r:0},e.HCM,{bK:b,k:{literal:b}},e.CNM,l]}});hljs.registerLanguage("css",function(e){var c="[a-zA-Z-][a-zA-Z0-9_-]*",t={b:/[A-Z\_\.\-]+\s*:/,rB:!0,e:";",eW:!0,c:[{cN:"attribute",b:/\S/,e:":",eE:!0,starts:{eW:!0,eE:!0,c:[{b:/[\w-]+\(/,rB:!0,c:[{cN:"built_in",b:/[\w-]+/},{b:/\(/,e:/\)/,c:[e.ASM,e.QSM]}]},e.CSSNM,e.QSM,e.ASM,e.CBCM,{cN:"number",b:"#[0-9A-Fa-f]+"},{cN:"meta",b:"!important"}]}}]};return{cI:!0,i:/[=\/|'\$]/,c:[e.CBCM,{cN:"selector-id",b:/#[A-Za-z0-9_-]+/},{cN:"selector-class",b:/\.[A-Za-z0-9_-]+/},{cN:"selector-attr",b:/\[/,e:/\]/,i:"$"},{cN:"selector-pseudo",b:/:(:)?[a-zA-Z0-9\_\-\+\(\)"'.]+/},{b:"@(font-face|page)",l:"[a-z-]+",k:"font-face page"},{b:"@",e:"[{;]",i:/:/,c:[{cN:"keyword",b:/\w+/},{b:/\s/,eW:!0,eE:!0,r:0,c:[e.ASM,e.QSM,e.CSSNM]}]},{cN:"selector-tag",b:c,r:0},{b:"{",e:"}",i:/\S/,c:[e.CBCM,t]}]}});hljs.registerLanguage("fortran",function(e){var t={cN:"params",b:"\\(",e:"\\)"},n={literal:".False. .True.",keyword:"kind do while private call intrinsic where elsewhere type endtype endmodule endselect endinterface end enddo endif if forall endforall only contains default return stop then public subroutine|10 function program .and. .or. .not. .le. .eq. .ge. .gt. .lt. goto save else use module select case access blank direct exist file fmt form formatted iostat name named nextrec number opened rec recl sequential status unformatted unit continue format pause cycle exit c_null_char c_alert c_backspace c_form_feed flush wait decimal round iomsg synchronous nopass non_overridable pass protected volatile abstract extends import non_intrinsic value deferred generic final enumerator class associate bind enum c_int c_short c_long c_long_long c_signed_char c_size_t c_int8_t c_int16_t c_int32_t c_int64_t c_int_least8_t c_int_least16_t c_int_least32_t c_int_least64_t c_int_fast8_t c_int_fast16_t c_int_fast32_t c_int_fast64_t c_intmax_t C_intptr_t c_float c_double c_long_double c_float_complex c_double_complex c_long_double_complex c_bool c_char c_null_ptr c_null_funptr c_new_line c_carriage_return c_horizontal_tab c_vertical_tab iso_c_binding c_loc c_funloc c_associated c_f_pointer c_ptr c_funptr iso_fortran_env character_storage_size error_unit file_storage_size input_unit iostat_end iostat_eor numeric_storage_size output_unit c_f_procpointer ieee_arithmetic ieee_support_underflow_control ieee_get_underflow_mode ieee_set_underflow_mode newunit contiguous recursive pad position action delim readwrite eor advance nml interface procedure namelist include sequence elemental pure integer real character complex logical dimension allocatable|10 parameter external implicit|10 none double precision assign intent optional pointer target in out common equivalence data",built_in:"alog alog10 amax0 amax1 amin0 amin1 amod cabs ccos cexp clog csin csqrt dabs dacos dasin datan datan2 dcos dcosh ddim dexp dint dlog dlog10 dmax1 dmin1 dmod dnint dsign dsin dsinh dsqrt dtan dtanh float iabs idim idint idnint ifix isign max0 max1 min0 min1 sngl algama cdabs cdcos cdexp cdlog cdsin cdsqrt cqabs cqcos cqexp cqlog cqsin cqsqrt dcmplx dconjg derf derfc dfloat dgamma dimag dlgama iqint qabs qacos qasin qatan qatan2 qcmplx qconjg qcos qcosh qdim qerf qerfc qexp qgamma qimag qlgama qlog qlog10 qmax1 qmin1 qmod qnint qsign qsin qsinh qsqrt qtan qtanh abs acos aimag aint anint asin atan atan2 char cmplx conjg cos cosh exp ichar index int log log10 max min nint sign sin sinh sqrt tan tanh print write dim lge lgt lle llt mod nullify allocate deallocate adjustl adjustr all allocated any associated bit_size btest ceiling count cshift date_and_time digits dot_product eoshift epsilon exponent floor fraction huge iand ibclr ibits ibset ieor ior ishft ishftc lbound len_trim matmul maxexponent maxloc maxval merge minexponent minloc minval modulo mvbits nearest pack present product radix random_number random_seed range repeat reshape rrspacing scale scan selected_int_kind selected_real_kind set_exponent shape size spacing spread sum system_clock tiny transpose trim ubound unpack verify achar iachar transfer dble entry dprod cpu_time command_argument_count get_command get_command_argument get_environment_variable is_iostat_end ieee_arithmetic ieee_support_underflow_control ieee_get_underflow_mode ieee_set_underflow_mode is_iostat_eor move_alloc new_line selected_char_kind same_type_as extends_type_ofacosh asinh atanh bessel_j0 bessel_j1 bessel_jn bessel_y0 bessel_y1 bessel_yn erf erfc erfc_scaled gamma log_gamma hypot norm2 atomic_define atomic_ref execute_command_line leadz trailz storage_size merge_bits bge bgt ble blt dshiftl dshiftr findloc iall iany iparity image_index lcobound ucobound maskl maskr num_images parity popcnt poppar shifta shiftl shiftr this_image"};return{cI:!0,aliases:["f90","f95"],k:n,i:/\/\*/,c:[e.inherit(e.ASM,{cN:"string",r:0}),e.inherit(e.QSM,{cN:"string",r:0}),{cN:"function",bK:"subroutine function program",i:"[${=\\n]",c:[e.UTM,t]},e.C("!","$",{r:0}),{cN:"number",b:"(?=\\b|\\+|\\-|\\.)(?=\\.\\d|\\d)(?:\\d+)?(?:\\.?\\d*)(?:[de][+-]?\\d+)?\\b\\.?",r:0}]}});hljs.registerLanguage("awk",function(e){var r={cN:"variable",v:[{b:/\$[\w\d#@][\w\d_]*/},{b:/\$\{(.*?)}/}]},b="BEGIN END if else while do for in break continue delete next nextfile function func exit|10",n={cN:"string",c:[e.BE],v:[{b:/(u|b)?r?'''/,e:/'''/,r:10},{b:/(u|b)?r?"""/,e:/"""/,r:10},{b:/(u|r|ur)'/,e:/'/,r:10},{b:/(u|r|ur)"/,e:/"/,r:10},{b:/(b|br)'/,e:/'/},{b:/(b|br)"/,e:/"/},e.ASM,e.QSM]};return{k:{keyword:b},c:[r,n,e.RM,e.HCM,e.NM]}});hljs.registerLanguage("makefile",function(e){var i={cN:"variable",v:[{b:"\\$\\("+e.UIR+"\\)",c:[e.BE]},{b:/\$[@%<?\^\+\*]/}]},r={cN:"string",b:/"/,e:/"/,c:[e.BE,i]},a={cN:"variable",b:/\$\([\w-]+\s/,e:/\)/,k:{built_in:"subst patsubst strip findstring filter filter-out sort word wordlist firstword lastword dir notdir suffix basename addsuffix addprefix join wildcard realpath abspath error warning shell origin flavor foreach if or and call eval file value"},c:[i]},n={b:"^"+e.UIR+"\\s*[:+?]?=",i:"\\n",rB:!0,c:[{b:"^"+e.UIR,e:"[:+?]?=",eE:!0}]},t={cN:"meta",b:/^\.PHONY:/,e:/$/,k:{"meta-keyword":".PHONY"},l:/[\.\w]+/},l={cN:"section",b:/^[^\s]+:/,e:/$/,c:[i]};return{aliases:["mk","mak"],k:"define endef undefine ifdef ifndef ifeq ifneq else endif include -include sinclude override export unexport private vpath",l:/[\w-]+/,c:[e.HCM,i,r,a,n,t,l]}});hljs.registerLanguage("java",function(e){var a="[À-ʸa-zA-Z_$][À-ʸa-zA-Z_$0-9]*",t=a+"(<"+a+"(\\s*,\\s*"+a+")*>)?",r="false synchronized int abstract float private char boolean static null if const for true while long strictfp finally protected import native final void enum else break transient catch instanceof byte super volatile case assert short package default double public try this switch continue throws protected public private module requires exports do",s="\\b(0[bB]([01]+[01_]+[01]+|[01]+)|0[xX]([a-fA-F0-9]+[a-fA-F0-9_]+[a-fA-F0-9]+|[a-fA-F0-9]+)|(([\\d]+[\\d_]+[\\d]+|[\\d]+)(\\.([\\d]+[\\d_]+[\\d]+|[\\d]+))?|\\.([\\d]+[\\d_]+[\\d]+|[\\d]+))([eE][-+]?\\d+)?)[lLfF]?",c={cN:"number",b:s,r:0};return{aliases:["jsp"],k:r,i:/<\/|#/,c:[e.C("/\\*\\*","\\*/",{r:0,c:[{b:/\w+@/,r:0},{cN:"doctag",b:"@[A-Za-z]+"}]}),e.CLCM,e.CBCM,e.ASM,e.QSM,{cN:"class",bK:"class interface",e:/[{;=]/,eE:!0,k:"class interface",i:/[:"\[\]]/,c:[{bK:"extends implements"},e.UTM]},{bK:"new throw return else",r:0},{cN:"function",b:"("+t+"\\s+)+"+e.UIR+"\\s*\\(",rB:!0,e:/[{;=]/,eE:!0,k:r,c:[{b:e.UIR+"\\s*\\(",rB:!0,r:0,c:[e.UTM]},{cN:"params",b:/\(/,e:/\)/,k:r,r:0,c:[e.ASM,e.QSM,e.CNM,e.CBCM]},e.CLCM,e.CBCM]},c,{cN:"meta",b:"@[A-Za-z]+"}]}});hljs.registerLanguage("stan",function(e){return{c:[e.HCM,e.CLCM,e.CBCM,{b:e.UIR,l:e.UIR,k:{name:"for in while repeat until if then else",symbol:"bernoulli bernoulli_logit binomial binomial_logit beta_binomial hypergeometric categorical categorical_logit ordered_logistic neg_binomial neg_binomial_2 neg_binomial_2_log poisson poisson_log multinomial normal exp_mod_normal skew_normal student_t cauchy double_exponential logistic gumbel lognormal chi_square inv_chi_square scaled_inv_chi_square exponential inv_gamma weibull frechet rayleigh wiener pareto pareto_type_2 von_mises uniform multi_normal multi_normal_prec multi_normal_cholesky multi_gp multi_gp_cholesky multi_student_t gaussian_dlm_obs dirichlet lkj_corr lkj_corr_cholesky wishart inv_wishart","selector-tag":"int real vector simplex unit_vector ordered positive_ordered row_vector matrix cholesky_factor_corr cholesky_factor_cov corr_matrix cov_matrix",title:"functions model data parameters quantities transformed generated",literal:"true false"},r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"0[xX][0-9a-fA-F]+[Li]?\\b",r:0},{cN:"number",b:"\\d+(?:[eE][+\\-]?\\d*)?L\\b",r:0},{cN:"number",b:"\\d+\\.(?!\\d)(?:i\\b)?",r:0},{cN:"number",b:"\\d+(?:\\.\\d*)?(?:[eE][+\\-]?\\d*)?i?\\b",r:0},{cN:"number",b:"\\.\\d+(?:[eE][+\\-]?\\d*)?i?\\b",r:0}]}});hljs.registerLanguage("javascript",function(e){var r="[A-Za-z$_][0-9A-Za-z$_]*",t={keyword:"in of if for while finally var new function do return void else break catch instanceof with throw case default try this switch continue typeof delete let yield const export super debugger as async await static import from as",literal:"true false null undefined NaN Infinity",built_in:"eval isFinite isNaN parseFloat parseInt decodeURI decodeURIComponent encodeURI encodeURIComponent escape unescape Object Function Boolean Error EvalError InternalError RangeError ReferenceError StopIteration SyntaxError TypeError URIError Number Math Date String RegExp Array Float32Array Float64Array Int16Array Int32Array Int8Array Uint16Array Uint32Array Uint8Array Uint8ClampedArray ArrayBuffer DataView JSON Intl arguments require module console window document Symbol Set Map WeakSet WeakMap Proxy Reflect Promise"},a={cN:"number",v:[{b:"\\b(0[bB][01]+)"},{b:"\\b(0[oO][0-7]+)"},{b:e.CNR}],r:0},n={cN:"subst",b:"\\$\\{",e:"\\}",k:t,c:[]},c={cN:"string",b:"`",e:"`",c:[e.BE,n]};n.c=[e.ASM,e.QSM,c,a,e.RM];var s=n.c.concat([e.CBCM,e.CLCM]);return{aliases:["js","jsx"],k:t,c:[{cN:"meta",r:10,b:/^\s*['"]use (strict|asm)['"]/},{cN:"meta",b:/^#!/,e:/$/},e.ASM,e.QSM,c,e.CLCM,e.CBCM,a,{b:/[{,]\s*/,r:0,c:[{b:r+"\\s*:",rB:!0,r:0,c:[{cN:"attr",b:r,r:0}]}]},{b:"("+e.RSR+"|\\b(case|return|throw)\\b)\\s*",k:"return throw case",c:[e.CLCM,e.CBCM,e.RM,{cN:"function",b:"(\\(.*?\\)|"+r+")\\s*=>",rB:!0,e:"\\s*=>",c:[{cN:"params",v:[{b:r},{b:/\(\s*\)/},{b:/\(/,e:/\)/,eB:!0,eE:!0,k:t,c:s}]}]},{b:/</,e:/(\/\w+|\w+\/)>/,sL:"xml",c:[{b:/<\w+\s*\/>/,skip:!0},{b:/<\w+/,e:/(\/\w+|\w+\/)>/,skip:!0,c:[{b:/<\w+\s*\/>/,skip:!0},"self"]}]}],r:0},{cN:"function",bK:"function",e:/\{/,eE:!0,c:[e.inherit(e.TM,{b:r}),{cN:"params",b:/\(/,e:/\)/,eB:!0,eE:!0,c:s}],i:/\[|%/},{b:/\$[(.]/},e.METHOD_GUARD,{cN:"class",bK:"class",e:/[{;=]/,eE:!0,i:/[:"\[\]]/,c:[{bK:"extends"},e.UTM]},{bK:"constructor",e:/\{/,eE:!0}],i:/#(?!!)/}});hljs.registerLanguage("tex",function(c){var e={cN:"tag",b:/\\/,r:0,c:[{cN:"name",v:[{b:/[a-zA-Zа-яА-я]+[*]?/},{b:/[^a-zA-Zа-яА-я0-9]/}],starts:{eW:!0,r:0,c:[{cN:"string",v:[{b:/\[/,e:/\]/},{b:/\{/,e:/\}/}]},{b:/\s*=\s*/,eW:!0,r:0,c:[{cN:"number",b:/-?\d*\.?\d+(pt|pc|mm|cm|in|dd|cc|ex|em)?/}]}]}}]};return{c:[e,{cN:"formula",c:[e],r:0,v:[{b:/\$\$/,e:/\$\$/},{b:/\$/,e:/\$/}]},c.C("%","$",{r:0})]}});hljs.registerLanguage("xml",function(s){var e="[A-Za-z0-9\\._:-]+",t={eW:!0,i:/</,r:0,c:[{cN:"attr",b:e,r:0},{b:/=\s*/,r:0,c:[{cN:"string",endsParent:!0,v:[{b:/"/,e:/"/},{b:/'/,e:/'/},{b:/[^\s"'=<>`]+/}]}]}]};return{aliases:["html","xhtml","rss","atom","xjb","xsd","xsl","plist"],cI:!0,c:[{cN:"meta",b:"<!DOCTYPE",e:">",r:10,c:[{b:"\\[",e:"\\]"}]},s.C("<!--","-->",{r:10}),{b:"<\\!\\[CDATA\\[",e:"\\]\\]>",r:10},{b:/<\?(php)?/,e:/\?>/,sL:"php",c:[{b:"/\\*",e:"\\*/",skip:!0}]},{cN:"tag",b:"<style(?=\\s|>|$)",e:">",k:{name:"style"},c:[t],starts:{e:"</style>",rE:!0,sL:["css","xml"]}},{cN:"tag",b:"<script(?=\\s|>|$)",e:">",k:{name:"script"},c:[t],starts:{e:"</script>",rE:!0,sL:["actionscript","javascript","handlebars","xml"]}},{cN:"meta",v:[{b:/<\?xml/,e:/\?>/,r:10},{b:/<\?\w+/,e:/\?>/}]},{cN:"tag",b:"</?",e:"/?>",c:[{cN:"name",b:/[^\/><\s]+/,r:0},t]}]}});hljs.registerLanguage("markdown",function(e){return{aliases:["md","mkdown","mkd"],c:[{cN:"section",v:[{b:"^#{1,6}",e:"$"},{b:"^.+?\\n[=-]{2,}$"}]},{b:"<",e:">",sL:"xml",r:0},{cN:"bullet",b:"^([*+-]|(\\d+\\.))\\s+"},{cN:"strong",b:"[*_]{2}.+?[*_]{2}"},{cN:"emphasis",v:[{b:"\\*.+?\\*"},{b:"_.+?_",r:0}]},{cN:"quote",b:"^>\\s+",e:"$"},{cN:"code",v:[{b:"^```w*s*$",e:"^```s*$"},{b:"`.+?`"},{b:"^( {4}| )",e:"$",r:0}]},{b:"^[-\\*]{3,}",e:"$"},{b:"\\[.+?\\][\\(\\[].*?[\\)\\]]",rB:!0,c:[{cN:"string",b:"\\[",e:"\\]",eB:!0,rE:!0,r:0},{cN:"link",b:"\\]\\(",e:"\\)",eB:!0,eE:!0},{cN:"symbol",b:"\\]\\[",e:"\\]",eB:!0,eE:!0}],r:10},{b:/^\[[^\n]+\]:/,rB:!0,c:[{cN:"symbol",b:/\[/,e:/\]/,eB:!0,eE:!0},{cN:"link",b:/:\s*/,e:/$/,eB:!0}]}]}});hljs.registerLanguage("json",function(e){var i={literal:"true false null"},n=[e.QSM,e.CNM],r={e:",",eW:!0,eE:!0,c:n,k:i},t={b:"{",e:"}",c:[{cN:"attr",b:/"/,e:/"/,c:[e.BE],i:"\\n"},e.inherit(r,{b:/:/})],i:"\\S"},c={b:"\\[",e:"\\]",c:[e.inherit(r)],i:"\\S"};return n.splice(n.length,0,t,c),{c:n,k:i,i:"\\S"}});
\ No newline at end of file
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/textmate.css b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/textmate.css
new file mode 100644
index 0000000000000000000000000000000000000000..6efd4356067866530ca6c18f7578573820996919
--- /dev/null
+++ b/model_v2/SPRG_demand_v2.1_BA_files/highlightjs-9.12.0/textmate.css
@@ -0,0 +1,19 @@
+.hljs-literal {
+ color: rgb(88, 72, 246);
+}
+
+.hljs-number {
+ color: rgb(0, 0, 205);
+}
+
+.hljs-comment {
+ color: rgb(76, 136, 107);
+}
+
+.hljs-keyword {
+ color: rgb(0, 0, 255);
+}
+
+.hljs-string {
+ color: rgb(3, 106, 7);
+}
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/FileSaver.min.js b/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/FileSaver.min.js
deleted file mode 100644
index 6268ec99ddec211426a5806a08eeb49e977bfa1e..0000000000000000000000000000000000000000
--- a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/FileSaver.min.js
+++ /dev/null
@@ -1,2 +0,0 @@
-/*! @source http://purl.eligrey.com/github/FileSaver.js/blob/master/FileSaver.js */
-var saveAs=saveAs||function(e){"use strict";if("undefined"==typeof navigator||!/MSIE [1-9]\./.test(navigator.userAgent)){var t=e.document,n=function(){return e.URL||e.webkitURL||e},o=t.createElementNS("http://www.w3.org/1999/xhtml","a"),r="download"in o,i=function(e){var t=new MouseEvent("click");e.dispatchEvent(t)},a=/Version\/[\d\.]+.*Safari/.test(navigator.userAgent),c=e.webkitRequestFileSystem,f=e.requestFileSystem||c||e.mozRequestFileSystem,u=function(t){(e.setImmediate||e.setTimeout)(function(){throw t},0)},d="application/octet-stream",s=0,l=4e4,v=function(e){var t=function(){"string"==typeof e?n().revokeObjectURL(e):e.remove()};setTimeout(t,l)},p=function(e,t,n){t=[].concat(t);for(var o=t.length;o--;){var r=e["on"+t[o]];if("function"==typeof r)try{r.call(e,n||e)}catch(i){u(i)}}},w=function(e){return/^\s*(?:text\/\S*|application\/xml|\S*\/\S*\+xml)\s*;.*charset\s*=\s*utf-8/i.test(e.type)?new Blob(["\ufeff",e],{type:e.type}):e},y=function(t,u,l){l||(t=w(t));var y,m,S,h=this,R=t.type,O=!1,g=function(){p(h,"writestart progress write writeend".split(" "))},b=function(){if(m&&a&&"undefined"!=typeof FileReader){var o=new FileReader;return o.onloadend=function(){var e=o.result;m.location.href="data:attachment/file"+e.slice(e.search(/[,;]/)),h.readyState=h.DONE,g()},o.readAsDataURL(t),void(h.readyState=h.INIT)}if((O||!y)&&(y=n().createObjectURL(t)),m)m.location.href=y;else{var r=e.open(y,"_blank");void 0===r&&a&&(e.location.href=y)}h.readyState=h.DONE,g(),v(y)},E=function(e){return function(){return h.readyState!==h.DONE?e.apply(this,arguments):void 0}},N={create:!0,exclusive:!1};return h.readyState=h.INIT,u||(u="download"),r?(y=n().createObjectURL(t),void setTimeout(function(){o.href=y,o.download=u,i(o),g(),v(y),h.readyState=h.DONE})):(e.chrome&&R&&R!==d&&(S=t.slice||t.webkitSlice,t=S.call(t,0,t.size,d),O=!0),c&&"download"!==u&&(u+=".download"),(R===d||c)&&(m=e),f?(s+=t.size,void f(e.TEMPORARY,s,E(function(e){e.root.getDirectory("saved",N,E(function(e){var n=function(){e.getFile(u,N,E(function(e){e.createWriter(E(function(n){n.onwriteend=function(t){m.location.href=e.toURL(),h.readyState=h.DONE,p(h,"writeend",t),v(e)},n.onerror=function(){var e=n.error;e.code!==e.ABORT_ERR&&b()},"writestart progress write abort".split(" ").forEach(function(e){n["on"+e]=h["on"+e]}),n.write(t),h.abort=function(){n.abort(),h.readyState=h.DONE},h.readyState=h.WRITING}),b)}),b)};e.getFile(u,{create:!1},E(function(e){e.remove(),n()}),E(function(e){e.code===e.NOT_FOUND_ERR?n():b()}))}),b)}),b)):void b())},m=y.prototype,S=function(e,t,n){return new y(e,t,n)};return"undefined"!=typeof navigator&&navigator.msSaveOrOpenBlob?function(e,t,n){return n||(e=w(e)),navigator.msSaveOrOpenBlob(e,t||"download")}:(m.abort=function(){var e=this;e.readyState=e.DONE,p(e,"abort")},m.readyState=m.INIT=0,m.WRITING=1,m.DONE=2,m.error=m.onwritestart=m.onprogress=m.onwrite=m.onabort=m.onerror=m.onwriteend=null,S)}}("undefined"!=typeof self&&self||"undefined"!=typeof window&&window||this.content);"undefined"!=typeof module&&module.exports?module.exports.saveAs=saveAs:"undefined"!=typeof define&&null!==define&&null!==define.amd&&define([],function(){return saveAs});
\ No newline at end of file
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/codefolding.js b/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/codefolding.js
index 4938425052e4bbeb1053dc61634d695f2223b13f..1e16fde9f89a24f29b12b71d800bc9cc3b17ce70 100644
--- a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/codefolding.js
+++ b/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/codefolding.js
@@ -17,26 +17,26 @@ window.initializeCodeFolding = function(show) {
var currentIndex = 1;
// select all R code blocks
- var rCodeBlocks = $('pre.r');
+ var rCodeBlocks = $('pre.r, pre.python, pre.bash, pre.sql, pre.cpp, pre.stan, pre.julia, pre.foldable');
rCodeBlocks.each(function() {
// create a collapsable div to wrap the code in
var div = $('<div class="collapse r-code-collapse"></div>');
- if (show)
- div.addClass('in');
+ var showThis = (show || $(this).hasClass('fold-show')) && !$(this).hasClass('fold-hide');
+ if (showThis) div.addClass('in');
var id = 'rcode-643E0F36' + currentIndex++;
div.attr('id', id);
$(this).before(div);
$(this).detach().appendTo(div);
// add a show code button right above
- var showCodeText = $('<span>' + (show ? 'Hide' : 'Code') + '</span>');
+ var showCodeText = $('<span>' + (showThis ? 'Hide' : 'Code') + '</span>');
var showCodeButton = $('<button type="button" class="btn btn-default btn-xs code-folding-btn pull-right"></button>');
showCodeButton.append(showCodeText);
showCodeButton
.attr('data-toggle', 'collapse')
.attr('data-target', '#' + id)
- .attr('aria-expanded', show)
+ .attr('aria-expanded', showThis)
.attr('aria-controls', id);
var buttonRow = $('<div class="row"></div>');
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/sourceembed.js b/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/sourceembed.js
index e1b2cf852fdc769b178b192f8dd543da5ce3232b..8464b0c88eb5c7f08f2fb1041eef0fa939f3c573 100644
--- a/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/sourceembed.js
+++ b/model_v2/SPRG_demand_v2.1_BA_files/navigation-1.1/sourceembed.js
@@ -1,9 +1,12 @@
-
window.initializeSourceEmbed = function(filename) {
$("#rmd-download-source").click(function() {
- var src = window.atob($("#rmd-source-code").html());
- var blob = new Blob([src], {type: "text/x-r-markdown"});
- saveAs(blob, filename);
+ var src = $("#rmd-source-code").html();
+ var a = document.createElement('a');
+ a.href = "data:text/x-r-markdown;base64," + src;
+ a.download = filename;
+ document.body.appendChild(a);
+ a.click();
+ document.body.removeChild(a);
});
};
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.css b/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.css
index bee8f33a05be008c881735c1f45eb18dbb5b78a9..2102138854d9a3064656711a637edec1a2f8f712 100644
--- a/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.css
+++ b/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.css
@@ -11,8 +11,6 @@
margin-left: 2%;
position: fixed;
border: 1px solid #ccc;
- webkit-border-radius: 6px;
- moz-border-radius: 6px;
border-radius: 6px;
}
@@ -45,11 +43,15 @@
.tocify-subheader .tocify-subheader {
text-indent: 30px;
}
-
-/* Further indents third level subheader elements. You can continue this pattern if you have more nested elements. */
.tocify-subheader .tocify-subheader .tocify-subheader {
text-indent: 40px;
}
+.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
+ text-indent: 50px;
+}
+.tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader .tocify-subheader {
+ text-indent: 60px;
+}
/* Twitter Bootstrap Override Style */
.tocify .tocify-item > a, .tocify .nav-list .nav-header {
diff --git a/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.js b/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.js
index 259d19357ec741e9d57aa6aee8a74e153b601ef1..ba24a7dd8465969a7e633aa88b63c835c73377d2 100644
--- a/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.js
+++ b/model_v2/SPRG_demand_v2.1_BA_files/tocify-1.9.1/jquery.tocify.js
@@ -386,13 +386,13 @@
item.append($("<a/>", {
- "text": self.text()
+ "html": self.html()
}));
} else {
- item.text(self.text());
+ item.html(self.html());
}