From 994edaac6cc8382e69630b888d146af2cdab1ed6 Mon Sep 17 00:00:00 2001
From: Elijah Andrews <eda1g15@soton.ac.uk>
Date: Thu, 12 Mar 2020 16:54:34 +0000
Subject: [PATCH] Separated collapse plot modelling and plotting functionality.
---
numerical/models/slot_h_collapse.py | 84 ++----------------
..._q_collapse.py => slot_h_collapse_plot.py} | 59 +++++--------
numerical/models/slot_y_collapse.py | 43 +++++++++
numerical/models/slot_y_collapse_plot.py | 87 +++++++++++++++++++
4 files changed, 160 insertions(+), 113 deletions(-)
rename numerical/models/{slot_q_collapse.py => slot_h_collapse_plot.py} (53%)
create mode 100644 numerical/models/slot_y_collapse.py
create mode 100644 numerical/models/slot_y_collapse_plot.py
diff --git a/numerical/models/slot_h_collapse.py b/numerical/models/slot_h_collapse.py
index b380e7e..dd26957 100644
--- a/numerical/models/slot_h_collapse.py
+++ b/numerical/models/slot_h_collapse.py
@@ -1,20 +1,13 @@
import os
-import matplotlib.pyplot as plt
-import math
import numpy as np
import numerical.bem as bem
import numerical.util.gen_utils as gen
-import common.util.plotting_utils as pu
-import matplotlib.patches as patches
+from common.util.file_utils import lists_to_csv
+from common.util.plotting_utils import initialize_plt
-plt.rc('text', usetex=True)
-font = {'family': 'serif', 'size': 10, 'serif': ['cmr10']}
-plt.rc('font', **font)
-plt.rc('lines', linewidth=1, markersize=3)
-plt.rc('axes', linewidth=0.5)
-plt.rc('patch', linewidth=0.5)
+initialize_plt()
Hs = np.linspace(1, 5, 5)
W = 2
@@ -24,22 +17,8 @@ Y = 2
normalize = True
m_0 = 1
-n = 20000
+n = 2000
-fig_width = 5.31445
-fig = plt.figure(figsize=(fig_width, fig_width / 2))
-
-left_pos = 0.11
-right_pos = 0.98
-wspace = 0.3
-plt.subplots_adjust(top=0.95, bottom=0.3, left=left_pos, right=right_pos, wspace=wspace)
-fig.patch.set_facecolor('white')
-ax = fig.add_subplot(121)
-ax.locator_params(nbins=6)
-norm_ax = fig.add_subplot(122)
-norm_ax.locator_params(nbins=6)
-norm_ax.set_xlim(-5.5, 5.5)
-norm_ax.set_ylim(-1.1, 1.1)
xs = Xs / (0.5 * W)
for i, H in enumerate(Hs):
@@ -55,54 +34,9 @@ for i, H in enumerate(Hs):
points[:, 1] = Y
points[:, 2] = 0
vels = bem.get_jet_dirs(points, centroids, normals, areas, m_0, R_inv, verbose=True)
- theta_js = np.arctan2(vels[:, 1], vels[:, 0]) + 0.5 * np.pi
-
- x_to_plot = xs
- theta_j_to_plot = theta_js
-
- theta_j_star, x_star = sorted(zip(theta_js, xs), key=lambda k: k[0])[-1]
- norm_x_to_plot = np.divide(xs, x_star)
- norm_theta_j_to_plot = np.divide(theta_js, theta_j_star)
-
- label_frac = "h"
- if i == 0:
- ax.plot(x_to_plot, theta_j_to_plot, label=f"${label_frac} = {H / W:.2f}$")
- norm_ax.plot(norm_x_to_plot, norm_theta_j_to_plot, label=f"${label_frac} = {H / W:.2f}$")
- else:
- ax.plot(x_to_plot, theta_j_to_plot, label=f"${label_frac} = {H / W:.2f}$", linestyle="--",
- dashes=(i, 2 * i))
- norm_ax.plot(norm_x_to_plot, norm_theta_j_to_plot, label=f"${label_frac} = {H / W:.2f}$", linestyle="--",
- dashes=(i, 2 * i))
-
-# TODO: Convert to data generator + data plotter
-
-label_pad = 0
-norm_ax.set_xlabel("$\\hat{x}$", labelpad=label_pad)
-norm_ax.set_ylabel("$\\hat{\\theta}$", labelpad=label_pad)
-ax.set_xlabel("$x$", labelpad=label_pad)
-ax.set_ylabel("$\\theta_j$", labelpad=label_pad)
-ax.axvline(x=-1, linestyle='--', color='gray')
-ax.axvline(x=1, linestyle='--', color='gray')
-# ax.legend()
-
-ax.legend(bbox_to_anchor=(0, -0.34, 2.3, .05), loc=10, ncol=len(Hs), mode="expand",
- borderaxespad=0,
- fancybox=False, edgecolor='k', shadow=False, handlelength=1.5, handletextpad=0.5)
-ax.annotate('($a$)', xy=(0, 0), xytext=(0.115, 0.89), textcoords='figure fraction', horizontalalignment='left',
- verticalalignment='bottom')
-norm_ax.annotate('($b$)', xy=(0, 0), xytext=(0.61, 0.89), textcoords='figure fraction',
- horizontalalignment='left', verticalalignment='bottom')
-# ymin, ymax = ax.get_ylim()
-# ax.set_yticks(np.round(np.linspace(ymin, ymax, 5), 2))
-#
-# xmin, xmax = ax.get_xlim()
-# ax.set_xticks(np.round(np.linspace(xmin, xmax, 5), 2))
-#
-# ymin, ymax = norm_ax.get_ylim()
-# norm_ax.set_yticks(np.round(np.linspace(ymin, ymax, 5), 2))
-#
-# xmin, xmax = norm_ax.get_xlim()
-# norm_ax.set_xticks(np.round(np.linspace(xmin, xmax, 5), 2))
+ thetas = np.arctan2(vels[:, 1], vels[:, 0]) + 0.5 * np.pi
-plt.savefig('model_outputs/h_sweep_plot.pdf')
-plt.show()
+ f_dir = "model_outputs/slot_h_collapse/"
+ f_name = f"h_collapse_n{n}_H{H}.csv"
+ if not os.path.exists(f_dir + f_name):
+ lists_to_csv(f_dir, f_name, [xs, thetas], ["x", "theta"])
diff --git a/numerical/models/slot_q_collapse.py b/numerical/models/slot_h_collapse_plot.py
similarity index 53%
rename from numerical/models/slot_q_collapse.py
rename to numerical/models/slot_h_collapse_plot.py
index e2f52e1..4ece908 100644
--- a/numerical/models/slot_q_collapse.py
+++ b/numerical/models/slot_h_collapse_plot.py
@@ -6,25 +6,21 @@ import numpy as np
import numerical.bem as bem
import numerical.util.gen_utils as gen
-import common.util.plotting_utils as pu
+from common.util.plotting_utils import initialize_plt
+from common.util.file_utils import csv_to_lists
import matplotlib.patches as patches
-plt.rc('text', usetex=True)
-font = {'family': 'serif', 'size': 10, 'serif': ['cmr10']}
-plt.rc('font', **font)
-plt.rc('lines', linewidth=1, markersize=3)
-plt.rc('axes', linewidth=0.5)
-plt.rc('patch', linewidth=0.5)
+initialize_plt()
-H = 2
+Hs = np.linspace(1, 5, 5)
W = 2
Xs = np.linspace(-3 * W, 3 * W, 300)
-Ys = np.linspace(1, 5, 5)
+Y = 2
normalize = True
m_0 = 1
-n = 20000
+n = 2000
fig_width = 5.31445
fig = plt.figure(figsize=(fig_width, fig_width / 2))
@@ -42,49 +38,36 @@ norm_ax.set_xlim(-5.5, 5.5)
norm_ax.set_ylim(-1.1, 1.1)
xs = Xs / (0.5 * W)
-centroids, normals, areas = gen.gen_varied_slot(n=n, H=H, W=W, length=50, depth=50, w_thresh=12, density_ratio=0.25)
-print("Requested n = {0}, using n = {1}.".format(n, len(centroids)))
-print(np.mean(centroids, 0))
-R_matrix = bem.get_R_matrix(centroids, normals, areas, dtype=np.float32)
-R_inv = np.linalg.inv(R_matrix)
-for i, Y in enumerate(Ys):
- print(f"Testing Y = {Y}")
- points = np.empty((len(Xs), 3))
- points[:, 0] = Xs
- points[:, 1] = Y
- points[:, 2] = 0
- vels = bem.get_jet_dirs(points, centroids, normals, areas, m_0, R_inv, verbose=True)
- theta_js = np.arctan2(vels[:, 1], vels[:, 0]) + 0.5 * np.pi
+for i, H in enumerate(Hs):
+ print(f"Reading H = {H}")
+ f_dir = "model_outputs/slot_h_collapse/"
+ f_name = f"h_collapse_n{n}_H{H}.csv"
+ xs, thetas = csv_to_lists(f_dir, f_name, True)
- x_to_plot = xs
- theta_j_to_plot = theta_js
-
- theta_j_star, x_star = sorted(zip(theta_js, xs), key=lambda k: k[0])[-1]
+ theta_star, x_star = sorted(zip(thetas, xs), key=lambda k: k[0])[-1]
norm_x_to_plot = np.divide(xs, x_star)
- norm_theta_j_to_plot = np.divide(theta_js, theta_j_star)
+ norm_theta_to_plot = np.divide(thetas, theta_star)
- label_frac = "y"
+ label_frac = "h"
if i == 0:
- ax.plot(x_to_plot, theta_j_to_plot, label=f"${label_frac} = {Y / W:.2f}$")
- norm_ax.plot(norm_x_to_plot, norm_theta_j_to_plot, label=f"${label_frac} = {Y / W:.2f}$")
+ ax.plot(xs, thetas, label=f"${label_frac} = {H / W:.2f}$")
+ norm_ax.plot(norm_x_to_plot, norm_theta_to_plot, label=f"${label_frac} = {H / W:.2f}$")
else:
- ax.plot(x_to_plot, theta_j_to_plot, label=f"${label_frac} = {Y / W:.2f}$", linestyle="--",
+ ax.plot(xs, thetas, label=f"${label_frac} = {H / W:.2f}$", linestyle="--",
dashes=(i, 2 * i))
- norm_ax.plot(norm_x_to_plot, norm_theta_j_to_plot, label=f"${label_frac} = {Y / W:.2f}$", linestyle="--",
+ norm_ax.plot(norm_x_to_plot, norm_theta_to_plot, label=f"${label_frac} = {H / W:.2f}$", linestyle="--",
dashes=(i, 2 * i))
-# TODO: Convert to data generator + data plotter
-
label_pad = 0
norm_ax.set_xlabel("$\\hat{x}$", labelpad=label_pad)
norm_ax.set_ylabel("$\\hat{\\theta}$", labelpad=label_pad)
ax.set_xlabel("$x$", labelpad=label_pad)
-ax.set_ylabel("$\\theta_j$", labelpad=label_pad)
+ax.set_ylabel("$\\theta$ (rad)", labelpad=label_pad)
ax.axvline(x=-1, linestyle='--', color='gray')
ax.axvline(x=1, linestyle='--', color='gray')
# ax.legend()
-ax.legend(bbox_to_anchor=(0, -0.34, 2.3, .05), loc=10, ncol=len(Ys), mode="expand",
+ax.legend(bbox_to_anchor=(0, -0.34, 2.3, .05), loc=10, ncol=len(Hs), mode="expand",
borderaxespad=0,
fancybox=False, edgecolor='k', shadow=False, handlelength=1.5, handletextpad=0.5)
ax.annotate('($a$)', xy=(0, 0), xytext=(0.115, 0.89), textcoords='figure fraction', horizontalalignment='left',
@@ -103,5 +86,5 @@ norm_ax.annotate('($b$)', xy=(0, 0), xytext=(0.61, 0.89), textcoords='figure fra
# xmin, xmax = norm_ax.get_xlim()
# norm_ax.set_xticks(np.round(np.linspace(xmin, xmax, 5), 2))
-plt.savefig('model_outputs/q_sweep_plot.pdf')
+plt.savefig('model_outputs/h_sweep_plot.pdf')
plt.show()
diff --git a/numerical/models/slot_y_collapse.py b/numerical/models/slot_y_collapse.py
new file mode 100644
index 0000000..a5ca4fd
--- /dev/null
+++ b/numerical/models/slot_y_collapse.py
@@ -0,0 +1,43 @@
+import os
+
+import numpy as np
+
+import numerical.bem as bem
+import numerical.util.gen_utils as gen
+from common.util.file_utils import lists_to_csv
+
+H = 2
+W = 2
+Xs = np.linspace(-3 * W, 3 * W, 300)
+Ys = np.linspace(1, 5, 5)
+
+m_0 = 1
+n = 20000
+
+xs = Xs / (0.5 * W)
+
+centroids, normals, areas = gen.gen_varied_slot(n=n, H=H, W=W, length=50, depth=50, w_thresh=12, density_ratio=0.25)
+print("Requested n = {0}, using n = {1}.".format(n, len(centroids)))
+print(np.mean(centroids, 0))
+R_matrix = bem.get_R_matrix(centroids, normals, areas, dtype=np.float32)
+R_inv = np.linalg.inv(R_matrix)
+for i, Y in enumerate(Ys):
+ print(f"Testing Y = {Y}")
+ points = np.empty((len(Xs), 3))
+ points[:, 0] = Xs
+ points[:, 1] = Y
+ points[:, 2] = 0
+ vels = bem.get_jet_dirs(points, centroids, normals, areas, m_0, R_inv, verbose=True)
+ thetas = np.arctan2(vels[:, 1], vels[:, 0]) + 0.5 * np.pi
+
+ x_to_plot = xs
+ theta_to_plot = thetas
+
+ theta_star, x_star = sorted(zip(thetas, xs), key=lambda k: k[0])[-1]
+ norm_x_to_plot = np.divide(xs, x_star)
+ norm_theta_to_plot = np.divide(thetas, theta_star)
+
+ f_dir = "model_outputs/slot_y_collapse/"
+ f_name = f"y_collapse_n{n}_Y{Y}.csv"
+ if not os.path.exists(f_dir + f_name):
+ lists_to_csv(f_dir, f_name, [xs, thetas], ["x", "theta"])
diff --git a/numerical/models/slot_y_collapse_plot.py b/numerical/models/slot_y_collapse_plot.py
new file mode 100644
index 0000000..b8a5100
--- /dev/null
+++ b/numerical/models/slot_y_collapse_plot.py
@@ -0,0 +1,87 @@
+import os
+
+import matplotlib.pyplot as plt
+import math
+import numpy as np
+
+import numerical.bem as bem
+import numerical.util.gen_utils as gen
+from common.util.plotting_utils import initialize_plt
+from common.util.file_utils import csv_to_lists
+import matplotlib.patches as patches
+
+initialize_plt()
+
+H = 2
+W = 2
+Xs = np.linspace(-3 * W, 3 * W, 300)
+Ys = np.linspace(1, 5, 5)
+
+m_0 = 1
+n = 2000
+
+fig_width = 5.31445
+fig = plt.figure(figsize=(fig_width, fig_width / 2))
+
+left_pos = 0.11
+right_pos = 0.98
+wspace = 0.3
+plt.subplots_adjust(top=0.95, bottom=0.3, left=left_pos, right=right_pos, wspace=wspace)
+fig.patch.set_facecolor('white')
+ax = fig.add_subplot(121)
+ax.locator_params(nbins=6)
+norm_ax = fig.add_subplot(122)
+norm_ax.locator_params(nbins=6)
+norm_ax.set_xlim(-5.5, 5.5)
+norm_ax.set_ylim(-1.1, 1.1)
+xs = Xs / (0.5 * W)
+
+for i, Y in enumerate(Ys):
+ print(f"Reading Y = {Y}")
+ f_dir = "model_outputs/slot_y_collapse/"
+ f_name = f"y_collapse_n{n}_Y{Y}.csv"
+ xs, thetas = csv_to_lists(f_dir, f_name, True)
+
+ theta_star, x_star = sorted(zip(thetas, xs), key=lambda k: k[0])[-1]
+ norm_x_to_plot = np.divide(xs, x_star)
+ norm_theta_to_plot = np.divide(thetas, theta_star)
+
+ label_frac = "y"
+ if i == 0:
+ ax.plot(xs, thetas, label=f"${label_frac} = {Y / W:.2f}$")
+ norm_ax.plot(norm_x_to_plot, norm_theta_to_plot, label=f"${label_frac} = {Y / W:.2f}$")
+ else:
+ ax.plot(xs, thetas, label=f"${label_frac} = {Y / W:.2f}$", linestyle="--",
+ dashes=(i, 2 * i))
+ norm_ax.plot(norm_x_to_plot, norm_theta_to_plot, label=f"${label_frac} = {Y / W:.2f}$", linestyle="--",
+ dashes=(i, 2 * i))
+
+label_pad = 0
+norm_ax.set_xlabel("$\\hat{x}$", labelpad=label_pad)
+norm_ax.set_ylabel("$\\hat{\\theta}$", labelpad=label_pad)
+ax.set_xlabel("$x$", labelpad=label_pad)
+ax.set_ylabel("$\\theta$ (rad)", labelpad=label_pad)
+ax.axvline(x=-1, linestyle='--', color='gray')
+ax.axvline(x=1, linestyle='--', color='gray')
+# ax.legend()
+
+ax.legend(bbox_to_anchor=(0, -0.34, 2.3, .05), loc=10, ncol=len(Ys), mode="expand",
+ borderaxespad=0,
+ fancybox=False, edgecolor='k', shadow=False, handlelength=1.5, handletextpad=0.5)
+ax.annotate('($a$)', xy=(0, 0), xytext=(0.05, 0.95), textcoords='axes fraction', horizontalalignment='left',
+ verticalalignment='top')
+norm_ax.annotate('($b$)', xy=(0, 0), xytext=(0.05, 0.95), textcoords='axes fraction',
+ horizontalalignment='left', verticalalignment='top')
+# ymin, ymax = ax.get_ylim()
+# ax.set_yticks(np.round(np.linspace(ymin, ymax, 5), 2))
+#
+# xmin, xmax = ax.get_xlim()
+# ax.set_xticks(np.round(np.linspace(xmin, xmax, 5), 2))
+#
+# ymin, ymax = norm_ax.get_ylim()
+# norm_ax.set_yticks(np.round(np.linspace(ymin, ymax, 5), 2))
+#
+# xmin, xmax = norm_ax.get_xlim()
+# norm_ax.set_xticks(np.round(np.linspace(xmin, xmax, 5), 2))
+
+plt.show()
--
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