Added standoff vs displacement plotting for initial porous plates data.

experimental/plotting/standoff_vs_displacement_plates.py

+import os
+import sys
+import importlib
+import experimental.util.analysis_utils as au
+from common.util.plotting_utils import initialize_plt
+import numpy as np
+import matplotlib.pyplot as plt
+
+dirs = []
+root_dir = "../../../../../Porous Materials/Data/"
+for root, _, files in os.walk(root_dir):
+    if "params.py" in files:
+        dirs.append(root + "/")
+print(f"Found {len(dirs)} data sets")
+
+radii = []
+displacements = []
+avg_vels = []
+ps = []
+qs = []
+theta_js = []
+sup_disps = []
+times = []
+idxs = []
+
+initialize_plt(font_size=14, line_scale=2)
+plt.figure()
+
+for i, dir_path in enumerate(dirs):
+    sys.path.append(dir_path)
+    import params
+
+    importlib.reload(params)
+    sys.path.remove(dir_path)
+
+    y_offset = params.upper_surface_y
+
+    readings = au.load_readings(dir_path + "readings_dump.csv")
+
+    zetas = []
+    norm_disps = []
+    standoffs = []
+    for j, reading in enumerate(readings):
+        pos = reading.get_bubble_pos_mm(params.mm_per_px)
+        # p = pos[0]
+        q = pos[1] - y_offset
+
+        if q >= 0:
+            # ps.append(p)
+            # qs.append(q)
+            radius = np.sqrt(reading.max_bubble_area / np.pi) * params.mm_per_px
+            radii.append(radius)
+            displacement = np.linalg.norm(reading.disp_vect) * params.mm_per_px
+            displacements.append(displacement)
+            # avg_vels.append((displacement / 1000) * 1e5 / reading.inter_max_frames)  # m/s
+            # theta_js.append(reading.get_jet_angle())
+            standoff = q / radius
+            if standoff ** (-2) < 0.012:
+                print(reading.idx, reading.repeat_number)
+            standoffs.append(standoff ** (-2))
+            norm_disps.append(displacement / radius)
+            # sup_disps.append(np.linalg.norm(reading.sup_disp_vect) * params.mm_per_px)
+            # times.append(reading.inter_max_frames)
+            # idxs.append(j)
+
+    plt.scatter(standoffs, norm_disps, label=dir_path.split("/")[-2])
+
+
+# filt_zetas, filt_disps, filt_radii = \
+#     zip(*[(z, d, r) for z, d, r, p in zip(zetas, displacements, radii, ps) if np.abs(p) > 4])
+# fit_params = np.polyfit(np.log(filt_zetas), np.log(np.divide(filt_disps, filt_radii)), 1)
+# fit_zetas = np.linspace(min(filt_zetas), max(filt_zetas), 100)
+# fit_disps = np.exp(fit_params[1]) * np.power(fit_zetas, fit_params[0])
+# fit_label = "$%.3f \\zeta^{%.3f}$ (fitted)" % (np.exp(fit_params[1]), fit_params[0])
+# print(len(filt_zetas))
+# plt.plot(fit_zetas, fit_disps, label=fit_label, color="C1")
+
+plt.xlabel("$\\gamma^{-2}$")
+plt.ylabel("$\Delta / R$ = displacement / radius")
+plt.xscale('log')
+plt.yscale('log')
+plt.legend(frameon=False)
+plt.tight_layout()
+plt.show()