code to plot movies from the data, find perimeter and long axis

convergence_extension/perimeter_long_axis.py

+import numpy as np
+import matplotlib.pyplot as plt
+import pandas as pd
+from matplotlib.widgets import Slider
+
+def perimeter(X, Y, n):
+    # Initialize perimeter
+    perimeter = 0
+
+    # Calculate distance between each pair of consecutive points
+    for j in range(n):
+
+        # Get current point
+        x1, y1 = X[j], Y[j]
+
+        # Get next point (if i is the last index, get the first point)
+        if j == n-1:
+            x2, y2 = X[0], Y[0]
+        else:
+            x2, y2 = X[j+1], Y[j+1]
+        
+        # Calculate distance between points and add to perimeter
+        perimeter += np.sqrt((x2-x1)**2 + (y2-y1)**2)
+
+    return perimeter
+
+def long_axis(x, y):
+    x_diff = x[:, None] - x
+    y_diff = y[:, None] - y
+    distances = np.sqrt(x_diff**2 + y_diff**2)
+    return np.max(distances)
+
+# NOTE: check perimeter and long_axis functions on known shapes
+# x = np.array([0, 1, 0, -1])
+# y = np.array([2, 0, -2, 0])
+# print(x, y)
+# print(long_axis(x, y))   
+# raise SystemExit
+
+file = np.loadtxt('xy_coordinates_movie1.txt')
+number_of_pixels = file.shape[0]
+time_points = file.shape[1]
+time_array = np.arange(0, 5*int(time_points/2), 5)
+
+# x, y coordinates from data
+x, y = np.zeros((number_of_pixels, int(time_points/2))), np.zeros((number_of_pixels, int(time_points/2)))
+
+for i in range(0, int(time_points/2)):
+    x[:, i] = file[:, 2*i]
+    y[:, i] = file[:, 2*i+1]
+
+# Interpolate a value to replace NaN based on its neighbors
+x = pd.DataFrame(x)
+x = np.array(x.interpolate(method='linear', axis=0, limit_direction='both'))
+y= pd.DataFrame(y)
+y = np.array(y.interpolate(method='linear', axis=0, limit_direction='both'))
+
+# x, y = (time x pixels)
+x = x.T
+y = y.T
+
+# make movie of the contours
+fig, ax = plt.subplots(1, 1, sharex=True, figsize=(8,8))
+ax.set_xlabel(r'$x$')
+ax.set_xlim(np.min(x), np.max(x))
+ax.set_ylim(np.min(y), np.max(y))
+ax.set_ylabel(r'$y$')
+
+outlineplot, = ax.plot(x[0], y[0], marker = 'o', ms=3, linestyle='None')
+    
+def update(value):
+    ti = np.abs(time_array - value).argmin()
+    outlineplot.set_ydata(y[ti])
+    outlineplot.set_xdata(x[ti])
+    plt.draw()
+        
+sax = plt.axes([0.1, 0.92, 0.7, 0.02])
+slider = Slider(sax, r'$t/\tau$', min(time_array), max(time_array),
+            valinit=min(time_array), valfmt='%3.1f',
+            fc='#999999')
+slider.drawon = False
+slider.on_changed(update)
+plt.show()
+
+# find the long axis
+long_axis_array = np.zeros(int(time_points/2))
+for k in range(0, int(time_points/2)):
+    long_axis_array[k] = long_axis(x[k], y[k])
+plt.plot(time_array, long_axis_array, marker='o', linestyle='None')
+plt.xlabel('Time')
+plt.ylabel('Length of the long axis')
+plt.show()
+
+# find the perimeter
+perimeter_array = np.zeros(int(time_points/2))
+
+for k in range(0,  int(time_points/2)):
+    perimeter_array[k] = perimeter(x[k], y[k], number_of_pixels)   
+
+plt.plot(time_array, perimeter_array, marker='o', linestyle='None')     
+plt.xlabel('Time')
+plt.ylabel('Perimeter')
+plt.show()
+