added code to find area enclosed by the contour

convergence_extension/perimeter_long_axis.py

@@ -4,15 +4,15 @@ import pandas as pd
 from matplotlib.widgets import Slider
 from matplotlib.widgets import Slider
 from scipy.spatial import ConvexHull
 from scipy.spatial import ConvexHull
 
 
-def perimeter(X, Y):
+def perimeter_area(X, Y):
     points = np.column_stack((X, Y))
     points = np.column_stack((X, Y))
     hull = ConvexHull(points)
     hull = ConvexHull(points)
     N = len(hull.vertices)
     N = len(hull.vertices)
-    value = 0
+    perimeter_value = 0
     for i in range(N):
     for i in range(N):
-        value += np.linalg.norm(points[hull.vertices[i]] - points[hull.vertices[(i+1)%N]]) 
+        perimeter_value += np.linalg.norm(points[hull.vertices[i]] - points[hull.vertices[(i+1)%N]]) 
         # The (i+1)%N part ensures that after the last vertex, we go back to the first vertex, creating a closed loop
         # The (i+1)%N part ensures that after the last vertex, we go back to the first vertex, creating a closed loop
-    return value
+    return (perimeter_value, hull.volume)
 
 
 def long_axis(x, y):
 def long_axis(x, y):
     x_diff = x[:, None] - x
     x_diff = x[:, None] - x
@@ -21,16 +21,16 @@ def long_axis(x, y):
     return np.max(distances)
     return np.max(distances)
 
 
 # NOTE: check perimeter and long_axis functions on known shapes
 # NOTE: check perimeter and long_axis functions on known shapes
-# x = np.array([1, 0, -1, 0])
-# y = np.array([0, 2, 0, -2])
-# print(long_axis(x, y))
+# x = np.array([1, -1, -1, 1])
+# y = np.array([1, 1, -1, -1])
 
 
 # points = np.column_stack((x, y))
 # points = np.column_stack((x, y))
 # hull = ConvexHull(points)
 # hull = ConvexHull(points)
+# print(perimeter_area(x, y))
 # print(long_axis(x, y))
 # print(long_axis(x, y))
 # raise SystemExit
 # raise SystemExit
 
 
-file = np.loadtxt('xy_coordinates_movie15.txt')
+file = np.loadtxt('xy_coordinates_movie1.txt')
 number_of_pixels = file.shape[0]
 number_of_pixels = file.shape[0]
 time_points = file.shape[1]
 time_points = file.shape[1]
 time_array = np.arange(0, 5*int(time_points/2), 5)
 time_array = np.arange(0, 5*int(time_points/2), 5)
@@ -84,14 +84,19 @@ plt.xlabel('Time')
 plt.ylabel('Length of the long axis')
 plt.ylabel('Length of the long axis')
 plt.show()
 plt.show()
 
 
-# find the perimeter
+# find the perimeter and area
 perimeter_array = np.zeros(int(time_points/2))
 perimeter_array = np.zeros(int(time_points/2))
+area_array = np.zeros(int(time_points/2))
 
 
 for k in range(0,  int(time_points/2)):
 for k in range(0,  int(time_points/2)):
-    perimeter_array[k] = perimeter(x[k], y[k])   
+    perimeter_array[k], area_array[k] = perimeter_area(x[k], y[k])   
 
 
 plt.plot(time_array, perimeter_array, marker='o', linestyle='None')     
 plt.plot(time_array, perimeter_array, marker='o', linestyle='None')     
-plt.xlabel('Time')
-plt.ylabel('Perimeter')
+plt.xlabel('Time (min)')
+plt.ylabel('Perimeter ($\mu m$)')
 plt.show()
 plt.show()
 
 
+plt.plot(time_array, area_array, marker='o', linestyle='None')     
+plt.xlabel('Time (min)')
+plt.ylabel('Area ($\mu m^2$)')
+plt.show()