added animation

particles.py

@@ -0,0 +1,57 @@
+from brown.interaction import UFuncWrapper
+from brown.brown import BrownIterator
+import numpy as np
+from collections import deque
+from copy import copy
+import matplotlib.pyplot as plt
+import matplotlib.animation as ani
+
+c = np.array([5, 10, 20, 30, 0, 0, 0, 1, -20, 0, -2, -0.1, 2, 0, 0, 0, 0, 0, 0], dtype=np.float16)
+#force_function = UFuncWrapper(0, c)
+#interaction2D = UFuncWrapper(1, c)
+
+borders_x = [-100, 100]
+borders_y = [-100, 100]
+n_particles = 6
+frames = 1000
+
+x_coords = np.random.uniform(borders_x[0] / 2, borders_x[1] / 2, n_particles).astype(np.float16)
+y_coords = np.random.uniform(borders_y[0] / 2, borders_y[1] / 2, n_particles).astype(np.float16)
+
+
+x_momenta = np.zeros(n_particles, dtype=np.float16)
+y_momenta = np.zeros(n_particles, dtype=np.float16)
+
+
+
+fig = plt.figure(figsize=(7, 7))
+ax = fig.add_axes([0, 0, 1, 1], frameon=False)
+ax.set_xlim(*borders_x)
+ax.set_xticks([])
+ax.set_ylim(*borders_y)
+ax.set_yticks([])
+
+plot, = ax.plot(x_coords, y_coords, "b.")
+center_of_mass, = ax.plot(x_coords.mean(), y_coords.mean(), "r-")
+center_of_mass_history_x = deque([x_coords.mean()])
+center_of_mass_history_y = deque([y_coords.mean()])
+
+brown = BrownIterator(-1, c
+			, x_coords, y_coords
+			, y_momenta, y_momenta
+			, borders_x, borders_y
+			, border_dampening=1
+			, dt=0.001)
+
+u = iter(brown)
+
+def update(i):
+	data = next(u)
+	center_of_mass_history_x.append(x_coords.mean())
+	center_of_mass_history_y.append(y_coords.mean())
+
+	plot.set_data(*data)
+	center_of_mass.set_data(center_of_mass_history_x, center_of_mass_history_y)
+
+animation = ani.FuncAnimation(fig, update, range(frames), interval=1)
+plt.show()