Stuff

python_scripts/animation.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib
+from matplotlib.animation import FuncAnimation
+import ast
+
+import seaborn as sns 
+
+sns.set_theme()
+params = {
+    "font.family": "Serif",
+    "font.serif": "Roman",
+    "text.usetex": True,
+    "axes.titlesize": "large",
+    "axes.labelsize": "large",
+    "xtick.labelsize": "large",
+    "ytick.labelsize": "large",
+    "legend.fontsize": "medium",
+}
+plt.rcParams.update(params)
+
+wave_arr = []
+fig = plt.figure()
+ax = plt.gca()
+img = ax.imshow([[]])
+
+def plot():
+    with open("data/animation.txt") as f:
+        lines = f.readlines();
+        size = int(lines[0])
+        for line in lines[1:]:
+            arr = line.strip().split("\t")
+            arr = np.asarray(list(map(lambda x: ((a := complex(*ast.literal_eval(x)))*a.conjugate()).real, arr)))
+
+            # print(sum(arr))
+            arr = arr.reshape(size,size)
+            wave_arr.append(arr.T)
+            # print(arr)
+
+            # plt.imshow(arr, cmap="hot", interpolation="nearest")
+            # plt.show()
+
+
+def animation(i):
+    norm = matplotlib.cm.colors.Normalize(vmin=0, vmax=np.max(wave_arr[i]))
+    img.set_norm(norm)
+    img.set_data(wave_arr[i])
+
+
+if __name__ == "__main__":
+    plot()
+    
+    norm = matplotlib.cm.colors.Normalize(vmin=0, vmax=np.max(wave_arr[0]))
+    plt.grid(False)
+    img = ax.imshow(wave_arr[0], extent=[0,1,0,1], cmap=sns.color_palette("mako", as_cmap=True), norm=norm)
+    anim = FuncAnimation(fig, animation, interval=1, frames=np.arange(0,len(wave_arr)), repeat=True, blit=0)
+    # plt.show()
+
+    anim.save("./animation.gif", writer="ffmpeg", bitrate=10000, fps=15)