Initiate

plotting/plot_animated.py

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+#! /usr/bin/env python
+
+"""
+Plot the time-dependent density expectation value in Lieb-Liniger (n-hole wavepacket).
+
+Setup:
+- ensure matplotlib and numpy are installed in your python environment
+- make this file executable (chmod +x plot_animated.py)
+
+Usage: ./plot_animated.py [rho file name]
+"""
+
+
+import math
+import matplotlib.pyplot as plt
+import matplotlib.animation as animation
+import numpy as np
+import sys
+
+filename = str(sys.argv[1])
+
+data = filename.rpartition('/')[2]
+
+data = data.partition('c_')[2]
+c = float(data.partition('_')[0])
+data = data.partition('N_')[2]
+N = int(data.partition('_')[0])
+L = float(N)
+data = data.partition('nholes_')[2]
+nholes = int(data.partition('_')[0])
+data = data.partition('width_')[2]
+width = int(data.partition('_')[0])
+data = data.partition('offset_')[2]
+offset = int(data.partition('_')[0])
+data = data.partition('tmax_')[2].partition('.rhoxt')[0]
+tmax = float(data.partition('_')[0])
+
+
+x = np.loadtxt(filename.replace('.rhoxt','.x'), unpack=True)
+
+Nx = x.size
+
+rho = np.loadtxt(filename, unpack=True)
+
+Nt = int(rho.size/rho[0].size)
+dt = tmax/(Nt-1)
+
+fig, ax = plt.subplots()
+
+artists = []
+
+for i in range(Nt):
+    container = ax.plot(x, rho[i], '.', markersize=4, color='blue')
+    artists.append(container)
+
+ani = animation.ArtistAnimation(fig=fig, artists=artists, interval=100)
+
+plt.xlabel('x')
+plt.ylabel(r'$\rho(x, t)$')
+plt.title(f"Density expectation value\n{c=}, {N=}, nh={nholes}, w={width}, o={offset}")
+
+ani.save(filename.replace("rhoxt", "mp4"))
+
+plt.show()