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plotting/multiplot_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 multiplot_animated.py)
+
+Usage: ./multiplot_animated.py [plot output filename] [1st rho file name] [2nd rho file name] ... [last rho file name]
+"""
+
+
+import math
+import matplotlib.pyplot as plt
+import matplotlib.animation as animation
+import numpy as np
+import sys
+
+argc = len(sys.argv) # The number of plot lines is argc-2
+
+output_filename = str(sys.argv[1])
+
+lines = []
+
+for i in range(2,argc):
+    filename = str(sys.argv[i])
+    data = filename.rpartition('/')[2]
+    data = data.partition('c_')[2]
+    linedict = {}
+    linedict["c"] = float(data.partition('_')[0])
+    data = data.partition('N_')[2]
+    linedict["N"] = int(data.partition('_')[0])
+    linedict["L"] = float(linedict["N"])
+    data = data.partition('nholes_')[2]
+    linedict["nholes"] = int(data.partition('_')[0])
+    data = data.partition('width_')[2]
+    linedict["width"] = int(data.partition('_')[0])
+    data = data.partition('offset_')[2]
+    linedict["offset"] = int(data.partition('_')[0])
+    data = data.partition('_')[2]
+    linedict["protocol"] = data.partition('_Nx')[0]
+    data = data.partition('tmax_')[2].partition('.rhoxt')[0]
+    linedict["tmax"] = float(data.partition('_')[0])
+    linedict["x"] = np.loadtxt(filename.replace('.rhoxt','.x'), unpack=True)
+    linedict["Nx"] = linedict["x"].size
+    linedict["rho"] = np.loadtxt(filename, unpack=True)
+    linedict["Nt"] = int(linedict["rho"].size/linedict["rho"][0].size)
+    linedict["dt"] = linedict["tmax"]/(linedict["Nt"]-1)
+    lines.append(linedict)
+
+
+fig, ax = plt.subplots()
+
+for line in lines:
+    line["line"] = ax.plot(
+        line["x"], line["rho"][0], '.', markersize=4,
+        label=f"c={line['c']} N={line['N']} nh={line['nholes']} w={line['width']} o={line['offset']} {line['protocol']}"
+    )[0]
+
+ax.set(
+    xlabel='x',
+    ylabel=r'$\rho(x, t)$',
+    title=f"Density expectation value")
+ax.legend(bbox_to_anchor=(0.05, -0.16), loc="upper left")
+plt.tight_layout()
+
+time_text = fig.text(0.8, 0.15, f"t=0")
+
+
+def update(frame):
+    for line in lines:
+        line["line"].set_ydata(line["rho"][frame])
+    time_text.set_text(f"t={frame*lines[0]['dt']}")
+    return (lines, time_text)
+
+
+ani = animation.FuncAnimation(fig=fig, func=update, frames=lines[0]["Nt"], interval=100)
+
+ani.save(output_filename + ".mp4")
+
+plt.show()

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()

plotting/plot_t0.py

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+#! /usr/bin/env python
+
+"""
+Plot the t=0 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_to.py)
+
+Usage: ./plot_t0.py [rho file name]
+"""
+
+
+import math
+import matplotlib.pyplot as plt
+import numpy as np
+import sys
+
+filename = str(sys.argv[1])
+
+x = np.loadtxt(filename.replace('.rhoxt','.x'), unpack=True)
+
+rho = np.loadtxt(filename, usecols=(0), unpack=True)
+
+plt.plot(x, rho, '.', markersize=4)
+
+plt.xlabel('x')
+plt.ylabel(r'$\rho(x, t=0)$')
+plt.title('Density expectation value\n' + filename)
+
+plt.savefig(filename.replace('.rhoxt', '.png'))
+
+plt.show()