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79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
#!/usr/bin/env python
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"""
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Plot: Area
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Plots areas
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@ Author: Moussouni, Yaël (MSc student) & Bhat, Junaid Ramzan (MSc student)
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@ Institution: Université de Strasbourg, CNRS, Observatoire astronomique
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de Strasbourg, UMR 7550, F-67000 Strasbourg, France
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@ Date: 2024-11-29
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"""
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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if "YII_1" in plt.style.available: plt.style.use("YII_1")
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OUT_DIR = "./Output/"
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FILENAME_PREFIX = "phase_separation_"
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EXTENSION = ".csv"
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def plot_area(filelist: list, mu_c = 1e-4) -> int:
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"""
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Plot all the Poincaré sections in the file list.
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@params:
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- filelist: the list of files in the output directory, with the format
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"poincare_sections_{linear, parallel}_[1/E].csv"
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- title: title of the figure
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@returns:
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- 0.
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"""
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orderlist = np.argsort([(int(file
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.replace(FILENAME_PREFIX, "")
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.replace(EXTENSION, "")))
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for file in filelist])
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filelist = np.array(filelist)[orderlist]
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N = len(filelist)
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E = np.linspace(1/100, 1/6, N)
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mu = []
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for filename in filelist:
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with open(OUT_DIR + filename) as file:
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data = file.readlines()
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data = [np.float64(d.replace("\n", "")) for d in data]
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mu.append(data)
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mu = np.array(mu)
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fig, ax = plt.subplots(1)
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ax.scatter([], [], s=1, color="k", label="Data")
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for i in range(len(mu)):
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Y = mu[i]
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ax.scatter([E[i]]*len(Y), Y, s=1, color="k", alpha=0.1)
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ax.scatter(E, np.mean(mu, axis=1), s=5,
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color="C1", marker="o", label="Mean")
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ax.scatter(E, np.median(mu, axis=1), s=5,
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color="C3", marker="s", label="Median")
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ax.plot(E, [mu_c]*len(E),
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color="C5", label="Critical value $\\mu_\\mathrm{{c}}$")
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ax.text(0.01, 1e-5, "Regular", va="bottom", ha="left", color="C5")
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ax.text(0.01, 1e-3, "Chaotic", va="top", ha="left", color="C5")
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ax.set_xlabel("Energy $E$")
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ax.set_ylabel("Phase-space squared distance $\\mu$")
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ax.set_yscale("log")
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ax.legend()
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fig.savefig("mu.pdf")
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fig, ax = plt.subplots(1)
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N_reg = np.count_nonzero(mu < mu_c, axis=1)
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N = np.shape(mu)[1]
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Area = N_reg / N
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ax.scatter(E, Area, s=5, color="C0")
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ax.set_xlabel("Energy $E$")
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ax.set_ylabel("Area $N_\\mathrm{{reg}}/N_\\mathrm{{part}}$")
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fig.savefig("area.pdf")
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return 0
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filelist = [f for f in os.listdir(OUT_DIR) if FILENAME_PREFIX in f]
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plot_area(filelist)
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plt.show()
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