41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
import glob
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import matplotlib.pyplot as plt
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import pandas as pd
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import seaborn as sb
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import numpy as np
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def main():
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time = np.arange(0.0, 4.0, 0.01)
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xstart = 1.0
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ystart = 1.0
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x_mean = xstart * np.exp(-time)
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y_mean = ystart * np.exp(-time)
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x_sq_mean = xstart*xstart * np.exp(-2*time) + (1 - np.exp(-2*time))
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y_sq_mean = ystart*ystart * np.exp(-2 * time) + (1 - np.exp(-2 * time))
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x = pd.read_csv("./data/out/harmonic_force_euler_L0_x.dat")
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x_sq = pd.read_csv("./data/out/harmonic_force_euler_L0_x_squared.dat")
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msd = pd.read_csv("./data/out/harmonic_force_euler_L0_msd.dat")
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msd_mean = (1-np.exp(-2*time))
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plt.plot(time, x_mean, label="a <x>")
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plt.plot(x["time"], x["val"], label="<x>")
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plt.plot(time, x_sq_mean, label="a <x²>")
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plt.plot(x_sq["time"], x_sq["val"], label="<x²>")
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plt.plot(time, 2*msd_mean,label="a msd")
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plt.plot(msd["time"], msd["val"], label="msd")
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#plt.plot(x["time"], x_sq["val"] - np.power(x["val"], 2.0))
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plt.plot(x["time"], 2.0*(x_sq["val"] - np.power(x["val"], 2.0)), label="<x²>-<x>²")
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plt.legend(loc = 1)
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plt.show()
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if __name__ == "__main__":
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main()
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