# Penning Trap Simulation: src/scripts/plot_relative_error.py Source File

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plot_relative_error.py
Go to the documentation of this file.
import matplotlib.pyplot as plt
import numpy as np
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)
def main():
directories = [
"output/relative_error/RK4/",
"output/relative_error/euler/",
]
files = [
"4000_steps.txt",
"8000_steps.txt",
"16000_steps.txt",
"32000_steps.txt",
]
labels = [
r"$n_1$",
r"$n_2$",
r"$n_3$",
r"$n_4$",
]
titles = [
"(a)",
"(b)"
]
methods = [
"rk4",
"euler"
]
colors = [
"seagreen",
"darkred",
"darkgoldenrod",
"steelblue"
]
fig1, axs1 = plt.subplots(2,1)
for i, (dir, title) in enumerate(list(zip(directories, titles))):
max_err = []
for label, file, color in zip(labels, files, colors):
with open(dir+file) as f:
lines = f.readlines()
t = np.linspace(0, 50, len(lines))
r = np.array([float(line.strip()) for line in lines])
max_err.append(max(r))
axs1[i].plot(t, r, label=label, color=color)
axs1[i].set(xlabel=r"t $(\mu s)$", ylabel = r"relative error $(\mu m)$")
axs1[i].legend()
axs1[i].set_title(title)
conv_rate = 1/3 * sum([np.log2(max_err[i+1]/max_err[i])/np.log2(.5) for i in range(3)])
print(f"{methods[i]}: {conv_rate}")
plt.tight_layout()
fig1.savefig("../latex/images/relative_error.pdf", bbox_inches="tight")
if __name__ == "__main__":
main()