96 lines
2.8 KiB
Python
96 lines
2.8 KiB
Python
import numpy as np, os
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import matplotlib.pyplot as plt
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import matplotlib.ticker as mtick
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from squish import Simulation, DomainParams, ordered
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from squish.common import OUTPUT_DIR
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from script_tools import (
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RC_SETTINGS,
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get_args,
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get_data,
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get_simulation_data,
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get_ordered_data,
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)
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NAME = "VEEDiff-PoD"
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def main():
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sims_path, regen = get_args(
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"Scatter plot of VEE difference and disordered equilibria.",
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"folders that contains various N simulations to plot",
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)
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packages = []
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for fol in sims_path.iterdir():
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if fol.is_file():
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continue
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data, n, r = get_data(
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fol / "package.pkl", get_simulation_data, args=(fol,), regen=regen
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)
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domain, alphas = DomainParams(n, 1, 1, r), data["all"]["alpha"]
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ordered_data = get_data(
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OUTPUT_DIR / "OrderedCache" / f"{n}.pkl",
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get_ordered_data,
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args=(domain, alphas),
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regen=regen,
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)
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packages.append([data, ordered_data, domain])
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packages.sort(key=lambda x: x[2].n)
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plt.rcParams.update(RC_SETTINGS)
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fig = plt.figure(figsize=(20, 9))
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gs = fig.add_gridspec(1, 1)
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ax = fig.add_subplot(gs[0])
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for j, package in enumerate(packages):
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data, ordered_data, domain = package
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min_disorder, max_disorder = [], []
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for i, energies in enumerate(data["distinct"]["Energy"]):
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disorder_energies = []
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for j, energy in enumerate(energies):
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if not data["distinct"]["Ordered"][i][j]:
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disorder_energies.append(energy)
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min_disorder.append(min(disorder_energies))
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max_disorder.append(max(disorder_energies))
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min_order = []
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for i, energies in enumerate(ordered_data["Energy"]):
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min_order.append(energies[0])
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e_hex = ordered.e_hex(domain)
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min_disorder = np.array(min_disorder) / domain.n - e_hex
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max_disorder = np.array(max_disorder) / domain.n - e_hex
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min_order = np.array(min_order) / domain.n - e_hex
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all_disorder_count = []
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for disorders in data["all"]["Ordered"]:
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all_disorder_count.append(
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100 * np.count_nonzero(disorders == False) / len(disorders)
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)
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ax.scatter(
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100 * (min_order - min_disorder), all_disorder_count, label=f"N={domain.n}"
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)
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ax.set_ylabel("POD")
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ax.set_xlabel(r"VEE Difference $\left[\times 10^{2}\right]$")
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ax.yaxis.set_major_formatter(mtick.PercentFormatter())
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ax.set_ylim(48, 102)
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ax.set_yticks(np.arange(50, 101, 10))
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ax.grid(zorder=0)
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ax.legend()
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fig.savefig(OUTPUT_DIR / (NAME + ".png"))
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print(f"Wrote to {OUTPUT_DIR / (NAME + '.png')}")
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if __name__ == "__main__":
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main()
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