118 lines
3.4 KiB
Python
118 lines
3.4 KiB
Python
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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, Energy, 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 = "PoD"
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def main():
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sims_path, regen = get_args(
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"Various graphs for single N data.",
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"folder that contains simulation data at various aspect ratios for some N",
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)
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data, n, r = get_data(
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sims_path / "package.pkl", get_simulation_data, args=(sims_path,), 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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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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plt.rcParams.update(RC_SETTINGS)
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fig = plt.figure(figsize=(15, 15))
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gs = fig.add_gridspec(1, 1)
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ax = fig.add_subplot(gs[0])
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ax2 = ax.twinx()
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ax.plot(alphas, 100 * (min_order - min_disorder), color="C2")
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ax2.plot(alphas, all_disorder_count, color="C4")
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ax.set_xlim(0.3, 1)
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ax.set_xticks(np.arange(0.3, 1.01, 0.1))
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start, end = ax.get_ylim()
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# space = np.linspace(0, end, 20)
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space = np.arange(-2.3, 3.3, 0.5)
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ax.set_ylim(-2.5, 3.4)
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ax.set_yticks(space)
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ax.ticklabel_format(axis="y", style="sci")
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# start, end = ax2.get_ylim()
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# space = np.linspace(start, end, 20)
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# space += 100 - space[-2]
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space = np.linspace(50, 100, len(space))
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ax2.set_ylim(
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space[0] - (space[1] - space[0]) * 0.4, space[-1] + (space[1] - space[0]) * 0.6
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)
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ax2.set_yticks(space)
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# ax2.set_ylim(start, space[-1])
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# ax2.set_yticks(space[1:-1])
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ax2.yaxis.set_major_formatter(mtick.PercentFormatter())
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ax.set_xlabel("Aspect Ratio")
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ax.set_ylabel(r"VEE $\left[\times 10^{2}\right]$", color="C2")
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ax2.set_ylabel("Percent of Disordered Equilibria", color="C4")
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# ax.legend(loc=(0.23, 0.5))
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ax.grid(zorder=0)
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props = dict(boxstyle="round", facecolor="white", alpha=0.8, zorder=20)
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ax.text(
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0.873,
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0.97,
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f"N={domain.n}",
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transform=ax.transAxes,
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verticalalignment="top",
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bbox=props,
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)
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out = OUTPUT_DIR / f"{NAME}-N{domain.n}.png"
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fig.savefig(out)
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print(f"Wrote to {out}.")
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if __name__ == "__main__":
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os.environ["QT_LOGGING_RULES"] = "*=false"
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try:
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main()
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except KeyboardInterrupt:
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print("Program terminated by user.")
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