109 lines
3.0 KiB
Python
109 lines
3.0 KiB
Python
import numpy as np, os, csv
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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 = "Cumulative-VEE"
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ALPHA = 1.0
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def main():
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sims_path, regen = get_args(
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"Anti-cumulative distribution of VEE and percent of equilibria for fixed alpha",
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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=(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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my_cool_data = [["VEE", 61, 67, 73, 81, 84, 100]]
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for vee in np.linspace(0, 0.06, 10000):
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my_cool_data.append([vee])
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for j, package in enumerate(packages):
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data, ordered_data, domain = package
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e_hex = ordered.e_hex(domain)
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alpha_index = np.where(data["all"]["alpha"] == ALPHA)[0][0]
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energies = data["all"]["Energy"][alpha_index] / domain.n - e_hex
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min_order = ordered_data["Energy"][alpha_index][0] / domain.n - e_hex
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vees = np.linspace(0, 0.06, 10000)
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index = np.argmin(np.abs(vees - min_order))
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counts = np.empty(vees.shape, dtype=float)
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for i, vee in enumerate(vees):
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counts[i] = np.count_nonzero(energies >= vee)
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counts = 100 * counts / len(energies)
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for i, count in enumerate(counts):
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my_cool_data[i + 1].append(count)
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ax.plot(100*vees, counts, label=f"N={domain.n}")
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#ax.plot(
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# 100 * vees[: index + 1],
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# counts[: index + 1],
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# label=f"N={domain.n}",
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# color=f"C{j}",
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#)
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#ax.plot(
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# 100 * vees[index:],
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# counts[index:],
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# label=f"_nolegend_",
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# linestyle="dotted",
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# color=f"C{j}",
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#)
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with open("cumulative-vee.csv", "w") as csvfile:
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writer = csv.writer(csvfile)
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writer.writerows(my_cool_data)
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ax.set_xlim(0, 6.3)
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ax.yaxis.set_major_formatter(mtick.PercentFormatter())
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ax.set_xlabel(r"VEE $\left[\times 10^{2}\right]$")
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ax.set_ylabel("Percent of Equilibria")
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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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