90 lines
2.3 KiB
Python
90 lines
2.3 KiB
Python
import argparse, numpy as np, os
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from multiprocessing import Pool, cpu_count
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import matplotlib.pyplot as plt
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from squish import ordered
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from squish.common import OUTPUT_DIR
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from script_tools import RC_SETTINGS, get_data, format_data
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NAME = "RegHexTessRatios"
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def get_ratios(n: int):
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return (n, ordered.hexagon_alpha(n))
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def main():
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parser = argparse.ArgumentParser(
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description="Generates graph for regular hexagonal tessellation ratios"
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)
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parser.add_argument(
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"max_n", metavar="N", type=int, help="maximum N of which to calculate"
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)
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parser.add_argument(
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"--regenerate",
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dest="regen",
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action="store_true",
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help="regenerates the cache file for processed data",
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)
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args = parser.parse_args()
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def f():
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data = {"alpha": [], "N": []}
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with Pool(cpu_count()) as pool:
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for i, res in enumerate(
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pool.imap_unordered(get_ratios, range(2, args.max_n + 1))
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):
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for ratio in res[1]:
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data["N"].append(res[0])
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data["alpha"].append(ratio)
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hashes = int(21 * i / (args.max_n - 1))
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print(
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f'Processed N={res[0]} |{"#"*hashes}{" "*(20-hashes)}|'
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+ f" {i+1}/{args.max_n-1}",
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flush=True,
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end="\r",
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)
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print(flush=True)
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return data
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data = get_data(OUTPUT_DIR / "OrderedCache" / (NAME + ".pkl"), f, regen=args.regen)
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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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alphas, ns = [], []
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for alpha, n in zip(data["alpha"], data["N"]):
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if n <= args.max_n:
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alphas.append(alpha)
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ns.append(n)
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ax.scatter(alphas, ns, s=5)
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ax.set_xlim(-0.01, 1.01)
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ax.set_xticks(np.arange(0, 1.01, 0.1))
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ax.set_ylim(0, args.max_n)
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ax.set_ylabel(r"$N$")
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ax.set_xlabel("Aspect Ratio")
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ax.grid(zorder=0)
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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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os.environ["QT_log10GING_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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