79 lines
2.1 KiB
Python
79 lines
2.1 KiB
Python
import argparse
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import gzip
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import logging
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import multiprocessing as mp
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import pathlib
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import pickle
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import matplotlib.pyplot as plt
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import matplotlib.animation as animation
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from matplotlib.gridspec import GridSpec
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from matplotlib.ticker import MultipleLocator
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import numpy as np
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from scipy import interpolate
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from .olaflow import OFModel
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parser = argparse.ArgumentParser(description="Post-process olaflow results")
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parser.add_argument("-v", "--verbose", action="count", default=0)
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parser.add_argument(
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"-o",
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"--output",
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type=pathlib.Path,
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help="Output directory for pickled data",
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required=True,
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)
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parser.add_argument(
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"-m",
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"--max",
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help="Only compute maximum rather than animation",
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action="store_true",
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)
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parser.add_argument(
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"-i",
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"--initial",
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help="Only compute initial domain",
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action="store_true",
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)
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args = parser.parse_args()
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logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
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log = logging.getLogger("ola_post")
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log.info("Animating olaFlow output")
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out = args.output
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out.mkdir(parents=True, exist_ok=True)
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with (
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path.open("rb")
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if (path := out.joinpath("pickle")).exists()
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else gzip.open(path.with_suffix(".gz"), "rb")
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) as f:
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model = pickle.load(f)
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x0, idx0 = np.unique(model.x.astype(np.half), return_inverse=True)
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z0, idz0 = np.unique(model.z.astype(np.half), return_inverse=True)
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ix0 = np.argsort(x0)
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iz0 = np.argsort(z0)[::-1]
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X, Z = np.meshgrid(x0, z0)
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P = np.full((model.t.size, *X.shape), np.nan)
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P[:, iz0[idz0], ix0[idx0]] = model.fields["porosity"]
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AW = np.full((model.t.size, *X.shape), np.nan)
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AW[:, iz0[idz0], ix0[idx0]] = model.fields["alpha.water"]
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#U = np.full((model.t.size, *X.shape), np.nan)
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#U[:, iz0[idz0], ix0[idx0]] = np.linalg.norm(model.fields["U"], axis=1)
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i0 = np.argmin(np.abs(model.t[:, None] - np.asarray((102, 118, 144.5, 176.5))[None, :]), axis=0)
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fig, ax_ = plt.subplots(
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2, 2, figsize=(15 / 2.54, 4 / 2.54), dpi=200, constrained_layout=True
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)
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for ax, i in zip(ax_.flatten(), i0):
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ax.imshow(AW[i], cmap="Blues", vmin=0, vmax=1)
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fig.savefig(out.joinpath("snap.pdf"))
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