206 lines
5.4 KiB
Python
206 lines
5.4 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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fig = plt.figure(
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figsize=(15 / 2.54, 4 / 2.54), dpi=200, constrained_layout=True
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)
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gs = GridSpec(
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3 if not args.initial else 1,
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1,
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figure=fig,
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height_ratios=[1, 0.1, 0.1] if not args.initial else [1],
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)
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ax = fig.add_subplot(gs[0])
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if not args.initial:
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cax1 = fig.add_subplot(gs[1])
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cax2 = fig.add_subplot(gs[2])
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aw_m = ax.imshow(
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AW[0],
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vmin=0,
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vmax=1,
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extent=(x0.min(), x0.max(), z0.min(), z0.max()),
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cmap="Blues",
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zorder=1,
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)
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p_m = ax.imshow(
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P[1],
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vmin=0,
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vmax=1,
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extent=(x0.min(), x0.max(), z0.min(), z0.max()),
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cmap="Greys_r",
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alpha=(np.nan_to_num(1 - P[1]) / 2).clip(0, 1),
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zorder=1.1,
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)
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ax.axhline(4.5, ls="-.", lw=1, c="k", alpha=0.2, zorder=1.2)
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if not args.initial:
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fig.colorbar(
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aw_m, label=r"$\alpha_w$", cax=cax1, shrink=0.6, orientation="horizontal"
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)
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fig.colorbar(p_m, label=r"Porosity", cax=cax2, shrink=0.6, orientation="horizontal")
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ax.set(xlabel="x (m)", ylabel="z (m)", aspect="equal", facecolor="#000000")
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ax.grid(c="k", alpha=0.2)
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ax.xaxis.set_minor_locator(MultipleLocator(5))
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ax.yaxis.set_minor_locator(MultipleLocator(5))
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figU = plt.figure()
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gsU = GridSpec(
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2 if args.max else 3,
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1,
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figure=figU,
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height_ratios=[1, 0.05] if args.max else [1, 0.05, 0.05],
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)
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axU = figU.add_subplot(gsU[0])
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caxu1 = figU.add_subplot(gsU[1])
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if not args.max:
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caxu2 = figU.add_subplot(gsU[2])
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u_m = axU.imshow(
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U[0],
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cmap="BuPu",
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vmin=0,
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vmax=20,
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extent=(x0.min(), x0.max(), z0.min(), z0.max()),
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zorder=1,
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alpha=np.nan_to_num(AW[0]).clip(0, 1),
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)
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ur_m = axU.imshow(
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U[0],
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cmap="YlOrBr",
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vmin=0,
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vmax=20,
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extent=(x0.min(), x0.max(), z0.min(), z0.max()),
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zorder=1,
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alpha=1 - np.nan_to_num(AW[0]).clip(0, 1),
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)
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# aw_u = axU.contour(X, Z, AW[0], levels=(.5,))
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axU.set(xlabel="x (m)", ylabel="z (m)", aspect="equal", facecolor="#bebebe")
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axU.grid(c="k", alpha=0.2)
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figU.colorbar(u_m, label=r"$U_w$", cax=caxu1, shrink=0.6, orientation="horizontal")
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if args.max:
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aw_m.set_array(AW.max(axis=0))
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u_m.set_array(np.nanmax(np.where(AW > 0.5, U, np.nan), axis=0, initial=0))
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u_m.set_alpha(1)
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u_m.set_cmap("hot_r")
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ur_m.remove()
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fig.savefig(out.joinpath("max_aw.pdf"))
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figU.savefig(out.joinpath("max_U.pdf"))
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elif args.initial:
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aw_m.set_array(AW[0])
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ax.vlines(-20, -15, 15, color="k", lw=1, ls="--", label="Measurements")
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ax.text(-20, 15, "Measurements", ha="right", va="bottom")
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fig.savefig(out.joinpath("aw_t0.pdf"))
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fig.savefig(out.joinpath("aw_t0.jpg"), dpi=200)
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else:
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fig.set(figwidth=19.2, figheight=10.8, dpi=100)
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figU.set(figwidth=19.2, figheight=10.8, dpi=100)
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figU.colorbar(ur_m, label=r"$U_a$", cax=caxu2, shrink=0.6, orientation="horizontal")
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tit = ax.text(
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0.5,
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0.95,
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f"t={model.t[0]}s",
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horizontalalignment="center",
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verticalalignment="top",
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transform=ax.transAxes,
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)
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titU = axU.text(
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0.5,
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0.95,
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f"t={model.t[0]}s",
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horizontalalignment="center",
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verticalalignment="top",
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transform=axU.transAxes,
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)
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def anim(i):
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tit.set_text(f"t={model.t[i]}s")
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aw_m.set_array(AW[i])
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def animU(i):
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titU.set_text(f"t={model.t[i]}s")
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u_m.set_array(U[i])
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u_m.set_alpha(np.nan_to_num(AW[i]).clip(0, 1))
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ur_m.set_array(U[i])
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ur_m.set_alpha(1 - np.nan_to_num(AW[i]).clip(0, 1))
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ani = animation.FuncAnimation(fig, anim, frames=model.t.size, interval=1 / 24)
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aniU = animation.FuncAnimation(figU, animU, frames=model.t.size, interval=1 / 24)
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ani.save(out.joinpath("anim.mp4"), fps=24)
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aniU.save(out.joinpath("animU.mp4"), fps=24)
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