104 lines
2.7 KiB
Python
104 lines
2.7 KiB
Python
import argparse
|
|
import gzip
|
|
import logging
|
|
import multiprocessing as mp
|
|
import pathlib
|
|
import pickle
|
|
|
|
import matplotlib.pyplot as plt
|
|
import matplotlib.animation as animation
|
|
from matplotlib.gridspec import GridSpec
|
|
import numpy as np
|
|
from scipy import interpolate
|
|
|
|
from .olaflow import OFModel
|
|
|
|
parser = argparse.ArgumentParser(description="Post-process olaflow results")
|
|
parser.add_argument("-v", "--verbose", action="count", default=0)
|
|
parser.add_argument(
|
|
"-o",
|
|
"--output",
|
|
type=pathlib.Path,
|
|
help="Output directory for pickled data",
|
|
required=True,
|
|
)
|
|
args = parser.parse_args()
|
|
|
|
logging.basicConfig(level=max((10, 20 - 10 * args.verbose)))
|
|
log = logging.getLogger("ola_post")
|
|
|
|
log.info("Animating olaFlow output")
|
|
out = args.output
|
|
out.mkdir(parents=True, exist_ok=True)
|
|
|
|
with (
|
|
path.open("rb")
|
|
if (path := out.joinpath("pickle")).exists()
|
|
else gzip.open(path.with_suffix(".gz"), "rb")
|
|
) as f:
|
|
model = pickle.load(f)
|
|
|
|
flt = np.where((model.x >= -60) & (model.x <= -20) & (model.z >= 0) & (model.z <= 10))[
|
|
0
|
|
]
|
|
x0, idx0 = np.unique(model.x[flt].astype(np.half), return_inverse=True)
|
|
z0, idz0 = np.unique(model.z[flt].astype(np.half), return_inverse=True)
|
|
|
|
X, Z = np.meshgrid(x0, z0)
|
|
|
|
P = np.full((model.t.size, *X.shape), np.nan)
|
|
P[:, idz0, idx0] = model.fields["porosity"][:, flt]
|
|
|
|
AW = np.full((model.t.size, *X.shape), np.nan)
|
|
AW[:, idz0, idx0] = model.fields["alpha.water"][:, flt]
|
|
|
|
watl = z0[np.argmax((AW > 0.5)[:, ::-1, :], axis=1)]
|
|
|
|
U = np.full((model.t.size, 2, *X.shape), np.nan)
|
|
UU = np.full((model.t.size, *X.shape), np.nan)
|
|
U[..., idz0, idx0] = model.fields["U"][..., flt][:, (0, 2)]
|
|
UU[..., idz0, idx0] = np.linalg.norm(model.fields["U"][..., flt], axis=1)
|
|
|
|
figU = plt.figure(figsize=(19.2, 10.8), dpi=100)
|
|
gsU = GridSpec(2, 1, figure=figU, height_ratios=[1, 0.05])
|
|
axU = figU.add_subplot(gsU[0])
|
|
caxu1 = figU.add_subplot(gsU[1])
|
|
# caxu2 = figU.add_subplot(gsU[2])
|
|
|
|
alp = np.clip(np.nan_to_num(AW), 0, 1)
|
|
axU.pcolormesh(X, Z, P[1], vmin=0, vmax=1, cmap="Greys_r")
|
|
u_m = axU.quiver(
|
|
X,
|
|
Z,
|
|
*U[0],
|
|
UU[0],
|
|
alpha=alp[0],
|
|
cmap="inferno_r",
|
|
clim=(0, np.nanmax(UU)),
|
|
)
|
|
# (wat_p,) = axU.plot(x0, watl[0])
|
|
|
|
axU.set(xlabel="x (m)", ylabel="z (m)", aspect="equal", facecolor="#bebebe")
|
|
axU.grid(c="k", alpha=0.2)
|
|
titU = axU.text(
|
|
0.5,
|
|
0.95,
|
|
f"t={model.t[0]}s",
|
|
horizontalalignment="center",
|
|
verticalalignment="top",
|
|
transform=axU.transAxes,
|
|
)
|
|
|
|
figU.colorbar(u_m, label=r"$U$", cax=caxu1, shrink=0.6, orientation="horizontal")
|
|
|
|
|
|
def animU(i):
|
|
titU.set_text(f"t={model.t[i]}s")
|
|
u_m.set_UVC(*U[i], UU[i])
|
|
u_m.set_alpha(alp[i])
|
|
# wat_p.set_ydata(watl[i])
|
|
|
|
|
|
aniU = animation.FuncAnimation(figU, animU, frames=model.t.size, interval=1 / 24)
|
|
|
|
aniU.save(out.joinpath("animUzoom.mp4"), fps=24)
|