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Highly improved efficiency in processing.animate to find grid

This commit is contained in:
Edgar P. Burkhart 2022-04-15 11:22:36 +02:00
parent 47bf31fb3a
commit f7261d2e6b
Signed by: edpibu
GPG key ID: 9833D3C5A25BD227

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@ -38,21 +38,19 @@ x0 = config.getfloat("post", "x")
z0 = config.getfloat("post", "z")
i0 = np.argmin(np.abs((model.x - x0) + 1j * (model.z - z0)))
X, Z = np.meshgrid(np.unique(model.x), np.unique(model.z))
x0, idx0 = np.unique(model.x.astype(np.half), return_inverse=True)
z0, idz0 = np.unique(model.z.astype(np.half), return_inverse=True)
C = np.where(
(model.x[:, None, None].astype(np.single) == X[None, :, :].astype(np.single))
& (model.z[:, None, None].astype(np.single) == Z[None, :, :].astype(np.single))
)
X, Z = np.meshgrid(x0, z0)
P = np.full((model.t.size, *X.shape), np.nan)
P[:, C[1], C[2]] = model.fields["porosity"][:, C[0]]
P[:, idz0, idx0] = model.fields["porosity"]
AW = np.full((model.t.size, *X.shape), np.nan)
AW[:, C[1], C[2]] = model.fields["alpha.water"][:, C[0]]
AW[:, idz0, idx0] = model.fields["alpha.water"]
U = np.full((model.t.size, *X.shape), np.nan)
U[:, C[1], C[2]] = np.linalg.norm(model.fields["U"], axis=1)[:, C[0]]
U[:, idz0, idx0] = np.linalg.norm(model.fields["U"], axis=1)
fig, ax = plt.subplots(figsize=(19.2, 10.8), dpi=100)
tit = ax.text(
@ -129,9 +127,10 @@ def animU(i):
ur_m.set_array(U[i])
ur_m.set_alpha(1 - np.nan_to_num(AW[i]).clip(0, 1))
plt.show()
ani = animation.FuncAnimation(fig, anim, frames=model.t.size, interval=1 / 24)
aniU = animation.FuncAnimation(figU, animU, frames=model.t.size, interval=1 / 24)
ani.save(out.joinpath("anim.mp4"), fps=24)
aniU.save(out.joinpath("animU.mp4"), fps=24)
#ani = animation.FuncAnimation(fig, anim, frames=model.t.size, interval=1/24)
#aniU = animation.FuncAnimation(figU, animU, frames=model.t.size, interval=1/24)
#
#ani.save(out.joinpath("anim.mp4"), fps=24)
#aniU.save(out.joinpath("animU.mp4"), fps=24)