def _main():
parser = argparse.ArgumentParser(description=__doc__)
_ = vutil.common_argparse(parser)
if _HAS_SCIPY:
warnings.filterwarnings("ignore", category=OptimizeWarning)
f = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[0].xdmf'))
mp = viscid.get_mp_info(f['pp'],
f['b'],
f['j'],
f['e_cc'],
fit='mp_xloc',
slc="x=7f:12.0f, y=-6f:6f, z=-6f:6f",
cache=False)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
# # get normals from paraboloid surface
if isinstance(mp['paraboloid'], viscid.DeferredImportError):
xfail("Scipy not installed; paraboloid curve fitting not tested")
else:
parab_n = viscid.paraboloid_normal(Y, Z, *mp['paraboloid'][0])
parab_n = parab_n.reshape(3, -1)
# get normals from minvar
minvar_y = Y.reshape(-1)
minvar_z = Z.reshape(-1)
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[1]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
lmn = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0, n=64)
minvar_n[:, i] = lmn[2, :]
theta = (180 / np.pi) * np.arccos(np.sum(parab_n * minvar_n, axis=0))
# make sure paraboloid normals and minvar normals are closeish
# this is a poor check, but at least it's something
assert np.min(theta) < 3.0
assert np.average(theta) < 20.0
assert np.median(theta) < 20.0
assert np.max(theta) < 70.0
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
_ = vutil.common_argparse(parser)
if _HAS_SCIPY:
warnings.filterwarnings("ignore", category=OptimizeWarning)
f = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[0].xdmf'))
mp = viscid.get_mp_info(f['pp'], f['b'], f['j'], f['e_cc'], fit='mp_xloc',
slc="x=7j:12.0j, y=-6j:6j, z=-6j:6j",
cache=False)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
# # get normals from paraboloid surface
if isinstance(mp['paraboloid'], viscid.DeferredImportError):
xfail("Scipy not installed; paraboloid curve fitting not tested")
else:
parab_n = viscid.paraboloid_normal(Y, Z, *mp['paraboloid'][0])
parab_n = parab_n.reshape(3, -1)
# get normals from minvar
minvar_y = Y.reshape(-1)
minvar_z = Z.reshape(-1)
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[1]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
lmn = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0, n=64)
minvar_n[:, i] = lmn[2, :]
theta = (180 / np.pi) * np.arccos(np.sum(parab_n * minvar_n, axis=0))
# make sure paraboloid normals and minvar normals are closeish
# this is a poor check, but at least it's something
assert np.min(theta) < 3.0
assert np.average(theta) < 20.0
assert np.median(theta) < 20.0
assert np.max(theta) < 70.0
return 0
def _main():
f = viscid.load_file("$WORK/xi_fte_001/*.3d.[4050f].xdmf")
mp = get_mp_info(f['pp'], f['b'], f['j'], f['e_cc'], fit='mp_xloc',
slc="x=6.5j:10.5j, y=-4j:4j, z=-4.8j:3j", cache=False)
y, z = mp['pp_max_xloc'].meshgrid_flat(prune=True)
x = mp['pp_max_xloc'].data.reshape(-1)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
x2 = paraboloid(Y, Z, *mp['paraboloid'][0])
skip = 117
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
minvar_y = Y.reshape(-1)[::skip]
minvar_z = Z.reshape(-1)[::skip]
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[0]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
minvar_n[:, i] = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0, n=64)[2, :]
# 2d plots, normals don't look normal in the matplotlib projection
if False: # pylint: disable=using-constant-test
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
normals = paraboloid_normal(Y, Z, *mp['paraboloid'][0])
p0 = np.array([x2, Y, Z]).reshape(3, -1)
p1 = p0 + normals.reshape(3, -1)
vlt.scatter_3d(np.vstack([x, y, z])[:, ::skip], equal=True)
for i in range(0, p0.shape[1], skip):
plt.gca().plot([p0[0, i], p1[0, i]],
[p0[1, i], p1[1, i]],
[p0[2, i], p1[2, i]], color='c')
# z2 = _ellipsiod(X, Y, *popt)
plt.gca().plot_surface(Y, Z, x2, color='r')
vlt.show()
# mayavi 3d plots, normals look better here
if True: # pylint: disable=using-constant-test
from viscid.plot import vlab
vlab.points3d(x[::skip], y[::skip], z[::skip], scale_factor=0.25,
color=(0.0, 0.0, 1.0))
mp_width = mp['mp_width']['x=0']
mp_sheath_edge = mp['mp_sheath_edge']['x=0']
mp_sphere_edge = mp_sheath_edge - mp_width
vlab.mesh(x2, Y, Z, scalars=mp_width.data)
vlab.mesh(mp_sheath_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
vlab.mesh(mp_sphere_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
n[0], n[1], n[2], color=(1, 0, 0))
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
minvar_n[0], minvar_n[1], minvar_n[2], color=(0, 0, 1))
vlab.show()
def _main():
f = viscid.load_file("$WORK/xi_fte_001/*.3d.[4050f].xdmf")
mp = get_mp_info(f['pp'],
f['b'],
f['j'],
f['e_cc'],
fit='mp_xloc',
slc="x=6.5f:10.5f, y=-4f:4f, z=-4.8f:3f",
cache=False)
y, z = mp['pp_max_xloc'].meshgrid_flat(prune=True)
x = mp['pp_max_xloc'].data.reshape(-1)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
x2 = paraboloid(Y, Z, *mp['paraboloid'][0])
skip = 117
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
minvar_y = Y.reshape(-1)[::skip]
minvar_z = Z.reshape(-1)[::skip]
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[0]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
minvar_n[:, i] = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0,
n=64)[2, :]
# 2d plots, normals don't look normal in the matplotlib projection
if False: # pylint: disable=using-constant-test
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
normals = paraboloid_normal(Y, Z, *mp['paraboloid'][0])
p0 = np.array([x2, Y, Z]).reshape(3, -1)
p1 = p0 + normals.reshape(3, -1)
vlt.scatter_3d(np.vstack([x, y, z])[:, ::skip], equal=True)
for i in range(0, p0.shape[1], skip):
plt.gca().plot([p0[0, i], p1[0, i]], [p0[1, i], p1[1, i]],
[p0[2, i], p1[2, i]],
color='c')
# z2 = _ellipsiod(X, Y, *popt)
plt.gca().plot_surface(Y, Z, x2, color='r')
vlt.show()
# mayavi 3d plots, normals look better here
if True: # pylint: disable=using-constant-test
from viscid.plot import vlab
vlab.points3d(x[::skip],
y[::skip],
z[::skip],
scale_factor=0.25,
color=(0.0, 0.0, 1.0))
mp_width = mp['mp_width']['x=0']
mp_sheath_edge = mp['mp_sheath_edge']['x=0']
mp_sphere_edge = mp_sheath_edge - mp_width
vlab.mesh(x2, Y, Z, scalars=mp_width.data)
vlab.mesh(mp_sheath_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
vlab.mesh(mp_sphere_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
n = paraboloid_normal(Y, Z,
*mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
n[0],
n[1],
n[2],
color=(1, 0, 0))
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
minvar_n[0],
minvar_n[1],
minvar_n[2],
color=(0, 0, 1))
vlab.show()
