def guess_dipole_moment(b, r=2.0, strength=DEFAULT_STRENGTH, cap_angle=40,
cap_ntheta=121, cap_nphi=121, plot=False):
"""guess dipole moment from a B field"""
viscid.logger.warning("guess_dipole_moment doesn't seem to do better than "
"1.6 degrees, you may want to use cotr instead.")
cap = seed.SphericalCap(r=r, angle=cap_angle, ntheta=cap_ntheta,
nphi=cap_nphi)
b_cap = interp_trilin(b, cap)
# FIXME: this doesn't get closer than 1.6 deg @ (theta, mu) = (0, 7.5)
# so maybe the index is incorrect somehow?
idx = np.argmax(viscid.magnitude(b_cap).data)
pole = cap.points()[:, idx]
# FIXME: it should be achievabe to get strength from the magimum magnitude,
# up to the direction
pole = strength * pole / np.linalg.norm(pole)
# # not sure where 0.133 comes from, this is probably not correct
# pole *= 0.133 * np.dot(pole, b_cap.data.reshape(-1, 3)[idx, :]) * r**3
if plot:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
vlt.plot(viscid.magnitude(b_cap))
vlt.plot(viscid.magnitude(b_cap), style='contour', levels=10,
colors='k', colorbar=False, ax=plt.gca())
vlt.show()
return pole
def main():
f = viscid.load_file("~/dev/work/tmedium/*.3d.[-1].xdmf")
grid = f.get_grid()
gslc = "x=-26f:12.5f, y=-15f:15f, z=-15f:15f"
# gslc = "x=-12.5f:26f, y=-15f:15f, z=-15f:15f"
b_cc = f['b_cc'][gslc]
b_cc.name = "b_cc"
b_fc = f['b_fc'][gslc]
b_fc.name = "b_fc"
e_cc = f['e_cc'][gslc]
e_cc.name = "e_cc"
e_ec = f['e_ec'][gslc]
e_ec.name = "e_ec"
pp = f['pp'][gslc]
pp.name = 'pp'
pargs = dict(logscale=True, earth=True)
# mpl.clf()
# ax1 = mpl.subplot(211)
# mpl.plot(f['pp']['y=0f'], **pargs)
# # mpl.plot(viscid.magnitude(f['b_cc']['y=0f']), **pargs)
# # mpl.show()
# mpl.subplot(212, sharex=ax1, sharey=ax1)
# mpl.plot(viscid.magnitude(viscid.fc2cc(f['b_fc'])['y=0f']), **pargs)
# mpl.show()
basename = './tmediumR.3d.{0:06d}'.format(int(grid.time))
viscid.save_fields(basename + '.h5', [b_cc, b_fc, e_cc, e_ec, pp])
f2 = viscid.load_file(basename + ".xdmf")
pargs = dict(logscale=True, earth=True)
mpl.clf()
ax1 = mpl.subplot(211)
mpl.plot(f2['pp']['y=0f'], style='contour', levels=5, colorbar=None,
colors='k', **pargs)
mpl.plot(viscid.magnitude(f2['b_cc']['y=0f']), **pargs)
mpl.subplot(212, sharex=ax1, sharey=ax1)
mpl.plot(viscid.magnitude(viscid.fc2cc(f2['b_fc'])['y=0f']), **pargs)
mpl.show()
os.remove(basename + '.h5')
os.remove(basename + '.xdmf')
return 0
def main():
f = viscid.load_file("~/dev/work/tmedium/*.3d.[-1].xdmf")
grid = f.get_grid()
gslc = "x=-26f:12.5f, y=-15f:15f, z=-15f:15f"
# gslc = "x=-12.5f:26f, y=-15f:15f, z=-15f:15f"
b_cc = f['b_cc'][gslc]
b_cc.name = "b_cc"
b_fc = f['b_fc'][gslc]
b_fc.name = "b_fc"
e_cc = f['e_cc'][gslc]
e_cc.name = "e_cc"
e_ec = f['e_ec'][gslc]
e_ec.name = "e_ec"
pp = f['pp'][gslc]
pp.name = 'pp'
pargs = dict(logscale=True, earth=True)
# vlt.clf()
# ax1 = vlt.subplot(211)
# vlt.plot(f['pp']['y=0f'], **pargs)
# # vlt.plot(viscid.magnitude(f['b_cc']['y=0f']), **pargs)
# # vlt.show()
# vlt.subplot(212, sharex=ax1, sharey=ax1)
# vlt.plot(viscid.magnitude(viscid.fc2cc(f['b_fc'])['y=0f']), **pargs)
# vlt.show()
basename = './tmediumR.3d.{0:06d}'.format(int(grid.time))
viscid.save_fields(basename + '.h5', [b_cc, b_fc, e_cc, e_ec, pp])
f2 = viscid.load_file(basename + ".xdmf")
pargs = dict(logscale=True, earth=True)
vlt.clf()
ax1 = vlt.subplot(211)
vlt.plot(f2['pp']['y=0f'], style='contour', levels=5, colorbar=None,
colors='k', **pargs)
vlt.plot(viscid.magnitude(f2['b_cc']['y=0f']), **pargs)
vlt.subplot(212, sharex=ax1, sharey=ax1)
vlt.plot(viscid.magnitude(viscid.fc2cc(f2['b_fc'])['y=0f']), **pargs)
vlt.show()
os.remove(basename + '.h5')
os.remove(basename + '.xdmf')
return 0
def compare_vectors(orig_fld, cmp_fld, catol=1e-8, rtol=2e-6,
trim_slc='x=2:-2, y=2:-2, z=2:-2', make_plots=False):
# mag_shape = list(orig_fld.sshape) + [1]
mag = viscid.magnitude(orig_fld) # .data.reshape(mag_shape)
reldiff = (cmp_fld - orig_fld) / mag
reldiff = reldiff[trim_slc]
reldiff.name = cmp_fld.name + " - " + orig_fld.name
reldiff.pretty_name = cmp_fld.pretty_name + " - " + orig_fld.pretty_name
comp_beyond_limit = [False] * 3
for i, d in enumerate('xyz'):
abs_max_rel_diff = np.nanmax(np.abs(reldiff[d]))
max_crd_diff = np.max(orig_fld.get_crd(d) - cmp_fld.get_crd(d))
print("{0}{1}, max absolute relative diff: {2:.3e} ({1} crds: {3:.1e})"
"".format(cmp_fld.name, d, abs_max_rel_diff, max_crd_diff))
if abs_max_rel_diff > rtol or abs(max_crd_diff) > catol:
comp_beyond_limit[i] = True
# plot differences?
if make_plots:
plt.clf()
ax1 = plt.subplot(311)
vlt.plot(orig_fld[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(cmp_fld[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff[d]['y=0j'], symmetric=True, earth=True)
vlt.show()
def run_test_2d(f, main__file__, show=False):
mpl.clf()
slc = "x=-20f:12f, y=0f"
plot_kwargs = dict(title=True, earth=True)
mpl.subplot(141)
mpl.plot(f['pp'], slc, logscale=True, **plot_kwargs)
mpl.plot(np.abs(f['psi']), style='contour', logscale=True, levels=30,
linewidths=0.8, colors='grey', linestyles='solid', cbar=None,
x=(-20, 12))
mpl.subplot(142)
mpl.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
mpl.plot2d_quiver(f['v'][slc], step=5, color='y', pivot='mid', width=0.03,
scale=600)
mpl.subplot(143)
mpl.plot(f['jy'], slc, clim=[-0.005, 0.005], **plot_kwargs)
mpl.streamplot(f['v'][slc], linewidth=0.3)
mpl.subplot(144)
mpl.plot(f['jy'], "x=7f:12f, y=0f, z=0f")
mpl.plt.suptitle("2D File")
mpl.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
mpl.plt.gcf().set_size_inches(10, 4)
mpl.savefig(next_plot_fname(main__file__))
if show:
mpl.show()
def run_mag_test(fld, show=False):
vx, vy, vz = fld.component_views() #pylint: disable=W0612
vx, vy, vz = fld.component_fields()
t0 = time()
mag_ne = viscid.magnitude(fld, preferred="numexpr", only=True)
t1 = time()
logger.info("numexpr mag runtime: %g", t1 - t0)
t0 = time()
planes = ["z=0", "y=0"]
nrows = 4
ncols = len(planes)
ax = plt.subplot2grid((nrows, ncols), (0, 0))
ax.axis("equal")
for ind, p in enumerate(planes):
plt.subplot2grid((nrows, ncols), (0, ind), sharex=ax, sharey=ax)
mpl.plot(vx, p, show=False)
plt.subplot2grid((nrows, ncols), (1, ind), sharex=ax, sharey=ax)
mpl.plot(vy, p, show=False)
plt.subplot2grid((nrows, ncols), (2, ind), sharex=ax, sharey=ax)
mpl.plot(vz, p, show=False)
plt.subplot2grid((nrows, ncols), (3, ind), sharex=ax, sharey=ax)
mpl.plot(mag_ne, p, show=False)
if show:
mpl.mplshow()
def run_test_2d(f, main__file__, show=False):
vlt.clf()
slc = "x=-20j:12j, y=0j"
plot_kwargs = dict(title=True, earth=True)
vlt.subplot(141)
vlt.plot(f['pp'], slc, logscale=True, **plot_kwargs)
vlt.plot(np.abs(f['psi']), style='contour', logscale=True, levels=30,
linewidths=0.8, colors='grey', linestyles='solid', colorbar=None,
x=(-20, 12))
vlt.subplot(142)
vlt.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
vlt.plot2d_quiver(f['v'][slc], step=5, color='y', pivot='mid', width=0.03,
scale=600)
vlt.subplot(143)
vlt.plot(f['jy'], slc, clim=[-0.005, 0.005], **plot_kwargs)
vlt.streamplot(f['v'][slc], linewidth=0.3)
vlt.subplot(144)
vlt.plot(f['jy'], "x=7j:12j, y=0j, z=0j")
plt.suptitle("2D File")
vlt.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
plt.gcf().set_size_inches(10, 4)
vlt.savefig(next_plot_fname(main__file__))
if show:
vlt.show()
def run_mag_test(fld, title="", show=False):
vx, vy, vz = fld.component_views() # pylint: disable=W0612
vx, vy, vz = fld.component_fields()
try:
t0 = time()
mag_ne = viscid.magnitude(fld, preferred="numexpr", only=False)
t1 = time()
logger.info("numexpr mag runtime: %g", t1 - t0)
except viscid.verror.BackendNotFound:
xfail("Numexpr is not installed")
planes = ["z=0", "y=0"]
nrows = 4
ncols = len(planes)
_, axes = plt.subplots(nrows, ncols, sharex=True, sharey=True, squeeze=False)
for ind, p in enumerate(planes):
vlt.plot(vx, p, ax=axes[0, ind], show=False)
vlt.plot(vy, p, ax=axes[1, ind], show=False)
vlt.plot(vz, p, ax=axes[2, ind], show=False)
vlt.plot(mag_ne, p, ax=axes[3, ind], show=False)
plt.suptitle(title)
vlt.auto_adjust_subplots(subplot_params=dict(top=0.9, right=0.9))
plt.gcf().set_size_inches(6, 7)
plt.savefig(next_plot_fname(__file__))
if show:
vlt.mplshow()
def compare_vectors(cc_fld, ecfc_fld, to_cc_fn, catol=1e-8, rtol=2.2e-6,
trim_slc=':', bnd=True, make_plots=False):
trimmed = cc_fld[trim_slc]
cc = to_cc_fn(ecfc_fld, bnd=bnd)
reldiff = (cc - trimmed) / viscid.magnitude(trimmed)
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = cc.name + " - " + trimmed.name
reldiff.pretty_name = cc.pretty_name + " - " + trimmed.pretty_name
comp_beyond_limit = [False] * 3
for i, d in enumerate('xyz'):
abs_max_rel_diff = np.nanmax(np.abs(reldiff[d]))
# trim first and last when diffing crds since they're extrapolated
# in the ecfc field, so we already know they won't match up do dx
max_crd_diff = np.max((trimmed.get_crd(d) - cc.get_crd(d))[1:-1])
print("{0}{1}, max absolute relative diff: {2:.3e} ({1} crds: {3:.1e})"
"".format(cc_fld.name, d, abs_max_rel_diff, max_crd_diff))
if abs_max_rel_diff > rtol or abs(max_crd_diff) > catol:
comp_beyond_limit[i] = True
# plot differences?
if make_plots:
ax1 = plt.subplot(311)
vlt.plot(cc_fld[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(cc[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff[d]['y=0j'], symmetric=True, earth=True)
vlt.show()
if any(comp_beyond_limit):
raise RuntimeError("Tolerance exceeded on ->CC accuracy")
def run_mag_test(fld, title="", show=False):
vx, vy, vz = fld.component_views() # pylint: disable=W0612
vx, vy, vz = fld.component_fields()
try:
t0 = time()
mag_ne = viscid.magnitude(fld, preferred="numexpr", only=False)
t1 = time()
logger.info("numexpr mag runtime: %g", t1 - t0)
except viscid.verror.BackendNotFound:
xfail("Numexpr is not installed")
planes = ["z=0", "y=0"]
nrows = 4
ncols = len(planes)
ax = plt.subplot2grid((nrows, ncols), (0, 0))
ax.axis("equal")
for ind, p in enumerate(planes):
plt.subplot2grid((nrows, ncols), (0, ind), sharex=ax, sharey=ax)
mpl.plot(vx, p, show=False)
plt.subplot2grid((nrows, ncols), (1, ind), sharex=ax, sharey=ax)
mpl.plot(vy, p, show=False)
plt.subplot2grid((nrows, ncols), (2, ind), sharex=ax, sharey=ax)
mpl.plot(vz, p, show=False)
plt.subplot2grid((nrows, ncols), (3, ind), sharex=ax, sharey=ax)
mpl.plot(mag_ne, p, show=False)
mpl.plt.suptitle(title)
mpl.auto_adjust_subplots(subplot_params=dict(top=0.9))
mpl.plt.gcf().set_size_inches(6, 7)
mpl.plt.savefig(next_plot_fname(__file__))
if show:
mpl.mplshow()
def default_fluid_callback(i,
t,
seeds=None,
v_field=None,
anc_fields=None,
grid0=None,
grid1=None,
streamlines=None,
series_fname=None,
show=False,
**kwargs):
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
_, ax0 = plt.subplots(1, 1)
vlt.plot(viscid.magnitude(v_field).atmost_nd(2), ax=ax0)
vlt.scatter_2d(seeds, ax=ax0)
vlt.streamplot(v_field.atmost_nd(2))
vlt.plot_lines2d(streamlines, ax=ax0)
plt.title('{0:8.3f}'.format(t))
if series_fname:
plt.savefig('{0}_{1:06d}.png'.format(series_fname, i))
if show:
vlt.show()
else:
plt.close()
def run_test_3d(f, main__file__, show=False):
vlt.clf()
slc = "x=-20f:12f, y=0f"
plot_kwargs = dict(title=True, earth=True)
vlt.subplot(141)
vlt.plot(f['pp'], slc, logscale=True, **plot_kwargs)
vlt.subplot(142)
vlt.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
vlt.plot2d_quiver(f['v'][slc],
step=5,
color='y',
pivot='mid',
width=0.03,
scale=600)
vlt.subplot(143)
vlt.plot(f['jy'], slc, clim=(-0.005, 0.005), **plot_kwargs)
vlt.streamplot(f['v'][slc], linewidth=0.3)
vlt.subplot(144)
vlt.plot(f['jy'], "x=7f:12f, y=0f, z=0f")
plt.suptitle("3D File")
vlt.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
plt.gcf().set_size_inches(10, 4)
vlt.savefig(next_plot_fname(main__file__))
if show:
vlt.show()
def compare_vectors(orig_fld,
cmp_fld,
catol=1e-8,
rtol=2e-6,
trim_slc='x=2:-2, y=2:-2, z=2:-2',
make_plots=False):
# mag_shape = list(orig_fld.sshape) + [1]
mag = viscid.magnitude(orig_fld) # .data.reshape(mag_shape)
reldiff = (cmp_fld - orig_fld) / mag
reldiff = reldiff[trim_slc]
reldiff.name = cmp_fld.name + " - " + orig_fld.name
reldiff.pretty_name = cmp_fld.pretty_name + " - " + orig_fld.pretty_name
comp_beyond_limit = [False] * 3
for i, d in enumerate('xyz'):
abs_max_rel_diff = np.nanmax(np.abs(reldiff[d]))
max_crd_diff = np.max(orig_fld.get_crd(d) - cmp_fld.get_crd(d))
print("{0}{1}, max absolute relative diff: {2:.3e} ({1} crds: {3:.1e})"
"".format(cmp_fld.name, d, abs_max_rel_diff, max_crd_diff))
if abs_max_rel_diff > rtol or abs(max_crd_diff) > catol:
comp_beyond_limit[i] = True
# plot differences?
if make_plots:
plt.clf()
ax1 = plt.subplot(311)
vlt.plot(orig_fld[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(cmp_fld[d]['y=0j'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff[d]['y=0j'], symmetric=True, earth=True)
vlt.show()
def compare_vectors(cc_fld, ecfc_fld, to_cc_fn, catol=1e-8, rtol=2.2e-6,
trim_slc='x=1:-1, y=1:-1, z=1:-1', make_plots=False):
trimmed = cc_fld[trim_slc]
cc = to_cc_fn(ecfc_fld)
reldiff = (cc - trimmed) / viscid.magnitude(trimmed)
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = cc.name + " - " + trimmed.name
reldiff.pretty_name = cc.pretty_name + " - " + trimmed.pretty_name
comp_beyond_limit = [False] * 3
for i, d in enumerate('xyz'):
abs_max_rel_diff = np.nanmax(np.abs(reldiff[d]))
max_crd_diff = np.max(trimmed.get_crd(d) - cc.get_crd(d))
print("{0}{1}, max absolute relative diff: {2:.3e} ({1} crds: {3:.1e})"
"".format(cc_fld.name, d, abs_max_rel_diff, max_crd_diff))
if abs_max_rel_diff > rtol or abs(max_crd_diff) > catol:
comp_beyond_limit[i] = True
# plot differences?
if make_plots:
ax1 = mpl.plt.subplot(311)
mpl.plot(cc_fld[d]['y=0f'], symmetric=True, earth=True)
mpl.plt.subplot(312, sharex=ax1, sharey=ax1)
mpl.plot(cc[d]['y=0f'], symmetric=True, earth=True)
mpl.plt.subplot(313, sharex=ax1, sharey=ax1)
mpl.plot(reldiff[d]['y=0f'], symmetric=True, earth=True)
mpl.show()
if any(comp_beyond_limit):
raise RuntimeError("Tolerance exceeded on ->CC accuracy")
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
dtype = "float32"
x = np.array(np.linspace(-1, 1, 2), dtype=dtype)
y = np.array(np.linspace(-2, 2, 30), dtype=dtype)
z = np.array(np.linspace(-5, 5, 90), dtype=dtype)
v = viscid.empty([x, y, z], nr_comps=3, name="V", center="cell", layout="interlaced")
X, Y, Z = v.get_crds_cc(shaped=True)
v["x"] = 0.5 * X ** 2 + Y + 0.0 * Z
v["y"] = 0.0 * X + 0.5 * Y ** 2 + 0.0 * Z
v["z"] = 0.0 * X + 0.0 * Y + 0.5 * Z ** 2
mag = viscid.magnitude(v)
mag2 = np.sqrt(np.sum(v * v, axis=v.nr_comp))
another = np.transpose(mag)
plt.subplot(151)
mpl.plot(v["x"])
plt.subplot(152)
mpl.plot(v["y"])
plt.subplot(153)
mpl.plot(mag)
plt.subplot(154)
mpl.plot(mag2)
plt.subplot(155)
mpl.plot(another)
if args.show:
plt.show()
return 0
def run_test(_fld, _seeds, plot2d=True, plot3d=True, title='', show=False,
**kwargs):
lines, topo = viscid.calc_streamlines(_fld, _seeds, **kwargs)
topo_color = viscid.topology2color(topo)
# downsample lines for plotting
lines = [line[:, ::8] for line in lines]
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
vlt.plot2d_lines(lines, scalars=topo_color, symdir='y', marker='^')
if title:
plt.title(title)
plt.savefig(next_plot_fname(__file__, series='2d'))
if show:
plt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import vlab
try:
fig = _global_ns['figure']
vlab.clf()
except KeyError:
fig = vlab.figure(size=[1200, 800], offscreen=not show,
bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
_global_ns['figure'] = fig
fld_mag = np.log(viscid.magnitude(_fld))
try:
# note: mayavi.mlab.mesh can't take color tuples as scalars
# so one can't use topo_color on a mesh surface. This
# is a limitation of mayavi. To actually plot a specific
# set of colors on a mesh, one must use a texture
mesh = vlab.mesh_from_seeds(_seeds, scalars=topo, opacity=0.6)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
vlab.plot_lines(lines, scalars=fld_mag, tube_radius=0.01,
cmap='viridis')
if title:
vlab.title(title)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show()
except ImportError:
pass
def run_test(_fld, _seeds, plot2d=True, plot3d=True, title="", show=False, **kwargs):
lines, topo = viscid.calc_streamlines(_fld, _seeds, **kwargs)
topo_color = viscid.topology2color(topo)
# downsample lines for plotting
lines = [line[:, ::8] for line in lines]
try:
if not plot2d:
raise ImportError
from viscid.plot import mpl
mpl.plt.clf()
mpl.plot2d_lines(lines, scalars=topo_color, symdir="y", marker="^")
if title:
mpl.plt.title(title)
mpl.plt.savefig(next_plot_fname(__file__, series="2d"))
if show:
mpl.plt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import mvi
try:
fig = _global_ns["figure"]
mvi.clf()
except KeyError:
fig = mvi.figure(size=[1200, 800], offscreen=not show)
_global_ns["figure"] = fig
fld_mag = np.log(viscid.magnitude(_fld))
try:
# note: mayavi.mlab.mesh can't take color tuples as scalars
# so one can't use topo_color on a mesh surface. This
# is a limitation of mayavi. To actually plot a specific
# set of colors on a mesh, one must use a texture
mesh = mvi.mesh_from_seeds(_seeds, scalars=topo, opacity=0.6)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
mvi.plot_lines(lines, scalars=fld_mag, tube_radius=0.01, cmap="viridis")
if title:
mvi.title(title)
mvi.savefig(next_plot_fname(__file__, series="3d"))
if show:
mvi.show()
except ImportError:
pass
def run_test(_fld, _seeds, plot2d=True, plot3d=True, title='', show=False,
**kwargs):
lines, topo = viscid.calc_streamlines(_fld, _seeds, **kwargs)
topo_color = viscid.topology2color(topo)
# downsample lines for plotting
lines = [line[:, ::8] for line in lines]
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
vlt.plot2d_lines(lines, scalars=topo_color, symdir='y', marker='^')
if title:
plt.title(title)
plt.savefig(next_plot_fname(__file__, series='2d'))
if show:
plt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
vlab, _ = get_mvi_fig()
fld_mag = np.log(viscid.magnitude(_fld))
try:
# note: mayavi.mlab.mesh can't take color tuples as scalars
# so one can't use topo_color on a mesh surface. This
# is a limitation of mayavi. To actually plot a specific
# set of colors on a mesh, one must use a texture
mesh = vlab.mesh_from_seeds(_seeds, scalars=topo, opacity=0.6)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
vlab.plot_lines(lines, scalars=fld_mag, tube_radius=0.01,
cmap='viridis')
if title:
vlab.title(title)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show()
except ImportError:
pass
def run_test(_fld, _seeds, plot2d=True, plot3d=True, show=False, **kwargs):
lines, topo = viscid.calc_streamlines(_fld, _seeds, **kwargs)
topo_fld = _seeds.wrap_field(topo)
topo_color = viscid.topology2color(topo)
# downsample lines for plotting
lines = [line[:, ::8] for line in lines]
try:
if not plot2d:
raise ImportError
from viscid.plot import mpl
mpl.plt.clf()
mpl.plot2d_lines(lines, scalars=topo_color, symdir="y", marker="^")
if show:
mpl.plt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import mvi
mvi.clf()
fld_mag = np.log(viscid.magnitude(_fld))
try:
# note: mayavi.mlab.mesh can't take color tuples as scalars
# so one can't use topo_color on a mesh surface. This
# is a limitation of mayavi. To actually plot a specific
# set of colors on a mesh, one must use a texture
vertices, scalars = _seeds.wrap_mesh(topo_fld.data)
mesh = mvi.mlab.mesh(vertices[0], vertices[1], vertices[2], scalars=scalars, opacity=0.5)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
mvi.plot_lines(lines, scalars=fld_mag, tube_radius=0.005)
if show:
mvi.show()
except ImportError:
pass
def default_fluid_callback(i, t, seeds=None, v_field=None, anc_fields=None,
grid0=None, grid1=None, streamlines=None,
series_fname=None, show=False, **kwargs):
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
_, ax0 = plt.subplots(1, 1)
vlt.plot(viscid.magnitude(v_field).atmost_nd(2), ax=ax0)
vlt.scatter_2d(seeds, ax=ax0)
vlt.streamplot(v_field.atmost_nd(2))
vlt.plot_lines2d(streamlines, ax=ax0)
plt.title('{0:8.3f}'.format(t))
if series_fname:
plt.savefig('{0}_{1:06d}.png'.format(series_fname, i))
if show:
vlt.show()
else:
plt.close()
def compare_vectors(cc_fld,
ecfc_fld,
to_cc_fn,
catol=1e-8,
rtol=2.2e-6,
trim_slc=':',
bnd=True,
make_plots=False):
trimmed = cc_fld[trim_slc]
cc = to_cc_fn(ecfc_fld, bnd=bnd)
reldiff = (cc - trimmed) / viscid.magnitude(trimmed)
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = cc.name + " - " + trimmed.name
reldiff.pretty_name = cc.pretty_name + " - " + trimmed.pretty_name
comp_beyond_limit = [False] * 3
for i, d in enumerate('xyz'):
abs_max_rel_diff = np.nanmax(np.abs(reldiff[d]))
# trim first and last when diffing crds since they're extrapolated
# in the ecfc field, so we already know they won't match up do dx
max_crd_diff = np.max((trimmed.get_crd(d) - cc.get_crd(d))[1:-1])
print("{0}{1}, max absolute relative diff: {2:.3e} ({1} crds: {3:.1e})"
"".format(cc_fld.name, d, abs_max_rel_diff, max_crd_diff))
if abs_max_rel_diff > rtol or abs(max_crd_diff) > catol:
comp_beyond_limit[i] = True
# plot differences?
if make_plots:
ax1 = plt.subplot(311)
vlt.plot(cc_fld[d]['y=0f'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(cc[d]['y=0f'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff[d]['y=0f'], symmetric=True, earth=True)
vlt.show()
if any(comp_beyond_limit):
raise RuntimeError("Tolerance exceeded on ->CC accuracy")
def run_test_3d(f, main__file__, show=False):
mpl.clf()
slc = "x=-20f:12f, y=0f"
plot_kwargs = dict(title=True, earth=True)
mpl.subplot(141)
mpl.plot(f['pp'], slc, logscale=True, **plot_kwargs)
mpl.subplot(142)
mpl.plot(viscid.magnitude(f['bcc']), slc, logscale=True, **plot_kwargs)
mpl.plot2d_quiver(f['v'][slc], step=5, color='y', pivot='mid', width=0.03,
scale=600)
mpl.subplot(143)
mpl.plot(f['jy'], slc, clim=(-0.005, 0.005), **plot_kwargs)
mpl.streamplot(f['v'][slc], linewidth=0.3)
mpl.subplot(144)
mpl.plot(f['jy'], "x=7f:12f, y=0f, z=0f")
mpl.plt.suptitle("3D File")
mpl.auto_adjust_subplots(subplot_params=dict(top=0.9, wspace=1.3))
mpl.plt.gcf().set_size_inches(10, 4)
mpl.savefig(next_plot_fname(main__file__))
if show:
mpl.show()
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
dtype = 'float32'
########################################################################
# hard core test transpose (since this is used for mapfield transforms)
x = np.array(np.linspace( 1, -1, 9), dtype=dtype)
y = np.array(np.linspace(-1, 1, 9), dtype=dtype)
z = np.array(np.linspace(-1, 1, 9), dtype=dtype)
vI1 = viscid.empty([x, y, z], nr_comps=3, name='V', center='cell',
layout='interlaced')
vI2 = viscid.empty([z, y, x], nr_comps=3, name='V', center='cell',
layout='interlaced', crd_names='zyx')
vF1 = viscid.empty([x, y, z], nr_comps=3, name='V', center='cell',
layout='flat')
vF2 = viscid.empty([z, y, x], nr_comps=3, name='V', center='cell',
layout='flat', crd_names='zyx')
X1, Y1, Z1 = vI1.get_crds_cc(shaped=True)
X2, Y2, Z2 = vI2.get_crds_cc(shaped=True)
for v in (vI1, vF1):
v['x'] = (0.5 * X1) + (0.0 * Y1) + (0.0 * Z1)
v['y'] = (0.0 * X1) + (0.5 * Y1) + (0.5 * Z1)
v['z'] = (0.0 * X1) + (0.5 * Y1) + (0.5 * Z1)
for v in (vI2, vF2):
v['z'] = (0.5 * X2) + (0.5 * Y2) + (0.0 * Z2)
v['y'] = (0.5 * X2) + (0.5 * Y2) + (0.0 * Z2)
v['x'] = (0.0 * X2) + (0.0 * Y2) + (0.5 * Z2)
assert_different(vI1, vI2)
# test some straight up transposes of both interlaced and flat fields
assert_similar(vI1.spatial_transpose(), vI2)
assert_similar(vI1.ST, vI2)
assert_similar(vF1.spatial_transpose(), vF2)
assert_similar(vI1.transpose(), vF2)
assert_similar(vI1.T, vF2)
assert_different(vI1.transpose(), vI2)
assert_similar(vF1.transpose(), vI2)
assert_different(vF1.transpose(), vF2)
assert_similar(np.transpose(vI1), vF2)
assert_similar(np.transpose(vF1), vI2)
# now specify specific axes using all 3 interfaces
assert_similar(vI1.spatial_transpose('x', 'z', 'y'), vI1)
assert_similar(np.transpose(vI1, axes=[0, 2, 1, 3]), vI1)
assert_similar(vI1.transpose(0, 2, 1, 3), vI1)
assert_similar(vF1.spatial_transpose('x', 'z', 'y'), vF1)
assert_similar(np.transpose(vF1, axes=(0, 1, 3, 2)), vF1)
assert_similar(vF1.transpose(0, 1, 3, 2), vF1)
# now test swapaxes since that uses
assert_similar(vI1.swapaxes(1, 2), vI1)
assert_similar(np.swapaxes(vI1, 1, 2), vI1)
assert_similar(vI1.swap_crd_axes('y', 'z'), vI1)
##############################
# test some other mathy stuff
x = np.array(np.linspace(-1, 1, 2), dtype=dtype)
y = np.array(np.linspace(-2, 2, 30), dtype=dtype)
z = np.array(np.linspace(-5, 5, 90), dtype=dtype)
v = viscid.empty([x, y, z], nr_comps=3, name='V', center='cell',
layout='interlaced')
X, Y, Z = v.get_crds_cc(shaped=True)
v['x'] = (0.5 * X**2) + ( Y ) + (0.0 * Z )
v['y'] = (0.0 * X ) + (0.5 * Y**2) + (0.0 * Z )
v['z'] = (0.0 * X ) + (0.0 * Y ) + (0.5 * Z**2)
mag = viscid.magnitude(v)
mag2 = np.sqrt(np.sum(v * v, axis=v.nr_comp))
another = np.transpose(mag)
plt.subplot(151)
vlt.plot(v['x'])
plt.subplot(152)
vlt.plot(v['y'])
plt.subplot(153)
vlt.plot(mag)
plt.subplot(154)
vlt.plot(mag2)
plt.subplot(155)
vlt.plot(another)
plt.savefig(next_plot_fname(__file__))
if args.show:
plt.show()
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
dtype = 'float32'
########################################################################
# hard core test transpose (since this is used for mapfield transforms)
x = np.array(np.linspace(1, -1, 9), dtype=dtype)
y = np.array(np.linspace(-1, 1, 9), dtype=dtype)
z = np.array(np.linspace(-1, 1, 9), dtype=dtype)
vI1 = viscid.empty([x, y, z],
nr_comps=3,
name='V',
center='cell',
layout='interlaced')
vI2 = viscid.empty([z, y, x],
nr_comps=3,
name='V',
center='cell',
layout='interlaced',
crd_names='zyx')
vF1 = viscid.empty([x, y, z],
nr_comps=3,
name='V',
center='cell',
layout='flat')
vF2 = viscid.empty([z, y, x],
nr_comps=3,
name='V',
center='cell',
layout='flat',
crd_names='zyx')
X1, Y1, Z1 = vI1.get_crds_cc(shaped=True)
X2, Y2, Z2 = vI2.get_crds_cc(shaped=True)
for v in (vI1, vF1):
v['x'] = (0.5 * X1) + (0.0 * Y1) + (0.0 * Z1)
v['y'] = (0.0 * X1) + (0.5 * Y1) + (0.5 * Z1)
v['z'] = (0.0 * X1) + (0.5 * Y1) + (0.5 * Z1)
for v in (vI2, vF2):
v['z'] = (0.5 * X2) + (0.5 * Y2) + (0.0 * Z2)
v['y'] = (0.5 * X2) + (0.5 * Y2) + (0.0 * Z2)
v['x'] = (0.0 * X2) + (0.0 * Y2) + (0.5 * Z2)
assert_different(vI1, vI2)
# test some straight up transposes of both interlaced and flat fields
assert_similar(vI1.spatial_transpose(), vI2)
assert_similar(vI1.ST, vI2)
assert_similar(vF1.spatial_transpose(), vF2)
assert_similar(vI1.transpose(), vF2)
assert_similar(vI1.T, vF2)
assert_different(vI1.transpose(), vI2)
assert_similar(vF1.transpose(), vI2)
assert_different(vF1.transpose(), vF2)
assert_similar(np.transpose(vI1), vF2)
assert_similar(np.transpose(vF1), vI2)
# now specify specific axes using all 3 interfaces
assert_similar(vI1.spatial_transpose('x', 'z', 'y'), vI1)
assert_similar(np.transpose(vI1, axes=[0, 2, 1, 3]), vI1)
assert_similar(vI1.transpose(0, 2, 1, 3), vI1)
assert_similar(vF1.spatial_transpose('x', 'z', 'y'), vF1)
assert_similar(np.transpose(vF1, axes=(0, 1, 3, 2)), vF1)
assert_similar(vF1.transpose(0, 1, 3, 2), vF1)
# now test swapaxes since that uses
assert_similar(vI1.swapaxes(1, 2), vI1)
assert_similar(np.swapaxes(vI1, 1, 2), vI1)
assert_similar(vI1.swap_crd_axes('y', 'z'), vI1)
##############################
# test some other mathy stuff
x = np.array(np.linspace(-1, 1, 2), dtype=dtype)
y = np.array(np.linspace(-2, 2, 30), dtype=dtype)
z = np.array(np.linspace(-5, 5, 90), dtype=dtype)
v = viscid.empty([x, y, z],
nr_comps=3,
name='V',
center='cell',
layout='interlaced')
X, Y, Z = v.get_crds_cc(shaped=True)
v['x'] = (0.5 * X**2) + (Y) + (0.0 * Z)
v['y'] = (0.0 * X) + (0.5 * Y**2) + (0.0 * Z)
v['z'] = (0.0 * X) + (0.0 * Y) + (0.5 * Z**2)
mag = viscid.magnitude(v)
mag2 = np.sqrt(np.sum(v * v, axis=v.nr_comp))
another = np.transpose(mag)
plt.subplot(151)
vlt.plot(v['x'])
plt.subplot(152)
vlt.plot(v['y'])
plt.subplot(153)
vlt.plot(mag)
plt.subplot(154)
vlt.plot(mag2)
plt.subplot(155)
vlt.plot(another)
plt.savefig(next_plot_fname(__file__))
if args.show:
plt.show()
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
viscid.logger.setLevel(viscid.logging.DEBUG)
args.show = False
cotr = viscid.Cotr(dip_tilt=20.0, dip_gsm=15.0) # pylint: disable=not-callable
b = viscid.make_dipole(m=cotr.get_dipole_moment(), n=(32, 32, 32))
seeds = viscid.Circle(n=5, r=1.5, pole=[0, 0, 1])
lines, topo = viscid.calc_streamlines(b, seeds, ibound=1.4, method='rk45')
for i in range(2):
# make sure this works for lines with 0, 1, 2, 3 vertices
if i == 1:
lines[1] = lines[2][:, :0]
lines[2] = lines[2][:, :1]
lines[3] = lines[3][:, :2]
lines[4] = lines[4][:, :3]
viscid.logger.debug('---')
viscid.logger.debug('{0}'.format(len(lines)))
for line in lines:
viscid.logger.debug('line shape: {0}'.format(line.shape))
viscid.logger.debug('---')
do_test(lines,
scalars=None,
txt='given None',
show=args.show)
do_test(lines,
scalars='#ff0000',
txt='given a single 24bit rgb hex color',
show=args.show)
do_test(lines,
scalars='#ff000066',
txt='given a single 32bit rgba hex color',
show=args.show)
do_test(lines,
scalars='#f00',
txt='given a single 12bit rgb hex color',
show=args.show)
do_test(lines,
scalars='#f006',
txt='given a single 16bit rgba hex color',
show=args.show)
do_test(lines,
scalars=['#ff0000', '#cc0000', '#aa0000', '#880000', '#660000'],
txt='given a list of Nlines 24bit rgb hex colors',
show=args.show)
do_test(lines,
scalars=['#ff000066', '#cc000066', '#aa000066', '#88000066',
'#66000066'],
txt='given a list of Nlines 32bit rgba hex colors',
show=args.show)
do_test(lines,
scalars=['#f00', '#c00', '#a00', '#800', '#600'],
txt='given a list of Nlines 12bit rgb hex colors',
show=args.show)
do_test(lines,
scalars=['#f00a', '#c009', '#a008', '#8007', '#6006'],
txt='given a list of Nlines 16bit rgba hex colors',
show=args.show)
do_test(lines,
scalars=[0.8, 0.0, 0.2],
txt='given a single rgb [0..1] color',
show=args.show)
do_test(lines,
scalars=[0.8, 0.0, 0.2, 0.8],
txt='given a single rgba [0..1] color',
show=args.show)
do_test(lines,
scalars=[(0.8, 0.0, 0.2), (0.7, 0.0, 0.3), (0.6, 0.0, 0.4),
(0.5, 0.0, 0.5), (0.4, 0.0, 0.6)],
txt='given a list of Nlines rgb [0..1] tuples',
show=args.show)
do_test(lines,
scalars=[(0.8, 0.0, 0.2, 1.0), (0.7, 0.0, 0.3, 0.9),
(0.6, 0.0, 0.4, 0.8), (0.5, 0.0, 0.5, 0.7),
(0.4, 0.0, 0.6, 0.6)],
txt='given a list of Nlines rgba [0..1] tuples',
show=args.show)
do_test(lines,
scalars=[250, 0, 250],
txt='given a single rgb [0..255] color',
show=args.show)
do_test(lines,
scalars=[250, 0, 250, 190],
txt='given a single rgba [0..255] color',
show=args.show)
do_test(lines,
scalars=[(204, 0, 51), (179, 0, 77), (153, 0, 102),
(127, 0, 127), (0.4, 0, 102)],
txt='given a list of Nlines rgb [0..255] tuples',
show=args.show)
do_test(lines,
scalars=[(204, 0, 51, 255), (179, 0, 77, 230),
(153, 0, 102, 204), (127, 0, 127, 179),
(102, 0, 102, 153)],
txt='given a list of Nlines rgba [0..255] tuples',
show=args.show)
do_test(lines,
scalars=['#ff000088', 'blue', 'lavenderblush', 'c', '#4f4'],
txt='given a mix of color hex/html color names',
show=args.show)
do_test(lines,
scalars=topo,
txt='scalars == topo value',
show=args.show)
do_test(lines,
scalars=viscid.topology2color(topo),
txt='scalars == topo2color value',
show=args.show)
do_test(lines,
scalars=np.log(viscid.magnitude(b)),
txt='given bmag',
show=args.show)
# prevent weird xorg bad-instructions on tear down
if 'figure' in _global_ns and _global_ns['figure'] is not None:
from viscid.plot import vlab
vlab.mlab.close(_global_ns['figure'])
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
viscid.logger.setLevel(viscid.logging.DEBUG)
args.show = False
cotr = viscid.Cotr(dip_tilt=20.0, dip_gsm=15.0) # pylint: disable=not-callable
b = viscid.make_dipole(m=cotr.get_dipole_moment(), n=(32, 32, 32))
seeds = viscid.Circle(n=5, r=1.5, pole=[0, 0, 1])
lines, topo = viscid.calc_streamlines(b, seeds, ibound=1.4, method='rk45')
for i in range(2):
# make sure this works for lines with 0, 1, 2, 3 vertices
if i == 1:
lines[1] = lines[2][:, :0]
lines[2] = lines[2][:, :1]
lines[3] = lines[3][:, :2]
lines[4] = lines[4][:, :3]
viscid.logger.debug('---')
viscid.logger.debug('{0}'.format(len(lines)))
for line in lines:
viscid.logger.debug('line shape: {0}'.format(line.shape))
viscid.logger.debug('---')
do_test(lines,
scalars=None,
txt='given None',
show=args.show)
do_test(lines,
scalars='#ff0000',
txt='given a single 24bit rgb hex color',
show=args.show)
do_test(lines,
scalars='#ff000066',
txt='given a single 32bit rgba hex color',
show=args.show)
do_test(lines,
scalars='#f00',
txt='given a single 12bit rgb hex color',
show=args.show)
do_test(lines,
scalars='#f006',
txt='given a single 16bit rgba hex color',
show=args.show)
do_test(lines,
scalars=['#ff0000', '#cc0000', '#aa0000', '#880000', '#660000'],
txt='given a list of Nlines 24bit rgb hex colors',
show=args.show)
do_test(lines,
scalars=['#ff000066', '#cc000066', '#aa000066', '#88000066',
'#66000066'],
txt='given a list of Nlines 32bit rgba hex colors',
show=args.show)
do_test(lines,
scalars=['#f00', '#c00', '#a00', '#800', '#600'],
txt='given a list of Nlines 12bit rgb hex colors',
show=args.show)
do_test(lines,
scalars=['#f00a', '#c009', '#a008', '#8007', '#6006'],
txt='given a list of Nlines 16bit rgba hex colors',
show=args.show)
do_test(lines,
scalars=[0.8, 0.0, 0.2],
txt='given a single rgb [0..1] color',
show=args.show)
do_test(lines,
scalars=[0.8, 0.0, 0.2, 0.8],
txt='given a single rgba [0..1] color',
show=args.show)
do_test(lines,
scalars=[(0.8, 0.0, 0.2), (0.7, 0.0, 0.3), (0.6, 0.0, 0.4),
(0.5, 0.0, 0.5), (0.4, 0.0, 0.6)],
txt='given a list of Nlines rgb [0..1] tuples',
show=args.show)
do_test(lines,
scalars=[(0.8, 0.0, 0.2, 1.0), (0.7, 0.0, 0.3, 0.9),
(0.6, 0.0, 0.4, 0.8), (0.5, 0.0, 0.5, 0.7),
(0.4, 0.0, 0.6, 0.6)],
txt='given a list of Nlines rgba [0..1] tuples',
show=args.show)
do_test(lines,
scalars=[250, 0, 250],
txt='given a single rgb [0..255] color',
show=args.show)
do_test(lines,
scalars=[250, 0, 250, 190],
txt='given a single rgba [0..255] color',
show=args.show)
do_test(lines,
scalars=[(204, 0, 51), (179, 0, 77), (153, 0, 102),
(127, 0, 127), (0.4, 0, 102)],
txt='given a list of Nlines rgb [0..255] tuples',
show=args.show)
do_test(lines,
scalars=[(204, 0, 51, 255), (179, 0, 77, 230),
(153, 0, 102, 204), (127, 0, 127, 179),
(102, 0, 102, 153)],
txt='given a list of Nlines rgba [0..255] tuples',
show=args.show)
do_test(lines,
scalars=['#ff000088', 'blue', 'lavenderblush', 'c', '#4f4'],
txt='given a mix of color hex/html color names',
show=args.show)
do_test(lines,
scalars=topo,
txt='scalars == topo value',
show=args.show)
do_test(lines,
scalars=viscid.topology2color(topo),
txt='scalars == topo2color value',
show=args.show)
do_test(lines,
scalars=np.log(viscid.magnitude(b)),
txt='given bmag',
show=args.show)
# prevent weird xorg bad-instructions on tear down
if 'figure' in _global_ns and _global_ns['figure'] is not None:
from viscid.plot import vlab
vlab.mlab.close(_global_ns['figure'])
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--prof", action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
b = viscid.make_dipole(l=(-5, -5, -5), h=(5, 5, 5), n=(255, 255, 127),
m=(0, 0, -1))
b2 = np.sum(b * b, axis=b.nr_comp)
if args.prof:
print("Without boundaries")
viscid.timeit(viscid.grad, b2, bnd=False, timeit_repeat=10,
timeit_print_stats=True)
print("With boundaries")
viscid.timeit(viscid.grad, b2, bnd=True, timeit_repeat=10,
timeit_print_stats=True)
grad_b2 = viscid.grad(b2)
grad_b2.pretty_name = r"$\nabla$ B$^2$"
conv = viscid.convective_deriv(b)
conv.pretty_name = r"(B $\cdot \nabla$) B"
_ = plt.figure(figsize=(9, 4.2))
ax1 = vlt.subplot(231)
vlt.plot(b2['z=0f'], logscale=True)
vlt.plot(b2['z=0f'], logscale=True, style='contour', levels=10, colors='grey')
# vlt.plot2d_quiver(viscid.normalize(b['z=0f']), step=16, pivot='mid')
ax2 = vlt.subplot(234)
vlt.plot(b2['y=0f'], logscale=True)
vlt.plot(b2['y=0f'], logscale=True, style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(b['y=0f'], preferred='numpy'),
step=16, pivot='mid')
vlt.subplot(232, sharex=ax1, sharey=ax1)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['z=0f']), logscale=True)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['z=0f']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(grad_b2['z=0f']), step=16, pivot='mid')
vlt.subplot(235, sharex=ax2, sharey=ax2)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['y=0f']), logscale=True)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['y=0f']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(grad_b2['y=0f']), step=16, pivot='mid')
vlt.subplot(233, sharex=ax1, sharey=ax1)
vlt.plot(viscid.magnitude(conv['z=0f']), logscale=True)
vlt.plot(viscid.magnitude(conv['z=0f']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(conv['z=0f']), step=16, pivot='mid')
vlt.subplot(236, sharex=ax2, sharey=ax2)
vlt.plot(viscid.magnitude(conv['y=0f']), logscale=True)
vlt.plot(viscid.magnitude(conv['y=0f']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(conv['y=0f']), step=16, pivot='mid')
vlt.auto_adjust_subplots()
plt.savefig(next_plot_fname(__file__))
if args.show:
vlt.show()
return 0
def main():
mhd_type = "C"
make_plots = 1
test_fc = 1
test_ec = 1
test_div = 1
test_interp = 1
test_streamline = 1
mhd_type = mhd_type.upper()
if mhd_type.startswith("C"):
if mhd_type in ("C", ):
f = viscid.load_file("$WORK/tmedium/*.3d.[-1].xdmf")
elif mhd_type in ("C2", "C3"):
f = viscid.load_file("$WORK/tmedium2/*.3d.[-1].xdmf")
else:
raise ValueError()
catol = 1e-8
rtol = 5e-6
elif mhd_type in ("F", "FORTRAN"):
f = viscid.load_file("$WORK/tmedium3/*.3df.[-1]")
catol = 1e-8
rtol = 7e-2
else:
raise ValueError()
ISLICE = slice(None)
# ISLICE = 'y=0f:0.15f'
# #################
# # test out fc2cc
if test_fc:
b = f['b'][ISLICE]
b1 = f['b1'][ISLICE]
compare_vectors(b,
b1,
viscid.fc2cc,
catol=catol,
rtol=rtol,
make_plots=make_plots)
#################
# test out ec2cc
if test_ec:
e_cc = f['e_cc'][ISLICE]
e_ec = f['e_ec'][ISLICE]
if mhd_type not in ("F", "FORTRAN"):
compare_vectors(e_cc,
e_ec,
viscid.ec2cc,
catol=catol,
rtol=rtol,
make_plots=make_plots)
#################
# test out divfc
# Note: Relative error on Div B is meaningless b/c the coordinates
# are not the same up to order (dx/4) I think. You can see this
# since (fcdiv - divb_trimmed) is both noisy and stripy
if test_div:
bnd = 0
if mhd_type not in ("F", "FORTRAN"):
b1 = f['b1'][ISLICE]
divb = f['divB'][ISLICE]
if bnd:
trimmed = divb
else:
trimmed = divb['x=1:-1, y=1:-1, z=1:-1']
b1mag = viscid.magnitude(viscid.fc2cc(b1, bnd=bnd))
divb1 = viscid.div_fc(b1, bnd=bnd)
viscid.set_in_region(trimmed,
trimmed,
alpha=0.0,
beta=0.0,
out=trimmed,
mask=viscid.make_spherical_mask(trimmed,
rmax=5.0))
viscid.set_in_region(divb1,
divb1,
alpha=0.0,
beta=0.0,
out=divb1,
mask=viscid.make_spherical_mask(divb1,
rmax=5.0))
reldiff = (divb1 - trimmed) / b1mag
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = divb1.name + " - " + trimmed.name
reldiff.pretty_name = divb1.pretty_name + " - " + trimmed.pretty_name
abs_max_rel_diff = np.nanmax(np.abs(reldiff))
max_crd_diff = [0.0] * 3
for i, d in enumerate('xyz'):
max_crd_diff[i] = np.max(trimmed.get_crd(d) - divb1.get_crd(d))
print("divB max absolute relative diff: {0:.3e} "
"(crds: X: {1[0]:.3e}, Y: {1[1]:.3e}, Z: {1[2]:.3e})"
"".format(abs_max_rel_diff, max_crd_diff))
# plot differences?
if make_plots:
ax1 = plt.subplot(311)
vlt.plot(divb['y=0f'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(divb1['y=0f'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff['y=0f'], symmetric=True, earth=True)
vlt.show()
# Since the coordinates will be different by order dx^2 (i think),
# there is no way to compare the divB from simulation with the
# one we get here. However, they should be the same up to a few %, and
# down to noise level with stripes of enhanced noise. These stripes
# are the errors in the coordinate values (since the output only
# gives us weird nc = averaged cc locations)
#
# if abs_max_rel_diff > rtol or np.any(np.abs(max_crd_diff) > catol):
# raise RuntimeError("Tolerance exceeded on divB calculation")
if test_streamline:
b_cc = f['b_cc']['x=-40f:12f, y=-15f:15f, z=-15f:15f']
b_fc = f['b_fc']['x=-40f:12f, y=-15f:15f, z=-15f:15f']
cotr = viscid.cotr.Cotr()
r_mask = 3.0
# set b_cc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_cc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_cc)
viscid.fill_dipole(b_cc, m=moment, mask=isphere_mask)
# set b_fc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_fc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_fc)
viscid.fill_dipole(b_fc, m=moment, mask=isphere_mask)
seeds = viscid.Volume([-10, 0, -5], [10, 0, 5], (16, 1, 3))
sl_kwargs = dict(ibound=1.0, method=viscid.EULER1A)
lines_cc, topo_cc = viscid.calc_streamlines(b_cc, seeds, **sl_kwargs)
lines_fc, topo_fc = viscid.calc_streamlines(b_fc, seeds, **sl_kwargs)
if make_plots:
plt.figure(figsize=(10, 6))
ax0 = plt.subplot(211)
topo_cc_colors = viscid.topology2color(topo_cc)
vlt.plot(f['pp']['y=0f'], logscale=True, earth=True, cmap='plasma')
vlt.plot2d_lines(lines_cc, topo_cc_colors, symdir='y')
ax0 = plt.subplot(212, sharex=ax0, sharey=ax0)
topo_fc_colors = viscid.topology2color(topo_fc)
vlt.plot(f['pp']['y=0f'], logscale=True, earth=True, cmap='plasma')
vlt.plot2d_lines(lines_fc, topo_fc_colors, symdir='y')
plt.xlim(-20, 10)
plt.ylim(-10, 10)
vlt.auto_adjust_subplots()
vlt.show()
if test_interp:
# test interpolation with E . B / B
b_cc = f['b_cc']
b_fc = f['b_fc']
e_cc = f['e_cc']
e_ec = f['e_ec']
cotr = viscid.cotr.Cotr()
r_mask = 3.0
# set b_cc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_cc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_cc)
viscid.fill_dipole(b_cc, m=moment, mask=isphere_mask)
# set b_fc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_fc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_fc)
viscid.fill_dipole(b_fc, m=moment, mask=isphere_mask)
# zero out e_cc inside some sphere
viscid.set_in_region(e_cc,
e_cc,
alpha=0.0,
beta=0.0,
out=e_cc,
mask=viscid.make_spherical_mask(e_cc,
rmax=r_mask))
# zero out e_ec inside some sphere
viscid.set_in_region(e_ec,
e_ec,
alpha=0.0,
beta=0.0,
out=e_ec,
mask=viscid.make_spherical_mask(e_ec,
rmax=r_mask))
tmp = viscid.empty([
np.linspace(-10, 10, 64),
np.linspace(-10, 10, 64),
np.linspace(-10, 10, 64)
],
center="Cell")
b_cc_interp = viscid.interp_linear(b_cc, tmp)
b_fc_interp = viscid.interp_linear(b_fc, tmp)
e_cc_interp = viscid.interp_linear(e_cc, tmp)
e_ec_interp = viscid.interp_linear(e_ec, tmp)
epar_cc = viscid.dot(e_cc_interp,
b_cc_interp) / viscid.magnitude(b_cc_interp)
epar_ecfc = viscid.dot(e_ec_interp,
b_fc_interp) / viscid.magnitude(b_fc_interp)
if make_plots:
# plt.figure()
# ax0 = plt.subplot(121)
# vlt.plot(b_cc['x']['y=0f'], clim=(-40, 40))
# plt.subplot(122, sharex=ax0, sharey=ax0)
# vlt.plot(b_fc['x']['y=0f'], clim=(-40, 40))
# vlt.show()
plt.figure(figsize=(14, 5))
ax0 = plt.subplot(131)
vlt.plot(epar_cc['y=0f'], symmetric=True, cbarlabel="Epar CC")
plt.subplot(132, sharex=ax0, sharey=ax0)
vlt.plot(epar_ecfc['y=0f'], symmetric=True, cbarlabel="Epar ECFC")
plt.subplot(133, sharex=ax0, sharey=ax0)
vlt.plot(((epar_cc - epar_ecfc) / epar_cc)['y=0f'],
clim=(-10, 10),
cbarlabel="Rel Diff")
vlt.auto_adjust_subplots()
vlt.show()
return 0
def main():
mhd_type = "C"
make_plots = 1
test_fc = 1
test_ec = 1
test_div = 1
test_interp = 1
test_streamline = 1
mhd_type = mhd_type.upper()
if mhd_type.startswith("C"):
if mhd_type in ("C",):
f = viscid.load_file("$WORK/tmedium/*.3d.[-1].xdmf")
elif mhd_type in ("C2", "C3"):
f = viscid.load_file("$WORK/tmedium2/*.3d.[-1].xdmf")
else:
raise ValueError()
catol = 1e-8
rtol = 5e-6
elif mhd_type in ("F", "FORTRAN"):
f = viscid.load_file("$WORK/tmedium3/*.3df.[-1]")
catol = 1e-8
rtol = 7e-2
else:
raise ValueError()
ISLICE = slice(None)
# ISLICE = 'y=0j:0.15j'
# #################
# # test out fc2cc
if test_fc:
b = f['b'][ISLICE]
b1 = f['b1'][ISLICE]
compare_vectors(b, b1, viscid.fc2cc, catol=catol, rtol=rtol,
make_plots=make_plots)
#################
# test out ec2cc
if test_ec:
e_cc = f['e_cc'][ISLICE]
e_ec = f['e_ec'][ISLICE]
if mhd_type not in ("F", "FORTRAN"):
compare_vectors(e_cc, e_ec, viscid.ec2cc, catol=catol, rtol=rtol,
make_plots=make_plots)
#################
# test out divfc
# Note: Relative error on Div B is meaningless b/c the coordinates
# are not the same up to order (dx/4) I think. You can see this
# since (fcdiv - divb_trimmed) is both noisy and stripy
if test_div:
bnd = 0
if mhd_type not in ("F", "FORTRAN"):
b1 = f['b1'][ISLICE]
divb = f['divB'][ISLICE]
if bnd:
trimmed = divb
else:
trimmed = divb['x=1:-1, y=1:-1, z=1:-1']
b1mag = viscid.magnitude(viscid.fc2cc(b1, bnd=bnd))
divb1 = viscid.div_fc(b1, bnd=bnd)
viscid.set_in_region(trimmed, trimmed, alpha=0.0, beta=0.0, out=trimmed,
mask=viscid.make_spherical_mask(trimmed, rmax=5.0))
viscid.set_in_region(divb1, divb1, alpha=0.0, beta=0.0, out=divb1,
mask=viscid.make_spherical_mask(divb1, rmax=5.0))
reldiff = (divb1 - trimmed) / b1mag
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = divb1.name + " - " + trimmed.name
reldiff.pretty_name = divb1.pretty_name + " - " + trimmed.pretty_name
abs_max_rel_diff = np.nanmax(np.abs(reldiff))
max_crd_diff = [0.0] * 3
for i, d in enumerate('xyz'):
max_crd_diff[i] = np.max(trimmed.get_crd(d) - divb1.get_crd(d))
print("divB max absolute relative diff: {0:.3e} "
"(crds: X: {1[0]:.3e}, Y: {1[1]:.3e}, Z: {1[2]:.3e})"
"".format(abs_max_rel_diff, max_crd_diff))
# plot differences?
if make_plots:
ax1 = plt.subplot(311)
vlt.plot(divb['y=0j'], symmetric=True, earth=True)
plt.subplot(312, sharex=ax1, sharey=ax1)
vlt.plot(divb1['y=0j'], symmetric=True, earth=True)
plt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(reldiff['y=0j'], symmetric=True, earth=True)
vlt.show()
# Since the coordinates will be different by order dx^2 (i think),
# there is no way to compare the divB from simulation with the
# one we get here. However, they should be the same up to a few %, and
# down to noise level with stripes of enhanced noise. These stripes
# are the errors in the coordinate values (since the output only
# gives us weird nc = averaged cc locations)
#
# if abs_max_rel_diff > rtol or np.any(np.abs(max_crd_diff) > catol):
# raise RuntimeError("Tolerance exceeded on divB calculation")
if test_streamline:
b_cc = f['b_cc']['x=-40j:12j, y=-15j:15j, z=-15j:15j']
b_fc = f['b_fc']['x=-40j:12j, y=-15j:15j, z=-15j:15j']
cotr = viscid.cotr.Cotr()
r_mask = 3.0
# set b_cc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_cc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_cc)
viscid.fill_dipole(b_cc, m=moment, mask=isphere_mask)
# set b_fc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_fc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_fc)
viscid.fill_dipole(b_fc, m=moment, mask=isphere_mask)
seeds = viscid.Volume([-10, 0, -5], [10, 0, 5], (16, 1, 3))
sl_kwargs = dict(ibound=1.0, method=viscid.EULER1A)
lines_cc, topo_cc = viscid.calc_streamlines(b_cc, seeds, **sl_kwargs)
lines_fc, topo_fc = viscid.calc_streamlines(b_fc, seeds, **sl_kwargs)
if make_plots:
plt.figure(figsize=(10, 6))
ax0 = plt.subplot(211)
topo_cc_colors = viscid.topology2color(topo_cc)
vlt.plot(f['pp']['y=0j'], logscale=True, earth=True, cmap='plasma')
vlt.plot2d_lines(lines_cc, topo_cc_colors, symdir='y')
ax0 = plt.subplot(212, sharex=ax0, sharey=ax0)
topo_fc_colors = viscid.topology2color(topo_fc)
vlt.plot(f['pp']['y=0j'], logscale=True, earth=True, cmap='plasma')
vlt.plot2d_lines(lines_fc, topo_fc_colors, symdir='y')
plt.xlim(-20, 10)
plt.ylim(-10, 10)
vlt.auto_adjust_subplots()
vlt.show()
if test_interp:
# test interpolation with E . B / B
b_cc = f['b_cc']
b_fc = f['b_fc']
e_cc = f['e_cc']
e_ec = f['e_ec']
cotr = viscid.cotr.Cotr()
r_mask = 3.0
# set b_cc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_cc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_cc)
viscid.fill_dipole(b_cc, m=moment, mask=isphere_mask)
# set b_fc to dipole inside some sphere
isphere_mask = viscid.make_spherical_mask(b_fc, rmax=r_mask)
moment = cotr.get_dipole_moment(crd_system=b_fc)
viscid.fill_dipole(b_fc, m=moment, mask=isphere_mask)
# zero out e_cc inside some sphere
viscid.set_in_region(e_cc, e_cc, alpha=0.0, beta=0.0, out=e_cc,
mask=viscid.make_spherical_mask(e_cc, rmax=r_mask))
# zero out e_ec inside some sphere
viscid.set_in_region(e_ec, e_ec, alpha=0.0, beta=0.0, out=e_ec,
mask=viscid.make_spherical_mask(e_ec, rmax=r_mask))
tmp = viscid.empty([np.linspace(-10, 10, 64), np.linspace(-10, 10, 64),
np.linspace(-10, 10, 64)], center="Cell")
b_cc_interp = viscid.interp_linear(b_cc, tmp)
b_fc_interp = viscid.interp_linear(b_fc, tmp)
e_cc_interp = viscid.interp_linear(e_cc, tmp)
e_ec_interp = viscid.interp_linear(e_ec, tmp)
epar_cc = viscid.dot(e_cc_interp, b_cc_interp) / viscid.magnitude(b_cc_interp)
epar_ecfc = viscid.dot(e_ec_interp, b_fc_interp) / viscid.magnitude(b_fc_interp)
if make_plots:
# plt.figure()
# ax0 = plt.subplot(121)
# vlt.plot(b_cc['x']['y=0j'], clim=(-40, 40))
# plt.subplot(122, sharex=ax0, sharey=ax0)
# vlt.plot(b_fc['x']['y=0j'], clim=(-40, 40))
# vlt.show()
plt.figure(figsize=(14, 5))
ax0 = plt.subplot(131)
vlt.plot(epar_cc['y=0j'], symmetric=True, cbarlabel="Epar CC")
plt.subplot(132, sharex=ax0, sharey=ax0)
vlt.plot(epar_ecfc['y=0j'], symmetric=True, cbarlabel="Epar ECFC")
plt.subplot(133, sharex=ax0, sharey=ax0)
vlt.plot(((epar_cc - epar_ecfc) / epar_cc)['y=0j'], clim=(-10, 10),
cbarlabel="Rel Diff")
vlt.auto_adjust_subplots()
vlt.show()
return 0
def main():
mhd_type = "C"
make_plots = 1
test_fc = 1
test_ec = 1
test_div = 1
mhd_type = mhd_type.upper()
if mhd_type.startswith("C"):
if mhd_type in ("C",):
f = viscid.load_file("$WORK/tmedium/*.3d.[-1].xdmf")
elif mhd_type in ("C2", "C3"):
f = viscid.load_file("$WORK/tmedium2/*.3d.[-1].xdmf")
else:
raise ValueError()
catol = 1e-8
rtol = 2.2e-6
elif mhd_type in ("F", "FORTRAN"):
f = viscid.load_file("$WORK/tmedium3/*.3df.[-1]")
catol = 1e-8
rtol = 7e-2
else:
raise ValueError()
ISLICE = slice(None)
# ISLICE = 'y=0f:0.15f'
# #################
# # test out fc2cc
if test_fc:
b = f['b'][ISLICE]
b1 = f['b1'][ISLICE]
compare_vectors(b, b1, viscid.fc2cc, catol=catol, rtol=rtol,
make_plots=make_plots)
#################
# test out ec2cc
if test_ec:
e_cc = f['e_cc'][ISLICE]
e_ec = f['e_ec'][ISLICE]
if mhd_type not in ("F", "FORTRAN"):
compare_vectors(e_cc, e_ec, viscid.ec2cc, catol=catol, rtol=rtol,
make_plots=make_plots)
#################
# test out divfc
# Note: Relative error on Div B is meaningless b/c the coordinates
# are not the same up to order (dx/4) I think. You can see this
# since (fcdiv - divb_trimmed) is both noisy and stripy
if test_div:
bnd = 0
if mhd_type not in ("F", "FORTRAN"):
b1 = f['b1'][ISLICE]
divb = f['divB'][ISLICE]
if bnd:
trimmed = divb
else:
trimmed = divb['x=1:-1, y=1:-1, z=1:-1']
b1mag = viscid.magnitude(viscid.fc2cc(b1, bnd=bnd))
divb1 = viscid.div_fc(b1, bnd=bnd)
viscid.set_in_region(trimmed, trimmed, alpha=0.0, beta=0.0, out=trimmed,
mask=viscid.make_spherical_mask(trimmed, rmax=5.0))
viscid.set_in_region(divb1, divb1, alpha=0.0, beta=0.0, out=divb1,
mask=viscid.make_spherical_mask(divb1, rmax=5.0))
reldiff = (divb1 - trimmed) / b1mag
reldiff = reldiff["x=1:-1, y=1:-1, z=1:-1"]
reldiff.name = divb1.name + " - " + trimmed.name
reldiff.pretty_name = divb1.pretty_name + " - " + trimmed.pretty_name
abs_max_rel_diff = np.nanmax(np.abs(reldiff))
max_crd_diff = [0.0] * 3
for i, d in enumerate('xyz'):
max_crd_diff[i] = np.max(trimmed.get_crd(d) - divb1.get_crd(d))
print("divB max absolute relative diff: {0:.3e} "
"(crds: X: {1[0]:.3e}, Y: {1[1]:.3e}, Z: {1[2]:.3e})"
"".format(abs_max_rel_diff, max_crd_diff))
# plot differences?
if make_plots:
ax1 = mpl.plt.subplot(311)
mpl.plot(divb['y=0f'], symmetric=True, earth=True)
mpl.plt.subplot(312, sharex=ax1, sharey=ax1)
mpl.plot(divb1['y=0f'], symmetric=True, earth=True)
mpl.plt.subplot(313, sharex=ax1, sharey=ax1)
mpl.plot(reldiff['y=0f'], symmetric=True, earth=True)
mpl.show()
# Since the coordinates will be different by order dx^2 (i think),
# there is no way to compare the divB from simulation with the
# one we get here. However, they should be the same up to a few %, and
# down to noise level with stripes of enhanced noise. These stripes
# are the errors in the coordinate values (since the output only
# gives us weird nc = averaged cc locations)
#
# if abs_max_rel_diff > rtol or np.any(np.abs(max_crd_diff) > catol):
# raise RuntimeError("Tolerance exceeded on divB calculation")
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--prof", action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
b = viscid.make_dipole(l=(-5, -5, -5), h=(5, 5, 5), n=(255, 255, 127),
m=(0, 0, -1))
b2 = np.sum(b * b, axis=b.nr_comp)
if args.prof:
print("Without boundaries")
viscid.timeit(viscid.grad, b2, bnd=False, timeit_repeat=10,
timeit_print_stats=True)
print("With boundaries")
viscid.timeit(viscid.grad, b2, bnd=True, timeit_repeat=10,
timeit_print_stats=True)
grad_b2 = viscid.grad(b2)
grad_b2.pretty_name = r"$\nabla$ B$^2$"
conv = viscid.convective_deriv(b)
conv.pretty_name = r"(B $\cdot \nabla$) B"
_ = plt.figure(figsize=(9, 4.2))
ax1 = vlt.subplot(231)
vlt.plot(b2['z=0j'], logscale=True)
vlt.plot(b2['z=0j'], logscale=True, style='contour', levels=10, colors='grey')
# vlt.plot2d_quiver(viscid.normalize(b['z=0j']), step=16, pivot='mid')
ax2 = vlt.subplot(234)
vlt.plot(b2['y=0j'], logscale=True)
vlt.plot(b2['y=0j'], logscale=True, style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(b['y=0j'], preferred='numpy'),
step=16, pivot='mid')
vlt.subplot(232, sharex=ax1, sharey=ax1)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['z=0j']), logscale=True)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['z=0j']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(grad_b2['z=0j']), step=16, pivot='mid')
vlt.subplot(235, sharex=ax2, sharey=ax2)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['y=0j']), logscale=True)
vlt.plot(1e-4 + viscid.magnitude(grad_b2['y=0j']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(grad_b2['y=0j']), step=16, pivot='mid')
vlt.subplot(233, sharex=ax1, sharey=ax1)
vlt.plot(viscid.magnitude(conv['z=0j']), logscale=True)
vlt.plot(viscid.magnitude(conv['z=0j']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(conv['z=0j']), step=16, pivot='mid')
vlt.subplot(236, sharex=ax2, sharey=ax2)
vlt.plot(viscid.magnitude(conv['y=0j']), logscale=True)
vlt.plot(viscid.magnitude(conv['y=0j']), logscale=True,
style='contour', levels=10, colors='grey')
vlt.plot2d_quiver(viscid.normalize(conv['y=0j']), step=16, pivot='mid')
vlt.auto_adjust_subplots()
plt.savefig(next_plot_fname(__file__))
if args.show:
vlt.show()
return 0
