def _main():
crd_system = 'gse'
print(
viscid.get_dipole_moment_ang(dip_tilt=45.0,
dip_gsm=0.0,
crd_system=crd_system))
print(
viscid.get_dipole_moment_ang(dip_tilt=0.0,
dip_gsm=45.0,
crd_system=crd_system))
print(
viscid.get_dipole_moment_ang(dip_tilt=45.0,
dip_gsm=45.0,
crd_system=crd_system))
print("---")
ptsNP = np.array([[+2, -2, +2], [+2, -1, +2], [+2, 1, +2], [+2, 2, +2]]).T
ptsSP = np.array([[+2, -2, -2], [+2, -1, -2], [+2, 1, -2], [+2, 2, -2]]).T
ptsNN = np.array([[-2, -2, +2], [-2, -1, +2], [-2, 1, +2], [-2, 2, +2]]).T
ptsSN = np.array([[-2, -2, -2], [-2, -1, -2], [-2, 1, -2], [-2, 2, -2]]).T
mapped_ptsNP = dipole_map(ptsNP)
mapped_ptsNN = dipole_map(ptsNN)
mapped_ptsSP = dipole_map(ptsSP)
mapped_ptsSN = dipole_map(ptsSN)
try:
from viscid.plot import vlab
colors1 = np.array([(0.6, 0.2, 0.2), (0.2, 0.2, 0.6), (0.6, 0.6, 0.2),
(0.2, 0.6, 0.6)])
colors2 = colors1 * 0.5
vlab.points3d(ptsNP, scale_factor=0.4, color=tuple(colors1[0]))
vlab.points3d(ptsNN, scale_factor=0.4, color=tuple(colors1[1]))
vlab.points3d(ptsSP, scale_factor=0.4, color=tuple(colors1[2]))
vlab.points3d(ptsSN, scale_factor=0.4, color=tuple(colors1[3]))
vlab.points3d(mapped_ptsNP, scale_factor=0.4, color=tuple(colors2[0]))
vlab.points3d(mapped_ptsNN, scale_factor=0.4, color=tuple(colors2[1]))
vlab.points3d(mapped_ptsSP, scale_factor=0.4, color=tuple(colors2[2]))
vlab.points3d(mapped_ptsSN, scale_factor=0.4, color=tuple(colors2[3]))
b = make_dipole()
vlab.plot_lines(
viscid.calc_streamlines(b, mapped_ptsNP, ibound=0.5)[0])
vlab.plot_lines(
viscid.calc_streamlines(b, mapped_ptsNN, ibound=0.5)[0])
vlab.show()
except ImportError:
print("Mayavi not installed, no 3D plots", file=sys.stderr)
def _main():
crd_system = 'gse'
print(viscid.get_dipole_moment_ang(dip_tilt=45.0, dip_gsm=0.0,
crd_system=crd_system))
print(viscid.get_dipole_moment_ang(dip_tilt=0.0, dip_gsm=45.0,
crd_system=crd_system))
print(viscid.get_dipole_moment_ang(dip_tilt=45.0, dip_gsm=45.0,
crd_system=crd_system))
print("---")
ptsNP = np.array([[+2, -2, +2], [+2, -1, +2], [+2, 1, +2], [+2, 2, +2]]).T
ptsSP = np.array([[+2, -2, -2], [+2, -1, -2], [+2, 1, -2], [+2, 2, -2]]).T
ptsNN = np.array([[-2, -2, +2], [-2, -1, +2], [-2, 1, +2], [-2, 2, +2]]).T
ptsSN = np.array([[-2, -2, -2], [-2, -1, -2], [-2, 1, -2], [-2, 2, -2]]).T
mapped_ptsNP = dipole_map(ptsNP)
mapped_ptsNN = dipole_map(ptsNN)
mapped_ptsSP = dipole_map(ptsSP)
mapped_ptsSN = dipole_map(ptsSN)
try:
from viscid.plot import vlab
colors1 = np.array([(0.6, 0.2, 0.2),
(0.2, 0.2, 0.6),
(0.6, 0.6, 0.2),
(0.2, 0.6, 0.6)])
colors2 = colors1 * 0.5
vlab.points3d(ptsNP, scale_factor=0.4, color=tuple(colors1[0]))
vlab.points3d(ptsNN, scale_factor=0.4, color=tuple(colors1[1]))
vlab.points3d(ptsSP, scale_factor=0.4, color=tuple(colors1[2]))
vlab.points3d(ptsSN, scale_factor=0.4, color=tuple(colors1[3]))
vlab.points3d(mapped_ptsNP, scale_factor=0.4, color=tuple(colors2[0]))
vlab.points3d(mapped_ptsNN, scale_factor=0.4, color=tuple(colors2[1]))
vlab.points3d(mapped_ptsSP, scale_factor=0.4, color=tuple(colors2[2]))
vlab.points3d(mapped_ptsSN, scale_factor=0.4, color=tuple(colors2[3]))
b = make_dipole()
vlab.plot_lines(viscid.calc_streamlines(b, mapped_ptsNP, ibound=0.5)[0])
vlab.plot_lines(viscid.calc_streamlines(b, mapped_ptsNN, ibound=0.5)[0])
vlab.show()
except ImportError:
print("Mayavi not installed, no 3D plots", file=sys.stderr)
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
####### test 5-moment uniform grids
gk_uniform = viscid.load_file(os.path.join(sample_dir,
'sample_gkeyll_uniform_q_*.h5'))
plt.figure(figsize=(9, 3))
for i, grid in enumerate(gk_uniform.iter_times(":")):
plt.subplot2grid((1, 2), (0, i))
vlt.plot(grid['rho_i'], logscale=True, style='contourf', levels=128)
seeds = viscid.Line((-1.2, 0, 0), (1.4, 0, 0), 8)
b_lines, _ = viscid.calc_streamlines(grid['b'], seeds, method='euler1',
max_length=20.0)
vlt.plot2d_lines(b_lines, scalars='#000000', symdir='z', linewidth=1.0)
plt.title(grid.format_time('.02f'))
vlt.auto_adjust_subplots()
plt.suptitle("Uniform Gkeyll Dataset")
plt.savefig(next_plot_fname(__file__))
if args.show:
plt.show()
plt.clf()
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
####### test 5-moment uniform grids
gk_uniform = viscid.load_file(os.path.join(sample_dir,
'sample_gkeyll_uniform_q_*.h5'))
_, axes = plt.subplots(1, 2, figsize=(9, 3))
for i, grid in enumerate(gk_uniform.iter_times(":")):
vlt.plot(grid['rho_i'], logscale=True, style='contourf', levels=128,
ax=axes[i])
seeds = viscid.Line((-1.2, 0, 0), (1.4, 0, 0), 8)
b_lines, _ = viscid.calc_streamlines(grid['b'], seeds, method='euler1',
max_length=20.0)
vlt.plot2d_lines(b_lines, scalars='#000000', symdir='z', linewidth=1.0)
plt.title(grid.format_time('.02f'))
vlt.auto_adjust_subplots()
plt.suptitle("Uniform Gkeyll Dataset")
plt.savefig(next_plot_fname(__file__))
if args.show:
plt.show()
plt.clf()
return 0
def get_sep_pts_bitor(fld, seed, trace_opts=None, make_3d=True, **kwargs):
"""bitor topologies to find separator points in uv map from seed
Args:
fld (VectorField): Magnetic Field
seed (viscid.seed.SeedGen): Any Seed generator with a 2d local
representation
trace_opts (dict): kwargs for calc_streamlines
make_3d (bool): convert result from uv to 3d space
**kwargs: passed to :py:func:`topology_bitor_clusters`
Returns:
3xN ndarray of N separator points in uv space or 3d space
depending on the `make_3d` kwarg
"""
trace_opts = _prep_trace_opt_defaults(trace_opts)
topo = viscid.calc_streamlines(fld, seed, **trace_opts)[1]
try:
pt_bnds = seed.pt_bnds
except AttributeError:
pt_bnds = ()
try:
periodic = seed.periodic
except AttributeError:
periodic = "00"
kwargs.setdefault("pt_bnds", pt_bnds)
kwargs.setdefault("periodic", periodic)
pts = topology_bitor_clusters(topo, **kwargs)
if make_3d:
pts = seed.uv_to_3d(pts)
return pts
def get_sep_pts_bitor(fld, seed, trace_opts=None, make_3d=True, **kwargs):
"""bitor topologies to find separator points in uv map from seed
Args:
fld (VectorField): Magnetic Field
seed (viscid.seed.SeedGen): Any Seed generator with a 2d local
representation
trace_opts (dict): kwargs for calc_streamlines
make_3d (bool): convert result from uv to 3d space
**kwargs: passed to :py:func:`topology_bitor_clusters`
Returns:
3xN ndarray of N separator points in uv space or 3d space
depending on the `make_3d` kwarg
"""
trace_opts = _prep_trace_opt_defaults(trace_opts)
topo = viscid.calc_streamlines(fld, seed, **trace_opts)[1]
try:
pt_bnds = seed.pt_bnds
except AttributeError:
pt_bnds = ()
try:
periodic = seed.periodic
except AttributeError:
periodic = "00"
kwargs.setdefault('pt_bnds', pt_bnds)
kwargs.setdefault('periodic', periodic)
pts = topology_bitor_clusters(topo, **kwargs)
if make_3d:
pts = seed.uv_to_3d(pts)
return pts
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 check():
"""Runtime check compiled modules"""
import os
import sys
import numpy as np
import viscid
ret = 0
check_version()
print()
#####################################################
# run streamline calculation (checks cython modules)
try:
cotr = viscid.Cotr(dip_tilt=15.0, dip_gsm=21.0) # pylint: disable=not-callable
m = cotr.get_dipole_moment(crd_system='gse')
seeds = viscid.seed.Sphere((0.0, 0.0, 0.0),
2.0,
pole=-m,
ntheta=25,
nphi=25,
thetalim=(5, 90),
philim=(5, 360),
phi_endpoint=False)
B = viscid.make_dipole(m=m,
crd_system='gse',
n=(32, 32, 32),
l=(-25, -25, -25),
h=(25, 25, 25),
dtype='f8')
lines, _ = viscid.calc_streamlines(B, seeds, ibound=1.0)
for line in lines:
if np.any(np.isnan(line)):
raise ValueError("NaN in line")
print("Cython module ran successfully")
except Exception as e:
print("Cython module has runtime errors.")
print(str(e))
ret |= (1 << 0)
print()
####################################
# load a jrrle file (checks fortran)
try:
f3d = viscid.load_file(
os.path.join(viscid.sample_dir, 'sample_jrrle.3df.*'))
_ = np.array(f3d['pp'].data)
print("Fortran module ran successfully")
except Exception as e:
print("Fortran module has runtime errors.")
print(str(e))
ret |= (1 << 1)
print()
return ret
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 main():
parser = argparse.ArgumentParser(description="Test quasi potential")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
b, e = make_arcade(8.0, N=[64, 64, 64])
epar = viscid.project(e, b)
epar.pretty_name = "E parallel"
###############
# Calculate Xi
seeds = viscid.Volume(xl=[-10, 0.0, -10], xh=[10, 0.0, 10],
n=[64, 1, 64])
b_lines, _ = viscid.calc_streamlines(b, seeds)
xi_dat = viscid.integrate_along_lines(b_lines, e, reduction='dot')
xi = seeds.wrap_field(xi_dat, name='xi', pretty_name=r"$\Xi$")
################################
# Make 2D Matplotlib plot of Xi
mpl.plot(xi, x=(-10, 10), y=(-10, 10), style='contourf', levels=256,
lin=(2e-4, 1.5718))
mpl.plot(xi, x=(-10, 10), y=(-10, 10), style='contour', colors='grey',
levels=[0.5, 1.0])
mpl.savefig(next_plot_fname(__file__))
if args.show:
mpl.show()
############################################################
# Make 3D mayavi plot of Xi and the 'brightest' field lines
# as well as some other field lines for context
try:
from viscid.plot import mvi
except ImportError:
xfail("Mayavi not installed")
mvi.figure(size=[1200, 800], offscreen=not args.show)
inds = np.argsort(xi_dat)[-64:]
inds = np.concatenate([inds, np.arange(len(xi_dat))[::71]])
s = mvi.plot_lines(b_lines[inds], scalars=epar, cmap='viridis')
mvi.mesh_from_seeds(seeds, scalars=xi, cmap='inferno')
mvi.colorbar(s, orientation='horizontal', title=epar.pretty_name)
# mvi.streamline(b, scalars=e, seedtype='sphere', seed_resolution=4,
# integration_direction='both')
oa = mvi.orientation_axes()
oa.marker.set_viewport(0.75, 0.75, 1.0, 1.0)
mvi.view(roll=0, azimuth=90, elevation=25, distance=30.0,
focalpoint=[0, 2, 0])
mvi.savefig(next_plot_fname(__file__))
if args.show:
mvi.show()
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 check():
"""Runtime check compiled modules"""
import os
import sys
import numpy as np
import viscid
ret = 0
check_version()
print()
#####################################################
# run streamline calculation (checks cython modules)
try:
cotr = viscid.Cotr(dip_tilt=15.0, dip_gsm=21.0) # pylint: disable=not-callable
m = cotr.get_dipole_moment(crd_system='gse')
seeds = viscid.seed.Sphere((0.0, 0.0, 0.0), 2.0, pole=-m, ntheta=25,
nphi=25, thetalim=(5, 90), philim=(5, 360),
phi_endpoint=False)
B = viscid.make_dipole(m=m, crd_system='gse', n=(32, 32, 32),
l=(-25, -25, -25), h=(25, 25, 25), dtype='f8')
lines, _ = viscid.calc_streamlines(B, seeds, ibound=1.0)
for line in lines:
if np.any(np.isnan(line)):
raise ValueError("NaN in line")
print("Cython module ran successfully")
except Exception as e:
print("Cython module has runtime errors.")
print(str(e))
ret |= (1 << 0)
print()
####################################
# load a jrrle file (checks fortran)
try:
f3d = viscid.load_file(os.path.join(viscid.sample_dir,
'sample_jrrle.3df.*'))
_ = np.array(f3d['pp'].data)
print("Fortran module ran successfully")
except Exception as e:
print("Fortran module has runtime errors.")
print(str(e))
ret |= (1 << 1)
print()
return ret
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 main():
parser = argparse.ArgumentParser(description="Test calc")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
f3d = viscid.load_file(_viscid_root + '/../sample/sample.3df.[0].xdmf')
f_iono = viscid.load_file(_viscid_root + "/../sample/*.iof.[0].xdmf")
b = f3d["b"]
pp = f3d["pp"]
# plot a scalar cut plane of pressure
pp_src = mvi.field2source(pp, center='node')
scp = mlab.pipeline.scalar_cut_plane(pp_src, plane_orientation='z_axes',
transparent=True, opacity=0.5,
view_controls=False)
scp.implicit_plane.normal = [0, 0, -1]
scp.implicit_plane.origin = [0, 0, 0]
# i don't know why this log10 doesn't seem to work
scp.module_manager.scalar_lut_manager.lut.scale = 'log10'
scp.module_manager.scalar_lut_manager.lut_mode = 'Reds'
scp.module_manager.scalar_lut_manager.reverse_lut = True
scp.module_manager.scalar_lut_manager.show_scalar_bar = True
# calculate B field lines && topology in viscid and plot them
seeds = viscid.SphericalPatch([0, 0, 0], [2, 0, 1], 30, 15, r=5.0,
nalpha=5, nbeta=5)
b_lines, topo = viscid.calc_streamlines(b, seeds, ibound=3.5,
obound0=[-25, -20, -20],
obound1=[15, 20, 20])
mvi.plot_lines(b_lines, scalars=viscid.topology2color(topo))
# Use Mayavi (VTK) to calculate field lines using an interactive seed
b_src = mvi.field2source(b, center='node')
bsl2 = mlab.pipeline.streamline(b_src, seedtype='sphere',
integration_direction='both',
seed_resolution=4)
bsl2.stream_tracer.maximum_propagation = 20.
bsl2.seed.widget.center = [-11, 0, 0]
bsl2.seed.widget.radius = 1.0
bsl2.streamline_type = 'tube'
bsl2.tube_filter.radius = 0.03
bsl2.stop() # this stop/start was a hack to get something to work?
bsl2.start()
bsl2.seed.widget.enabled = True
# Plot the ionosphere too
fac_tot = 1e9 * f_iono['fac_tot']
crd_system = 'gse'
m = mvi.plot_ionosphere(fac_tot, crd_system=crd_system, bounding_lat=30.0,
vmin=-300, vmax=300, opacity=0.75)
m.module_manager.scalar_lut_manager.lut_mode = 'RdBu'
m.module_manager.scalar_lut_manager.reverse_lut = True
mvi.plot_blue_marble(r=1.0, orientation=(0, 21.5, -45.0))
# now shade the night side with a transparent black hemisphere
mvi.plot_earth_3d(radius=1.01, crd_system="gse", night_only=True,
opacity=0.5)
mlab.axes(pp_src, nb_labels=5)
mlab.orientation_axes()
mvi.resize([1200, 800])
mlab.view(azimuth=40, elevation=70, distance=35.0, focalpoint=[-3, 0, 0])
# # Save Figure
# print("saving png")
# mvi.mlab.savefig('mayavi_msphere_sample.png')
# print("saving x3d")
# # x3d files can be turned into COLLADA files with meshlab, and
# # COLLADA (.dae) files can be opened in OS X's preview
# #
# # IMPORTANT: for some reason, using bounding_lat in mvi.plot_ionosphere
# # causes a segfault when saving x3d files
# #
# mvi.mlab.savefig('mayavi_msphere_sample.x3d')
# print("done")
if args.show:
mlab.show()
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
parser.add_argument("--interact", "-i", action="store_true")
args = vutil.common_argparse(parser)
f3d = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[0].xdmf'))
f_iono = viscid.load_file(os.path.join(sample_dir, "sample_xdmf.iof.[0].xdmf"))
b = f3d["b"]
v = f3d["v"]
pp = f3d["pp"]
e = f3d["e_cc"]
vlab.figure(size=(1280, 800), offscreen=not args.show)
##########################################################
# make b a dipole inside 3.1Re and set e = 0 inside 4.0Re
cotr = viscid.Cotr(time='1990-03-21T14:48', dip_tilt=0.0) # pylint: disable=not-callable
moment = cotr.get_dipole_moment(crd_system=b)
isphere_mask = viscid.make_spherical_mask(b, rmax=3.1)
viscid.fill_dipole(b, m=moment, mask=isphere_mask)
e_mask = viscid.make_spherical_mask(b, rmax=4.0)
viscid.set_in_region(e, 0.0, alpha=0.0, mask=e_mask, out=e)
######################################
# plot a scalar cut plane of pressure
pp_src = vlab.field2source(pp, center='node')
scp = vlab.scalar_cut_plane(pp_src, plane_orientation='z_axes', opacity=0.5,
transparent=True, view_controls=False,
cmap="inferno", logscale=True)
scp.implicit_plane.normal = [0, 0, -1]
scp.implicit_plane.origin = [0, 0, 0]
scp.enable_contours = True
scp.contour.filled_contours = True
scp.contour.number_of_contours = 64
cbar = vlab.colorbar(scp, title=pp.name, orientation='vertical')
cbar.scalar_bar_representation.position = (0.01, 0.13)
cbar.scalar_bar_representation.position2 = (0.08, 0.76)
######################################
# plot a vector cut plane of the flow
vcp = vlab.vector_cut_plane(v, scalars=pp_src, plane_orientation='z_axes',
view_controls=False, mode='arrow',
cmap='Greens_r')
vcp.implicit_plane.normal = [0, 0, -1]
vcp.implicit_plane.origin = [0, 0, 0]
##############################
# plot very faint isosurfaces
vx_src = vlab.field2source(v['x'], center='node')
iso = vlab.iso_surface(vx_src, contours=[0.0], opacity=0.008, cmap='Pastel1')
##############################################################
# calculate B field lines && topology in Viscid and plot them
seedsA = viscid.SphericalPatch([0, 0, 0], [2, 0, 1], 30, 15, r=5.0,
nalpha=5, nbeta=5)
seedsB = viscid.SphericalPatch([0, 0, 0], [1.9, 0, -20], 30, 15, r=5.0,
nalpha=1, nbeta=5)
seeds = np.concatenate([seedsA, seedsB], axis=1)
b_lines, topo = viscid.calc_streamlines(b, seeds, ibound=3.5,
obound0=[-25, -20, -20],
obound1=[15, 20, 20], wrap=True)
vlab.plot_lines(b_lines, scalars=viscid.topology2color(topo))
######################################################################
# plot a random circle at geosynchronus orbit with scalars colored
# by the Matplotlib viridis color map, just because we can; this is
# a useful toy for debugging
circle = viscid.Circle(p0=[0, 0, 0], r=6.618, n=128, endpoint=True)
scalar = np.sin(circle.as_local_coordinates().get_crd('phi'))
surf = vlab.plot_line(circle.get_points(), scalars=scalar, clim=0.8,
cmap="Spectral_r")
######################################################################
# Use Mayavi (VTK) to calculate field lines using an interactive seed
# These field lines are colored by E parallel
epar = viscid.project(e, b)
epar.name = "Epar"
bsl2 = vlab.streamline(b, epar, seedtype='plane', seed_resolution=4,
integration_direction='both', clim=(-0.05, 0.05))
# now tweak the VTK streamlines
bsl2.stream_tracer.maximum_propagation = 20.
bsl2.seed.widget.origin = [-11, -5.0, -2.0]
bsl2.seed.widget.point1 = [-11, 5.0, -2.0]
bsl2.seed.widget.point2 = [-11.0, -5.0, 2.0]
bsl2.streamline_type = 'tube'
bsl2.tube_filter.radius = 0.03
bsl2.stop() # this stop/start was a hack to get something to update
bsl2.start()
bsl2.seed.widget.enabled = False
cbar = vlab.colorbar(bsl2, title=epar.name, label_fmt='%.3f',
orientation='horizontal')
cbar.scalar_bar_representation.position = (0.15, 0.01)
cbar.scalar_bar_representation.position2 = (0.72, 0.10)
###############################################################
# Make a contour at the open-closed boundary in the ionosphere
seeds_iono = viscid.Sphere(r=1.063, pole=-moment, ntheta=256, nphi=256,
thetalim=(0, 180), philim=(0, 360), crd_system=b)
_, topo_iono = viscid.calc_streamlines(b, seeds_iono, ibound=1.0,
nr_procs='all',
output=viscid.OUTPUT_TOPOLOGY)
topo_iono = np.log2(topo_iono)
m = vlab.mesh_from_seeds(seeds_iono, scalars=topo_iono, opacity=1.0,
clim=(0, 3), color=(0.992, 0.445, 0.0))
m.enable_contours = True
m.actor.property.line_width = 4.0
m.contour.number_of_contours = 4
####################################################################
# Plot the ionosphere, note that the sample data has the ionosphere
# at a different time, so the open-closed boundary found above
# will not be consistant with the field aligned currents
fac_tot = 1e9 * f_iono['fac_tot']
m = vlab.plot_ionosphere(fac_tot, bounding_lat=30.0, vmin=-300, vmax=300,
opacity=0.75, rotate=cotr, crd_system=b)
m.actor.property.backface_culling = True
########################################################################
# Add some markers for earth, i.e., real earth, and dayside / nightside
# representation
vlab.plot_blue_marble(r=1.0, lines=False, ntheta=64, nphi=128,
rotate=cotr, crd_system=b)
# now shade the night side with a transparent black hemisphere
vlab.plot_earth_3d(radius=1.01, night_only=True, opacity=0.5, crd_system=b)
####################
# Finishing Touches
# vlab.axes(pp_src, nb_labels=5)
oa = vlab.orientation_axes()
oa.marker.set_viewport(0.75, 0.75, 1.0, 1.0)
# note that resize won't work if the current figure has the
# off_screen_rendering flag set
# vlab.resize([1200, 800])
vlab.view(azimuth=45, elevation=70, distance=35.0, focalpoint=[-2, 0, 0])
##############
# Save Figure
# print("saving png")
# vlab.savefig('mayavi_msphere_sample.png')
# print("saving x3d")
# # x3d files can be turned into COLLADA files with meshlab, and
# # COLLADA (.dae) files can be opened in OS X's preview
# #
# # IMPORTANT: for some reason, using bounding_lat in vlab.plot_ionosphere
# # causes a segfault when saving x3d files
# #
# vlab.savefig('mayavi_msphere_sample.x3d')
# print("done")
vlab.savefig(next_plot_fname(__file__))
###########################
# Interact Programatically
if args.interact:
vlab.interact()
#######################
# Interact Graphically
if args.show:
vlab.show()
try:
vlab.mlab.close()
except AttributeError:
pass
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 _follow_fluid_step(i, dt, grid, root_seeds, plot_function, stream_opts,
speed_scale):
direction = int(dt / np.abs(dt))
if direction >= 0:
sl_direction = streamline.DIR_FORWARD
else:
sl_direction = streamline.DIR_BACKWARD
logger.info("working on timestep {0} {1}".format(i, grid.time))
v = grid["v"]
logger.debug("finished reading V field")
logger.debug("calculating new streamline positions")
flow_lines = calc_streamlines(v, root_seeds,
output=viscid.OUTPUT_STREAMLINES,
stream_dir=sl_direction,
**stream_opts)[0]
logger.debug("done with that, now i'm plotting...")
plot_function(i, grid, v, flow_lines, root_seeds)
############################################################
# now recalculate the seed positions for the next timestep
logger.debug("finding new seed positions...")
root_pts = root_seeds.genr_points()
valid_pt_inds = []
for i in range(root_pts.shape[1]):
valid_pt = True
# get the index of the root point in teh 2d flow line array
# dist = flow_lines[i] - root_pts[:, [i]]
# root_ind = np.argmin(np.sum(dist**2, axis=0))
# print("!!!", root_pts[:, i], "==", flow_lines[i][:, root_ind])
# interpolate velocity onto teh flow line, and get speed too
v_interp = cycalc.interp_trilin(v, seed.Point(flow_lines[i]))
speed = np.sqrt(np.sum(v_interp * v_interp, axis=1))
# this is a super slopy way to integrate velocity
# keep marching along the flow line until we get to the next timestep
t = 0.0
ind = 0
if direction < 0:
flow_lines[i] = flow_lines[i][:, ::-1]
speed = speed[::-1]
while t < np.abs(dt):
ind += 1
if ind >= len(speed):
# set valid_pt to True if you want to keep that point for
# future time steps, but most likely if we're here, the seed
# has gone out of our region of interest
ind = len(speed) - 1
valid_pt = False
logger.info("OOPS: ran out of streamline, increase "
"max_length when tracing flow lines if this "
"is unexpected")
break
t += stream_opts["ds0"] / (speed_scale * speed[ind])
root_pts[:, i] = flow_lines[i][:, ind]
if valid_pt:
valid_pt_inds.append(i)
# remove seeds that have flown out of our region of interest
# (aka, beyond the flow line we drew)
root_pts = root_pts[:, valid_pt_inds]
logger.debug("ok, done with all that :)")
return root_pts
def _get_sep_pts_bisect(fld,
seed,
trace_opts=None,
min_depth=3,
max_depth=7,
plot=False,
perimeter_check=perimeter_check_bitwise_or,
make_3d=True,
start_uneven=False,
_base_quadrent="",
_uneven_mask=0,
_first_recurse=True):
if len(_base_quadrent) == max_depth:
return [_base_quadrent] # causes pylint to complain
if trace_opts is None:
trace_opts = dict()
nx, ny = seed.uv_shape
(xlim, ylim) = seed.uv_extent
if _first_recurse and start_uneven:
_uneven_mask = UNEVEN_MASK
if _first_recurse and plot:
from viscid.plot import vlab
from viscid.plot import vpyplot as vlt
vlt.clf()
_, all_topo = viscid.calc_streamlines(fld, seed, **trace_opts)
vlt.plot(np.bitwise_and(all_topo, 15), show=False)
verts, arr = seed.wrap_mesh(all_topo.data)
vlab.mesh(verts[0], verts[1], verts[2], scalars=arr, opacity=0.75)
# quadrents and lines are indexed as follows...
# directions are counter clackwise around the quadrent with
# lower index (which matters for lines which are shared among
# more than one quadrent, aka, lines 1,2,6,7). Notice that even
# numbered lines are horizontal, like the interstate system :)
# -<--10-----<-8---
# | ^ ^
# 11 2 9 3 7
# \/ | |
# --<-2-----<-6----
# | ^ ^
# 3 0 1 1 5
# \/ | |
# ----0->-----4->--
# find low(left), mid(center), and high(right) crds in x and y
low_quad = "{0}{1:x}".format(_base_quadrent, 0 | _uneven_mask)
high_quad = "{0}{1:x}".format(_base_quadrent, 3 | _uneven_mask)
xl, xm, yl, ym = _quadrent_limits(low_quad, xlim, ylim)
_, xh, _, yh = _quadrent_limits(high_quad, xlim, ylim)
segsx, segsy = [None] * 12, [None] * 12
topo = [None] * 12
nxm, nym = nx // 2, ny // 2
# make all the line segments
segsx[0], segsy[0] = np.linspace(xl, xm, nxm), np.linspace(yl, yl, nxm)
segsx[1], segsy[1] = np.linspace(xm, xm, nym), np.linspace(yl, ym, nym)
segsx[2], segsy[2] = np.linspace(xm, xl, nxm), np.linspace(ym, ym, nxm)
segsx[3], segsy[3] = np.linspace(xl, xl, nym), np.linspace(ym, yl, nym)
segsx[4], segsy[4] = np.linspace(xm, xh, nxm), np.linspace(yl, yl, nxm)
segsx[5], segsy[5] = np.linspace(xh, xh, nym), np.linspace(yl, ym, nym)
segsx[6], segsy[6] = np.linspace(xh, xm, nxm), np.linspace(ym, ym, nxm)
segsx[7], segsy[7] = np.linspace(xh, xh, nym), np.linspace(ym, yh, nym)
segsx[8], segsy[8] = np.linspace(xh, xm, nxm), np.linspace(yh, yh, nxm)
segsx[9], segsy[9] = np.linspace(xm, xm, nym), np.linspace(ym, yh, nym)
segsx[10], segsy[10] = np.linspace(xm, xl, nxm), np.linspace(yh, yh, nxm)
segsx[11], segsy[11] = np.linspace(xl, xl, nym), np.linspace(yh, ym, nym)
allx = np.concatenate(segsx)
ally = np.concatenate(segsy)
# print("plot::", _base_quadrent, '|', _uneven_mask, '|', len(allx), len(ally))
pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
_, all_topo = viscid.calc_streamlines(fld, pts3d, **trace_opts)
topo[0] = all_topo[:len(segsx[0])]
cnt = len(topo[0])
for i, segx in zip(count(1), segsx[1:]):
topo[i] = all_topo[cnt:cnt + len(segx)]
# print("??", i, cnt, cnt + len(segx), np.bitwise_and.reduce(topo[i]))
cnt += len(topo[i])
# assemble the lines into the four quadrents
quad_topo = [None] * 4
# all arrays snip off the last element since those are
# duplicated by the next line... reversed arrays do the
# snipping with -1:0:-1
quad_topo[0] = np.concatenate(
[topo[0][:-1], topo[1][:-1], topo[2][:-1], topo[3][:-1]])
quad_topo[1] = np.concatenate(
[topo[4][:-1], topo[5][:-1], topo[6][:-1], topo[1][-1:0:-1]])
quad_topo[2] = np.concatenate(
[topo[2][-1:0:-1], topo[9][:-1], topo[10][:-1], topo[11][:-1]])
quad_topo[3] = np.concatenate(
[topo[6][-1:0:-1], topo[7][:-1], topo[8][:-1], topo[9][-1:0:-1]])
# now that the quad arrays are populated, decide which quadrents
# still contain the separator (could be > 1)
required_uneven_subquads = False
ret = []
for i in range(4):
if perimeter_check(quad_topo[i]):
next_quad = "{0}{1:x}".format(_base_quadrent, i | _uneven_mask)
subquads = _get_sep_pts_bisect(fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=next_quad,
_uneven_mask=0,
_first_recurse=False)
ret += subquads
if len(ret) == 0:
perimeter = np.concatenate([
topo[0][::-1], topo[4][::-1], topo[5][::-1], topo[7][::-1],
topo[8][::-1], topo[10][::-1], topo[11][::-1], topo[3][::-1]
])
if _uneven_mask:
if len(_base_quadrent) > min_depth:
print("sep trace issue, but min depth reached: {0} > {1}"
"".format(len(_base_quadrent), min_depth))
ret = [_base_quadrent]
else:
print("sep trace issue, the separator ended prematurely")
elif perimeter_check(perimeter):
ret = _get_sep_pts_bisect(fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=_base_quadrent,
_uneven_mask=UNEVEN_MASK,
_first_recurse=False)
required_uneven_subquads = True
if plot and not required_uneven_subquads:
from viscid.plot import vlab
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
_pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
vlab.points3d(_pts3d[0],
_pts3d[1],
_pts3d[2],
all_topo.data.reshape(-1),
scale_mode='none',
scale_factor=0.02)
plt.scatter(allx,
ally,
color=np.bitwise_and(all_topo, 15),
vmin=0,
vmax=15,
marker='o',
edgecolor='y',
s=40)
if _first_recurse:
# turn quadrent strings into locations
xc = np.empty(len(ret))
yc = np.empty(len(ret))
for i, r in enumerate(ret):
xc[i], yc[i] = _quadrent_center(r, xlim, ylim)
pts_uv = np.array([xc, yc])
if plot:
from viscid.plot import vlab
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
plt.plot(pts_uv[0],
pts_uv[1],
"y*",
ms=20,
markeredgecolor='k',
markeredgewidth=1.0)
vlt.show(block=False)
vlab.show(stop=True)
# return seed.to_3d(seed.uv_to_local(pts_uv))
# if pts_uv.size == 0:
# return None
if make_3d:
return seed.uv_to_3d(pts_uv)
else:
return pts_uv
else:
return ret
def follow_fluid(dset, initial_seeds, time_slice=slice(None),
curator=None, callback=default_fluid_callback,
speed_scale=1.0, dt=None, tstart=None, tstop=None,
duration=None, dt_interp=None,
v_key='v', anc_keys=(), fld_slc=Ellipsis,
stream_opts={}, callback_kwargs={}):
"""Trace fluid elements
Note:
you want speed_scale if say V is in km/s and x/y/z is in Re ;)
Parameters:
vfile: a vFile object that we can call iter_times on
time_slice: string, slice notation, like 1200:2400:1
initial_seeds: any SeedGen object
plot_function: function that is called each time step,
arguments should be exactly: (i [int], grid, v [Vector
Field], v_lines [result of streamline trace],
root_seeds [SeedGen])
stream_opts: must have ds0 and max_length, maxit will be
automatically calculated
Returns:
root points after following the fluid
"""
curator = SeedCurator() if curator is None else curator
grids = [grid for grid in dset.iter_times(time_slice)]
times = [g.time for g in grids]
slc_range = dset.tslc_range(time_slice)
time_slice_dir = np.sign(times[-1] - times[0]).astype('f')
slice_min_dt = 1.0 if len(times) <= 1 else np.min(np.abs(np.diff(times)))
# figure out direction (forward / backward)
if tstart is not None and tstop is not None:
tdir = np.sign(tstop - tstart).astype('f')
elif (dt is not None and dt < 0) or (duration is not None and duration < 0):
tdir = -1.0
else:
tdir = 1.0 if time_slice_dir == 0.0 else time_slice_dir
# enforce that grids and times arrays are reordered to match tdir
if (tdir > 0 and time_slice_dir < 0) or (tdir < 0 and time_slice_dir > 0):
grids = grids[::-1]
times = times[::-1]
slc_range = slc_range[::-1]
time_slice_dir *= -1
# set tstart and tstop if they're not already given
if tstart is None:
tstart = slc_range[0]
if tstop is None:
if duration is not None:
tstop = tstart + tdir * np.abs(duration)
else:
tstop = slc_range[1]
# set dt if they're not given
dt = np.abs(dt) if dt is not None else slice_min_dt
dt_interp = np.abs(dt_interp) if dt_interp is not None else dt
# ------ main loop
fld_keys = [v_key] + list(anc_keys)
times = np.array(times)
t = tstart
if np.any(np.sign(np.diff(times)) != tdir):
raise RuntimeError("times is not monotonic")
i = 0
seeds = initial_seeds.get_points()
while tdir * (t - tstop) <= 0.0:
idx0 = max(np.sum(tdir * (times - t) < 0.0) - 1, 0)
idx1 = min(idx0 + 1, len(grids) - 1)
time0, grid0 = times[idx0], grids[idx0]
time1, grid1 = times[idx1], grids[idx1]
frac_interp = 0.0 if time0 == time1 else (t - time0) / (time1 - time0)
# get / calculate fields for each key at the current time
if grid0 is grid1:
flds = [grid0[key] for key in fld_keys]
else:
a = frac_interp
b = 1.0 - frac_interp
flds = [viscid.axpby(a, grid0[k][fld_slc], b, grid1[k][fld_slc])
for k in fld_keys]
anc_fields = OrderedDict([(k, v) for k, v in zip(anc_keys, flds[1:])])
t_next_interp = t + tdir * dt_interp
while tdir * (t - t_next_interp) < 0 and tdir * (t - tstop) <= 0.0:
if 'method' not in stream_opts:
stream_opts['method'] = 'rk45'
vpaths = viscid.calc_streamlines(tdir * speed_scale * flds[0], seeds,
max_t=dt,
output=viscid.OUTPUT_STREAMLINES,
stream_dir=viscid.DIR_FORWARD,
**stream_opts)[0]
callback(i, t, seeds=seeds, v_field=flds[0], anc_fields=anc_fields,
grid0=grid0, grid1=grid1, streamlines=vpaths,
**callback_kwargs)
i += 1
# prepare seeds for next iteration
for iseed in range(seeds.shape[1]):
seeds[:, iseed] = vpaths[iseed][:, -1]
seeds = curator.update(flds[0], seeds, time=t)
t += tdir * dt
def _get_sep_pts_bisect(
fld,
seed,
trace_opts=None,
min_depth=3,
max_depth=7,
plot=False,
perimeter_check=perimeter_check_bitwise_or,
make_3d=True,
start_uneven=False,
_base_quadrent="",
_uneven_mask=0,
_first_recurse=True,
):
if len(_base_quadrent) == max_depth:
return [_base_quadrent] # causes pylint to complain
if trace_opts is None:
trace_opts = dict()
nx, ny = seed.uv_shape
(xlim, ylim) = seed.uv_extent
if _first_recurse and start_uneven:
_uneven_mask = UNEVEN_MASK
if _first_recurse and plot:
from viscid.plot import mvi
from viscid.plot import mpl
mpl.clf()
_, all_topo = viscid.calc_streamlines(fld, seed, **trace_opts)
mpl.plot(np.bitwise_and(all_topo, 15), show=False)
verts, arr = seed.wrap_mesh(all_topo.data)
mvi.mesh(verts[0], verts[1], verts[2], scalars=arr, opacity=0.75)
# quadrents and lines are indexed as follows...
# directions are counter clackwise around the quadrent with
# lower index (which matters for lines which are shared among
# more than one quadrent, aka, lines 1,2,6,7). Notice that even
# numbered lines are horizontal, like the interstate system :)
# -<--10-----<-8---
# | ^ ^
# 11 2 9 3 7
# \/ | |
# --<-2-----<-6----
# | ^ ^
# 3 0 1 1 5
# \/ | |
# ----0->-----4->--
# find low(left), mid(center), and high(right) crds in x and y
low_quad = "{0}{1:x}".format(_base_quadrent, 0 | _uneven_mask)
high_quad = "{0}{1:x}".format(_base_quadrent, 3 | _uneven_mask)
xl, xm, yl, ym = _quadrent_limits(low_quad, xlim, ylim)
_, xh, _, yh = _quadrent_limits(high_quad, xlim, ylim)
segsx, segsy = [None] * 12, [None] * 12
topo = [None] * 12
nxm, nym = nx // 2, ny // 2
# make all the line segments
segsx[0], segsy[0] = np.linspace(xl, xm, nxm), np.linspace(yl, yl, nxm)
segsx[1], segsy[1] = np.linspace(xm, xm, nym), np.linspace(yl, ym, nym)
segsx[2], segsy[2] = np.linspace(xm, xl, nxm), np.linspace(ym, ym, nxm)
segsx[3], segsy[3] = np.linspace(xl, xl, nym), np.linspace(ym, yl, nym)
segsx[4], segsy[4] = np.linspace(xm, xh, nxm), np.linspace(yl, yl, nxm)
segsx[5], segsy[5] = np.linspace(xh, xh, nym), np.linspace(yl, ym, nym)
segsx[6], segsy[6] = np.linspace(xh, xm, nxm), np.linspace(ym, ym, nxm)
segsx[7], segsy[7] = np.linspace(xh, xh, nym), np.linspace(ym, yh, nym)
segsx[8], segsy[8] = np.linspace(xh, xm, nxm), np.linspace(yh, yh, nxm)
segsx[9], segsy[9] = np.linspace(xm, xm, nym), np.linspace(ym, yh, nym)
segsx[10], segsy[10] = np.linspace(xm, xl, nxm), np.linspace(yh, yh, nxm)
segsx[11], segsy[11] = np.linspace(xl, xl, nym), np.linspace(yh, ym, nym)
allx = np.concatenate(segsx)
ally = np.concatenate(segsy)
# print("plot::", _base_quadrent, '|', _uneven_mask, '|', len(allx), len(ally))
pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
_, all_topo = viscid.calc_streamlines(fld, pts3d, **trace_opts)
topo[0] = all_topo[: len(segsx[0])]
cnt = len(topo[0])
for i, segx in zip(count(1), segsx[1:]):
topo[i] = all_topo[cnt : cnt + len(segx)]
# print("??", i, cnt, cnt + len(segx), np.bitwise_and.reduce(topo[i]))
cnt += len(topo[i])
# assemble the lines into the four quadrents
quad_topo = [None] * 4
# all arrays snip off the last element since those are
# duplicated by the next line... reversed arrays do the
# snipping with -1:0:-1
quad_topo[0] = np.concatenate([topo[0][:-1], topo[1][:-1], topo[2][:-1], topo[3][:-1]])
quad_topo[1] = np.concatenate([topo[4][:-1], topo[5][:-1], topo[6][:-1], topo[1][-1:0:-1]])
quad_topo[2] = np.concatenate([topo[2][-1:0:-1], topo[9][:-1], topo[10][:-1], topo[11][:-1]])
quad_topo[3] = np.concatenate([topo[6][-1:0:-1], topo[7][:-1], topo[8][:-1], topo[9][-1:0:-1]])
# now that the quad arrays are populated, decide which quadrents
# still contain the separator (could be > 1)
required_uneven_subquads = False
ret = []
for i in range(4):
if perimeter_check(quad_topo[i]):
next_quad = "{0}{1:x}".format(_base_quadrent, i | _uneven_mask)
subquads = _get_sep_pts_bisect(
fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=next_quad,
_uneven_mask=0,
_first_recurse=False,
)
ret += subquads
if len(ret) == 0:
perimeter = np.concatenate(
[
topo[0][::-1],
topo[4][::-1],
topo[5][::-1],
topo[7][::-1],
topo[8][::-1],
topo[10][::-1],
topo[11][::-1],
topo[3][::-1],
]
)
if _uneven_mask:
if len(_base_quadrent) > min_depth:
print("sep trace issue, but min depth reached: {0} > {1}" "".format(len(_base_quadrent), min_depth))
ret = [_base_quadrent]
else:
print("sep trace issue, the separator ended prematurely")
elif perimeter_check(perimeter):
ret = _get_sep_pts_bisect(
fld,
seed,
trace_opts=trace_opts,
min_depth=min_depth,
max_depth=max_depth,
plot=plot,
_base_quadrent=_base_quadrent,
_uneven_mask=UNEVEN_MASK,
_first_recurse=False,
)
required_uneven_subquads = True
if plot and not required_uneven_subquads:
from viscid.plot import mvi
from viscid.plot import mpl
_pts3d = seed.to_3d(seed.uv_to_local(np.array([allx, ally])))
mvi.points3d(_pts3d[0], _pts3d[1], _pts3d[2], all_topo.data.reshape(-1), scale_mode="none", scale_factor=0.02)
mpl.plt.scatter(
allx, ally, color=np.bitwise_and(all_topo, 15), vmin=0, vmax=15, marker="o", edgecolor="y", s=40
)
if _first_recurse:
# turn quadrent strings into locations
xc = np.empty(len(ret))
yc = np.empty(len(ret))
for i, r in enumerate(ret):
xc[i], yc[i] = _quadrent_center(r, xlim, ylim)
pts_uv = np.array([xc, yc])
if plot:
from viscid.plot import mvi
from viscid.plot import mpl
mpl.plt.plot(pts_uv[0], pts_uv[1], "y*", ms=20, markeredgecolor="k", markeredgewidth=1.0)
mpl.show(block=False)
mvi.show(stop=True)
# return seed.to_3d(seed.uv_to_local(pts_uv))
# if pts_uv.size == 0:
# return None
if make_3d:
return seed.uv_to_3d(pts_uv)
else:
return pts_uv
else:
return ret
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
parser.add_argument("--interact", "-i", action="store_true")
args = vutil.common_argparse(parser)
f3d = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[0].xdmf'))
f_iono = viscid.load_file(
os.path.join(sample_dir, "sample_xdmf.iof.[0].xdmf"))
b = f3d["b"]
v = f3d["v"]
pp = f3d["pp"]
e = f3d["e_cc"]
vlab.mlab.options.offscreen = not args.show
vlab.figure(size=(1280, 800))
##########################################################
# make b a dipole inside 3.1Re and set e = 0 inside 4.0Re
cotr = viscid.Cotr(time='1990-03-21T14:48', dip_tilt=0.0) # pylint: disable=not-callable
moment = cotr.get_dipole_moment(crd_system=b)
isphere_mask = viscid.make_spherical_mask(b, rmax=3.1)
viscid.fill_dipole(b, m=moment, mask=isphere_mask)
e_mask = viscid.make_spherical_mask(b, rmax=4.0)
viscid.set_in_region(e, 0.0, alpha=0.0, mask=e_mask, out=e)
######################################
# plot a scalar cut plane of pressure
pp_src = vlab.field2source(pp, center='node')
scp = vlab.scalar_cut_plane(pp_src,
plane_orientation='z_axes',
opacity=0.5,
transparent=True,
view_controls=False,
cmap="inferno",
logscale=True)
scp.implicit_plane.normal = [0, 0, -1]
scp.implicit_plane.origin = [0, 0, 0]
scp.enable_contours = True
scp.contour.filled_contours = True
scp.contour.number_of_contours = 64
cbar = vlab.colorbar(scp, title=pp.name, orientation='vertical')
cbar.scalar_bar_representation.position = (0.01, 0.13)
cbar.scalar_bar_representation.position2 = (0.08, 0.76)
######################################
# plot a vector cut plane of the flow
vcp = vlab.vector_cut_plane(v,
scalars=pp_src,
plane_orientation='z_axes',
view_controls=False,
mode='arrow',
cmap='Greens_r')
vcp.implicit_plane.normal = [0, 0, -1]
vcp.implicit_plane.origin = [0, 0, 0]
##############################
# plot very faint isosurfaces
vx_src = vlab.field2source(v['x'], center='node')
iso = vlab.iso_surface(vx_src,
contours=[0.0],
opacity=0.008,
cmap='Pastel1')
##############################################################
# calculate B field lines && topology in Viscid and plot them
seedsA = viscid.SphericalPatch([0, 0, 0], [2, 0, 1],
30,
15,
r=5.0,
nalpha=5,
nbeta=5)
seedsB = viscid.SphericalPatch([0, 0, 0], [1.9, 0, -20],
30,
15,
r=5.0,
nalpha=1,
nbeta=5)
seeds = np.concatenate([seedsA, seedsB], axis=1)
b_lines, topo = viscid.calc_streamlines(b,
seeds,
ibound=3.5,
obound0=[-25, -20, -20],
obound1=[15, 20, 20],
wrap=True)
vlab.plot_lines(b_lines, scalars=viscid.topology2color(topo))
######################################################################
# plot a random circle at geosynchronus orbit with scalars colored
# by the Matplotlib viridis color map, just because we can; this is
# a useful toy for debugging
circle = viscid.Circle(p0=[0, 0, 0], r=6.618, n=128, endpoint=True)
scalar = np.sin(circle.as_local_coordinates().get_crd('phi'))
surf = vlab.plot_line(circle.get_points(),
scalars=scalar,
clim=0.8,
cmap="Spectral_r")
######################################################################
# Use Mayavi (VTK) to calculate field lines using an interactive seed
# These field lines are colored by E parallel
epar = viscid.project(e, b)
epar.name = "Epar"
bsl2 = vlab.streamline(b,
epar,
seedtype='plane',
seed_resolution=4,
integration_direction='both',
clim=(-0.05, 0.05))
# now tweak the VTK streamlines
bsl2.stream_tracer.maximum_propagation = 20.
bsl2.seed.widget.origin = [-11, -5.0, -2.0]
bsl2.seed.widget.point1 = [-11, 5.0, -2.0]
bsl2.seed.widget.point2 = [-11.0, -5.0, 2.0]
bsl2.streamline_type = 'tube'
bsl2.tube_filter.radius = 0.03
bsl2.stop() # this stop/start was a hack to get something to update
bsl2.start()
bsl2.seed.widget.enabled = False
cbar = vlab.colorbar(bsl2,
title=epar.name,
label_fmt='%.3f',
orientation='horizontal')
cbar.scalar_bar_representation.position = (0.15, 0.01)
cbar.scalar_bar_representation.position2 = (0.72, 0.10)
###############################################################
# Make a contour at the open-closed boundary in the ionosphere
seeds_iono = viscid.Sphere(r=1.063,
pole=-moment,
ntheta=256,
nphi=256,
thetalim=(0, 180),
philim=(0, 360),
crd_system=b)
_, topo_iono = viscid.calc_streamlines(b,
seeds_iono,
ibound=1.0,
nr_procs='all',
output=viscid.OUTPUT_TOPOLOGY)
topo_iono = np.log2(topo_iono)
m = vlab.mesh_from_seeds(seeds_iono,
scalars=topo_iono,
opacity=1.0,
clim=(0, 3),
color=(0.992, 0.445, 0.0))
m.enable_contours = True
m.actor.property.line_width = 4.0
m.contour.number_of_contours = 4
####################################################################
# Plot the ionosphere, note that the sample data has the ionosphere
# at a different time, so the open-closed boundary found above
# will not be consistant with the field aligned currents
fac_tot = 1e9 * f_iono['fac_tot']
m = vlab.plot_ionosphere(fac_tot,
bounding_lat=30.0,
vmin=-300,
vmax=300,
opacity=0.75,
rotate=cotr,
crd_system=b)
m.actor.property.backface_culling = True
########################################################################
# Add some markers for earth, i.e., real earth, and dayside / nightside
# representation
vlab.plot_blue_marble(r=1.0,
lines=False,
ntheta=64,
nphi=128,
rotate=cotr,
crd_system=b)
# now shade the night side with a transparent black hemisphere
vlab.plot_earth_3d(radius=1.01, night_only=True, opacity=0.5, crd_system=b)
####################
# Finishing Touches
# vlab.axes(pp_src, nb_labels=5)
oa = vlab.orientation_axes()
oa.marker.set_viewport(0.75, 0.75, 1.0, 1.0)
# note that resize won't work if the current figure has the
# off_screen_rendering flag set
# vlab.resize([1200, 800])
vlab.view(azimuth=45, elevation=70, distance=35.0, focalpoint=[-2, 0, 0])
##############
# Save Figure
# print("saving png")
# vlab.savefig('mayavi_msphere_sample.png')
# print("saving x3d")
# # x3d files can be turned into COLLADA files with meshlab, and
# # COLLADA (.dae) files can be opened in OS X's preview
# #
# # IMPORTANT: for some reason, using bounding_lat in vlab.plot_ionosphere
# # causes a segfault when saving x3d files
# #
# vlab.savefig('mayavi_msphere_sample.x3d')
# print("done")
vlab.savefig(next_plot_fname(__file__))
###########################
# Interact Programatically
if args.interact:
vlab.interact()
#######################
# Interact Graphically
if args.show:
vlab.show()
try:
vlab.mlab.close()
except AttributeError:
pass
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
b, e = make_arcade(8.0, N=[64, 64, 64])
epar = viscid.project(e, b)
epar.pretty_name = "E parallel"
###############
# Calculate Xi
seeds = viscid.Volume(xl=[-10, 0.0, -10], xh=[10, 0.0, 10], n=[64, 1, 64])
b_lines, _ = viscid.calc_streamlines(b, seeds)
xi_dat = viscid.integrate_along_lines(b_lines, e, reduction='dot')
xi = seeds.wrap_field(xi_dat, name='xi', pretty_name=r"$\Xi$")
################################
# Make 2D Matplotlib plot of Xi
vlt.plot(xi,
x=(-10, 10),
y=(-10, 10),
style='contourf',
levels=256,
lin=(2e-4, 1.5718))
vlt.plot(xi,
x=(-10, 10),
y=(-10, 10),
style='contour',
colors='grey',
levels=[0.5, 1.0])
vlt.savefig(next_plot_fname(__file__))
if args.show:
vlt.show()
############################################################
# Make 3D mayavi plot of Xi and the 'brightest' field lines
# as well as some other field lines for context
try:
from viscid.plot import vlab
except ImportError:
xfail("Mayavi not installed")
vlab.figure(size=[1200, 800], offscreen=not args.show)
inds = np.argsort(xi_dat)[-64:]
inds = np.concatenate([inds, np.arange(len(xi_dat))[::71]])
s = vlab.plot_lines(b_lines[inds], scalars=epar, cmap='viridis')
vlab.mesh_from_seeds(seeds, scalars=xi, cmap='inferno')
vlab.colorbar(s, orientation='horizontal', title=epar.pretty_name)
# vlab.streamline(b, scalars=e, seedtype='sphere', seed_resolution=4,
# integration_direction='both')
oa = vlab.orientation_axes()
oa.marker.set_viewport(0.75, 0.75, 1.0, 1.0)
vlab.view(roll=0,
azimuth=90,
elevation=25,
distance=30.0,
focalpoint=[0, 2, 0])
vlab.savefig(next_plot_fname(__file__))
if args.show:
vlab.show()
try:
vlab.mlab.close()
except AttributeError:
pass
return 0
def follow_fluid(dset,
initial_seeds,
time_slice=slice(None),
curator=None,
callback=default_fluid_callback,
speed_scale=1.0,
dt=None,
tstart=None,
tstop=None,
duration=None,
dt_interp=None,
v_key='v',
anc_keys=(),
fld_slc=Ellipsis,
stream_opts={},
callback_kwargs={}):
"""Trace fluid elements
Note:
you want speed_scale if say V is in km/s and x/y/z is in Re ;)
Parameters:
vfile: a vFile object that we can call iter_times on
time_slice: string, slice notation, like 1200:2400:1
initial_seeds: any SeedGen object
plot_function: function that is called each time step,
arguments should be exactly: (i [int], grid, v [Vector
Field], v_lines [result of streamline trace],
root_seeds [SeedGen])
stream_opts: must have ds0 and max_length, maxit will be
automatically calculated
Returns:
root points after following the fluid
"""
curator = SeedCurator() if curator is None else curator
grids = [grid for grid in dset.iter_times(time_slice)]
times = [g.time for g in grids]
slc_range = dset.tslc_range(time_slice)
time_slice_dir = np.sign(times[-1] - times[0]).astype('f')
slice_min_dt = 1.0 if len(times) <= 1 else np.min(np.abs(np.diff(times)))
# figure out direction (forward / backward)
if tstart is not None and tstop is not None:
tdir = np.sign(tstop - tstart).astype('f')
elif (dt is not None and dt < 0) or (duration is not None
and duration < 0):
tdir = -1.0
else:
tdir = 1.0 if time_slice_dir == 0.0 else time_slice_dir
# enforce that grids and times arrays are reordered to match tdir
if (tdir > 0 and time_slice_dir < 0) or (tdir < 0 and time_slice_dir > 0):
grids = grids[::-1]
times = times[::-1]
slc_range = slc_range[::-1]
time_slice_dir *= -1
# set tstart and tstop if they're not already given
if tstart is None:
tstart = slc_range[0]
if tstop is None:
if duration is not None:
tstop = tstart + tdir * np.abs(duration)
else:
tstop = slc_range[1]
# set dt if they're not given
dt = np.abs(dt) if dt is not None else slice_min_dt
dt_interp = np.abs(dt_interp) if dt_interp is not None else dt
# ------ main loop
fld_keys = [v_key] + list(anc_keys)
times = np.array(times)
t = tstart
if np.any(np.sign(np.diff(times)) != tdir):
raise RuntimeError("times is not monotonic")
i = 0
seeds = initial_seeds.get_points()
while tdir * (t - tstop) <= 0.0:
idx0 = max(np.sum(tdir * (times - t) < 0.0) - 1, 0)
idx1 = min(idx0 + 1, len(grids) - 1)
time0, grid0 = times[idx0], grids[idx0]
time1, grid1 = times[idx1], grids[idx1]
frac_interp = 0.0 if time0 == time1 else (t - time0) / (time1 - time0)
# get / calculate fields for each key at the current time
if grid0 is grid1:
flds = [grid0[key] for key in fld_keys]
else:
a = frac_interp
b = 1.0 - frac_interp
flds = [
viscid.axpby(a, grid0[k][fld_slc], b, grid1[k][fld_slc])
for k in fld_keys
]
anc_fields = OrderedDict([(k, v) for k, v in zip(anc_keys, flds[1:])])
t_next_interp = t + tdir * dt_interp
while tdir * (t - t_next_interp) < 0 and tdir * (t - tstop) <= 0.0:
if 'method' not in stream_opts:
stream_opts['method'] = 'rk45'
vpaths = viscid.calc_streamlines(tdir * speed_scale * flds[0],
seeds,
max_t=dt,
output=viscid.OUTPUT_STREAMLINES,
stream_dir=viscid.DIR_FORWARD,
**stream_opts)[0]
callback(i,
t,
seeds=seeds,
v_field=flds[0],
anc_fields=anc_fields,
grid0=grid0,
grid1=grid1,
streamlines=vpaths,
**callback_kwargs)
i += 1
# prepare seeds for next iteration
for iseed in range(seeds.shape[1]):
seeds[:, iseed] = vpaths[iseed][:, -1]
seeds = curator.update(flds[0], seeds, time=t)
t += tdir * dt
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():
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
