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 _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 get_mp_info(pp, b, j, e, cache=True, cache_dir=None,
slc="x=5.5j:11.0j, y=-4.0j:4.0j, z=-3.6j:3.6j",
fit="mp_xloc", fit_p0=(9.0, 0.0, 0.0, 1.0, -1.0, -1.0)):
"""Get info about m-pause as flattened fields
Notes:
The first thing this function does is mask locations where
the GSE-y current density < 1e-4. This masks out the bow
shock and current free regions. This works for southward IMF,
but it is not very general.
Parameters:
pp (ScalarcField): pressure
b (VectorField): magnetic field
j (VectorField): current density
e (VectorField, None): electric field (same centering as b). If
None, then the info that requires E will be filled with NaN
cache (bool, str): Save to and load from cache, if "force",
then don't load from cache if it exists, but do save a
cache at the end
cache_dir (str): Directory for cache, if None, same directory
as that file to which the grid belongs
slc (str): slice that gives a box that contains the m-pause
fit (str): to which resulting field should the paraboloid be fit,
defaults to mp_xloc, but pp_max_xloc might be useful in some
circumstances
fit_p0 (tuple): Initial guess vector for paraboloid fit
Returns:
dict: Unless otherwise noted, the entiries are 2D (y-z) fields
- **mp_xloc** location of minimum abs(Bz), this works
better than max of J^2 for FTEs
- **mp_sheath_edge** location where Jy > 0.1 * Jy when
coming in from the sheath side
- **mp_sphere_edge** location where Jy > 0.1 * Jy when
coming in from the sphere side
- **mp_width** difference between m-sheath edge and
msphere edge
- **mp_shear** magnetic shear taken 6 grid points into
the m-sheath / m-sphere
- **pp_max** max pp
- **pp_max_xloc** location of max pp
- **epar_max** max e parallel
- **epar_max_xloc** location of max e parallel
- **paraboloid** numpy.recarray of paraboloid fit. The
parameters are given in the 0th element, and
the 1st element contains the 1-sigma values for the fit
Raises:
RuntimeError: if using MHD crds instead of GSE crds
"""
if not cache_dir:
cache_dir = pp.find_info("_viscid_dirname", "./")
run_name = pp.find_info("run", None)
if cache and run_name:
t = pp.time
mp_fname = "{0}/{1}.mpause.{2:06.0f}".format(cache_dir, run_name, t)
else:
mp_fname = ""
try:
force = cache.strip().lower() == "force"
except AttributeError:
force = False
try:
if force or not mp_fname or not os.path.isfile(mp_fname + ".xdmf"):
raise IOError()
mp_info = {}
with viscid.load_file(mp_fname + ".xdmf") as dat:
fld_names = ["mp_xloc", "mp_sheath_edge", "mp_sphere_edge",
"mp_width", "mp_shear", "pp_max", "pp_max_xloc",
"epar_max", "epar_max_xloc"]
for fld_name in fld_names:
mp_info[fld_name] = dat[fld_name]["x=0"]
except (IOError, KeyError):
mp_info = {}
crd_system = viscid.as_crd_system(b, None)
if crd_system != 'gse':
raise RuntimeError("get_mp_info can't work in MHD crds, "
"switch to GSE please")
if j.nr_patches == 1:
pp_block = pp[slc]
b_block = b[slc]
j_block = j[slc]
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = e[slc]
else:
# interpolate an amr grid so we can proceed
obnd = pp.get_slice_extent(slc)
dx = np.min(pp.skeleton.L / pp.skeleton.n, axis=0)
nx = np.ceil((obnd[1] - obnd[0]) / dx)
vol = viscid.seed.Volume(obnd[0], obnd[1], nx, cache=True)
pp_block = vol.wrap_field(viscid.interp_trilin(pp, vol),
name="P").as_cell_centered()
b_block = vol.wrap_field(viscid.interp_trilin(b, vol),
name="B").as_cell_centered()
j_block = vol.wrap_field(viscid.interp_trilin(j, vol),
name="J").as_cell_centered()
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = vol.wrap_field(viscid.interp_trilin(e, vol),
name="E").as_cell_centered()
# jsq = viscid.dot(j_block, j_block)
bsq = viscid.dot(b_block, b_block)
# extract ndarrays and mask out bow shock / current free regions
maskval = 1e-4
jy_mask = j_block['y'].data < maskval
masked_bsq = 1.0 * bsq
masked_bsq.data = np.ma.masked_where(jy_mask, bsq)
xcc = j_block.get_crd_cc('x')
nx = len(xcc)
mp_xloc = np.argmin(masked_bsq, axis=0) # indices
mp_xloc = mp_xloc.wrap(xcc[mp_xloc.data]) # location
pp_max = np.max(pp_block, axis=0)
pp_max_xloc = np.argmax(pp_block, axis=0) # indices
pp_max_xloc = pp_max_xloc.wrap(xcc[pp_max_xloc.data]) # location
epar = viscid.project(e_block, b_block)
epar_max = np.max(epar, axis=0)
epar_max_xloc = np.argmax(epar, axis=0) # indices
epar_max_xloc = pp_max_xloc.wrap(xcc[epar_max_xloc.data]) # location
_ret = find_mp_edges(j_block, 0.1, 0.1, maskval=maskval)
sheath_edge, msphere_edge, mp_width, sheath_ind, sphere_ind = _ret
# extract b and b**2 at sheath + 6 grid points and sphere - 6 grid pointns
# clipping cases where things go outside the block. clipped ponints are
# set to nan
step = 6
# extract b
if b_block.layout == "flat":
comp_axis = 0
ic, _, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ic, ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ic, ix, iy, iz]
elif b_block.layout == "interlaced":
comp_axis = 3
_, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape[:-1]])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ix, iy, iz]
# extract b**2
bmag_sheath = np.sqrt(np.sum(b_sheath**2, axis=comp_axis))
bmag_sphere = np.sqrt(np.sum(b_sphere**2, axis=comp_axis))
costheta = (np.sum(b_sheath * b_sphere, axis=comp_axis) /
(bmag_sphere * bmag_sheath))
costheta = np.where((sheath_ind + step < nx) & (sphere_ind - step >= 0),
costheta, np.nan)
mp_shear = mp_width.wrap((180.0 / np.pi) * np.arccos(costheta))
# don't bother with pretty name since it's not written to file
# plane_crds = b_block.crds.slice_keep('x=0', cc=True)
# fld_kwargs = dict(center="Cell", time=b.time)
mp_width.name = "mp_width"
mp_xloc.name = "mp_xloc"
sheath_edge.name = "mp_sheath_edge"
msphere_edge.name = "mp_sphere_edge"
mp_shear.name = "mp_shear"
pp_max.name = "pp_max"
pp_max_xloc.name = "pp_max_xloc"
epar_max.name = "epar_max"
epar_max_xloc.name = "epar_max_xloc"
mp_info = {}
mp_info["mp_width"] = mp_width
mp_info["mp_xloc"] = mp_xloc
mp_info["mp_sheath_edge"] = sheath_edge
mp_info["mp_sphere_edge"] = msphere_edge
mp_info["mp_shear"] = mp_shear
mp_info["pp_max"] = pp_max
mp_info["pp_max_xloc"] = pp_max_xloc
mp_info["epar_max"] = epar_max
mp_info["epar_max_xloc"] = epar_max_xloc
# cache new fields to disk
if mp_fname:
viscid.save_fields(mp_fname + ".h5", list(mp_info.values()))
try:
_paraboloid_params = fit_paraboloid(mp_info[fit], p0=fit_p0)
mp_info["paraboloid"] = _paraboloid_params
except ImportError as _exception:
try:
msg = _exception.message
except AttributeError:
msg = _exception.msg
mp_info["paraboloid"] = viscid.DeferredImportError(msg)
mp_info["mp_width"].pretty_name = "Magnetopause Width"
mp_info["mp_xloc"].pretty_name = "Magnetopause $X_{gse}$ Location"
mp_info["mp_sheath_edge"].pretty_name = "Magnetosheath Edge"
mp_info["mp_sphere_edge"].pretty_name = "Magnetosphere Edge"
mp_info["mp_shear"].pretty_name = "Magnetic Shear"
mp_info["pp_max"].pretty_name = "Max Pressure"
mp_info["pp_max_xloc"].pretty_name = "Max Pressure Location"
mp_info["epar_max"].pretty_name = "Max E Parallel"
mp_info["epar_max_xloc"].pretty_name = "Max E Parallel Location"
return mp_info
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 get_mp_info(pp,
b,
j,
e,
cache=True,
cache_dir=None,
slc="x=5.5f:11.0f, y=-4.0f:4.0f, z=-3.6f:3.6f",
fit="mp_xloc",
fit_p0=(9.0, 0.0, 0.0, 1.0, -1.0, -1.0)):
"""Get info about m-pause as flattened fields
Notes:
The first thing this function does is mask locations where
the GSE-y current density < 1e-4. This masks out the bow
shock and current free regions. This works for southward IMF,
but it is not very general.
Parameters:
pp (ScalarcField): pressure
b (VectorField): magnetic field
j (VectorField): current density
e (VectorField, None): electric field (same centering as b). If
None, then the info that requires E will be filled with NaN
cache (bool, str): Save to and load from cache, if "force",
then don't load from cache if it exists, but do save a
cache at the end
cache_dir (str): Directory for cache, if None, same directory
as that file to which the grid belongs
slc (str): slice that gives a box that contains the m-pause
fit (str): to which resulting field should the paraboloid be fit,
defaults to mp_xloc, but pp_max_xloc might be useful in some
circumstances
fit_p0 (tuple): Initial guess vector for paraboloid fit
Returns:
dict: Unless otherwise noted, the entiries are 2D (y-z) fields
- **mp_xloc** location of minimum abs(Bz), this works
better than max of J^2 for FTEs
- **mp_sheath_edge** location where Jy > 0.1 * Jy when
coming in from the sheath side
- **mp_sphere_edge** location where Jy > 0.1 * Jy when
coming in from the sphere side
- **mp_width** difference between m-sheath edge and
msphere edge
- **mp_shear** magnetic shear taken 6 grid points into
the m-sheath / m-sphere
- **pp_max** max pp
- **pp_max_xloc** location of max pp
- **epar_max** max e parallel
- **epar_max_xloc** location of max e parallel
- **paraboloid** numpy.recarray of paraboloid fit. The
parameters are given in the 0th element, and
the 1st element contains the 1-sigma values for the fit
Raises:
RuntimeError: if using MHD crds instead of GSE crds
"""
if not cache_dir:
cache_dir = pp.find_info("_viscid_dirname", "./")
run_name = pp.find_info("run", None)
if cache and run_name:
t = pp.time
mp_fname = "{0}/{1}.mpause.{2:06.0f}".format(cache_dir, run_name, t)
else:
mp_fname = ""
try:
force = cache.strip().lower() == "force"
except AttributeError:
force = False
try:
if force or not mp_fname or not os.path.isfile(mp_fname + ".xdmf"):
raise IOError()
mp_info = {}
with viscid.load_file(mp_fname + ".xdmf") as dat:
fld_names = [
"mp_xloc", "mp_sheath_edge", "mp_sphere_edge", "mp_width",
"mp_shear", "pp_max", "pp_max_xloc", "epar_max",
"epar_max_xloc"
]
for fld_name in fld_names:
mp_info[fld_name] = dat[fld_name]["x=0"]
except (IOError, KeyError):
mp_info = {}
crd_system = viscid.as_crd_system(b, None)
if crd_system != 'gse':
raise RuntimeError("get_mp_info can't work in MHD crds, "
"switch to GSE please")
if j.nr_patches == 1:
pp_block = pp[slc]
b_block = b[slc]
j_block = j[slc]
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = e[slc]
else:
# interpolate an amr grid so we can proceed
obnd = pp.get_slice_extent(slc)
dx = np.min(pp.skeleton.L / pp.skeleton.n, axis=0)
nx = np.ceil((obnd[1] - obnd[0]) / dx)
vol = viscid.seed.Volume(obnd[0], obnd[1], nx, cache=True)
pp_block = vol.wrap_field(viscid.interp_trilin(pp, vol),
name="P").as_cell_centered()
b_block = vol.wrap_field(viscid.interp_trilin(b, vol),
name="B").as_cell_centered()
j_block = vol.wrap_field(viscid.interp_trilin(j, vol),
name="J").as_cell_centered()
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = vol.wrap_field(viscid.interp_trilin(e, vol),
name="E").as_cell_centered()
# jsq = viscid.dot(j_block, j_block)
bsq = viscid.dot(b_block, b_block)
# extract ndarrays and mask out bow shock / current free regions
maskval = 1e-4
jy_mask = j_block['y'].data < maskval
masked_bsq = 1.0 * bsq
masked_bsq.data = np.ma.masked_where(jy_mask, bsq)
xcc = j_block.get_crd_cc('x')
nx = len(xcc)
mp_xloc = np.argmin(masked_bsq, axis=0) # indices
mp_xloc = mp_xloc.wrap(xcc[mp_xloc.data]) # location
pp_max = np.max(pp_block, axis=0)
pp_max_xloc = np.argmax(pp_block, axis=0) # indices
pp_max_xloc = pp_max_xloc.wrap(xcc[pp_max_xloc.data]) # location
epar = viscid.project(e_block, b_block)
epar_max = np.max(epar, axis=0)
epar_max_xloc = np.argmax(epar, axis=0) # indices
epar_max_xloc = pp_max_xloc.wrap(xcc[epar_max_xloc.data]) # location
_ret = find_mp_edges(j_block, 0.1, 0.1, maskval=maskval)
sheath_edge, msphere_edge, mp_width, sheath_ind, sphere_ind = _ret
# extract b and b**2 at sheath + 6 grid points and sphere - 6 grid pointns
# clipping cases where things go outside the block. clipped ponints are
# set to nan
step = 6
# extract b
if b_block.layout == "flat":
comp_axis = 0
ic, _, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ic, ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ic, ix, iy, iz]
elif b_block.layout == "interlaced":
comp_axis = 3
_, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape[:-1]])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ix, iy, iz]
# extract b**2
bmag_sheath = np.sqrt(np.sum(b_sheath**2, axis=comp_axis))
bmag_sphere = np.sqrt(np.sum(b_sphere**2, axis=comp_axis))
costheta = (np.sum(b_sheath * b_sphere, axis=comp_axis) /
(bmag_sphere * bmag_sheath))
costheta = np.where(
(sheath_ind + step < nx) & (sphere_ind - step >= 0), costheta,
np.nan)
mp_shear = mp_width.wrap((180.0 / np.pi) * np.arccos(costheta))
# don't bother with pretty name since it's not written to file
# plane_crds = b_block.crds.slice_keep('x=0', cc=True)
# fld_kwargs = dict(center="Cell", time=b.time)
mp_width.name = "mp_width"
mp_xloc.name = "mp_xloc"
sheath_edge.name = "mp_sheath_edge"
msphere_edge.name = "mp_sphere_edge"
mp_shear.name = "mp_shear"
pp_max.name = "pp_max"
pp_max_xloc.name = "pp_max_xloc"
epar_max.name = "epar_max"
epar_max_xloc.name = "epar_max_xloc"
mp_info = {}
mp_info["mp_width"] = mp_width
mp_info["mp_xloc"] = mp_xloc
mp_info["mp_sheath_edge"] = sheath_edge
mp_info["mp_sphere_edge"] = msphere_edge
mp_info["mp_shear"] = mp_shear
mp_info["pp_max"] = pp_max
mp_info["pp_max_xloc"] = pp_max_xloc
mp_info["epar_max"] = epar_max
mp_info["epar_max_xloc"] = epar_max_xloc
# cache new fields to disk
if mp_fname:
viscid.save_fields(mp_fname + ".h5", mp_info.values())
try:
_paraboloid_params = fit_paraboloid(mp_info[fit], p0=fit_p0)
mp_info["paraboloid"] = _paraboloid_params
except ImportError as _exception:
try:
msg = _exception.message
except AttributeError:
msg = _exception.msg
mp_info["paraboloid"] = viscid.DeferredImportError(msg)
mp_info["mp_width"].pretty_name = "Magnetopause Width"
mp_info["mp_xloc"].pretty_name = "Magnetopause $X_{gse}$ Location"
mp_info["mp_sheath_edge"].pretty_name = "Magnetosheath Edge"
mp_info["mp_sphere_edge"].pretty_name = "Magnetosphere Edge"
mp_info["mp_shear"].pretty_name = "Magnetic Shear"
mp_info["pp_max"].pretty_name = "Max Pressure"
mp_info["pp_max_xloc"].pretty_name = "Max Pressure Location"
mp_info["epar_max"].pretty_name = "Max E Parallel"
mp_info["epar_max_xloc"].pretty_name = "Max E Parallel Location"
return mp_info
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