def run_test(fld, seeds, plot2d=True, plot3d=True, add_title="",
view_kwargs=None, show=False, scatter_mpl=False, mesh_mvi=True):
interpolated_fld = viscid.interp_trilin(fld, seeds)
seed_name = seeds.__class__.__name__
if add_title:
seed_name += " " + add_title
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
# plt.plot(seeds.get_points()[2, :], fld)
mpl_plot_kwargs = dict()
if interpolated_fld.is_spherical():
mpl_plot_kwargs['hemisphere'] = 'north'
vlt.plot(interpolated_fld, **mpl_plot_kwargs)
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if show:
plt.show()
if scatter_mpl:
plt.clf()
vlt.plot2d_line(seeds.get_points(), fld, symdir='z', marker='o')
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
_ = get_mvi_fig(offscreen=not show)
try:
if mesh_mvi:
mesh = vlab.mesh_from_seeds(seeds, scalars=interpolated_fld)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
pts = seeds.get_points()
p = vlab.points3d(pts[0], pts[1], pts[2], interpolated_fld.flat_data,
scale_mode='none', scale_factor=0.02)
vlab.axes(p)
vlab.title(seed_name)
if view_kwargs:
vlab.view(**view_kwargs)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show(stop=True)
except ImportError:
pass
def do_test(lines, scalars, show=False, txt=""):
viscid.logger.info('--> ' + txt)
title = txt + '\n' + "\n".join(
textwrap.wrap("scalars = {0}".format(scalars), width=50))
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
vlt.clf()
vlt.plot_lines(lines, scalars=scalars)
plt.title(title)
vlt.savefig(next_plot_fname(__file__, series='q2'))
if show:
vlt.show()
except ImportError:
pass
try:
from mayavi import mlab
vlab, _ = get_mvi_fig()
vlab.clf()
vlab.plot_lines3d(lines, scalars=scalars)
vlab.fancy_axes()
mlab.text(0.05, 0.05, title)
vlab.savefig(next_plot_fname(__file__, series='q3'))
if show:
vlab.show(stop=True)
except ImportError:
pass
def run_test(fld, seeds, plot2d=True, plot3d=True, add_title="",
view_kwargs=None, show=False, scatter_mpl=False, mesh_mvi=True):
interpolated_fld = viscid.interp_trilin(fld, seeds)
seed_name = seeds.__class__.__name__
if add_title:
seed_name += " " + add_title
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
# plt.plot(seeds.get_points()[2, :], fld)
mpl_plot_kwargs = dict()
if interpolated_fld.is_spherical():
mpl_plot_kwargs['hemisphere'] = 'north'
vlt.plot(interpolated_fld, **mpl_plot_kwargs)
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if show:
plt.show()
if scatter_mpl:
plt.clf()
vlt.plot2d_line(seeds.get_points(), fld, symdir='z', marker='o')
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()
try:
if mesh_mvi:
mesh = vlab.mesh_from_seeds(seeds, scalars=interpolated_fld)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
pts = seeds.get_points()
p = vlab.points3d(pts[0], pts[1], pts[2], interpolated_fld.flat_data,
scale_mode='none', scale_factor=0.02)
vlab.axes(p)
vlab.title(seed_name)
if view_kwargs:
vlab.view(**view_kwargs)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show(stop=True)
except ImportError:
pass
def run_test(_fld, _seeds, plot2d=True, plot3d=True, title='', show=False,
**kwargs):
lines, topo = viscid.calc_streamlines(_fld, _seeds, **kwargs)
topo_color = viscid.topology2color(topo)
# downsample lines for plotting
lines = [line[:, ::8] for line in lines]
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
vlt.plot2d_lines(lines, scalars=topo_color, symdir='y', marker='^')
if title:
plt.title(title)
plt.savefig(next_plot_fname(__file__, series='2d'))
if show:
plt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import vlab
try:
fig = _global_ns['figure']
vlab.clf()
except KeyError:
fig = vlab.figure(size=[1200, 800], offscreen=not show,
bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
_global_ns['figure'] = fig
fld_mag = np.log(viscid.magnitude(_fld))
try:
# note: mayavi.mlab.mesh can't take color tuples as scalars
# so one can't use topo_color on a mesh surface. This
# is a limitation of mayavi. To actually plot a specific
# set of colors on a mesh, one must use a texture
mesh = vlab.mesh_from_seeds(_seeds, scalars=topo, opacity=0.6)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
vlab.plot_lines(lines, scalars=fld_mag, tube_radius=0.01,
cmap='viridis')
if title:
vlab.title(title)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show()
except ImportError:
pass
def run_test(fld, seeds, plot2d=True, plot3d=True, add_title="",
view_kwargs=None, show=False):
interpolated_fld = viscid.interp_trilin(fld, seeds)
seed_name = seeds.__class__.__name__
if add_title:
seed_name += " " + add_title
try:
if not plot2d:
raise ImportError
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
plt.clf()
# plt.plot(seeds.get_points()[2, :], fld)
mpl_plot_kwargs = dict()
if interpolated_fld.is_spherical():
mpl_plot_kwargs['hemisphere'] = 'north'
vlt.plot(interpolated_fld, **mpl_plot_kwargs)
plt.title(seed_name)
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)
_global_ns['figure'] = fig
try:
mesh = vlab.mesh_from_seeds(seeds, scalars=interpolated_fld)
mesh.actor.property.backface_culling = True
except RuntimeError:
pass
pts = seeds.get_points()
p = vlab.points3d(pts[0], pts[1], pts[2], interpolated_fld.flat_data,
scale_mode='none', scale_factor=0.02)
vlab.axes(p)
vlab.title(seed_name)
if view_kwargs:
vlab.view(**view_kwargs)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if show:
vlab.show()
except ImportError:
pass
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 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 _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():
try:
# raise ImportError
from viscid.plot import vlab
_HAS_MVI = True
except ImportError:
_HAS_MVI = False
def _test(_p1, _p2, r1=None, r2=None, color=(0.8, 0.8, 0.8)):
if r1 is not None:
_p1 = r1 * np.asarray(_p1) / np.linalg.norm(_p1)
if r2 is not None:
_p2 = r2 * np.asarray(_p2) / np.linalg.norm(_p2)
circ = great_circle(_p1, _p2)
if not np.all(np.isclose(circ[:, 0], _p1)):
print("!! great circle error P1:", _p1, ", P2:", _p2)
print(" first_point:", circ[:, 0], "!= P1")
if not np.all(np.isclose(circ[:, -1], _p2)):
print("!! great circle error P1:", _p1, ", P2:", _p2)
print(" last_point:", circ[:, -1], "!= P2")
if _HAS_MVI:
vlab.plot_lines([circ], tube_radius=0.02, color=color)
print("TEST 1")
_test([1, 0, 0], [0, 1, 0], r1=1.0, r2=1.0, color=(0.8, 0.8, 0.2))
print("TEST 2")
_test([1, 0, 0], [-1, 0, 0], r1=1.0, r2=1.0, color=(0.2, 0.8, 0.8))
print("TEST 3")
_test([1, 1, 0.01], [-1, -1, 0.01], r1=1.0, r2=1.5, color=(0.8, 0.2, 0.8))
print("TEST 4")
_test([-0.9947146, 1.3571029, 2.6095123],
[-0.3371437, -1.5566425, 2.6634643],
color=(0.8, 0.2, 0.2))
print("TEST 5")
_test([0.9775307, -1.3741084, 2.6030273],
[0.3273931, 1.5570284, 2.6652965],
color=(0.2, 0.2, 0.8))
if _HAS_MVI:
vlab.plot_blue_marble(r=1.0, lines=False, ntheta=64, nphi=128)
vlab.plot_earth_3d(radius=1.01, night_only=True, opacity=0.5)
vlab.show()
return 0
def _main():
try:
# raise ImportError
from viscid.plot import vlab
_HAS_MVI = True
except ImportError:
_HAS_MVI = False
def _test(_p1, _p2, r1=None, r2=None, color=(0.8, 0.8, 0.8)):
if r1 is not None:
_p1 = r1 * np.asarray(_p1) / np.linalg.norm(_p1)
if r2 is not None:
_p2 = r2 * np.asarray(_p2) / np.linalg.norm(_p2)
circ = great_circle(_p1, _p2)
if not np.all(np.isclose(circ[:, 0], _p1)):
print("!! great circle error P1:", _p1, ", P2:", _p2)
print(" first_point:", circ[:, 0], "!= P1")
if not np.all(np.isclose(circ[:, -1], _p2)):
print("!! great circle error P1:", _p1, ", P2:", _p2)
print(" last_point:", circ[:, -1], "!= P2")
if _HAS_MVI:
vlab.plot_lines([circ], tube_radius=0.02, color=color)
print("TEST 1")
_test([1, 0, 0], [0, 1, 0], r1=1.0, r2=1.0, color=(0.8, 0.8, 0.2))
print("TEST 2")
_test([1, 0, 0], [-1, 0, 0], r1=1.0, r2=1.0, color=(0.2, 0.8, 0.8))
print("TEST 3")
_test([1, 1, 0.01], [-1, -1, 0.01], r1=1.0, r2=1.5, color=(0.8, 0.2, 0.8))
print("TEST 4")
_test([-0.9947146, 1.3571029, 2.6095123], [-0.3371437, -1.5566425, 2.6634643],
color=(0.8, 0.2, 0.2))
print("TEST 5")
_test([0.9775307, -1.3741084, 2.6030273], [0.3273931, 1.5570284, 2.6652965],
color=(0.2, 0.2, 0.8))
if _HAS_MVI:
vlab.plot_blue_marble(r=1.0, lines=False, ntheta=64, nphi=128)
vlab.plot_earth_3d(radius=1.01, night_only=True, opacity=0.5)
vlab.show()
return 0
def do_test(lines, scalars, show=False, txt=""):
viscid.logger.info('--> ' + txt)
title = txt + '\n' + "\n".join(textwrap.wrap("scalars = {0}".format(scalars),
width=50))
try:
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
vlt.clf()
vlt.plot_lines(lines, scalars=scalars)
plt.title(title)
vlt.savefig(next_plot_fname(__file__, series='q2'))
if show:
vlt.show()
except ImportError:
pass
try:
from mayavi import mlab
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
vlab.clf()
vlab.plot_lines3d(lines, scalars=scalars)
vlab.fancy_axes()
mlab.text(0.05, 0.05, title)
vlab.savefig(next_plot_fname(__file__, series='q3'))
if show:
vlab.show(stop=True)
except ImportError:
pass
def do_test(lines, scalars, show=False, txt=""):
viscid.logger.info('--> ' + txt)
title = txt + '\n' + "\n".join(textwrap.wrap("scalars = {0}".format(scalars),
width=50))
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
vlt.clf()
vlt.plot_lines(lines, scalars=scalars)
plt.title(title)
vlt.savefig(next_plot_fname(__file__, series='q2'))
if show:
vlt.show()
except ImportError:
pass
try:
from mayavi import mlab
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
vlab.clf()
vlab.plot_lines3d(lines, scalars=scalars)
vlab.fancy_axes()
mlab.text(0.05, 0.05, title)
vlab.savefig(next_plot_fname(__file__, series='q3'))
if show:
vlab.show(stop=True)
except ImportError:
pass
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 viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
_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 viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
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 _main():
global offscreen_vlab
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# plot2d = True
# plot3d = True
# args.show = True
offscreen_vlab = not args.show
img = np.load(os.path.join(sample_dir, "logo.npy"))
x = np.linspace(-1, 1, img.shape[0])
y = np.linspace(-1, 1, img.shape[1])
z = np.linspace(-1, 1, img.shape[2])
logo = viscid.arrays2field([x, y, z], img)
if 1:
viscid.logger.info('Testing Point with custom local coordinates...')
pts = np.vstack([[-1, -0.5, 0, 0.5, 1],
[-1, -0.5, 0, 0.5, 1],
[ 0, 0.5, 1, 1.5, 2]])
local_crds = viscid.asarray_datetime64([0, 60, 120, 180, 240],
conservative=True)
seeds = viscid.Point(pts, local_crds=local_crds)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Line...')
seeds = viscid.Line([-1, -1, 0], [1, 1, 2], n=5)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Plane...')
seeds = viscid.Plane([0.0, 0.0, 0.0], [1, 1, 1], [1, 0, 0], 2, 2,
nl=160, nm=170, NL_are_vectors=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Volume...')
seeds = viscid.Volume([-0.8, -0.8, -0.8], [0.8, 0.8, 0.8],
n=[64, 64, 3])
# note: can't make a 2d plot of the volume w/o a slice
run_test(logo, seeds, plot2d=False, plot3d=plot3d, add_title="3d",
show=args.show)
if 1:
viscid.logger.info('Testing Volume (with ignorable dim)...')
seeds = viscid.Volume([-0.8, -0.8, 0.0], [0.8, 0.8, 0.0],
n=[64, 64, 1])
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="2d",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (phi, theta)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (theta, phi)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (phi, theta)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (theta, phi)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Patch...')
seeds = viscid.SphericalPatch(p0=[0, 0, 0], p1=[0, -0, -1],
max_alpha=30.0, max_beta=59.9,
nalpha=65, nbeta=80, r=0.5, roll=45.0)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
# this spline test is very custom
viscid.logger.info('Testing Spline...')
try:
import scipy.interpolate as interpolate
except ImportError:
msg = "XFail: ImportError (is scipy installed?)"
if plot2d:
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
plt.annotate(msg, xy=(0.3, 0.4), xycoords='axes fraction')
plt.savefig(next_plot_fname(__file__, series='2d'))
plt.savefig(next_plot_fname(__file__, series='2d'))
plt.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
plt.show()
except ImportError:
pass
else:
knots = np.array([[ 0.2, 0.5, 0.0], [-0.2, 0.5, 0.2],
[-0.2, 0.0, 0.4], [ 0.2, 0.0, 0.2],
[ 0.2, -0.5, 0.0], [-0.2, -0.5, 0.2]]).T
seed_name = "Spline"
fld = logo
seeds = viscid.Spline(knots)
seed_pts = seeds.get_points()
interp_fld = viscid.interp_trilin(fld, seeds)
if plot2d:
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
vlt.plot(interp_fld)
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
plt.show()
plt.clf()
from matplotlib import rcParams
_ms = rcParams['lines.markersize']
plt.gca().scatter(knots[0, :], knots[1, :],
s=(2 * _ms)**2, marker='^', color='y')
plt.gca().scatter(seed_pts[0, :], seed_pts[1, :],
s=(1.5 * _ms)**2, marker='o', color='k')
vlt.plot2d_line(seed_pts, scalars=interp_fld.flat_data,
symdir='z')
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
plt.show()
except ImportError:
pass
if plot3d:
try:
vlab, _ = get_mvi_fig()
vlab.points3d(knots[0], knots[1], knots[2],
color=(1.0, 1.0, 0), scale_mode='none',
scale_factor=0.04)
p = vlab.points3d(seed_pts[0], seed_pts[1], seed_pts[2],
color=(0, 0, 0), scale_mode='none',
scale_factor=0.03)
vlab.plot_line(seed_pts, scalars=interp_fld.flat_data,
tube_radius=0.01)
vlab.axes(p)
vlab.title(seed_name)
vlab.mlab.roll(-90.0)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
vlab.show(stop=True)
except ImportError:
pass
if 1:
viscid.logger.info('Testing RectilinearMeshPoints...')
f = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[-1].xdmf'))
slc = 'x=-40j:12j, y=-10j:10j, z=-10j:10j'
b = f['b'][slc]
z = b.get_crd('z')
sheet_iz = np.argmin(b['x']**2, axis=2)
sheet_pts = b['z=0:1'].get_points()
sheet_pts[2, :] = z[sheet_iz].reshape(-1)
isphere_mask = np.sum(sheet_pts[:2, :]**2, axis=0) < 5**2
day_mask = sheet_pts[0:1, :] > -1.0
sheet_pts[2, :] = np.choose(isphere_mask, [sheet_pts[2, :], 0])
sheet_pts[2, :] = np.choose(day_mask, [sheet_pts[2, :], 0])
nx, ny, _ = b.sshape
sheet_seed = viscid.RectilinearMeshPoints(sheet_pts.reshape(3, nx, ny))
vx_sheet = viscid.interp_nearest(f['vx'], sheet_seed)
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
vlt.clf()
vlt.plot(vx_sheet, symmetric=True)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
vlt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
vlab, _ = get_mvi_fig()
mesh = vlab.mesh_from_seeds(sheet_seed, scalars=vx_sheet,
clim=(-400, 400))
vlab.plot_earth_3d(crd_system=b)
vlab.view(azimuth=+90.0 + 45.0, elevation=90.0 - 25.0,
distance=30.0, focalpoint=(-10.0, +1.0, +1.0))
vlab.title("RectilinearMeshPoints")
vlab.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
vlab.show(stop=True)
except ImportError:
pass
# 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 _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 _main():
f = viscid.load_file("$WORK/xi_fte_001/*.3d.[4050f].xdmf")
mp = get_mp_info(f['pp'], f['b'], f['j'], f['e_cc'], fit='mp_xloc',
slc="x=6.5j:10.5j, y=-4j:4j, z=-4.8j:3j", cache=False)
y, z = mp['pp_max_xloc'].meshgrid_flat(prune=True)
x = mp['pp_max_xloc'].data.reshape(-1)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
x2 = paraboloid(Y, Z, *mp['paraboloid'][0])
skip = 117
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
minvar_y = Y.reshape(-1)[::skip]
minvar_z = Z.reshape(-1)[::skip]
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[0]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
minvar_n[:, i] = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0, n=64)[2, :]
# 2d plots, normals don't look normal in the matplotlib projection
if False: # pylint: disable=using-constant-test
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
normals = paraboloid_normal(Y, Z, *mp['paraboloid'][0])
p0 = np.array([x2, Y, Z]).reshape(3, -1)
p1 = p0 + normals.reshape(3, -1)
vlt.scatter_3d(np.vstack([x, y, z])[:, ::skip], equal=True)
for i in range(0, p0.shape[1], skip):
plt.gca().plot([p0[0, i], p1[0, i]],
[p0[1, i], p1[1, i]],
[p0[2, i], p1[2, i]], color='c')
# z2 = _ellipsiod(X, Y, *popt)
plt.gca().plot_surface(Y, Z, x2, color='r')
vlt.show()
# mayavi 3d plots, normals look better here
if True: # pylint: disable=using-constant-test
from viscid.plot import vlab
vlab.points3d(x[::skip], y[::skip], z[::skip], scale_factor=0.25,
color=(0.0, 0.0, 1.0))
mp_width = mp['mp_width']['x=0']
mp_sheath_edge = mp['mp_sheath_edge']['x=0']
mp_sphere_edge = mp_sheath_edge - mp_width
vlab.mesh(x2, Y, Z, scalars=mp_width.data)
vlab.mesh(mp_sheath_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
vlab.mesh(mp_sphere_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
n[0], n[1], n[2], color=(1, 0, 0))
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
minvar_n[0], minvar_n[1], minvar_n[2], color=(0, 0, 1))
vlab.show()
def _main():
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 _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# #################################################
# viscid.logger.info("Testing field lines on 2d field...")
B = viscid.make_dipole(twod=True)
line = viscid.seed.Line((0.2, 0.0, 0.0), (1.0, 0.0, 0.0), 10)
obound0 = np.array([-4, -4, -4], dtype=B.data.dtype)
obound1 = np.array([4, 4, 4], dtype=B.data.dtype)
run_test(B, line, plot2d=plot2d, plot3d=plot3d, title='2D', show=args.show,
ibound=0.07, obound0=obound0, obound1=obound1)
#################################################
viscid.logger.info("Testing field lines on 3d field...")
B = viscid.make_dipole(m=[0.2, 0.3, -0.9])
sphere = viscid.seed.Sphere((0.0, 0.0, 0.0), 2.0, ntheta=20, nphi=10)
obound0 = np.array([-4, -4, -4], dtype=B.data.dtype)
obound1 = np.array([4, 4, 4], dtype=B.data.dtype)
run_test(B, sphere, plot2d=plot2d, plot3d=plot3d, title='3D', show=args.show,
ibound=0.12, obound0=obound0, obound1=obound1, method=viscid.RK12)
# The Remainder of this test makes sure higher order methods are indeed
# more accurate than lower order methods... this could find a bug in
# the integrators
##################################################
# test accuracy of streamlines in an ideal dipole
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=(256, 256, 256),
l=(-25, -25, -25), h=(25, 25, 25), dtype='f8')
seeds_xyz = seeds.get_points()
# seeds_lsp = viscid.xyz2lsrlp(seeds_xyz, cotr=cotr, crd_system=B)[(0, 3), :]
seeds_lsp = viscid.xyz2lsrlp(seeds_xyz, cotr=cotr, crd_system=B)[(0, 3), :]
e1_lines, e1_lsps, t_e1 = lines_and_lsps(B, seeds, method='euler1',
ibound=1.0, cotr=cotr)
rk2_lines, rk2_lsps, t_rk2 = lines_and_lsps(B, seeds, method='rk2',
ibound=1.0, cotr=cotr)
rk4_lines, rk4_lsps, t_rk4 = lines_and_lsps(B, seeds, method='rk4',
ibound=1.0, cotr=cotr)
e1a_lines, e1a_lsps, t_e1a = lines_and_lsps(B, seeds, method='euler1a',
ibound=1.0, cotr=cotr)
rk12_lines, rk12_lsps, t_rk12 = lines_and_lsps(B, seeds, method='rk12',
ibound=1.0, cotr=cotr)
rk45_lines, rk45_lsps, t_rk45 = lines_and_lsps(B, seeds, method='rk45',
ibound=1.0, cotr=cotr)
def _calc_rel_diff(_lsp, _ideal_lsp, _d):
_diffs = []
for _ilsp, _iideal in zip(_lsp, _ideal_lsp.T):
_a = _ilsp[_d, :]
_b = _iideal[_d]
_diffs.append((_a - _b) / _b)
return _diffs
lshell_diff_e1 = _calc_rel_diff(e1_lsps, seeds_lsp, 0)
phi_diff_e1 = _calc_rel_diff(e1_lsps, seeds_lsp, 1)
lshell_diff_rk2 = _calc_rel_diff(rk2_lsps, seeds_lsp, 0)
phi_diff_rk2 = _calc_rel_diff(rk2_lsps, seeds_lsp, 1)
lshell_diff_rk4 = _calc_rel_diff(rk4_lsps, seeds_lsp, 0)
phi_diff_rk4 = _calc_rel_diff(rk4_lsps, seeds_lsp, 1)
lshell_diff_e1a = _calc_rel_diff(e1a_lsps, seeds_lsp, 0)
phi_diff_e1a = _calc_rel_diff(e1a_lsps, seeds_lsp, 1)
lshell_diff_rk12 = _calc_rel_diff(rk12_lsps, seeds_lsp, 0)
phi_diff_rk12 = _calc_rel_diff(rk12_lsps, seeds_lsp, 1)
lshell_diff_rk45 = _calc_rel_diff(rk45_lsps, seeds_lsp, 0)
phi_diff_rk45 = _calc_rel_diff(rk45_lsps, seeds_lsp, 1)
methods = ['Euler 1', 'Runge Kutta 2', 'Runge Kutta 4',
'Euler 1 Adaptive Step', 'Runge Kutta 12 Adaptive Step',
'Runge Kutta 45 Adaptive Step']
wall_ts = [t_e1, t_rk2, t_rk4, t_e1a, t_rk12, t_rk45]
all_lines = [e1_lines, rk2_lines, rk4_lines, e1a_lines, rk12_lines,
rk45_lines]
all_lshell_diffs = [lshell_diff_e1, lshell_diff_rk2, lshell_diff_rk4,
lshell_diff_e1a, lshell_diff_rk12, lshell_diff_rk45]
lshell_diffs = [np.abs(np.concatenate(lshell_diff_e1, axis=0)),
np.abs(np.concatenate(lshell_diff_rk2, axis=0)),
np.abs(np.concatenate(lshell_diff_rk4, axis=0)),
np.abs(np.concatenate(lshell_diff_e1a, axis=0)),
np.abs(np.concatenate(lshell_diff_rk12, axis=0)),
np.abs(np.concatenate(lshell_diff_rk45, axis=0))]
phi_diffs = [np.abs(np.concatenate(phi_diff_e1, axis=0)),
np.abs(np.concatenate(phi_diff_rk2, axis=0)),
np.abs(np.concatenate(phi_diff_rk4, axis=0)),
np.abs(np.concatenate(phi_diff_e1a, axis=0)),
np.abs(np.concatenate(phi_diff_rk12, axis=0)),
np.abs(np.concatenate(phi_diff_rk45, axis=0))]
npts = [len(lsd) for lsd in lshell_diffs]
lshell_75 = [np.percentile(lsdiff, 75) for lsdiff in lshell_diffs]
# # 3D DEBUG PLOT:: for really getting under the covers
# vlab.clf()
# earth1 = viscid.seed.Sphere((0.0, 0.0, 0.0), 1.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls1 = viscid.xyz2lsrlp(earth1.get_points(), cotr=cotr, crd_system='gse')[0, :]
# earth2 = viscid.seed.Sphere((0.0, 0.0, 0.0), 2.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls2 = viscid.xyz2lsrlp(earth2.get_points(), cotr=cotr, crd_system='gse')[0, :]
# earth4 = viscid.seed.Sphere((0.0, 0.0, 0.0), 4.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls4 = viscid.xyz2lsrlp(earth4.get_points(), cotr=cotr, crd_system='gse')[0, :]
# clim = [2.0, 6.0]
# vlab.mesh_from_seeds(earth1, scalars=ls1, clim=clim, logscale=True)
# vlab.mesh_from_seeds(earth2, scalars=ls2, clim=clim, logscale=True, opacity=0.5)
# vlab.mesh_from_seeds(earth4, scalars=ls2, clim=clim, logscale=True, opacity=0.25)
# vlab.plot3d_lines(e1_lines, scalars=[_e1_lsp[0, :] for _e1_lsp in e1_lsps],
# clim=clim, logscale=True)
# vlab.colorbar(title="L-Shell")
# vlab.show()
assert lshell_75[1] < lshell_75[0], "RK2 should have less error than Euler"
assert lshell_75[2] < lshell_75[1], "RK4 should have less error than RK2"
assert lshell_75[3] < lshell_75[0], "Euler 1a should have less error than Euler 1"
assert lshell_75[4] < lshell_75[0], "RK 12 should have less error than Euler 1"
assert lshell_75[5] < lshell_75[1], "RK 45 should have less error than RK2"
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
# stats on error for all points on all lines
_ = plt.figure(figsize=(15, 8))
ax1 = vlt.subplot(121)
v = plt.violinplot(lshell_diffs, showextrema=False, showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
t_txt = ", took {0:.2e} seconds".format(wall_ts[i])
stat_txt = format_data_range(lshell_diffs[i])
plt.text(xl + 0.35 * (xh - xl), i + 1.15, txt + t_txt, color=c)
plt.text(xl + 0.35 * (xh - xl), i + 0.85, stat_txt, color=c)
ax1.get_yaxis().set_visible(False)
plt.title('L-Shell')
plt.xlabel('Relative Difference from Ideal (as fraction)')
ax2 = vlt.subplot(122)
v = plt.violinplot(phi_diffs, showextrema=False, showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
t_txt = ", took {0:.2e} seconds".format(wall_ts[i])
stat_txt = format_data_range(phi_diffs[i])
plt.text(xl + 0.35 * (xh - xl), i + 1.15, txt + t_txt, color=c)
plt.text(xl + 0.35 * (xh - xl), i + 0.85, stat_txt, color=c)
ax2.get_yaxis().set_visible(False)
plt.title('Longitude')
plt.xlabel('Relative Difference from Ideal (as fraction)')
vlt.auto_adjust_subplots()
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.show()
# stats for ds for all points on all lines
_ = plt.figure(figsize=(10, 8))
ax1 = vlt.subplot(111)
ds = [np.concatenate([np.linalg.norm(_l[:, 1:] - _l[:, :-1], axis=0)
for _l in lines]) for lines in all_lines]
v = plt.violinplot(ds, showextrema=False, showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
stat_txt = format_data_range(ds[i])
plt.annotate(txt, xy=(0.55, i / len(methods) + 0.1), color=c,
xycoords='axes fraction')
plt.annotate(stat_txt, xy=(0.55, i / len(methods) + 0.04), color=c,
xycoords='axes fraction')
ax1.get_yaxis().set_visible(False)
plt.xscale('log')
plt.title('Step Size')
plt.xlabel('Absolute Step Size')
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.show()
# random other information
_ = plt.figure(figsize=(13, 10))
## wall time for each method
vlt.subplot(221)
plt.scatter(range(len(methods)), wall_ts, color=colors,
s=150, marker='s', edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, wall_ts[i]), xytext=(0, 15.0),
color=colors[i], horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Wall Time (s)")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(wall_ts), np.max(wall_ts)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## number of points calculated for each method
vlt.subplot(222)
plt.scatter(range(len(methods)), npts, color=colors,
s=150, marker='s', edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, npts[i]), xytext=(0, 15.0),
color=colors[i], horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Number of Streamline Points Calculated")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(npts), np.max(npts)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## Wall time per segment, this should show the overhead of the method
vlt.subplot(223)
wall_t_per_seg = np.asarray(wall_ts) / np.asarray(npts)
plt.scatter(range(len(methods)), wall_t_per_seg, color=colors,
s=150, marker='s', edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, wall_t_per_seg[i]), xytext=(0, 15.0),
color=colors[i], horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Wall Time Per Line Segment")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(wall_t_per_seg), np.max(wall_t_per_seg)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
plt.gca().xaxis.set_major_formatter(viscid.plot.mpl_extra.steve_axfmt)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## 75th percentile of l-shell error for each method
vlt.subplot(224)
plt.scatter(range(len(methods)), lshell_75, color=colors,
s=150, marker='s', edgecolors='none')
plt.yscale('log')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, lshell_75[i]), xytext=(0, 15.0),
color=colors[i], horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("75th Percentile of Relative L-Shell Error")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
ymin, ymax = np.min(lshell_75), np.max(lshell_75)
plt.ylim(0.75 * ymin, 2.5 * ymax)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
vlt.auto_adjust_subplots(subplot_params=dict(wspace=0.25, hspace=0.15))
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.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 args.show,
bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
_global_ns['figure'] = fig
for i, method in zip(count(), methods):
# if i in (3, 4):
# next_plot_fname(__file__, series='q3')
# print(i, "::", [line.shape[1] for line in all_lines[i]])
# # continue
vlab.clf()
_lshell_diff = [np.abs(s) for s in all_lshell_diffs[i]]
vlab.plot3d_lines(all_lines[i], scalars=_lshell_diff)
vlab.colorbar(title="Relative L-Shell Error (as fraction)")
vlab.title(method, size=0.5)
vlab.orientation_axes()
vlab.view(azimuth=40, elevation=140, distance=80.0,
focalpoint=[0, 0, 0])
vlab.savefig(next_plot_fname(__file__, series='q3'))
if args.show:
vlab.show()
except ImportError:
pass
# 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
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("$WORK/tmedium2/*.3d.[-1].xdmf")
else:
raise ValueError()
catol = 1e-8
rtol = 2e-6
elif mhd_type in ("F", "FORTRAN"):
f = viscid.load_file("$WORK/tmedium3/*.3df.[-1]")
catol = 1e-8
rtol = 7e-2
else:
raise ValueError()
do_fill_dipole = True
gslc = "x=-21.2j:12j, y=-11j:11j, z=-11j:11j"
b = f['b_cc'][gslc]
b1 = f['b_fc'][gslc]
e_cc = f['e_cc'][gslc]
e_ec = f['e_ec'][gslc]
if do_fill_dipole:
mask = viscid.make_spherical_mask(b, rmax=3.5)
viscid.fill_dipole(b, mask=mask)
mask = viscid.make_spherical_mask(b1, rmax=3.5)
viscid.fill_dipole(b1, mask=mask)
mask = None
# seeds = viscid.SphericalCap(r=1.02, ntheta=64, nphi=32, angle0=17, angle=20,
# philim=(100, 260), roll=-180.0)
# seeds = viscid.SphericalCap(r=1.02, ntheta=64, nphi=32, angle0=17, angle=20,
# philim=(0, 10), roll=0.0)
seedsN = viscid.Sphere(r=1.02,
ntheta=16,
nphi=16,
thetalim=(15, 25),
philim=(0, 300),
crd_system=b)
seedsS = viscid.Sphere(r=1.02,
ntheta=16,
nphi=16,
thetalim=(155, 165),
philim=(0, 300),
crd_system=b)
bl_kwargs = dict(ibound=0.9, obound0=(-20, -10, -10), obound1=(11, 10, 10))
# blines_cc, topo_cc = viscid.streamlines(b, seeds, **bl_kwargs)
blinesN_fc, topoN_fc = viscid.streamlines(b1, seedsN, **bl_kwargs)
_, topoS_fc = viscid.streamlines(b1,
seedsS,
output=viscid.OUTPUT_TOPOLOGY,
**bl_kwargs)
if True:
from viscid.plot import vlab
mesh = vlab.mesh_from_seeds(seedsN, scalars=topoN_fc)
mesh.actor.property.backface_culling = True
# vlab.plot_lines(blines_cc, scalars="#000000", tube_radius=0.03)
vlab.plot_lines(blinesN_fc,
scalars=viscid.topology2color(topoN_fc),
opacity=0.7)
vlab.plot_blue_marble(r=1.0)
vlab.plot_earth_3d(radius=1.01,
crd_system=b,
night_only=True,
opacity=0.5)
vlab.show()
if True:
vlt.subplot(121, projection='polar')
vlt.plot(topoN_fc)
vlt.subplot(122, projection='polar')
vlt.plot(topoS_fc)
vlt.show()
return 0
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("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# plot2d = True
# plot3d = True
# args.show = True
img = np.load(os.path.join(sample_dir, "logo.npy"))
x = np.linspace(-1, 1, img.shape[0])
y = np.linspace(-1, 1, img.shape[1])
z = np.linspace(-1, 1, img.shape[2])
logo = viscid.arrays2field([x, y, z], img)
if 1:
viscid.logger.info('Testing Line...')
seeds = viscid.Line([-1, -1, 0], [1, 1, 2], n=5)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Plane...')
seeds = viscid.Plane([0.0, 0.0, 0.0], [1, 1, 1], [1, 0, 0], 2, 2,
nl=160, nm=170, NL_are_vectors=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Volume...')
seeds = viscid.Volume([-0.8, -0.8, -0.8], [0.8, 0.8, 0.8],
n=[64, 64, 3])
# note: can't make a 2d plot of the volume w/o a slice
run_test(logo, seeds, plot2d=False, plot3d=plot3d, add_title="3d",
show=args.show)
if 1:
viscid.logger.info('Testing Volume (with ignorable dim)...')
seeds = viscid.Volume([-0.8, -0.8, 0.0], [0.8, 0.8, 0.0],
n=[64, 64, 1])
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="2d",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (phi, theta)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (theta, phi)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (phi, theta)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (theta, phi)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Patch...')
seeds = viscid.SphericalPatch(p0=[0, 0, 0], p1=[0, -0, -1],
max_alpha=30.0, max_beta=59.9,
nalpha=65, nbeta=80, r=0.5, roll=45.0)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing RectilinearMeshPoints...')
f = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[-1].xdmf'))
slc = 'x=-40f:12f, y=-10f:10f, z=-10f:10f'
b = f['b'][slc]
z = b.get_crd('z')
sheet_iz = np.argmin(b['x']**2, axis=2)
sheet_pts = b['z=0:1'].get_points()
sheet_pts[2, :] = z[sheet_iz].reshape(-1)
isphere_mask = np.sum(sheet_pts[:2, :]**2, axis=0) < 5**2
day_mask = sheet_pts[0:1, :] > -1.0
sheet_pts[2, :] = np.choose(isphere_mask, [sheet_pts[2, :], 0])
sheet_pts[2, :] = np.choose(day_mask, [sheet_pts[2, :], 0])
nx, ny, _ = b.sshape
sheet_seed = viscid.RectilinearMeshPoints(sheet_pts.reshape(3, nx, ny))
vx_sheet = viscid.interp_nearest(f['vx'], sheet_seed)
try:
if not plot2d:
raise ImportError
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
vlt.clf()
vlt.plot(vx_sheet, symmetric=True)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
vlt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import vlab
vlab.clf()
mesh = vlab.mesh_from_seeds(sheet_seed, scalars=vx_sheet,
clim=(-400, 400))
vlab.plot_earth_3d(crd_system=b)
vlab.view(azimuth=+90.0 + 45.0, elevation=90.0 - 25.0,
distance=30.0, focalpoint=(-10.0, +1.0, +1.0))
vlab.title("RectilinearMeshPoints")
vlab.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
vlab.show()
except ImportError:
pass
# prevent weird xorg bad-instructions on tear down
if 'figure' in _global_ns and _global_ns['figure'] is not None:
from viscid.plot import vlab
vlab.mlab.close(_global_ns['figure'])
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--show", "--plot", action="store_true")
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():
f = viscid.load_file("$WORK/xi_fte_001/*.3d.[4050f].xdmf")
mp = get_mp_info(f['pp'],
f['b'],
f['j'],
f['e_cc'],
fit='mp_xloc',
slc="x=6.5f:10.5f, y=-4f:4f, z=-4.8f:3f",
cache=False)
y, z = mp['pp_max_xloc'].meshgrid_flat(prune=True)
x = mp['pp_max_xloc'].data.reshape(-1)
Y, Z = mp['pp_max_xloc'].meshgrid(prune=True)
x2 = paraboloid(Y, Z, *mp['paraboloid'][0])
skip = 117
n = paraboloid_normal(Y, Z, *mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
minvar_y = Y.reshape(-1)[::skip]
minvar_z = Z.reshape(-1)[::skip]
minvar_n = np.zeros([3, len(minvar_y)])
for i in range(minvar_n.shape[0]):
p0 = [0.0, minvar_y[i], minvar_z[i]]
p0[0] = mp['pp_max_xloc']['y={0[0]}f, z={0[1]}f'.format(p0)]
minvar_n[:, i] = viscid.find_minvar_lmn_around(f['b'], p0, l=2.0,
n=64)[2, :]
# 2d plots, normals don't look normal in the matplotlib projection
if False: # pylint: disable=using-constant-test
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
normals = paraboloid_normal(Y, Z, *mp['paraboloid'][0])
p0 = np.array([x2, Y, Z]).reshape(3, -1)
p1 = p0 + normals.reshape(3, -1)
vlt.scatter_3d(np.vstack([x, y, z])[:, ::skip], equal=True)
for i in range(0, p0.shape[1], skip):
plt.gca().plot([p0[0, i], p1[0, i]], [p0[1, i], p1[1, i]],
[p0[2, i], p1[2, i]],
color='c')
# z2 = _ellipsiod(X, Y, *popt)
plt.gca().plot_surface(Y, Z, x2, color='r')
vlt.show()
# mayavi 3d plots, normals look better here
if True: # pylint: disable=using-constant-test
from viscid.plot import vlab
vlab.points3d(x[::skip],
y[::skip],
z[::skip],
scale_factor=0.25,
color=(0.0, 0.0, 1.0))
mp_width = mp['mp_width']['x=0']
mp_sheath_edge = mp['mp_sheath_edge']['x=0']
mp_sphere_edge = mp_sheath_edge - mp_width
vlab.mesh(x2, Y, Z, scalars=mp_width.data)
vlab.mesh(mp_sheath_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
vlab.mesh(mp_sphere_edge.data, Y, Z, opacity=0.75, color=(0.75, ) * 3)
n = paraboloid_normal(Y, Z,
*mp['paraboloid'][0]).reshape(3, -1)[:, ::skip]
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
n[0],
n[1],
n[2],
color=(1, 0, 0))
vlab.quiver3d(x2.reshape(-1)[::skip],
Y.reshape(-1)[::skip],
Z.reshape(-1)[::skip],
minvar_n[0],
minvar_n[1],
minvar_n[2],
color=(0, 0, 1))
vlab.show()
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# #################################################
# viscid.logger.info("Testing field lines on 2d field...")
B = viscid.make_dipole(twod=True)
line = viscid.seed.Line((0.2, 0.0, 0.0), (1.0, 0.0, 0.0), 10)
obound0 = np.array([-4, -4, -4], dtype=B.data.dtype)
obound1 = np.array([4, 4, 4], dtype=B.data.dtype)
run_test(B,
line,
plot2d=plot2d,
plot3d=plot3d,
title='2D',
show=args.show,
ibound=0.07,
obound0=obound0,
obound1=obound1)
#################################################
viscid.logger.info("Testing field lines on 3d field...")
B = viscid.make_dipole(m=[0.2, 0.3, -0.9])
sphere = viscid.seed.Sphere((0.0, 0.0, 0.0), 2.0, ntheta=20, nphi=10)
obound0 = np.array([-4, -4, -4], dtype=B.data.dtype)
obound1 = np.array([4, 4, 4], dtype=B.data.dtype)
run_test(B,
sphere,
plot2d=plot2d,
plot3d=plot3d,
title='3D',
show=args.show,
ibound=0.12,
obound0=obound0,
obound1=obound1,
method=viscid.RK12)
# The Remainder of this test makes sure higher order methods are indeed
# more accurate than lower order methods... this could find a bug in
# the integrators
##################################################
# test accuracy of streamlines in an ideal dipole
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=(256, 256, 256),
l=(-25, -25, -25),
h=(25, 25, 25),
dtype='f8')
seeds_xyz = seeds.get_points()
# seeds_lsp = viscid.xyz2lsrlp(seeds_xyz, cotr=cotr, crd_system=B)[(0, 3), :]
seeds_lsp = viscid.xyz2lsrlp(seeds_xyz, cotr=cotr, crd_system=B)[(0, 3), :]
e1_lines, e1_lsps, t_e1 = lines_and_lsps(B,
seeds,
method='euler1',
ibound=1.0,
cotr=cotr)
rk2_lines, rk2_lsps, t_rk2 = lines_and_lsps(B,
seeds,
method='rk2',
ibound=1.0,
cotr=cotr)
rk4_lines, rk4_lsps, t_rk4 = lines_and_lsps(B,
seeds,
method='rk4',
ibound=1.0,
cotr=cotr)
e1a_lines, e1a_lsps, t_e1a = lines_and_lsps(B,
seeds,
method='euler1a',
ibound=1.0,
cotr=cotr)
rk12_lines, rk12_lsps, t_rk12 = lines_and_lsps(B,
seeds,
method='rk12',
ibound=1.0,
cotr=cotr)
rk45_lines, rk45_lsps, t_rk45 = lines_and_lsps(B,
seeds,
method='rk45',
ibound=1.0,
cotr=cotr)
def _calc_rel_diff(_lsp, _ideal_lsp, _d):
_diffs = []
for _ilsp, _iideal in zip(_lsp, _ideal_lsp.T):
_a = _ilsp[_d, :]
_b = _iideal[_d]
_diffs.append((_a - _b) / _b)
return _diffs
lshell_diff_e1 = _calc_rel_diff(e1_lsps, seeds_lsp, 0)
phi_diff_e1 = _calc_rel_diff(e1_lsps, seeds_lsp, 1)
lshell_diff_rk2 = _calc_rel_diff(rk2_lsps, seeds_lsp, 0)
phi_diff_rk2 = _calc_rel_diff(rk2_lsps, seeds_lsp, 1)
lshell_diff_rk4 = _calc_rel_diff(rk4_lsps, seeds_lsp, 0)
phi_diff_rk4 = _calc_rel_diff(rk4_lsps, seeds_lsp, 1)
lshell_diff_e1a = _calc_rel_diff(e1a_lsps, seeds_lsp, 0)
phi_diff_e1a = _calc_rel_diff(e1a_lsps, seeds_lsp, 1)
lshell_diff_rk12 = _calc_rel_diff(rk12_lsps, seeds_lsp, 0)
phi_diff_rk12 = _calc_rel_diff(rk12_lsps, seeds_lsp, 1)
lshell_diff_rk45 = _calc_rel_diff(rk45_lsps, seeds_lsp, 0)
phi_diff_rk45 = _calc_rel_diff(rk45_lsps, seeds_lsp, 1)
methods = [
'Euler 1', 'Runge Kutta 2', 'Runge Kutta 4', 'Euler 1 Adaptive Step',
'Runge Kutta 12 Adaptive Step', 'Runge Kutta 45 Adaptive Step'
]
wall_ts = [t_e1, t_rk2, t_rk4, t_e1a, t_rk12, t_rk45]
all_lines = [
e1_lines, rk2_lines, rk4_lines, e1a_lines, rk12_lines, rk45_lines
]
all_lshell_diffs = [
lshell_diff_e1, lshell_diff_rk2, lshell_diff_rk4, lshell_diff_e1a,
lshell_diff_rk12, lshell_diff_rk45
]
lshell_diffs = [
np.abs(np.concatenate(lshell_diff_e1, axis=0)),
np.abs(np.concatenate(lshell_diff_rk2, axis=0)),
np.abs(np.concatenate(lshell_diff_rk4, axis=0)),
np.abs(np.concatenate(lshell_diff_e1a, axis=0)),
np.abs(np.concatenate(lshell_diff_rk12, axis=0)),
np.abs(np.concatenate(lshell_diff_rk45, axis=0))
]
phi_diffs = [
np.abs(np.concatenate(phi_diff_e1, axis=0)),
np.abs(np.concatenate(phi_diff_rk2, axis=0)),
np.abs(np.concatenate(phi_diff_rk4, axis=0)),
np.abs(np.concatenate(phi_diff_e1a, axis=0)),
np.abs(np.concatenate(phi_diff_rk12, axis=0)),
np.abs(np.concatenate(phi_diff_rk45, axis=0))
]
npts = [len(lsd) for lsd in lshell_diffs]
lshell_75 = [np.percentile(lsdiff, 75) for lsdiff in lshell_diffs]
# # 3D DEBUG PLOT:: for really getting under the covers
# vlab.clf()
# earth1 = viscid.seed.Sphere((0.0, 0.0, 0.0), 1.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls1 = viscid.xyz2lsrlp(earth1.get_points(), cotr=cotr, crd_system='gse')[0, :]
# earth2 = viscid.seed.Sphere((0.0, 0.0, 0.0), 2.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls2 = viscid.xyz2lsrlp(earth2.get_points(), cotr=cotr, crd_system='gse')[0, :]
# earth4 = viscid.seed.Sphere((0.0, 0.0, 0.0), 4.0, pole=-m, ntheta=60, nphi=120,
# thetalim=(15, 165), philim=(0, 360))
# ls4 = viscid.xyz2lsrlp(earth4.get_points(), cotr=cotr, crd_system='gse')[0, :]
# clim = [2.0, 6.0]
# vlab.mesh_from_seeds(earth1, scalars=ls1, clim=clim, logscale=True)
# vlab.mesh_from_seeds(earth2, scalars=ls2, clim=clim, logscale=True, opacity=0.5)
# vlab.mesh_from_seeds(earth4, scalars=ls2, clim=clim, logscale=True, opacity=0.25)
# vlab.plot3d_lines(e1_lines, scalars=[_e1_lsp[0, :] for _e1_lsp in e1_lsps],
# clim=clim, logscale=True)
# vlab.colorbar(title="L-Shell")
# vlab.show()
assert lshell_75[1] < lshell_75[0], "RK2 should have less error than Euler"
assert lshell_75[2] < lshell_75[1], "RK4 should have less error than RK2"
assert lshell_75[3] < lshell_75[
0], "Euler 1a should have less error than Euler 1"
assert lshell_75[4] < lshell_75[
0], "RK 12 should have less error than Euler 1"
assert lshell_75[5] < lshell_75[1], "RK 45 should have less error than RK2"
try:
if not plot2d:
raise ImportError
from matplotlib import pyplot as plt
from viscid.plot import vpyplot as vlt
# stats on error for all points on all lines
_ = plt.figure(figsize=(15, 8))
ax1 = vlt.subplot(121)
v = plt.violinplot(lshell_diffs,
showextrema=False,
showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
t_txt = ", took {0:.2e} seconds".format(wall_ts[i])
stat_txt = format_data_range(lshell_diffs[i])
plt.text(xl + 0.35 * (xh - xl), i + 1.15, txt + t_txt, color=c)
plt.text(xl + 0.35 * (xh - xl), i + 0.85, stat_txt, color=c)
ax1.get_yaxis().set_visible(False)
plt.title('L-Shell')
plt.xlabel('Relative Difference from Ideal (as fraction)')
ax2 = vlt.subplot(122)
v = plt.violinplot(phi_diffs,
showextrema=False,
showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
t_txt = ", took {0:.2e} seconds".format(wall_ts[i])
stat_txt = format_data_range(phi_diffs[i])
plt.text(xl + 0.35 * (xh - xl), i + 1.15, txt + t_txt, color=c)
plt.text(xl + 0.35 * (xh - xl), i + 0.85, stat_txt, color=c)
ax2.get_yaxis().set_visible(False)
plt.title('Longitude')
plt.xlabel('Relative Difference from Ideal (as fraction)')
vlt.auto_adjust_subplots()
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.show()
# stats for ds for all points on all lines
_ = plt.figure(figsize=(10, 8))
ax1 = vlt.subplot(111)
ds = [
np.concatenate([
np.linalg.norm(_l[:, 1:] - _l[:, :-1], axis=0) for _l in lines
]) for lines in all_lines
]
v = plt.violinplot(ds,
showextrema=False,
showmedians=False,
vert=False)
colors = set_violin_colors(v)
xl, xh = plt.gca().get_xlim()
for i, txt, c in zip(count(), methods, colors):
stat_txt = format_data_range(ds[i])
plt.text(xl + 0.01 * (xh - xl), i + 1.15, txt, color=c)
plt.text(xl + 0.01 * (xh - xl), i + 0.85, stat_txt, color=c)
ax1.get_yaxis().set_visible(False)
plt.xscale('log')
plt.title('Step Size')
plt.xlabel('Absolute Step Size')
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.show()
# random other information
_ = plt.figure(figsize=(13, 10))
## wall time for each method
vlt.subplot(221)
plt.scatter(range(len(methods)),
wall_ts,
color=colors,
s=150,
marker='s',
edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, wall_ts[i]),
xytext=(0, 15.0),
color=colors[i],
horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Wall Time (s)")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(wall_ts), np.max(wall_ts)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## number of points calculated for each method
vlt.subplot(222)
plt.scatter(range(len(methods)),
npts,
color=colors,
s=150,
marker='s',
edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, npts[i]),
xytext=(0, 15.0),
color=colors[i],
horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Number of Streamline Points Calculated")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(npts), np.max(npts)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## Wall time per segment, this should show the overhead of the method
vlt.subplot(223)
wall_t_per_seg = np.asarray(wall_ts) / np.asarray(npts)
plt.scatter(range(len(methods)),
wall_t_per_seg,
color=colors,
s=150,
marker='s',
edgecolors='none')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, wall_t_per_seg[i]),
xytext=(0, 15.0),
color=colors[i],
horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("Wall Time Per Line Segment")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
yl, yh = np.min(wall_t_per_seg), np.max(wall_t_per_seg)
y_padding = 0.4 * (yh - yl)
plt.ylim(yl - y_padding, yh + y_padding)
plt.gca().get_xaxis().set_visible(False)
plt.gca().xaxis.set_major_formatter(viscid.plot.mpl_extra.steve_axfmt)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
## 75th percentile of l-shell error for each method
vlt.subplot(224)
plt.scatter(range(len(methods)),
lshell_75,
color=colors,
s=150,
marker='s',
edgecolors='none')
plt.yscale('log')
for i, meth in enumerate(methods):
meth = meth.replace(" Adaptive Step", "\nAdaptive Step")
plt.annotate(meth, (i, lshell_75[i]),
xytext=(0, 15.0),
color=colors[i],
horizontalalignment='center',
verticalalignment='bottom',
textcoords='offset points')
plt.ylabel("75th Percentile of Relative L-Shell Error")
x_padding = 0.5
plt.xlim(-x_padding, len(methods) - x_padding)
ymin, ymax = np.min(lshell_75), np.max(lshell_75)
plt.ylim(0.75 * ymin, 2.5 * ymax)
plt.gca().get_xaxis().set_visible(False)
for _which in ('right', 'top'):
plt.gca().spines[_which].set_color('none')
vlt.auto_adjust_subplots(subplot_params=dict(wspace=0.25, hspace=0.15))
vlt.savefig(next_plot_fname(__file__, series='q2'))
if args.show:
vlt.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 args.show,
bgcolor=(1, 1, 1),
fgcolor=(0, 0, 0))
_global_ns['figure'] = fig
for i, method in zip(count(), methods):
# if i in (3, 4):
# next_plot_fname(__file__, series='q3')
# print(i, "::", [line.shape[1] for line in all_lines[i]])
# # continue
vlab.clf()
_lshell_diff = [np.abs(s) for s in all_lshell_diffs[i]]
vlab.plot3d_lines(all_lines[i], scalars=_lshell_diff)
vlab.colorbar(title="Relative L-Shell Error (as fraction)")
vlab.title(method, size=0.5)
vlab.orientation_axes()
vlab.view(azimuth=40,
elevation=140,
distance=80.0,
focalpoint=[0, 0, 0])
vlab.savefig(next_plot_fname(__file__, series='q3'))
if args.show:
vlab.show()
except ImportError:
pass
# 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():
f = viscid.load_file('~/dev/work/xi_fte_001/*.3d.*.xdmf')
time_slice = ':'
times = np.array([grid.time for grid in f.iter_times(time_slice)])
# XYZ coordinates of virtual satelites in warped "plasma sheet coords"
x_sat_psc = np.linspace(-30, 0, 31) # X (GSE == PSC)
y_sat_psc = np.linspace(-10, 10, 21) # Y (GSE == PSC)
z_sat_psc = np.linspace(-2, 2, 5) # Z in PSC (z=0 is the plasma sheet)
# the GSE z location of the virtual satelites in the warped plasma sheet
# coordinates, so sat_z_gse_ts['x=5j, y=1j, z=0j'] would give the
# plasma sheet location at x=5.0, y=1.0
# These fields depend on time because the plasma sheet moves in time
sat_z_gse_ts = viscid.zeros([times, x_sat_psc, y_sat_psc, z_sat_psc],
crd_names='txyz', center='node',
name='PlasmaSheetZ_GSE')
vx_ts = viscid.zeros_like(sat_z_gse_ts)
bz_ts = viscid.zeros_like(sat_z_gse_ts)
for itime, grid in enumerate(f.iter_times(time_slice)):
print("Processing time slice", itime, grid.time)
gse_slice = 'x=-35j:0j, y=-15j:15j, z=-6j:6j'
bx = grid['bx'][gse_slice]
bx_argmin = np.argmin(bx**2, axis=2)
z_gse = bx.get_crd('z')
# ps_zloc_gse is the plasma sheet z location along the GGCM grid x/y
ps_z_gse = viscid.zeros_like(bx[:, :, 0:1])
ps_z_gse[...] = z_gse[bx_argmin]
# Note: Here you could apply a gaussian filter to
# ps_z_gse[:, :, 0].data in order to smooth the surface
# if desired. Scipy / Scikit-Image have some functions
# that do this
# ok, we found the plasma sheet z GSE location on the actual GGCM
# grid, but we just want a subset of that grid for our virtual
# satelites, so just interpolate the ps z location to our subset
ps_z_gse_subset = viscid.interp_trilin(ps_z_gse,
sat_z_gse_ts[itime, :, :, 0:1],
wrap=True)
# now we know the plasma sheet z location in GSE, and how far
# apart we want the satelites in z, so put those two things together
# to get a bunch of satelite locations
sat_z_gse_ts[itime] = ps_z_gse_subset.data + z_sat_psc.reshape(1, 1, -1)
# make a seed generator that we can use to fill the vx and bz
# time series for this instant in time
sat_loc_gse = sat_z_gse_ts[itime].get_points()
sat_loc_gse[2, :] = sat_z_gse_ts[itime].data.reshape(-1)
# slicing the field before doing the interpolation makes this
# faster for hdf5 data, but probably for other data too
vx_ts[itime] = viscid.interp_trilin(grid['vx'][gse_slice],
sat_loc_gse,
wrap=False
).reshape(vx_ts.shape[1:])
bz_ts[itime] = viscid.interp_trilin(grid['bz'][gse_slice],
sat_loc_gse,
wrap=False
).reshape(bz_ts.shape[1:])
# 2d plots of the plasma sheet z location to make sure we did the
# interpolation correctly
if False: # pylint: disable=using-constant-test
from viscid.plot import vpyplot as vlt
fig, (ax0, ax1) = vlt.subplots(2, 1) # pylint: disable=unused-variable
vlt.plot(ps_z_gse, ax=ax0, clim=(-5, 5))
vlt.plot(ps_z_gse_subset, ax=ax1, clim=(-5, 5))
vlt.auto_adjust_subplots()
vlt.show()
# make a 3d plot of the plasma sheet surface to verify that it
# makes sense
if True: # pylint: disable=using-constant-test
from viscid.plot import vlab
fig = vlab.figure(size=(1280, 800), bgcolor=(1, 1, 1),
fgcolor=(0, 0, 0))
vlab.clf()
# plot the plasma sheet coloured by vx
# Note: points closer to x = 0 are unsightly since the plasma
# sheet criteria starts to fall apart on the flanks, so
# just remove the first few rows
ps_z_gse_tail = ps_z_gse['x=:-2.25j']
ps_mesh_shape = [3, ps_z_gse_tail.shape[0], ps_z_gse_tail.shape[1]]
ps_pts = ps_z_gse_tail.get_points().reshape(ps_mesh_shape)
ps_pts[2, :, :] = ps_z_gse_tail[:, :, 0]
plasma_sheet = viscid.RectilinearMeshPoints(ps_pts)
ps_vx = viscid.interp_trilin(grid['vx'][gse_slice], plasma_sheet)
_ = vlab.mesh_from_seeds(plasma_sheet, scalars=ps_vx)
vx_clim = (-1400, 1400)
vx_cmap = 'viridis'
vlab.colorbar(title='Vx', clim=vx_clim, cmap=vx_cmap,
nb_labels=5)
# plot satelite locations as dots colored by Vx with the same
# limits and color as the plasma sheet mesh
sat3d = vlab.points3d(sat_loc_gse[0], sat_loc_gse[1], sat_loc_gse[2],
vx_ts[itime].data.reshape(-1),
scale_mode='none', scale_factor=0.2)
vlab.apply_cmap(sat3d, clim=vx_clim, cmap=vx_cmap)
# plot Earth for reference
cotr = viscid.Cotr(dip_tilt=0.0) # pylint: disable=not-callable
vlab.plot_blue_marble(r=1.0, lines=False, ntheta=64, nphi=128,
rotate=cotr, crd_system='mhd')
vlab.plot_earth_3d(radius=1.01, night_only=True, opacity=0.5,
crd_system='gse')
vlab.view(azimuth=45, elevation=70, distance=35.0,
focalpoint=[-9, 3, -1])
vlab.savefig('plasma_sheet_3d_{0:02d}.png'.format(itime))
vlab.show()
try:
vlab.mlab.close(fig)
except TypeError:
pass # this happens if the figure is already closed
# now do what we will with the time series... this is not a good
# presentation of this data, but you get the idea
from viscid.plot import vpyplot as vlt
fig, axes = vlt.subplots(4, 4, figsize=(12, 12))
for ax_row, yloc in zip(axes, np.linspace(-5, 5, len(axes))[::-1]):
for ax, xloc in zip(ax_row, np.linspace(4, 7, len(ax_row))):
vlt.plot(vx_ts['x={0}j, y={1}j, z=0j'.format(xloc, yloc)], ax=ax)
ax.set_ylabel('')
vlt.plt.title('x = {0:g}, y = {1:g}'.format(xloc, yloc))
vlt.plt.suptitle('Vx [km/s]')
vlt.auto_adjust_subplots()
vlt.show()
return 0
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--notwo", dest='notwo', action="store_true")
parser.add_argument("--nothree", dest='nothree', action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = viscid.vutil.common_argparse(parser, default_verb=0)
plot2d = not args.notwo
plot3d = not args.nothree
# plot2d = True
# plot3d = True
# args.show = True
img = np.load(os.path.join(sample_dir, "logo.npy"))
x = np.linspace(-1, 1, img.shape[0])
y = np.linspace(-1, 1, img.shape[1])
z = np.linspace(-1, 1, img.shape[2])
logo = viscid.arrays2field([x, y, z], img)
if 1:
viscid.logger.info('Testing Point with custom local coordinates...')
pts = np.vstack([[-1, -0.5, 0, 0.5, 1],
[-1, -0.5, 0, 0.5, 1],
[ 0, 0.5, 1, 1.5, 2]])
local_crds = viscid.asarray_datetime64([0, 60, 120, 180, 240],
conservative=True)
seeds = viscid.Point(pts, local_crds=local_crds)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Line...')
seeds = viscid.Line([-1, -1, 0], [1, 1, 2], n=5)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Plane...')
seeds = viscid.Plane([0.0, 0.0, 0.0], [1, 1, 1], [1, 0, 0], 2, 2,
nl=160, nm=170, NL_are_vectors=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
viscid.logger.info('Testing Volume...')
seeds = viscid.Volume([-0.8, -0.8, -0.8], [0.8, 0.8, 0.8],
n=[64, 64, 3])
# note: can't make a 2d plot of the volume w/o a slice
run_test(logo, seeds, plot2d=False, plot3d=plot3d, add_title="3d",
show=args.show)
if 1:
viscid.logger.info('Testing Volume (with ignorable dim)...')
seeds = viscid.Volume([-0.8, -0.8, 0.0], [0.8, 0.8, 0.0],
n=[64, 64, 1])
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="2d",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (phi, theta)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Sphere (theta, phi)...')
seeds = viscid.Sphere([0, 0, 0], r=1.0, ntheta=160, nphi=170,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (phi, theta)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=False)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="PT",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Cap (theta, phi)...')
seeds = viscid.SphericalCap(p0=[0, 0, 0], r=1.0, ntheta=64, nphi=80,
pole=[-1, -1, -1], theta_phi=True)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, add_title="TP",
view_kwargs=dict(azimuth=180, elevation=180), show=args.show)
if 1:
viscid.logger.info('Testing Spherical Patch...')
seeds = viscid.SphericalPatch(p0=[0, 0, 0], p1=[0, -0, -1],
max_alpha=30.0, max_beta=59.9,
nalpha=65, nbeta=80, r=0.5, roll=45.0)
run_test(logo, seeds, plot2d=plot2d, plot3d=plot3d, show=args.show)
if 1:
# this spline test is very custom
viscid.logger.info('Testing Spline...')
try:
import scipy.interpolate as interpolate
except ImportError:
msg = "XFail: ImportError (is scipy installed?)"
if plot2d:
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
plt.annotate(msg, xy=(0.3, 0.4), xycoords='axes fraction')
plt.savefig(next_plot_fname(__file__, series='2d'))
plt.savefig(next_plot_fname(__file__, series='2d'))
plt.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
plt.show()
except ImportError:
pass
else:
knots = np.array([[ 0.2, 0.5, 0.0], [-0.2, 0.5, 0.2],
[-0.2, 0.0, 0.4], [ 0.2, 0.0, 0.2],
[ 0.2, -0.5, 0.0], [-0.2, -0.5, 0.2]]).T
seed_name = "Spline"
fld = logo
seeds = viscid.Spline(knots)
seed_pts = seeds.get_points()
interp_fld = viscid.interp_trilin(fld, seeds)
if plot2d:
try:
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
plt.clf()
vlt.plot(interp_fld)
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
plt.show()
plt.clf()
from matplotlib import rcParams
_ms = rcParams['lines.markersize']
plt.gca().scatter(knots[0, :], knots[1, :],
s=(2 * _ms)**2, marker='^', color='y')
plt.gca().scatter(seed_pts[0, :], seed_pts[1, :],
s=(1.5 * _ms)**2, marker='o', color='k')
vlt.plot2d_line(seed_pts, scalars=interp_fld.flat_data,
symdir='z')
plt.title(seed_name)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
plt.show()
except ImportError:
pass
if plot3d:
try:
from viscid.plot import vlab
_ = get_mvi_fig(offscreen=not args.show)
vlab.points3d(knots[0], knots[1], knots[2],
color=(1.0, 1.0, 0), scale_mode='none',
scale_factor=0.04)
p = vlab.points3d(seed_pts[0], seed_pts[1], seed_pts[2],
color=(0, 0, 0), scale_mode='none',
scale_factor=0.03)
vlab.plot_line(seed_pts, scalars=interp_fld.flat_data,
tube_radius=0.01)
vlab.axes(p)
vlab.title(seed_name)
vlab.mlab.roll(-90.0)
vlab.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
vlab.show(stop=True)
except ImportError:
pass
if 1:
viscid.logger.info('Testing RectilinearMeshPoints...')
f = viscid.load_file(os.path.join(sample_dir, 'sample_xdmf.3d.[-1].xdmf'))
slc = 'x=-40j:12j, y=-10j:10j, z=-10j:10j'
b = f['b'][slc]
z = b.get_crd('z')
sheet_iz = np.argmin(b['x']**2, axis=2)
sheet_pts = b['z=0:1'].get_points()
sheet_pts[2, :] = z[sheet_iz].reshape(-1)
isphere_mask = np.sum(sheet_pts[:2, :]**2, axis=0) < 5**2
day_mask = sheet_pts[0:1, :] > -1.0
sheet_pts[2, :] = np.choose(isphere_mask, [sheet_pts[2, :], 0])
sheet_pts[2, :] = np.choose(day_mask, [sheet_pts[2, :], 0])
nx, ny, _ = b.sshape
sheet_seed = viscid.RectilinearMeshPoints(sheet_pts.reshape(3, nx, ny))
vx_sheet = viscid.interp_nearest(f['vx'], sheet_seed)
try:
if not plot2d:
raise ImportError
from viscid.plot import vpyplot as vlt
from matplotlib import pyplot as plt
vlt.clf()
vlt.plot(vx_sheet, symmetric=True)
plt.savefig(next_plot_fname(__file__, series='2d'))
if args.show:
vlt.show()
except ImportError:
pass
try:
if not plot3d:
raise ImportError
from viscid.plot import vlab
_ = get_mvi_fig(offscreen=not args.show)
mesh = vlab.mesh_from_seeds(sheet_seed, scalars=vx_sheet,
clim=(-400, 400))
vlab.plot_earth_3d(crd_system=b)
vlab.view(azimuth=+90.0 + 45.0, elevation=90.0 - 25.0,
distance=30.0, focalpoint=(-10.0, +1.0, +1.0))
vlab.title("RectilinearMeshPoints")
vlab.savefig(next_plot_fname(__file__, series='3d'))
if args.show:
vlab.show(stop=True)
except ImportError:
pass
# 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
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("$WORK/tmedium2/*.3d.[-1].xdmf")
else:
raise ValueError()
catol = 1e-8
rtol = 2e-6
elif mhd_type in ("F", "FORTRAN"):
f = viscid.load_file("$WORK/tmedium3/*.3df.[-1]")
catol = 1e-8
rtol = 7e-2
else:
raise ValueError()
do_fill_dipole = True
gslc = "x=-21.2j:12j, y=-11j:11j, z=-11j:11j"
b = f['b_cc'][gslc]
b1 = f['b_fc'][gslc]
e_cc = f['e_cc'][gslc]
e_ec = f['e_ec'][gslc]
if do_fill_dipole:
mask = viscid.make_spherical_mask(b, rmax=3.5)
viscid.fill_dipole(b, mask=mask)
mask = viscid.make_spherical_mask(b1, rmax=3.5)
viscid.fill_dipole(b1, mask=mask)
mask = None
# seeds = viscid.SphericalCap(r=1.02, ntheta=64, nphi=32, angle0=17, angle=20,
# philim=(100, 260), roll=-180.0)
# seeds = viscid.SphericalCap(r=1.02, ntheta=64, nphi=32, angle0=17, angle=20,
# philim=(0, 10), roll=0.0)
seedsN = viscid.Sphere(r=1.02, ntheta=16, nphi=16, thetalim=(15, 25),
philim=(0, 300), crd_system=b)
seedsS = viscid.Sphere(r=1.02, ntheta=16, nphi=16, thetalim=(155, 165),
philim=(0, 300), crd_system=b)
bl_kwargs = dict(ibound=0.9, obound0=(-20, -10, -10), obound1=(11, 10, 10))
# blines_cc, topo_cc = viscid.streamlines(b, seeds, **bl_kwargs)
blinesN_fc, topoN_fc = viscid.streamlines(b1, seedsN, **bl_kwargs)
_, topoS_fc = viscid.streamlines(b1, seedsS, output=viscid.OUTPUT_TOPOLOGY,
**bl_kwargs)
if True:
from viscid.plot import vlab
mesh = vlab.mesh_from_seeds(seedsN, scalars=topoN_fc)
mesh.actor.property.backface_culling = True
# vlab.plot_lines(blines_cc, scalars="#000000", tube_radius=0.03)
vlab.plot_lines(blinesN_fc, scalars=viscid.topology2color(topoN_fc),
opacity=0.7)
vlab.plot_blue_marble(r=1.0)
vlab.plot_earth_3d(radius=1.01, crd_system=b, night_only=True,
opacity=0.5)
vlab.show()
if True:
vlt.subplot(121, projection='polar')
vlt.plot(topoN_fc)
vlt.subplot(122, projection='polar')
vlt.plot(topoS_fc)
vlt.show()
return 0
