def main():
parser = argparse.ArgumentParser(description="Test divergence")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
dtype = 'float64'
# use 512 512 256 to inspect memory related things
x = np.array(np.linspace(-0.5, 0.5, 256), dtype=dtype)
y = np.array(np.linspace(-0.5, 0.5, 256), dtype=dtype)
z = np.array(np.linspace(-0.5, 0.5, 64), dtype=dtype)
v = viscid.empty([x, y, z], name="V", nr_comps=3, center="cell",
layout="interlaced")
exact_cc = viscid.empty([x, y, z], name="exact_cc", center='cell')
Xcc, Ycc, Zcc = exact_cc.get_crds_cc(shaped=True) #pylint: disable=W0612
v['x'] = ne.evaluate("(sin(Xcc))") # + Zcc
v['y'] = ne.evaluate("(cos(Ycc))") # + Xcc# + Zcc
v['z'] = ne.evaluate("-((sin(Zcc)))") # + Xcc# + Ycc
exact_cc[:, :, :] = ne.evaluate("cos(Xcc) - sin(Ycc) - cos(Zcc)")
logger.info("node centered tests")
v_nc = v.as_centered('node')
exact_nc = viscid.empty_like(v_nc['x'])
X, Y, Z = exact_nc.get_crds_nc(shaped=True) #pylint: disable=W0612
exact_nc[:, :, :] = ne.evaluate("cos(X) - sin(Y) - cos(Z)")
# FIXME: why is the error so much larger here?
run_div_test(v_nc, exact_nc, show=args.show, ignore_inexact=True)
logger.info("cell centered tests")
v_cc = v_nc.as_centered('cell')
run_div_test(v_cc, exact_cc, show=args.show)
def _main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--prof", action="store_true")
parser.add_argument("--show", "--plot", action="store_true")
args = vutil.common_argparse(parser)
dtype = 'float64'
# use 512 512 256 to inspect memory related things
x = np.array(np.linspace(-0.5, 0.5, 256), dtype=dtype)
y = np.array(np.linspace(-0.5, 0.5, 256), dtype=dtype)
z = np.array(np.linspace(-0.5, 0.5, 64), dtype=dtype)
v = viscid.empty([x, y, z], name="V", nr_comps=3, center="cell",
layout="interlaced")
exact_cc = viscid.empty([x, y, z], name="exact_cc", center='cell')
Xcc, Ycc, Zcc = exact_cc.get_crds_cc(shaped=True) # pylint: disable=W0612
if HAS_NUMEXPR:
v['x'] = ne.evaluate("(sin(Xcc))") # + Zcc
v['y'] = ne.evaluate("(cos(Ycc))") # + Xcc# + Zcc
v['z'] = ne.evaluate("-((sin(Zcc)))") # + Xcc# + Ycc
exact_cc[:, :, :] = ne.evaluate("cos(Xcc) - sin(Ycc) - cos(Zcc)")
else:
v['x'] = (np.sin(Xcc)) # + Zcc
v['y'] = (np.cos(Ycc)) # + Xcc# + Zcc
v['z'] = -((np.sin(Zcc))) # + Xcc# + Ycc
exact_cc[:, :, :] = np.cos(Xcc) - np.sin(Ycc) - np.cos(Zcc)
if args.prof:
print("Without boundaries")
viscid.timeit(viscid.div, v, bnd=False, timeit_repeat=10,
timeit_print_stats=True)
print("With boundaries")
viscid.timeit(viscid.div, v, bnd=True, timeit_repeat=10,
timeit_print_stats=True)
logger.info("node centered tests")
v_nc = v.as_centered('node')
exact_nc = viscid.empty_like(v_nc['x'])
X, Y, Z = exact_nc.get_crds_nc(shaped=True) # pylint: disable=W0612
if HAS_NUMEXPR:
exact_nc[:, :, :] = ne.evaluate("cos(X) - sin(Y) - cos(Z)")
else:
exact_nc[:, :, :] = np.cos(X) - np.sin(Y) - np.cos(Z)
# FIXME: why is the error so much larger here?
run_div_test(v_nc, exact_nc, title='Node Centered', show=args.show,
ignore_inexact=True)
logger.info("cell centered tests")
v_cc = v_nc.as_centered('cell')
run_div_test(v_cc, exact_cc, title="Cell Centered", show=args.show)
return 0
def main():
mhd_type = "C3"
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()
b = f['b_cc']
b1 = f['b_fc']
e_cc = f['e_cc']
e_ec = f['e_ec']
# divb = f['divB']
# viscid.interact()
if True:
bD = viscid.empty_like(b)
bD.data = np.array(b.data)
b1D = viscid.empty_like(b1)
b1D.data = np.array(b1.data)
mask5 = viscid.make_spherical_mask(bD, rmax=3.5)
mask1_5 = viscid.make_spherical_mask(bD, rmax=1.5)
viscid.fill_dipole(bD, mask=mask5)
viscid.set_in_region(bD, bD, 0.0, 0.0, mask=mask1_5, out=bD)
# compare_vectors(_b, bD, make_plots=True)
mask5 = viscid.make_spherical_mask(b1D, rmax=3.5)
mask1_5 = viscid.make_spherical_mask(b1D, rmax=1.5)
viscid.fill_dipole(b1D, mask=mask5)
viscid.set_in_region(b1D, b1D, 0.0, 0.0, mask=mask1_5, out=b1D)
compare_vectors(bD["x=1:-1, y=1:-1, z=1:-1"], b1D.as_cell_centered(),
make_plots=True)
# plt.clf()
# dkwargs = dict(symmetric=True, earth=True, clim=(-1e2, 1e2))
# ax1 = plt.subplot(311)
# vlt.plot(viscid.div(b1)['y=0j'], **dkwargs)
# plt.subplot(312, sharex=ax1, sharey=ax1)
# vlt.plot(viscid.div(b)['y=0j'], **dkwargs)
# plt.subplot(313, sharex=ax1, sharey=ax1)
# vlt.plot(viscid.div(b1D)['y=0j'], **dkwargs)
# vlt.show()
bD = b1D = mask5 = mask1_5 = None
# straight up interpolate b1 to cc crds and compare with b
if True:
b1_cc = viscid.interp_trilin(b1, b).as_flat()
viscid.set_in_region(b, b, alpha=0.0, beta=0.0, out=b,
mask=viscid.make_spherical_mask(b, rmax=5.0))
viscid.set_in_region(b1_cc, b1_cc, alpha=0.0, beta=0.0, out=b1_cc,
mask=viscid.make_spherical_mask(b1_cc, rmax=5.0))
compare_vectors(b, b1_cc, make_plots=True)
# make div?
if True:
# make seeds for 1.5x supersampling b1
n = 128
seeds = viscid.Volume((5.1, -0.02, -5.0), (12.0, 0.02, 5.0), (n, 3, n))
# do interpolation onto new seeds
b2 = viscid.interp_trilin(b1, seeds)
div_b = viscid.div(b)
div_b1 = viscid.div(b1)
div_b2 = viscid.div(b2)
viscid.set_in_region(div_b, div_b, alpha=0.0, beta=0.0, out=div_b,
mask=viscid.make_spherical_mask(div_b, rmax=5.0))
viscid.set_in_region(div_b1, div_b1, alpha=0.0, beta=0.0, out=div_b1,
mask=viscid.make_spherical_mask(div_b1, rmax=5.0))
viscid.set_in_region(div_b2, div_b2, alpha=0.0, beta=0.0, out=div_b2,
mask=viscid.make_spherical_mask(div_b2, rmax=5.0))
viscid.set_in_region(divb, divb, alpha=0.0, beta=0.0, out=divb,
mask=viscid.make_spherical_mask(divb, rmax=5.0))
plt.clf()
ax1 = vlt.subplot(311)
vlt.plot(div_b['y=0j'], symmetric=True, earth=True)
vlt.subplot(312, sharex=ax1, sharey=ax1)
# vlt.plot(div_b1['y=0j'], symmetric=True, earth=True)
vlt.plot(div_b2['y=0j'], symmetric=True, earth=True)
vlt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(divb['y=0j'], symmetric=True, earth=True)
vlt.show()
return 0
def get_mp_info(pp, b, j, e, cache=True, cache_dir=None,
slc="x=5.5j:11.0j, y=-4.0j:4.0j, z=-3.6j:3.6j",
fit="mp_xloc", fit_p0=(9.0, 0.0, 0.0, 1.0, -1.0, -1.0)):
"""Get info about m-pause as flattened fields
Notes:
The first thing this function does is mask locations where
the GSE-y current density < 1e-4. This masks out the bow
shock and current free regions. This works for southward IMF,
but it is not very general.
Parameters:
pp (ScalarcField): pressure
b (VectorField): magnetic field
j (VectorField): current density
e (VectorField, None): electric field (same centering as b). If
None, then the info that requires E will be filled with NaN
cache (bool, str): Save to and load from cache, if "force",
then don't load from cache if it exists, but do save a
cache at the end
cache_dir (str): Directory for cache, if None, same directory
as that file to which the grid belongs
slc (str): slice that gives a box that contains the m-pause
fit (str): to which resulting field should the paraboloid be fit,
defaults to mp_xloc, but pp_max_xloc might be useful in some
circumstances
fit_p0 (tuple): Initial guess vector for paraboloid fit
Returns:
dict: Unless otherwise noted, the entiries are 2D (y-z) fields
- **mp_xloc** location of minimum abs(Bz), this works
better than max of J^2 for FTEs
- **mp_sheath_edge** location where Jy > 0.1 * Jy when
coming in from the sheath side
- **mp_sphere_edge** location where Jy > 0.1 * Jy when
coming in from the sphere side
- **mp_width** difference between m-sheath edge and
msphere edge
- **mp_shear** magnetic shear taken 6 grid points into
the m-sheath / m-sphere
- **pp_max** max pp
- **pp_max_xloc** location of max pp
- **epar_max** max e parallel
- **epar_max_xloc** location of max e parallel
- **paraboloid** numpy.recarray of paraboloid fit. The
parameters are given in the 0th element, and
the 1st element contains the 1-sigma values for the fit
Raises:
RuntimeError: if using MHD crds instead of GSE crds
"""
if not cache_dir:
cache_dir = pp.find_info("_viscid_dirname", "./")
run_name = pp.find_info("run", None)
if cache and run_name:
t = pp.time
mp_fname = "{0}/{1}.mpause.{2:06.0f}".format(cache_dir, run_name, t)
else:
mp_fname = ""
try:
force = cache.strip().lower() == "force"
except AttributeError:
force = False
try:
if force or not mp_fname or not os.path.isfile(mp_fname + ".xdmf"):
raise IOError()
mp_info = {}
with viscid.load_file(mp_fname + ".xdmf") as dat:
fld_names = ["mp_xloc", "mp_sheath_edge", "mp_sphere_edge",
"mp_width", "mp_shear", "pp_max", "pp_max_xloc",
"epar_max", "epar_max_xloc"]
for fld_name in fld_names:
mp_info[fld_name] = dat[fld_name]["x=0"]
except (IOError, KeyError):
mp_info = {}
crd_system = viscid.as_crd_system(b, None)
if crd_system != 'gse':
raise RuntimeError("get_mp_info can't work in MHD crds, "
"switch to GSE please")
if j.nr_patches == 1:
pp_block = pp[slc]
b_block = b[slc]
j_block = j[slc]
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = e[slc]
else:
# interpolate an amr grid so we can proceed
obnd = pp.get_slice_extent(slc)
dx = np.min(pp.skeleton.L / pp.skeleton.n, axis=0)
nx = np.ceil((obnd[1] - obnd[0]) / dx)
vol = viscid.seed.Volume(obnd[0], obnd[1], nx, cache=True)
pp_block = vol.wrap_field(viscid.interp_trilin(pp, vol),
name="P").as_cell_centered()
b_block = vol.wrap_field(viscid.interp_trilin(b, vol),
name="B").as_cell_centered()
j_block = vol.wrap_field(viscid.interp_trilin(j, vol),
name="J").as_cell_centered()
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = vol.wrap_field(viscid.interp_trilin(e, vol),
name="E").as_cell_centered()
# jsq = viscid.dot(j_block, j_block)
bsq = viscid.dot(b_block, b_block)
# extract ndarrays and mask out bow shock / current free regions
maskval = 1e-4
jy_mask = j_block['y'].data < maskval
masked_bsq = 1.0 * bsq
masked_bsq.data = np.ma.masked_where(jy_mask, bsq)
xcc = j_block.get_crd_cc('x')
nx = len(xcc)
mp_xloc = np.argmin(masked_bsq, axis=0) # indices
mp_xloc = mp_xloc.wrap(xcc[mp_xloc.data]) # location
pp_max = np.max(pp_block, axis=0)
pp_max_xloc = np.argmax(pp_block, axis=0) # indices
pp_max_xloc = pp_max_xloc.wrap(xcc[pp_max_xloc.data]) # location
epar = viscid.project(e_block, b_block)
epar_max = np.max(epar, axis=0)
epar_max_xloc = np.argmax(epar, axis=0) # indices
epar_max_xloc = pp_max_xloc.wrap(xcc[epar_max_xloc.data]) # location
_ret = find_mp_edges(j_block, 0.1, 0.1, maskval=maskval)
sheath_edge, msphere_edge, mp_width, sheath_ind, sphere_ind = _ret
# extract b and b**2 at sheath + 6 grid points and sphere - 6 grid pointns
# clipping cases where things go outside the block. clipped ponints are
# set to nan
step = 6
# extract b
if b_block.layout == "flat":
comp_axis = 0
ic, _, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ic, ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ic, ix, iy, iz]
elif b_block.layout == "interlaced":
comp_axis = 3
_, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape[:-1]])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ix, iy, iz]
# extract b**2
bmag_sheath = np.sqrt(np.sum(b_sheath**2, axis=comp_axis))
bmag_sphere = np.sqrt(np.sum(b_sphere**2, axis=comp_axis))
costheta = (np.sum(b_sheath * b_sphere, axis=comp_axis) /
(bmag_sphere * bmag_sheath))
costheta = np.where((sheath_ind + step < nx) & (sphere_ind - step >= 0),
costheta, np.nan)
mp_shear = mp_width.wrap((180.0 / np.pi) * np.arccos(costheta))
# don't bother with pretty name since it's not written to file
# plane_crds = b_block.crds.slice_keep('x=0', cc=True)
# fld_kwargs = dict(center="Cell", time=b.time)
mp_width.name = "mp_width"
mp_xloc.name = "mp_xloc"
sheath_edge.name = "mp_sheath_edge"
msphere_edge.name = "mp_sphere_edge"
mp_shear.name = "mp_shear"
pp_max.name = "pp_max"
pp_max_xloc.name = "pp_max_xloc"
epar_max.name = "epar_max"
epar_max_xloc.name = "epar_max_xloc"
mp_info = {}
mp_info["mp_width"] = mp_width
mp_info["mp_xloc"] = mp_xloc
mp_info["mp_sheath_edge"] = sheath_edge
mp_info["mp_sphere_edge"] = msphere_edge
mp_info["mp_shear"] = mp_shear
mp_info["pp_max"] = pp_max
mp_info["pp_max_xloc"] = pp_max_xloc
mp_info["epar_max"] = epar_max
mp_info["epar_max_xloc"] = epar_max_xloc
# cache new fields to disk
if mp_fname:
viscid.save_fields(mp_fname + ".h5", list(mp_info.values()))
try:
_paraboloid_params = fit_paraboloid(mp_info[fit], p0=fit_p0)
mp_info["paraboloid"] = _paraboloid_params
except ImportError as _exception:
try:
msg = _exception.message
except AttributeError:
msg = _exception.msg
mp_info["paraboloid"] = viscid.DeferredImportError(msg)
mp_info["mp_width"].pretty_name = "Magnetopause Width"
mp_info["mp_xloc"].pretty_name = "Magnetopause $X_{gse}$ Location"
mp_info["mp_sheath_edge"].pretty_name = "Magnetosheath Edge"
mp_info["mp_sphere_edge"].pretty_name = "Magnetosphere Edge"
mp_info["mp_shear"].pretty_name = "Magnetic Shear"
mp_info["pp_max"].pretty_name = "Max Pressure"
mp_info["pp_max_xloc"].pretty_name = "Max Pressure Location"
mp_info["epar_max"].pretty_name = "Max E Parallel"
mp_info["epar_max_xloc"].pretty_name = "Max E Parallel Location"
return mp_info
def main():
mhd_type = "C3"
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()
b = f['b_cc']
b1 = f['b_fc']
e_cc = f['e_cc']
e_ec = f['e_ec']
# divb = f['divB']
# viscid.interact()
if True:
bD = viscid.empty_like(b)
bD.data = np.array(b.data)
b1D = viscid.empty_like(b1)
b1D.data = np.array(b1.data)
mask5 = viscid.make_spherical_mask(bD, rmax=3.5)
mask1_5 = viscid.make_spherical_mask(bD, rmax=1.5)
viscid.fill_dipole(bD, mask=mask5)
viscid.set_in_region(bD, bD, 0.0, 0.0, mask=mask1_5, out=bD)
# compare_vectors(_b, bD, make_plots=True)
mask5 = viscid.make_spherical_mask(b1D, rmax=3.5)
mask1_5 = viscid.make_spherical_mask(b1D, rmax=1.5)
viscid.fill_dipole(b1D, mask=mask5)
viscid.set_in_region(b1D, b1D, 0.0, 0.0, mask=mask1_5, out=b1D)
compare_vectors(bD["x=1:-1, y=1:-1, z=1:-1"],
b1D.as_cell_centered(),
make_plots=True)
# plt.clf()
# dkwargs = dict(symmetric=True, earth=True, clim=(-1e2, 1e2))
# ax1 = plt.subplot(311)
# vlt.plot(viscid.div(b1)['y=0j'], **dkwargs)
# plt.subplot(312, sharex=ax1, sharey=ax1)
# vlt.plot(viscid.div(b)['y=0j'], **dkwargs)
# plt.subplot(313, sharex=ax1, sharey=ax1)
# vlt.plot(viscid.div(b1D)['y=0j'], **dkwargs)
# vlt.show()
bD = b1D = mask5 = mask1_5 = None
# straight up interpolate b1 to cc crds and compare with b
if True:
b1_cc = viscid.interp_trilin(b1, b).as_flat()
viscid.set_in_region(b,
b,
alpha=0.0,
beta=0.0,
out=b,
mask=viscid.make_spherical_mask(b, rmax=5.0))
viscid.set_in_region(b1_cc,
b1_cc,
alpha=0.0,
beta=0.0,
out=b1_cc,
mask=viscid.make_spherical_mask(b1_cc, rmax=5.0))
compare_vectors(b, b1_cc, make_plots=True)
# make div?
if True:
# make seeds for 1.5x supersampling b1
n = 128
seeds = viscid.Volume((5.1, -0.02, -5.0), (12.0, 0.02, 5.0), (n, 3, n))
# do interpolation onto new seeds
b2 = viscid.interp_trilin(b1, seeds)
div_b = viscid.div(b)
div_b1 = viscid.div(b1)
div_b2 = viscid.div(b2)
viscid.set_in_region(div_b,
div_b,
alpha=0.0,
beta=0.0,
out=div_b,
mask=viscid.make_spherical_mask(div_b, rmax=5.0))
viscid.set_in_region(div_b1,
div_b1,
alpha=0.0,
beta=0.0,
out=div_b1,
mask=viscid.make_spherical_mask(div_b1, rmax=5.0))
viscid.set_in_region(div_b2,
div_b2,
alpha=0.0,
beta=0.0,
out=div_b2,
mask=viscid.make_spherical_mask(div_b2, rmax=5.0))
viscid.set_in_region(divb,
divb,
alpha=0.0,
beta=0.0,
out=divb,
mask=viscid.make_spherical_mask(divb, rmax=5.0))
plt.clf()
ax1 = vlt.subplot(311)
vlt.plot(div_b['y=0j'], symmetric=True, earth=True)
vlt.subplot(312, sharex=ax1, sharey=ax1)
# vlt.plot(div_b1['y=0j'], symmetric=True, earth=True)
vlt.plot(div_b2['y=0j'], symmetric=True, earth=True)
vlt.subplot(313, sharex=ax1, sharey=ax1)
vlt.plot(divb['y=0j'], symmetric=True, earth=True)
vlt.show()
return 0
def get_mp_info(pp,
b,
j,
e,
cache=True,
cache_dir=None,
slc="x=5.5f:11.0f, y=-4.0f:4.0f, z=-3.6f:3.6f",
fit="mp_xloc",
fit_p0=(9.0, 0.0, 0.0, 1.0, -1.0, -1.0)):
"""Get info about m-pause as flattened fields
Notes:
The first thing this function does is mask locations where
the GSE-y current density < 1e-4. This masks out the bow
shock and current free regions. This works for southward IMF,
but it is not very general.
Parameters:
pp (ScalarcField): pressure
b (VectorField): magnetic field
j (VectorField): current density
e (VectorField, None): electric field (same centering as b). If
None, then the info that requires E will be filled with NaN
cache (bool, str): Save to and load from cache, if "force",
then don't load from cache if it exists, but do save a
cache at the end
cache_dir (str): Directory for cache, if None, same directory
as that file to which the grid belongs
slc (str): slice that gives a box that contains the m-pause
fit (str): to which resulting field should the paraboloid be fit,
defaults to mp_xloc, but pp_max_xloc might be useful in some
circumstances
fit_p0 (tuple): Initial guess vector for paraboloid fit
Returns:
dict: Unless otherwise noted, the entiries are 2D (y-z) fields
- **mp_xloc** location of minimum abs(Bz), this works
better than max of J^2 for FTEs
- **mp_sheath_edge** location where Jy > 0.1 * Jy when
coming in from the sheath side
- **mp_sphere_edge** location where Jy > 0.1 * Jy when
coming in from the sphere side
- **mp_width** difference between m-sheath edge and
msphere edge
- **mp_shear** magnetic shear taken 6 grid points into
the m-sheath / m-sphere
- **pp_max** max pp
- **pp_max_xloc** location of max pp
- **epar_max** max e parallel
- **epar_max_xloc** location of max e parallel
- **paraboloid** numpy.recarray of paraboloid fit. The
parameters are given in the 0th element, and
the 1st element contains the 1-sigma values for the fit
Raises:
RuntimeError: if using MHD crds instead of GSE crds
"""
if not cache_dir:
cache_dir = pp.find_info("_viscid_dirname", "./")
run_name = pp.find_info("run", None)
if cache and run_name:
t = pp.time
mp_fname = "{0}/{1}.mpause.{2:06.0f}".format(cache_dir, run_name, t)
else:
mp_fname = ""
try:
force = cache.strip().lower() == "force"
except AttributeError:
force = False
try:
if force or not mp_fname or not os.path.isfile(mp_fname + ".xdmf"):
raise IOError()
mp_info = {}
with viscid.load_file(mp_fname + ".xdmf") as dat:
fld_names = [
"mp_xloc", "mp_sheath_edge", "mp_sphere_edge", "mp_width",
"mp_shear", "pp_max", "pp_max_xloc", "epar_max",
"epar_max_xloc"
]
for fld_name in fld_names:
mp_info[fld_name] = dat[fld_name]["x=0"]
except (IOError, KeyError):
mp_info = {}
crd_system = viscid.as_crd_system(b, None)
if crd_system != 'gse':
raise RuntimeError("get_mp_info can't work in MHD crds, "
"switch to GSE please")
if j.nr_patches == 1:
pp_block = pp[slc]
b_block = b[slc]
j_block = j[slc]
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = e[slc]
else:
# interpolate an amr grid so we can proceed
obnd = pp.get_slice_extent(slc)
dx = np.min(pp.skeleton.L / pp.skeleton.n, axis=0)
nx = np.ceil((obnd[1] - obnd[0]) / dx)
vol = viscid.seed.Volume(obnd[0], obnd[1], nx, cache=True)
pp_block = vol.wrap_field(viscid.interp_trilin(pp, vol),
name="P").as_cell_centered()
b_block = vol.wrap_field(viscid.interp_trilin(b, vol),
name="B").as_cell_centered()
j_block = vol.wrap_field(viscid.interp_trilin(j, vol),
name="J").as_cell_centered()
if e is None:
e_block = np.nan * viscid.empty_like(j_block)
else:
e_block = vol.wrap_field(viscid.interp_trilin(e, vol),
name="E").as_cell_centered()
# jsq = viscid.dot(j_block, j_block)
bsq = viscid.dot(b_block, b_block)
# extract ndarrays and mask out bow shock / current free regions
maskval = 1e-4
jy_mask = j_block['y'].data < maskval
masked_bsq = 1.0 * bsq
masked_bsq.data = np.ma.masked_where(jy_mask, bsq)
xcc = j_block.get_crd_cc('x')
nx = len(xcc)
mp_xloc = np.argmin(masked_bsq, axis=0) # indices
mp_xloc = mp_xloc.wrap(xcc[mp_xloc.data]) # location
pp_max = np.max(pp_block, axis=0)
pp_max_xloc = np.argmax(pp_block, axis=0) # indices
pp_max_xloc = pp_max_xloc.wrap(xcc[pp_max_xloc.data]) # location
epar = viscid.project(e_block, b_block)
epar_max = np.max(epar, axis=0)
epar_max_xloc = np.argmax(epar, axis=0) # indices
epar_max_xloc = pp_max_xloc.wrap(xcc[epar_max_xloc.data]) # location
_ret = find_mp_edges(j_block, 0.1, 0.1, maskval=maskval)
sheath_edge, msphere_edge, mp_width, sheath_ind, sphere_ind = _ret
# extract b and b**2 at sheath + 6 grid points and sphere - 6 grid pointns
# clipping cases where things go outside the block. clipped ponints are
# set to nan
step = 6
# extract b
if b_block.layout == "flat":
comp_axis = 0
ic, _, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ic, ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ic, ix, iy, iz]
elif b_block.layout == "interlaced":
comp_axis = 3
_, iy, iz = np.ix_(*[np.arange(si) for si in b_block.shape[:-1]])
ix = np.clip(sheath_ind + step, 0, nx - 1)
b_sheath = b_block.data[ix, iy, iz]
ix = np.clip(sheath_ind - step, 0, nx - 1)
b_sphere = b_block.data[ix, iy, iz]
# extract b**2
bmag_sheath = np.sqrt(np.sum(b_sheath**2, axis=comp_axis))
bmag_sphere = np.sqrt(np.sum(b_sphere**2, axis=comp_axis))
costheta = (np.sum(b_sheath * b_sphere, axis=comp_axis) /
(bmag_sphere * bmag_sheath))
costheta = np.where(
(sheath_ind + step < nx) & (sphere_ind - step >= 0), costheta,
np.nan)
mp_shear = mp_width.wrap((180.0 / np.pi) * np.arccos(costheta))
# don't bother with pretty name since it's not written to file
# plane_crds = b_block.crds.slice_keep('x=0', cc=True)
# fld_kwargs = dict(center="Cell", time=b.time)
mp_width.name = "mp_width"
mp_xloc.name = "mp_xloc"
sheath_edge.name = "mp_sheath_edge"
msphere_edge.name = "mp_sphere_edge"
mp_shear.name = "mp_shear"
pp_max.name = "pp_max"
pp_max_xloc.name = "pp_max_xloc"
epar_max.name = "epar_max"
epar_max_xloc.name = "epar_max_xloc"
mp_info = {}
mp_info["mp_width"] = mp_width
mp_info["mp_xloc"] = mp_xloc
mp_info["mp_sheath_edge"] = sheath_edge
mp_info["mp_sphere_edge"] = msphere_edge
mp_info["mp_shear"] = mp_shear
mp_info["pp_max"] = pp_max
mp_info["pp_max_xloc"] = pp_max_xloc
mp_info["epar_max"] = epar_max
mp_info["epar_max_xloc"] = epar_max_xloc
# cache new fields to disk
if mp_fname:
viscid.save_fields(mp_fname + ".h5", mp_info.values())
try:
_paraboloid_params = fit_paraboloid(mp_info[fit], p0=fit_p0)
mp_info["paraboloid"] = _paraboloid_params
except ImportError as _exception:
try:
msg = _exception.message
except AttributeError:
msg = _exception.msg
mp_info["paraboloid"] = viscid.DeferredImportError(msg)
mp_info["mp_width"].pretty_name = "Magnetopause Width"
mp_info["mp_xloc"].pretty_name = "Magnetopause $X_{gse}$ Location"
mp_info["mp_sheath_edge"].pretty_name = "Magnetosheath Edge"
mp_info["mp_sphere_edge"].pretty_name = "Magnetosphere Edge"
mp_info["mp_shear"].pretty_name = "Magnetic Shear"
mp_info["pp_max"].pretty_name = "Max Pressure"
mp_info["pp_max_xloc"].pretty_name = "Max Pressure Location"
mp_info["epar_max"].pretty_name = "Max E Parallel"
mp_info["epar_max_xloc"].pretty_name = "Max E Parallel Location"
return mp_info