def test_input_args(self):
""" Check that scalar_field can take different input arguments """
# Check for 2D arrays as positions vectors, and a function for
# the data
f = lambda x, y, z: x**2 + y**2
x, y = np.mgrid[-3:3, -3:3]
z = np.zeros_like(x)
ss = sources.scalar_field(x, y, z, f, figure=None)
self.check_positions(ss, x, y, z)
s = f(x, y, z)
self.check_scalars(ss, s)
# Check for a 2D array as data, and no position vectors
s = np.random.random((10, 10))
ss = sources.scalar_field(s, figure=None)
self.check_scalars(ss, s)
# Check for a 3D array as data, and no position vectors
s = np.random.random((10, 10, 10))
ss = sources.scalar_field(s, figure=None)
self.check_scalars(ss, s)
# Check for a 3D array as data, and 3D arrays as position
x, y, z = np.mgrid[-3:3, -3:3, -3:3]
ss = sources.scalar_field(x, y, z, z, figure=None)
self.check_positions(ss, x, y, z)
self.check_scalars(ss, z)
def test_input_args(self):
""" Check that scalar_field can take different input arguments """
# Check for 2D arrays as positions vectors, and a function for
# the data
f = lambda x, y, z: x**2 + y**2
x, y = np.mgrid[-3:3, -3:3]
z = np.zeros_like(x)
ss = sources.scalar_field(x, y, z, f, figure=None)
self.check_positions(ss, x, y, z)
s = f(x, y, z)
self.check_scalars(ss, s)
# Check for a 2D array as data, and no position vectors
s = np.random.random((10, 10))
ss = sources.scalar_field(s, figure=None)
self.check_scalars(ss, s)
# Check for a 3D array as data, and no position vectors
s = np.random.random((10, 10, 10))
ss = sources.scalar_field(s, figure=None)
self.check_scalars(ss, s)
# Check for a 3D array as data, and 3D arrays as position
x, y, z = np.mgrid[-3:3, -3:3, -3:3]
ss = sources.scalar_field(x, y, z, z, figure=None)
self.check_positions(ss, x, y, z)
self.check_scalars(ss, z)
def get_sacdata_mlab(f, cube_slice, flux=True):
"""
Reads in useful variables from a hdf5 file to vtk data structures
Parameters
----------
f : hdf5 file handle
SAC HDF5 file
flux : boolean
Read variables for flux calculation?
cube_slice : np.slice
Slice to apply to the arrays
Returns
-------
bfield, vfield[, density, valf, cs, beta]
"""
# Do this before convert_B
if flux:
va_f = f.get_va()
cs_f = f.get_cs()
thermal_p, mag_p = f.get_thermalp(beta=True)
beta_f = mag_p / thermal_p
# Convert B to Tesla
f.convert_B()
# Create TVTK datasets
bfield = vector_field(
f.w_sac["b3"][cube_slice] * 1e3,
f.w_sac["b2"][cube_slice] * 1e3,
f.w_sac["b1"][cube_slice] * 1e3,
name="Magnetic Field",
figure=None,
)
vfield = vector_field(
f.w_sac["v3"][cube_slice] / 1e3,
f.w_sac["v2"][cube_slice] / 1e3,
f.w_sac["v1"][cube_slice] / 1e3,
name="Velocity Field",
figure=None,
)
if flux:
density = scalar_field(f.w_sac["rho"][cube_slice], name="Density", figure=None)
valf = scalar_field(va_f, name="Alven Speed", figure=None)
cs = scalar_field(cs_f, name="Sound Speed", figure=None)
beta = scalar_field(beta_f, name="Beta", figure=None)
return bfield, vfield, density, valf, cs, beta
else:
return bfield, vfield
def yt_to_mlab_scalar(ds, key, cube_slice=np.s_[:, :, :], field_name=""):
"""
Convert obe yt keys to a mlab scalar field
Parameters
----------
ds : yt dataset
The dataset to get the data from.
key : string
yt field names for the three vector components.
cube_slice : numpy slice
The array slice to crop the yt fields with.
field_name : string
The mlab name for the field.
Returns
-------
field : mayavi vector field
"""
cg = ds.index.grids[0]
return scalar_field(cg[key][cube_slice], name=field_name, figure=None)
def get_yt_mlab(ds, cube_slice, flux=True):
"""
Reads in useful variables from yt to vtk data structures, converts into SI
units before return.
Parameters
----------
ds : yt dataset
with derived fields
flux : boolean
Read variables for flux calculation?
cube_slice : np.slice
Slice to apply to the arrays
Returns
-------
if flux:
bfield, vfield, density, valf, cs, beta
else:
bfield, vfield
"""
cg = ds.index.grids[0]
# Create TVTK datasets
bfield = yt_to_mlab_vector(
ds, "mag_field_x", "mag_field_y", "mag_field_z", cube_slice=cube_slice, field_name="Magnetic Field"
)
vfield = yt_to_mlab_vector(
ds, "velocity_x", "velocity_y", "velocity_z", cube_slice=cube_slice, field_name="Velocity Field"
)
if flux:
density = scalar_field(cg["density"][cube_slice] * 1e-3, name="Density", figure=None)
valf = scalar_field(cg["alfven_speed"] * 1e-2, name="Alven Speed", figure=None)
cs = scalar_field(cg["sound_speed"] * 1e-2, name="Sound Speed", figure=None)
beta = scalar_field(cg["plasma_beta"], name="Beta", figure=None)
return bfield, vfield, density, valf, cs, beta
else:
return bfield, vfield
