def _ortho_pixelize(self, data_source, field, bounds, size, antialias, dim,
periodic):
# We should be using fcoords
period = self.period[:2].copy() # dummy here
period[0] = self.period[self.x_axis[dim]]
period[1] = self.period[self.y_axis[dim]]
if hasattr(period, 'in_units'):
period = period.in_units("code_length").d
buff = np.zeros((size[1], size[0]), dtype="f8")
finfo = self.ds._get_field_info(field)
nodal_flag = finfo.nodal_flag
if np.any(nodal_flag):
nodal_data = get_nodal_data(data_source, field)
coord = data_source.coord.d
pixelize_cartesian_nodal(buff, data_source['px'],
data_source['py'], data_source['pz'],
data_source['pdx'], data_source['pdy'],
data_source['pdz'], nodal_data, coord,
bounds, int(antialias), period,
int(periodic))
else:
pixelize_cartesian(buff, data_source['px'], data_source['py'],
data_source['pdx'],
data_source['pdy'], data_source[field], bounds,
int(antialias), period, int(periodic))
return buff
def _ortho_pixelize(self, data_source, field, bounds, size, antialias, dim,
periodic):
from yt.data_objects.construction_data_containers import YTParticleProj
from yt.data_objects.selection_objects.slices import YTSlice
from yt.frontends.sph.data_structures import ParticleDataset
from yt.frontends.stream.data_structures import StreamParticlesDataset
# We should be using fcoords
field = data_source._determine_fields(field)[0]
finfo = data_source.ds.field_info[field]
period = self.period[:2].copy() # dummy here
period[0] = self.period[self.x_axis[dim]]
period[1] = self.period[self.y_axis[dim]]
if hasattr(period, "in_units"):
period = period.in_units("code_length").d
buff = np.zeros((size[1], size[0]), dtype="f8")
particle_datasets = (ParticleDataset, StreamParticlesDataset)
is_sph_field = finfo.is_sph_field
finfo = self.ds._get_field_info(field)
if np.any(finfo.nodal_flag):
nodal_data = get_nodal_data(data_source, field)
coord = data_source.coord.d
pixelize_cartesian_nodal(
buff,
data_source["px"],
data_source["py"],
data_source["pz"],
data_source["pdx"],
data_source["pdy"],
data_source["pdz"],
nodal_data,
coord,
bounds,
int(antialias),
period,
int(periodic),
)
elif isinstance(data_source.ds, particle_datasets) and is_sph_field:
ptype = field[0]
if ptype == "gas":
ptype = data_source.ds._sph_ptypes[0]
px_name = self.axis_name[self.x_axis[dim]]
py_name = self.axis_name[self.y_axis[dim]]
ounits = data_source.ds.field_info[field].output_units
bnds = data_source.ds.arr(bounds, "code_length").tolist()
if isinstance(data_source, YTParticleProj):
weight = data_source.weight_field
le, re = data_source.data_source.get_bbox()
xa = self.x_axis[dim]
ya = self.y_axis[dim]
# If we're not periodic, we need to clip to the boundary edges
# or we get errors about extending off the edge of the region.
if not self.ds.periodicity[xa]:
le[xa] = max(bounds[0], self.ds.domain_left_edge[xa])
re[xa] = min(bounds[1], self.ds.domain_right_edge[xa])
else:
le[xa] = bounds[0]
re[xa] = bounds[1]
if not self.ds.periodicity[ya]:
le[ya] = max(bounds[2], self.ds.domain_left_edge[ya])
re[ya] = min(bounds[3], self.ds.domain_right_edge[ya])
else:
le[ya] = bounds[2]
re[ya] = bounds[3]
# We actually need to clip these
proj_reg = data_source.ds.region(
left_edge=le,
right_edge=re,
center=data_source.center,
data_source=data_source.data_source,
)
proj_reg.set_field_parameter("axis", data_source.axis)
buff = np.zeros(size, dtype="float64")
if weight is None:
for chunk in proj_reg.chunks([], "io"):
data_source._initialize_projected_units([field], chunk)
pixelize_sph_kernel_projection(
buff,
chunk[ptype, px_name].to("code_length"),
chunk[ptype, py_name].to("code_length"),
chunk[ptype, "smoothing_length"].to("code_length"),
chunk[ptype, "mass"].to("code_mass"),
chunk[ptype, "density"].to("code_density"),
chunk[field].in_units(ounits),
bnds,
check_period=int(periodic),
period=period,
)
# We use code length here, but to get the path length right
# we need to multiply by the conversion factor between
# code length and the unit system's length unit
default_path_length_unit = data_source.ds.unit_system[
"length"]
dl_conv = data_source.ds.quan(
1.0, "code_length").to(default_path_length_unit)
buff *= dl_conv.v
# if there is a weight field, take two projections:
# one of field*weight, the other of just weight, and divide them
else:
weight_buff = np.zeros(size, dtype="float64")
buff = np.zeros(size, dtype="float64")
wounits = data_source.ds.field_info[weight].output_units
for chunk in proj_reg.chunks([], "io"):
data_source._initialize_projected_units([field], chunk)
data_source._initialize_projected_units([weight],
chunk)
pixelize_sph_kernel_projection(
buff,
chunk[ptype, px_name].to("code_length"),
chunk[ptype, py_name].to("code_length"),
chunk[ptype, "smoothing_length"].to("code_length"),
chunk[ptype, "mass"].to("code_mass"),
chunk[ptype, "density"].to("code_density"),
chunk[field].in_units(ounits),
bnds,
check_period=int(periodic),
period=period,
weight_field=chunk[weight].in_units(wounits),
)
mylog.info(
"Making a fixed resolution buffer of (%s) %d by %d",
weight,
size[0],
size[1],
)
for chunk in proj_reg.chunks([], "io"):
data_source._initialize_projected_units([weight],
chunk)
pixelize_sph_kernel_projection(
weight_buff,
chunk[ptype, px_name].to("code_length"),
chunk[ptype, py_name].to("code_length"),
chunk[ptype, "smoothing_length"].to("code_length"),
chunk[ptype, "mass"].to("code_mass"),
chunk[ptype, "density"].to("code_density"),
chunk[weight].in_units(wounits),
bnds,
check_period=int(periodic),
period=period,
)
normalization_2d_utility(buff, weight_buff)
elif isinstance(data_source, YTSlice):
smoothing_style = getattr(self.ds, "sph_smoothing_style",
"scatter")
normalize = getattr(self.ds, "use_sph_normalization", True)
if smoothing_style == "scatter":
buff = np.zeros(size, dtype="float64")
if normalize:
buff_den = np.zeros(size, dtype="float64")
for chunk in data_source.chunks([], "io"):
pixelize_sph_kernel_slice(
buff,
chunk[ptype, px_name].to("code_length"),
chunk[ptype, py_name].to("code_length"),
chunk[ptype, "smoothing_length"].to("code_length"),
chunk[ptype, "mass"].to("code_mass"),
chunk[ptype, "density"].to("code_density"),
chunk[field].in_units(ounits),
bnds,
check_period=int(periodic),
period=period,
)
if normalize:
pixelize_sph_kernel_slice(
buff_den,
chunk[ptype, px_name].to("code_length"),
chunk[ptype, py_name].to("code_length"),
chunk[ptype,
"smoothing_length"].to("code_length"),
chunk[ptype, "mass"].to("code_mass"),
chunk[ptype, "density"].to("code_density"),
np.ones(chunk[ptype, "density"].shape[0]),
bnds,
check_period=int(periodic),
period=period,
)
if normalize:
normalization_2d_utility(buff, buff_den)
if smoothing_style == "gather":
# Here we find out which axis are going to be the "x" and
# "y" axis for the actual visualisation and then we set the
# buffer size and bounds to match. The z axis of the plot
# is the axis we slice over and the buffer will be of size 1
# in that dimension
x, y, z = self.x_axis[dim], self.y_axis[dim], dim
buff_size = np.zeros(3, dtype="int64")
buff_size[x] = size[0]
buff_size[y] = size[1]
buff_size[z] = 1
buff_bounds = np.zeros(6, dtype="float64")
buff_bounds[2 * x:2 * x + 2] = bounds[0:2]
buff_bounds[2 * y:2 * y + 2] = bounds[2:4]
buff_bounds[2 * z] = data_source.coord
buff_bounds[2 * z + 1] = data_source.coord
# then we do the interpolation
buff_temp = np.zeros(buff_size, dtype="float64")
fields_to_get = [
"particle_position",
"density",
"mass",
"smoothing_length",
field[1],
]
all_fields = all_data(self.ds,
ptype,
fields_to_get,
kdtree=True)
num_neighbors = getattr(self.ds, "num_neighbors", 32)
interpolate_sph_grid_gather(
buff_temp,
all_fields["particle_position"].to("code_length"),
buff_bounds,
all_fields["smoothing_length"].to("code_length"),
all_fields["mass"].to("code_mass"),
all_fields["density"].to("code_density"),
all_fields[field[1]].in_units(ounits),
self.ds.index.kdtree,
num_neigh=num_neighbors,
use_normalization=normalize,
)
# We swap the axes back so the axis which was sliced over
# is the last axis, as this is the "z" axis of the plots.
if z != 2:
buff_temp = buff_temp.swapaxes(2, z)
if x == 2:
x = z
else:
y = z
buff = buff_temp[:, :, 0]
# Then we just transpose if the buffer x and y are
# different than the plot x and y
if y < x:
buff = buff.transpose()
else:
raise NotImplementedError(
"A pixelization routine has not been implemented for %s "
"data objects" % str(type(data_source)))
buff = buff.transpose()
else:
pixelize_cartesian(
buff,
data_source["px"],
data_source["py"],
data_source["pdx"],
data_source["pdy"],
data_source[field],
bounds,
int(antialias),
period,
int(periodic),
)
return buff