def get_cartesian(comm, pos, cosmo=None):
"""
Utility function to convert sky coordinates to Cartesian coordinates and
return the implied box size from the position bounds.
If ``cosmo`` is not provided, return coordinates on the unit sphere.
"""
from nbodykit.utils import get_data_bounds
# get RA,DEC in degrees
ra, dec = numpy.deg2rad(pos[:, 0]), numpy.deg2rad(pos[:, 1])
# cartesian position
x = numpy.cos(dec) * numpy.cos(ra)
y = numpy.cos(dec) * numpy.sin(ra)
z = numpy.sin(dec)
cpos = numpy.vstack([x, y, z]).T
# multiply by comoving distance?
if cosmo is not None:
assert pos.shape[-1] == 3
rdist = cosmo.comoving_distance(pos[:, 2]) # in Mpc/h
cpos = rdist[:, None] * cpos
else:
rdist = None
# min/max of position
cpos_min, cpos_max = get_data_bounds(cpos, comm)
boxsize = numpy.ceil(abs(cpos_max - cpos_min))
return cpos, boxsize, rdist
def get_cartesian(comm, pos, cosmo=None):
"""
Utility function to convert sky coordinates to Cartesian coordinates and
return the implied box size from the position bounds.
If ``cosmo`` is not provided, return coordinates on the unit sphere.
"""
from nbodykit.utils import get_data_bounds
# get RA,DEC in degrees
ra, dec = numpy.deg2rad(pos[:,0]), numpy.deg2rad(pos[:,1])
# cartesian position
x = numpy.cos( dec ) * numpy.cos( ra )
y = numpy.cos( dec ) * numpy.sin( ra )
z = numpy.sin( dec )
cpos = numpy.vstack([x,y,z]).T
# multiply by comoving distance?
if cosmo is not None:
assert pos.shape[-1] == 3
rdist = cosmo.comoving_distance(pos[:,2]) # in Mpc/h
cpos = rdist[:,None] * cpos
else:
rdist = None
# min/max of position
cpos_min, cpos_max = get_data_bounds(cpos, comm)
boxsize = abs(cpos_max - cpos_min)
# some padding to avoid weird effects with domain decomposition
# like sitting on an edge and goes out of bound due to round off errors.
return cpos, cpos_min - 1e-3 * boxsize, cpos_max + 1e-3 * boxsize, rdist
def get_cartesian(comm, pos, cosmo=None):
"""
Utility function to convert sky coordinates to Cartesian coordinates and
return the implied box size from the position bounds.
If ``cosmo`` is not provided, return coordinates on the unit sphere.
"""
from nbodykit.utils import get_data_bounds
# get RA,DEC in degrees
ra, dec = numpy.deg2rad(pos[:,0]), numpy.deg2rad(pos[:,1])
# cartesian position
x = numpy.cos( dec ) * numpy.cos( ra )
y = numpy.cos( dec ) * numpy.sin( ra )
z = numpy.sin( dec )
cpos = numpy.vstack([x,y,z]).T
# multiply by comoving distance?
if cosmo is not None:
assert pos.shape[-1] == 3
rdist = cosmo.comoving_distance(pos[:,2]) # in Mpc/h
cpos = rdist[:,None] * cpos
else:
rdist = None
# min/max of position
cpos_min, cpos_max = get_data_bounds(cpos, comm)
boxsize = abs(cpos_max - cpos_min)
# some padding to avoid weird effects with domain decomposition
# like sitting on an edge and goes out of bound due to round off errors.
return cpos, cpos_min - 1e-3 * boxsize, cpos_max + 1e-3 * boxsize, rdist
def _define_bbox(self, position, selection, species):
"""
Internal function to put the :attr:`randoms` CatalogSource in a
Cartesian bounding box, using the positions of the given species.
This function computings the size and center of the bounding box.
#. `BoxSize` : array_like, (3,)
if not provided, the BoxSize in each direction is computed from
the maximum extent of the Cartesian coordinates of the :attr:`randoms`
Source, with an optional, additional padding
#. `BoxCenter`: array_like, (3,)
the mean coordinate value in each direction; this is used to re-center
the Cartesian coordinates of the :attr:`data` and :attr:`randoms`
to the range of ``[-BoxSize/2, BoxSize/2]``
"""
from nbodykit.utils import get_data_bounds
# compute the min/max of the position data
pos, sel = self[species].read([position, selection])
pos_min, pos_max = get_data_bounds(pos, self.comm, selection=sel)
if self.comm.rank == 0:
self.logger.info("cartesian coordinate range: %s : %s" %
(str(pos_min), str(pos_max)))
if numpy.isinf(pos_min).any() or numpy.isinf(pos_max).any():
raise ValueError(
"Range of positions from `%s` is infinite;"
"try to use the other species with (bbox_from_species='data'."
% species)
# used to center the data in the first cartesian quadrant
delta = abs(pos_max - pos_min)
BoxCenter = 0.5 * (pos_min + pos_max)
# BoxSize is padded diff of min/max coordinates
if self.attrs['BoxSize'] is None:
delta *= 1.0 + self.attrs['BoxPad']
BoxSize = numpy.ceil(delta) # round up to nearest integer
else:
BoxSize = self.attrs['BoxSize']
return BoxSize, BoxCenter
def shift_to_box_center(pos, BoxSize, comm):
"""
Find the bounds of the input position array, and if needed, shift the
position to an observer at the box center.
Position should be bounded by [0, BoxSize] or [-BoxSize/2, BoxSize/2];
if not, an exception will be raised.
Parameters
----------
pos : dask array
the dask array holding the Position
BoxSize : array_like
the size of the box
comm :
the MPI communicator
Returns
-------
pos : dask array
the position array, shifted such that observer is in the box center
"""
from nbodykit.utils import get_data_bounds
# make BoxSize is a 3-vector
_BoxSize = numpy.empty(3)
_BoxSize[:] = BoxSize
# get min/max of position (3-vectors)
pos_min, pos_max = get_data_bounds(pos, comm)
# Position is [0, BoxSize] --> shift to center of box
if (pos_min > 0.).all() and (pos_max < _BoxSize).all():
pos -= 0.5 * _BoxSize
elif (pos_min > -0.5 * _BoxSize).all() and (pos_max <
0.5 * _BoxSize).all():
pass
else:
raise ValueError(
"input Position should be bounded by [0,BoxSize] or [-BoxSize/2,BoxSize/2]"
)
return pos
def _define_bbox(self, position, selection, species):
"""
Internal function to put the :attr:`randoms` CatalogSource in a
Cartesian bounding box, using the positions of the given species.
This function computings the size and center of the bounding box.
#. `BoxSize` : array_like, (3,)
if not provided, the BoxSize in each direction is computed from
the maximum extent of the Cartesian coordinates of the :attr:`randoms`
Source, with an optional, additional padding
#. `BoxCenter`: array_like, (3,)
the mean coordinate value in each direction; this is used to re-center
the Cartesian coordinates of the :attr:`data` and :attr:`randoms`
to the range of ``[-BoxSize/2, BoxSize/2]``
"""
from nbodykit.utils import get_data_bounds
# compute the min/max of the position data
pos, sel = self[species].read([position, selection])
pos_min, pos_max = get_data_bounds(pos, self.comm, selection=sel)
if self.comm.rank == 0:
self.logger.info("cartesian coordinate range: %s : %s" %(str(pos_min), str(pos_max)))
if numpy.isinf(pos_min).any() or numpy.isinf(pos_max).any():
raise ValueError("Range of positions from `%s` is infinite;"
"try to use the other species with (bbox_from_species='data'." % species)
# used to center the data in the first cartesian quadrant
delta = abs(pos_max - pos_min)
BoxCenter = 0.5 * (pos_min + pos_max)
# BoxSize is padded diff of min/max coordinates
if self.attrs['BoxSize'] is None:
delta *= 1.0 + self.attrs['BoxPad']
BoxSize = numpy.ceil(delta) # round up to nearest integer
else:
BoxSize = self.attrs['BoxSize']
return BoxSize, BoxCenter
def define_cartesian_box(catalogue, position='Position', selection='Selection', BoxCenter=None, BoxSize=None, BoxPad=0.05, **kwargs):
"""
Internal function to put the CatalogSource in a
Cartesian box.
This function add two necessary attribues:
#. :attr:`BoxSize` : array_like, (3,)
if not provided, the BoxSize in each direction is computed from
the maximum extent of the Cartesian coordinates of the :attr:`randoms`
Source, with an optional, additional padding
#. :attr:`BoxCenter`: array_like, (3,)
the mean coordinate value in each direction; this is used to re-center
the Cartesian coordinates of the :attr:`data` and :attr:`randoms`
to the range of ``[-BoxSize/2, BoxSize/2]``
"""
from nbodykit.utils import get_data_bounds
# compute the min/max of the position data
pos, sel = catalogue.read([position, selection])
pos_min, pos_max = get_data_bounds(pos, catalogue.comm, selection=sel)
# used to center the data in the first cartesian quadrant
delta = abs(pos_max - pos_min)
catalogue.attrs['BoxCenter'] = BoxCenter
if catalogue.attrs['BoxCenter'] is None: catalogue.attrs['BoxCenter'] = 0.5 * (pos_min + pos_max)
# BoxSize is padded diff of min/max coordinates
catalogue.attrs['BoxSize'] = BoxSize
catalogue.attrs['BoxPad'] = BoxPad
if catalogue.attrs['BoxSize'] is None:
delta *= 1.0 + catalogue.attrs['BoxPad']
catalogue.attrs['BoxSize'] = numpy.ceil(delta) # round up to nearest integer
if (catalogue.attrs['BoxSize']<delta).any(): raise ValueError('BoxSize too small to contain all data.')
# log some info
if catalogue.comm.rank == 0:
catalogue.logger.info("BoxSize = %s" %str(catalogue.attrs['BoxSize']))
catalogue.logger.info("cartesian coordinate range: %s : %s" %(str(pos_min), str(pos_max)))
catalogue.logger.info("BoxCenter = %s" %str(catalogue.attrs['BoxCenter']))
def shift_to_box_center(pos, BoxSize, comm):
"""
Find the bounds of the input position array, and if needed, shift the
position to an observer at the box center.
Position should be bounded by [0, BoxSize] or [-BoxSize/2, BoxSize/2];
if not, an exception will be raised.
Parameters
----------
pos : dask array
the dask array holding the Position
BoxSize : array_like
the size of the box
comm :
the MPI communicator
Returns
-------
pos : dask array
the position array, shifted such that observer is in the box center
"""
from nbodykit.utils import get_data_bounds
# make BoxSize is a 3-vector
_BoxSize = numpy.empty(3)
_BoxSize[:] = BoxSize
# get min/max of position (3-vectors)
pos_min, pos_max = get_data_bounds(pos, comm)
# Position is [0, BoxSize] --> shift to center of box
if (pos_min > 0.).all() and (pos_max < _BoxSize).all():
pos -= 0.5 * _BoxSize
elif (pos_min > -0.5*_BoxSize).all() and (pos_max < 0.5*_BoxSize).all():
pass
else:
raise ValueError("input Position should be bounded by [0,BoxSize] or [-BoxSize/2,BoxSize/2]")
return pos
def _define_cartesian_box(self, position, selection):
"""
Internal function to put the :attr:`randoms` CatalogSource in a
Cartesian box.
This function add two necessary attribues:
#. :attr:`BoxSize` : array_like, (3,)
if not provided, the BoxSize in each direction is computed from
the maximum extent of the Cartesian coordinates of the :attr:`randoms`
Source, with an optional, additional padding
#. :attr:`BoxCenter`: array_like, (3,)
the mean coordinate value in each direction; this is used to re-center
the Cartesian coordinates of the :attr:`data` and :attr:`randoms`
to the range of ``[-BoxSize/2, BoxSize/2]``
"""
from nbodykit.utils import get_data_bounds
# compute the min/max of the position data
pos, sel = self['randoms'].read([position, selection])
pos_min, pos_max = get_data_bounds(pos, self.comm, selection=sel)
# used to center the data in the first cartesian quadrant
delta = abs(pos_max - pos_min)
self.attrs['BoxCenter'] = 0.5 * (pos_min + pos_max)
# BoxSize is padded diff of min/max coordinates
if self.attrs['BoxSize'] is None:
delta *= 1.0 + self.attrs['BoxPad']
self.attrs['BoxSize'] = numpy.ceil(
delta) # round up to nearest integer
# log some info
if self.comm.rank == 0:
self.logger.info("BoxSize = %s" % str(self.attrs['BoxSize']))
self.logger.info("cartesian coordinate range: %s : %s" %
(str(pos_min), str(pos_max)))
self.logger.info("BoxCenter = %s" % str(self.attrs['BoxCenter']))
