def angular_slice_to_physical(input_slice, z, slice_size_deg, output_cell_size, output_size_mpc, order=0, prefilter=True):
'''
Interpolate a slice in angular coordinates to physical
Returns:
(physical_slice, size_mpc)
'''
#Resample
slice_size_mpc = cm.deg_to_cdist(slice_size_deg, z)
n_cells_resampled = int(slice_size_mpc/output_cell_size)
#Avoid edge effects with even number of cells
if n_cells_resampled % 2 == 0:
n_cells_resampled += 1
resampled_slice = resample_slice(input_slice, n_cells_resampled, order, prefilter)
#Remove cells to get correct size
n_cutout_cells = int(output_size_mpc/output_cell_size)# np.round(resampled_slice.shape[0]*output_size_mpc/slice_size_mpc)
if n_cutout_cells > input_slice.shape[0]:
if input_slice.shape[0] - n_cutout_cells > 2:
print 'Warning! Cutout slice is larger than original.'
print 'This should not happen'
n_cutout_cells = input_slice.shape[0]
slice_cutout = resampled_slice[:n_cutout_cells, :n_cutout_cells]
return slice_cutout
def physical_slice_to_angular(input_slice,
z,
slice_size_mpc,
fov_deg,
dtheta,
order=0):
'''
Interpolate a slice in physical coordinates to angular coordinates.
Parameters:
* input_slice (numpy array): the 2D slice in physical coordinates
* z (float): the redshift of the input slice
* slice_size_Mpc (float): the size of the input slice in cMpc
* fov_deg (float): the field-of-view in degrees. The output will be
padded to match this size
* dtheta (float): the target resolution in arcmin
Returns:
(angular_slice, size_deg)
'''
#Resample
fov_mpc = cm.deg_to_cdist(fov_deg, z)
cell_size_mpc = fov_mpc / (fov_deg * 60. / dtheta)
n_cells_resampled = int(slice_size_mpc / cell_size_mpc)
#Avoid edge effects with even number of cells
if n_cells_resampled % 2 == 0:
n_cells_resampled -= 1
resampled_slice = resample_slice(input_slice, n_cells_resampled, order)
#Pad the array
slice_n = resampled_slice.shape[0]
padded_n = fov_deg * 60. / dtheta # np.round(slice_n*(fov_mpc/slice_size_mpc))
if padded_n < slice_n:
if slice_n - padded_n > 2:
print 'Warning! Padded slice is significantly smaller than original!'
print 'This should not happen...'
padded_n = slice_n
padded_slice = _get_padded_slice(resampled_slice, padded_n)
return padded_slice
def physical_slice_to_angular(input_slice, z, slice_size_mpc, fov_deg, dtheta, order=0):
'''
Interpolate a slice in physical coordinates to angular coordinates.
Parameters:
* input_slice (numpy array): the 2D slice in physical coordinates
* z (float): the redshift of the input slice
* slice_size_Mpc (float): the size of the input slice in cMpc
* fov_deg (float): the field-of-view in degrees. The output will be
padded to match this size
* dtheta (float): the target resolution in arcmin
Returns:
(angular_slice, size_deg)
'''
#Resample
fov_mpc = cm.deg_to_cdist(fov_deg, z)
cell_size_mpc = fov_mpc/(fov_deg*60./dtheta)
n_cells_resampled = int(slice_size_mpc/cell_size_mpc)
#Avoid edge effects with even number of cells
if n_cells_resampled % 2 == 0:
n_cells_resampled -= 1
resampled_slice = resample_slice(input_slice, n_cells_resampled, order)
#Pad the array
slice_n = resampled_slice.shape[0]
padded_n = fov_deg*60./dtheta# np.round(slice_n*(fov_mpc/slice_size_mpc))
if padded_n < slice_n:
if slice_n - padded_n > 2:
print 'Warning! Padded slice is significantly smaller than original!'
print 'This should not happen...'
padded_n = slice_n
padded_slice = _get_padded_slice(resampled_slice, padded_n)
return padded_slice
