def subtract_psf(data, psf, positions, fluxes, mask=None):
"""
Removes PSF/PRF at the given positions.
To calculate residual images the PSF/PRF model is subtracted from the data
at the given positions.
Parameters
----------
data : ndarray
Image data.
psf : `photutils.psf.DiscretePRF` or `photutils.psf.GaussianPSF`
PSF/PRF model to be substracted from the data.
positions : ndarray
List of center positions where PSF/PRF is removed.
fluxes : ndarray
List of fluxes of the sources, for correct
normalization.
"""
# Set up indices
indices = np.indices(data.shape)
data_ = data.copy()
# Loop over position
for i, position in enumerate(positions):
x_0, y_0 = position
y = extract_array(indices[0], psf.shape, (y_0, x_0))
x = extract_array(indices[1], psf.shape, (y_0, x_0))
psf.amplitude.value = fluxes[i]
psf.x_0.value, psf.y_0.value = x_0, y_0
psf_image = psf(x, y)
data_ = add_array(data_, -psf_image, (y_0, x_0))
return data_
def subtract_psf(data, psf, positions, fluxes, mask=None):
"""
Removes PSF/PRF at the given positions.
To calculate residual images the PSF/PRF model is subtracted from the data
at the given positions.
Parameters
----------
data : ndarray
Image data.
psf : `photutils.psf.DiscretePRF` or `photutils.psf.GaussianPSF`
PSF/PRF model to be substracted from the data.
positions : ndarray
List of center positions where PSF/PRF is removed.
fluxes : ndarray
List of fluxes of the sources, for correct
normalization.
"""
# Set up indices
indices = np.indices(data.shape)
data_ = data.copy()
# Loop over position
for i, position in enumerate(positions):
x_0, y_0 = position
y = extract_array(indices[0], psf.shape, (y_0, x_0))
x = extract_array(indices[1], psf.shape, (y_0, x_0))
psf.amplitude.value = fluxes[i]
psf.x_0.value, psf.y_0.value = x_0, y_0
psf_image = psf(x, y)
data_ = add_array(data_, -psf_image, (y_0, x_0))
return data_
def test_add_array_equal_shape():
"""
Test add_array_2D utility function.
Test by adding an array of ones out of an array of zeros.
"""
large_test_array = np.zeros((11, 11))
small_test_array = np.ones((11, 11))
large_test_array_ref = large_test_array.copy()
large_test_array_ref += small_test_array
added_array = add_array(large_test_array, small_test_array, (5, 5))
assert np.all(added_array == large_test_array_ref)
def test_add_array_even_shape():
"""
Test add_array_2D utility function.
Test by adding an array of ones out of an array of zeros.
"""
large_test_array = np.zeros((11, 11))
small_test_array = np.ones((4, 4))
large_test_array_ref = large_test_array.copy()
large_test_array_ref[0:2, 0:2] += small_test_array[2:4, 2:4]
added_array = add_array(large_test_array, small_test_array, (0, 0))
assert np.all(added_array == large_test_array_ref)
def test_add_array_even_shape():
"""
Test add_array_2D utility function.
Test by adding an array of ones out of an array of zeros.
"""
large_test_array = np.zeros((11, 11))
small_test_array = np.ones((4, 4))
large_test_array_ref = large_test_array.copy()
large_test_array_ref[0:2, 0:2] += small_test_array[2:4, 2:4]
added_array = add_array(large_test_array, small_test_array, (0, 0))
assert np.all(added_array == large_test_array_ref)
def test_add_array_odd_shape():
"""
Test add_array utility function.
Test by adding an array of ones out of an array of zeros.
"""
large_test_array = np.zeros((11, 11))
small_test_array = np.ones((5, 5))
large_test_array_ref = large_test_array.copy()
large_test_array_ref[3:8, 3:8] += small_test_array
added_array = add_array(large_test_array, small_test_array, (5, 5))
assert np.all(added_array == large_test_array_ref)
def subtract_psf(data, psf, posflux, subshape=None):
"""
Subtract PSF/PRFs from an image.
Parameters
----------
data : `~astropy.nddata.NDData` or array (must be 2D)
Image data.
psf : `astropy.modeling.Fittable2DModel` instance
PSF/PRF model to be substracted from the data.
posflux : Array-like of shape (3, N) or `~astropy.table.Table`
Positions and fluxes for the objects to subtract. If an array,
it is interpreted as ``(x, y, flux)`` If a table, the columns
'x_fit', 'y_fit', and 'flux_fit' must be present.
subshape : length-2 or None
The shape of the region around the center of the location to
subtract the PSF from. If None, subtract from the whole image.
Returns
-------
subdata : same shape and type as ``data``
The image with the PSF subtracted
"""
if data.ndim != 2:
raise ValueError(f'{data.ndim}-d array not supported. Only 2-d '
'arrays can be passed to subtract_psf.')
# translate array input into table
if hasattr(posflux, 'colnames'):
if 'x_fit' not in posflux.colnames:
raise ValueError('Input table does not have x_fit')
if 'y_fit' not in posflux.colnames:
raise ValueError('Input table does not have y_fit')
if 'flux_fit' not in posflux.colnames:
raise ValueError('Input table does not have flux_fit')
else:
posflux = Table(names=['x_fit', 'y_fit', 'flux_fit'], data=posflux)
# Set up contstants across the loop
psf = psf.copy()
xname, yname, fluxname = _extract_psf_fitting_names(psf)
indices = np.indices(data.shape)
subbeddata = data.copy()
if subshape is None:
indicies_reversed = indices[::-1]
for row in posflux:
getattr(psf, xname).value = row['x_fit']
getattr(psf, yname).value = row['y_fit']
getattr(psf, fluxname).value = row['flux_fit']
subbeddata -= psf(*indicies_reversed)
else:
for row in posflux:
x_0, y_0 = row['x_fit'], row['y_fit']
# float dtype needed for fill_value=np.nan
y = extract_array(indices[0].astype(float), subshape, (y_0, x_0))
x = extract_array(indices[1].astype(float), subshape, (y_0, x_0))
getattr(psf, xname).value = x_0
getattr(psf, yname).value = y_0
getattr(psf, fluxname).value = row['flux_fit']
subbeddata = add_array(subbeddata, -psf(x, y), (y_0, x_0))
return subbeddata
def subtract_psf(data, psf, posflux, subshape=None):
"""
Subtract PSF/PRFs from an image.
Parameters
----------
data : `~astropy.nddata.NDData` or array (must be 2D)
Image data.
psf : `astropy.modeling.Fittable2DModel` instance
PSF/PRF model to be substracted from the data.
posflux : Array-like of shape (3, N) or `~astropy.table.Table`
Positions and fluxes for the objects to subtract. If an array,
it is interpreted as ``(x, y, flux)`` If a table, the columns
'x_fit', 'y_fit', and 'flux_fit' must be present.
subshape : length-2 or None
The shape of the region around the center of the location to
subtract the PSF from. If None, subtract from the whole image.
Returns
-------
subdata : same shape and type as ``data``
The image with the PSF subtracted
"""
if data.ndim != 2:
raise ValueError('{0}-d array not supported. Only 2-d arrays can be '
'passed to subtract_psf.'.format(data.ndim))
# translate array input into table
if hasattr(posflux, 'colnames'):
if 'x_fit' not in posflux.colnames:
raise ValueError('Input table does not have x_fit')
if 'y_fit' not in posflux.colnames:
raise ValueError('Input table does not have y_fit')
if 'flux_fit' not in posflux.colnames:
raise ValueError('Input table does not have flux_fit')
else:
posflux = Table(names=['x_fit', 'y_fit', 'flux_fit'], data=posflux)
# Set up contstants across the loop
psf = psf.copy()
xname, yname, fluxname = _extract_psf_fitting_names(psf)
indices = np.indices(data.shape)
subbeddata = data.copy()
if subshape is None:
indicies_reversed = indices[::-1]
for row in posflux:
getattr(psf, xname).value = row['x_fit']
getattr(psf, yname).value = row['y_fit']
getattr(psf, fluxname).value = row['flux_fit']
subbeddata -= psf(*indicies_reversed)
else:
for row in posflux:
x_0, y_0 = row['x_fit'], row['y_fit']
y = extract_array(indices[0], subshape, (y_0, x_0))
x = extract_array(indices[1], subshape, (y_0, x_0))
getattr(psf, xname).value = x_0
getattr(psf, yname).value = y_0
getattr(psf, fluxname).value = row['flux_fit']
subbeddata = add_array(subbeddata, -psf(x, y), (y_0, x_0))
return subbeddata