def transform_coords(self, catalog=None, x=None, y=None):
"""
Use the solution to transform the pixel coordinates
"""
from astropyp.catalog import Catalog
ungroup = False
if catalog is None:
try:
len(x)
except TypeError:
x = [x]
y = [y]
ungroup = True
catalog = table.Table([x, y], names=('x', 'y'))
if not isinstance(catalog, Catalog):
cat = Catalog(catalog)
else:
cat = catalog
x_tbl = get_transform_tbl(cat.x, cat.y, self.order, 'A')
x_tbl['Intercept'] = 1
x = 0
for column, value in self.x_tx.items():
x += x_tbl[column] * value
y_tbl = get_transform_tbl(cat.y, cat.x, self.order, 'B')
y_tbl['Intercept'] = 1
y = 0
for column, value in self.y_tx.items():
y += y_tbl[column] * value
if ungroup:
x = x[0]
y = y[0]
return x, y
def pix2world(self, x, y):
"""
Convert pixel coordinates to wcs using
an astropyp astrometric solution.
Parameters
----------
x,y: array-like
Pixel coordinates of the sources
Result
------
ra, dec
"""
ra_tbl = get_transform_tbl(x - self.crpix[0], y - self.crpix[1],
self.order, 'A')
dec_tbl = get_transform_tbl(y - self.crpix[1], x - self.crpix[0],
self.order, 'B')
ra_tbl['Intercept'] = 1
dec_tbl['Intercept'] = 1
ra = 0
dec = 0
for column, value in self.x2ra.items():
ra += ra_tbl[column] * value
for column, value in self.y2dec.items():
dec += dec_tbl[column] * value
return ra + self.crval[0], dec + self.crval[1]
def world2pix(self, ra, dec):
"""
Convert pixel coordinates to wcs using
an astropyp astrometric solution.
Parameters
----------
x,y: array-like
Pixel coordinates of the sources
Result
------
ra, dec
"""
x_tbl = get_transform_tbl(ra - self.crval[0], dec - self.crval[1],
self.order, 'Ap')
y_tbl = get_transform_tbl(dec - self.crval[1], ra - self.crval[0],
self.order, 'Bp')
x_tbl['Intercept'] = 1
y_tbl['Intercept'] = 1
x = 0
y = 0
for column, value in self.ra2x.items():
x += x_tbl[column] * value
for column, value in self.dec2y.items():
y += y_tbl[column] * value
return x + self.crpix[0], y + self.crpix[1]
def transform_coords(self, catalog=None, x=None, y=None):
"""
Use the solution to transform the pixel coordinates
"""
from astropyp.catalog import Catalog
ungroup = False
if catalog is None:
try:
len(x)
except TypeError:
x = [x]
y = [y]
ungroup = True
catalog = table.Table([x, y], names=('x', 'y'))
if not isinstance(catalog, Catalog):
cat = Catalog(catalog)
else:
cat = catalog
x_tbl = get_transform_tbl(cat.x, cat.y, self.order, 'A')
x_tbl['Intercept'] = 1
x = 0
for column, value in self.x_tx.items():
x += x_tbl[column] * value
y_tbl = get_transform_tbl(cat.y, cat.x, self.order, 'B')
y_tbl['Intercept'] = 1
y = 0
for column, value in self.y_tx.items():
y += y_tbl[column] * value
if ungroup:
x = x[0]
y = y[0]
return x, y
def world2pix(self, ra, dec):
"""
Convert pixel coordinates to wcs using
an astropyp astrometric solution.
Parameters
----------
x,y: array-like
Pixel coordinates of the sources
Result
------
ra, dec
"""
x_tbl = get_transform_tbl(ra - self.crval[0], dec - self.crval[1],
self.order, 'Ap')
y_tbl = get_transform_tbl(dec - self.crval[1], ra - self.crval[0],
self.order, 'Bp')
x_tbl['Intercept'] = 1
y_tbl['Intercept'] = 1
x = 0
y = 0
for column, value in self.ra2x.items():
x += x_tbl[column] * value
for column, value in self.dec2y.items():
y += y_tbl[column] * value
return x + self.crpix[0], y + self.crpix[1]
def pix2world(self, x, y):
"""
Convert pixel coordinates to wcs using
an astropyp astrometric solution.
Parameters
----------
x,y: array-like
Pixel coordinates of the sources
Result
------
ra, dec
"""
ra_tbl = get_transform_tbl(x - self.crpix[0], y - self.crpix[1],
self.order, 'A')
dec_tbl = get_transform_tbl(y - self.crpix[1], x - self.crpix[0],
self.order, 'B')
ra_tbl['Intercept'] = 1
dec_tbl['Intercept'] = 1
ra = 0
dec = 0
for column, value in self.x2ra.items():
ra += ra_tbl[column] * value
for column, value in self.y2dec.items():
dec += dec_tbl[column] * value
return ra + self.crval[0], dec + self.crval[1]
def _get_solution(coord1,
coord2,
ref_coord,
order,
param_name,
prefix='A',
fit_package='statsmodels',
weights=None):
"""
Given a set of source coordinates and the reference coordinate,
get the coefficients for the astrometric (or inverse) solution
Parameters
----------
coord1, coord2: array-like
Arrays of source coordinates
ref_coord: array-like
Array of reference coordinates
order: int
Order of the solution polynomial
param_name: string
The name of the parameter we are solving for (for example:
'x','y','ra','dec')
prefix: string
The prefix of the coefficient name
fitpackage: string, optional
Name of the fit package to use. Currently only the default
'statsmodels' is available.
"""
if fit_package == 'statsmodels':
try:
import statsmodels.formula.api as smf
except:
raise Exception("'statsmodels' package required for this type of "
"astrometric solution")
tbl = get_transform_tbl(coord1, coord2, order, prefix)
formula = build_formula(param_name, tbl)
tbl[param_name] = ref_coord
if weights is None:
result = smf.OLS.from_formula(formula=formula, data=tbl).fit()
else:
result = smf.WLS.from_formula(formula=formula,
data=tbl,
weights=weights).fit()
result = {
'params': _statsmodels_to_result(result.params),
'statsmodels': result
}
elif fit_package == 'lst_sq':
result = _lst_sq_fit(coord1, coord2, ref_coord, order, weights, prefix)
result = {'params': result}
else:
raise ValueError("fit_package must be either statsmodels' or"
" 'lst_sq'")
return result
def _get_solution(coord1, coord2, ref_coord, order, param_name,
prefix='A', fit_package='statsmodels', weights=None):
"""
Given a set of source coordinates and the reference coordinate,
get the coefficients for the astrometric (or inverse) solution
Parameters
----------
coord1, coord2: array-like
Arrays of source coordinates
ref_coord: array-like
Array of reference coordinates
order: int
Order of the solution polynomial
param_name: string
The name of the parameter we are solving for (for example:
'x','y','ra','dec')
prefix: string
The prefix of the coefficient name
fitpackage: string, optional
Name of the fit package to use. Currently only the default
'statsmodels' is available.
"""
if fit_package == 'statsmodels':
try:
import statsmodels.formula.api as smf
except:
raise Exception(
"'statsmodels' package required for this type of "
"astrometric solution")
tbl = get_transform_tbl(coord1, coord2, order, prefix)
formula = build_formula(param_name, tbl)
tbl[param_name] = ref_coord
if weights is None:
result = smf.OLS.from_formula(formula=formula,
data=tbl).fit()
else:
result = smf.WLS.from_formula(formula=formula,
data=tbl, weights=weights).fit()
result = {
'params': _statsmodels_to_result(result.params),
'statsmodels': result
}
elif fit_package == 'lst_sq':
result = _lst_sq_fit(coord1, coord2, ref_coord, order, weights, prefix)
result = {'params': result}
else:
raise ValueError("fit_package must be either statsmodels' or"
" 'lst_sq'")
return result
def _lst_sq_fit(coord1, coord2, ref_coord, order, weights=None, prefix='A'):
from astropyp.astrometry import get_transform_tbl
A = get_transform_tbl(coord1, coord2, order, prefix)
columns = ['Intercept'] + A.columns.keys()
tbl_dtype = A[A.columns.keys()[0]].dtype
A['Intercept'] = np.ones((len(A)), dtype=tbl_dtype)
A = A[columns]
A = A.as_array().view(tbl_dtype).reshape((len(A), len(A.columns)))
y = ref_coord
if weights is not None:
w = np.vstack([weights for n in range(A.shape[1])]).T
A = A * w
y = y * weights
result = np.linalg.lstsq(A, y)[0]
solution = OrderedDict([
(columns[n], result[n]) for n in range(len(columns))])
return solution
def _lst_sq_fit(coord1, coord2, ref_coord, order, weights=None, prefix='A'):
from astropyp.astrometry import get_transform_tbl
A = get_transform_tbl(coord1, coord2, order, prefix)
columns = ['Intercept'] + A.columns.keys()
tbl_dtype = A[A.columns.keys()[0]].dtype
A['Intercept'] = np.ones((len(A)), dtype=tbl_dtype)
A = A[columns]
A = A.as_array().view(tbl_dtype).reshape((len(A), len(A.columns)))
y = ref_coord
if weights is not None:
w = np.vstack([weights for n in range(A.shape[1])]).T
A = A * w
y = y * weights
result = np.linalg.lstsq(A, y)[0]
solution = OrderedDict([(columns[n], result[n])
for n in range(len(columns))])
return solution
