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Deprecate "accuracy" in favor of "tolerance" in all_world2pix #166

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Nov 19, 2020
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Deprecate "accuracy" in favor of "tolerance" in all_world2pix #166

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4 changes: 4 additions & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,10 @@
- Make WCS and headerlet name comparisons case-insensitive when applying
headerlets. [#163]

- Deprecate ``accuracy`` argument in ``all_world2pix`` and replace it with
``tolerance`` in order to have compatible function signature with
``astropy``'s ``all_world2pix()``'. [#166]


1.6.0 (2020-07-16)
------------------
Expand Down
43 changes: 23 additions & 20 deletions stwcs/wcsutil/hstwcs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,9 @@
import warnings
from astropy.wcs import WCS
from astropy.io import fits
from astropy import log
from astropy.utils.decorators import deprecated_renamed_argument

from ..distortion import models, coeff_converter
import numpy as np
from stsci.tools import fileutil
Expand All @@ -12,7 +15,6 @@
from .mappings import inst_mappings, ins_spec_kw
from ..wcsutil.altwcs import exclude_hst_specific

from astropy import log
default_log_level = log.getEffectiveLevel()

__all__ = ['HSTWCS']
Expand Down Expand Up @@ -473,19 +475,20 @@ def pc2cd(self):
if self.wcs.has_pc():
self.wcs.cd = self.wcs.pc * self.wcs.cdelt[1]

@deprecated_renamed_argument('accuracy', 'tolerance', '1.6.1', arg_in_kwargs=True)
def all_world2pix(self, *args, **kwargs):
"""
all_world2pix(*arg, accuracy=1.0e-4, maxiter=20, adaptive=False,
all_world2pix(*arg, tolerance=1.0e-4, maxiter=20, adaptive=False,
detect_divergence=True, quiet=False)

Performs full inverse transformation using iterative solution
on full forward transformation with complete distortion model.

Parameters
----------
accuracy : float, optional (Default = 1.0e-4)
Required accuracy of the solution. Iteration terminates when the
correction to the solution found during the previous iteration
tolerance : float, optional (Default = 1.0e-4)
Absolute tolerance required the solution. Iteration terminates when
the correction to the solution found during the previous iteration
is smaller (in the sence of the L2 norm) than `accuracy` .

maxiter : int, optional (Default = 20)
Expand Down Expand Up @@ -562,7 +565,7 @@ def all_world2pix(self, *args, **kwargs):
switch to the adaptive algorithm.

.. note::
When accuracy has been achieved, small increases in
When absolute tolerance has been achieved, small increases in
current corrections may be possible due to rounding errors
(when `adaptive` is `False` ) and such increases
will be ignored.
Expand Down Expand Up @@ -640,7 +643,7 @@ def all_world2pix(self, *args, **kwargs):
[[ 1.00000233 0.99999997]
[ 2.00000232 0.99999997]
[ 3.00000233 0.99999998]]
>>> xy = w.all_world2pix(radec,1, maxiter=3, accuracy=1.0e-10,
>>> xy = w.all_world2pix(radec,1, maxiter=3, tolerance=1.0e-10,
quiet=False)
NoConvergence: 'HSTWCS.all_world2pix' failed to converge to requested
accuracy after 3 iterations.
Expand All @@ -654,7 +657,7 @@ def all_world2pix(self, *args, **kwargs):
[ 5.52653313 -72.05170814]]

>>> try:
>>> xy = w.all_world2pix(divradec,1, maxiter=20, accuracy=1.0e-4,
>>> xy = w.all_world2pix(divradec,1, maxiter=20, tolerance=1.0e-4,
adaptive=False, detect_divergence=True, quiet=False)
>>> except stwcs.wcsutil.hstwcs.NoConvergence as e:
>>> print("Indices of diverging points: {}".format(e.divergent))
Expand All @@ -680,7 +683,7 @@ def all_world2pix(self, *args, **kwargs):
After 5 iterations, the solution is diverging at least for one input point.

>>> try:
>>> xy = w.all_world2pix(divradec,1, maxiter=20, accuracy=1.0e-4,
>>> xy = w.all_world2pix(divradec,1, maxiter=20, tolerance=1.0e-4,
adaptive=False, detect_divergence=False, quiet=False)
>>> except stwcs.wcsutil.hstwcs.NoConvergence as e:
>>> print("Indices of diverging points: {}".format(e.divergent))
Expand Down Expand Up @@ -736,7 +739,7 @@ def all_world2pix(self, *args, **kwargs):
raise TypeError("Expected 2 or 3 arguments, {:d} given.".format(nargs))

# process optional arguments:
accuracy = kwargs.pop('accuracy', 1.0e-4)
tolerance = kwargs.pop('tolerance', 1.0e-4)
maxiter = kwargs.pop('maxiter', 20)
adaptive = kwargs.pop('adaptive', False)
detect_divergence = kwargs.pop('detect_divergence', True)
Expand Down Expand Up @@ -783,7 +786,7 @@ def all_world2pix(self, *args, **kwargs):

# prepare for iterative process
iterlist = list(range(1, maxiter + 1))
accuracy2 = accuracy ** 2
tolerance2 = tolerance ** 2
ind = None
inddiv = None

Expand All @@ -800,7 +803,7 @@ def all_world2pix(self, *args, **kwargs):
if not adaptive:
for k in iterlist:
# check convergence:
if np.max(dn2) < accuracy2:
if np.max(dn2) < tolerance2:
break

# find correction to the previous solution:
Expand All @@ -822,13 +825,13 @@ def all_world2pix(self, *args, **kwargs):
ind, = np.where(dn2 <= dn2prev)
if ind.shape[0] < npts:
inddiv, = np.where(
np.logical_and(dn2 > dn2prev, dn2 >= accuracy2))
np.logical_and(dn2 > dn2prev, dn2 >= tolerance2))
if inddiv.shape[0] > 0:
# apply correction only to the converging points:
x[ind] -= dx[ind]
y[ind] -= dy[ind]
# switch to adaptive iterations:
ind, = np.where((dn2 >= accuracy2) &
ind, = np.where((dn2 >= tolerance2) &
(dn2 <= dn2prev) & np.isfinite(dn2))
iterlist = iterlist[k:]
adaptive = True
Expand Down Expand Up @@ -866,12 +869,12 @@ def all_world2pix(self, *args, **kwargs):

# update indices of elements that still need correction:
if detect_divergence:
ind, = np.where((dn2 >= accuracy2) & (dn2 <= dn2prev))
# ind = ind[np.where((dn2[ind] >= accuracy2) & (dn2[ind] <= dn2prev))]
ind, = np.where((dn2 >= tolerance2) & (dn2 <= dn2prev))
# ind = ind[np.where((dn2[ind] >= tolerance2) & (dn2[ind] <= dn2prev))]
dn2prev[ind] = dn2[ind]
else:
ind, = np.where(dn2 >= accuracy2)
# ind = ind[np.where(dn2[ind] >= accuracy2)]
ind, = np.where(dn2 >= tolerance2)
# ind = ind[np.where(dn2[ind] >= tolerance2)]

# apply correction:
x[ind] -= dx[ind]
Expand All @@ -887,13 +890,13 @@ def all_world2pix(self, *args, **kwargs):
(np.isfinite(ra)) & (np.isfinite(dec)))
# When detect_divergence==False, dn2prev is outdated (it is the
# norm^2 of the very first correction). Still better than nothing...
inddiv, = np.where(((dn2 >= accuracy2) & (dn2 > dn2prev)) | invalid)
inddiv, = np.where(((dn2 >= tolerance2) & (dn2 > dn2prev)) | invalid)
if inddiv.shape[0] == 0:
inddiv = None
# identify points that did not converge within
# 'maxiter' iterations:
if k >= maxiter:
ind, = np.where((dn2 >= accuracy2) & (dn2 <= dn2prev) & (~invalid))
ind, = np.where((dn2 >= tolerance2) & (dn2 <= dn2prev) & (~invalid))
if ind.shape[0] == 0:
ind = None
else:
Expand Down