JP-3896: Deprecate or remove various assign_wcs utility functions

changes/9221.assign_wcs.rst

@@ -0,0 +1 @@
+Deprecate util.reproject and remove some private util functions

jwst/assign_wcs/tests/test_nircam.py

@@ -10,7 +10,6 @@
 """
 import numpy as np
 import pytest
-import re
 
 
 from astropy.io import fits
@@ -21,6 +20,7 @@
 from jwst.assign_wcs.assign_wcs_step import AssignWcsStep
 from jwst.assign_wcs import nircam
 from jwst.assign_wcs import util
+from stcal.alignment.util import sregion_to_footprint
 
 
 # Allowed settings for nircam
@@ -247,22 +247,6 @@ def test_wfss_sip():
         assert key in wfss_model.meta.wcsinfo.instance
 
 
-def _sregion_to_footprint(s_region):
-    """
-    Parameters
-    ----------
-    s_region : str
-        The S_REGION header keyword
-
-    Returns
-    -------
-    footprint : np.array
-        A 2D array of the footprint of the region, shape (N, 2)
-    """
-    no_prefix = re.sub(r"[a-zA-Z]", "", s_region)
-    return np.array(no_prefix.split(), dtype=float).reshape(-1, 2)
-
-
 def test_update_s_region_imaging():
     """Ensure the s_region keyword matches output of wcs.footprint()"""
     model = ImageModel(create_hdul())
@@ -271,5 +255,5 @@ def test_update_s_region_imaging():
 
     s_region = model.meta.wcsinfo.s_region
     footprint = model.meta.wcs.footprint().flatten()
-    footprint_sregion = _sregion_to_footprint(s_region).flatten()
+    footprint_sregion = sregion_to_footprint(s_region).flatten()
     assert np.allclose(footprint, footprint_sregion, rtol=1e-9)

jwst/assign_wcs/util.py

@@ -5,9 +5,9 @@
 import logging
 import functools
 import numpy as np
+import warnings
 
 from astropy.coordinates import SkyCoord
-from astropy.io import fits
 from astropy.modeling import models as astmodels
 from astropy.table import QTable
 from astropy.constants import c
@@ -64,16 +64,12 @@
         super().__init__(64, message)
 
 
-def _domain_to_bounding_box(domain):
-    # TODO: remove this when domain is completely removed
-    bb = tuple([(item['lower'], item['upper']) for item in domain])
-    if len(bb) == 1:
-        bb = bb[0]
-    return bb
-
-
 def reproject(wcs1, wcs2):
     """
+    .. deprecated:: 1.17.2
+        :py:func:`reproject()` has been deprecated and will be removed
+        in a future release. Use :py:func:`stcal.alignment.util.reproject` instead.
+
     Given two WCSs return a function which takes pixel coordinates in
     the first WCS and computes their location in the second one.
 
@@ -91,6 +87,13 @@
         Function to compute the transformations.  It takes x, y
         positions in ``wcs1`` and returns x, y positions in ``wcs2``.
     """
+    warnings.warn(
+        "'reproject()' has been deprecated since 1.17.2 and "
+        "will be removed in a future release. "
+        "Use 'stcal.alignment.util.reproject()' instead.",
+        DeprecationWarning,
+        stacklevel=2
+    )
 
     def _reproject(x, y):
         sky = wcs1.forward_transform(x, y)
@@ -196,101 +199,6 @@
     return [pc1_1, pc1_2, pc2_1, pc2_2]
 
 
-def compute_fiducial(wcslist, bounding_box=None):
-    """
-    For a celestial footprint this is the center.
-    For a spectral footprint, it is the beginning of the range.
-
-    This function assumes all WCSs have the same output coordinate frame.
-    """
-
-    axes_types = wcslist[0].output_frame.axes_type
-    spatial_axes = np.array(axes_types) == 'SPATIAL'
-    spectral_axes = np.array(axes_types) == 'SPECTRAL'
-    footprints = np.hstack([w.footprint(bounding_box=bounding_box).T for w in wcslist])
-    spatial_footprint = footprints[spatial_axes]
-    spectral_footprint = footprints[spectral_axes]
-
-    fiducial = np.empty(len(axes_types))
-    if spatial_footprint.any():
-        lon, lat = spatial_footprint
-        lon, lat = np.deg2rad(lon), np.deg2rad(lat)
-        x = np.cos(lat) * np.cos(lon)
-        y = np.cos(lat) * np.sin(lon)
-        z = np.sin(lat)
-
-        x_mid = (np.max(x) + np.min(x)) / 2.
-        y_mid = (np.max(y) + np.min(y)) / 2.
-        z_mid = (np.max(z) + np.min(z)) / 2.
-        lon_fiducial = np.rad2deg(np.arctan2(y_mid, x_mid)) % 360.0
-        lat_fiducial = np.rad2deg(np.arctan2(z_mid, np.sqrt(x_mid ** 2 + y_mid ** 2)))
-        fiducial[spatial_axes] = lon_fiducial, lat_fiducial
-    if spectral_footprint.any():
-        fiducial[spectral_axes] = spectral_footprint.min()
-    return fiducial
-
-
-def is_fits(input_img):
-    """
-    Returns
-    --------
-    isFits: tuple
-        An ``(isfits, fitstype)`` tuple.  The values of ``isfits`` and
-        ``fitstype`` are specified as:
-
-         - ``isfits``: True|False
-         - ``fitstype``: if True, one of 'waiver', 'mef', 'simple'; if False, None
-
-    Notes
-    -----
-    Input images which do not have a valid FITS filename will automatically
-    result in a return of (False, None).
-
-    In the case that the input has a valid FITS filename but runs into some
-    error upon opening, this routine will raise that exception for the calling
-    routine/user to handle.
-    """
-
-    isfits = False
-    fitstype = None
-    names = ['fits', 'fit', 'FITS', 'FIT']
-    # determine if input is a fits file based on extension
-    # Only check type of FITS file if filename ends in valid FITS string
-    f = None
-    fileclose = False
-    if isinstance(input_img, fits.HDUList):
-        isfits = True
-        f = input_img
-    else:
-        isfits = True in [input_img.endswith(suffix) for suffix in names]
-
-    # if input is a fits file determine what kind of fits it is
-    # waiver fits len(shape) == 3
-    if isfits:
-        if not f:
-            try:
-                f = fits.open(input_img, mode='readonly')
-                fileclose = True
-            except Exception:
-                if f is not None:
-                    f.close()
-                raise
-        data0 = f[0].data
-        if data0 is not None:
-            try:
-                if isinstance(f[1], fits.TableHDU):
-                    fitstype = 'waiver'
-            except IndexError:
-                fitstype = 'simple'
-
-        else:
-            fitstype = 'mef'
-        if fileclose:
-            f.close()
-
-    return isfits, fitstype
-
-
 def subarray_transform(input_model):
     """
     Return an offset model if the observation uses a subarray.
@@ -705,22 +613,6 @@
     return final_objects
 
 
-def get_num_msa_open_shutters(shutter_state):
-    """
-    Return the number of open shutters in a slitlet.
-
-    Parameters
-    ----------
-    shutter_state : str
-        ``Slit.shutter_state`` attribute - a combination of
-        ``1`` - open shutter, ``0`` - closed shutter, ``x`` - main shutter.
-    """
-    num = shutter_state.count('1')
-    if 'x' in shutter_state:
-        num += 1
-    return num
-
-
 def transform_bbox_from_shape(shape, order="C"):
     """Create a bounding box from the shape of the data.
 

jwst/resample/tests/test_resample_step.py

@@ -10,7 +10,7 @@
 
 from jwst.datamodels import ModelContainer, ModelLibrary
 from jwst.assign_wcs import AssignWcsStep
-from jwst.assign_wcs.util import compute_fiducial, compute_scale
+from jwst.assign_wcs.util import compute_scale
 from jwst.exp_to_source import multislit_to_container
 from jwst.extract_2d import Extract2dStep
 from jwst.resample import ResampleSpecStep, ResampleStep
@@ -1179,14 +1179,14 @@ def test_custom_wcs_pscale_resample_imaging(nircam_rate, ratio):
     im = AssignWcsStep.call(nircam_rate, sip_approx=False)
     im.data += 5
 
-    fiducial = compute_fiducial([im.meta.wcs])
-    input_scale = compute_scale(wcs=im.meta.wcs, fiducial=fiducial)
+    crval = (22.04019, 11.98262)
+    input_scale = compute_scale(wcs=im.meta.wcs, fiducial=crval)
     result = ResampleStep.call(
         im,
         pixel_scale_ratio=ratio,
         pixel_scale=3600 * input_scale * 0.75
     )
-    output_scale = compute_scale(wcs=result.meta.wcs, fiducial=fiducial)
+    output_scale = compute_scale(wcs=result.meta.wcs, fiducial=crval)
 
     # test scales are close
     assert np.allclose(output_scale, input_scale * 0.75)