Delete jump step unit test that has been moved to STCAL (#8319)

Co-authored-by: Howard Bushouse <[email protected]>

CHANGES.rst

@@ -8,7 +8,7 @@ associations
   sub-pixel dithers, so that only exposures from other nod positions
   are used as background members in "spec2" associations. [#8184]
 
--  JP-3290 Isolate candidate processing into their own pools [#8227]
+- Isolate candidate processing into their own pools [#8227]
 
 cube_build
 ----------
@@ -82,6 +82,12 @@ general
 
 - Update minimum required stdatamodels version to include 1.10.0 [#8322]
 
+jump
+----
+
+- Removed a unit test in Jump that was moved to STCAL to decrease
+  the coupling of the two repos. [#8319]
+
 outlier_detection
 -----------------
 

jwst/jump/tests/test_detect_jumps.py

@@ -307,51 +307,6 @@ def test_multiple_neighbor_jumps_firstlastbad(setup_inputs):
     assert_array_equal(out_model.groupdq[0, :, 4, 4], [1, 0, 0, 0, 0, 0, 0, 0, 0, 1])
 
 
-def test_nirspec_saturated_pix(setup_inputs):
-    """
-    This test is based on an actual NIRSpec exposure that has some pixels
-    flagged as saturated in one or more groups, which the jump step is
-    supposed to ignore, but an old version of the code was setting JUMP flags
-    for some of the saturated groups. This is to verify that the saturated
-    groups are no longer flagged with jumps.
-    """
-    grouptime = 3.0
-    ingain = 1.0
-    inreadnoise = 10.7
-    ngroups = 7
-    nrows = 6
-    ncols = 6
-
-    model, rnoise, gain = setup_inputs(ngroups=ngroups, nints=1, nrows=nrows,
-                                       ncols=ncols, gain=ingain,
-                                       readnoise=inreadnoise, deltatime=grouptime)
-
-    # Setup the needed input pixel and DQ values
-    model.data[0, :, 1, 1] = [639854.75, 4872.451, -17861.791, 14022.15, 22320.176,
-                              1116.3828, 1936.9746]
-    model.groupdq[0, :, 1, 1] = [0, 0, 0, 0, 0, 2, 2]
-    model.data[0, :, 2, 2] = [8.25666812e+05, -1.10471914e+05, 1.95755371e+02, 1.83118457e+03,
-                              1.72250879e+03, 1.81733496e+03, 1.65188281e+03]
-    # 2 non-sat groups means only 1 non-sat diff, so no jumps should be flagged
-    model.groupdq[0, :, 2, 2] = [0, 0, 2, 2, 2, 2, 2]
-    model.data[0, :, 3, 3] = [1228767., 46392.234, -3245.6553, 7762.413,
-                              37190.76, 266611.62, 5072.4434]
-    model.groupdq[0, :, 3, 3] = [0, 0, 0, 0, 0, 0, 2]
-
-    # run jump detection
-    out_model = run_detect_jumps(model, gain, rnoise, rejection_thresh=200.0, three_grp_thresh=200,
-                                 four_grp_thresh=200,
-                                 max_cores='none', max_jump_to_flag_neighbors=200,
-                                 min_jump_to_flag_neighbors=10, flag_4_neighbors=True)
-
-    # Check the results. There should not be any pixels with DQ values of 6, which
-    # is saturated (2) plus jump (4). All the DQ's should be either just 2 or just 4.
-    assert_array_equal(out_model.groupdq[0, :, 1, 1], [0, 4, 4, 4, 0, 2, 2])
-    # assert that no groups are flagged when theres only 1 non-sat. grp
-    assert_array_equal(out_model.groupdq[0, :, 2, 2], [0, 0, 2, 2, 2, 2, 2])
-    assert_array_equal(out_model.groupdq[0, :, 3, 3], [0, 4, 4, 0, 0, 4, 2])
-
-
 def add_crs(model, crs_frac):
     """"
     Randomly add a cosmic ray of magnitude CR_MAG to a fraction (crs_frac)