JP-3550: Multi-integration jump detection

CHANGES.rst

@@ -28,6 +28,12 @@ jump
 - Fix the code to at least always flag the group with the shower and the requested
   groups after the primary shower. [#237]
 
+- Enable the use of multiple integrations to find outliers. Also,
+  when the number of groups is above a threshold use single pass
+  outlier flagging rather than the iterative flagging. [#242]
+
+=======
+
 Other
 -----
 
@@ -846,4 +852,4 @@ ramp_fitting
 0.1.0 (2021-03-19)
 ==================
 
-- Added code to manipulate bitmasks.
+- Added code to manipulate bitmasks.

src/stcal/jump/jump.py

@@ -1,14 +1,14 @@
 import logging
 import multiprocessing
 import time
+
 import numpy as np
 import cv2 as cv
 import astropy.stats as stats
 
 from astropy.convolution import Ring2DKernel
 from astropy.convolution import convolve
 
-
 from . import constants
 from . import twopoint_difference as twopt
 
@@ -56,6 +56,7 @@ def detect_jumps(
     minimum_groups=3,
     minimum_sigclip_groups=100,
     only_use_ints=True,
+    min_diffs_single_pass=10,
     mask_persist_grps_next_int=True,
     persist_grps_flagged=25,
 ):
@@ -209,6 +210,15 @@ def detect_jumps(
     min_sat_radius_extend : float
         The minimum radius of the saturated core of a snowball for the core to
         be extended
+    minimum_groups: int
+       The minimum number of groups for jump detection
+    minimum_sigclip_groups: int
+       The minimum number of groups required to use sigma clipping to find outliers.
+    only_use_ints: boolean
+       In sigma clipping, if True only differences between integrations are compared. If False,
+       then all differences are processed at once.
+    min_diffs_single_pass: int
+       The minimum number of groups to switch to flagging all outliers in a single pass.
 
     Returns
     -------
@@ -280,6 +290,7 @@ def detect_jumps(
             minimum_groups=3,
             minimum_sigclip_groups=minimum_sigclip_groups,
             only_use_ints=only_use_ints,
+            min_diffs_single_pass=min_diffs_single_pass,
         )
         # remove redundant bits in pixels that have jump flagged but were
         # already flagged as do_not_use or saturated.
@@ -362,6 +373,7 @@ def detect_jumps(
                     minimum_groups,
                     minimum_sigclip_groups,
                     only_use_ints,
+                    min_diffs_single_pass,
                 ),
             )
 
@@ -388,6 +400,7 @@ def detect_jumps(
                 minimum_groups,
                 minimum_sigclip_groups,
                 only_use_ints,
+                min_diffs_single_pass,
             ),
         )
         log.info("Creating %d processes for jump detection ", n_slices)
@@ -744,10 +757,10 @@ def find_last_grp(grp, ngrps, num_grps_masked):
     ----------
     grp : int
         The location of the shower
-    
+
     ngrps : int
         The number of groups in the integration
-    
+
     num_grps_masked : int
         The requested number of groups to be flagged after the shower
 
@@ -905,10 +918,13 @@ def find_faint_extended(
       ellipse_expand: float
           The relative increase in the size of the fitted ellipse to be
           applied to the shower.
-    num_grps_masked: int
-        The number of groups after the detected shower to be flagged as jump.
-    max_extended_radius: int
-        The upper limit for the extension of saturation and jump
+      num_grps_masked: int
+          The number of groups after the detected shower to be flagged as jump.
+      max_extended_radius: int
+          The upper limit for the extension of saturation and jump
+      minimum_sigclip_groups: int
+          The minimum number of groups to use sigma clipping.
+
 
     Returns
     -------