JP-3770: emicorr memory and run time improvement

changes/8849.refpix.rst

@@ -0,0 +1 @@
+Removed the interleve array and do interleving of noise and subtraction in-place to avoid creating 2 arrays of equal dimensions to data

jwst/emicorr/emicorr.py

@@ -438,25 +438,23 @@ def apply_emicorr(output_model, emicorr_model,
         # This is the phase matched noise model to subtract from each pixel of the input image
         dd_noise = lut[(phaseall * period_in_pixels).astype(int)]
 
-        # Interleave (straight copy) into 4 amps
-        noise = np.zeros((nints, ngroups, ny, nx))   # same size as input data
-        noise_x = np.arange(nx4) * 4
-        for k in range(4):
-            noise[:, :, :, noise_x + k] = dd_noise
-
         # Safety catch; anywhere the noise value is not finite, set it to zero
-        noise[~np.isfinite(noise)] = 0.0
+        dd_noise[~np.isfinite(dd_noise)] = 0.0
 
         # Subtract EMI noise from the input data
         log.info('Subtracting EMI noise from data')
-        output_model.data = output_model.data - noise
+
+        # Interleave (straight copy) into 4 amps
+        noise_x = np.arange(nx4) * 4
+        for k in range(4):
+            output_model.data[..., noise_x + k] -= dd_noise
 
         # clean up
         del data
         del dd_all
         del times_this_int
         del phaseall
-        del noise
+        del dd_noise
 
     if save_intermediate_results and save_onthefly_reffile is not None:
         if 'FAST' in readpatt:

jwst/emicorr/tests/test_emicorr.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 from jwst.emicorr import emicorr, emicorr_step
-from stdatamodels.jwst.datamodels import Level1bModel, EmiModel
+from stdatamodels.jwst.datamodels import RampModel, EmiModel
 
 
 subarray_example_case = {
@@ -33,7 +33,7 @@
 
 def mk_data_mdl(data, subarray, readpatt, detector):
     # create input_model
-    input_model = Level1bModel(data=data)
+    input_model = RampModel(data=data)
     input_model.meta.instrument.name = 'MIRI'
     input_model.meta.instrument.detector = detector
     input_model.meta.exposure.type = 'MIR_4QPM'