Updating the STCAL code to use the algorithm class variable in the JW…

…ST RampFitStep class to call the C code vs the python code. To call the C code set the algorithm class variable needs to be set to 'OLS_C'.

src/stcal/ramp_fitting/ols_fit.py

@@ -661,9 +661,9 @@ def ols_ramp_fit_single(ramp_data, buffsize, save_opt, readnoise_2d, gain_2d, we
     opt_info : tuple
         The tuple of computed optional results arrays for fitting.
     """
-    use_c = False
+    # use_c = False
     # use_c = True
-    # use_c = ramp_data.dbg_run_c_code
+    use_c = ramp_data.dbg_run_c_code
     if use_c:
         print(" ")
         print("=" * 80)
@@ -689,6 +689,11 @@ def ols_ramp_fit_single(ramp_data, buffsize, save_opt, readnoise_2d, gain_2d, we
         if gain_bswap:
             gain_2d.newbyteorder('S').byteswap(inplace=True)
 
+        c_diff = c_end - c_start
+        print('-' * 80)
+        print(f"    **** Total C time: {c_diff}")
+        print('-' * 80)
+
         return image_info, integ_info, opt_info
 
     # XXX start python time
@@ -702,8 +707,10 @@ def ols_ramp_fit_single(ramp_data, buffsize, save_opt, readnoise_2d, gain_2d, we
 
     # XXX end python time
     p_end = time.time()
-    if use_c:
-        c_python_time_comparison(c_start, c_end, p_start, p_end)
+    p_diff = p_end - p_start
+    print('-' * 80)
+    print(f"    **** Total Python time: {p_diff}")
+    print('-' * 80)
 
     return image_info, integ_info, opt_info
 

src/stcal/ramp_fitting/ramp_fit.py

@@ -172,6 +172,9 @@ def ramp_fit(
     # data models.
     ramp_data = create_ramp_fit_class(model, dqflags, suppress_one_group)
 
+    if algorithm.upper() == "OLS_C":
+        ramp_data.dbg_run_c_code = True
+
     return ramp_fit_data(
         ramp_data, buffsize, save_opt, readnoise_2d, gain_2d, algorithm, weighting, max_cores, dqflags
     )
@@ -242,6 +245,7 @@ def ramp_fit_data(
         )
         opt_info = None
     else:
+        # Default to OLS.
         # Get readnoise array for calculation of variance of noiseless ramps, and
         #   gain array in case optimal weighting is to be done
         nframes = ramp_data.nframes

src/stcal/ramp_fitting/ramp_fit_class.py

@@ -39,13 +39,15 @@ def __init__(self):
         # One group ramp suppression for saturated ramps after 0th group.
         self.suppress_one_group_ramps = False
 
+        # C code debugging switch.
+        self.dbg_run_c_code = False
+
         self.one_groups_locs = None  # One good group locations.
         self.one_groups_time = None  # Time to use for one good group ramps.
 
         self.current_integ = -1
 
     def set_arrays(self, data, err, groupdq, pixeldq, average_dark_current):
-        self.dbg_run_c_code = False
         """
         Set the arrays needed for ramp fitting.