clean up extra parameters

spacetelescope · Feb 5, 2024 · 7c11971 · 7c11971
1 parent af6fbca
commit 7c11971
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Showing 3 changed files with 56 additions and 56 deletions.
diff --git a/tests/test_ramp_fitting.py b/tests/test_ramp_fitting.py
@@ -132,7 +132,7 @@ def base_neg_med_rates_multi_integrations():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores
     )
 
     return slopes, cube, optional, gls_dummy, dims
@@ -216,7 +216,7 @@ def base_neg_med_rates_single_integration_multi_segment():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores,
     )
 
     return slopes, cube, optional, gls_dummy, dims
@@ -277,7 +277,7 @@ def test_utils_dq_compress_final():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores,
     )
 
     dq = slopes[1]
@@ -356,7 +356,7 @@ def test_miri_ramp_dnu_at_ramp_beginning():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes1, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores,
     )
 
     s1 = slopes1[0]
@@ -378,7 +378,7 @@ def test_miri_ramp_dnu_and_jump_at_ramp_beginning():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes2, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores,
     )
 
     s2 = slopes2[0]
@@ -449,7 +449,7 @@ def test_2_group_cases():
     # Run ramp fit on RampData
     buffsize, save_opt, algo, wt, ncores = 512, True, "OLS", "optimal", "none"
     slopes, cube, optional, gls_dummy = ramp_fit_data(
-        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores, dqflags, avg_dark_current
+        ramp_data, buffsize, save_opt, rnoise, gain, algo, wt, ncores,
     )
 
     # Check the outputs
@@ -525,7 +525,7 @@ def run_one_group_ramp_suppression(nints, suppress):
     save_opt, ncores, bufsize = False, "none", 1024 * 30000
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
         ramp_data, bufsize, save_opt, rnoise2d, gain2d, algo,
-        "optimal", ncores, dqflags, avg_dark_current
+        "optimal", ncores,
     )
 
     return slopes, cube, dims
@@ -799,7 +799,7 @@ def test_zeroframe():
     algo, save_opt, ncores, bufsize = "OLS", False, "none", 1024 * 30000
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
         ramp_data, bufsize, save_opt, rnoise, gain, algo,
-        "optimal", ncores, dqflags, avg_dark_current)
+        "optimal", ncores,)
 
     tol = 1.0e-5
 
@@ -917,7 +917,7 @@ def test_only_good_0th_group():
     algo, save_opt, ncores, bufsize = "OLS", False, "none", 1024 * 30000
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
         ramp_data, bufsize, save_opt, rnoise, gain, algo,
-        "optimal", ncores, dqflags, avg_dark_current
+        "optimal", ncores,
     )
 
     tol = 1.0e-5
@@ -967,7 +967,7 @@ def test_all_sat():
     algo, save_opt, ncores, bufsize = "OLS", False, "none", 1024 * 30000
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
         ramp, bufsize, save_opt, rnoise, gain, algo,
-        "optimal", ncores, dqflags, avg_dark_current
+        "optimal", ncores,
     )
 
     assert slopes is None
@@ -997,7 +997,7 @@ def test_dq_multi_int_dnu():
     avg_dark_current = 0.0
     algo, save_opt, ncores, bufsize = "OLS", False, "none", 1024 * 30000
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current)
+        ramp, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,)
 
     tol = 1.0e-5
 
@@ -1094,7 +1094,7 @@ def test_multi_more_cores_than_rows():
 
     bufsize, algo, save_opt, ncores = 512, "OLS", False, "all"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
          )
     # This part of the test is simply to make sure ramp fitting
     # doesn't crash.  No asserts are necessary here.
@@ -1245,7 +1245,7 @@ def test_new_saturation():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = False, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores, dqflags, avg_dark_current
+        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores,
     )
 
     tol = 1.0e-5
@@ -1335,7 +1335,7 @@ def test_invalid_integrations():
 
     save_opt, ncores, bufsize, algo = False, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores, dqflags, avg_dark_current
+        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores,
     )
 
     tol = 1.0e-5
@@ -1397,7 +1397,7 @@ def test_one_group():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = False, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores, dqflags, avg_dark_current
+        ramp, bufsize, save_opt, rnoise, gain, algo,"optimal", ncores,
     )
 
     tol = 1e-5

diff --git a/tests/test_ramp_fitting_cases.py b/tests/test_ramp_fitting_cases.py
@@ -60,7 +60,7 @@ def test_pix_0():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -101,7 +101,7 @@ def test_pix_1():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -134,7 +134,7 @@ def test_pix_2():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -177,7 +177,7 @@ def test_pix_3():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -219,7 +219,7 @@ def test_pix_4():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -302,7 +302,7 @@ def test_pix_5():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # XXX see the note above for the differences in C and python testing values.
@@ -351,7 +351,7 @@ def test_pix_6():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -392,7 +392,7 @@ def test_pix_7():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -425,7 +425,7 @@ def test_pix_8():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -459,7 +459,7 @@ def test_pix_9():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -502,7 +502,7 @@ def test_pix_10():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -543,7 +543,7 @@ def test_pix_11():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -579,7 +579,7 @@ def test_pix_12():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results for pixel 1:
@@ -633,7 +633,7 @@ def test_miri_0():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -667,7 +667,7 @@ def test_miri_1():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -701,7 +701,7 @@ def test_miri_2():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results:
@@ -735,7 +735,7 @@ def test_miri_3():
     avg_dark_current = 0.0
     save_opt, ncores, bufsize, algo = True, "none", 1024 * 30000, "OLS"
     slopes, cube, ols_opt, gls_opt = ramp_fit_data(
-        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores, dqflags, avg_dark_current
+        ramp_data, bufsize, save_opt, rnoise, gain, algo, "optimal", ncores,
     )
 
     # Set truth values for PRIMARY results: