Fixes to tests

Author: LukeSeifert

tests/integration/test-data/reference/test3/group_parameters.csv

@@ -1,3 +1,3 @@
-yield,sigma yield,half_life,sigma half_life
-0.06561555942369902,0.0,99.9999999999952,0.0
-0.0005084399691176243,0.0,55.63999999952086,0.0
+yield,half_life,sigma yield,sigma half_life
+0.06561555942369908,99.99999999999518,0.001672995207318731,0.5528496294002693
+0.0005084399691175771,55.639999999517265,0.001564055272232799,91.6936023752787

tests/integration/test-data/reference/test4/group_parameters.csv

@@ -1,7 +1,7 @@
 yield,sigma yield,half_life,sigma half_life
-0.0005084852570765399,0.0,55.63931448495001,0.0
-0.0024535591084901484,0.0,24.56927233369564,0.0
-0.001377371099639429,0.0,16.373491615853005,0.0
-0.0023955672306150803,0.0,5.604183496795593,0.0
-0.005777660031332877,0.0,2.575728332103662,0.0
-0.010862441234444095,0.0,0.9776276227180541,0.0
+0.000508486880542578,4.3502129768958245e-05,55.63928808844705,0.7215024773561042
+0.002453769309859816,0.005873434217216382,24.568939200888735,8.816877235898911
+0.0013771589037769047,0.004240700772171031,16.372661057577172,30.601676240434546
+0.002392173058981913,0.015862556241462843,5.606052854708616,9.603148047301824
+0.005766222769694957,0.10647493156241294,2.57894530924091,19.32521879828046
+0.010877272588931326,0.1114842109562966,0.9792603712095544,13.710152861118603

tests/unit/test_groupfit.py

@@ -130,7 +130,7 @@ def run_grouper_fit_test(irrad_type: str, grouper: Grouper,
     count_data = {
         'times': times,
         'counts': counts,
-        'sigma counts': np.zeros(len(counts))
+        'sigma counts': counts*1e-12
     }
 
     assert grouper.irrad_type == irrad_type
@@ -139,8 +139,8 @@ def run_grouper_fit_test(irrad_type: str, grouper: Grouper,
     test_half_lives = [data[key]['half_life'] for key in range(grouper.num_groups)]
     parameters = test_yields + test_half_lives
     adjusted_parameters = grouper._restructure_intermediate_yields(parameters)
-    residual_known = np.linalg.norm(grouper._residual_function(adjusted_parameters, times, counts, None, [], [], fit_func))
-    residual_previous = np.linalg.norm(grouper._residual_function(adjusted_parameters, times, func_counts, None, [], [], fit_func))
+    residual_known = np.linalg.norm(grouper._residual_function(adjusted_parameters, times, counts, None, [], [], counts*1e-12, fit_func))
+    residual_previous = np.linalg.norm(grouper._residual_function(adjusted_parameters, times, func_counts, None, [], [], func_counts*1e-12, fit_func))
     grouper.logger.error(f'{base_parameters = }')
     grouper.logger.error(f'{base_inter_parameters = }')
     grouper.logger.error(f'{parameters = }')