Remove unecessary code

Removed a step that would mask zeros as np.nan right before storing the results.
This is not necessary anymore as the benchmark for the system tests is being
updated in this PR.

Updated the benchmark once again to match current state of vesuvio analysis.

src/mvesuvio/analysis_reduction.py

@@ -814,8 +814,7 @@ def _replace_zero_columns_with_ncp_fit(self):
             OutputWorkspace=self._workspace_for_corrections.name() + "_CorrectionsInput"
         )
         for row in range(self._workspace_for_corrections.getNumberHistograms()):
-            # TODO: Once the option to change point to hist is removed, remove [:len(ncp)]
-            self._workspace_for_corrections.dataY(row)[self._zero_columns_boolean_mask] = ncp[row, self._zero_columns_boolean_mask[:len(ncp[row])]]
+            self._workspace_for_corrections.dataY(row)[self._zero_columns_boolean_mask] = ncp[row, self._zero_columns_boolean_mask]
 
         SumSpectra(
             InputWorkspace=self._workspace_for_corrections.name(), 
@@ -1069,14 +1068,6 @@ def _set_results(self):
     def _save_results(self):
         """Saves all of the arrays stored in this object"""
 
-        maskedDetectorIdx = np.array(self._mask_spectra) - min(self._workspace_being_fit.getSpectrumNumbers())
-
-        # TODO: Take out nans next time when running original results
-        # Because original results were recently saved with nans, mask spectra with nans
-        self.all_spec_best_par_chi_nit[:, maskedDetectorIdx, :] = np.nan
-        self.all_ncp_for_each_mass[:, maskedDetectorIdx, :, :] = np.nan
-        self.all_tot_ncp[:, maskedDetectorIdx, :] = np.nan
-
         if not self._save_results_path:
             return 
 

tests/system/analysis/test_analysis.py

@@ -117,14 +117,10 @@ def setUpClass(cls):
 
     def setUp(self):
         self.orincp = self.benchmarkResults["all_tot_ncp"]
-
         self.optncp = self.currentResults.all_tot_ncp
 
     def test_ncp(self):
-        correctNansOri = np.where(
-            (self.orincp == 0) & np.isnan(self.optncp), np.nan, self.orincp
-        )
-        nptest.assert_almost_equal(correctNansOri, self.optncp, decimal=5)
+        nptest.assert_almost_equal(self.orincp, self.optncp, decimal=5)
 
 
 class TestMeanWidths(unittest.TestCase):