Merge pull request #58 from jtniehof/test_updates

Unit test updates to run on my machine

Author: pleasant-menlo

scripts/convert_product_definition_to_yaml.py

@@ -37,7 +37,8 @@ def convert_csv_to_yaml(file_path):
                 else:
                     required_variables = required_for_data
 
-                if row[header_to_index["RECORD_VARYING"]].lower() == "nrv":
+                if (("RECORD_VARYING" in required_variables or "RECORD_VARYING" in header_to_index)
+                   and row[header_to_index["RECORD_VARYING"]].lower() == "nrv"):
                     required_variables = [variable for variable in required_variables if
                                           variable != "DEPEND_0"]
 

tests/hit/l3/pha/science/test_range_fit_lookup.py

@@ -76,8 +76,8 @@ def test_loads_csv_into_array(self):
                     charges, delta_e_loss = lookup_table.evaluate_e_prime(range, e_prime)
 
                     np.testing.assert_equal(charges, expected_charges)
-                    np.testing.assert_equal([double_power_law(e_prime, *charge1_parameters),
-                                             double_power_law(e_prime, *charge2_parameters)], delta_e_loss)
+                    np.testing.assert_allclose([double_power_law(e_prime, *charge1_parameters),
+                                                double_power_law(e_prime, *charge2_parameters)], delta_e_loss)
 
     def test_load_from_real_example_files(self):
         range_fit_lookup = RangeFitLookup.from_files(

tests/maps/test_spectral_fit.py

@@ -174,8 +174,8 @@ def test_finds_best_fit_with_nan_in_flux(self):
 
                 scalar_coefficients, result, result_error = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_equal(result, np.array(true_gamma).reshape(1, 1, *spacial_dimension_shape))
-                np.testing.assert_array_equal(scalar_coefficients,
-                                              np.array(true_A).reshape(1, 1, *spacial_dimension_shape))
+                np.testing.assert_allclose(scalar_coefficients,
+                                           np.array(true_A).reshape(1, 1, *spacial_dimension_shape))
 
     def test_spectral_fit_map_negative_gammas(self):
         epoch = np.array([datetime.now()])
@@ -244,8 +244,8 @@ def test_finds_best_fit_with_nan_in_uncertainty(self):
 
                 scalar_coefficients, result, result_error = fit_arrays_to_power_law(flux, uncertainty, energies)
                 np.testing.assert_array_equal(result, np.array(true_gamma).reshape(1, 1, *spacial_dimension_shape))
-                np.testing.assert_array_equal(scalar_coefficients,
-                                              np.array(true_A).reshape(1, 1, *spacial_dimension_shape))
+                np.testing.assert_allclose(scalar_coefficients,
+                                           np.array(true_A).reshape(1, 1, *spacial_dimension_shape))
 
     def test_finds_best_fit_with_zero_in_flux_and_uncertainty(self):
         energies = np.geomspace(1, 10, 23)

tests/scripts/test_convert_product_definition_to_yaml.py

@@ -25,7 +25,8 @@ def test_parse_required_for_data_with_multiple_depend(self):
             "FILLVAL": ["-1.00E+31", "", ""],
             "LABL_PTR_1": ["energy_label", "", ""],
             "LABL_PTR_2": ["pitch_angle_label", "", ""],
-            "VARIABLE_PURPOSE": ["primary var, summary", "", ""]
+            "VARIABLE_PURPOSE": ["primary var, summary", "", ""],
+            "RECORD_VARYING": ["rv", "nrv", "nrv"]
         }
 
         rows = [
@@ -58,6 +59,7 @@ def test_parse_required_for_data_with_multiple_depend(self):
    LABL_PTR_1: energy_label
    LABL_PTR_2: pitch_angle_label
    VARIABLE_PURPOSE: primary var, summary
+   RECORD_VARYING: rv
 energy_label:
    NAME: energy_label
    DATA_TYPE: str
@@ -160,7 +162,8 @@ def test_parse_required_for_support_data_non_rv(self):
 
     def test_parse_required_for_data_epoch(self):
         required_for_data = ["NAME", "DATA_TYPE", "CATDESC", "VAR_TYPE", "DEPEND_0", "DISPLAY_TYPE",
-                             "FIELDNAM", "FORMAT", "LABLAXIS", "UNITS", "VALIDMIN", "VALIDMAX", "FILLVAL"]
+                             "FIELDNAM", "FORMAT", "LABLAXIS", "UNITS", "VALIDMIN", "VALIDMAX", "FILLVAL",
+                             "RECORD_VARYING"]
 
         test_csv_values = [
             "epoch",
@@ -175,7 +178,8 @@ def test_parse_required_for_data_epoch(self):
             "",
             "",
             "",
-            "-1.00E+31"
+            "-1.00E+31",
+            "rv"
         ]
         filePath = "csv_test_file.csv"
         with open(filePath, "w", newline='') as csvfile:
@@ -193,7 +197,8 @@ def test_parse_required_for_data_epoch(self):
    UNITS: ' '
    VALIDMIN: ' '
    VALIDMAX: ' '
-   FILLVAL: -1.00E+31"""
+   FILLVAL: -1.00E+31
+   RECORD_VARYING: rv"""
         actual_yaml = convert_csv_to_yaml(filePath)
         self.assertEqual(expected_yaml, actual_yaml)
 

tests/swapi/l3a/science/test_calculate_proton_solar_wind_temperature_and_density.py

@@ -292,7 +292,7 @@ def test_throws_error_when_chi_squared_over_ten(self):
             coincident_count_rates, energy, 1)
 
         self.assertAlmostEqual(77665.54856, proton_solar_wind_temp_and_density.temperature.nominal_value,
-                               4)
+                               3)
         self.assertAlmostEqual(3676.14173, proton_solar_wind_temp_and_density.temperature.std_dev, 3)
         self.assertAlmostEqual(0.03594, proton_solar_wind_temp_and_density.density.nominal_value,
                                5)