Merge pull request #72 from HeloiseS/agewizard_errors

Agewizard errors

hoki/age/tests/test_utils.py

@@ -0,0 +1,182 @@
+import hoki.age.utils as au
+from hoki.age.wizard import AgeWizard
+import hoki.load as load
+import pkg_resources
+import numpy as np
+import pandas as pd
+import pytest
+from hoki.utils.exceptions import HokiFatalError, HokiUserWarning, HokiFormatError
+
+# Loading Data
+
+data_path = pkg_resources.resource_filename('hoki', 'data')
+hr_file = data_path + '/hrs-sin-imf_chab100.zem4.dat'
+cmd_file = data_path + '/cmd_bv_z002_bin_imf135_300'
+myhrd = load.model_output(hr_file, hr_type='TL')
+mycmd = load.unpickle(cmd_file)
+
+#### Creating Test Inputs
+
+# Version 1 AgeWizard
+fake_hrd_input = pd.DataFrame.from_dict({'name': ['star1', 'star2', 'star3'],
+                                         'logT': np.array([4.58, 4.48, 4.14]),
+                                         'logL': np.array([4.83, 5.07, 5.40])})
+
+bad_hrd_input = pd.DataFrame.from_dict({'logT': np.array(['bla']),
+                                        'logL': np.array([4.83])})
+
+no_name_input = pd.DataFrame.from_dict({'logT': np.array([4.58, 4.48, 4.14]),
+                                        'logL': np.array([4.83, 5.07, 5.40])})
+
+bad_hrd_input2 = pd.DataFrame.from_dict({'logT': np.array([4.58, 'bla']),
+                                         'logL': np.array([4.83, 2.0])})
+
+fake_cmd_input = pd.DataFrame.from_dict({'name': ['star1', 'star2', 'STAR3'],
+                                         'col': np.array([-0.3, 0.5, -0.25]),
+                                         'mag': np.array([-5, -10, -1])})
+
+bad_cmd_input = pd.DataFrame.from_dict({'col': np.array(['bla']),
+                                        'mag': np.array([-5])})
+
+# Version 2 AgeWizard
+stars_none = pd.DataFrame.from_dict({'name': np.array(['118-1', '118-2', '118-3', '118-4']),
+                                     'logL': np.array([5.0, 5.1, 4.9, 5.9]),
+                                     'logT': np.array([4.48, 4.45, 4.46, 4.47]),
+                                     })
+
+stars_SYM = pd.DataFrame.from_dict({'name': np.array(['118-1', '118-2', '118-3', '118-4']),
+                                    'logL': np.array([5.0, 5.1, 4.9, 5.9]),
+                                    'logL_err': np.array([0.1, 0.2, 0.1, 0.1]),
+                                    'logT': np.array([4.48, 4.45, 4.46, 4.47]),
+                                    'logT_err': np.array([0.1, 0.2, 0.1, 0.1]),
+                                    })
+
+stars_SYM_T_err_missing = pd.DataFrame.from_dict({'name': np.array(['118-1', '118-2', '118-3', '118-4']),
+                                    'logL': np.array([5.0, 5.1, 4.9, 5.9]),
+                                    'logL_err': np.array([0.1, 0.2, 0.1, 0.1]),
+                                    'logT': np.array([4.48, 4.45, 4.46, 4.47]),
+                                    'logT_err': np.array([0.1, 0.2, 0.1, 0.1]),
+                                    })
+
+#########
+# MISC  #
+#########
+
+class TestNormalise1D(object):
+    def test_it_runs(self):
+        au.normalise_1d(np.array([0, 1, 4, 5, 0, 1, 7, 8]))
+
+    def test_basic(self):
+        norm = au.normalise_1d(np.array([0, 0, 1, 0, 0, 0, 0]))
+        assert norm[2] == 1, 'Normalisation done wrong'
+        assert sum(norm) == 1, "Normalisaton done wrong"
+
+class TestErrorFlag(object):
+    def test_no_err(self):
+        assert au._error_flag(stars_none) is None, "Error Flag should be None"
+
+    def test_ERR(self):
+        assert au._error_flag(stars_SYM) == 'ERR', "Error Flag should be ERR"
+
+
+#######################
+# FINDING COORDINATES #
+#######################
+
+
+class TestFindCoordinates(object):
+    def test_hrd_input(self):
+        T_coord, L_coord = au.find_coordinates(obs_df=fake_hrd_input, model=myhrd)
+        assert np.sum(
+            np.isclose([T_coord[0], T_coord[1], T_coord[2]], [45, 44, 40])) == 3, "Temperature coordinates wrong"
+        assert np.sum(
+            np.isclose([L_coord[0], L_coord[1], L_coord[2]], [77, 80, 83])) == 3, "Luminosity coordinates wrong"
+
+    def test_cmd_input(self):
+        col_coord, mag_range = au.find_coordinates(obs_df=fake_cmd_input, model=mycmd)
+        assert np.sum(
+            np.isclose([col_coord[0], col_coord[1], col_coord[2]], [27, 35, 27])) == 3, "color coordinates wrong"
+        assert np.sum(
+            np.isclose([mag_range[0], mag_range[1], mag_range[2]], [90, 40, 130])) == 3, "magnitude coordinates wrong"
+
+
+class TestFindCMDCoordinates(object):
+    def test_fake_input(self):
+        col_coord, mag_range = au._find_cmd_coordinates(obs_df=fake_cmd_input, mycmd=mycmd)
+        assert np.sum(
+            np.isclose([col_coord[0], col_coord[1], col_coord[2]], [27, 35, 27])) == 3, "color coordinates wrong"
+        assert np.sum(
+            np.isclose([mag_range[0], mag_range[1], mag_range[2]], [90, 40, 130])) == 3, "magnitude coordinates wrong"
+
+    def test_bad_input(self):
+        with pytest.raises(HokiFormatError):
+            col_coord, mag_range = au._find_cmd_coordinates(obs_df=bad_hrd_input, mycmd=mycmd)
+
+    def test_bad_input_2(self):
+        col_coord, mag_range = au._find_cmd_coordinates(obs_df=bad_cmd_input, mycmd=mycmd)
+        assert np.isclose(mag_range[0], 90), "This L coordinate is wrong - test_bad_input."
+
+
+class TestFindHRDCoordinates(object):
+    def test_fake_input(self):
+        T_coord, L_coord = au._find_hrd_coordinates(obs_df=fake_hrd_input, myhrd=myhrd)
+        assert np.sum(
+            np.isclose([T_coord[0], T_coord[1], T_coord[2]], [45, 44, 40])) == 3, "Temperature coordinates wrong"
+        assert np.sum(
+            np.isclose([L_coord[0], L_coord[1], L_coord[2]], [77, 80, 83])) == 3, "Luminosity coordinates wrong"
+
+    def test_bad_input(self):
+        with pytest.raises(HokiFormatError):
+            __, __ = au._find_hrd_coordinates(obs_df=bad_cmd_input, mycmd=mycmd)
+
+    def test_bad_input(self):
+        T_coord, L_coord = au._find_hrd_coordinates(obs_df=bad_hrd_input, myhrd=myhrd)
+        #assert np.isnan(T_coord[0]), "This should be a nan"
+        assert np.isclose(L_coord[0], 77), "This L coordinate is wrong - test_bad_input."
+
+
+###############################
+# CALCULATING INDIVIDUAL PDFS #
+###############################
+
+
+class TestCalculatePDFs(object):
+    def test_fake_input(self):
+        pdf_df = au.calculate_individual_pdfs(fake_hrd_input, myhrd)
+        assert 'star1' in pdf_df.columns, "Column name issue"
+        assert int(sum(pdf_df.star1)) == 1, "PDF not calculated correctly"
+
+    def test_input_without_name(self):
+        pdf_df = au.calculate_individual_pdfs(no_name_input, myhrd)
+
+        assert 's1' in pdf_df.columns, "Column names not created right"
+
+    def test_bad_input(self):
+        pdf_df = au.calculate_individual_pdfs(bad_hrd_input2, myhrd)
+        assert not np.isnan(sum(pdf_df.s0)), "something went wrong"
+
+    def test_symmetric_errors(self):
+        pdf_df = au.calculate_individual_pdfs(stars_SYM, myhrd)
+        assert not np.isnan(sum(pdf_df['118-4'])), "something went wrong with symmetric errors"
+
+#####################################
+# PUTTING PDFS TOGETHER IN SOME WAY #
+#####################################
+
+
+class TestCalculateSamplePDF(object):
+    def test_basic(self):
+        distributions = au.calculate_distributions(fake_hrd_input, myhrd)
+        combined = au.calculate_sample_pdf(distributions)
+        assert np.isclose(combined.pdf[9], 0.2715379752638662), "combined PDF not right"
+
+    def test_drop_bad(self):
+        distributions = au.calculate_distributions(fake_hrd_input, myhrd)
+        combined = au.calculate_sample_pdf(distributions, not_you=[3])
+        assert np.isclose(combined.pdf[9], 0.2715379752638662), "combined PDF not right"
+
+    def test_drop_good(self):
+        distributions = au.calculate_distributions(fake_hrd_input, myhrd)
+        combined = au.calculate_sample_pdf(distributions, not_you=['star1'])
+        assert np.isclose(combined.pdf[9], 0.774602971512809), "combined PDF not right"
+

hoki/age/tests/test_wizard.py

@@ -0,0 +1,80 @@
+import hoki.age.utils as au
+from hoki.age.wizard import AgeWizard
+import hoki.load as load
+import pkg_resources
+import numpy as np
+import pandas as pd
+import pytest
+from hoki.utils.exceptions import HokiFatalError, HokiUserWarning, HokiFormatError
+
+
+# Loading Data
+
+data_path = pkg_resources.resource_filename('hoki', 'data')
+hr_file = data_path + '/hrs-sin-imf_chab100.zem4.dat'
+cmd_file = data_path + '/cmd_bv_z002_bin_imf135_300'
+myhrd = load.model_output(hr_file, hr_type='TL')
+mycmd = load.unpickle(cmd_file)
+# Creating Test Inputs
+
+fake_hrd_input = pd.DataFrame.from_dict({'name': ['star1', 'star2', 'star3'],
+                                         'logT': np.array([4.58, 4.48, 4.14]),
+                                         'logL': np.array([4.83, 5.07, 5.40])})
+
+bad_hrd_input = pd.DataFrame.from_dict({'logT': np.array(['bla']),
+                                        'logL': np.array([4.83])})
+
+no_name_input = pd.DataFrame.from_dict({'logT': np.array([4.58, 4.48, 4.14]),
+                                        'logL': np.array([4.83, 5.07, 5.40])})
+
+bad_hrd_input2 = pd.DataFrame.from_dict({'logT': np.array([4.58, 'bla']),
+                                         'logL': np.array([4.83, 2.0])})
+
+fake_cmd_input = pd.DataFrame.from_dict({'name': ['star1', 'star2', 'STAR3'],
+                                         'col': np.array([-0.3, 0.5, -0.25]),
+                                         'mag': np.array([-5, -10, -1])})
+
+bad_cmd_input = pd.DataFrame.from_dict({'col': np.array(['bla']),
+                                        'mag': np.array([-5])})
+
+
+class TestAgeWizardBasic(object):
+    def test_init_basic(self):
+        assert AgeWizard(obs_df=fake_hrd_input, model=hr_file), "Loading HRD file path failed"
+        assert AgeWizard(obs_df=fake_hrd_input, model=myhrd), "Loading with hoki.hrdiagrams.HRDiagram failed"
+        assert AgeWizard(obs_df=fake_cmd_input, model=mycmd), 'Loading with hoki.cmd.CMD'
+        assert AgeWizard(obs_df=fake_cmd_input, model=cmd_file), 'Loading CMD from frile failed'
+
+    def test_bad_init(self):
+        with pytest.raises(HokiFatalError):
+            __, __ = AgeWizard(obs_df=fake_cmd_input, model='sdfghj'), 'HokiFatalError should be raised'
+
+        with pytest.raises(HokiFormatError):
+            __, __ = AgeWizard(obs_df='edrftgyhu', model=cmd_file), 'HokiFormatError should be raised'
+
+    def test_combine_pdfs_not_you(self):
+        wiz = AgeWizard(fake_hrd_input, myhrd)
+        wiz.calculate_sample_pdf(not_you=['star1'])
+        cpdf = wiz.sample_pdf.pdf
+        assert np.sum(np.isclose([cpdf[0], cpdf[9]], [0.0,  0.7231526323765232])) == 2, "combined pdf is not right"
+
+    def test_most_likely_age(self):
+        wiz = AgeWizard(obs_df=fake_hrd_input, model=hr_file)
+        assert np.isclose(wiz.most_likely_age[0], 6.9), "Most likely age wrong"
+
+    def test_most_likely_ages(self):
+        wiz = AgeWizard(obs_df=fake_hrd_input, model=hr_file)
+        a = wiz.most_likely_ages
+        assert np.sum(np.isclose([a[0], a[1], a[2]], [6.9, 6.9, 6.9])) == 3, "Most likely ages not right"
+
+    def test_combine_pdfs(self):
+        wiz = AgeWizard(fake_hrd_input, myhrd)
+        wiz.calculate_sample_pdf()
+        assert np.isclose(wiz.sample_pdf.pdf[9],0.551756734145878), "Something is wrong with the combined_Age PDF"
+
+    def test_calculate_p_given_age_range(self):
+        wiz = AgeWizard(fake_hrd_input, myhrd)
+        probas = wiz.calculate_p_given_age_range([6.7, 6.9])
+        assert np.sum(np.isclose([probas[0], probas[1], probas[2]],
+                                 [0.515233714952414, 0.7920611550946726, 0.6542441096583737])) == 3, \
+            "probability given age range is messed up"