diff options
author | zsloan | 2021-11-11 11:23:39 -0600 |
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committer | GitHub | 2021-11-11 11:23:39 -0600 |
commit | 8c77af63efae6f06d7c7c3269fc0e41811a8037a (patch) | |
tree | 9ffa4b84fd36f09e772db3e218bc980999324c41 /tests | |
parent | 607c6e627c23c1bce3b199b145855182ab51b211 (diff) | |
parent | 249b85102063debfeeb1b0565956059b8a3af1cf (diff) | |
download | genenetwork3-8c77af63efae6f06d7c7c3269fc0e41811a8037a.tar.gz |
Merge branch 'main' into feature/add_rqtl_pairscan
Diffstat (limited to 'tests')
-rw-r--r-- | tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv | 101 | ||||
-rw-r--r-- | tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv | 101 | ||||
-rw-r--r-- | tests/unit/computations/test_biweight.py | 21 | ||||
-rw-r--r-- | tests/unit/computations/test_correlation.py | 37 | ||||
-rw-r--r-- | tests/unit/computations/test_partial_correlations.py | 335 | ||||
-rw-r--r-- | tests/unit/computations/test_wgcna.py | 14 | ||||
-rw-r--r-- | tests/unit/db/test_traits.py | 176 | ||||
-rw-r--r-- | tests/unit/test_authentication.py | 101 | ||||
-rw-r--r-- | tests/unit/test_data_helpers.py | 61 | ||||
-rw-r--r-- | tests/unit/test_heatmaps.py | 87 |
10 files changed, 899 insertions, 135 deletions
diff --git a/tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv b/tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv new file mode 100644 index 0000000..a1558a0 --- /dev/null +++ b/tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv @@ -0,0 +1,101 @@ +"function_name","count","x","y","z","method","rm","result" +"pcor.mat",13,"-89.1427156049758, -70.2603165991604, 52.4590492714196, -57.2846714872867, -26.3361851219088, -0.000567594543099403, 17.9622953757644, -64.1319836024195, 39.2497098539025, 20.8931459579617, 74.1897551808506, -35.3126015048474, -55.9552798978984","47.3745858296752, -68.9209029078484, -31.9765134248883, -45.0486478861421, -85.1716816890985, 65.432888455689, 19.2734406329691, 87.9198614973575, -68.2076670229435, -38.1280574947596, 52.754437038675, -73.271297942847, 67.7760738879442","-78.9239354431629, -85.3030194528401, -20.3673145733774, -22.6184178609401, 16.5013548452407, 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-31.7320866975933, 33.8117491919547, 49.1156910546124, -42.7486607804894","p",FALSE,0.109506018207148 diff --git a/tests/unit/computations/test_biweight.py b/tests/unit/computations/test_biweight.py deleted file mode 100644 index ad404f1..0000000 --- a/tests/unit/computations/test_biweight.py +++ /dev/null @@ -1,21 +0,0 @@ -"""test for biweight script""" -from unittest import TestCase -from unittest import mock - -from gn3.computations.biweight import calculate_biweight_corr - - -class TestBiweight(TestCase): - """test class for biweight""" - - @mock.patch("gn3.computations.biweight.subprocess.check_output") - def test_calculate_biweight_corr(self, mock_check_output): - """test for calculate_biweight_corr func""" - mock_check_output.return_value = "0.1 0.5" - results = calculate_biweight_corr(command="Rscript", - path_to_script="./r_script.R", - trait_vals=[ - 1.2, 1.1, 1.9], - target_vals=[1.9, 0.4, 1.1]) - - self.assertEqual(results, (0.1, 0.5)) diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py index fc52ec1..706520a 100644 --- a/tests/unit/computations/test_correlation.py +++ b/tests/unit/computations/test_correlation.py @@ -1,14 +1,15 @@ """Module contains the tests for correlation""" from unittest import TestCase from unittest import mock +import unittest from collections import namedtuple from gn3.computations.correlations import normalize_values -from gn3.computations.correlations import do_bicor from gn3.computations.correlations import compute_sample_r_correlation from gn3.computations.correlations import compute_all_sample_correlation from gn3.computations.correlations import filter_shared_sample_keys + from gn3.computations.correlations import tissue_correlation_for_trait from gn3.computations.correlations import lit_correlation_for_trait from gn3.computations.correlations import fetch_lit_correlation_data @@ -94,20 +95,11 @@ class TestCorrelation(TestCase): results = normalize_values([2.3, None, None, 3.2, 4.1, 5], [3.4, 7.2, 1.3, None, 6.2, 4.1]) - expected_results = ([2.3, 4.1, 5], [3.4, 6.2, 4.1], 3) - - self.assertEqual(results, expected_results) - - @mock.patch("gn3.computations.correlations.calculate_biweight_corr") - def test_bicor(self, mock_biweight): - """Test for doing biweight mid correlation """ - mock_biweight.return_value = (1.0, 0.0) - - results = do_bicor(x_val=[1, 2, 3], y_val=[4, 5, 6]) + expected_results = [(2.3, 4.1, 5), (3.4, 6.2, 4.1)] - self.assertEqual(results, (1.0, 0.0) - ) + self.assertEqual(list(zip(*list(results))), expected_results) + @unittest.skip("reason for skipping") @mock.patch("gn3.computations.correlations.compute_corr_coeff_p_value") @mock.patch("gn3.computations.correlations.normalize_values") def test_compute_sample_r_correlation(self, norm_vals, compute_corr): @@ -163,22 +155,23 @@ class TestCorrelation(TestCase): } - filtered_target_samplelist = ["1.23", "6.565", "6.456"] - filtered_this_samplelist = ["6.266", "6.565", "6.456"] + filtered_target_samplelist = ("1.23", "6.565", "6.456") + filtered_this_samplelist = ("6.266", "6.565", "6.456") results = filter_shared_sample_keys( this_samplelist=this_samplelist, target_samplelist=target_samplelist) - self.assertEqual(results, (filtered_this_samplelist, - filtered_target_samplelist)) + self.assertEqual(list(zip(*list(results))), [filtered_this_samplelist, + filtered_target_samplelist]) @mock.patch("gn3.computations.correlations.compute_sample_r_correlation") @mock.patch("gn3.computations.correlations.filter_shared_sample_keys") def test_compute_all_sample(self, filter_shared_samples, sample_r_corr): """Given target dataset compute all sample r correlation""" - filter_shared_samples.return_value = (["1.23", "6.565", "6.456"], [ - "6.266", "6.565", "6.456"]) + filter_shared_samples.return_value = [iter(val) for val in [( + "1.23", "6.266"), ("6.565", "6.565"), ("6.456", "6.456")]] + sample_r_corr.return_value = (["1419792_at", -1.0, 0.9, 6]) this_trait_data = { @@ -210,10 +203,8 @@ class TestCorrelation(TestCase): this_trait=this_trait_data, target_dataset=traits_dataset), sample_all_results) sample_r_corr.assert_called_once_with( trait_name='1419792_at', - corr_method="pearson", trait_vals=['1.23', '6.565', '6.456'], - target_samples_vals=['6.266', '6.565', '6.456']) - filter_shared_samples.assert_called_once_with( - this_trait_data.get("trait_sample_data"), traits_dataset[0].get("trait_sample_data")) + corr_method="pearson", trait_vals=('1.23', '6.565', '6.456'), + target_samples_vals=('6.266', '6.565', '6.456')) @mock.patch("gn3.computations.correlations.compute_corr_coeff_p_value") def test_tissue_correlation_for_trait(self, mock_compute_corr_coeff): diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py new file mode 100644 index 0000000..83cb9d9 --- /dev/null +++ b/tests/unit/computations/test_partial_correlations.py @@ -0,0 +1,335 @@ +"""Module contains tests for gn3.partial_correlations""" + +import csv +from unittest import TestCase, skip +from gn3.computations.partial_correlations import ( + fix_samples, + control_samples, + dictify_by_samples, + tissue_correlation, + find_identical_traits, + partial_correlation_matrix, + good_dataset_samples_indexes, + partial_correlation_recursive) + +sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] +control_traits = ( + { + "mysqlid": 36688172, + "data": { + "B6cC3-1": { + "sample_name": "B6cC3-1", "value": 7.51879, "variance": None, + "ndata": None}, + "BXD1": { + "sample_name": "BXD1", "value": 7.77141, "variance": None, + "ndata": None}, + "BXD12": { + "sample_name": "BXD12", "value": 8.39265, "variance": None, + "ndata": None}, + "BXD16": { + "sample_name": "BXD16", "value": 8.17443, "variance": None, + "ndata": None}, + "BXD19": { + "sample_name": "BXD19", "value": 8.30401, "variance": None, + "ndata": None}, + "BXD2": { + "sample_name": "BXD2", "value": 7.80944, "variance": None, + "ndata": None}}}, + { + "mysqlid": 36688172, + "data": { + "B6cC3-21": { + "sample_name": "B6cC3-1", "value": 7.51879, "variance": None, + "ndata": None}, + "BXD21": { + "sample_name": "BXD1", "value": 7.77141, "variance": None, + "ndata": None}, + "BXD12": { + "sample_name": "BXD12", "value": 8.39265, "variance": None, + "ndata": None}, + "BXD16": { + "sample_name": "BXD16", "value": 8.17443, "variance": None, + "ndata": None}, + "BXD19": { + "sample_name": "BXD19", "value": 8.30401, "variance": None, + "ndata": None}, + "BXD2": { + "sample_name": "BXD2", "value": 7.80944, "variance": None, + "ndata": None}}}, + { + "mysqlid": 36688172, + "data": { + "B6cC3-1": { + "sample_name": "B6cC3-1", "value": 7.51879, "variance": None, + "ndata": None}, + "BXD1": { + "sample_name": "BXD1", "value": 7.77141, "variance": None, + "ndata": None}, + "BXD12": { + "sample_name": "BXD12", "value": None, "variance": None, + "ndata": None}, + "BXD16": { + "sample_name": "BXD16", "value": None, "variance": None, + "ndata": None}, + "BXD19": { + "sample_name": "BXD19", "value": None, "variance": None, + "ndata": None}, + "BXD2": { + "sample_name": "BXD2", "value": 7.80944, "variance": None, + "ndata": None}}}) + +dictified_control_samples = ( + {"B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879, "variance": None}, + "BXD1": {"sample_name": "BXD1", "value": 7.77141, "variance": None}, + "BXD12": {"sample_name": "BXD12", "value": 8.39265, "variance": None}, + "BXD16": {"sample_name": "BXD16", "value": 8.17443, "variance": None}, + "BXD19": {"sample_name": "BXD19", "value": 8.30401, "variance": None}, + "BXD2": {"sample_name": "BXD2", "value": 7.80944, "variance": None}}, + {"BXD12": {"sample_name": "BXD12", "value": 8.39265, "variance": None}, + "BXD16": {"sample_name": "BXD16", "value": 8.17443, "variance": None}, + "BXD19": {"sample_name": "BXD19", "value": 8.30401, "variance": None}, + "BXD2": {"sample_name": "BXD2", "value": 7.80944, "variance": None}}, + {"B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879, "variance": None}, + "BXD1": {"sample_name": "BXD1", "value": 7.77141, "variance": None}, + "BXD2": {"sample_name": "BXD2", "value": 7.80944, "variance": None}}) + +def parse_test_data_csv(filename): + """ + Parse test data csv files for R -> Python conversion of some functions. + """ + def __str__to_tuple(line, field): + return tuple(float(s.strip()) for s in line[field].split(",")) + + with open(filename, newline="\n") as csvfile: + reader = csv.DictReader(csvfile, delimiter=",", quotechar='"') + lines = tuple(row for row in reader) + + methods = {"p": "pearson", "s": "spearman", "k": "kendall"} + return tuple({ + **line, + "x": __str__to_tuple(line, "x"), + "y": __str__to_tuple(line, "y"), + "z": __str__to_tuple(line, "z"), + "method": methods[line["method"]], + "rm": line["rm"] == "TRUE", + "result": float(line["result"]) + } for line in lines) + + +class TestPartialCorrelations(TestCase): + """Class for testing partial correlations computation functions""" + + def test_control_samples(self): + """Test that the control_samples works as expected.""" + self.assertEqual( + control_samples(control_traits, sampleslist), + ((("B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"), + ("BXD12", "BXD16", "BXD19", "BXD2"), + ("B6cC3-1", "BXD1", "BXD2")), + ((7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944), + (8.39265, 8.17443, 8.30401, 7.80944), + (7.51879, 7.77141, 7.80944)), + ((None, None, None, None, None, None), (None, None, None, None), + (None, None, None)), + (6, 4, 3))) + + def test_dictify_by_samples(self): + """ + Test that `dictify_by_samples` generates the appropriate dict + + Given: + a sequence of sequences with sample names, values and variances, as + in the output of `gn3.partial_correlations.control_samples` or + the output of `gn3.db.traits.export_informative` + When: + the sequence is passed as an argument into the + `gn3.partial_correlations.dictify_by_sample` + Then: + return a sequence of dicts with keys being the values of the sample + names, and each of who's values being sub-dicts with the keys + 'sample_name', 'value' and 'variance' whose values correspond to the + values passed in. + """ + self.assertEqual( + dictify_by_samples( + ((("B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"), + ("BXD12", "BXD16", "BXD19", "BXD2"), + ("B6cC3-1", "BXD1", "BXD2")), + ((7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944), + (8.39265, 8.17443, 8.30401, 7.80944), + (7.51879, 7.77141, 7.80944)), + ((None, None, None, None, None, None), (None, None, None, None), + (None, None, None)), + (6, 4, 3))), + dictified_control_samples) + + def test_fix_samples(self): + """ + Test that `fix_samples` returns only the common samples + + Given: + - A primary trait + - A sequence of control samples + When: + - The two arguments are passed to `fix_samples` + Then: + - Only the names of the samples present in the primary trait that + are also present in ALL the control traits are present in the + return value + - Only the values of the samples present in the primary trait that + are also present in ALL the control traits are present in the + return value + - ALL the values for ALL the control traits are present in the + return value + - Only the variances of the samples present in the primary trait + that are also present in ALL the control traits are present in the + return value + - ALL the variances for ALL the control traits are present in the + return value + - The return value is a tuple of the above items, in the following + order: + ((sample_names, ...), (primary_trait_values, ...), + (control_traits_values, ...), (primary_trait_variances, ...) + (control_traits_variances, ...)) + """ + self.assertEqual( + fix_samples( + {"B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879, + "variance": None}, + "BXD1": {"sample_name": "BXD1", "value": 7.77141, + "variance": None}, + "BXD2": {"sample_name": "BXD2", "value": 7.80944, + "variance": None}}, + dictified_control_samples), + (("BXD2",), (7.80944,), + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944, 8.39265, + 8.17443, 8.30401, 7.80944, 7.51879, 7.77141, 7.80944), + (None,), + (None, None, None, None, None, None, None, None, None, None, None, + None, None))) + + def test_find_identical_traits(self): + """ + Test `gn3.partial_correlations.find_identical_traits`. + + Given: + - the name of a primary trait + - the value of a primary trait + - a sequence of names of control traits + - a sequence of values of control traits + When: + - the arguments above are passed to the `find_identical_traits` + function + Then: + - Return ALL trait names that have the same value when up to three + decimal places are considered + """ + for primn, primv, contn, contv, expected in ( + ("pt", 12.98395, ("ct0", "ct1", "ct2"), + (0.1234, 2.3456, 3.4567), tuple()), + ("pt", 12.98395, ("ct0", "ct1", "ct2"), + (12.98354, 2.3456, 3.4567), ("pt", "ct0")), + ("pt", 12.98395, ("ct0", "ct1", "ct2", "ct3"), + (0.1234, 2.3456, 0.1233, 4.5678), ("ct0", "ct2")) + ): + with self.subTest( + primary_name=primn, primary_value=primv, + control_names=contn, control_values=contv): + self.assertEqual( + find_identical_traits(primn, primv, contn, contv), expected) + + def test_tissue_correlation_error(self): + """ + Test that `tissue_correlation` raises specific exceptions for particular + error conditions. + """ + for primary, target, method, error, error_msg in ( + ((1, 2, 3), (4, 5, 6, 7), "pearson", + AssertionError, + ( + "The lengths of the `primary_trait_values` and " + "`target_trait_values` must be equal")), + ((1, 2, 3), (4, 5, 6, 7), "spearman", + AssertionError, + ( + "The lengths of the `primary_trait_values` and " + "`target_trait_values` must be equal")), + ((1, 2, 3, 4), (5, 6, 7), "pearson", + AssertionError, + ( + "The lengths of the `primary_trait_values` and " + "`target_trait_values` must be equal")), + ((1, 2, 3, 4), (5, 6, 7), "spearman", + AssertionError, + ( + "The lengths of the `primary_trait_values` and " + "`target_trait_values` must be equal")), + ((1, 2, 3), (4, 5, 6), "nonexistentmethod", + AssertionError, + ( + "Method must be one of: pearson, spearman"))): + with self.subTest(primary=primary, target=target, method=method): + with self.assertRaises(error, msg=error_msg): + tissue_correlation(primary, target, method) + + def test_tissue_correlation(self): + """ + Test that the correct correlation values are computed for the given: + - primary trait + - target trait + - method + """ + for primary, target, method, expected in ( + ((12.34, 18.36, 42.51), (37.25, 46.25, 46.56), "pearson", + (0.6761779253, 0.5272701134)), + ((1, 2, 3, 4, 5), (5, 6, 7, 8, 7), "spearman", + (0.8207826817, 0.0885870053))): + with self.subTest(primary=primary, target=target, method=method): + self.assertEqual( + tissue_correlation(primary, target, method), expected) + + def test_good_dataset_samples_indexes(self): + """ + Test that `good_dataset_samples_indexes` returns correct indices. + """ + self.assertEqual( + good_dataset_samples_indexes( + ("a", "e", "i", "k"), + ("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l")), + (0, 4, 8, 10)) + + @skip + def test_partial_correlation_matrix(self): + """ + Test that `partial_correlation_matrix` computes the appropriate + correlation value. + """ + for sample in parse_test_data_csv( + ("tests/unit/computations/partial_correlations_test_data/" + "pcor_mat_blackbox_test.csv")): + with self.subTest( + xdata=sample["x"], ydata=sample["y"], zdata=sample["z"], + method=sample["method"], omit_nones=sample["rm"]): + self.assertEqual( + partial_correlation_matrix( + sample["x"], sample["y"], sample["z"], + method=sample["method"], omit_nones=sample["rm"]), + sample["result"]) + + @skip + def test_partial_correlation_recursive(self): + """ + Test that `partial_correlation_recursive` computes the appropriate + correlation value. + """ + for sample in parse_test_data_csv( + ("tests/unit/computations/partial_correlations_test_data/" + "pcor_rec_blackbox_test.csv")): + with self.subTest( + xdata=sample["x"], ydata=sample["y"], zdata=sample["z"], + method=sample["method"], omit_nones=sample["rm"]): + self.assertEqual( + partial_correlation_recursive( + sample["x"], sample["y"], sample["z"], + method=sample["method"], omit_nones=sample["rm"]), + sample["result"]) diff --git a/tests/unit/computations/test_wgcna.py b/tests/unit/computations/test_wgcna.py index ec81d94..5f23a86 100644 --- a/tests/unit/computations/test_wgcna.py +++ b/tests/unit/computations/test_wgcna.py @@ -10,13 +10,16 @@ from gn3.computations.wgcna import call_wgcna_script class TestWgcna(TestCase): """test class for wgcna""" + @mock.patch("gn3.computations.wgcna.process_image") @mock.patch("gn3.computations.wgcna.run_cmd") @mock.patch("gn3.computations.wgcna.compose_wgcna_cmd") @mock.patch("gn3.computations.wgcna.dump_wgcna_data") def test_call_wgcna_script(self, mock_dumping_data, mock_compose_wgcna, - mock_run_cmd): + mock_run_cmd, + mock_img, + ): """test for calling wgcna script""" # pylint: disable = line-too-long @@ -50,7 +53,7 @@ class TestWgcna(TestCase): "output": "Flagging genes and samples with too many missing values...\n ..step 1\nAllowing parallel execution with up to 3 working processes.\npickSoftThreshold: will use block size 7.\n pickSoftThreshold: calculating connectivity for given powers...\n ..working on genes 1 through 7 of 7\n Flagging genes and samples with too many missing values...\n ..step 1\n ..Working on block 1 .\n TOM calculation: adjacency..\n ..will not use multithreading.\nclustering..\n ....detecting modules..\n ....calculating module eigengenes..\n ....checking kME in modules..\n ..merging modules that are too close..\n mergeCloseModules: Merging modules whose distance is less than 0.15\n mergeCloseModules: less than two proper modules.\n ..color levels are turquoise\n ..there is nothing to merge.\n Calculating new MEs...\n" } - json_output = "{\"inputdata\":{\"trait_sample_data \":{},\"minModuleSize\":30,\"TOMtype\":\"unsigned\"},\"outputdata\":{\"eigengenes\":[],\"colors\":[]}}" + json_output = "{\"inputdata\":{\"trait_sample_data \":{},\"minModuleSize\":30,\"TOMtype\":\"unsigned\"},\"output\":{\"eigengenes\":[],\"imageLoc\":[],\"colors\":[]}}" expected_output = { @@ -61,9 +64,11 @@ class TestWgcna(TestCase): "TOMtype": "unsigned" }, - "outputdata": { + "output": { "eigengenes": [], - "colors": [] + "imageLoc": [], + "colors": [], + "image_data": "AFDSFNBSDGJJHH" } }, @@ -74,6 +79,7 @@ class TestWgcna(TestCase): with mock.patch("builtins.open", mock.mock_open(read_data=json_output)): mock_run_cmd.return_value = mock_run_cmd_results + mock_img.return_value = b"AFDSFNBSDGJJHH" results = call_wgcna_script( "Rscript/GUIX_PATH/scripts/r_file.R", request_data) diff --git a/tests/unit/db/test_traits.py b/tests/unit/db/test_traits.py index 8af8e82..4aa9389 100644 --- a/tests/unit/db/test_traits.py +++ b/tests/unit/db/test_traits.py @@ -2,6 +2,8 @@ from unittest import mock, TestCase from gn3.db.traits import ( build_trait_name, + export_trait_data, + export_informative, set_haveinfo_field, update_sample_data, retrieve_trait_info, @@ -12,6 +14,38 @@ from gn3.db.traits import ( retrieve_publish_trait_info, retrieve_probeset_trait_info) +samplelist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] +trait_data = { + "mysqlid": 36688172, + "data": { + "B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879, "variance": None, "ndata": None}, + "BXD1": {"sample_name": "BXD1", "value": 7.77141, "variance": None, "ndata": None}, + "BXD12": {"sample_name": "BXD12", "value": 8.39265, "variance": None, "ndata": None}, + "BXD16": {"sample_name": "BXD16", "value": 8.17443, "variance": None, "ndata": None}, + "BXD19": {"sample_name": "BXD19", "value": 8.30401, "variance": None, "ndata": None}, + "BXD2": {"sample_name": "BXD2", "value": 7.80944, "variance": None, "ndata": None}, + "BXD21": {"sample_name": "BXD21", "value": 8.93809, "variance": None, "ndata": None}, + "BXD24": {"sample_name": "BXD24", "value": 7.99415, "variance": None, "ndata": None}, + "BXD27": {"sample_name": "BXD27", "value": 8.12177, "variance": None, "ndata": None}, + "BXD28": {"sample_name": "BXD28", "value": 7.67688, "variance": None, "ndata": None}, + "BXD32": {"sample_name": "BXD32", "value": 7.79062, "variance": None, "ndata": None}, + "BXD39": {"sample_name": "BXD39", "value": 8.27641, "variance": None, "ndata": None}, + "BXD40": {"sample_name": "BXD40", "value": 8.18012, "variance": None, "ndata": None}, + "BXD42": {"sample_name": "BXD42", "value": 7.82433, "variance": None, "ndata": None}, + "BXD6": {"sample_name": "BXD6", "value": 8.09718, "variance": None, "ndata": None}, + "BXH14": {"sample_name": "BXH14", "value": 7.97475, "variance": None, "ndata": None}, + "BXH19": {"sample_name": "BXH19", "value": 7.67223, "variance": None, "ndata": None}, + "BXH2": {"sample_name": "BXH2", "value": 7.93622, "variance": None, "ndata": None}, + "BXH22": {"sample_name": "BXH22", "value": 7.43692, "variance": None, "ndata": None}, + "BXH4": {"sample_name": "BXH4", "value": 7.96336, "variance": None, "ndata": None}, + "BXH6": {"sample_name": "BXH6", "value": 7.75132, "variance": None, "ndata": None}, + "BXH7": {"sample_name": "BXH7", "value": 8.12927, "variance": None, "ndata": None}, + "BXH8": {"sample_name": "BXH8", "value": 6.77338, "variance": None, "ndata": None}, + "BXH9": {"sample_name": "BXH9", "value": 8.03836, "variance": None, "ndata": None}, + "C3H/HeJ": {"sample_name": "C3H/HeJ", "value": 7.42795, "variance": None, "ndata": None}, + "C57BL/6J": {"sample_name": "C57BL/6J", "value": 7.50606, "variance": None, "ndata": None}, + "DBA/2J": {"sample_name": "DBA/2J", "value": 7.72588, "variance": None, "ndata": None}}} + class TestTraitsDBFunctions(TestCase): "Test cases for traits functions" @@ -226,3 +260,145 @@ class TestTraitsDBFunctions(TestCase): with self.subTest(trait_info=trait_info, expected=expected): self.assertEqual( set_confidential_field(trait_type, trait_info), expected) + + def test_export_trait_data_dtype(self): + """ + Test `export_trait_data` with different values for the `dtype` keyword + argument + """ + for dtype, expected in [ + ["val", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["var", (None, None, None, None, None, None)], + ["N", (None, None, None, None, None, None)], + ["all", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)]]: + with self.subTest(dtype=dtype): + self.assertEqual( + export_trait_data(trait_data, samplelist, dtype=dtype), + expected) + + def test_export_trait_data_dtype_all_flags(self): + """ + Test `export_trait_data` with different values for the `dtype` keyword + argument and the different flags set up + """ + for dtype, vflag, nflag, expected in [ + ["val", False, False, + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["val", False, True, + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["val", True, False, + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["val", True, True, + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["var", False, False, (None, None, None, None, None, None)], + ["var", False, True, (None, None, None, None, None, None)], + ["var", True, False, (None, None, None, None, None, None)], + ["var", True, True, (None, None, None, None, None, None)], + ["N", False, False, (None, None, None, None, None, None)], + ["N", False, True, (None, None, None, None, None, None)], + ["N", True, False, (None, None, None, None, None, None)], + ["N", True, True, (None, None, None, None, None, None)], + ["all", False, False, + (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], + ["all", False, True, + (7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None, + 8.30401, None, 7.80944, None)], + ["all", True, False, + (7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None, + 8.30401, None, 7.80944, None)], + ["all", True, True, + (7.51879, None, None, 7.77141, None, None, 8.39265, None, None, + 8.17443, None, None, 8.30401, None, None, 7.80944, None, None)] + ]: + with self.subTest(dtype=dtype, vflag=vflag, nflag=nflag): + self.assertEqual( + export_trait_data( + trait_data, samplelist, dtype=dtype, var_exists=vflag, + n_exists=nflag), + expected) + + def test_export_informative(self): + """Test that the function exports appropriate data.""" + # pylint: disable=W0621 + for trait_data, inc_var, expected in [ + [{"data": { + "sample1": { + "sample_name": "sample1", "value": 9, "variance": None, + "ndata": 13 + }, + "sample2": { + "sample_name": "sample2", "value": 8, "variance": None, + "ndata": 13 + }, + "sample3": { + "sample_name": "sample3", "value": 7, "variance": None, + "ndata": 13 + }, + "sample4": { + "sample_name": "sample4", "value": 6, "variance": None, + "ndata": 13 + }, + }}, 0, ( + ("sample1", "sample2", "sample3", "sample4"), (9, 8, 7, 6), + (None, None, None, None))], + [{"data": { + "sample1": { + "sample_name": "sample1", "value": 9, "variance": None, + "ndata": 13 + }, + "sample2": { + "sample_name": "sample2", "value": 8, "variance": None, + "ndata": 13 + }, + "sample3": { + "sample_name": "sample3", "value": None, "variance": None, + "ndata": 13 + }, + "sample4": { + "sample_name": "sample4", "value": 6, "variance": None, + "ndata": 13 + }, + }}, 0, ( + ("sample1", "sample2", "sample4"), (9, 8, 6), + (None, None, None))], + [{"data": { + "sample1": { + "sample_name": "sample1", "value": 9, "variance": None, + "ndata": 13 + }, + "sample2": { + "sample_name": "sample2", "value": 8, "variance": None, + "ndata": 13 + }, + "sample3": { + "sample_name": "sample3", "value": 7, "variance": None, + "ndata": 13 + }, + "sample4": { + "sample_name": "sample4", "value": 6, "variance": None, + "ndata": 13 + }, + }}, True, (tuple(), tuple(), tuple())], + [{"data": { + "sample1": { + "sample_name": "sample1", "value": 9, "variance": None, + "ndata": 13 + }, + "sample2": { + "sample_name": "sample2", "value": 8, "variance": 0.657, + "ndata": 13 + }, + "sample3": { + "sample_name": "sample3", "value": 7, "variance": None, + "ndata": 13 + }, + "sample4": { + "sample_name": "sample4", "value": 6, "variance": None, + "ndata": 13 + }, + }}, 0, ( + ("sample1", "sample2", "sample3", "sample4"), (9, 8, 7, 6), + (None, 0.657, None, None))]]: + with self.subTest(trait_data=trait_data): + self.assertEqual( + export_informative(trait_data, inc_var), expected) diff --git a/tests/unit/test_authentication.py b/tests/unit/test_authentication.py new file mode 100644 index 0000000..061b684 --- /dev/null +++ b/tests/unit/test_authentication.py @@ -0,0 +1,101 @@ +"""Test cases for authentication.py""" +import json +import unittest + +from unittest import mock +from gn3.authentication import AdminRole +from gn3.authentication import DataRole +from gn3.authentication import get_highest_user_access_role +from gn3.authentication import get_user_membership + + +class TestGetUserMembership(unittest.TestCase): + """Test cases for `get_user_membership`""" + + def setUp(self): + conn = mock.MagicMock() + conn.hgetall.return_value = { + '7fa95d07-0e2d-4bc5-b47c-448fdc1260b2': ( + '{"name": "editors", ' + '"admins": ["8ad942fe-490d-453e-bd37-56f252e41604", "rand"], ' + '"members": ["8ad942fe-490d-453e-bd37-56f252e41603", ' + '"rand"], ' + '"changed_timestamp": "Oct 06 2021 06:39PM", ' + '"created_timestamp": "Oct 06 2021 06:39PM"}')} + self.conn = conn + + def test_user_is_group_member_only(self): + """Test that a user is only a group member""" + self.assertEqual( + get_user_membership( + conn=self.conn, + user_id="8ad942fe-490d-453e-bd37-56f252e41603", + group_id="7fa95d07-0e2d-4bc5-b47c-448fdc1260b2"), + {"member": True, + "admin": False}) + + def test_user_is_group_admin_only(self): + """Test that a user is a group admin only""" + self.assertEqual( + get_user_membership( + conn=self.conn, + user_id="8ad942fe-490d-453e-bd37-56f252e41604", + group_id="7fa95d07-0e2d-4bc5-b47c-448fdc1260b2"), + {"member": False, + "admin": True}) + + def test_user_is_both_group_member_and_admin(self): + """Test that a user is both an admin and member of a group""" + self.assertEqual( + get_user_membership( + conn=self.conn, + user_id="rand", + group_id="7fa95d07-0e2d-4bc5-b47c-448fdc1260b2"), + {"member": True, + "admin": True}) + + +class TestCheckUserAccessRole(unittest.TestCase): + """Test cases for `get_highest_user_access_role`""" + + @mock.patch("gn3.authentication.requests.get") + def test_edit_access(self, requests_mock): + """Test that the right access roles are set if the user has edit access""" + response = mock.PropertyMock(return_value=json.dumps( + { + 'data': ['no-access', 'view', 'edit', ], + 'metadata': ['no-access', 'view', 'edit', ], + 'admin': ['not-admin', 'edit-access', ], + } + )) + type(requests_mock.return_value).content = response + self.assertEqual( + get_highest_user_access_role( + resource_id="0196d92e1665091f202f", + user_id="8ad942fe-490d-453e-bd37"), + { + "data": DataRole.EDIT, + "metadata": DataRole.EDIT, + "admin": AdminRole.EDIT_ACCESS, + }) + + @mock.patch("gn3.authentication.requests.get") + def test_no_access(self, requests_mock): + """Test that the right access roles are set if the user has no access""" + response = mock.PropertyMock(return_value=json.dumps( + { + 'data': ['no-access', ], + 'metadata': ['no-access', ], + 'admin': ['not-admin', ], + } + )) + type(requests_mock.return_value).content = response + self.assertEqual( + get_highest_user_access_role( + resource_id="0196d92e1665091f202f", + user_id=""), + { + "data": DataRole.NO_ACCESS, + "metadata": DataRole.NO_ACCESS, + "admin": AdminRole.NOT_ADMIN, + }) diff --git a/tests/unit/test_data_helpers.py b/tests/unit/test_data_helpers.py new file mode 100644 index 0000000..39aea45 --- /dev/null +++ b/tests/unit/test_data_helpers.py @@ -0,0 +1,61 @@ +""" +Test functions in gn3.data_helpers +""" + +from unittest import TestCase + +from gn3.data_helpers import partition_all, parse_csv_line + +class TestDataHelpers(TestCase): + """ + Test functions in gn3.data_helpers + """ + + def test_partition_all(self): + """ + Test that `gn3.data_helpers.partition_all` partitions sequences as expected. + + Given: + - `num`: The number of items per partition + - `items`: A sequence of items + When: + - The arguments above are passed to the `gn3.data_helpers.partition_all` + Then: + - Return a new sequence with partitions, each of which has `num` + items in the same order as those in `items`, save for the last + partition which might have fewer items than `num`. + """ + for count, items, expected in ( + (1, [0, 1, 2, 3], ((0,), (1,), (2,), (3,))), + (3, (0, 1, 2, 3, 4, 5, 6, 7, 8, 9), + ((0, 1, 2), (3, 4, 5), (6, 7, 8), (9, ))), + (4, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], + ((0, 1, 2, 3), (4, 5, 6, 7), (8, 9))), + (13, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], + ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9), ))): + with self.subTest(n=count, items=items): + self.assertEqual(partition_all(count, items), expected) + + def test_parse_csv_line(self): + """ + Test parsing a single line from a CSV file + + Given: + - `line`: a line read from a csv file + - `delimiter`: the expected delimiter in the csv file + - `quoting`: the quoting enclosing each column in the csv file + When: + - `line` is parsed with the `parse_csv_file` with the given + parameters + Then: + - return a tuple of the columns in the CSV file, without the + delimiter and quoting + """ + for line, delimiter, quoting, expected in ( + ('"this","is","a","test"', ",", '"', ("this", "is", "a", "test")), + ('"this","is","a","test"', ",", None, ('"this"', '"is"', '"a"', '"test"'))): + with self.subTest(line=line, delimiter=delimiter, quoting=quoting): + self.assertEqual( + parse_csv_line( + line=line, delimiter=delimiter, quoting=quoting), + expected) diff --git a/tests/unit/test_heatmaps.py b/tests/unit/test_heatmaps.py index 7b66688..03fd4a6 100644 --- a/tests/unit/test_heatmaps.py +++ b/tests/unit/test_heatmaps.py @@ -4,43 +4,12 @@ from gn3.heatmaps import ( cluster_traits, get_loci_names, get_lrs_from_chr, - export_trait_data, compute_traits_order, retrieve_samples_and_values, process_traits_data_for_heatmap) from tests.unit.sample_test_data import organised_trait_1, organised_trait_2 samplelist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] -trait_data = { - "mysqlid": 36688172, - "data": { - "B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879, "variance": None, "ndata": None}, - "BXD1": {"sample_name": "BXD1", "value": 7.77141, "variance": None, "ndata": None}, - "BXD12": {"sample_name": "BXD12", "value": 8.39265, "variance": None, "ndata": None}, - "BXD16": {"sample_name": "BXD16", "value": 8.17443, "variance": None, "ndata": None}, - "BXD19": {"sample_name": "BXD19", "value": 8.30401, "variance": None, "ndata": None}, - "BXD2": {"sample_name": "BXD2", "value": 7.80944, "variance": None, "ndata": None}, - "BXD21": {"sample_name": "BXD21", "value": 8.93809, "variance": None, "ndata": None}, - "BXD24": {"sample_name": "BXD24", "value": 7.99415, "variance": None, "ndata": None}, - "BXD27": {"sample_name": "BXD27", "value": 8.12177, "variance": None, "ndata": None}, - "BXD28": {"sample_name": "BXD28", "value": 7.67688, "variance": None, "ndata": None}, - "BXD32": {"sample_name": "BXD32", "value": 7.79062, "variance": None, "ndata": None}, - "BXD39": {"sample_name": "BXD39", "value": 8.27641, "variance": None, "ndata": None}, - "BXD40": {"sample_name": "BXD40", "value": 8.18012, "variance": None, "ndata": None}, - "BXD42": {"sample_name": "BXD42", "value": 7.82433, "variance": None, "ndata": None}, - "BXD6": {"sample_name": "BXD6", "value": 8.09718, "variance": None, "ndata": None}, - "BXH14": {"sample_name": "BXH14", "value": 7.97475, "variance": None, "ndata": None}, - "BXH19": {"sample_name": "BXH19", "value": 7.67223, "variance": None, "ndata": None}, - "BXH2": {"sample_name": "BXH2", "value": 7.93622, "variance": None, "ndata": None}, - "BXH22": {"sample_name": "BXH22", "value": 7.43692, "variance": None, "ndata": None}, - "BXH4": {"sample_name": "BXH4", "value": 7.96336, "variance": None, "ndata": None}, - "BXH6": {"sample_name": "BXH6", "value": 7.75132, "variance": None, "ndata": None}, - "BXH7": {"sample_name": "BXH7", "value": 8.12927, "variance": None, "ndata": None}, - "BXH8": {"sample_name": "BXH8", "value": 6.77338, "variance": None, "ndata": None}, - "BXH9": {"sample_name": "BXH9", "value": 8.03836, "variance": None, "ndata": None}, - "C3H/HeJ": {"sample_name": "C3H/HeJ", "value": 7.42795, "variance": None, "ndata": None}, - "C57BL/6J": {"sample_name": "C57BL/6J", "value": 7.50606, "variance": None, "ndata": None}, - "DBA/2J": {"sample_name": "DBA/2J", "value": 7.72588, "variance": None, "ndata": None}}} slinked = ( (((0, 2, 0.16381088984330505), @@ -55,62 +24,6 @@ slinked = ( class TestHeatmap(TestCase): """Class for testing heatmap computation functions""" - def test_export_trait_data_dtype(self): - """ - Test `export_trait_data` with different values for the `dtype` keyword - argument - """ - for dtype, expected in [ - ["val", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["var", (None, None, None, None, None, None)], - ["N", (None, None, None, None, None, None)], - ["all", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)]]: - with self.subTest(dtype=dtype): - self.assertEqual( - export_trait_data(trait_data, samplelist, dtype=dtype), - expected) - - def test_export_trait_data_dtype_all_flags(self): - """ - Test `export_trait_data` with different values for the `dtype` keyword - argument and the different flags set up - """ - for dtype, vflag, nflag, expected in [ - ["val", False, False, - (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["val", False, True, - (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["val", True, False, - (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["val", True, True, - (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["var", False, False, (None, None, None, None, None, None)], - ["var", False, True, (None, None, None, None, None, None)], - ["var", True, False, (None, None, None, None, None, None)], - ["var", True, True, (None, None, None, None, None, None)], - ["N", False, False, (None, None, None, None, None, None)], - ["N", False, True, (None, None, None, None, None, None)], - ["N", True, False, (None, None, None, None, None, None)], - ["N", True, True, (None, None, None, None, None, None)], - ["all", False, False, - (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)], - ["all", False, True, - (7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None, - 8.30401, None, 7.80944, None)], - ["all", True, False, - (7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None, - 8.30401, None, 7.80944, None)], - ["all", True, True, - (7.51879, None, None, 7.77141, None, None, 8.39265, None, None, - 8.17443, None, None, 8.30401, None, None, 7.80944, None, None)] - ]: - with self.subTest(dtype=dtype, vflag=vflag, nflag=nflag): - self.assertEqual( - export_trait_data( - trait_data, samplelist, dtype=dtype, var_exists=vflag, - n_exists=nflag), - expected) - def test_cluster_traits(self): """ Test that the clustering is working as expected. |