From 0bb51bd78479c05839d7b7f9f878db4b5616cfda Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Fri, 29 Oct 2021 06:34:19 +0300 Subject: Implement `tissue_correlation` function Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: New function (tissue_correlation) * tests/unit/test_partial_correlations.py -> tests/unit/computations/test_partial_correlations.py: Move module. Implement tests for new function Migrate the `cal_tissue_corr` function embedded in the `web.webqtl.correlation.correlationFunction.batchCalTissueCorr` function in GN1 and implement tests to ensure it works correctly. --- .../unit/computations/test_partial_correlations.py | 258 +++++++++++++++++++++ 1 file changed, 258 insertions(+) create mode 100644 tests/unit/computations/test_partial_correlations.py (limited to 'tests/unit/computations') diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py new file mode 100644 index 0000000..7ff8b80 --- /dev/null +++ b/tests/unit/computations/test_partial_correlations.py @@ -0,0 +1,258 @@ +"""Module contains tests for gn3.partial_correlations""" + +from unittest import TestCase +from gn3.computations.partial_correlations import * + +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}}) + +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", + (0.6761779252651052, 0.5272701133657985)), + ((1, 2, 3, 4, 5), (5, 6, 7, 8, 7), "spearman", + (0.8207826816681233, 0.08858700531354381)) + ): + with self.subTest(primary=primary, target=target, method=method): + self.assertEqual( + tissue_correlation(primary, target, method), expected) -- cgit v1.2.3 From eeb0d6d7ee1b65f1cbe9c32a9f9ee9237189a113 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Fri, 29 Oct 2021 07:06:04 +0300 Subject: Fix some linting errors Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi --- tests/unit/computations/test_partial_correlations.py | 17 +++++++++++------ 1 file changed, 11 insertions(+), 6 deletions(-) (limited to 'tests/unit/computations') diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 7ff8b80..ac5eb20 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -1,7 +1,12 @@ """Module contains tests for gn3.partial_correlations""" from unittest import TestCase -from gn3.computations.partial_correlations import * +from gn3.computations.partial_correlations import ( + fix_samples, + control_samples, + dictify_by_samples, + tissue_correlation, + find_identical_traits) sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] control_traits = ( @@ -212,27 +217,27 @@ class TestPartialCorrelations(TestCase): error conditions. """ for primary, target, method, error, error_msg in ( - ((1,2,3), (4,5,6,7), "pearson", + ((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", + ((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", + ((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", + ((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", + ((1, 2, 3), (4, 5, 6), "nonexistentmethod", AssertionError, ( "Method must be one of: pearson, spearman"))): -- cgit v1.2.3 From 116006464a61edcfa354b729ea40a7af28c08d61 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Fri, 29 Oct 2021 08:38:48 +0300 Subject: Specify ten (10) decimal places Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: specify 10 decimal places * tests/unit/computations/test_partial_correlations.py: update examples Slight differences in python implementations, possibly hardware and operating systems could cause the value of float (double) values to be different in the less significant parts of the decimal places. This commit limits the usable part of the decimals to the first 10 decimal places for now. --- gn3/computations/partial_correlations.py | 4 +++- tests/unit/computations/test_partial_correlations.py | 5 ++--- 2 files changed, 5 insertions(+), 4 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index fce6ad2..8a00931 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -148,7 +148,9 @@ def tissue_correlation( assert method in method_fns.keys(), ( "Method must be one of: {}".format(",".join(method_fns.keys()))) - return method_fns[method](primary_trait_values, target_trait_values) + return tuple( + round(n, 10) for n in + method_fns[method](primary_trait_values, target_trait_values)) def batch_computed_tissue_correlation( primary_trait_values: Tuple[float, ...], target_traits_dict: dict, diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index ac5eb20..c4ec79a 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -254,10 +254,9 @@ class TestPartialCorrelations(TestCase): """ for primary, target, method, expected in ( ((12.34, 18.36, 42.51), (37.25, 46.25, 46.56), "pearson", - (0.6761779252651052, 0.5272701133657985)), + (0.6761779253, 0.5272701134)), ((1, 2, 3, 4, 5), (5, 6, 7, 8, 7), "spearman", - (0.8207826816681233, 0.08858700531354381)) - ): + (0.8207826817, 0.0885870053))): with self.subTest(primary=primary, target=target, method=method): self.assertEqual( tissue_correlation(primary, target, method), expected) -- cgit v1.2.3 From 37cf87e94a44ba2ab26a8e458e0c5a90fe5ecc7a Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Mon, 1 Nov 2021 08:18:48 +0300 Subject: Retrieve indices of the selected samples Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: New function (good_dataset_samples_indexes). * tests/unit/computations/test_partial_correlations.py: Tests for new function (good_dataset_samples_indexes) Get the indices of the selected samples. This is a partial migration of the `web.webqtl.correlation.PartialCorrDBPage.getPartialCorrelationsFast` function in GN1. --- gn3/computations/partial_correlations.py | 15 +++++++++++++++ tests/unit/computations/test_partial_correlations.py | 13 ++++++++++++- 2 files changed, 27 insertions(+), 1 deletion(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 151143a..ba4de9e 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -177,3 +177,18 @@ def correlations_of_all_tissue_traits( primary_trait_values = tuple(primary_trait_symbol_value_dict.values())[0] return batch_computed_tissue_correlation( primary_trait_values, symbol_value_dict, method) + +def good_dataset_samples_indexes( + samples: Tuple[str, ...], + samples_from_file: Tuple[str, ...]) -> Tuple[int, ...]: + """ + Return the indexes of the items in `samples_from_files` that are also found + in `samples`. + + This is a partial migration of the + `web.webqtl.correlation.PartialCorrDBPage.getPartialCorrelationsFast` + function in GeneNetwork1. + """ + return tuple(sorted( + samples_from_file.index(good) for good in + set(samples).intersection(set(samples_from_file)))) diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index c4ec79a..f7217a9 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -6,7 +6,8 @@ from gn3.computations.partial_correlations import ( control_samples, dictify_by_samples, tissue_correlation, - find_identical_traits) + find_identical_traits, + good_dataset_samples_indexes) sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] control_traits = ( @@ -260,3 +261,13 @@ class TestPartialCorrelations(TestCase): 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)) -- cgit v1.2.3 From 32e6d788ac5b6fa8daf4c26b2ad7bca32d71d828 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Thu, 4 Nov 2021 08:51:50 +0300 Subject: Create blackbox tests for some functions migrated from R Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: new stub functions (partial_correlation_matrix, partial_correlation_recursive) * tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv: blackbox sample data and results for variance-covariance matrix method * tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv: blackbox sample data and results for recursive method * tests/unit/computations/test_partial_correlations.py: Tests for new function Provide some blackbox testing sample data for checking the operation of the functions migrated from R. --- gn3/computations/partial_correlations.py | 30 ++++++ .../pcor_mat_blackbox_test.csv | 101 +++++++++++++++++++++ .../pcor_rec_blackbox_test.csv | 101 +++++++++++++++++++++ .../unit/computations/test_partial_correlations.py | 61 ++++++++++++- 4 files changed, 292 insertions(+), 1 deletion(-) create mode 100644 tests/unit/computations/partial_correlations_test_data/pcor_mat_blackbox_test.csv create mode 100644 tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index fb372a9..07dc16d 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -257,3 +257,33 @@ def compute_partial_correlations_fast(# pylint: disable=[R0913, R0914] (fetched_correlations[corr[0]],) if correlation_type == "literature" else fetched_correlations[corr[0]][0:2]) for idx, corr in enumerate(all_correlations)) + +def partial_correlation_matrix( + xdata: Tuple[float, ...], ydata: Tuple[float, ...], + zdata: Tuple[float, ...], method: str = "pearsons", + omit_nones: bool = True) -> float: + """ + Computes the partial correlation coefficient using the + 'variance-covariance matrix' method + + This is a partial migration of the + `web.webqtl.correlation.correlationFunction.determinPartialsByR` function in + GeneNetwork1, specifically the `pcor.mat` function written in the R + programming language. + """ + return 0 + +def partial_correlation_recursive( + xdata: Tuple[float, ...], ydata: Tuple[float, ...], + zdata: Tuple[float, ...], method: str = "pearsons", + omit_nones: bool = True) -> float: + """ + Computes the partial correlation coefficient using the 'recursive formula' + method + + This is a partial migration of the + `web.webqtl.correlation.correlationFunction.determinPartialsByR` function in + GeneNetwork1, specifically the `pcor.rec` function written in the R + programming language. + """ + return 0 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, 18.5637861024588, 96.5889988467097, 36.156284250319, 35.1589790545404, -73.1023930944502, -50.7484216243029, 41.8345319107175, -47.8776978328824","s",TRUE,-0.0325789017360908 +"pcor.mat",18,"64.013504376635, 53.1150240916759, -77.8307237662375, -33.1533540505916, -13.6034480296075, 93.2804300449789, -46.3470680173486, 17.427362408489, -66.663983091712, 4.23776390962303, 77.7521491982043, -3.10332304798067, -61.5989458281547, -13.5284000542015, 7.71856023930013, 89.0885920263827, -35.3556916583329, -95.9261478390545","-35.6941626407206, 41.877265740186, 69.6430462878197, 64.2008605413139, -59.4343301840127, 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47.9975900612772, 36.5392371080816, -51.0348361451179, 7.82818463630974, -6.9301129784435, -75.5731589626521, 47.0917036756873, -58.8109106291085, 33.4785438142717","54.0308193303645, 41.3668432738632, 98.2857145369053, -14.9101806804538, 30.7341996114701, 92.3570320941508, -35.8356348704547, -91.0546428058296, 77.7767921797931, 13.7820704840124","-65.3565419837832, -24.2730437777936, 13.4862332604825, -97.8464429732412, 91.0171907860786, -52.4954450316727, -31.7320866975933, 33.8117491919547, 49.1156910546124, -42.7486607804894","p",FALSE,0.109506018207148 diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index f7217a9..c5c35d1 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -1,5 +1,6 @@ """Module contains tests for gn3.partial_correlations""" +import csv from unittest import TestCase from gn3.computations.partial_correlations import ( fix_samples, @@ -7,7 +8,9 @@ from gn3.computations.partial_correlations import ( dictify_by_samples, tissue_correlation, find_identical_traits, - good_dataset_samples_indexes) + partial_correlation_matrix, + good_dataset_samples_indexes, + partial_correlation_recursive) sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] control_traits = ( @@ -90,6 +93,28 @@ dictified_control_samples = ( "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""" @@ -271,3 +296,37 @@ class TestPartialCorrelations(TestCase): ("a", "e", "i", "k"), ("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l")), (0, 4, 8, 10)) + + 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"]) + + 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"]) -- cgit v1.2.3 From 0357f5c5e6eeb146eb259337019c87079363a256 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Thu, 4 Nov 2021 12:38:27 +0300 Subject: Implement `build_data_frame` Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: new function (`build_data_frame`) * tests/unit/computations/test_partial_correlations.py: Add tests for new function Add a new function to build a pandas DataFrame object from the provided values: - x: a vector of floats (represented with a tuple of floats) - y: a vector of floats (represented with a tuple of floats) - z: a vector OR matrix of floats (represented with a tuple of floats or a tuple of tuples of floats) --- gn3/computations/partial_correlations.py | 16 ++++++++++++++++ .../unit/computations/test_partial_correlations.py | 22 ++++++++++++++++++++++ 2 files changed, 38 insertions(+) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 07dc16d..ffdf0c5 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -10,6 +10,8 @@ from typing import Any, Tuple, Sequence from scipy.stats import pearsonr, spearmanr from gn3.settings import TEXTDIR +import pandas + from gn3.data_helpers import parse_csv_line def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]): @@ -258,6 +260,20 @@ def compute_partial_correlations_fast(# pylint: disable=[R0913, R0914] else fetched_correlations[corr[0]][0:2]) for idx, corr in enumerate(all_correlations)) +def build_data_frame( + xdata: Tuple[float, ...], ydata: Tuple[float, ...], + zdata: Union[ + Tuple[float, ...], + Tuple[Tuple[float, ...], ...]]) -> pandas.DataFrame: + """ + Build a pandas DataFrame object from xdata, ydata and zdata + """ + x_y_df = pandas.DataFrame({"x": xdata, "y": ydata}) + if isinstance(zdata[0], float): + return x_y_df.join(pandas.DataFrame({"z": zdata})) + return x_y_df.join(pandas.DataFrame( + {"z{}".format(i): val for i, val in enumerate(row)} for row in zdata)) + def partial_correlation_matrix( xdata: Tuple[float, ...], ydata: Tuple[float, ...], zdata: Tuple[float, ...], method: str = "pearsons", diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index c5c35d1..b22bc62 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -2,9 +2,12 @@ import csv from unittest import TestCase + +import pandas from gn3.computations.partial_correlations import ( fix_samples, control_samples, + build_data_frame, dictify_by_samples, tissue_correlation, find_identical_traits, @@ -297,6 +300,25 @@ class TestPartialCorrelations(TestCase): ("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l")), (0, 4, 8, 10)) + def test_build_data_frame(self): + """ + Check that the function builds the correct data frame. + """ + for xdata, ydata, zdata, expected in ( + ((0.1, 1.1, 2.1), (2.1, 3.1, 4.1), (5.1, 6.1 ,7.1), + pandas.DataFrame({ + "x": (0.1, 1.1, 2.1), "y": (2.1, 3.1, 4.1), + "z": (5.1, 6.1 ,7.1)})), + ((0.1, 1.1, 2.1), (2.1, 3.1, 4.1), + ((5.1, 6.1 ,7.1), (5.2, 6.2, 7.2), (5.3, 6.3, 7.3)), + pandas.DataFrame({ + "x": (0.1, 1.1, 2.1), "y": (2.1, 3.1, 4.1), + "z0": (5.1, 5.2 ,5.3), "z1": (6.1, 6.2 ,6.3), + "z2": (7.1, 7.2 ,7.3)}))): + with self.subTest(xdata=xdata, ydata=ydata, zdata=zdata): + self.assertTrue( + build_data_frame(xdata, ydata, zdata).equals(expected)) + def test_partial_correlation_matrix(self): """ Test that `partial_correlation_matrix` computes the appropriate -- cgit v1.2.3 From 9647226ea4c85449581df713c2bb583aeed6940f Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Thu, 4 Nov 2021 12:43:28 +0300 Subject: Partially implement `partial_correlation_recursive` Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: Implement one path for the `gn3.computations.partial_correlations.partial_correlation_recursive` function. * gn3/settings.py: Add a setting for how many decimal places to round to * tests/unit/computations/test_partial_correlations.py: Update test to take the number of decimal places into consideration Implement a single path (where the z value is a vector and not a matrix) for the `partial_correlation_recursive` function. --- gn3/computations/partial_correlations.py | 41 ++++++++++++++++++---- gn3/settings.py | 2 ++ .../unit/computations/test_partial_correlations.py | 4 ++- 3 files changed, 39 insertions(+), 8 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index ffdf0c5..bd127a7 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -5,13 +5,14 @@ It is an attempt to migrate over the partial correlations feature from GeneNetwork1. """ +import math from functools import reduce -from typing import Any, Tuple, Sequence +from typing import Any, Tuple, Union, Sequence from scipy.stats import pearsonr, spearmanr -from gn3.settings import TEXTDIR import pandas +from gn3.settings import TEXTDIR, ROUND_TO from gn3.data_helpers import parse_csv_line def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]): @@ -276,8 +277,8 @@ def build_data_frame( def partial_correlation_matrix( xdata: Tuple[float, ...], ydata: Tuple[float, ...], - zdata: Tuple[float, ...], method: str = "pearsons", - omit_nones: bool = True) -> float: + zdata: Union[Tuple[float, ...], Tuple[Tuple[float, ...], ...]], + method: str = "pearson", omit_nones: bool = True) -> float: """ Computes the partial correlation coefficient using the 'variance-covariance matrix' method @@ -291,8 +292,8 @@ def partial_correlation_matrix( def partial_correlation_recursive( xdata: Tuple[float, ...], ydata: Tuple[float, ...], - zdata: Tuple[float, ...], method: str = "pearsons", - omit_nones: bool = True) -> float: + zdata: Union[Tuple[float, ...], Tuple[Tuple[float, ...], ...]], + method: str = "pearson", omit_nones: bool = True) -> float: """ Computes the partial correlation coefficient using the 'recursive formula' method @@ -302,4 +303,30 @@ def partial_correlation_recursive( GeneNetwork1, specifically the `pcor.rec` function written in the R programming language. """ - return 0 + assert method in ("pearson", "spearman", "kendall") + data = ( + build_data_frame(xdata, ydata, zdata).dropna(axis=0) + if omit_nones else + build_data_frame(xdata, ydata, zdata)) + + if data.shape[1] == 3: # z is a vector, not matrix + fields = { + "rxy": ("x", "y"), + "rxz": ("x", "z"), + "ryz": ("y", "z")} + tdata = { + corr_type: pandas.DataFrame( + {cols[0]: data[cols[0]], + cols[1]: data[cols[1]]}).dropna(axis=0) + for corr_type, cols in fields.items() + } + corrs = { + corr_type: tdata[corr_type][cols[0]].corr( + tdata[corr_type][cols[1]], method=method) + for corr_type, cols in fields.items() + } + return round(( + (corrs["rxy"] - corrs["rxz"] * corrs["ryz"]) / + (math.sqrt(1 - corrs["rxz"]**2) * + math.sqrt(1 - corrs["ryz"]**2))), ROUND_TO) + return round(0, ROUND_TO) diff --git a/gn3/settings.py b/gn3/settings.py index 57c63df..eaf8f23 100644 --- a/gn3/settings.py +++ b/gn3/settings.py @@ -53,3 +53,5 @@ CORS_HEADERS = [ GNSHARE = os.environ.get("GNSHARE", "/gnshare/gn/") TEXTDIR = f"{GNSHARE}/web/ProbeSetFreeze_DataMatrix" + +ROUND_TO = 10 diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index b22bc62..981801a 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -4,6 +4,8 @@ import csv from unittest import TestCase import pandas + +from gn3.settings import ROUND_TO from gn3.computations.partial_correlations import ( fix_samples, control_samples, @@ -115,7 +117,7 @@ def parse_test_data_csv(filename): "z": __str__to_tuple(line, "z"), "method": methods[line["method"]], "rm": line["rm"] == "TRUE", - "result": float(line["result"]) + "result": round(float(line["result"]), ROUND_TO) } for line in lines) class TestPartialCorrelations(TestCase): -- cgit v1.2.3 From b38be1a60ea04e3087d36ff68e7b047922295d4e Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Tue, 9 Nov 2021 10:08:46 +0300 Subject: Update test data: have both vectors and matrices Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * Delete the older test data that was only testing with `z` being a vector and replace it with data that has `z` being a vector or matrix from data item to data item. --- .../pcor_rec_blackbox_test.csv | 101 ---------------- .../pcor_rec_blackbox_test.txt | 127 +++++++++++++++++++++ 2 files changed, 127 insertions(+), 101 deletions(-) delete mode 100644 tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv create mode 100644 tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt (limited to 'tests/unit/computations') diff --git a/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv b/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv deleted file mode 100644 index a1558a0..0000000 --- a/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.csv +++ /dev/null @@ -1,101 +0,0 @@ -"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, 18.5637861024588, 96.5889988467097, 36.156284250319, 35.1589790545404, -73.1023930944502, -50.7484216243029, 41.8345319107175, -47.8776978328824","s",TRUE,-0.0325789017360908 -"pcor.mat",18,"64.013504376635, 53.1150240916759, 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96.9413920771331, 47.8810616768897, -0.438442826271057, 3.20979873649776, 20.6230421550572, 89.096216019243, -82.9677095636725, 91.9871860649437, 74.0136182866991, 38.2246119901538, -10.429418226704, 89.3207651097327, -13.5560743510723, 4.01417766697705, -34.4030613079667, 95.2031007036567, -43.0174002423882 +input.z.6: 80.8942574542016, -39.6212201565504, 14.2572369426489, -78.1328707933426, -96.1618753615767, 61.9455046951771, -42.8125618491322, 45.2630438376218, -26.2891847174615, -37.7531661652029, 71.7649383936077, -76.2287222314626, 86.0407523345202, 83.4333196282387, 11.858429107815, 90.0938509497792, 27.1023083478212 +input.z.7: -68.578722840175, -72.2220734227449, 83.0359090585262, 44.5527241565287, 19.0210536122322, 19.7943818289787, 42.1044544316828, -10.6518527492881, 85.2387520018965, -89.5295495167375, -14.2881830222905, 15.0138720404357, 73.6910053994507, 95.9490245208144, 29.4783721212298, -32.2806132957339, 98.4265907201916 +input.z.8: -63.3846850600094, -75.9456290863454, 98.109992640093, -8.30751904286444, -65.3464913833886, 57.9990320838988, -97.9716447182, 48.3666017185897, -11.2887284718454, 38.4293566923589, -4.15021106600761, -6.2844387255609, -20.7505342550576, -56.9003260694444, 96.397353708744, -90.6195733696222, -40.7526909839362 +input.z.9: 81.5076497849077, 13.3879841770977, -66.9347247574478, -4.78587108664215, 30.7318323291838, -55.0735270604491, 9.40470518544316, 66.8840528000146, -31.3702027779073, 69.8431192431599, -86.8119182996452, 37.1748886071146, -39.0971344895661, -6.33791824802756, -4.74258312024176, -37.5578073319048, 16.0260049626231 +------------------------------------------------------------ +function_name: pcor.rec +count: 15 +x: 13.3217854890972, 3.74524784274399, 42.3860765993595, 70.1574267819524, -36.6772301495075, 43.096883688122, 11.656632553786, 49.6097341645509, 35.055069392547, -34.170615952462, -12.3891159426421, 95.595167670399, 27.9552156571299, 60.3556469082832, -64.5174876786768 +y: 93.0693128611892, 94.2700367886573, -59.7466928884387, 75.3644049633294, 38.714852463454, -25.7440742570907, -26.9153070170432, -39.7653248626739, -2.73380884900689, -51.2801296077669, 55.7282803580165, 9.4015384092927, -56.5411465242505, -14.9695897940546, -58.2891712896526 +z: 48.0578206945211, -49.0533413831145, -62.5287163536996, 77.8333532158285, 70.9992234129459, -80.4808055050671, 63.4501236490905, 1.48282377049327, -52.8766040224582, -60.6905648484826, 75.8240396622568, -26.8130346667022, -66.6958931367844, -14.8776702582836, 57.7621683478355 +method: p +rm: FALSE +result: 0.223987436768198 +------------------------------------------------------------ -- cgit v1.2.3 From 89691df0d7ba096fb7a154aca3adf40f8dfaa8ae Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Tue, 9 Nov 2021 10:16:50 +0300 Subject: Implement remaining part of `partial_correlation_recursive` function Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * gn3/computations/partial_correlations.py: implement remaining portion of `partial_correlation_recursive` function. * tests/unit/computations/test_partial_correlations.py: add parsing for new data format and update tests --- gn3/computations/partial_correlations.py | 27 ++++++- .../unit/computations/test_partial_correlations.py | 82 +++++++++++++++++++++- 2 files changed, 105 insertions(+), 4 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 9d73197..07a67be 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -332,4 +332,29 @@ def partial_correlation_recursive( (corrs["rxy"] - corrs["rxz"] * corrs["ryz"]) / (math.sqrt(1 - corrs["rxz"]**2) * math.sqrt(1 - corrs["ryz"]**2))), ROUND_TO) - return round(0, ROUND_TO) + + remaining_cols = [ + colname for colname, series in data.items() + if colname not in ("x", "y", "z0") + ] + + new_xdata = tuple(data["x"]) + new_ydata = tuple(data["y"]) + zc = tuple( + tuple(row_series[1]) + for row_series in data[remaining_cols].iterrows()) + + rxy_zc = partial_correlation_recursive( + new_xdata, new_ydata, zc, method=method, + omit_nones=omit_nones) + rxz0_zc = partial_correlation_recursive( + new_xdata, tuple(data["z0"]), zc, method=method, + omit_nones=omit_nones) + ryz0_zc = partial_correlation_recursive( + new_ydata, tuple(data["z0"]), zc, method=method, + omit_nones=omit_nones) + + return round( + ((rxy_zc - rxz0_zc * ryz0_zc) /( + math.sqrt(1 - rxz0_zc**2) * math.sqrt(1 - ryz0_zc**2))), + ROUND_TO) diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 981801a..28c9548 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -6,6 +6,8 @@ from unittest import TestCase import pandas from gn3.settings import ROUND_TO +from gn3.function_helpers import compose +from gn3.data_helpers import partition_by from gn3.computations.partial_correlations import ( fix_samples, control_samples, @@ -120,6 +122,80 @@ def parse_test_data_csv(filename): "result": round(float(line["result"]), ROUND_TO) } for line in lines) +def parse_method(key_value): + """Parse the partial correlation method""" + key, value = key_value + if key == "method": + methods_dict = {"p": "pearson", "k": "kendall", "s": "spearman"} + return (key, methods_dict[value]) + return key_value + +def parse_count(key_value): + """Parse the value of count into an integer""" + key, value = key_value + if key == "count": + return (key, int(value)) + return key_value + +def parse_xyz(key_value): + """Parse the values of x, y, and z* items into sequences of floats""" + key, value = key_value + if (key in ("x", "y", "z")) or key.startswith("input.z"): + return ( + key.replace("input", "").replace(".", ""), + tuple(float(val.strip("\n\t ")) for val in value.split(","))) + return key_value + +def parse_rm(key_value): + """Parse the rm value into a python True/False value.""" + key, value = key_value + if key == "rm": + return (key, value == "TRUE") + return key_value + +def parse_result(key_value): + """Parse the result into a float value.""" + key, value = key_value + if key == "result": + return (key, float(value)) + return key_value + +parser_function = compose( + parse_result, + parse_rm, + parse_xyz, + parse_count, + parse_method, + lambda k_v: tuple(item.strip("\n\t ") for item in k_v), + lambda s: s.split(":")) + +def parse_input_line(line): + return tuple( + parser_function(item) for item in line if not item.startswith("------")) + +def merge_z(item): + without_z = { + key: val for key, val in item.items() if not key.startswith("z")} + return { + **without_z, + "z": item.get( + "z", + tuple(val for key, val in item.items() if key.startswith("z")))} + +def parse_input(lines): + return tuple( + merge_z(dict(item)) + for item in (parse_input_line(line) for line in lines) + if len(item) != 0) + +def parse_test_data(filename): + with open("pcor_rec_blackbox_attempt.txt", newline="\n") as fl: + input_lines = partition_by( + lambda s: s.startswith("------"), + (line.strip("\n\t ") for line in fl.readlines())) + + return parse_input(input_lines) + class TestPartialCorrelations(TestCase): """Class for testing partial correlations computation functions""" @@ -343,9 +419,9 @@ class TestPartialCorrelations(TestCase): Test that `partial_correlation_recursive` computes the appropriate correlation value. """ - for sample in parse_test_data_csv( + for sample in parse_test_data( ("tests/unit/computations/partial_correlations_test_data/" - "pcor_rec_blackbox_test.csv")): + "pcor_rec_blackbox_test.txt")): with self.subTest( xdata=sample["x"], ydata=sample["y"], zdata=sample["z"], method=sample["method"], omit_nones=sample["rm"]): @@ -353,4 +429,4 @@ class TestPartialCorrelations(TestCase): partial_correlation_recursive( sample["x"], sample["y"], sample["z"], method=sample["method"], omit_nones=sample["rm"]), - sample["result"]) + round(sample["result"], ROUND_TO)) -- cgit v1.2.3 From d895eea22ab908c11f4ebb77f99518367879b1f6 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Fri, 12 Nov 2021 03:56:01 +0300 Subject: Pass in parser function for flexibility Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * To improve the usefulness of already existing code, provide the parser function as an argument to the `parse_input_line` function. This was found to be useful when writing code to compare the `pcor.test` function in GN1 and the `pingouin.partial_corr` function. The format of the data generated when getting results for the `pcor.test` function shared a lot with that of the `pcor.rec` function, but it was different in a few, places, and the differences were non-trivial, needing different parsing processes. In such a case, it was found necessary to just pass in the function to do the actual parsing, rather than create code with the same form as the existing one, save for the function being called. --- tests/unit/computations/test_partial_correlations.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) (limited to 'tests/unit/computations') diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index e702f6e..7cf8cd8 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -161,7 +161,7 @@ def parse_result(key_value): return (key, float(value)) return key_value -parser_function = compose( +parse_for_rec = compose( parse_result, parse_rm, parse_xyz, @@ -170,7 +170,7 @@ parser_function = compose( lambda k_v: tuple(item.strip("\n\t ") for item in k_v), lambda s: s.split(":")) -def parse_input_line(line): +def parse_input_line(line, parser_function): return tuple( parser_function(item) for item in line if not item.startswith("------")) @@ -183,10 +183,10 @@ def merge_z(item): "z", tuple(val for key, val in item.items() if key.startswith("z")))} -def parse_input(lines): +def parse_input(lines, parser_function): return tuple( merge_z(dict(item)) - for item in (parse_input_line(line) for line in lines) + for item in (parse_input_line(line, parser_function) for line in lines) if len(item) != 0) def parse_test_data(filename): @@ -195,7 +195,7 @@ def parse_test_data(filename): lambda s: s.startswith("------"), (line.strip("\n\t ") for line in fl.readlines())) - return parse_input(input_lines) + return parse_input(input_lines, parse_for_rec) class TestPartialCorrelations(TestCase): """Class for testing partial correlations computation functions""" -- cgit v1.2.3 From 63b70daaffd2c3e095fde3ed59a07bb9ee894c4f Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Mon, 15 Nov 2021 07:06:58 +0300 Subject: Fix the columns in built data frame Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * When the z value is a Sequence of sequences of values, each of the internal sequences should form a column of its own, and not a row, as it was originally set up to do. --- gn3/computations/partial_correlations.py | 2 +- tests/unit/computations/test_partial_correlations.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 07a67be..156e74c 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -273,7 +273,7 @@ def build_data_frame( if isinstance(zdata[0], float): return x_y_df.join(pandas.DataFrame({"z": zdata})) interm_df = x_y_df.join(pandas.DataFrame( - {"z{}".format(i): val for i, val in enumerate(row)} for row in zdata)) + {"z{}".format(i): val for i, val in enumerate(zdata)})) if interm_df.shape[1] == 3: return interm_df.rename(columns={"z0": "z"}) return interm_df diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 7cf8cd8..f25145c 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -392,8 +392,8 @@ class TestPartialCorrelations(TestCase): ((5.1, 6.1 ,7.1), (5.2, 6.2, 7.2), (5.3, 6.3, 7.3)), pandas.DataFrame({ "x": (0.1, 1.1, 2.1), "y": (2.1, 3.1, 4.1), - "z0": (5.1, 5.2 ,5.3), "z1": (6.1, 6.2 ,6.3), - "z2": (7.1, 7.2 ,7.3)}))): + "z0": (5.1, 6.1, 7.1), "z1": (5.2, 6.2 ,7.2), + "z2": (5.3, 6.3 ,7.3)}))): with self.subTest(xdata=xdata, ydata=ydata, zdata=zdata): self.assertTrue( build_data_frame(xdata, ydata, zdata).equals(expected)) -- cgit v1.2.3 From 29fc003070b45f61e7ab1048a818201b5beb9298 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Mon, 15 Nov 2021 07:58:10 +0300 Subject: Fix bugs in recursive partial correlations * gn3/computations/partial_correlations.py: Remove rounding. Fix computation of remaining covariates * tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt: reduce the number of covariates to between one (1) and three (3) * tests/unit/computations/test_partial_correlations.py: fix some minor bugs It turns out that the computation complexity increases exponentially, with the number of covariates. Therefore, to get a somewhat sensible test time, while retaining a large-ish number of tests, this commit reduces the number of covariates to between 1 and 3. --- gn3/computations/partial_correlations.py | 16 +- .../pcor_rec_blackbox_test.txt | 1034 ++++++++++++++++++-- .../unit/computations/test_partial_correlations.py | 17 +- 3 files changed, 974 insertions(+), 93 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 156e74c..519dce9 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -12,7 +12,7 @@ from scipy.stats import pearsonr, spearmanr import pandas -from gn3.settings import TEXTDIR, ROUND_TO +from gn3.settings import TEXTDIR from gn3.data_helpers import parse_csv_line def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]): @@ -328,10 +328,10 @@ def partial_correlation_recursive( tdata[corr_type][cols[1]], method=method) for corr_type, cols in fields.items() } - return round(( + return ( (corrs["rxy"] - corrs["rxz"] * corrs["ryz"]) / (math.sqrt(1 - corrs["rxz"]**2) * - math.sqrt(1 - corrs["ryz"]**2))), ROUND_TO) + math.sqrt(1 - corrs["ryz"]**2))) remaining_cols = [ colname for colname, series in data.items() @@ -340,9 +340,7 @@ def partial_correlation_recursive( new_xdata = tuple(data["x"]) new_ydata = tuple(data["y"]) - zc = tuple( - tuple(row_series[1]) - for row_series in data[remaining_cols].iterrows()) + zc = tuple(tuple(data[colname]) for colname in data[remaining_cols].columns) rxy_zc = partial_correlation_recursive( new_xdata, new_ydata, zc, method=method, @@ -354,7 +352,5 @@ def partial_correlation_recursive( new_ydata, tuple(data["z0"]), zc, method=method, omit_nones=omit_nones) - return round( - ((rxy_zc - rxz0_zc * ryz0_zc) /( - math.sqrt(1 - rxz0_zc**2) * math.sqrt(1 - ryz0_zc**2))), - ROUND_TO) + return ((rxy_zc - rxz0_zc * ryz0_zc) /( + math.sqrt(1 - rxz0_zc**2) * math.sqrt(1 - ryz0_zc**2))) diff --git a/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt b/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt index 4b9f68a..6254902 100644 --- a/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt +++ b/tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt @@ -1,127 +1,1009 @@ ------------------------------------------------------------ function_name: pcor.rec count: 18 -x: 39.43254314363, 71.7503248248249, -25.9237891994417, -71.4318438898772, 5.86411766707897, 20.5873795319349, -55.2685840055346, -8.46728710457683, -92.6864624489099, -93.9637628849596, 63.8542262371629, -57.1248637512326, -57.3486962355673, -15.5142558738589, -81.5054637845606, -52.3766598664224, 64.1838387586176, 59.4040210358799 -y: 1.37278931215405, 17.6336284726858, -81.062437640503, -71.6937384102494, 3.27541613951325, -61.2097083125263, -89.2936512362212, 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-25.5232597701252, 56.1190348584205, -62.1999088674784, -84.2725639231503, -35.7946417294443, -20.4277000855654, -81.0949407052249, 48.0415523983538 ------------------------------------------------------------ diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index f25145c..39e6e8e 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -189,13 +189,13 @@ def parse_input(lines, parser_function): for item in (parse_input_line(line, parser_function) for line in lines) if len(item) != 0) -def parse_test_data(filename): - with open("pcor_rec_blackbox_attempt.txt", newline="\n") as fl: +def parse_test_data(filename, parser_function): + with open(filename, newline="\n") as fl: input_lines = partition_by( lambda s: s.startswith("------"), (line.strip("\n\t ") for line in fl.readlines())) - return parse_input(input_lines, parse_for_rec) + return parse_input(input_lines, parser_function) class TestPartialCorrelations(TestCase): """Class for testing partial correlations computation functions""" @@ -422,12 +422,15 @@ class TestPartialCorrelations(TestCase): """ for sample in parse_test_data( ("tests/unit/computations/partial_correlations_test_data/" - "pcor_rec_blackbox_test.txt")): + "pcor_rec_blackbox_test.txt"), + parse_for_rec): 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"]), + round( + partial_correlation_recursive( + sample["x"], sample["y"], sample["z"], + method=sample["method"], omit_nones=sample["rm"]), + ROUND_TO), round(sample["result"], ROUND_TO)) -- cgit v1.2.3 From 21fbbfd599c841f082d88ddfc5f4cb362e1eb869 Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Thu, 18 Nov 2021 10:58:34 +0300 Subject: Replace code migrated from R with pingouin functions Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * Replace the code that was in the process of being migrated from R in GeneNetwork1 with calls to pingouin functions that achieve the same thing. Since the functions in this case are computing correlations and partial correlations, rather than having home-rolled functions to do that, this commit makes use of the tried and tested pingouin functions. This avoids complicating our code with edge-case checks, and leverages the performance optimisations done in pingouin. --- gn3/computations/partial_correlations.py | 114 ++++++++------------- .../unit/computations/test_partial_correlations.py | 41 +------- 2 files changed, 44 insertions(+), 111 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 519dce9..4b0cf30 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -11,6 +11,7 @@ from typing import Any, Tuple, Union, Sequence from scipy.stats import pearsonr, spearmanr import pandas +import pingouin from gn3.settings import TEXTDIR from gn3.data_helpers import parse_csv_line @@ -248,7 +249,7 @@ def compute_partial_correlations_fast(# pylint: disable=[R0913, R0914] all_target_trait_names: Tuple[str, ...] = processed_trait_names_values[0] all_target_trait_values: Tuple[float, ...] = processed_trait_names_values[1] - all_correlations = determine_partials( + all_correlations = compute_partial( primary_vals, control_vals, all_target_trait_names, all_target_trait_values, method) ## Line 772 to 779 in GN1 are the cause of the weird complexity in the @@ -278,79 +279,50 @@ def build_data_frame( return interm_df.rename(columns={"z0": "z"}) return interm_df -def partial_correlation_matrix( - xdata: Tuple[float, ...], ydata: Tuple[float, ...], - zdata: Union[Tuple[float, ...], Tuple[Tuple[float, ...], ...]], - method: str = "pearson", omit_nones: bool = True) -> float: +def compute_partial( + primary_val, control_vals, target_vals, target_names, + method: str) -> Tuple[ + Union[ + Tuple[str, int, float, float, float, float], None], + ...]: """ - Computes the partial correlation coefficient using the - 'variance-covariance matrix' method + Compute the partial correlations. - This is a partial migration of the - `web.webqtl.correlation.correlationFunction.determinPartialsByR` function in - GeneNetwork1, specifically the `pcor.mat` function written in the R - programming language. - """ - return 0 + This is a re-implementation of the + `web.webqtl.correlation.correlationFunction.determinePartialsByR` function + in GeneNetwork1. -def partial_correlation_recursive( - xdata: Tuple[float, ...], ydata: Tuple[float, ...], - zdata: Union[Tuple[float, ...], Tuple[Tuple[float, ...], ...]], - method: str = "pearson", omit_nones: bool = True) -> float: - """ - Computes the partial correlation coefficient using the 'recursive formula' - method + This implementation reworks the child function `compute_partial` which will + then be used in the place of `determinPartialsByR`. - This is a partial migration of the - `web.webqtl.correlation.correlationFunction.determinPartialsByR` function in - GeneNetwork1, specifically the `pcor.rec` function written in the R - programming language. + TODO: moving forward, we might need to use the multiprocessing library to + speed up the computations, in case they are found to be slow. """ - assert method in ("pearson", "spearman", "kendall") - data = ( - build_data_frame(xdata, ydata, zdata).dropna(axis=0) - if omit_nones else - build_data_frame(xdata, ydata, zdata)) - - if data.shape[1] == 3: # z is a vector, not matrix - fields = { - "rxy": ("x", "y"), - "rxz": ("x", "z"), - "ryz": ("y", "z")} - tdata = { - corr_type: pandas.DataFrame( - {cols[0]: data[cols[0]], - cols[1]: data[cols[1]]}).dropna(axis=0) - for corr_type, cols in fields.items() - } - corrs = { - corr_type: tdata[corr_type][cols[0]].corr( - tdata[corr_type][cols[1]], method=method) - for corr_type, cols in fields.items() - } + # replace the R code with `pingouin.partial_corr` + def __compute_trait_info__(target): + df = build_data_frame( + [prim for targ, prim in zip(target, primary_vals) + if targ is not None], + [targ for targ in target if targ is not None], + [cont for i, cont in enumerate(control) if target[i] is not None]) + covariates = "z" if df.shape[1] == 3 else [ + col for col in df.columns if col not in ("x", "y")] + ppc = pingouin.partial_corr( + data=df, x="x", y="y", covar=covariates, method=method) + pc_coeff = ppc["r"] + + zero_order_corr = pingouin.corr(df["x"], df["y"], method=method) + + if math.isnan(pc_coeff): + return ( + target[1], len(primary), pc_coeff, 1, zero_order_corr["r"], + zero_order_corr["p-val"]) return ( - (corrs["rxy"] - corrs["rxz"] * corrs["ryz"]) / - (math.sqrt(1 - corrs["rxz"]**2) * - math.sqrt(1 - corrs["ryz"]**2))) - - remaining_cols = [ - colname for colname, series in data.items() - if colname not in ("x", "y", "z0") - ] - - new_xdata = tuple(data["x"]) - new_ydata = tuple(data["y"]) - zc = tuple(tuple(data[colname]) for colname in data[remaining_cols].columns) - - rxy_zc = partial_correlation_recursive( - new_xdata, new_ydata, zc, method=method, - omit_nones=omit_nones) - rxz0_zc = partial_correlation_recursive( - new_xdata, tuple(data["z0"]), zc, method=method, - omit_nones=omit_nones) - ryz0_zc = partial_correlation_recursive( - new_ydata, tuple(data["z0"]), zc, method=method, - omit_nones=omit_nones) - - return ((rxy_zc - rxz0_zc * ryz0_zc) /( - math.sqrt(1 - rxz0_zc**2) * math.sqrt(1 - ryz0_zc**2))) + target[1], len(primary), pc_coeff, + (ppc["p-val"] if not math.isnan(ppc["p-val"]) else ( + 0 if (abs(pc_coeff - 1) < 0.0000001) else 1)), + zero_order_corr["r"], zero_order_corr["p-val"]) + + return tuple( + __compute_trait_info__(target) + for target in zip(target_vals, target_names)) diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 39e6e8e..138155d 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -16,9 +16,7 @@ from gn3.computations.partial_correlations import ( dictify_by_samples, tissue_correlation, find_identical_traits, - partial_correlation_matrix, - good_dataset_samples_indexes, - partial_correlation_recursive) + good_dataset_samples_indexes) sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"] control_traits = ( @@ -397,40 +395,3 @@ class TestPartialCorrelations(TestCase): with self.subTest(xdata=xdata, ydata=ydata, zdata=zdata): self.assertTrue( build_data_frame(xdata, ydata, zdata).equals(expected)) - - 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"]) - - def test_partial_correlation_recursive(self): - """ - Test that `partial_correlation_recursive` computes the appropriate - correlation value. - """ - for sample in parse_test_data( - ("tests/unit/computations/partial_correlations_test_data/" - "pcor_rec_blackbox_test.txt"), - parse_for_rec): - with self.subTest( - xdata=sample["x"], ydata=sample["y"], zdata=sample["z"], - method=sample["method"], omit_nones=sample["rm"]): - self.assertEqual( - round( - partial_correlation_recursive( - sample["x"], sample["y"], sample["z"], - method=sample["method"], omit_nones=sample["rm"]), - ROUND_TO), - round(sample["result"], ROUND_TO)) -- cgit v1.2.3 From 3dd5fbda7e08999b6470cfe1fbbd19d767adea9b Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Thu, 18 Nov 2021 11:59:53 +0300 Subject: Fix some linting errors Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/partial-correlations.gmi * Fix some obvious linting errors and remove obsolete code --- gn3/computations/partial_correlations.py | 22 ++-- .../unit/computations/test_partial_correlations.py | 111 +-------------------- tests/unit/test_data_helpers.py | 15 +++ tests/unit/test_heatmaps.py | 8 +- 4 files changed, 38 insertions(+), 118 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index 4b0cf30..ee47290 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -280,7 +280,7 @@ def build_data_frame( return interm_df def compute_partial( - primary_val, control_vals, target_vals, target_names, + primary_vals, control_vals, target_vals, target_names, method: str) -> Tuple[ Union[ Tuple[str, int, float, float, float, float], None], @@ -300,18 +300,22 @@ def compute_partial( """ # replace the R code with `pingouin.partial_corr` def __compute_trait_info__(target): - df = build_data_frame( - [prim for targ, prim in zip(target, primary_vals) - if targ is not None], + primary = [ + prim for targ, prim in zip(target, primary_vals) + if targ is not None] + datafrm = build_data_frame( + primary, [targ for targ in target if targ is not None], - [cont for i, cont in enumerate(control) if target[i] is not None]) - covariates = "z" if df.shape[1] == 3 else [ - col for col in df.columns if col not in ("x", "y")] + [cont for i, cont in enumerate(control_vals) + if target[i] is not None]) + covariates = "z" if datafrm.shape[1] == 3 else [ + col for col in datafrm.columns if col not in ("x", "y")] ppc = pingouin.partial_corr( - data=df, x="x", y="y", covar=covariates, method=method) + data=datafrm, x="x", y="y", covar=covariates, method=method) pc_coeff = ppc["r"] - zero_order_corr = pingouin.corr(df["x"], df["y"], method=method) + zero_order_corr = pingouin.corr( + datafrm["x"], datafrm["y"], method=method) if math.isnan(pc_coeff): return ( diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 138155d..f77a066 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -1,14 +1,9 @@ """Module contains tests for gn3.partial_correlations""" -import csv from unittest import TestCase import pandas -from gn3.settings import ROUND_TO -from gn3.function_helpers import compose -from gn3.data_helpers import partition_by - from gn3.computations.partial_correlations import ( fix_samples, control_samples, @@ -99,102 +94,6 @@ dictified_control_samples = ( "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": round(float(line["result"]), ROUND_TO) - } for line in lines) - -def parse_method(key_value): - """Parse the partial correlation method""" - key, value = key_value - if key == "method": - methods_dict = {"p": "pearson", "k": "kendall", "s": "spearman"} - return (key, methods_dict[value]) - return key_value - -def parse_count(key_value): - """Parse the value of count into an integer""" - key, value = key_value - if key == "count": - return (key, int(value)) - return key_value - -def parse_xyz(key_value): - """Parse the values of x, y, and z* items into sequences of floats""" - key, value = key_value - if (key in ("x", "y", "z")) or key.startswith("input.z"): - return ( - key.replace("input", "").replace(".", ""), - tuple(float(val.strip("\n\t ")) for val in value.split(","))) - return key_value - -def parse_rm(key_value): - """Parse the rm value into a python True/False value.""" - key, value = key_value - if key == "rm": - return (key, value == "TRUE") - return key_value - -def parse_result(key_value): - """Parse the result into a float value.""" - key, value = key_value - if key == "result": - return (key, float(value)) - return key_value - -parse_for_rec = compose( - parse_result, - parse_rm, - parse_xyz, - parse_count, - parse_method, - lambda k_v: tuple(item.strip("\n\t ") for item in k_v), - lambda s: s.split(":")) - -def parse_input_line(line, parser_function): - return tuple( - parser_function(item) for item in line if not item.startswith("------")) - -def merge_z(item): - without_z = { - key: val for key, val in item.items() if not key.startswith("z")} - return { - **without_z, - "z": item.get( - "z", - tuple(val for key, val in item.items() if key.startswith("z")))} - -def parse_input(lines, parser_function): - return tuple( - merge_z(dict(item)) - for item in (parse_input_line(line, parser_function) for line in lines) - if len(item) != 0) - -def parse_test_data(filename, parser_function): - with open(filename, newline="\n") as fl: - input_lines = partition_by( - lambda s: s.startswith("------"), - (line.strip("\n\t ") for line in fl.readlines())) - - return parse_input(input_lines, parser_function) - class TestPartialCorrelations(TestCase): """Class for testing partial correlations computation functions""" @@ -382,16 +281,16 @@ class TestPartialCorrelations(TestCase): Check that the function builds the correct data frame. """ for xdata, ydata, zdata, expected in ( - ((0.1, 1.1, 2.1), (2.1, 3.1, 4.1), (5.1, 6.1 ,7.1), + ((0.1, 1.1, 2.1), (2.1, 3.1, 4.1), (5.1, 6.1, 7.1), pandas.DataFrame({ "x": (0.1, 1.1, 2.1), "y": (2.1, 3.1, 4.1), - "z": (5.1, 6.1 ,7.1)})), + "z": (5.1, 6.1, 7.1)})), ((0.1, 1.1, 2.1), (2.1, 3.1, 4.1), - ((5.1, 6.1 ,7.1), (5.2, 6.2, 7.2), (5.3, 6.3, 7.3)), + ((5.1, 6.1, 7.1), (5.2, 6.2, 7.2), (5.3, 6.3, 7.3)), pandas.DataFrame({ "x": (0.1, 1.1, 2.1), "y": (2.1, 3.1, 4.1), - "z0": (5.1, 6.1, 7.1), "z1": (5.2, 6.2 ,7.2), - "z2": (5.3, 6.3 ,7.3)}))): + "z0": (5.1, 6.1, 7.1), "z1": (5.2, 6.2, 7.2), + "z2": (5.3, 6.3, 7.3)}))): with self.subTest(xdata=xdata, ydata=ydata, zdata=zdata): self.assertTrue( build_data_frame(xdata, ydata, zdata).equals(expected)) diff --git a/tests/unit/test_data_helpers.py b/tests/unit/test_data_helpers.py index 3f76344..88ea469 100644 --- a/tests/unit/test_data_helpers.py +++ b/tests/unit/test_data_helpers.py @@ -61,6 +61,21 @@ class TestDataHelpers(TestCase): expected) def test_partition_by(self): + """ + Test that `partition_by` groups the data using the given predicate + + Given: + - `part_fn`: a predicate funtion that return boolean True/False + - `items`: a sequence of items + When: + - the partitioning predicate function and the sequence of items are + passed to the `partition_by` function + Then: + - the result is a tuple, with sub-tuples containing the data in the + original sequence. Each sub-tuple is a partition, ending as soon as + the next value in the sequence, when passed to `part_fn`, returns + boolean `True`. + """ for part_fn, items, expected in ( (lambda s: s.startswith("----"), ("------", "a", "b", "-----", "c", "----", "d", "e", "---", diff --git a/tests/unit/test_heatmaps.py b/tests/unit/test_heatmaps.py index e4c929d..69e1c3c 100644 --- a/tests/unit/test_heatmaps.py +++ b/tests/unit/test_heatmaps.py @@ -1,6 +1,8 @@ """Module contains tests for gn3.heatmaps.heatmaps""" from unittest import TestCase -from numpy.testing import assert_allclose + +from numpy import allclose + from gn3.heatmaps import ( cluster_traits, get_loci_names, @@ -40,7 +42,7 @@ class TestHeatmap(TestCase): (6.84118, 7.08432, 7.59844, 7.08229, 7.26774, 7.24991), (9.45215, 10.6943, 8.64719, 10.1592, 7.75044, 8.78615), (7.04737, 6.87185, 7.58586, 6.92456, 6.84243, 7.36913)] - assert_allclose( + self.assertTrue(allclose( cluster_traits(traits_data_list), ((0.0, 0.20337048635536847, 0.16381088984330505, 1.7388553629398245, 1.5025235756329178, 0.6952839500255574, 1.271661230252733, @@ -72,7 +74,7 @@ class TestHeatmap(TestCase): (0.7934461515867415, 0.4497104244247795, 0.7127042590637039, 0.9313185954797953, 1.1683723389247052, 0.23451785425383564, 1.7413442197913358, 0.33370067057028485, 1.3256191648260216, - 0.0))) + 0.0)))) def test_compute_heatmap_order(self): """Test the orders.""" -- cgit v1.2.3 From 08c81b8892060353bb7fb15555875f03bbdcb46e Mon Sep 17 00:00:00 2001 From: Frederick Muriuki Muriithi Date: Fri, 19 Nov 2021 10:56:35 +0300 Subject: Avoid rounding: compare floats approximately Notes: https://github.com/genenetwork/genenetwork3/pull/56#issuecomment-973798918 * As mentioned in the notes, rather than rounding to an arbitrary number of decimal places, it is a much better practice to use approximate comparisons of floats for the tests. --- gn3/computations/partial_correlations.py | 2 +- tests/unit/computations/test_partial_correlations.py | 9 +++++---- 2 files changed, 6 insertions(+), 5 deletions(-) (limited to 'tests/unit/computations') diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py index ee47290..4f45159 100644 --- a/gn3/computations/partial_correlations.py +++ b/gn3/computations/partial_correlations.py @@ -156,7 +156,7 @@ def tissue_correlation( "Method must be one of: {}".format(",".join(method_fns.keys()))) corr, pvalue = method_fns[method](primary_trait_values, target_trait_values) - return (round(corr, 10), round(pvalue, 10)) + return (corr, pvalue) def batch_computed_tissue_correlation( primary_trait_values: Tuple[float, ...], target_traits_dict: dict, diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index f77a066..3e1b6e1 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -3,6 +3,7 @@ from unittest import TestCase import pandas +from numpy.testing import assert_allclose from gn3.computations.partial_correlations import ( fix_samples, @@ -250,7 +251,7 @@ class TestPartialCorrelations(TestCase): with self.assertRaises(error, msg=error_msg): tissue_correlation(primary, target, method) - def test_tissue_correlation(self): + def test_tissue_correlation(self): # pylint: disable=R0201 """ Test that the correct correlation values are computed for the given: - primary trait @@ -259,11 +260,11 @@ class TestPartialCorrelations(TestCase): """ for primary, target, method, expected in ( ((12.34, 18.36, 42.51), (37.25, 46.25, 46.56), "pearson", - (0.6761779253, 0.5272701134)), + (0.6761779252651052, 0.5272701133657985)), ((1, 2, 3, 4, 5), (5, 6, 7, 8, 7), "spearman", - (0.8207826817, 0.0885870053))): + (0.8207826816681233, 0.08858700531354381))): with self.subTest(primary=primary, target=target, method=method): - self.assertEqual( + assert_allclose( tissue_correlation(primary, target, method), expected) def test_good_dataset_samples_indexes(self): -- cgit v1.2.3