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-rw-r--r--tests/unit/computations/test_partial_correlations.py273
1 files changed, 273 insertions, 0 deletions
diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py
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+++ b/tests/unit/computations/test_partial_correlations.py
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+"""Module contains tests for gn3.partial_correlations"""
+
+from unittest import TestCase
+from gn3.computations.partial_correlations import (
+ fix_samples,
+ control_samples,
+ dictify_by_samples,
+ tissue_correlation,
+ find_identical_traits,
+ good_dataset_samples_indexes)
+
+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",
+ (0.6761779253, 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))
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-22 11:46:37 +0000