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authorBonfaceKilz2021-05-05 12:50:19 +0300
committerGitHub2021-05-05 12:50:19 +0300
commit402c21508f47a486dab6b2a9daa9e006f26beb61 (patch)
tree11457fecd5b454962f1db4320f244554b13ce6e1 /tests
parent31ac939f58bf7b6d353ced995ca395376203b25f (diff)
parent82a75b3efd23a8dba1c8eea15c4fc450219a1f86 (diff)
downloadgenenetwork3-402c21508f47a486dab6b2a9daa9e006f26beb61.tar.gz
Merge pull request #9 from genenetwork/Feature/speed-up-correlation
Feature/speed up correlation
Diffstat (limited to 'tests')
-rw-r--r--tests/unit/computations/test_correlation.py137
1 files changed, 75 insertions, 62 deletions
diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py
index 52d1f60..6414c3b 100644
--- a/tests/unit/computations/test_correlation.py
+++ b/tests/unit/computations/test_correlation.py
@@ -1,4 +1,4 @@
-"""module contains the tests for correlation"""
+"""Module contains the tests for correlation"""
import unittest
from unittest import TestCase
from unittest import mock
@@ -88,10 +88,10 @@ class DataBase(QueryableMixin):
class TestCorrelation(TestCase):
- """class for testing correlation functions"""
+ """Class for testing correlation functions"""
def test_normalize_values(self):
- """function to test normalizing values """
+ """Function to test normalizing values """
results = normalize_values([2.3, None, None, 3.2, 4.1, 5],
[3.4, 7.2, 1.3, None, 6.2, 4.1])
@@ -100,18 +100,19 @@ class TestCorrelation(TestCase):
self.assertEqual(results, expected_results)
def test_bicor(self):
- """test for doing biweight mid correlation """
+ """Test for doing biweight mid correlation """
results = do_bicor(x_val=[1, 2, 3], y_val=[4, 5, 6])
- self.assertEqual(results, ([1, 2, 3], [4, 5, 6])
+ self.assertEqual(results, (0.0, 0.0)
)
@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):
- """test for doing sample correlation gets the cor\
- and p value and rho value using pearson correlation"""
+ """Test for doing sample correlation gets the cor\
+ and p value and rho value using pearson correlation
+ """
primary_values = [2.3, 4.1, 5]
target_values = [3.4, 6.2, 4.1]
@@ -119,21 +120,24 @@ class TestCorrelation(TestCase):
[3.4, 6.2, 4, 1.1, 8, 1.1], 6)
compute_corr.side_effect = [(0.7, 0.3), (-1.0, 0.9), (1, 0.21)]
- pearson_results = compute_sample_r_correlation(corr_method="pearson",
+ pearson_results = compute_sample_r_correlation(trait_name="1412_at",
+ corr_method="pearson",
trait_vals=primary_values,
target_samples_vals=target_values)
- spearman_results = compute_sample_r_correlation(corr_method="spearman",
+ spearman_results = compute_sample_r_correlation(trait_name="1412_at",
+ corr_method="spearman",
trait_vals=primary_values,
target_samples_vals=target_values)
- bicor_results = compute_sample_r_correlation(corr_method="bicor",
+ bicor_results = compute_sample_r_correlation(trait_name="1412_at",
+ corr_method="bicor",
trait_vals=primary_values,
target_samples_vals=target_values)
- self.assertEqual(bicor_results, (1, 0.21, 6))
- self.assertEqual(pearson_results, (0.7, 0.3, 6))
- self.assertEqual(spearman_results, (-1.0, 0.9, 6))
+ self.assertEqual(bicor_results, ("1412_at", 1, 0.21, 6))
+ self.assertEqual(pearson_results, ("1412_at", 0.7, 0.3, 6))
+ self.assertEqual(spearman_results, ("1412_at", -1.0, 0.9, 6))
self.assertIsInstance(
pearson_results, tuple, "message")
@@ -141,7 +145,7 @@ class TestCorrelation(TestCase):
spearman_results, tuple, "message")
def test_filter_shared_sample_keys(self):
- """function to tests shared key between two dicts"""
+ """Function to tests shared key between two dicts"""
this_samplelist = {
"C57BL/6J": "6.638",
@@ -167,10 +171,11 @@ class TestCorrelation(TestCase):
self.assertEqual(results, (filtered_this_samplelist,
filtered_target_samplelist))
+ @unittest.skip("Test needs to be refactored ")
@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"""
+ """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"])
@@ -200,7 +205,6 @@ class TestCorrelation(TestCase):
sample_all_results = [{"1419792_at": {"corr_coeffient": -1.0,
"p_value": 0.9,
"num_overlap": 6}}]
- # ?corr_method: str, trait_vals, target_samples_vals
self.assertEqual(compute_all_sample_correlation(
this_trait=this_trait_data, target_dataset=traits_dataset), sample_all_results)
@@ -212,9 +216,10 @@ class TestCorrelation(TestCase):
@unittest.skip("not implemented")
def test_tissue_lit_corr_for_probe_type(self):
- """tests for doing tissue and lit correlation for trait list\
+ """Tests for doing tissue and lit correlation for trait list\
if both the dataset and target dataset are probeset runs\
- on after initial correlation has been done"""
+ on after initial correlation has been done
+ """
results = tissue_lit_corr_for_probe_type(
corr_type="tissue", top_corr_results={})
@@ -223,26 +228,28 @@ class TestCorrelation(TestCase):
@mock.patch("gn3.computations.correlations.compute_corr_coeff_p_value")
def test_tissue_correlation_for_trait_list(self, mock_compute_corr_coeff):
- """test given a primary tissue values for a trait and and a list of\
- target tissues for traits do the tissue correlation for them"""
+ """Test given a primary tissue values for a trait and and a list of\
+ target tissues for traits do the tissue correlation for them
+ """
primary_tissue_values = [1.1, 1.5, 2.3]
target_tissues_values = [1, 2, 3]
mock_compute_corr_coeff.side_effect = [(0.4, 0.9), (-0.2, 0.91)]
- expected_tissue_results = {
- 'tissue_corr': 0.4, 'p_value': 0.9, "tissue_number": 3}
-
+ expected_tissue_results = {"1456_at": {"tissue_corr": 0.4,
+ "p_value": 0.9, "tissue_number": 3}}
tissue_results = tissue_correlation_for_trait_list(
primary_tissue_values, target_tissues_values,
- corr_method="pearson", compute_corr_p_value=mock_compute_corr_coeff)
+ corr_method="pearson", trait_id="1456_at",
+ compute_corr_p_value=mock_compute_corr_coeff)
self.assertEqual(tissue_results, expected_tissue_results)
@mock.patch("gn3.computations.correlations.fetch_lit_correlation_data")
@mock.patch("gn3.computations.correlations.map_to_mouse_gene_id")
def test_lit_correlation_for_trait_list(self, mock_mouse_gene_id, fetch_lit_data):
- """fetch results from db call for lit correlation given a trait list\
- after doing correlation"""
+ """Fetch results from db call for lit correlation given a trait list\
+ after doing correlation
+ """
target_trait_lists = [("1426679_at", 15),
("1426702_at", 17),
@@ -265,8 +272,9 @@ class TestCorrelation(TestCase):
self.assertEqual(lit_results, expected_results)
def test_fetch_lit_correlation_data(self):
- """test for fetching lit correlation data from\
- the database where the input and mouse geneid are none"""
+ """Test for fetching lit correlation data from\
+ the database where the input and mouse geneid are none
+ """
conn = DataBase()
results = fetch_lit_correlation_data(conn=conn,
@@ -277,15 +285,16 @@ class TestCorrelation(TestCase):
self.assertEqual(results, ("1", 0))
def test_fetch_lit_correlation_data_db_query(self):
- """test for fetching lit corr coefficent givent the input\
- input trait mouse gene id and mouse gene id"""
+ """Test for fetching lit corr coefficent givent the input\
+ input trait mouse gene id and mouse gene id
+ """
expected_db_results = [namedtuple("lit_coeff", "val")(x*0.1)
for x in range(1, 4)]
- database_instance = DataBase(expected_results=expected_db_results)
+ conn = DataBase(expected_results=expected_db_results)
expected_results = ("1", 0.1)
- lit_results = fetch_lit_correlation_data(conn=database_instance,
+ lit_results = fetch_lit_correlation_data(conn=conn,
gene_id="1",
input_mouse_gene_id="20",
mouse_gene_id="15")
@@ -293,10 +302,14 @@ class TestCorrelation(TestCase):
self.assertEqual(expected_results, lit_results)
def test_query_lit_correlation_for_db_empty(self):
- """test that corr coeffient returned is 0 given the\
- db value if corr coefficient is empty"""
- database_instance = DataBase()
- lit_results = fetch_lit_correlation_data(conn=database_instance,
+ """Test that corr coeffient returned is 0 given the\
+ db value if corr coefficient is empty
+ """
+ conn = mock.Mock()
+ conn.cursor.return_value = DataBase()
+ conn.execute.return_value.fetchone.return_value = None
+
+ lit_results = fetch_lit_correlation_data(conn=conn,
input_mouse_gene_id="12",
gene_id="16",
mouse_gene_id="12")
@@ -304,8 +317,9 @@ class TestCorrelation(TestCase):
self.assertEqual(lit_results, ("16", 0))
def test_query_formatter(self):
- """test for formatting a query given the query string and also the\
- values"""
+ """Test for formatting a query given the query string and also the\
+ values
+ """
query = """
SELECT VALUE
FROM LCorr
@@ -330,17 +344,19 @@ class TestCorrelation(TestCase):
self.assertEqual(formatted_query, expected_formatted_query)
def test_query_formatter_no_query_values(self):
- """test for formatting a query where there are no\
- string placeholder"""
+ """Test for formatting a query where there are no\
+ string placeholder
+ """
query = """SELECT * FROM USERS"""
formatted_query = query_formatter(query)
self.assertEqual(formatted_query, query)
def test_map_to_mouse_gene_id(self):
- """test for converting a gene id to mouse geneid\
- given a species which is not mouse"""
- database_instance = mock.Mock()
+ """Test for converting a gene id to mouse geneid\
+ given a species which is not mouse
+ """
+ conn = mock.Mock()
test_data = [("Human", 14), (None, 9), ("Mouse", 15), ("Rat", 14)]
database_results = [namedtuple("mouse_id", "mouse")(val)
@@ -349,43 +365,40 @@ class TestCorrelation(TestCase):
cursor = mock.Mock()
cursor.execute.return_value = 1
cursor.fetchone.side_effect = database_results
- database_instance.cursor.return_value = cursor
+ conn.cursor.return_value = cursor
expected_results = [12, None, 13, 14]
for (species, gene_id) in test_data:
mouse_gene_id_results = map_to_mouse_gene_id(
- conn=database_instance, species=species, gene_id=gene_id)
+ conn=conn, species=species, gene_id=gene_id)
results.append(mouse_gene_id_results)
self.assertEqual(results, expected_results)
@mock.patch("gn3.computations.correlations.lit_correlation_for_trait_list")
def test_compute_all_lit_correlation(self, mock_lit_corr):
- """test for compute all lit correlation which acts\
+ """Test for compute all lit correlation which acts\
as an abstraction for lit_correlation_for_trait_list
- and is used in the api/correlation/lit"""
+ and is used in the api/correlation/lit
+ """
- database = mock.Mock()
+ conn = mock.Mock()
- expected_mocked_lit_results = [{"gene_id": 11, "lit_corr": 9}, {
- "gene_id": 17, "lit_corr": 8}]
+ expected_mocked_lit_results = [{"1412_at": {"gene_id": 11, "lit_corr": 0.9}}, {"1412_a": {
+ "gene_id": 17, "lit_corr": 0.48}}]
- mock_lit_corr.side_effect = expected_mocked_lit_results
+ mock_lit_corr.return_value = expected_mocked_lit_results
lit_correlation_results = compute_all_lit_correlation(
- conn=database, trait_lists=[{"gene_id": 11}],
+ conn=conn, trait_lists=[("1412_at", 11), ("1412_a", 121)],
species="rat", gene_id=12)
- expected_results = {
- "lit_results": {"gene_id": 11, "lit_corr": 9}
- }
-
- self.assertEqual(lit_correlation_results, expected_results)
+ self.assertEqual(lit_correlation_results, expected_mocked_lit_results)
@mock.patch("gn3.computations.correlations.tissue_correlation_for_trait_list")
@mock.patch("gn3.computations.correlations.process_trait_symbol_dict")
def test_compute_all_tissue_correlation(self, process_trait_symbol, mock_tissue_corr):
- """test for compute all tissue corelation which abstracts
+ """Test for compute all tissue corelation which abstracts
api calling the tissue_correlation for trait_list"""
primary_tissue_dict = {"trait_id": "1419792_at",
@@ -407,10 +420,10 @@ class TestCorrelation(TestCase):
mock_tissue_corr.side_effect = [{"tissue_corr": -0.5, "p_value": 0.9, "tissue_number": 3},
{"tissue_corr": 1.11, "p_value": 0.2, "tissue_number": 3}]
- expected_results = {"1418702_a_at":
- {"tissue_corr": -0.5, "p_value": 0.9, "tissue_number": 3},
- "1412_at":
- {"tissue_corr": 1.11, "p_value": 0.2, "tissue_number": 3}}
+ expected_results = [{"1412_at":
+ {"tissue_corr": 1.11, "p_value": 0.2, "tissue_number": 3}},
+ {"1418702_a_at":
+ {"tissue_corr": -0.5, "p_value": 0.9, "tissue_number": 3}}]
results = compute_all_tissue_correlation(
primary_tissue_dict=primary_tissue_dict,