diff options
Diffstat (limited to 'tests/unit/computations')
| -rw-r--r-- | tests/unit/computations/partial_correlations_test_data/pcor_rec_blackbox_test.txt | 127 | ||||
| -rw-r--r-- | tests/unit/computations/test_partial_correlations.py | 112 |
2 files changed, 232 insertions, 7 deletions
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-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 +------------------------------------------------------------ diff --git a/tests/unit/computations/test_partial_correlations.py b/tests/unit/computations/test_partial_correlations.py index 83cb9d9..e702f6e 100644 --- a/tests/unit/computations/test_partial_correlations.py +++ b/tests/unit/computations/test_partial_correlations.py @@ -1,10 +1,18 @@ """Module contains tests for gn3.partial_correlations""" import csv -from unittest import TestCase, skip +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, + build_data_frame, dictify_by_samples, tissue_correlation, find_identical_traits, @@ -112,9 +120,82 @@ 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) +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""" @@ -298,7 +379,25 @@ class TestPartialCorrelations(TestCase): ("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l")), (0, 4, 8, 10)) - @skip + 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 @@ -316,15 +415,14 @@ class TestPartialCorrelations(TestCase): method=sample["method"], omit_nones=sample["rm"]), sample["result"]) - @skip def test_partial_correlation_recursive(self): """ Test that `partial_correlation_recursive` computes the appropriate correlation value. """ - for sample in parse_test_data_csv( + 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"]): @@ -332,4 +430,4 @@ 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)) |