1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
|
"""gn3.computations.rust_correlation unittests"""
import json
import os
import pytest
from gn3.computations.rust_correlation import generate_json_file
from gn3.computations.rust_correlation import generate_input_files
from gn3.computations.rust_correlation import get_samples
from gn3.computations.rust_correlation import parse_correlation_output
@pytest.mark.unit_test
def test_generate_input():
"""test generating text files"""
test_dataset = [
["14_at",12.1,14.1,None],
["15_at",12.2,14.1,None],
["17_at",12.1,14.1,11.4]
]
expected = ["14_at,12.1,14.1,", "15_at,12.2,14.1,", "17_at,12.1,14.1,11.4"]
(_tmp_dir, tmp_file) = generate_input_files(test_dataset,
output_dir="/tmp")
with open(tmp_file, "r", encoding="utf-8") as file_reader:
test_results = [line.rstrip() for line in file_reader]
os.remove(tmp_file)
assert test_results == expected
# @pytest.mark.unit_test
def test_json_file():
"""test for generating json files """
tmp_file, _tmp_json_file = generate_json_file(
tmp_dir="/tmp/correlation",
tmp_file="/data.txt",
method="pearson",
x_vals="12.1,11.3,16.5,7.5,3.2",
delimiter=",")
with open(tmp_file, "r+", encoding="utf-8") as file_reader:
results = json.load(file_reader)
assert results == {
"method": "pearson",
"file_path": "/data.txt",
"x_vals": "12.1,11.3,16.5,7.5,3.2",
"file_delimiter": ","}
@pytest.mark.unit_test
def test_parse_results():
"""test for parsing file results"""
raw_data = [
["63.62", "0.97", "0.00", "12"],
["19", "-0.96", "0.22", "12"],
["77.92", "-0.94", "0.31", "12"],
["84.04", "0.94", "0.11", "12"],
["23", "-0.91", "0.11", "12"]
]
expected_results = {
trait: {
"num_overlap": num_overlap,
"corr_coefficient": corr_coeff,
"p_value": p_val}
for (trait, corr_coeff, p_val, num_overlap) in raw_data
}
assert (parse_correlation_output(
"tests/unit/computations/data/correlation/sorted_results.txt",
"sample", len(raw_data))
== expected_results)
@pytest.mark.unit_test
def test_get_samples_no_excluded():
"""test for getting sample data"""
al_samples = {
"BXD": "12.1",
"BXD3": "16.1",
"BXD4": " x",
"BXD6": "1.1",
"BXD5": "1.37",
"BXD11": "1.91",
"BXD31": "1.1"
}
base = [
"BXD",
"BXD4",
"BXD7",
"BXD31"
]
assert get_samples(all_samples=al_samples,
base_samples=base,
excluded=[]) == {
"BXD": 12.1,
"BXD31": 1.1
}
@pytest.mark.unit_test
def test_get_samples():
"""test for getting samples with exluded"""
al_samples = {
"BXD": "12.1",
"BXD3": "16.1",
"BXD4": " x",
"BXD5": "1.1",
"BXD6": "1.37",
"BXD11": "1.91",
"BXD31": "1.1"
}
assert get_samples(all_samples=al_samples,
base_samples=["BXD", "BXD4", "BXD5", "BXD6",
"BXD11"
], excluded=["BXD", "BXD11"]), {
"BXD5": 1.1,
"BXD6": 1.37
}
|
