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
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
|
"""Module contains tests for gn3.computations.heatmap"""
from unittest import TestCase
from gn3.computations.heatmap import (
cluster_traits,
export_trait_data,
compute_traits_order,
retrieve_strains_and_values)
strainlist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"]
trait_data = {
"mysqlid": 36688172,
"data": {
"B6cC3-1": {"strain_name": "B6cC3-1", "value": 7.51879, "variance": None, "ndata": None},
"BXD1": {"strain_name": "BXD1", "value": 7.77141, "variance": None, "ndata": None},
"BXD12": {"strain_name": "BXD12", "value": 8.39265, "variance": None, "ndata": None},
"BXD16": {"strain_name": "BXD16", "value": 8.17443, "variance": None, "ndata": None},
"BXD19": {"strain_name": "BXD19", "value": 8.30401, "variance": None, "ndata": None},
"BXD2": {"strain_name": "BXD2", "value": 7.80944, "variance": None, "ndata": None},
"BXD21": {"strain_name": "BXD21", "value": 8.93809, "variance": None, "ndata": None},
"BXD24": {"strain_name": "BXD24", "value": 7.99415, "variance": None, "ndata": None},
"BXD27": {"strain_name": "BXD27", "value": 8.12177, "variance": None, "ndata": None},
"BXD28": {"strain_name": "BXD28", "value": 7.67688, "variance": None, "ndata": None},
"BXD32": {"strain_name": "BXD32", "value": 7.79062, "variance": None, "ndata": None},
"BXD39": {"strain_name": "BXD39", "value": 8.27641, "variance": None, "ndata": None},
"BXD40": {"strain_name": "BXD40", "value": 8.18012, "variance": None, "ndata": None},
"BXD42": {"strain_name": "BXD42", "value": 7.82433, "variance": None, "ndata": None},
"BXD6": {"strain_name": "BXD6", "value": 8.09718, "variance": None, "ndata": None},
"BXH14": {"strain_name": "BXH14", "value": 7.97475, "variance": None, "ndata": None},
"BXH19": {"strain_name": "BXH19", "value": 7.67223, "variance": None, "ndata": None},
"BXH2": {"strain_name": "BXH2", "value": 7.93622, "variance": None, "ndata": None},
"BXH22": {"strain_name": "BXH22", "value": 7.43692, "variance": None, "ndata": None},
"BXH4": {"strain_name": "BXH4", "value": 7.96336, "variance": None, "ndata": None},
"BXH6": {"strain_name": "BXH6", "value": 7.75132, "variance": None, "ndata": None},
"BXH7": {"strain_name": "BXH7", "value": 8.12927, "variance": None, "ndata": None},
"BXH8": {"strain_name": "BXH8", "value": 6.77338, "variance": None, "ndata": None},
"BXH9": {"strain_name": "BXH9", "value": 8.03836, "variance": None, "ndata": None},
"C3H/HeJ": {"strain_name": "C3H/HeJ", "value": 7.42795, "variance": None, "ndata": None},
"C57BL/6J": {"strain_name": "C57BL/6J", "value": 7.50606, "variance": None, "ndata": None},
"DBA/2J": {"strain_name": "DBA/2J", "value": 7.72588, "variance": None, "ndata": None}}}
slinked = (
(((0, 2, 0.16381088984330505),
((1, 7, 0.06024619831474998), 5, 0.19179284676938602),
0.20337048635536847),
9,
0.23451785425383564),
((3, (6, 8, 0.2140799896286565), 0.25879514152086425),
4, 0.8968250491499363),
0.9313185954797953)
class TestHeatmap(TestCase):
"""Class for testing heatmap computation functions"""
def test_export_trait_data_dtype(self):
"""
Test `export_trait_data` with different values for the `dtype` keyword
argument
"""
for dtype, expected in [
["val", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["var", (None, None, None, None, None, None)],
["N", (None, None, None, None, None, None)],
["all", (7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)]]:
with self.subTest(dtype=dtype):
self.assertEqual(
export_trait_data(trait_data, strainlist, dtype=dtype),
expected)
def test_export_trait_data_dtype_all_flags(self):
"""
Test `export_trait_data` with different values for the `dtype` keyword
argument and the different flags set up
"""
for dtype, vflag, nflag, expected in [
["val", False, False,
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["val", False, True,
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["val", True, False,
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["val", True, True,
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["var", False, False, (None, None, None, None, None, None)],
["var", False, True, (None, None, None, None, None, None)],
["var", True, False, (None, None, None, None, None, None)],
["var", True, True, (None, None, None, None, None, None)],
["N", False, False, (None, None, None, None, None, None)],
["N", False, True, (None, None, None, None, None, None)],
["N", True, False, (None, None, None, None, None, None)],
["N", True, True, (None, None, None, None, None, None)],
["all", False, False,
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944)],
["all", False, True,
(7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None,
8.30401, None, 7.80944, None)],
["all", True, False,
(7.51879, None, 7.77141, None, 8.39265, None, 8.17443, None,
8.30401, None, 7.80944, None)],
["all", True, True,
(7.51879, None, None, 7.77141, None, None, 8.39265, None, None,
8.17443, None, None, 8.30401, None, None, 7.80944, None, None)]
]:
with self.subTest(dtype=dtype, vflag=vflag, nflag=nflag):
self.assertEqual(
export_trait_data(
trait_data, strainlist, dtype=dtype, var_exists=vflag,
n_exists=nflag),
expected)
def test_cluster_traits(self):
"""
Test that the clustering is working as expected.
"""
traits_data_list = [
(7.51879, 7.77141, 8.39265, 8.17443, 8.30401, 7.80944),
(6.1427, 6.50588, 7.73705, 6.68328, 7.49293, 7.27398),
(8.4211, 8.30581, 9.24076, 8.51173, 9.18455, 8.36077),
(10.0904, 10.6509, 9.36716, 9.91202, 8.57444, 10.5731),
(10.188, 9.76652, 9.54813, 9.05074, 9.52319, 9.10505),
(6.74676, 7.01029, 7.54169, 6.48574, 7.01427, 7.26815),
(6.39359, 6.85321, 5.78337, 7.11141, 6.22101, 6.16544),
(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)]
self.assertEqual(
cluster_traits(traits_data_list),
((0.0, 0.20337048635536847, 0.16381088984330505, 1.7388553629398245,
1.5025235756329178, 0.6952839500255574, 1.271661230252733,
0.2100487290977544, 1.4699690641062024, 0.7934461515867415),
(0.20337048635536847, 0.0, 0.2198321044997198, 1.5753041735592204,
1.4815755944537086, 0.26087293140686374, 1.6939790104301427,
0.06024619831474998, 1.7430082449189215, 0.4497104244247795),
(0.16381088984330505, 0.2198321044997198, 0.0, 1.9073926868549234,
1.0396738891139845, 0.5278328671176757, 1.6275069061182947,
0.2636503792482082, 1.739617877037615, 0.7127042590637039),
(1.7388553629398245, 1.5753041735592204, 1.9073926868549234, 0.0,
0.9936846292920328, 1.1169999189889366, 0.6007483980555253,
1.430209221053372, 0.25879514152086425, 0.9313185954797953),
(1.5025235756329178, 1.4815755944537086, 1.0396738891139845,
0.9936846292920328, 0.0, 1.027827186339337, 1.1441743109173244,
1.4122477962364253, 0.8968250491499363, 1.1683723389247052),
(0.6952839500255574, 0.26087293140686374, 0.5278328671176757,
1.1169999189889366, 1.027827186339337, 0.0, 1.8420471110023269,
0.19179284676938602, 1.4875072385631605, 0.23451785425383564),
(1.271661230252733, 1.6939790104301427, 1.6275069061182947,
0.6007483980555253, 1.1441743109173244, 1.8420471110023269, 0.0,
1.6540234785929928, 0.2140799896286565, 1.7413442197913358),
(0.2100487290977544, 0.06024619831474998, 0.2636503792482082,
1.430209221053372, 1.4122477962364253, 0.19179284676938602,
1.6540234785929928, 0.0, 1.5225640692832796, 0.33370067057028485),
(1.4699690641062024, 1.7430082449189215, 1.739617877037615,
0.25879514152086425, 0.8968250491499363, 1.4875072385631605,
0.2140799896286565, 1.5225640692832796, 0.0, 1.3256191648260216),
(0.7934461515867415, 0.4497104244247795, 0.7127042590637039,
0.9313185954797953, 1.1683723389247052, 0.23451785425383564,
1.7413442197913358, 0.33370067057028485, 1.3256191648260216,
0.0)))
def test_compute_heatmap_order(self):
"""Test the orders."""
self.assertEqual(
compute_traits_order(slinked), (0, 2, 1, 7, 5, 9, 3, 6, 8, 4))
def test_retrieve_strains_and_values(self):
"""Test retrieval of strains and values."""
for orders, slist, tdata, expected in [
[
[(60, 2)],
["s1", "s2", "s3", "s4"],
[[2, 9, 6, None, 4],
[7, 5, None, None, 4],
[9, None, 5, 4, 7],
[6, None, None, 4, None]],
[[(60, 2), ["s1", "s3", "s4"], [9, 5, 4]]]
],
[
[(60, 3)],
["s1", "s2", "s3", "s4", "s5"],
[[2, 9, 6, None, 4],
[7, 5, None, None, 4],
[9, None, 5, 4, 7],
[6, None, None, 4, None]],
[[(60, 3), ["s1", "s4"], [6, 4]]]
]]:
with self.subTest(strainlist=slist, traitdata=tdata):
self.assertEqual(
retrieve_strains_and_values(orders, slist, tdata), expected)
|
