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LukeMathWalkerjturner314
LukeMathWalker
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jturner314
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Move numeric tests into the numeric test submodule
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2 files changed

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-169
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2 files changed

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-169
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‎tests/array.rs‎

Lines changed: 0 additions & 167 deletions
Original file line numberDiff line numberDiff line change
@@ -925,173 +925,6 @@ fn assign()
925925
assert_eq!(a, arr2(&[[0, 0], [3, 4]]));
926926
}
927927

928-
#[test]
929-
fn sum_mean()
930-
{
931-
let a = arr2(&[[1., 2.], [3., 4.]]);
932-
assert_eq!(a.sum_axis(Axis(0)), arr1(&[4., 6.]));
933-
assert_eq!(a.sum_axis(Axis(1)), arr1(&[3., 7.]));
934-
assert_eq!(a.mean_axis(Axis(0)), Some(arr1(&[2., 3.])));
935-
assert_eq!(a.mean_axis(Axis(1)), Some(arr1(&[1.5, 3.5])));
936-
assert_eq!(a.sum_axis(Axis(1)).sum_axis(Axis(0)), arr0(10.));
937-
assert_eq!(a.view().mean_axis(Axis(1)).unwrap(), aview1(&[1.5, 3.5]));
938-
assert_eq!(a.sum(), 10.);
939-
}
940-
941-
#[test]
942-
fn sum_mean_empty() {
943-
assert_eq!(Array3::<f32>::ones((2, 0, 3)).sum(), 0.);
944-
assert_eq!(Array1::<f32>::ones(0).sum_axis(Axis(0)), arr0(0.));
945-
assert_eq!(
946-
Array3::<f32>::ones((2, 0, 3)).sum_axis(Axis(1)),
947-
Array::zeros((2, 3)),
948-
);
949-
let a = Array1::<f32>::ones(0).mean_axis(Axis(0));
950-
assert_eq!(a, None);
951-
let a = Array3::<f32>::ones((2, 0, 3)).mean_axis(Axis(1));
952-
assert_eq!(a, None);
953-
}
954-
955-
#[test]
956-
fn var_axis() {
957-
let a = array![
958-
[
959-
[-9.76, -0.38, 1.59, 6.23],
960-
[-8.57, -9.27, 5.76, 6.01],
961-
[-9.54, 5.09, 3.21, 6.56],
962-
],
963-
[
964-
[ 8.23, -9.63, 3.76, -3.48],
965-
[-5.46, 5.86, -2.81, 1.35],
966-
[-1.08, 4.66, 8.34, -0.73],
967-
],
968-
];
969-
assert!(a.var_axis(Axis(0), 1.5).all_close(
970-
&aview2(&[
971-
[3.236401e+02, 8.556250e+01, 4.708900e+00, 9.428410e+01],
972-
[9.672100e+00, 2.289169e+02, 7.344490e+01, 2.171560e+01],
973-
[7.157160e+01, 1.849000e-01, 2.631690e+01, 5.314410e+01]
974-
]),
975-
1e-4,
976-
));
977-
assert!(a.var_axis(Axis(1), 1.7).all_close(
978-
&aview2(&[
979-
[0.61676923, 80.81092308, 6.79892308, 0.11789744],
980-
[75.19912821, 114.25235897, 48.32405128, 9.03020513],
981-
]),
982-
1e-8,
983-
));
984-
assert!(a.var_axis(Axis(2), 2.3).all_close(
985-
&aview2(&[
986-
[ 79.64552941, 129.09663235, 95.98929412],
987-
[109.64952941, 43.28758824, 36.27439706],
988-
]),
989-
1e-8,
990-
));
991-
992-
let b = array![[1.1, 2.3, 4.7]];
993-
assert!(b.var_axis(Axis(0), 0.).all_close(&aview1(&[0., 0., 0.]), 1e-12));
994-
assert!(b.var_axis(Axis(1), 0.).all_close(&aview1(&[2.24]), 1e-12));
995-
996-
let c = array![[], []];
997-
assert_eq!(c.var_axis(Axis(0), 0.), aview1(&[]));
998-
999-
let d = array![1.1, 2.7, 3.5, 4.9];
1000-
assert!(d.var_axis(Axis(0), 0.).all_close(&aview0(&1.8875), 1e-12));
1001-
}
1002-
1003-
#[test]
1004-
fn std_axis() {
1005-
let a = array![
1006-
[
1007-
[ 0.22935481, 0.08030619, 0.60827517, 0.73684379],
1008-
[ 0.90339851, 0.82859436, 0.64020362, 0.2774583 ],
1009-
[ 0.44485313, 0.63316367, 0.11005111, 0.08656246]
1010-
],
1011-
[
1012-
[ 0.28924665, 0.44082454, 0.59837736, 0.41014531],
1013-
[ 0.08382316, 0.43259439, 0.1428889 , 0.44830176],
1014-
[ 0.51529756, 0.70111616, 0.20799415, 0.91851457]
1015-
],
1016-
];
1017-
assert!(a.std_axis(Axis(0), 1.5).all_close(
1018-
&aview2(&[
1019-
[ 0.05989184, 0.36051836, 0.00989781, 0.32669847],
1020-
[ 0.81957535, 0.39599997, 0.49731472, 0.17084346],
1021-
[ 0.07044443, 0.06795249, 0.09794304, 0.83195211],
1022-
]),
1023-
1e-4,
1024-
));
1025-
assert!(a.std_axis(Axis(1), 1.7).all_close(
1026-
&aview2(&[
1027-
[ 0.42698655, 0.48139215, 0.36874991, 0.41458724],
1028-
[ 0.26769097, 0.18941435, 0.30555015, 0.35118674],
1029-
]),
1030-
1e-8,
1031-
));
1032-
assert!(a.std_axis(Axis(2), 2.3).all_close(
1033-
&aview2(&[
1034-
[ 0.41117907, 0.37130425, 0.35332388],
1035-
[ 0.16905862, 0.25304841, 0.39978276],
1036-
]),
1037-
1e-8,
1038-
));
1039-
1040-
let b = array![[100000., 1., 0.01]];
1041-
assert!(b.std_axis(Axis(0), 0.).all_close(&aview1(&[0., 0., 0.]), 1e-12));
1042-
assert!(
1043-
b.std_axis(Axis(1), 0.).all_close(&aview1(&[47140.214021552769]), 1e-6),
1044-
);
1045-
1046-
let c = array![[], []];
1047-
assert_eq!(c.std_axis(Axis(0), 0.), aview1(&[]));
1048-
}
1049-
1050-
#[test]
1051-
#[should_panic]
1052-
fn var_axis_negative_ddof() {
1053-
let a = array![1., 2., 3.];
1054-
a.var_axis(Axis(0), -1.);
1055-
}
1056-
1057-
#[test]
1058-
#[should_panic]
1059-
fn var_axis_too_large_ddof() {
1060-
let a = array![1., 2., 3.];
1061-
a.var_axis(Axis(0), 4.);
1062-
}
1063-
1064-
#[test]
1065-
fn var_axis_nan_ddof() {
1066-
let a = Array2::<f64>::zeros((2, 3));
1067-
let v = a.var_axis(Axis(1), ::std::f64::NAN);
1068-
assert_eq!(v.shape(), &[2]);
1069-
v.mapv(|x| assert!(x.is_nan()));
1070-
}
1071-
1072-
#[test]
1073-
fn var_axis_empty_axis() {
1074-
let a = Array2::<f64>::zeros((2, 0));
1075-
let v = a.var_axis(Axis(1), 0.);
1076-
assert_eq!(v.shape(), &[2]);
1077-
v.mapv(|x| assert!(x.is_nan()));
1078-
}
1079-
1080-
#[test]
1081-
#[should_panic]
1082-
fn std_axis_bad_dof() {
1083-
let a = array![1., 2., 3.];
1084-
a.std_axis(Axis(0), 4.);
1085-
}
1086-
1087-
#[test]
1088-
fn std_axis_empty_axis() {
1089-
let a = Array2::<f64>::zeros((2, 0));
1090-
let v = a.std_axis(Axis(1), 0.);
1091-
assert_eq!(v.shape(), &[2]);
1092-
v.mapv(|x| assert!(x.is_nan()));
1093-
}
1094-
1095928
#[test]
1096929
fn iter_size_hint()
1097930
{

‎tests/numeric.rs‎

Lines changed: 170 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
11
extern crate approx;
22
use std::f64;
3-
use ndarray::{Array1, array};
3+
use ndarray::{array, Axis, aview1, aview2, aview0, arr0, arr1, arr2, Array, Array1, Array2, Array3};
44
use approx::abs_diff_eq;
55

66
#[test]
@@ -32,4 +32,172 @@ fn test_mean_with_array_of_floats() {
3232
// Computed using NumPy
3333
let expected_mean = 0.5475494059146699;
3434
abs_diff_eq!(a.mean().unwrap(), expected_mean, epsilon = f64::EPSILON);
35-
}
35+
}
36+
37+
#[test]
38+
fn sum_mean()
39+
{
40+
let a = arr2(&[[1., 2.], [3., 4.]]);
41+
assert_eq!(a.sum_axis(Axis(0)), arr1(&[4., 6.]));
42+
assert_eq!(a.sum_axis(Axis(1)), arr1(&[3., 7.]));
43+
assert_eq!(a.mean_axis(Axis(0)), Some(arr1(&[2., 3.])));
44+
assert_eq!(a.mean_axis(Axis(1)), Some(arr1(&[1.5, 3.5])));
45+
assert_eq!(a.sum_axis(Axis(1)).sum_axis(Axis(0)), arr0(10.));
46+
assert_eq!(a.view().mean_axis(Axis(1)).unwrap(), aview1(&[1.5, 3.5]));
47+
assert_eq!(a.sum(), 10.);
48+
}
49+
50+
#[test]
51+
fn sum_mean_empty() {
52+
assert_eq!(Array3::<f32>::ones((2, 0, 3)).sum(), 0.);
53+
assert_eq!(Array1::<f32>::ones(0).sum_axis(Axis(0)), arr0(0.));
54+
assert_eq!(
55+
Array3::<f32>::ones((2, 0, 3)).sum_axis(Axis(1)),
56+
Array::zeros((2, 3)),
57+
);
58+
let a = Array1::<f32>::ones(0).mean_axis(Axis(0));
59+
assert_eq!(a, None);
60+
let a = Array3::<f32>::ones((2, 0, 3)).mean_axis(Axis(1));
61+
assert_eq!(a, None);
62+
}
63+
64+
#[test]
65+
fn var_axis() {
66+
let a = array![
67+
[
68+
[-9.76, -0.38, 1.59, 6.23],
69+
[-8.57, -9.27, 5.76, 6.01],
70+
[-9.54, 5.09, 3.21, 6.56],
71+
],
72+
[
73+
[ 8.23, -9.63, 3.76, -3.48],
74+
[-5.46, 5.86, -2.81, 1.35],
75+
[-1.08, 4.66, 8.34, -0.73],
76+
],
77+
];
78+
assert!(a.var_axis(Axis(0), 1.5).all_close(
79+
&aview2(&[
80+
[3.236401e+02, 8.556250e+01, 4.708900e+00, 9.428410e+01],
81+
[9.672100e+00, 2.289169e+02, 7.344490e+01, 2.171560e+01],
82+
[7.157160e+01, 1.849000e-01, 2.631690e+01, 5.314410e+01]
83+
]),
84+
1e-4,
85+
));
86+
assert!(a.var_axis(Axis(1), 1.7).all_close(
87+
&aview2(&[
88+
[0.61676923, 80.81092308, 6.79892308, 0.11789744],
89+
[75.19912821, 114.25235897, 48.32405128, 9.03020513],
90+
]),
91+
1e-8,
92+
));
93+
assert!(a.var_axis(Axis(2), 2.3).all_close(
94+
&aview2(&[
95+
[ 79.64552941, 129.09663235, 95.98929412],
96+
[109.64952941, 43.28758824, 36.27439706],
97+
]),
98+
1e-8,
99+
));
100+
101+
let b = array![[1.1, 2.3, 4.7]];
102+
assert!(b.var_axis(Axis(0), 0.).all_close(&aview1(&[0., 0., 0.]), 1e-12));
103+
assert!(b.var_axis(Axis(1), 0.).all_close(&aview1(&[2.24]), 1e-12));
104+
105+
let c = array![[], []];
106+
assert_eq!(c.var_axis(Axis(0), 0.), aview1(&[]));
107+
108+
let d = array![1.1, 2.7, 3.5, 4.9];
109+
assert!(d.var_axis(Axis(0), 0.).all_close(&aview0(&1.8875), 1e-12));
110+
}
111+
112+
#[test]
113+
fn std_axis() {
114+
let a = array![
115+
[
116+
[ 0.22935481, 0.08030619, 0.60827517, 0.73684379],
117+
[ 0.90339851, 0.82859436, 0.64020362, 0.2774583 ],
118+
[ 0.44485313, 0.63316367, 0.11005111, 0.08656246]
119+
],
120+
[
121+
[ 0.28924665, 0.44082454, 0.59837736, 0.41014531],
122+
[ 0.08382316, 0.43259439, 0.1428889 , 0.44830176],
123+
[ 0.51529756, 0.70111616, 0.20799415, 0.91851457]
124+
],
125+
];
126+
assert!(a.std_axis(Axis(0), 1.5).all_close(
127+
&aview2(&[
128+
[ 0.05989184, 0.36051836, 0.00989781, 0.32669847],
129+
[ 0.81957535, 0.39599997, 0.49731472, 0.17084346],
130+
[ 0.07044443, 0.06795249, 0.09794304, 0.83195211],
131+
]),
132+
1e-4,
133+
));
134+
assert!(a.std_axis(Axis(1), 1.7).all_close(
135+
&aview2(&[
136+
[ 0.42698655, 0.48139215, 0.36874991, 0.41458724],
137+
[ 0.26769097, 0.18941435, 0.30555015, 0.35118674],
138+
]),
139+
1e-8,
140+
));
141+
assert!(a.std_axis(Axis(2), 2.3).all_close(
142+
&aview2(&[
143+
[ 0.41117907, 0.37130425, 0.35332388],
144+
[ 0.16905862, 0.25304841, 0.39978276],
145+
]),
146+
1e-8,
147+
));
148+
149+
let b = array![[100000., 1., 0.01]];
150+
assert!(b.std_axis(Axis(0), 0.).all_close(&aview1(&[0., 0., 0.]), 1e-12));
151+
assert!(
152+
b.std_axis(Axis(1), 0.).all_close(&aview1(&[47140.214021552769]), 1e-6),
153+
);
154+
155+
let c = array![[], []];
156+
assert_eq!(c.std_axis(Axis(0), 0.), aview1(&[]));
157+
}
158+
159+
#[test]
160+
#[should_panic]
161+
fn var_axis_negative_ddof() {
162+
let a = array![1., 2., 3.];
163+
a.var_axis(Axis(0), -1.);
164+
}
165+
166+
#[test]
167+
#[should_panic]
168+
fn var_axis_too_large_ddof() {
169+
let a = array![1., 2., 3.];
170+
a.var_axis(Axis(0), 4.);
171+
}
172+
173+
#[test]
174+
fn var_axis_nan_ddof() {
175+
let a = Array2::<f64>::zeros((2, 3));
176+
let v = a.var_axis(Axis(1), ::std::f64::NAN);
177+
assert_eq!(v.shape(), &[2]);
178+
v.mapv(|x| assert!(x.is_nan()));
179+
}
180+
181+
#[test]
182+
fn var_axis_empty_axis() {
183+
let a = Array2::<f64>::zeros((2, 0));
184+
let v = a.var_axis(Axis(1), 0.);
185+
assert_eq!(v.shape(), &[2]);
186+
v.mapv(|x| assert!(x.is_nan()));
187+
}
188+
189+
#[test]
190+
#[should_panic]
191+
fn std_axis_bad_dof() {
192+
let a = array![1., 2., 3.];
193+
a.std_axis(Axis(0), 4.);
194+
}
195+
196+
#[test]
197+
fn std_axis_empty_axis() {
198+
let a = Array2::<f64>::zeros((2, 0));
199+
let v = a.std_axis(Axis(1), 0.);
200+
assert_eq!(v.shape(), &[2]);
201+
v.mapv(|x| assert!(x.is_nan()));
202+
}
203+

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