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doctest: Fix doctest formatting with pydoctestplus
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8 files changed

+51
-52
lines changed

8 files changed

+51
-52
lines changed

‎nitime/analysis/coherence.py‎

Lines changed: 5 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -39,7 +39,6 @@ def __init__(self, input=None, method=None, unwrap_phases=False):
3939
Examples
4040
--------
4141
>>> import nitime.timeseries as ts
42-
>>> np.set_printoptions(precision=4) # for doctesting
4342
>>> t1 = ts.TimeSeries(data = np.arange(0,1024,1).reshape(2,512),
4443
... sampling_rate=np.pi)
4544
>>> c1 = CoherenceAnalyzer(t1)
@@ -48,11 +47,11 @@ def __init__(self, input=None, method=None, unwrap_phases=False):
4847
>>> c1.method['this_method']
4948
'welch'
5049
>>> c1.coherence[0,1]
51-
array([ 0.9024, 0.9027, 0.9652, 0.9433, 0.9297, 0.9213, 0.9161,
52-
0.9126, 0.9102, 0.9085, 0.9072, 0.9063, 0.9055, 0.905 ,
53-
0.9045, 0.9041, 0.9038, 0.9036, 0.9034, 0.9032, 0.9031,
54-
0.9029, 0.9028, 0.9027, 0.9027, 0.9026, 0.9026, 0.9025,
55-
0.9025, 0.9025, 0.9025, 0.9026, 1. ])
50+
array([0.9024, 0.9027, 0.9652, 0.9433, 0.9297, 0.9213, 0.9161, 0.9126,
51+
0.9102, 0.9085, 0.9072, 0.9063, 0.9055, 0.905 , 0.9045, 0.9041,
52+
0.9038, 0.9036, 0.9034, 0.9032, 0.9031, 0.9029, 0.9028, 0.9027,
53+
0.9027, 0.9026, 0.9026, 0.9025, 0.9025, 0.9025, 0.9025, 0.9026,
54+
1. ])
5655
>>> c1.phase[0,1]
5756
array([ 0. , -0.035 , -0.4839, -0.4073, -0.3373, -0.2828, -0.241 ,
5857
-0.2085, -0.1826, -0.1615, -0.144 , -0.1292, -0.1164, -0.1054,

‎nitime/analysis/correlation.py‎

Lines changed: 0 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -24,7 +24,6 @@ def __init__(self, input=None):
2424
2525
Examples
2626
--------
27-
>>> np.set_printoptions(precision=4) # for doctesting
2827
>>> t1 = ts.TimeSeries(data = np.sin(np.arange(0,
2928
... 10*np.pi,10*np.pi/100)).reshape(2,50),
3029
... sampling_rate=np.pi)

‎nitime/analysis/spectral.py‎

Lines changed: 6 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -43,7 +43,6 @@ def __init__(self, input=None, method=None, BW=None, adaptive=False,
4343
4444
Examples
4545
--------
46-
>>> np.set_printoptions(precision=4) # for doctesting
4746
>>> t1 = ts.TimeSeries(data = np.arange(0,1024,1).reshape(2,512),
4847
... sampling_rate=np.pi)
4948
>>> s1 = SpectralAnalyzer(t1)
@@ -53,13 +52,13 @@ def __init__(self, input=None, method=None, BW=None, adaptive=False,
5352
3.1415926535... Hz
5453
>>> f,s = s1.psd
5554
>>> f
56-
array([ 0. , 0.0491, 0.0982, 0.1473, 0.1963, 0.2454, 0.2945,
57-
0.3436, 0.3927, 0.4418, 0.4909, 0.54 , 0.589 , 0.6381,
58-
0.6872, 0.7363, 0.7854, 0.8345, 0.8836, 0.9327, 0.9817,
59-
1.0308, 1.0799, 1.129 , 1.1781, 1.2272, 1.2763, 1.3254,
60-
1.3744, 1.4235, 1.4726, 1.5217, 1.5708])
55+
array([0. , 0.0491, 0.0982, 0.1473, 0.1963, 0.2454, 0.2945, 0.3436,
56+
0.3927, 0.4418, 0.4909, 0.54 , 0.589 , 0.6381, 0.6872, 0.7363,
57+
0.7854, 0.8345, 0.8836, 0.9327, 0.9817, 1.0308, 1.0799, 1.129 ,
58+
1.1781, 1.2272, 1.2763, 1.3254, 1.3744, 1.4235, 1.4726, 1.5217,
59+
1.5708])
6160
>>> s[0,0] # doctest: +ELLIPSIS
62-
1128276.92538360...
61+
1128276.9253836009
6362
"""
6463
BaseAnalyzer.__init__(self, input)
6564

‎nitime/conftest.py‎

Lines changed: 7 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,7 @@
1+
import numpy as np
2+
import pytest
3+
4+
5+
@pytest.fixture(scope='session', autouse=True)
6+
def legacy_printoptions():
7+
np.set_printoptions(legacy='1.21', precision=4)

‎nitime/index_utils.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -44,9 +44,9 @@ def tri(N, M=None, k=0, dtype=float):
4444
[1, 1, 1, 1, 1]])
4545
4646
>>> np.tri(3, 5, -1)
47-
array([[ 0., 0., 0., 0., 0.],
48-
[ 1., 0., 0., 0., 0.],
49-
[ 1., 1., 0., 0., 0.]])
47+
array([[0., 0., 0., 0., 0.],
48+
[1., 0., 0., 0., 0.],
49+
[1., 1., 0., 0., 0.]])
5050
5151
"""
5252
if M is None: M = N

‎nitime/tests/test_timeseries.py‎

Lines changed: 8 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -131,10 +131,10 @@ def test_TimeArray_repr():
131131
"""
132132
>>> a = ts.TimeArray([1.1,2,3])
133133
>>> a
134-
TimeArray([ 1.1, 2. , 3. ], time_unit='s')
134+
TimeArray([1.1, 2. , 3. ], time_unit='s')
135135
>>> t = ts.TimeArray(a,time_unit='ms')
136136
>>> t
137-
TimeArray([ 1100., 2000., 3000.], time_unit='ms')
137+
TimeArray([1100., 2000., 3000.], time_unit='ms')
138138
>>> t[0]
139139
1100.0 ms
140140
"""
@@ -195,12 +195,12 @@ def test_TimeArray_convert_unit():
195195
>>> a = ts.TimeArray([1,2,3,4])
196196
>>> a.convert_unit('ms')
197197
>>> a
198-
TimeArray([ 1000., 2000., 3000., 4000.], time_unit='ms')
198+
TimeArray([1000., 2000., 3000., 4000.], time_unit='ms')
199199
>>> a.time_unit
200200
'ms'
201201
>>> b = ts.TimeArray([1,2,3,4],'s')
202202
>>> a==b
203-
array([ True, True, True, True], dtype=bool)
203+
array([ True, True, True, True])
204204
"""
205205

206206

@@ -431,13 +431,13 @@ def test_UniformTime_repr():
431431
>>> time1.sampling_rate
432432
1000.0 Hz
433433
>>> time1
434-
UniformTime([ 0., 1., 2.], time_unit='ms')
434+
UniformTime([0., 1., 2.], time_unit='ms')
435435
436436
>>> time2= ts.UniformTime(sampling_rate=1000,time_unit='s',length=3)
437437
>>> time2.sampling_rate
438438
1000.0 Hz
439439
>>> time2
440-
UniformTime([ 0. , 0.001, 0.002], time_unit='s')
440+
UniformTime([0. , 0.001, 0.002], time_unit='s')
441441
442442
>>> a = ts.UniformTime(length=5,sampling_rate=1,time_unit='ms')
443443
@@ -452,7 +452,7 @@ def test_UniformTime_repr():
452452
>>> b = ts.UniformTime(a,time_unit='s')
453453
454454
>>> b
455-
UniformTime([ 0., 1., 2., 3., 4.], time_unit='s')
455+
UniformTime([0., 1., 2., 3., 4.], time_unit='s')
456456
457457
>>> a = ts.UniformTime(length=1,sampling_rate=2)
458458
@@ -574,7 +574,7 @@ def test_TimeSeries_repr():
574574
3.0 Hz
575575
>>> tseries1 = ts.TimeSeries(data=[3,5,8],sampling_rate=3)
576576
>>> tseries1.time
577-
UniformTime([ 0. , 0.3333, 0.6667], time_unit='s')
577+
UniformTime([0. , 0.3333, 0.6667], time_unit='s')
578578
>>> tseries1.sampling_rate
579579
3.0 Hz
580580
>>> tseries1.sampling_interval

‎nitime/timeseries.py‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1107,7 +1107,7 @@ class UniformTime. Note that you can still also provide a different
11071107
11081108
>>> ts = TimeSeries([1,2,3],sampling_interval=0.25)
11091109
>>> ts.time
1110-
UniformTime([ 0. , 0.25, 0.5 ], time_unit='s')
1110+
UniformTime([0. , 0.25, 0.5 ], time_unit='s')
11111111
>>> ts.t0
11121112
0.0 s
11131113
>>> ts.sampling_rate
@@ -1117,7 +1117,7 @@ class UniformTime. Note that you can still also provide a different
11171117
11181118
>>> ts = TimeSeries([1,2,3],sampling_rate=2)
11191119
>>> ts.time
1120-
UniformTime([ 0. , 0.5, 1. ], time_unit='s')
1120+
UniformTime([0. , 0.5, 1. ], time_unit='s')
11211121
>>> ts.t0
11221122
0.0 s
11231123
>>> ts.sampling_interval
@@ -1129,7 +1129,7 @@ class UniformTime. Note that you can still also provide a different
11291129
>>> ts.data
11301130
array([1, 2, 3])
11311131
>>> ts.time
1132-
UniformTime([ 4.25, 4.75, 5.25], time_unit='s')
1132+
UniformTime([4.25, 4.75, 5.25], time_unit='s')
11331133
>>> ts.t0
11341134
4.25 s
11351135
>>> ts.sampling_interval
@@ -1141,7 +1141,7 @@ class UniformTime. Note that you can still also provide a different
11411141
>>> ts.data
11421142
array([1, 2, 3])
11431143
>>> ts.time
1144-
UniformTime([ 4.25, 4.75, 5.25], time_unit='s')
1144+
UniformTime([4.25, 4.75, 5.25], time_unit='s')
11451145
>>> ts.t0
11461146
4.25 s
11471147
>>> ts.sampling_interval

‎nitime/utils.py‎

Lines changed: 18 additions & 23 deletions
Original file line numberDiff line numberDiff line change
@@ -1704,12 +1704,11 @@ def structured_rand_arr(size, sample_func=np.random.random,
17041704
Examples
17051705
--------
17061706
>>> np.random.seed(0) # for doctesting
1707-
>>> np.set_printoptions(precision=4) # for doctesting
17081707
>>> structured_rand_arr(4)
1709-
array([[ 0.5488, 0.7152, 0.6028, 0.5449],
1710-
[ 0.7152, 0.6459, 0.4376, 0.8918],
1711-
[ 0.6028, 0.4376, 0.7917, 0.5289],
1712-
[ 0.5449, 0.8918, 0.5289, 0.0871]])
1708+
array([[0.5488, 0.7152, 0.6028, 0.5449],
1709+
[0.7152, 0.6459, 0.4376, 0.8918],
1710+
[0.6028, 0.4376, 0.7917, 0.5289],
1711+
[0.5449, 0.8918, 0.5289, 0.0871]])
17131712
>>> structured_rand_arr(4,ltfac=-10,utfac=10,fill_diag=0.5)
17141713
array([[ 0.5 , 8.3262, 7.7816, 8.7001],
17151714
[-8.3262, 0.5 , 4.6148, 7.8053],
@@ -1765,17 +1764,16 @@ def symm_rand_arr(size, sample_func=np.random.random, fill_diag=None):
17651764
Examples
17661765
--------
17671766
>>> np.random.seed(0) # for doctesting
1768-
>>> np.set_printoptions(precision=4) # for doctesting
17691767
>>> symm_rand_arr(4)
1770-
array([[ 0.5488, 0.7152, 0.6028, 0.5449],
1771-
[ 0.7152, 0.6459, 0.4376, 0.8918],
1772-
[ 0.6028, 0.4376, 0.7917, 0.5289],
1773-
[ 0.5449, 0.8918, 0.5289, 0.0871]])
1768+
array([[0.5488, 0.7152, 0.6028, 0.5449],
1769+
[0.7152, 0.6459, 0.4376, 0.8918],
1770+
[0.6028, 0.4376, 0.7917, 0.5289],
1771+
[0.5449, 0.8918, 0.5289, 0.0871]])
17741772
>>> symm_rand_arr(4,fill_diag=4)
1775-
array([[ 4. , 0.8326, 0.7782, 0.87 ],
1776-
[ 0.8326, 4. , 0.4615, 0.7805],
1777-
[ 0.7782, 0.4615, 4. , 0.9447],
1778-
[ 0.87 , 0.7805, 0.9447, 4. ]])
1773+
array([[4. , 0.8326, 0.7782, 0.87 ],
1774+
[0.8326, 4. , 0.4615, 0.7805],
1775+
[0.7782, 0.4615, 4. , 0.9447],
1776+
[0.87 , 0.7805, 0.9447, 4. ]])
17791777
"""
17801778
return structured_rand_arr(size, sample_func, fill_diag=fill_diag)
17811779

@@ -1797,7 +1795,6 @@ def antisymm_rand_arr(size, sample_func=np.random.random):
17971795
Examples
17981796
--------
17991797
>>> np.random.seed(0) # for doctesting
1800-
>>> np.set_printoptions(precision=4) # for doctesting
18011798
>>> antisymm_rand_arr(4)
18021799
array([[ 0. , 0.7152, 0.6028, 0.5449],
18031800
[-0.7152, 0. , 0.4376, 0.8918],
@@ -1830,16 +1827,15 @@ def threshold_arr(cmat, threshold=0.0, threshold2=None):
18301827
18311828
Examples
18321829
--------
1833-
>>> np.set_printoptions(precision=4) # For doctesting
18341830
>>> a = np.linspace(0,0.2,5)
18351831
>>> a
1836-
array([ 0. , 0.05, 0.1 , 0.15, 0.2 ])
1832+
array([0. , 0.05, 0.1 , 0.15, 0.2 ])
18371833
>>> threshold_arr(a,0.1)
1838-
(array([3, 4]), array([ 0.15, 0.2 ]))
1834+
(array([3, 4]), array([0.15, 0.2 ]))
18391835
18401836
With two thresholds:
18411837
>>> threshold_arr(a,0.1,0.2)
1842-
(array([0, 1]), array([ 0. , 0.05]))
1838+
(array([0, 1]), array([0. , 0.05]))
18431839
"""
18441840
# Select thresholds
18451841
if threshold2 is None:
@@ -1906,7 +1902,7 @@ def rescale_arr(arr, amin, amax):
19061902
>>> a = np.arange(5)
19071903
19081904
>>> rescale_arr(a,3,6)
1909-
array([ 3. , 3.75, 4.5 , 5.25, 6. ])
1905+
array([3. , 3.75, 4.5 , 5.25, 6. ])
19101906
"""
19111907

19121908
# old bounds
@@ -1941,16 +1937,15 @@ def minmax_norm(arr, mode='direct', folding_edges=None):
19411937
19421938
Examples
19431939
--------
1944-
>>> np.set_printoptions(precision=4) # for doctesting
19451940
>>> a = np.linspace(0.3,0.8,4)
19461941
>>> minmax_norm(a)
1947-
array([ 0. , 0.3333, 0.6667, 1. ])
1942+
array([0. , 0.3333, 0.6667, 1. ])
19481943
>>> b = np.concatenate([np.linspace(-0.7,-0.3,3),
19491944
... np.linspace(0.3,0.8,3)])
19501945
>>> b
19511946
array([-0.7 , -0.5 , -0.3 , 0.3 , 0.55, 0.8 ])
19521947
>>> minmax_norm(b,'folding',[-0.3,0.3])
1953-
array([ 0.8, 0.4, 0. , 0. , 0.5, 1. ])
1948+
array([0.8, 0.4, 0. , 0. , 0.5, 1. ])
19541949
"""
19551950
if mode == 'direct':
19561951
return rescale_arr(arr, 0, 1)

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