77import nipype .interfaces .fsl .model as fsl
88from nipype .interfaces .fsl import no_fsl
99from pathlib import Path
10- from ....pipeline import engine as pe
10+ from ....pipeline import engine as pe
1111
1212
1313@pytest .mark .skipif (no_fsl (), reason = "fsl is not installed" )
1414def test_MultipleRegressDesign (tmpdir ):
15- designer = pe .Node (fsl .MultipleRegressDesign (), name = 'designer' , base_dir = str (tmpdir ))
15+ designer = pe .Node (
16+ fsl .MultipleRegressDesign (), name = "designer" , base_dir = str (tmpdir )
17+ )
1618 designer .inputs .regressors = dict (
1719 voice_stenght = [1 , 1 , 1 ], age = [0.2 , 0.4 , 0.5 ], BMI = [1 , - 1 , 2 ]
1820 )
1921 con1 = ["voice_and_age" , "T" , ["age" , "voice_stenght" ], [0.5 , 0.5 ]]
2022 con2 = ["just_BMI" , "T" , ["BMI" ], [1 ]]
21- designer .inputs .contrasts = [con1 , con2 , ["con3" , "F" , [con1 , con2 ]], ["con4" , "F" , [con2 ]]]
23+ designer .inputs .contrasts = [
24+ con1 ,
25+ con2 ,
26+ ["con3" , "F" , [con1 , con2 ]],
27+ ["con4" , "F" , [con2 ]],
28+ ]
2229 res = designer .run ()
2330 outputs = res .outputs .get_traitsfree ()
2431
@@ -27,7 +34,9 @@ def test_MultipleRegressDesign(tmpdir):
2734
2835 expected_content = {}
2936
30- expected_content ["design_mat" ] = """/NumWaves 3
37+ expected_content [
38+ "design_mat"
39+ ] = """/NumWaves 3
3140/NumPoints 3
3241/PPheights 3.000000e+00 5.000000e-01 1.000000e+00
3342
@@ -37,7 +46,9 @@ def test_MultipleRegressDesign(tmpdir):
37462.000000e+00 5.000000e-01 1.000000e+00
3847"""
3948
40- expected_content ["design_con" ] = """/ContrastName1 voice_and_age
49+ expected_content [
50+ "design_con"
51+ ] = """/ContrastName1 voice_and_age
4152/ContrastName2 just_BMI
4253/NumWaves 3
4354/NumContrasts 2
@@ -49,15 +60,19 @@ def test_MultipleRegressDesign(tmpdir):
49601.000000e+00 0.000000e+00 0.000000e+00
5061"""
5162
52- expected_content ["design_fts" ] = """/NumWaves 2
63+ expected_content [
64+ "design_fts"
65+ ] = """/NumWaves 2
5366/NumContrasts 2
5467
5568/Matrix
56691 1
57700 1
5871"""
5972
60- expected_content ["design_grp" ] = """/NumWaves 1
73+ expected_content [
74+ "design_grp"
75+ ] = """/NumWaves 1
6176/NumPoints 3
6277
6378/Matrix
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