Unit tests for featdesign module. Still need to test voxelwise EVs

tests/test_featdesign.py

+#!/usr/bin/env python
+#
+# test_featdesign.py -
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+"""Test data sets (in testdata/test_feat) were generated with FSL 5.0.9, and
+then 'cleaned' to remove unnecessary files and reduce size, with the following
+commands:
+
+First level analyses:
+
+    find . -name "*png" -delete
+    find . -name "*ppm" -delete
+    find . -name "*html" -delete
+    rm -r logs .files tsplot .ramp.gif
+    for f in `find . -name "*nii.gz"`; do
+        echo $f > $f
+    done
+
+Second level analyses:
+
+    find . -name "*png" -delete
+    find . -name "*ppm" -delete
+    find . -name "*html" -delete
+    rm -r logs .files  .ramp.gif
+    for f in `find . -name "*nii.gz"`; do
+        echo $f > $f
+    done
+
+Second level cope?.feats:
+    rm -r logs .files tsplot .ramp.gif
+    
+
+
+`1stlevel_1.feat`
+
+ - 45 time points
+ - 10 EVs in total:
+   - 2 stimulus EVs
+   - 2 temporal derivative EVs
+   - 6 Standard motion parameters
+ - 2 contrasts - one on each stimulus EV
+
+`1stlevel_2.feat`
+
+ - 45 time points
+ - 11 EVs in total:
+   - 2 stimulus EVs
+   - 2 temporal derivative EVs
+   - 1 voxelwise EV
+   - 6 Standard motion parameters
+ - 2 contrasts - one on each stimulus EV 
+
+`1stlevel_3.feat`
+ - 45 time points
+ - 32 EVs in total:
+   - 2 stimulus EVs
+   - 1 Temporal derivative EV on first
+   - 2 gamma basis functions on second
+   - 24 Standard+extended motion parameters
+   - 2 Confound EVs
+   - 1 Voxelwise confound EV
+ - 2 contrasts - one on each stimulus EV
+
+`2ndlevel_1.feat`
+ - Three inputs
+ - Two copes
+ - One main EV - group average
+
+`2ndlevel_1.feat`
+ - Three inputs
+ - Two copes
+ - One main EV - group average
+ - One voxelwise EV
+"""
+
+
+import os.path as op
+
+import pytest
+
+import fsl.data.featdesign   as featdesign
+import fsl.data.featanalysis as featanalysis
+
+
+datadir = op.join(op.dirname(__file__), 'testdata', 'test_feat')
+
+
+
+def test_FeatFSFDesign():
+
+    featdirs = ['1stlevel_1.feat', '1stlevel_2.feat', '1stlevel_3.feat',
+                '2ndlevel_1.gfeat', '2ndlevel_2.gfeat']
+    nevs     = [10, 11, 32, 1, 2]
+    shapes   = [(45, 10), (45, 11), (45, 32), (3, 1), (3, 2)]    
+
+    for featdir, nev, shape in zip(featdirs, nevs, shapes):
+        featdir  = op.join(datadir, featdir)
+        settings = featanalysis.loadSettings(featdir)
+
+        # We can't load the voxelwise EVs
+        # here, because all of the .nii.gz
+        # files in the test directory are
+        # stubs.
+        # 
+        # See the test_firstLevelVoxelwiseEV
+        # function
+        des = featdesign.FEATFSFDesign(featdir,
+                                       loadVoxelwiseEVs=False)
+
+        # Can also specify the design.fsf settings
+        featdesign.FEATFSFDesign(featdir,
+                                 settings=settings,
+                                 loadVoxelwiseEVs=False)
+
+        assert len(des.getEVs()) == nev
+        assert des.getDesign().shape == shape
+        assert des.getDesign((10, 10, 3)).shape == shape
+
+
+def test_getFirstLevelEVs_1():
+    featdir  = op.join(datadir, '1stlevel_1.feat')
+    settings = featanalysis.loadSettings(featdir)
+    matrix   = featdesign.loadDesignMat(op.join(featdir, 'design.mat'))
+
+    expected = [(featdesign.NormalEV,             {'index' : 0, 'origIndex' : 0}),
+                (featdesign.TemporalDerivativeEV, {'index' : 1}),
+                (featdesign.NormalEV,             {'index' : 2, 'origIndex' : 1}),
+                (featdesign.TemporalDerivativeEV, {'index' : 3}),
+                (featdesign.MotionParameterEV,    {'index' : 4, 'motionIndex' : 0}),
+                (featdesign.MotionParameterEV,    {'index' : 5, 'motionIndex' : 1}),
+                (featdesign.MotionParameterEV,    {'index' : 6, 'motionIndex' : 2}),
+                (featdesign.MotionParameterEV,    {'index' : 7, 'motionIndex' : 3}),
+                (featdesign.MotionParameterEV,    {'index' : 8, 'motionIndex' : 4}),
+                (featdesign.MotionParameterEV,    {'index' : 9, 'motionIndex' : 5})]
+
+    evs = featdesign.getFirstLevelEVs(featdir, settings, matrix)
+    assert len(evs) == 10
+
+    for i, (evtype, atts) in enumerate(expected):
+
+        assert isinstance(evs[i], evtype)
+        for k, v in atts.items():
+            assert getattr(evs[i], k) == v
+
+
+def test_getFirstLevelEVs_2():
+    featdir  = op.join(datadir, '1stlevel_2.feat')
+    settings = featanalysis.loadSettings(featdir)
+    matrix   = featdesign.loadDesignMat(op.join(featdir, 'design.mat'))
+
+    expected = [(featdesign.NormalEV,             {'index' : 0, 'origIndex' : 0}),
+                (featdesign.TemporalDerivativeEV, {'index' : 1}),
+                (featdesign.NormalEV,             {'index' : 2, 'origIndex' : 1}),
+                (featdesign.TemporalDerivativeEV, {'index' : 3}),
+                (featdesign.VoxelwiseEV,          {'index' : 4, 'origIndex' : 2}),
+                (featdesign.MotionParameterEV,    {'index' : 5,  'motionIndex' : 0}),
+                (featdesign.MotionParameterEV,    {'index' : 6,  'motionIndex' : 1}),
+                (featdesign.MotionParameterEV,    {'index' : 7,  'motionIndex' : 2}),
+                (featdesign.MotionParameterEV,    {'index' : 8,  'motionIndex' : 3}),
+                (featdesign.MotionParameterEV,    {'index' : 9,  'motionIndex' : 4}),
+                (featdesign.MotionParameterEV,    {'index' : 10, 'motionIndex' : 5})]
+
+    evs = featdesign.getFirstLevelEVs(featdir, settings, matrix)
+    assert len(evs) == 11
+
+    for i, (evtype, atts) in enumerate(expected):
+
+        assert isinstance(evs[i], evtype)
+        for k, v in atts.items():
+            assert getattr(evs[i], k) == v
+
+
+def test_getFirstLevelEVs_3():
+    featdir  = op.join(datadir, '1stlevel_3.feat')
+    settings = featanalysis.loadSettings(featdir)
+    matrix   = featdesign.loadDesignMat(op.join(featdir, 'design.mat'))
+
+    expected = [(featdesign.NormalEV,             {'index' : 0, 'origIndex' : 0}),
+                (featdesign.TemporalDerivativeEV, {'index' : 1}),
+                (featdesign.NormalEV,             {'index' : 2, 'origIndex' : 1}),
+                (featdesign.BasisFunctionEV,      {'index' : 3}),
+                (featdesign.BasisFunctionEV,      {'index' : 4}),
+                (featdesign.VoxelwiseConfoundEV,  {'index' : 5, 'voxIndex'     : 0}),
+                (featdesign.MotionParameterEV,    {'index' : 6,  'motionIndex' : 0}),
+                (featdesign.MotionParameterEV,    {'index' : 7,  'motionIndex' : 1}),
+                (featdesign.MotionParameterEV,    {'index' : 8,  'motionIndex' : 2}),
+                (featdesign.MotionParameterEV,    {'index' : 9,  'motionIndex' : 3}),
+                (featdesign.MotionParameterEV,    {'index' : 10, 'motionIndex' : 4}),
+                (featdesign.MotionParameterEV,    {'index' : 11, 'motionIndex' : 5}),
+                (featdesign.MotionParameterEV,    {'index' : 12, 'motionIndex' : 6}),
+                (featdesign.MotionParameterEV,    {'index' : 13, 'motionIndex' : 7}),
+                (featdesign.MotionParameterEV,    {'index' : 14, 'motionIndex' : 8}),
+                (featdesign.MotionParameterEV,    {'index' : 15, 'motionIndex' : 9}),
+                (featdesign.MotionParameterEV,    {'index' : 16, 'motionIndex' : 10}),
+                (featdesign.MotionParameterEV,    {'index' : 17, 'motionIndex' : 11}),
+                (featdesign.MotionParameterEV,    {'index' : 18, 'motionIndex' : 12}),
+                (featdesign.MotionParameterEV,    {'index' : 19, 'motionIndex' : 13}),
+                (featdesign.MotionParameterEV,    {'index' : 20, 'motionIndex' : 14}),
+                (featdesign.MotionParameterEV,    {'index' : 21, 'motionIndex' : 15}),
+                (featdesign.MotionParameterEV,    {'index' : 22, 'motionIndex' : 16}),
+                (featdesign.MotionParameterEV,    {'index' : 23, 'motionIndex' : 17}),
+                (featdesign.MotionParameterEV,    {'index' : 24, 'motionIndex' : 18}),
+                (featdesign.MotionParameterEV,    {'index' : 25, 'motionIndex' : 19}),
+                (featdesign.MotionParameterEV,    {'index' : 26, 'motionIndex' : 20}),
+                (featdesign.MotionParameterEV,    {'index' : 27, 'motionIndex' : 21}),
+                (featdesign.MotionParameterEV,    {'index' : 28, 'motionIndex' : 22}),
+                (featdesign.MotionParameterEV,    {'index' : 29, 'motionIndex' : 23}),
+                (featdesign.ConfoundEV,           {'index' : 30, 'confIndex'   : 0}),
+                (featdesign.ConfoundEV,           {'index' : 31, 'confIndex'   : 1})]
+    
+
+    evs = featdesign.getFirstLevelEVs(featdir, settings, matrix)
+    
+    assert len(evs) == 32
+
+    for i, (evtype, atts) in enumerate(expected):
+
+        print(i, evs[i])
+
+        assert isinstance(evs[i], evtype)
+        for k, v in atts.items():
+            assert getattr(evs[i], k) == v
+
+
+def test_getHigherLevelEVs_1():
+
+    featdir  = op.join(datadir, '2ndlevel_1.gfeat')
+    settings = featanalysis.loadSettings(featdir)
+    matrix   = featdesign.loadDesignMat(op.join(featdir, 'design.mat'))
+
+    evs = featdesign.getHigherLevelEVs(featdir, settings, matrix)
+
+    assert len(evs) == 1
+    assert isinstance(evs[0], featdesign.NormalEV)
+    assert evs[0].index     == 0
+    assert evs[0].origIndex == 0
+ 
+    
+
+
+def test_getHigherLevelEVs_2():
+
+    featdir  = op.join(datadir, '2ndlevel_2.gfeat')
+    settings = featanalysis.loadSettings(featdir)
+    matrix   = featdesign.loadDesignMat(op.join(featdir, 'design.mat'))
+
+    evs = featdesign.getHigherLevelEVs(featdir, settings, matrix)
+
+    assert len(evs) == 2
+    assert isinstance(evs[0], featdesign.NormalEV)
+    assert evs[0].index     == 0
+    assert evs[0].origIndex == 0
+    assert isinstance(evs[1], featdesign.VoxelwiseEV)
+
+
+
+def test_loadDesignMat():
+
+    analyses = ['1stlevel_1.feat', '1stlevel_2.feat', '1stlevel_3.feat',
+                '2ndlevel_1.gfeat', '2ndlevel_2.gfeat']
+    shapes   = [(45, 10), (45, 11), (45, 32), (3, 1), (3, 2)]
+
+    for analysis, shape in zip(analyses, shapes):
+        featdir = op.join(datadir, analysis)
+        fname   = op.join(featdir, 'design.mat')
+        mat     = featdesign.loadDesignMat(fname)
+
+        assert mat.shape == shape
+
+    nonfile = op.join(datadir, 'non-existent-file')
+    badfile = op.join(datadir, '1stlevel_1.feat', 'design.fsf') 
+    with pytest.raises(Exception):
+        featdesign.loadDesignMat(nonfile)
+
+    with pytest.raises(Exception):
+        featdesign.loadDesignMat(badfile) 

tests/testdata/test_feat/1stlevel_1.feat/absbrainthresh.txt

+1000.0

tests/testdata/test_feat/1stlevel_1.feat/cluster_mask_zstat1.nii.gz

+./cluster_mask_zstat1.nii.gz

tests/testdata/test_feat/1stlevel_1.feat/cluster_mask_zstat2.nii.gz

+./cluster_mask_zstat2.nii.gz

tests/testdata/test_feat/1stlevel_1.feat/cluster_zstat1.txt

+Cluster Index	Voxels	P	-log10(P)	Z-MAX	Z-MAX X (vox)	Z-MAX Y (vox)	Z-MAX Z (vox)	Z-COG X (vox)	Z-COG Y (vox)	Z-COG Z (vox)	COPE-MAX	COPE-MAX X (vox)	COPE-MAX Y (vox)	COPE-MAX Z (vox)	COPE-MEAN
+1	296	1.79e-27	26.7	6.03	34	10	1	31.4	12.3	1.72	612	34	10	1	143

tests/testdata/test_feat/1stlevel_1.feat/cluster_zstat1_std.txt

+Cluster Index	Voxels	P	-log10(P)	Z-MAX	Z-MAX X (mm)	Z-MAX Y (mm)	Z-MAX Z (mm)	Z-COG X (mm)	Z-COG Y (mm)	Z-COG Z (mm)	COPE-MAX	COPE-MAX X (mm)	COPE-MAX Y (mm)	COPE-MAX Z (mm)	COPE-MEAN
+1	296	1.79e-27	26.7	6.03	-8.41	-89.9	-2.42	3.01	-81.2	2.15	612	-8.41	-89.9	-2.42	143

tests/testdata/test_feat/1stlevel_1.feat/cluster_zstat2.txt

+Cluster Index	Voxels	P	-log10(P)	Z-MAX	Z-MAX X (vox)	Z-MAX Y (vox)	Z-MAX Z (vox)	Z-COG X (vox)	Z-COG Y (vox)	Z-COG Z (vox)	COPE-MAX	COPE-MAX X (vox)	COPE-MAX Y (vox)	COPE-MAX Z (vox)	COPE-MEAN
+5	271	7.77e-26	25.1	6.27	47	27	2	44.3	29.7	1.72	468	46	25	3	113
+4	169	1.53e-18	17.8	5.75	20	32	2	23.9	28.4	1.45	304	19	31	1	100
+3	24	0.000341	3.47	4.58	17	39	3	18.8	38.3	2.23	157	22	39	0	62
+2	19	0.00202	2.69	4.88	25	44	0	26.3	42.1	0	197	26	43	0	118
+1	13	0.0213	1.67	3.73	26	19	2	26.6	21.3	1.85	97.1	26	19	2	69.2

tests/testdata/test_feat/1stlevel_1.feat/cluster_zstat2_std.txt

+Cluster Index	Voxels	P	-log10(P)	Z-MAX	Z-MAX X (mm)	Z-MAX Y (mm)	Z-MAX Z (mm)	Z-COG X (mm)	Z-COG Y (mm)	Z-COG Z (mm)	COPE-MAX	COPE-MAX X (mm)	COPE-MAX Y (mm)	COPE-MAX Z (mm)	COPE-MEAN
+5	271	7.77e-26	25.1	6.27	-63.6	-21.8	4	-51.3	-11.2	1.84	468	-59.6	-29.9	10.8	113
+4	169	1.53e-18	17.8	5.75	55.4	-4.27	2.45	37.9	-18.1	-0.842	304	59.8	-8.19	-4.25	100
+3	24	0.000341	3.47	4.58	69.3	23	8.65	61.3	20.6	3.62	157	47.6	23.8	-11.3	62
+2	19	0.00202	2.69	4.88	35	43.8	-11.4	29.3	36.5	-11.2	197	30.5	39.9	-11.3	118
+1	13	0.0213	1.67	3.73	27.6	-55.1	3.43	25.3	-46.1	2.31	97.1	27.6	-55.1	3.43	69.2

tests/testdata/test_feat/1stlevel_1.feat/confoundevs.txt

+0  -0.000264589  0.000183168  0.0217952  -0.0424268  -0.0254739  
+0.00070214  -0.000526306  0.000397315  0.0337431  -0.0193044  -0.0283846  
+0.000498598  -0.000809397  0  0.0395197  -0.0131337  -0.0452989  
+0.000579988  -0.000221715  8.21135e-05  0.0258738  0.0348006  -0.0129759  
+0.000381893  -0.000506425  0  0.0167397  0.0709324  -0.0453051  
+0.000388283  -0.000809397  0  0.0215977  -0.00161064  -0.0651091  
+0.00028076  -0.000604851  0  0.0241783  -0.0191748  -0.0536596  
+0  -0.000155116  0  0.0128543  -0.0191748  -0.0452136  
+0.000384396  -7.84812e-05  0  0.00734347  0.021921  -0.0415896  
+0.000321737  -0.000393791  0  0.00375303  -0.0230888  -0.0415753  
+0  0.000111998  0  -0.000902616  0.0727951  -0.0415698  
+0.000215285  -0.000136386  0  -0.00282623  -0.0354858  -0.0415777  
+0.000261125  -9.06374e-05  0  0.000629449  -0.0731166  -0.0415577  
+0.000486193  -0.000133878  0  0.00314586  0.000714271  -0.0452225  
+5.40494e-05  -2.19574e-05  0  0.00489143  -0.0056629  0.0214406  
+0.000459199  0.0004553  -0.000374243  -0.031751  -0.075842  0.0214637  
+0.000347496  0.000667638  -0.000316943  -0.0241288  -0.0550503  0.052287  
+0.000153477  -2.19574e-05  -0.000196968  -0.0113862  -0.0806421  0.0129587  
+0.000459199  0.000326759  -0.000257516  -0.018521  -0.0673269  0.0310445  
+-0.00010422  -0.000709562  -0.000551959  -0.0343409  -0.0673334  0.0190272  
+-4.78084e-05  -0.000709562  -0.000167275  -0.00978313  -0.0746766  -0.00060184  
+0.000459199  -0.000265855  -8.30117e-05  -0.00650845  -0.0269721  -0.00502952  
+-7.98919e-06  -0.000265855  9.6357e-06  -0.00184664  0.000679341  0.000189414  
+8.2695e-05  7.07945e-05  9.6357e-06  0.00353303  -0.0269518  -0.00502371  
+0.000151626  -0.000265855  -9.28369e-05  -0.00184551  -0.0269531  -0.012929  
+0.000381967  -0.000265855  -4.45114e-07  0.00220544  -0.0269575  -0.00503093  
+0.000198744  0.000212547  -4.45114e-07  -0.00184187  -0.0334269  0.0113516  
+-7.04892e-05  -0.000265855  -0.000111352  -0.00183592  -0.0434752  -0.0156616  
+0.000118964  -0.000265855  -4.45114e-07  -0.00184005  -0.0223293  -0.00503604  
+0.000458349  -0.000265855  -4.45114e-07  0.0217036  -0.00490347  -0.00509171  
+0.000571088  0.000180565  -0.000332005  0.0027614  -0.0223381  -0.00508851  
+0.000362825  0.000104016  -4.45114e-07  -0.0050014  -0.0505434  -0.00502399  
+0.00036589  -7.31897e-05  3.36877e-05  0.00123403  -0.0879296  -0.0285882  
+0.000133338  -0.000211688  -0.000144184  -0.00941317  -0.0856607  -0.00688414  
+0.000177832  0.000215669  -0.000185755  -0.0128922  -0.0856624  0.0114737  
+-0.000130942  -8.65635e-05  -1.11437e-05  -0.0021262  -0.0156379  -0.0286166  
+4.3281e-05  0.000387841  -0.00013645  -0.00962933  -0.0459189  0.0222458  
+-2.70728e-05  0.000729944  -0.000153679  -0.0179646  -0.0459249  0.0222224  
+4.3281e-05  0.000247161  -0.000452448  -0.0306068  -0.0621157  0.00586292  
+0.000128363  0.000237582  -0.00027413  -0.0180748  -0.065616  -0.00337989  
+4.3281e-05  0.000239086  -0.000195342  -0.018503  -0.0773948  -0.0033793  
+0.00038521  0.000105191  -0.000219467  -0.0197604  -0.0525178  -0.00335665  
+0.000186606  -0.000411083  -0.000184065  -0.0228653  -0.059242  -0.00333508  
+0.000446345  -0.000305936  -0.000125382  -0.0135317  -0.0429802  0.00123055  
+0.000197933  -0.000176617  -0.000408  -0.0193382  -0.0681025  1.65356e-05  

tests/testdata/test_feat/1stlevel_1.feat/design.con

+/ContrastName1	auditory 
+/ContrastName2	visual 
+/NumWaves	10
+/NumContrasts	2
+/PPheights		1.470856e+00	1.389712e+00
+/RequiredEffect		3.840	3.963
+
+/Matrix
+1.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 
+0.000000e+00 0.000000e+00 1.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 

tests/testdata/test_feat/1stlevel_1.feat/design.frf

+1
+1
+2
+2
+3
+3
+3
+3
+3
+3

tests/testdata/test_feat/1stlevel_1.feat/design.fsf

+
+# FEAT version number
+set fmri(version) 6.00
+
+# Are we in MELODIC?
+set fmri(inmelodic) 0
+
+# Analysis level
+# 1 : First-level analysis
+# 2 : Higher-level analysis
+set fmri(level) 1
+
+# Which stages to run
+# 0 : No first-level analysis (registration and/or group stats only)
+# 7 : Full first-level analysis
+# 1 : Pre-processing
+# 2 : Statistics
+set fmri(analysis) 7
+
+# Use relative filenames
+set fmri(relative_yn) 0
+
+# Balloon help
+set fmri(help_yn) 1
+
+# Run Featwatcher
+set fmri(featwatcher_yn) 1
+
+# Cleanup first-level standard-space images
+set fmri(sscleanup_yn) 0
+
+# Output directory
+set fmri(outputdir) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/fmri"
+
+# TR(s)
+set fmri(tr) 3.000000 
+
+# Total volumes
+set fmri(npts) 45
+
+# Delete volumes
+set fmri(ndelete) 0
+
+# Perfusion tag/control order
+set fmri(tagfirst) 1
+
+# Number of first-level analyses
+set fmri(multiple) 3
+
+# Higher-level input type
+# 1 : Inputs are lower-level FEAT directories
+# 2 : Inputs are cope images from FEAT directories
+set fmri(inputtype) 2
+
+# Carry out pre-stats processing?
+set fmri(filtering_yn) 1
+
+# Brain/background threshold, %
+set fmri(brain_thresh) 10
+
+# Critical z for design efficiency calculation
+set fmri(critical_z) 5.3
+
+# Noise level
+set fmri(noise) 0.66
+
+# Noise AR(1)
+set fmri(noisear) 0.34
+
+# Motion correction
+# 0 : None
+# 1 : MCFLIRT
+set fmri(mc) 1
+
+# Spin-history (currently obsolete)
+set fmri(sh_yn) 0
+
+# B0 fieldmap unwarping?
+set fmri(regunwarp_yn) 0
+
+# EPI dwell time (ms)
+set fmri(dwell) 0.7
+
+# EPI TE (ms)
+set fmri(te) 35
+
+# % Signal loss threshold
+set fmri(signallossthresh) 10
+
+# Unwarp direction
+set fmri(unwarp_dir) y-
+
+# Slice timing correction
+# 0 : None
+# 1 : Regular up (0, 1, 2, 3, ...)
+# 2 : Regular down
+# 3 : Use slice order file
+# 4 : Use slice timings file
+# 5 : Interleaved (0, 2, 4 ... 1, 3, 5 ... )
+set fmri(st) 0
+
+# Slice timings file
+set fmri(st_file) ""
+
+# BET brain extraction
+set fmri(bet_yn) 1
+
+# Spatial smoothing FWHM (mm)
+set fmri(smooth) 5
+
+# Intensity normalization
+set fmri(norm_yn) 0
+
+# Perfusion subtraction
+set fmri(perfsub_yn) 0
+
+# Highpass temporal filtering
+set fmri(temphp_yn) 1
+
+# Lowpass temporal filtering
+set fmri(templp_yn) 0
+
+# MELODIC ICA data exploration
+set fmri(melodic_yn) 0
+
+# Carry out main stats?
+set fmri(stats_yn) 1
+
+# Carry out prewhitening?
+set fmri(prewhiten_yn) 1
+
+# Add motion parameters to model
+# 0 : No
+# 1 : Yes
+set fmri(motionevs) 1
+set fmri(motionevsbeta) ""
+set fmri(scriptevsbeta) ""
+
+# Robust outlier detection in FLAME?
+set fmri(robust_yn) 0
+
+# Higher-level modelling
+# 3 : Fixed effects
+# 0 : Mixed Effects: Simple OLS
+# 2 : Mixed Effects: FLAME 1
+# 1 : Mixed Effects: FLAME 1+2
+set fmri(mixed_yn) 2
+
+# Number of EVs
+set fmri(evs_orig) 2
+set fmri(evs_real) 4
+set fmri(evs_vox) 0
+
+# Number of contrasts
+set fmri(ncon_orig) 2
+set fmri(ncon_real) 2
+
+# Number of F-tests
+set fmri(nftests_orig) 0
+set fmri(nftests_real) 0
+
+# Add constant column to design matrix? (obsolete)
+set fmri(constcol) 0
+
+# Carry out post-stats steps?
+set fmri(poststats_yn) 1
+
+# Pre-threshold masking?
+set fmri(threshmask) ""
+
+# Thresholding
+# 0 : None
+# 1 : Uncorrected
+# 2 : Voxel
+# 3 : Cluster
+set fmri(thresh) 3
+
+# P threshold
+set fmri(prob_thresh) 0.05
+
+# Z threshold
+set fmri(z_thresh) 2.3
+
+# Z min/max for colour rendering
+# 0 : Use actual Z min/max
+# 1 : Use preset Z min/max
+set fmri(zdisplay) 0
+
+# Z min in colour rendering
+set fmri(zmin) 2
+
+# Z max in colour rendering
+set fmri(zmax) 8
+
+# Colour rendering type
+# 0 : Solid blobs
+# 1 : Transparent blobs
+set fmri(rendertype) 1
+
+# Background image for higher-level stats overlays
+# 1 : Mean highres
+# 2 : First highres
+# 3 : Mean functional
+# 4 : First functional
+# 5 : Standard space template
+set fmri(bgimage) 1
+
+# Create time series plots
+set fmri(tsplot_yn) 1
+
+# Registration to initial structural
+set fmri(reginitial_highres_yn) 1
+
+# Search space for registration to initial structural
+# 0   : No search
+# 90  : Normal search
+# 180 : Full search
+set fmri(reginitial_highres_search) 90
+
+# Degrees of Freedom for registration to initial structural
+set fmri(reginitial_highres_dof) 3
+
+# Registration to main structural
+set fmri(reghighres_yn) 1
+
+# Search space for registration to main structural
+# 0   : No search
+# 90  : Normal search
+# 180 : Full search
+set fmri(reghighres_search) 90
+
+# Degrees of Freedom for registration to main structural
+set fmri(reghighres_dof) BBR
+
+# Registration to standard image?
+set fmri(regstandard_yn) 1
+
+# Use alternate reference images?
+set fmri(alternateReference_yn) 0
+
+# Standard image
+set fmri(regstandard) "/Users/paulmc/fsl_builds/fsl-5_0_9/data/standard/MNI152_T1_2mm_brain"
+
+# Search space for registration to standard space
+# 0   : No search
+# 90  : Normal search
+# 180 : Full search
+set fmri(regstandard_search) 90
+
+# Degrees of Freedom for registration to standard space
+set fmri(regstandard_dof) 12
+
+# Do nonlinear registration from structural to standard space?
+set fmri(regstandard_nonlinear_yn) 0
+
+# Control nonlinear warp field resolution
+set fmri(regstandard_nonlinear_warpres) 10 
+
+# High pass filter cutoff
+set fmri(paradigm_hp) 100
+
+# Total voxels
+set fmri(totalVoxels) 921600
+
+
+# Number of lower-level copes feeding into higher-level analysis
+set fmri(ncopeinputs) 0
+
+# 4D AVW data or FEAT directory (1)
+set feat_files(1) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/fmri1"
+
+# 4D AVW data or FEAT directory (2)
+set feat_files(2) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/fmri2"
+
+# 4D AVW data or FEAT directory (3)
+set feat_files(3) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/fmri3"
+
+# Add confound EVs text file
+set fmri(confoundevs) 0
+
+# Session's structural image for analysis 1
+set initial_highres_files(1) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/epiwholehead"
+
+# Session's structural image for analysis 2
+set initial_highres_files(2) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/epiwholehead"
+
+# Session's structural image for analysis 3
+set initial_highres_files(3) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/epiwholehead"
+
+# Subject's structural image for analysis 1
+set highres_files(1) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/structural_brain"
+
+# Subject's structural image for analysis 2
+set highres_files(2) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/structural_brain"
+
+# Subject's structural image for analysis 3
+set highres_files(3) "/Users/paulmc/Projects/fslpy/tests/testdata/test_feat/structural_brain"
+
+# EV 1 title
+set fmri(evtitle1) "visual"
+
+# Basic waveform shape (EV 1)
+# 0 : Square
+# 1 : Sinusoid
+# 2 : Custom (1 entry per volume)
+# 3 : Custom (3 column format)
+# 4 : Interaction
+# 10 : Empty (all zeros)
+set fmri(shape1) 0
+
+# Convolution (EV 1)
+# 0 : None
+# 1 : Gaussian
+# 2 : Gamma
+# 3 : Double-Gamma HRF
+# 4 : Gamma basis functions
+# 5 : Sine basis functions
+# 6 : FIR basis functions
+set fmri(convolve1) 2
+
+# Convolve phase (EV 1)
+set fmri(convolve_phase1) 0
+
+# Apply temporal filtering (EV 1)
+set fmri(tempfilt_yn1) 1
+
+# Add temporal derivative (EV 1)
+set fmri(deriv_yn1) 1
+
+# Skip (EV 1)
+set fmri(skip1) 0
+
+# Off (EV 1)
+set fmri(off1) 30
+
+# On (EV 1)
+set fmri(on1) 30
+
+# Phase (EV 1)
+set fmri(phase1) 30
+
+# Stop (EV 1)
+set fmri(stop1) -1
+
+# Gamma sigma (EV 1)
+set fmri(gammasigma1) 3
+
+# Gamma delay (EV 1)
+set fmri(gammadelay1) 6
+
+# Orthogonalise EV 1 wrt EV 0
+set fmri(ortho1.0) 0
+
+# Orthogonalise EV 1 wrt EV 1
+set fmri(ortho1.1) 0
+
+# Orthogonalise EV 1 wrt EV 2
+set fmri(ortho1.2) 0
+
+# EV 2 title
+set fmri(evtitle2) "auditory"
+
+# Basic waveform shape (EV 2)
+# 0 : Square
+# 1 : Sinusoid
+# 2 : Custom (1 entry per volume)
+# 3 : Custom (3 column format)
+# 4 : Interaction
+# 10 : Empty (all zeros)
+set fmri(shape2) 0
+
+# Convolution (EV 2)
+# 0 : None
+# 1 : Gaussian
+# 2 : Gamma
+# 3 : Double-Gamma HRF
+# 4 : Gamma basis functions
+# 5 : Sine basis functions
+# 6 : FIR basis functions
+set fmri(convolve2) 2
+
+# Convolve phase (EV 2)
+set fmri(convolve_phase2) 0
+
+# Apply temporal filtering (EV 2)
+set fmri(tempfilt_yn2) 1
+
+# Add temporal derivative (EV 2)
+set fmri(deriv_yn2) 1
+
+# Skip (EV 2)
+set fmri(skip2) 0
+
+# Off (EV 2)
+set fmri(off2) 45
+
+# On (EV 2)
+set fmri(on2) 45
+
+# Phase (EV 2)
+set fmri(phase2) 45
+
+# Stop (EV 2)
+set fmri(stop2) -1
+
+# Gamma sigma (EV 2)
+set fmri(gammasigma2) 3
+
+# Gamma delay (EV 2)
+set fmri(gammadelay2) 6
+
+# Orthogonalise EV 2 wrt EV 0
+set fmri(ortho2.0) 0
+
+# Orthogonalise EV 2 wrt EV 1
+set fmri(ortho2.1) 0
+
+# Orthogonalise EV 2 wrt EV 2
+set fmri(ortho2.2) 0
+
+# Contrast & F-tests mode
+# real : control real EVs
+# orig : control original EVs
+set fmri(con_mode_old) orig
+set fmri(con_mode) orig
+
+# Display images for contrast_real 1
+set fmri(conpic_real.1) 1
+
+# Title for contrast_real 1
+set fmri(conname_real.1) "auditory"
+
+# Real contrast_real vector 1 element 1
+set fmri(con_real1.1) 1
+
+# Real contrast_real vector 1 element 2
+set fmri(con_real1.2) 0
+
+# Real contrast_real vector 1 element 3
+set fmri(con_real1.3) 0
+
+# Real contrast_real vector 1 element 4
+set fmri(con_real1.4) 0
+
+# Display images for contrast_real 2
+set fmri(conpic_real.2) 1
+
+# Title for contrast_real 2
+set fmri(conname_real.2) "visual"
+
+# Real contrast_real vector 2 element 1
+set fmri(con_real2.1) 0
+
+# Real contrast_real vector 2 element 2
+set fmri(con_real2.2) 0
+
+# Real contrast_real vector 2 element 3
+set fmri(con_real2.3) 1
+
+# Real contrast_real vector 2 element 4
+set fmri(con_real2.4) 0
+
+# Display images for contrast_orig 1
+set fmri(conpic_orig.1) 1
+
+# Title for contrast_orig 1
+set fmri(conname_orig.1) "auditory"
+
+# Real contrast_orig vector 1 element 1
+set fmri(con_orig1.1) 1
+
+# Real contrast_orig vector 1 element 2
+set fmri(con_orig1.2) 0
+
+# Display images for contrast_orig 2
+set fmri(conpic_orig.2) 1
+
+# Title for contrast_orig 2
+set fmri(conname_orig.2) "visual"
+
+# Real contrast_orig vector 2 element 1
+set fmri(con_orig2.1) 0
+
+# Real contrast_orig vector 2 element 2
+set fmri(con_orig2.2) 1
+
+# Contrast masking - use >0 instead of thresholding?
+set fmri(conmask_zerothresh_yn) 0
+
+# Mask real contrast/F-test 1 with real contrast/F-test 2?
+set fmri(conmask1_2) 0
+
+# Mask real contrast/F-test 2 with real contrast/F-test 1?
+set fmri(conmask2_1) 0
+
+# Do contrast masking at all?
+set fmri(conmask1_1) 0
+
+##########################################################
+# Now options that don't appear in the GUI
+
+# Alternative (to BETting) mask image
+set fmri(alternative_mask) ""
+
+# Initial structural space registration initialisation transform
+set fmri(init_initial_highres) ""
+
+# Structural space registration initialisation transform
+set fmri(init_highres) ""
+
+# Standard space registration initialisation transform
+set fmri(init_standard) ""
+
+# For full FEAT analysis: overwrite existing .feat output dir?
+set fmri(overwrite_yn) 0

tests/testdata/test_feat/1stlevel_1.feat/design.mat

+/NumWaves	10
+/NumPoints	45
+/PPheights		1.000000e+00	7.177538e-01	1.000000e+00	7.176320e-01	8.330820e-04	1.539341e-03	9.492741e-04	7.386060e-02	1.607247e-01	1.173961e-01
+
+/Matrix
+8.273322e-02	1.370124e-02	-1.466625e-02	3.071752e-02	-3.592555e-04	1.477740e-04	1.011112e-04	9.546830e-04	-4.475104e-02	1.432601e-02	
+1.116071e-01	1.230935e-02	1.931900e-02	3.041906e-02	3.514549e-04	-1.342390e-04	3.279311e-04	1.456864e-02	-1.961891e-02	9.472378e-03	
+1.392951e-01	1.036381e-02	5.278270e-02	2.981382e-02	1.562587e-04	-4.369680e-04	-5.720387e-05	2.195038e-02	-1.145035e-02	-9.357386e-03	
+1.658102e-01	8.465335e-03	8.563168e-02	2.911651e-02	2.457701e-04	1.317185e-04	3.660835e-05	9.849632e-03	3.846691e-02	2.108108e-02	
+1.911687e-01	6.617652e-03	1.177736e-01	2.832911e-02	5.557265e-05	-1.713619e-04	-3.427523e-05	2.201787e-03	7.656402e-02	-1.309857e-02	
+2.153919e-01	4.824789e-03	1.491191e-01	2.745463e-02	6.963766e-05	-4.920981e-04	-2.350075e-05	8.488371e-03	5.966213e-03	-3.471601e-02	
+2.385053e-01	3.088905e-03	1.795816e-01	2.649490e-02	-3.043119e-05	-3.047297e-04	-1.316758e-05	1.244125e-02	-9.674905e-03	-2.504033e-02	
+2.605358e-01	1.412043e-03	2.090751e-01	2.545223e-02	-3.039557e-04	1.283931e-04	-3.260831e-06	2.434733e-03	-7.775902e-03	-1.832618e-02	
+2.815147e-01	-2.032793e-04	2.375177e-01	2.433007e-02	8.745953e-05	1.889597e-04	6.235032e-06	-1.811810e-03	3.519330e-02	-1.638996e-02	
+3.014756e-01	-1.177113e-02	2.648300e-01	2.313136e-02	3.160655e-05	-1.418967e-04	1.533617e-05	-4.189435e-03	-7.970006e-03	-1.801756e-02	
+3.004235e-01	-1.810264e-01	2.909357e-01	2.185918e-02	-2.835346e-04	3.488449e-04	2.405928e-05	-7.681923e-03	8.973243e-02	-1.960649e-02	
+-1.818422e-02	-3.536136e-01	3.157616e-01	2.051676e-02	-6.186031e-05	8.588991e-05	3.242156e-05	-8.490135e-03	-1.675871e-02	-2.116003e-02	
+-3.820436e-01	-2.670479e-01	3.392375e-01	1.910741e-02	-9.834183e-06	1.175213e-04	4.044066e-05	-3.964833e-03	-5.262913e-02	-2.263578e-02	
+-5.476570e-01	-1.027889e-01	3.612967e-01	1.763442e-02	2.212206e-04	6.059486e-05	4.813456e-05	-4.225377e-04	2.293236e-02	-2.774556e-02	
+-5.921639e-01	-1.948424e-02	3.818756e-01	6.085612e-03	-2.051318e-04	1.592389e-04	5.552161e-05	2.307278e-03	1.825582e-02	3.752398e-02	
+-5.936311e-01	7.862981e-03	3.808828e-01	-1.638036e-01	2.056174e-04	6.236075e-04	-3.116226e-04	-3.339040e-02	-5.025264e-02	3.620542e-02	
+-5.835248e-01	1.465431e-02	6.168101e-02	-3.455533e-01	9.932612e-05	8.234236e-04	-2.474931e-04	-2.486075e-02	-2.782016e-02	6.573923e-02	
+-5.708501e-01	1.553945e-02	-3.035190e-01	-2.694434e-01	-8.946509e-05	1.216532e-04	-1.209390e-04	-1.124579e-02	-5.180078e-02	2.517370e-02	
+-5.582720e-01	1.483750e-02	-4.713110e-01	-1.104634e-01	2.213045e-04	4.585224e-04	-1.751389e-04	-1.754106e-02	-3.690358e-02	4.207447e-02	
+-5.463051e-01	2.393122e-02	-5.189230e-01	-2.930725e-02	-3.372435e-04	-5.893360e-04	-4.634456e-04	-3.255199e-02	-3.535673e-02	2.892411e-02	
+-5.148773e-01	1.908326e-01	-5.245084e-01	-3.048970e-03	-2.761339e-04	-6.005804e-04	-7.281746e-05	-7.213539e-03	-4.117459e-02	8.213614e-03	
+-1.673683e-01	3.611846e-01	-5.196162e-01	2.880321e-03	2.354017e-04	-1.678404e-04	1.721724e-05	-3.184160e-03	8.027981e-03	2.755573e-03	
+2.239958e-01	2.725002e-01	-5.133321e-01	2.894631e-03	-2.274250e-04	-1.785440e-04	1.154830e-04	2.208670e-03	3.715103e-02	6.994610e-03	
+4.157953e-01	1.062364e-01	-5.083975e-01	1.246068e-03	-1.325431e-04	1.476525e-04	1.209679e-04	8.297986e-03	1.096592e-02	8.513002e-04	
+4.852464e-01	2.103735e-02	-5.053995e-01	-7.077888e-04	-5.957558e-05	-1.992104e-04	2.386663e-05	3.610028e-03	1.238604e-02	-7.935326e-03	
+5.104915e-01	-8.097320e-03	-5.043659e-01	-2.685395e-03	1.746429e-04	-2.091935e-04	1.215358e-04	8.334799e-03	1.377945e-02	-8.707073e-04	
+5.230704e-01	-1.657339e-02	-5.053209e-01	-4.683267e-03	-4.859663e-06	2.594479e-04	1.267389e-04	4.946845e-03	8.685297e-03	1.472519e-02	
+5.320596e-01	-1.904529e-02	-5.082852e-01	-6.697717e-03	-2.705279e-04	-2.284979e-04	2.098069e-05	5.599974e-03	-9.225252e-06	-1.302897e-02	
+5.401921e-01	-1.983729e-02	-5.132756e-01	-8.725059e-03	-7.766417e-05	-2.378287e-04	1.370015e-04	6.233121e-03	2.247010e-02	-3.099953e-03	
+5.480474e-01	-3.033747e-02	-5.203056e-01	-7.458574e-04	2.649778e-04	-2.469483e-04	1.421002e-04	3.040640e-02	4.121013e-02	-3.809056e-03	
+5.356143e-01	-1.985637e-01	-5.093533e-01	1.655120e-01	3.808204e-04	1.905636e-04	-1.843565e-04	1.208843e-02	2.507163e-02	-4.417578e-03	
+2.063291e-01	-3.701652e-01	-1.838433e-01	3.435760e-01	1.755075e-04	1.053206e-04	1.523304e-04	4.946651e-03	-1.854468e-03	-4.924532e-03	
+-1.675307e-01	-2.826616e-01	1.839590e-01	2.637339e-01	1.813682e-04	-8.036030e-05	1.916334e-04	1.180209e-02	-3.797724e-02	-2.902150e-02	
+-3.424992e-01	-1.175166e-01	3.506004e-01	1.009829e-01	-4.854353e-05	-2.271078e-04	1.899433e-05	1.776037e-03	-3.445954e-02	-7.813066e-03	
+-3.957522e-01	-3.338180e-02	3.932703e-01	1.602525e-02	-1.566701e-06	1.922356e-04	-1.726275e-05	-1.078612e-03	-3.322597e-02	1.008463e-02	
+-4.053984e-01	-5.264170e-03	3.900911e-01	-1.405686e-02	-3.080177e-04	-1.177629e-04	1.627625e-04	1.031707e-02	3.802138e-02	-3.043201e-02	
+-4.029501e-01	2.234324e-03	3.725897e-01	-2.382392e-02	-1.316347e-04	3.491380e-04	4.298846e-05	3.450923e-03	8.951866e-03	2.003611e-02	
+-3.974638e-01	3.759978e-03	3.498375e-01	-2.768142e-02	-1.999952e-04	6.840171e-04	3.142815e-05	-4.238116e-03	1.014700e-02	1.964873e-02	
+-3.916605e-01	3.628807e-03	3.245707e-01	-2.987275e-02	-1.278192e-04	1.943097e-04	-2.615182e-04	-1.622296e-02	-4.852042e-03	2.953765e-03	
+-3.861153e-01	1.322050e-02	2.973799e-01	-3.174652e-02	-4.109137e-05	1.781287e-04	-7.720638e-05	-3.020681e-03	-7.169048e-03	-6.597840e-03	
+-3.608218e-01	1.805443e-01	2.683052e-01	-3.357526e-02	-1.247098e-04	1.733782e-04	7.763064e-06	-2.763966e-03	-1.777217e-02	-6.881186e-03	
+-1.922919e-02	3.512408e-01	2.373924e-01	-3.535336e-02	2.184939e-04	3.360437e-05	-9.976886e-06	-3.320194e-03	8.273680e-03	-7.119446e-03	
+3.663621e-01	2.628205e-01	2.046929e-01	-3.707514e-02	2.096828e-05	-4.881420e-04	3.202901e-05	-5.706147e-03	2.712203e-03	-7.337583e-03	
+5.524539e-01	9.673835e-02	1.702640e-01	-3.873503e-02	2.815810e-04	-3.880274e-04	9.754928e-05	4.365581e-03	2.013122e-02	-2.992273e-03	
+6.161798e-01	3.379199e-02	1.341684e-01	-3.952834e-02	3.382905e-05	-2.632648e-04	-1.779844e-04	-6.823223e-04	-3.838828e-03	-4.409004e-03	

tests/testdata/test_feat/1stlevel_1.feat/design.min

+16
\ No newline at end of file

tests/testdata/test_feat/1stlevel_1.feat/design.trg

+-5.000000e-01 1.950000e+01 3.950000e+01 17.000000
+-5.000000e-01 1.950000e+01 3.950000e+01 17.000000
+-5.000000e-01 2.950000e+01 15.500000
+-5.000000e-01 2.950000e+01 15.500000
+0
+0
+0
+0
+0
+0

tests/testdata/test_feat/1stlevel_1.feat/example_func.nii.gz

+./example_func.nii.gz

tests/testdata/test_feat/1stlevel_1.feat/filtered_func_data.nii.gz

+./filtered_func_data.nii.gz

tests/testdata/test_feat/1stlevel_1.feat/lmax_zstat1.txt

+Cluster Index	Z	x	y	z	
+1	6.03	34	10	1
+1	5.72	35	7	3
+1	5.6	30	9	3
+1	5.42	33	14	0
+1	4.94	38	10	2
+1	4.82	37	12	1

tests/testdata/test_feat/1stlevel_1.feat/lmax_zstat1_std.txt

+Cluster Index	Z	x	y	z	
+1	6.03	-8.41	-89.9	-2.42
+1	5.72	-13.3	-102	11.2
+1	5.6	8.83	-94.4	10.9
+1	5.42	-3.46	-74.1	-9.4
+1	4.94	-26.1	-89.7	4.48
+1	4.82	-21.3	-81.8	-2.39

tests/testdata/test_feat/1stlevel_1.feat/lmax_zstat2.txt

+Cluster Index	Z	x	y	z	
+5	6.27	47	27	2
+5	5.68	47	22	1
+5	5.66	44	25	3
+5	5.34	45	31	2
+5	5.2	45	33	1
+5	5.08	40	33	0
+4	5.75	20	32	2
+4	5.38	20	30	2
+4	4.71	20	34	0
+4	4.65	32	29	1
+4	4.6	32	22	1
+4	4.41	26	27	2
+3	4.58	17	39	3
+3	3.47	19	38	3
+3	2.85	18	38	1
+3	2.59	22	40	0
+2	4.88	25	44	0
+2	3.29	28	41	0
+2	2.68	29	38	0
+1	3.73	26	19	2
+1	2.9	29	23	1