1 files changed, 84 insertions, 0 deletions
diff --git a/nitime/fmri/tests/test_io.py b/nitime/fmri/tests/test_io.py
new file mode 100644
index 0000000..973e599
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+++ b/nitime/fmri/tests/test_io.py
@@ -0,0 +1,84 @@
+"""
+
+Test the io submodule of the fMRI module of nitime
+
+"""
+import os
+
+import numpy as np
+import numpy.testing as npt
+
+import nitime
+import nitime.timeseries as ts
+
+#Skip the tests if you can't import nibabel:
+try:
+    import nitime.fmri.io as io
+    no_nibabel = False
+    no_nibabel_msg=''
+except ImportError as e:
+    no_nibabel = True
+    no_nibabel_msg=e.args[0]
+
+data_path = os.path.join(nitime.__path__[0],'data')
+
+@npt.dec.skipif(no_nibabel,no_nibabel_msg)
+def test_time_series_from_file():
+
+    """Testing reading of data from nifti files, using nibabel"""
+
+    TR = 1.35
+    ts_ff = io.time_series_from_file
+
+    #File names:
+    fmri_file1 = os.path.join(data_path,'fmri1.nii.gz')
+    fmri_file2 = os.path.join(data_path,'fmri2.nii.gz')
+
+    #Spatial coordinates into the volumes:
+    coords1 = np.array([[5,5,5,5],[5,5,5,5],[1,2,3,4]])
+    coords2 = np.array([[6,6,6,6],[6,6,6,6],[3,4,5,6]])
+
+    #No averaging, no normalization:
+    t1 = ts_ff([fmri_file1,fmri_file2],[coords1,coords2],TR)
+
+    npt.assert_equal(t1[0].shape,(4,80))  # 4 coordinates, 80 time-points
+
+    t2 = ts_ff([fmri_file1,fmri_file2],[coords1,coords2],TR,average=True)
+
+    npt.assert_equal(t2[0].shape,(80,))  # collapse coordinates,80 time-points
+
+    t3 = ts_ff(fmri_file1,coords1,TR,normalize='zscore')
+
+    #The mean of each channel should be almost equal to 0:
+    npt.assert_almost_equal(t3.data[0].mean(),0)
+    #And the standard deviation should be almost equal to 1:
+    npt.assert_almost_equal(t3.data[0].std(),1)
+
+    t4 = ts_ff(fmri_file1,coords1,TR,normalize='percent')
+
+    #In this case, the average is almost equal to 0, but no constraint on the
+    #std:
+    npt.assert_almost_equal(t4.data[0].mean(),0)
+
+    #Make sure that we didn't mess up the sampling interval:
+    npt.assert_equal(t4.sampling_interval,nitime.TimeArray(1.35))
+
+    # Test the default behavior:
+    data = io.load(fmri_file1).get_data()
+    t5 = ts_ff(fmri_file1)
+    npt.assert_equal(t5.shape, data.shape)
+    npt.assert_equal(t5.sampling_interval, ts.TimeArray(1, time_unit='s'))
+
+    # Test initializing TR with a TimeArray:
+    t6= ts_ff(fmri_file1, TR=ts.TimeArray(1350, time_unit='ms'))
+    npt.assert_equal(t4.sampling_interval, t6.sampling_interval)
+
+    # Check the concatenation dimensions:
+    t7 = ts_ff([fmri_file1, fmri_file2])
+    npt.assert_equal([t7.shape[:3], t7.shape[-1]], [data.shape[:3], data.shape[-1]*2])
+
+    t8 = ts_ff([fmri_file1, fmri_file2], average=True)
+    npt.assert_equal(t8.shape[0], data.shape[-1]*2)
+
+    t9 = ts_ff([fmri_file1, fmri_file2], average=True, normalize='zscore')
+    npt.assert_almost_equal(t9.data.mean(), 0)