Implemented _read_csv, and several changes following testing

nipype/interfaces/nitime/__init__.py

@@ -0,0 +1,6 @@
+# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
+# vi: set ft=python sts=4 ts=4 sw=4 et:
+
+from nipype.interfaces.nitime.analysis import (CoherenceAnalyzerInputSpec,
+ CoherenceAnalyzerOutputSpec,
+ CoherenceAnalyzer)

nipype/interfaces/nitime/analysis.py

@@ -10,27 +10,29 @@
 
 """
 
+
 from nipype.utils.misc import package_check
+package_check('nitime')
+package_check('matplotlib')
+
 
 from nipype.interfaces.base import (TraitedSpec, File, InputMultiPath,
  OutputMultiPath, Undefined, traits,
  BaseInterface)
-
 from nitime.analysis import CoherenceAnalyzer
 from nitime.timeseries import TimeSeries
 
-package_check('nitime')
-package_check('matplotlib')
-
+from matplotlib.mlab import csv2rec
+
 class CoherenceAnalyzerInputSpec(TraitedSpec):
 
  #Input either csv file, or time-series object and use _xor_inputs to
  #discriminate
- _xor_inputs('in_file','in_TS')
+ _xor_inputs=('in_file','in_TS')
  in_file = File(desc=('csv file with ROIs on the columns and ',
  'time-points on the rows. ROI names at the top row'),
  exists=True,
- requires=('sampling_rate'))
+ requires=('TR',))
 
  #If you gave just a file name, you need to specify the sampling_rate:
  TR = traits.Float(desc=('The TR used to collect the data',
@@ -79,16 +81,21 @@ class CoherenceAnalyzerOutputSpec(TraitedSpec):
 class CoherenceAnalyzer(BaseInterface):
 
  input_spec = CoherenceAnalyzerInputSpec
- output_spec = CoherenceAnayzerOutputSpec
+ output_spec = CoherenceAnalyzerOutputSpec
 
  def _read_csv(self):
+ #Check that input conforms to expectations:
+ first_row = open(self.inputs.in_file).readline()
+ if not first_row[1].isalpha():
+ raise ValueError("First row of in_file should contain ROI names as strings of characters")
 
- return roi_labels,TS
+ rec_array=csv2rec(self.inputs.in_file)
+ return rec_array
 
  #Rewrite _run_interface, but not run
  def _run_interface(self,runtime):
  lb, ub = self.inputs.frequency_range
- if
+
 
  #Rewrite _list_outputs (look at BET)
 
@@ -97,10 +104,15 @@ def _list_outputs(self):
  return outputs
 
 class GetTimeSeriesInputSpec():
+ pass
 class GetTimeSeriesOutputSpec():
+ pass
 class GetTimeSeries():
-
+ pass
 class CoherenceVizInputSpec():
+ pass
 class CoherenceVizOutputSpec():
+ pass
 class CoherenceViz():
+ pass
 

nipype/interfaces/nitime/tests/test_nitime.py

@@ -3,17 +3,24 @@
 import os
 import tempfile
 import shutil
-from matplotlib import mlab.csv2rec as csv2rec
 
 from nipype.testing import (assert_equal, assert_not_equal, assert_raises,
  with_setup, TraitError, parametric, skipif)
 
+from nipype.testing import example_data
+
+import nipype.interfaces.nitime as nitime 
 
 def test_read_csv():
  """Test that reading the data from csv file gives you back a reasonable
  time-series object """
 
- #XXX need to finish this:
- data_rec = csv2rec('data/fmri_timeseries.csv')
-
-
+ CA = nitime.CoherenceAnalyzer()
+ CA.inputs.TR = 1.89 # bogus value just to pass traits test
+ CA.inputs.in_file = example_data('fmri_timeseries_nolabels.csv')
+ yield assert_raises,ValueError,CA._read_csv 
+
+ CA.inputs.in_file = example_data('fmri_timeseries.csv')
+ rec_array = CA._read_csv()
+ yield assert_equal, rec_array['wm'][0],10125.9
+