average with only masked voxels; tests for ErrorMap

Author: lsqshr

nipype/algorithms/metrics.py

@@ -553,7 +553,7 @@ def _run_interface(self, runtime):
         errvectorexp[msk_idxs] = errvector
 
         # Get averaged error
-        self._distance = np.average(errvectorexp)
+        self._distance = np.average(errvector)
 
         errmap = errvectorexp.reshape(mapshape)
 

nipype/algorithms/tests/test_errormap.py

@@ -0,0 +1,75 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+from nipype.testing import (assert_equal, example_data)
+from nipype.algorithms.metrics import ErrorMap
+import nibabel as nib
+import numpy as np
+from tempfile import mkdtemp
+import os
+
+def test_errormap():
+
+	tempdir = mkdtemp()
+	# Single-Spectual
+	# Make two fake 2*2*2 voxel volumes
+	volume1 = np.array([[[2.0, 8.0], [1.0, 2.0]], [[1.0, 9.0], [0.0, 3.0]]]) # John von Neumann's birthday
+	volume2 = np.array([[[0.0, 7.0], [2.0, 3.0]], [[1.0, 9.0], [1.0, 2.0]]]) # Alan Turing's birthday
+	mask = np.array([[[1, 0], [0, 1]], [[1, 0], [0, 1]]])
+
+	img1 = nib.Nifti1Image(volume1, np.eye(4))
+	img2 = nib.Nifti1Image(volume2, np.eye(4))
+	maskimg = nib.Nifti1Image(mask, np.eye(4))
+
+	nib.save(img1, os.path.join(tempdir, 'von.nii.gz'))
+	nib.save(img2, os.path.join(tempdir, 'alan.nii.gz'))
+	nib.save(maskimg, os.path.join(tempdir, 'mask.nii.gz'))
+
+
+	# Default metric
+	errmap = ErrorMap()
+	errmap.inputs.in_tst = os.path.join(tempdir, 'von.nii.gz')
+	errmap.inputs.in_ref = os.path.join(tempdir, 'alan.nii.gz')
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 1.125 
+
+	# Square metric
+	errmap.inputs.metric = 'sqeuclidean'
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 1.125
+
+	# Linear metric
+	errmap.inputs.metric = 'euclidean'
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 0.875 
+
+	# Masked 
+	errmap.inputs.mask = os.path.join(tempdir, 'mask.nii.gz')
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 1.0
+
+	## Multi-Spectual
+	volume3 = np.array([[[1.0, 6.0], [0.0, 3.0]], [[1.0, 9.0], [3.0, 6.0]]]) # Raymond Vahan Damadian's birthday
+
+	msvolume1 = np.zeros(shape=(2,2,2,2))
+	msvolume1[:,:,:,0] = volume1
+	msvolume1[:,:,:,1] = volume3
+	msimg1 = nib.Nifti1Image(msvolume1, np.eye(4))
+
+	msvolume2 = np.zeros(shape=(2,2,2,2))
+	msvolume2[:,:,:,0] = volume2
+	msvolume2[:,:,:,1] = volume3
+	msimg2 = nib.Nifti1Image(msvolume2, np.eye(4))
+
+	nib.save(img1, os.path.join(tempdir, 'von-ray.nii.gz'))
+	nib.save(img2, os.path.join(tempdir, 'alan-ray.nii.gz'))
+
+	errmap.inputs.in_tst = os.path.join(tempdir, 'von-ray.nii.gz')
+	errmap.inputs.in_ref = os.path.join(tempdir, 'alan-ray.nii.gz')
+	errmap.inputs.metric = 'sqeuclidean'
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 7.0
+
+	errmap.inputs.metric = 'euclidean'
+	result = errmap.run()
+	yield assert_equal, result.outputs.distance, 2**0.5 + 6