import unittest
import numpy as np

from neurosynth.analysis import classify

from neurosynth.tests.utils import get_test_dataset


class TestAnalysis(unittest.TestCase):

    def setUp(self):
        """ Create a new Dataset and add features. """
        self.dataset = get_test_dataset()

    def test_meta_analysis(self):
        """ Test full meta-analysis stream. """
        pass

    def test_decoder(self):
        pass

    def test_coactivation(self):
        """ Test seed-based coactivation. """
        pass

    def test_roi_averaging(self):
        pass

    def test_get_random_voxels(self):
        pass

    def test_classify_regions(self):
        # score = classify.classify_regions(self.dataset,['data/regions/medial_motor.nii.gz', 'data/regions/vmPFC.nii.gz'], cross_val='4-Fold')['score']
        # self.assertEqual(score, 0.84600313479623823)

        # score = classify.classify_regions(self.dataset,['data/regions/medial_motor.nii.gz', 'data/regions/vmPFC.nii.gz'])['score']
        # self.assertEqual(score, 0.87813479623824453)

#     result = decode.classify_regions(self.dataset, masks=[get_test_data_path() + 'sgacc_mask.nii.gz'])
#     self.assertEquals(len(result['features']), 525)
#     self.assertEquals(result['scores'].shape = (3,525))


suite = unittest.TestLoader().loadTestsFromTestCase(TestAnalysis)

if __name__ == '__main__':
    unittest.main()

import unittest
import numpy as np

from neurosynth.analysis import classify

from neurosynth.tests.utils import get_test_dataset


class TestAnalysis(unittest.TestCase):

    def setUp(self):
        """ Create a new Dataset and add features. """
        self.dataset = get_test_dataset()

    def test_meta_analysis(self):
        """ Test full meta-analysis stream. """
        pass

    def test_decoder(self):
        pass

    def test_coactivation(self):
        """ Test seed-based coactivation. """
        pass

    def test_roi_averaging(self):
        pass

    def test_get_random_voxels(self):
        pass

    def test_classify_regions(self):
        # score = classify.classify_regions(self.dataset,['data/regions/medial_motor.nii.gz', 'data/regions/vmPFC.nii.gz'], cross_val='4-Fold')['score']
        # self.assertEqual(score, 0.84600313479623823)

        # score = classify.classify_regions(self.dataset,['data/regions/medial_motor.nii.gz', 'data/regions/vmPFC.nii.gz'])['score']
        # self.assertEqual(score, 0.87813479623824453)

#     result = decode.classify_regions(self.dataset, masks=[get_test_data_path() + 'sgacc_mask.nii.gz'])
#     self.assertEquals(len(result['features']), 525)
#     self.assertEquals(result['scores'].shape = (3,525))
        pass

suite = unittest.TestLoader().loadTestsFromTestCase(TestAnalysis)

if __name__ == '__main__':
    unittest.main()

test fix