def test_statmaps_processing(self):
# The counter is the count of the number of images with the field "transform" set to None
# The field is populated with the file when image comparisons are done, meaning that if there is only one
# image in the database (case below) we cannot calculate comparisons, and the "transform" field remains none
# This is currently the only way that we can test the counter, which will be "1" in this case
print "\nTesting Counter - added statistic maps ###"
Image1 = StatisticMap(name='Image1', collection=self.Collection1, file='motor_lips.nii.gz',
map_type="Z", analysis_level='G', number_of_subjects=10)
Image1.file = SimpleUploadedFile('motor_lips.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/motor_lips.nii.gz')).read())
Image1.save()
images_processing = count_processing_comparisons(Image1.pk)
print "%s images processing [should be 0]" %(images_processing)
self.assertEqual(images_processing,0)
# When we add an image, the comparison will be calculated with image1, and both images transform fields will be populated
# the counter will be set to 0. Celery runs in synchronous mode when testing (meaning that jobs are run locally, one
# after the other, instead of being sent to worker nodes) so there is no way to test submitting a batch of async
# jobs and watching the "images still processing" counter go from N to 0. There is also no way of arbitrarily
# setting an image transform field to "None" because on save, all image comparisons are automatically re-calcualted
Image2 = StatisticMap(name='Image2', collection=self.Collection2, file='beta_0001.nii.gz',
map_type="Other", analysis_level='G', number_of_subjects=10)
Image2.file = SimpleUploadedFile('beta_0001.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/beta_0001.nii.gz')).read())
Image2.save()
images_processing = count_processing_comparisons(Image1.pk)
print "%s images processing [should be 0]" %(images_processing)
self.assertEqual(images_processing,0)
# We should have 2 images total, so 1 comparison
total_comparisons = count_existing_comparisons(Image1.pk)
self.assertEqual(total_comparisons,1)
def test_statmaps_processing(self):
# The counter is the count of the number of images with the field "transform" set to None
# The field is populated with the file when image comparisons are done, meaning that if there is only one
# image in the database (case below) we cannot calculate comparisons, and the "transform" field remains none
# This is currently the only way that we can test the counter, which will be "1" in this case
print "\nTesting Counter - added statistic maps ###"
Image1 = StatisticMap(name='Image1', collection=self.Collection1, file='motor_lips.nii.gz', map_type="Z")
Image1.file = SimpleUploadedFile('motor_lips.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/motor_lips.nii.gz')).read())
Image1.save()
images_processing = count_processing_comparisons(Image1.pk)
print "%s images processing [should be 0]" %(images_processing)
self.assertEqual(images_processing,0)
# When we add an image, the comparison will be calculated with image1, and both images transform fields will be populated
# the counter will be set to 0. Celery runs in synchronous mode when testing (meaning that jobs are run locally, one
# after the other, instead of being sent to worker nodes) so there is no way to test submitting a batch of async
# jobs and watching the "images still processing" counter go from N to 0. There is also no way of arbitrarily
# setting an image transform field to "None" because on save, all image comparisons are automatically re-calcualted
Image2 = StatisticMap(name='Image2', collection=self.Collection2, file='beta_0001.nii.gz', map_type="Other")
Image2.file = SimpleUploadedFile('beta_0001.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/beta_0001.nii.gz')).read())
Image2.save()
images_processing = count_processing_comparisons(Image1.pk)
print "%s images processing [should be 0]" %(images_processing)
self.assertEqual(images_processing,0)
# We should have 2 images total, so 1 comparison
total_comparisons = count_existing_comparisons(Image1.pk)
self.assertEqual(total_comparisons,1)
def test_adding_nidm(self):
Image2 = StatisticMap(name='Image2', collection=self.Collection1, file='beta_0001.nii.gz', map_type="Other")
Image2.file = SimpleUploadedFile('beta_0001.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/beta_0001.nii.gz')).read())
Image2.save()
zip_file = open(os.path.join(self.test_path,'test_data/nidm/spm_example.nidm.zip'), 'rb')
post_dict = {
'name': 'spm_nidm',
'description':'{0} upload test'.format('spm_example'),
'collection':self.Collection2.pk}
fname = os.path.basename(os.path.join(self.test_path,'test_data/nidm/spm_example.nidm.zip'))
file_dict = {'zip_file': SimpleUploadedFile(fname, zip_file.read())}
zip_file.close()
form = NIDMResultsForm(post_dict, file_dict)
# Transforms should be generated synchronously
nidm = form.save()
print "\nTesting Counter - added nidm result ###"
# We should have 2 images total, so 1 comparison
total_comparisons = count_existing_comparisons(Image2.pk)
self.assertEqual(total_comparisons,1)
#Let's add a single subject map - this should not trigger a comparison
Image2ss = StatisticMap(name='Image2 - single subject', collection=self.Collection3, file='beta_0001.nii.gz', map_type="Other", analysis_level='S')
Image2ss.file = SimpleUploadedFile('beta_0001.nii.gz', file(os.path.join(self.test_path,'test_data/statmaps/beta_0001.nii.gz')).read())
Image2ss.save()
total_comparisons = count_existing_comparisons(Image2ss.pk)
self.assertEqual(total_comparisons,0)
# Make sure comparisons were calculated
number_comparisons = len(Comparison.objects.all())
print "\n %s comparisons exist after adding NIDM `[should not be 0]" %(number_comparisons)
self.assertEqual(number_comparisons>0,True)
def test_adding_nidm(self):
Image2 = StatisticMap(name='Image2',
collection=self.Collection1,
file='beta_0001.nii.gz',
map_type="Other")
Image2.file = SimpleUploadedFile(
'beta_0001.nii.gz',
file(
os.path.join(self.test_path,
'test_data/statmaps/beta_0001.nii.gz')).read())
Image2.save()
zip_file = open(
os.path.join(self.test_path,
'test_data/nidm/spm_example.nidm.zip'), 'rb')
post_dict = {
'name': 'spm_nidm',
'description': '{0} upload test'.format('spm_example'),
'collection': self.Collection2.pk
}
fname = os.path.basename(
os.path.join(self.test_path,
'test_data/nidm/spm_example.nidm.zip'))
file_dict = {'zip_file': SimpleUploadedFile(fname, zip_file.read())}
zip_file.close()
form = NIDMResultsForm(post_dict, file_dict)
# Transforms should be generated synchronously
nidm = form.save()
print "\nTesting Counter - added nidm result ###"
# We should have 2 images total, so 1 comparison
total_comparisons = count_existing_comparisons(Image2.pk)
self.assertEqual(total_comparisons, 1)
#Let's add a single subject map - this should not trigger a comparison
Image2ss = StatisticMap(name='Image2 - single subject',
collection=self.Collection3,
file='beta_0001.nii.gz',
map_type="Other",
analysis_level='S')
Image2ss.file = SimpleUploadedFile(
'beta_0001.nii.gz',
file(
os.path.join(self.test_path,
'test_data/statmaps/beta_0001.nii.gz')).read())
Image2ss.save()
total_comparisons = count_existing_comparisons(Image2ss.pk)
self.assertEqual(total_comparisons, 0)
# Make sure comparisons were calculated
number_comparisons = len(Comparison.objects.all())
print "\n %s comparisons exist after adding NIDM `[should not be 0]" % (
number_comparisons)
self.assertEqual(number_comparisons > 0, True)
