def testaddAFNI(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality':'fMRI-BOLD',
'map_type': 'T',
'collection':self.coll.pk,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname = os.path.join(testpath,'test_data/statmaps/saccade.I_C.MNI.nii.gz')
nii = nb.load(fname)
self.assertTrue(detect_4D(nii))
self.assertTrue(len(split_4D_to_3D(nii)) > 0)
file_dict = {'file': SimpleUploadedFile(fname, open(fname).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(StatisticMap.objects.filter(collection=self.coll.pk).count(), 2)
def testaddAFNI(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'number_of_subjects': 10,
'analysis_level': 'G',
'collection': self.coll.pk,
'target_template_image': 'GenericMNI',
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname = os.path.join(testpath,
'test_data/statmaps/saccade.I_C.MNI.nii.gz')
nii = nb.load(fname)
self.assertTrue(detect_4D(nii))
self.assertTrue(len(split_4D_to_3D(nii)) > 0)
file_dict = {'file': SimpleUploadedFile(fname, open(fname).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(
StatisticMap.objects.filter(collection=self.coll.pk).count(), 2)
def testaddImgHdr(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'number_of_subjects': 10,
'analysis_level': 'G',
'collection': self.coll.pk,
'target_template_image': 'GenericMNI',
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath,
'test_data/statmaps/box_0b_vs_1b.img')
fname_hdr = os.path.join(testpath,
'test_data/statmaps/box_0b_vs_1b.hdr')
file_dict = {
'file': SimpleUploadedFile(fname_img,
open(fname_img).read()),
'hdr_file': SimpleUploadedFile(fname_hdr,
open(fname_hdr).read())
}
form = StatisticMapForm(post_dict, file_dict)
self.assertFalse(form.is_valid())
self.assertTrue("thresholded" in form.errors["file"][0])
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'number_of_subjects': 10,
'analysis_level': 'G',
'collection': self.coll.pk,
'ignore_file_warning': True,
'target_template_image': 'GenericMNI',
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath,
'test_data/statmaps/box_0b_vs_1b.img')
fname_hdr = os.path.join(testpath,
'test_data/statmaps/box_0b_vs_1b.hdr')
file_dict = {
'file': SimpleUploadedFile(fname_img,
open(fname_img).read()),
'hdr_file': SimpleUploadedFile(fname_hdr,
open(fname_hdr).read())
}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(
StatisticMap.objects.filter(collection=self.coll.pk)[0].name,
"test map")
def save_statmap_form(image_path,collection,ignore_file_warning=False,image_name=None):
if image_name == None:
if isinstance(image_path,list):
image_name = image_path[0]
else:
image_name = image_path
post_dict = {
'name': image_name,
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'collection': collection.pk,
'ignore_file_warning': ignore_file_warning
}
# If image path is a list, we have img/hdr
if isinstance(image_path,list):
file_dict = {'file': SimpleUploadedFile(image_path[0], open(image_path[0]).read()),
'hdr_file': SimpleUploadedFile(image_path[1], open(image_path[1]).read())}
else:
file_dict = {'file': SimpleUploadedFile(image_path, open(image_path).read())}
form = StatisticMapForm(post_dict, file_dict)
# this is necessary to split 4D volumes
form.is_valid()
return form.save()
def save_statmap_form(image_path,collection,ignore_file_warning=False,image_name=None):
if image_name == None:
if isinstance(image_path,list):
image_name = image_path[0]
else:
image_name = image_path
post_dict = {
'name': image_name,
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'target_template_image': 'GenericMNI',
'collection': collection.pk,
'ignore_file_warning': ignore_file_warning
}
# If image path is a list, we have img/hdr
if isinstance(image_path,list):
file_dict = {'file': SimpleUploadedFile(image_path[0], open(image_path[0]).read()),
'hdr_file': SimpleUploadedFile(image_path[1], open(image_path[1]).read())}
else:
file_dict = {'file': SimpleUploadedFile(image_path, open(image_path).read())}
form = StatisticMapForm(post_dict, file_dict)
# this is necessary to split 4D volumes
form.is_valid()
return form.save()
def save_statmap_form(image_path, collection, ignore_file_warning=False, image_name=None):
if image_name == None:
if isinstance(image_path, list):
image_name = image_path[0]
else:
image_name = image_path
post_dict = {
"name": image_name,
"cognitive_paradigm_cogatlas": "trm_4f24126c22011",
"modality": "fMRI-BOLD",
"map_type": "T",
"collection": collection.pk,
"ignore_file_warning": ignore_file_warning,
}
# If image path is a list, we have img/hdr
if isinstance(image_path, list):
file_dict = {
"file": SimpleUploadedFile(image_path[0], open(image_path[0]).read()),
"hdr_file": SimpleUploadedFile(image_path[1], open(image_path[1]).read()),
}
else:
file_dict = {"file": SimpleUploadedFile(image_path, open(image_path).read())}
form = StatisticMapForm(post_dict, file_dict)
return form.save()
def testaddNiiGz(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality':'fMRI-BOLD',
'map_type': 'T',
'collection':self.coll.pk,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname = os.path.join(testpath,'test_data/statmaps/motor_lips.nii.gz')
file_dict = {'file': SimpleUploadedFile(fname, open(fname).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(StatisticMap.objects.filter(collection=self.coll.pk)[0].name, "test map")
def testaddImgHdr(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality':'fMRI-BOLD',
'map_type': 'T',
'number_of_subjects': 10,
'analysis_level': 'G',
'collection':self.coll.pk,
'target_template_image': 'GenericMNI',
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath,'test_data/statmaps/box_0b_vs_1b.img')
fname_hdr = os.path.join(testpath,'test_data/statmaps/box_0b_vs_1b.hdr')
file_dict = {'file': SimpleUploadedFile(fname_img, open(fname_img).read()),
'hdr_file': SimpleUploadedFile(fname_hdr, open(fname_hdr).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertFalse(form.is_valid())
self.assertTrue("thresholded" in form.errors["file"][0])
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality':'fMRI-BOLD',
'map_type': 'T',
'number_of_subjects': 10,
'analysis_level': 'G',
'collection':self.coll.pk,
'ignore_file_warning': True,
'target_template_image': 'GenericMNI',
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath,'test_data/statmaps/box_0b_vs_1b.img')
fname_hdr = os.path.join(testpath,'test_data/statmaps/box_0b_vs_1b.hdr')
file_dict = {'file': SimpleUploadedFile(fname_img, open(fname_img).read()),
'hdr_file': SimpleUploadedFile(fname_hdr, open(fname_hdr).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(StatisticMap.objects.filter(collection=self.coll.pk)[0].name, "test map")
def testaddNiiGz(self):
post_dict = {
"name": "test map",
"cognitive_paradigm_cogatlas": "trm_4f24126c22011",
"modality": "fMRI-BOLD",
"map_type": "T",
"collection": self.coll.pk,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname = os.path.join(testpath, "test_data/statmaps/motor_lips.nii.gz")
file_dict = {"file": SimpleUploadedFile(fname, open(fname).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(StatisticMap.objects.filter(collection=self.coll.pk)[0].name, "test map")
def testaddImgHdr(self):
post_dict = {
"name": "test map",
"cognitive_paradigm_cogatlas": "trm_4f24126c22011",
"modality": "fMRI-BOLD",
"map_type": "T",
"collection": self.coll.pk,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath, "test_data/statmaps/box_0b_vs_1b.img")
fname_hdr = os.path.join(testpath, "test_data/statmaps/box_0b_vs_1b.hdr")
file_dict = {
"file": SimpleUploadedFile(fname_img, open(fname_img).read()),
"hdr_file": SimpleUploadedFile(fname_hdr, open(fname_hdr).read()),
}
form = StatisticMapForm(post_dict, file_dict)
self.assertFalse(form.is_valid())
self.assertTrue("thresholded" in form.errors["file"][0])
post_dict = {
"name": "test map",
"cognitive_paradigm_cogatlas": "trm_4f24126c22011",
"modality": "fMRI-BOLD",
"map_type": "T",
"collection": self.coll.pk,
"ignore_file_warning": True,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname_img = os.path.join(testpath, "test_data/statmaps/box_0b_vs_1b.img")
fname_hdr = os.path.join(testpath, "test_data/statmaps/box_0b_vs_1b.hdr")
file_dict = {
"file": SimpleUploadedFile(fname_img, open(fname_img).read()),
"hdr_file": SimpleUploadedFile(fname_hdr, open(fname_hdr).read()),
}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(StatisticMap.objects.filter(collection=self.coll.pk)[0].name, "test map")
def testaddNiiGz(self):
post_dict = {
'name': "test map",
'cognitive_paradigm_cogatlas': 'trm_4f24126c22011',
'modality': 'fMRI-BOLD',
'map_type': 'T',
'collection': self.coll.pk,
}
testpath = os.path.abspath(os.path.dirname(__file__))
fname = os.path.join(testpath, 'test_data/statmaps/motor_lips.nii.gz')
file_dict = {'file': SimpleUploadedFile(fname, open(fname).read())}
form = StatisticMapForm(post_dict, file_dict)
self.assertTrue(form.is_valid())
form.save()
self.assertEqual(
StatisticMap.objects.filter(collection=self.coll.pk)[0].name,
"test map")
def add_image(request, collection_cid):
collection = get_collection(collection_cid, request)
image = StatisticMap(collection=collection)
if request.method == "POST":
form = StatisticMapForm(request.POST, request.FILES, instance=image)
if form.is_valid():
image = form.save()
return HttpResponseRedirect(image.get_absolute_url())
else:
form = StatisticMapForm(instance=image)
context = {"form": form}
return render(request, "statmaps/add_image.html.haml", context)
def add_image(request, collection_cid):
collection = get_collection(collection_cid,request)
image = StatisticMap(collection=collection)
if request.method == "POST":
form = StatisticMapForm(request.POST, request.FILES, instance=image)
if form.is_valid():
image = form.save()
return HttpResponseRedirect(image.get_absolute_url())
else:
form = StatisticMapForm(instance=image)
context = {"form": form}
return render(request, "statmaps/add_image.html.haml", context)
