def run_voxelwise_pearson_similarity(pk1):
from neurovault.apps.statmaps.models import Image
from neurovault.apps.statmaps.utils import get_images_to_compare_with
imgs_pks = get_images_to_compare_with(pk1, for_generation=True)
if imgs_pks:
image = Image.objects.get(pk=pk1)
# added for improved performance
if not image.reduced_representation or not os.path.exists(image.reduced_representation.path):
image = save_resampled_transformation_single(pk1)
# exclude single subject maps from analysis
for pk in imgs_pks:
save_voxelwise_pearson_similarity.apply_async([pk, pk1]) # Default uses reduced_representaion, reduced_representation = True
def run_voxelwise_pearson_similarity(pk1):
from neurovault.apps.statmaps.models import Image
from neurovault.apps.statmaps.utils import get_images_to_compare_with
imgs_pks = get_images_to_compare_with(pk1, for_generation=True)
if imgs_pks:
image = Image.objects.get(pk=pk1)
# added for improved performance
if not image.reduced_representation or not os.path.exists(image.reduced_representation.path):
image = save_resampled_transformation_single(pk1)
# exclude single subject maps from analysis
for pk in imgs_pks:
save_voxelwise_pearson_similarity.apply_async([pk, pk1]) # Default uses reduced_representaion, reduced_representation = True