def save(self, *args, **kwargs):
if self.DOI is not None and self.DOI.strip() == "":
self.DOI = None
if self.private_token is not None and self.private_token.strip() == "":
self.private_token = None
if self.DOI and not self.private and not self.doi_add_date:
self.doi_add_date = datetime.now()
# run calculations when collection turns public
privacy_changed = False
DOI_changed = False
if self.pk is not None:
old_object = Collection.objects.get(pk=self.pk)
old_is_private = old_object.private
old_has_DOI = old_object.DOI is not None
privacy_changed = old_is_private != self.private
DOI_changed = old_has_DOI != (self.DOI is not None)
super(Collection, self).save(*args, **kwargs)
if (privacy_changed
and not self.private) or (DOI_changed
and self.DOI is not None):
for image in self.basecollectionitem_set.instance_of(Image).all():
if image.pk:
generate_glassbrain_image.apply_async([image.pk])
run_voxelwise_pearson_similarity.apply_async([image.pk])
def save(self):
file_changed = False
collection_changed = False
if self.pk is not None:
old_pk = Image.objects.get(pk=self.pk)
if old_pk.file != self.file:
file_changed = True
if old_pk.collection != self.collection:
collection_changed = True
do_update = True if file_changed else False
new_image = True if self.pk is None else False
super(Image, self).save()
if (do_update or new_image) and self.collection and self.collection.private == False:
# Generate glass brain image
generate_glassbrain_image.apply_async([self.pk])
if collection_changed:
for field_name in self._meta.get_all_field_names():
field_instance = getattr(self, field_name)
if field_instance and isinstance(field_instance, FieldFile):
old_path = field_instance.path
new_name = upload_img_to(self, field_instance.name.split("/")[-1])
new_name = field_instance.storage.get_available_name(new_name)
new_path = field_instance.storage.path(new_name)
if not os.path.exists(os.path.dirname(new_path)):
os.mkdir(os.path.dirname(new_path))
shutil.copy(old_path, new_path)
field_instance.name = new_name
assert(old_path != new_path)
os.remove(old_path)
super(Image, self).save()
def save(self, *args, **kwargs):
if self.DOI is not None and self.DOI.strip() == "":
self.DOI = None
if self.private_token is not None and self.private_token.strip() == "":
self.private_token = None
if self.DOI and not self.private and not self.doi_add_date:
self.doi_add_date = datetime.now()
# run calculations when collection turns public
privacy_changed = False
DOI_changed = False
if self.pk is not None:
old_object = Collection.objects.get(pk=self.pk)
old_is_private = old_object.private
old_has_DOI = old_object.DOI is not None
privacy_changed = old_is_private != self.private
DOI_changed = old_has_DOI != (self.DOI is not None)
super(Collection, self).save(*args, **kwargs)
if (privacy_changed and not self.private) or (DOI_changed and self.DOI is not None):
for image in self.basecollectionitem_set.instance_of(Image).all():
if image.pk:
generate_glassbrain_image.apply_async([image.pk])
run_voxelwise_pearson_similarity.apply_async([image.pk])
def save(self, *args, **kwargs):
if self.DOI is not None and self.DOI.strip() == "":
self.DOI = None
if self.private_token is not None and self.private_token.strip() == "":
self.private_token = None
if self.DOI and not self.private and not self.doi_add_date:
self.doi_add_date = datetime.now()
# run calculations when collection turns public
privacy_changed = False
if self.pk is not None:
old_object = Collection.objects.get(pk=self.pk)
old_is_private = old_object.private
privacy_changed = old_is_private != self.private
super(Collection, self).save(*args, **kwargs)
assign_perm('delete_collection', self.owner, self)
assign_perm('change_collection', self.owner, self)
for image in self.image_set.all():
assign_perm('change_image', self.owner, image)
assign_perm('delete_image', self.owner, image)
for nidmresult in self.nidmresults_set.all():
assign_perm('change_nidmresults', self.owner, nidmresult)
assign_perm('delete_nidmresults', self.owner, nidmresult)
if privacy_changed and self.private == False:
for image in self.image_set.all():
if image.pk:
generate_glassbrain_image.apply_async([image.pk])
run_voxelwise_pearson_similarity.apply_async([image.pk])
def save(self):
file_changed = False
if self.pk is not None:
existing = Image.objects.get(pk=self.pk)
if existing.file != self.file:
file_changed = True
do_update = True if file_changed else False
new_image = True if self.pk is None else False
super(Image, self).save()
if (do_update or new_image) and self.collection and self.collection.private == False:
# Generate glass brain image
generate_glassbrain_image.apply_async([self.pk])
def save(self):
file_changed = False
if self.pk is not None:
existing = Image.objects.get(pk=self.pk)
if existing.file != self.file:
file_changed = True
do_update = True if file_changed else False
new_image = True if self.pk is None else False
super(Image, self).save()
if (do_update or new_image
) and self.collection and self.collection.private == False:
# Generate glass brain image
generate_glassbrain_image.apply_async([self.pk])
def save(self):
if self.DOI is not None and self.DOI.strip() == "":
self.DOI = None
if self.private_token is not None and self.private_token.strip() == "":
self.private_token = None
# run calculations when collection turns public
privacy_changed = False
if self.pk is not None:
old_object = Collection.objects.get(pk=self.pk)
old_is_private = old_object.private
privacy_changed = old_is_private != self.private
super(Collection, self).save()
if privacy_changed and self.private == False:
for image in self.image_set.all():
if image.pk:
generate_glassbrain_image.apply_async([image.pk])
run_voxelwise_pearson_similarity.apply_async([image.pk])
def save(self):
file_changed = False
collection_changed = False
if self.pk is not None:
old_pk = Image.objects.get(pk=self.pk)
if old_pk.file != self.file:
file_changed = True
if old_pk.collection != self.collection:
collection_changed = True
do_update = True if file_changed else False
new_image = True if self.pk is None else False
super(Image, self).save()
if (do_update or new_image
) and self.collection and self.collection.private == False:
# Generate glass brain image
generate_glassbrain_image.apply_async([self.pk])
if collection_changed:
for field_name in self._meta.get_all_field_names():
field_instance = getattr(self, field_name)
if field_instance and isinstance(field_instance, FieldFile):
old_path = field_instance.path
new_name = upload_img_to(
self,
field_instance.name.split("/")[-1])
new_name = field_instance.storage.get_available_name(
new_name)
new_path = field_instance.storage.path(new_name)
if not os.path.exists(os.path.dirname(new_path)):
os.mkdir(os.path.dirname(new_path))
shutil.copy(old_path, new_path)
field_instance.name = new_name
assert (old_path != new_path)
os.remove(old_path)
super(Image, self).save()
import os
import django
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "neurovault.settings")
django.setup()
from neurovault.apps.statmaps.models import StatisticMap
from neurovault.apps.statmaps.tasks import generate_glassbrain_image,\
save_resampled_transformation_single
for image in StatisticMap.objects.filter(collection__private=False).exclude(analysis_level = 'S').exclude(is_thresholded = True):
print image.id
generate_glassbrain_image.apply_async([image.id])
save_resampled_transformation_single.apply_async([image.id])