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from allensdk.core import sitk_utilities
from allensdk.api.warehouse_cache.cache import Cache, cacheable
from .reference_space_api import ReferenceSpaceApi
from .grid_data_api import GridDataApi
from .rma_pager import pageable
[docs]class MouseAtlasApi(ReferenceSpaceApi, GridDataApi):
''' Downloads Mouse Brain Atlas grid data, reference volumes, and metadata.
'''
MOUSE_ATLAS_PRODUCTS = (1,)
DEVMOUSE_ATLAS_PRODUCTS = (3,)
MOUSE_ORGANISM = (2,)
HUMAN_ORGANISM = (1,)
[docs] @cacheable()
@pageable(num_rows=2000, total_rows='all')
def get_section_data_sets(self, gene_ids=None, product_ids=None, **kwargs):
''' Download a list of section data sets (experiments) from the Mouse Brain
Atlas project.
Parameters
----------
gene_ids : list of int, optional
Filter results based on the genes whose expression was characterized
in each experiment. Default is all.
product_ids : list of int, optional
Filter results to a subset of products. Default is the Mouse Brain Atlas.
Returns
-------
list of dict :
Each element is a section data set record, with one or more gene
records nested in a list.
'''
if product_ids is None:
product_ids = list(self.MOUSE_ATLAS_PRODUCTS)
criteria = 'products[id$in{}]'.format(','.join(map(str, product_ids)))
if gene_ids is not None:
criteria += ',genes[id$in{}]'.format(','.join(map(str, gene_ids)))
order = kwargs.pop('order', ['\'id\''])
return self.model_query(model='SectionDataSet',
criteria=criteria,
include='genes',
order=order,
**kwargs)
[docs] @cacheable()
@pageable(num_rows=2000, total_rows='all')
def get_genes(self, organism_ids=None, chromosome_ids=None, **kwargs):
''' Download a list of genes
Parameters
----------
organism_ids : list of int, optional
Filter genes to those appearing in these organisms. Defaults to mouse (2).
chromosome_ids : list of int, optional
Filter genes to those appearing on these chromosomes. Defaults to all.
Returns
-------
list of dict:
Each element is a gene record, with a nested chromosome record (also a dict).
'''
if organism_ids is None:
organism_ids = list(self.MOUSE_ORGANISM)
criteria = '[organism_id$in{}]'.format(','.join(map(str, organism_ids)))
if chromosome_ids is not None:
criteria += ',[chromosome_id$in{}]'.format(','.join(map(str, chromosome_ids)))
order = kwargs.pop('order', ['\'id\''])
return self.model_query(model='Gene',
criteria=criteria,
include='chromosome',
order=order,
**kwargs)
[docs] @cacheable(strategy='create',
reader = sitk_utilities.read_ndarray_with_sitk,
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_expression_density(self, path, experiment_id):
self.download_gene_expression_grid_data(
experiment_id, GridDataApi.DENSITY, path)
[docs] @cacheable(strategy='create',
reader = sitk_utilities.read_ndarray_with_sitk,
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_expression_energy(self, path, experiment_id):
self.download_gene_expression_grid_data(
experiment_id, GridDataApi.ENERGY, path)
[docs] @cacheable(strategy='create',
reader = sitk_utilities.read_ndarray_with_sitk,
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_expression_intensity(self, path, experiment_id):
self.download_gene_expression_grid_data(
experiment_id, GridDataApi.INTENSITY, path)