def test_file_download_cached_file(nrrd_read, safe_mkdir, mca, cache, file_exists):
with patch.object(mca, "retrieve_file_over_http") as mock_retrieve:
@cacheable(reader=nrrd_read,
pathfinder=Cache.pathfinder(file_name_position=3,
secondary_file_name_position=1))
def download_volumetric_data(data_path,
file_name,
voxel_resolution=None,
save_file_path=None,
release=None,
coordinate_framework=None):
url = mca.build_volumetric_data_download_url(data_path,
file_name,
voxel_resolution,
release,
coordinate_framework)
mca.retrieve_file_over_http(url, save_file_path)
with patch('os.path.exists',
Mock(name="os.path.exists",
return_value=file_exists)) as mkdir:
nrrd_read.reset_mock()
download_volumetric_data(MCA.AVERAGE_TEMPLATE,
'annotation_10.nrrd',
MCA.VOXEL_RESOLUTION_10_MICRONS,
'volumetric.nrrd',
MCA.CCF_2016,
strategy='file')
assert not mock_retrieve.called, 'server should not have been called'
assert not safe_mkdir.called, 'safe_mkdir should not have been called.'
nrrd_read.assert_called_once_with('volumetric.nrrd')
def test_file_download_server(mock_imports, mca, cache, file_exists):
nrrd_read, MCA = mock_imports
@cacheable(reader=nrrd_read,
pathfinder=Cache.pathfinder(file_name_position=3,
secondary_file_name_position=1))
def download_volumetric_data(data_path,
file_name,
voxel_resolution=None,
save_file_path=None,
release=None,
coordinate_framework=None):
url = mca.build_volumetric_data_download_url(data_path, file_name,
voxel_resolution, release,
coordinate_framework)
mca.retrieve_file_over_http(url, save_file_path)
with patch('os.path.exists',
Mock(name="os.path.exists", return_value=file_exists)) as mkdir:
nrrd_read.reset_mock()
download_volumetric_data(MCA.AVERAGE_TEMPLATE,
'annotation_10.nrrd',
MCA.VOXEL_RESOLUTION_10_MICRONS,
'volumetric.nrrd',
MCA.CCF_2016,
strategy='create')
mca.retrieve_file_over_http.assert_called_once_with(
'http://download.alleninstitute.org/informatics-archive/annotation/ccf_2016/mouse_ccf/average_template/annotation_10.nrrd',
'volumetric.nrrd')
assert not Manifest.safe_mkdir.called, 'safe_mkdir should not have been called.'
nrrd_read.assert_called_once_with('volumetric.nrrd')
def test_file_download_lazy(nrrd_read, safe_mkdir, mca, cache, file_exists):
with patch.object(mca, "retrieve_file_over_http") as mock_retrieve:
@cacheable(strategy='lazy',
reader=nrrd_read,
pathfinder=Cache.pathfinder(file_name_position=3,
secondary_file_name_position=1))
def download_volumetric_data(data_path,
file_name,
voxel_resolution=None,
save_file_path=None,
release=None,
coordinate_framework=None):
url = mca.build_volumetric_data_download_url(data_path,
file_name,
voxel_resolution,
release,
coordinate_framework)
mca.retrieve_file_over_http(url, save_file_path)
with patch('os.path.exists',
Mock(name="os.path.exists",
return_value=file_exists)) as mkdir:
nrrd_read.reset_mock()
download_volumetric_data(MCA.AVERAGE_TEMPLATE,
'annotation_10.nrrd',
MCA.VOXEL_RESOLUTION_10_MICRONS,
'volumetric.nrrd',
MCA.CCF_2016,
strategy='lazy')
if file_exists:
assert not mock_retrieve.called, 'server call not needed when file exists'
else:
mock_retrieve.assert_called_once_with(
'http://download.alleninstitute.org/informatics-archive/annotation/ccf_2016/mouse_ccf/average_template/annotation_10.nrrd',
'volumetric.nrrd')
assert not safe_mkdir.called, 'safe_mkdir should not have been called.'
nrrd_read.assert_called_once_with('volumetric.nrrd')
class CellTypesApi(RmaApi):
NWB_FILE_TYPE = 'NWBDownload'
SWC_FILE_TYPE = '3DNeuronReconstruction'
MARKER_FILE_TYPE = '3DNeuronMarker'
MOUSE = 'Mus musculus'
HUMAN = 'H**o Sapiens'
def __init__(self, base_uri=None):
super(CellTypesApi, self).__init__(base_uri)
@cacheable()
def list_cells_api(self,
id=None,
require_morphology=False,
require_reconstruction=False,
reporter_status=None,
species=None):
criteria = None
if id:
criteria = "[specimen__id$eq%d]" % id
cells = self.model_query(
'ApiCellTypesSpecimenDetail', criteria=criteria, num_rows='all')
return cells
@deprecated("please use list_cells_api instead")
def list_cells(self,
id=None,
require_morphology=False,
require_reconstruction=False,
reporter_status=None,
species=None):
"""
Query the API for a list of all cells in the Cell Types Database.
Parameters
----------
id: int
ID of a cell. If not provided returns all matching cells.
require_morphology: boolean
Only return cells that have morphology images.
require_reconstruction: boolean
Only return cells that have morphological reconstructions.
reporter_status: list
Return cells that have a particular cell reporter status.
species: list
Filter for cells that belong to one or more species. If None, return all.
Must be one of [ CellTypesApi.MOUSE, CellTypesApi.HUMAN ].
Returns
-------
list
Meta data for all cells.
"""
if id:
criteria = "[id$eq'%d']" % id
else:
criteria = "[is_cell_specimen$eq'true'],products[name$in'Mouse Cell Types','Human Cell Types'],ephys_result[failed$eqfalse]"
include = ('structure,cortex_layer,donor(transgenic_lines,organism,conditions),specimen_tags,cell_soma_locations,' +
'ephys_features,data_sets,neuron_reconstructions,cell_reporter')
cells = self.model_query(
'Specimen', criteria=criteria, include=include, num_rows='all')
for cell in cells:
# specimen tags
for tag in cell['specimen_tags']:
tag_name, tag_value = tag['name'].split(' - ')
tag_name = tag_name.replace(' ', '_')
cell[tag_name] = tag_value
# morphology and reconstuction
cell['has_reconstruction'] = len(
cell['neuron_reconstructions']) > 0
cell['has_morphology'] = len(cell['data_sets']) > 0
# transgenic line
cell['transgenic_line'] = None
for tl in cell['donor']['transgenic_lines']:
if tl['transgenic_line_type_name'] == 'driver':
cell['transgenic_line'] = tl['name']
# cell reporter status
cell['reporter_status'] = cell.get('cell_reporter', {}).get('name', None)
# species
cell['species'] = cell.get('donor',{}).get('organism',{}).get('name', None)
# conditions (whitelist)
condition_types = [ 'disease categories' ]
condition_keys = dict(zip(condition_types,
[ ct.replace(' ', '_') for ct in condition_types ]))
for ct, ck in condition_keys.items():
cell[ck] = []
conditions = cell.get('donor',{}).get('conditions', [])
for condition in conditions:
c_type, c_val = condition['name'].split(' - ')
if c_type in condition_keys:
cell[condition_keys[c_type]].append(c_val)
result = self.filter_cells(cells, require_morphology, require_reconstruction, reporter_status, species)
return result
def get_cell(self, id):
'''
Query the API for a one cells in the Cell Types Database.
Returns
-------
list
Meta data for one cell.
'''
cells = self.list_cells_api(id=id)
cell = None if not cells else cells[0]
return cell
@cacheable()
def get_ephys_sweeps(self, specimen_id):
"""
Query the API for a list of sweeps for a particular cell in the Cell Types Database.
Parameters
----------
specimen_id: int
Specimen ID of a cell.
Returns
-------
list: List of sweep dictionaries belonging to a cell
"""
criteria = "[specimen_id$eq%d]" % specimen_id
sweeps = self.model_query(
'EphysSweep', criteria=criteria, num_rows='all')
return sorted(sweeps, key=lambda x: x['sweep_number'])
@deprecated("please use filter_cells_api")
def filter_cells(self, cells, require_morphology, require_reconstruction, reporter_status, species):
"""
Filter a list of cell specimens to those that optionally have morphologies
or have morphological reconstructions.
Parameters
----------
cells: list
List of cell metadata dictionaries to be filtered
require_morphology: boolean
Filter out cells that have no morphological images.
require_reconstruction: boolean
Filter out cells that have no morphological reconstructions.
reporter_status: list
Filter for cells that have a particular cell reporter status
species: list
Filter for cells that belong to one or more species. If None, return all.
Must be one of [ CellTypesApi.MOUSE, CellTypesApi.HUMAN ].
"""
if require_morphology:
cells = [c for c in cells if c['has_morphology']]
if require_reconstruction:
cells = [c for c in cells if c['has_reconstruction']]
if reporter_status:
cells = [c for c in cells if c[
'reporter_status'] in reporter_status]
if species:
species_lower = [ s.lower() for s in species ]
cells = [c for c in cells if c['donor']['organism']['name'].lower() in species_lower]
return cells
def filter_cells_api(self, cells,
require_morphology=False,
require_reconstruction=False,
reporter_status=None,
species=None,
simple=True):
"""
"""
if require_morphology or require_reconstruction:
cells = [c for c in cells if c.get('nr__reconstruction_type') is not None]
if reporter_status:
cells = [c for c in cells if c.get('cell_reporter_status') in reporter_status]
if species:
species_lower = [ s.lower() for s in species ]
cells = [c for c in cells if c.get('donor__species',"").lower() in species_lower]
if simple:
cells = self.simplify_cells_api(cells)
return cells
def simplify_cells_api(self, cells):
return [{
'reporter_status': cell['cell_reporter_status'],
'cell_soma_location': [ cell['csl__x'], cell['csl__y'], cell['csl__z'] ],
'species': cell['donor__species'],
'id': cell['specimen__id'],
'name': cell['specimen__name'],
'structure_layer_name': cell['structure__layer'],
'structure_area_id': cell['structure_parent__id'],
'structure_area_abbrev': cell['structure_parent__acronym'],
'transgenic_line': cell['line_name'],
'dendrite_type': cell['tag__dendrite_type'],
'apical': cell['tag__apical'],
'reconstruction_type': cell['nr__reconstruction_type'],
'disease_state': cell['donor__disease_state']
} for cell in cells ]
@cacheable()
def get_ephys_features(self):
"""
Query the API for the full table of EphysFeatures for all cells.
"""
return self.model_query(
'EphysFeature',
criteria='specimen(ephys_result[failed$eqfalse])',
num_rows='all')
@cacheable()
def get_morphology_features(self):
"""
Query the API for the full table of morphology features for all cells
Notes
-----
by default the tags column is removed because it isn't useful
"""
return self.model_query(
'NeuronReconstruction',
criteria="specimen(ephys_result[failed$eqfalse])",
excpt='tags',
num_rows='all')
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=2,
path_keyword='file_name'))
def save_ephys_data(self, specimen_id, file_name):
"""
Save the electrophysology recordings for a cell as an NWB file.
Parameters
----------
specimen_id: int
ID of the specimen, from the Specimens database model in the Allen Institute API.
file_name: str
Path to save the NWB file.
"""
criteria = '[id$eq%d],ephys_result(well_known_files(well_known_file_type[name$eq%s]))' % (
specimen_id, self.NWB_FILE_TYPE)
includes = 'ephys_result(well_known_files(well_known_file_type))'
results = self.model_query('Specimen',
criteria=criteria,
include=includes,
num_rows='all')
try:
file_url = results[0]['ephys_result'][
'well_known_files'][0]['download_link']
except Exception as _:
raise Exception("Specimen %d has no ephys data" % specimen_id)
self.retrieve_file_over_http(self.api_url + file_url, file_name)
def save_reconstruction(self, specimen_id, file_name):
"""
Save the morphological reconstruction of a cell as an SWC file.
Parameters
----------
specimen_id: int
ID of the specimen, from the Specimens database model in the Allen Institute API.
file_name: str
Path to save the SWC file.
"""
Manifest.safe_make_parent_dirs(file_name)
criteria = '[id$eq%d],neuron_reconstructions(well_known_files)' % specimen_id
includes = 'neuron_reconstructions(well_known_files(well_known_file_type[name$eq\'%s\']))' % self.SWC_FILE_TYPE
results = self.model_query('Specimen',
criteria=criteria,
include=includes,
num_rows='all')
try:
file_url = results[0]['neuron_reconstructions'][
0]['well_known_files'][0]['download_link']
except:
raise Exception("Specimen %d has no reconstruction" % specimen_id)
self.retrieve_file_over_http(self.api_url + file_url, file_name)
def save_reconstruction_markers(self, specimen_id, file_name):
"""
Save the marker file for the morphological reconstruction of a cell. These are
comma-delimited files indicating points of interest in a reconstruction (truncation
points, early tracing termination, etc).
Parameters
----------
specimen_id: int
ID of the specimen, from the Specimens database model in the Allen Institute API.
file_name: str
Path to save the marker file.
"""
Manifest.safe_make_parent_dirs(file_name)
criteria = '[id$eq%d],neuron_reconstructions(well_known_files)' % specimen_id
includes = 'neuron_reconstructions(well_known_files(well_known_file_type[name$eq\'%s\']))' % self.MARKER_FILE_TYPE
results = self.model_query('Specimen',
criteria=criteria,
include=includes,
num_rows='all')
try:
file_url = results[0]['neuron_reconstructions'][
0]['well_known_files'][0]['download_link']
except:
raise LookupError("Specimen %d has no marker file" % specimen_id)
self.retrieve_file_over_http(self.api_url + file_url, file_name)
class VoxelModelApi(MouseConnectivityApi):
'''HTTP Client extending MouseConnectivityApi to download model data.
'''
HTTP_MODEL_DIRECTORY = "http://download.alleninstitute.org/publications/"\
"A_high_resolution_data-driven_model_of_the_mouse_connectome/"
NODES_FILE = "nodes.csv.gz"
WEIGHTS_FILE = "weights.csv.gz"
SOURCE_MASK_FILE = "source_mask_params.json"
TARGET_MASK_FILE = "target_mask_params.json"
CONNECTION_DENSITY_FILE = 'connection_density.csv.gz'
CONNECTION_STRENGTH_FILE = 'connection_strength.csv.gz'
NORMALIZED_CONNECTION_DENSITY_FILE = 'normalized_connection_density.csv.gz'
NORMALIZED_CONNECTION_STRENGTH_FILE = 'normalized_connection_strength.csv.gz'
def download_model_files(self, file_name, save_file_path=None):
"""Download data.
Parameters
----------
file_name : string, optional
save_file_path : string, optional
File name to save as.
"""
url = self.HTTP_MODEL_DIRECTORY + file_name
self.retrieve_file_over_http(url, save_file_path)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_nodes(self, file_name):
self.download_model_files(self.NODES_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_weights(self, file_name):
self.download_model_files(self.WEIGHTS_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_source_mask_params(self, file_name):
self.download_model_files(self.SOURCE_MASK_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_target_mask_params(self, file_name):
self.download_model_files(self.TARGET_MASK_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_connection_density(self, file_name):
self.download_model_files(self.CONNECTION_DENSITY_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_connection_strength(self, file_name):
self.download_model_files(self.CONNECTION_STRENGTH_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_normalized_connection_density(self, file_name):
self.download_model_files(self.NORMALIZED_CONNECTION_DENSITY_FILE, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1, path_keyword='path'))
def download_normalized_connection_strength(self, file_name):
self.download_model_files(self.NORMALIZED_CONNECTION_STRENGTH_FILE, file_name)
class ReferenceSpaceApi(RmaApi):
AVERAGE_TEMPLATE = 'average_template'
ARA_NISSL = 'ara_nissl'
MOUSE_2011 = 'annotation/mouse_2011'
DEVMOUSE_2012 = 'annotation/devmouse_2012'
CCF_2015 = 'annotation/ccf_2015'
CCF_2016 = 'annotation/ccf_2016'
CCF_2017 = 'annotation/ccf_2017'
CCF_VERSION_DEFAULT = CCF_2017
VOXEL_RESOLUTION_10_MICRONS = 10
VOXEL_RESOLUTION_25_MICRONS = 25
VOXEL_RESOLUTION_50_MICRONS = 50
VOXEL_RESOLUTION_100_MICRONS = 100
def __init__(self, base_uri=None):
super(ReferenceSpaceApi, self).__init__(base_uri=base_uri)
@cacheable(strategy='create',
reader=nrrd.read,
pathfinder=Cache.pathfinder(file_name_position=3,
path_keyword='file_name'))
def download_annotation_volume(self, ccf_version, resolution, file_name):
'''
Download the annotation volume at a particular resolution.
Parameters
----------
ccf_version: string
Which reference space version to download. Defaults to "annotation/ccf_2017"
resolution: int
Desired resolution to download in microns.
Must be 10, 25, 50, or 100.
file_name: string
Where to save the annotation volume.
Note: the parameters must be used as positional parameters, not keywords
'''
if ccf_version is None:
ccf_version = ReferenceSpaceApi.CCF_VERSION_DEFAULT
self.download_volumetric_data(ccf_version,
'annotation_%d.nrrd' % resolution,
save_file_path=file_name)
@cacheable(strategy='create',
reader=sitk_utilities.read_ndarray_with_sitk,
pathfinder=Cache.pathfinder(file_name_position=3,
path_keyword='file_name'))
def download_mouse_atlas_volume(self, age, volume_type, file_name):
'''Download a reference volume (annotation, grid annotation, atlas volume)
from the mouse brain atlas project
Parameters
----------
age : str
Specify a mouse age for which to download the reference volume
volume_type : str
Specify the type of volume to download
file_name : str
Specify the path to the downloaded volume
'''
remote_file_name = '{}_{}.zip'.format(age, volume_type)
url = '/'.join([
self.informatics_archive_endpoint, 'current-release',
'mouse_annotation', remote_file_name
])
self.retrieve_file_over_http(url, file_name, zipped=True)
@cacheable(strategy='create',
reader=nrrd.read,
pathfinder=Cache.pathfinder(file_name_position=2,
path_keyword='file_name'))
def download_template_volume(self, resolution, file_name):
'''
Download the registration template volume at a particular resolution.
Parameters
----------
resolution: int
Desired resolution to download in microns. Must be 10, 25, 50, or 100.
file_name: string
Where to save the registration template volume.
'''
self.download_volumetric_data(ReferenceSpaceApi.AVERAGE_TEMPLATE,
'average_template_%d.nrrd' % resolution,
save_file_path=file_name)
@cacheable(strategy='create',
reader=nrrd.read,
pathfinder=Cache.pathfinder(file_name_position=4,
path_keyword='file_name'))
def download_structure_mask(self, structure_id, ccf_version, resolution,
file_name):
'''Download an indicator mask for a specific structure.
Parameters
----------
structure_id : int
Unique identifier for the annotated structure
ccf_version : string
Which reference space version to download. Defaults to "annotation/ccf_2017"
resolution : int
Desired resolution to download in microns. Must be 10, 25, 50, or 100.
file_name : string
Where to save the downloaded mask.
'''
if ccf_version is None:
ccf_version = ReferenceSpaceApi.CCF_VERSION_DEFAULT
structure_mask_dir = 'structure_masks_{0}'.format(resolution)
data_path = '{0}/{1}/{2}'.format(ccf_version, 'structure_masks',
structure_mask_dir)
remote_file_name = 'structure_{0}.nrrd'.format(structure_id)
try:
self.download_volumetric_data(data_path,
remote_file_name,
save_file_path=file_name)
except Exception as e:
self._file_download_log.error(
'''We weren't able to download a structure mask for structure {0}.
You can instead build the mask locally using
ReferenceSpace.many_structure_masks'''
)
raise
@cacheable(strategy='create',
reader=read_obj,
pathfinder=Cache.pathfinder(file_name_position=3,
path_keyword='file_name'))
def download_structure_mesh(self, structure_id, ccf_version, file_name):
'''Download a Wavefront obj file containing a triangulated 3d mesh built
from an annotated structure.
Parameters
----------
structure_id : int
Unique identifier for the annotated structure
ccf_version : string
Which reference space version to download. Defaults to "annotation/ccf_2017"
file_name : string
Where to save the downloaded mask.
'''
if ccf_version is None:
ccf_version = ReferenceSpaceApi.CCF_VERSION_DEFAULT
data_path = '{0}/{1}'.format(ccf_version, 'structure_meshes')
remote_file_name = '{0}.obj'.format(structure_id)
try:
self.download_volumetric_data(data_path,
remote_file_name,
save_file_path=file_name)
except Exception as e:
self._file_download_log.error(
'unable to download a structure mesh for structure {0}.'.
format(structure_id))
raise
def build_volumetric_data_download_url(self,
data_path,
file_name,
voxel_resolution=None,
release=None,
coordinate_framework=None):
'''Construct url to download 3D reference model in NRRD format.
Parameters
----------
data_path : string
'average_template', 'ara_nissl', 'annotation/ccf_{year}',
'annotation/mouse_2011', or 'annotation/devmouse_2012'
voxel_resolution : int
10, 25, 50 or 100
coordinate_framework : string
'mouse_ccf' (default) or 'mouse_annotation'
Notes
-----
See: `3-D Reference Models <http://help.brain-map.org/display/mouseconnectivity/API#API-3DReferenceModels>`_
for additional documentation.
'''
if voxel_resolution is None:
voxel_resolution = ReferenceSpaceApi.VOXEL_RESOLUTION_10_MICRONS
if release is None:
release = 'current-release'
if coordinate_framework is None:
coordinate_framework = 'mouse_ccf'
url = ''.join([
self.informatics_archive_endpoint,
'/%s/%s/' % (release, coordinate_framework), data_path, '/',
file_name
])
return url
def download_volumetric_data(self,
data_path,
file_name,
voxel_resolution=None,
save_file_path=None,
release=None,
coordinate_framework=None):
'''Download 3D reference model in NRRD format.
Parameters
----------
data_path : string
'average_template', 'ara_nissl', 'annotation/ccf_{year}',
'annotation/mouse_2011', or 'annotation/devmouse_2012'
file_name : string
server-side file name. 'annotation_10.nrrd' for example.
voxel_resolution : int
10, 25, 50 or 100
coordinate_framework : string
'mouse_ccf' (default) or 'mouse_annotation'
Notes
-----
See: `3-D Reference Models <http://help.brain-map.org/display/mouseconnectivity/API#API-3DReferenceModels>`_
for additional documentation.
'''
url = self.build_volumetric_data_download_url(data_path, file_name,
voxel_resolution,
release,
coordinate_framework)
if save_file_path is None:
save_file_path = file_name
if save_file_path is None:
save_file_path = 'volumetric_data.nrrd'
self.retrieve_file_over_http(url, save_file_path)
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, )
@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)))
return self.model_query(model='SectionDataSet',
criteria=criteria,
include='genes',
**kwargs)
@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)))
return self.model_query(model='Gene',
criteria=criteria,
include='chromosome',
**kwargs)
@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)
@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)
@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)
class MouseConnectivityApiPrerelease(MouseConnectivityApi):
'''Client for retrieving prereleased mouse connectivity data from lims.
Parameters
----------
base_uri : string, optional
Does not affect pulling from lims.
file_name : string, optional
File name to save/read storage_directories dict. Passed to
GridDataApiPrerelease constructor.
'''
def __init__(self,
storage_directories_file_name,
cache_storage_directories=True,
base_uri=None):
super(MouseConnectivityApiPrerelease, self).__init__(base_uri=base_uri)
self.grid_data_api = GridDataApiPrerelease.from_file_name(
storage_directories_file_name, cache=cache_storage_directories)
@cacheable()
def get_experiments(self):
query_result = lu.query(_EXPERIMENT_QUERY)
experiments = []
for row in query_result:
if str(row[b'id']) in self.grid_data_api.storage_directories:
exp_dict = _experiment_dict(row)
experiments.append(exp_dict)
return experiments
#@cacheable()
def get_structure_unionizes(self):
raise NotImplementedError()
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_injection_density(self, path, experiment_id, resolution):
file_name = "%s_%s.nrrd" % (GridDataApi.INJECTION_DENSITY, resolution)
self.grid_data_api.download_projection_grid_data(
path, experiment_id, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_projection_density(self, path, experiment_id, resolution):
file_name = "%s_%s.nrrd" % (GridDataApi.PROJECTION_DENSITY, resolution)
self.grid_data_api.download_projection_grid_data(
path, experiment_id, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_injection_fraction(self, path, experiment_id, resolution):
file_name = "%s_%s.nrrd" % (GridDataApi.INJECTION_FRACTION, resolution)
self.grid_data_api.download_projection_grid_data(
path, experiment_id, file_name)
@cacheable(strategy='create',
pathfinder=Cache.pathfinder(file_name_position=1,
path_keyword='path'))
def download_data_mask(self, path, experiment_id, resolution):
file_name = "%s_%s.nrrd" % (GridDataApi.DATA_MASK, resolution)
self.grid_data_api.download_projection_grid_data(
path, experiment_id, file_name)
