Files
cellxgene/backend/czi_hosted/common/annotations/annotations.py
T
Bruce Martin e334fbe96e remove experimental ontology support (#2300)
* remove experimental ontology support

* lint

* remove ontologies from unit tests

* additional test changes
2021-07-14 07:23:38 -07:00

111 lines
4.0 KiB
Python

import os
from flask import current_app, has_request_context
from backend.common.errors import DisabledFeatureError
from backend.common.utils.type_conversion_utils import get_schema_type_hint_of_array
from backend.common.genesets import write_gene_sets_tidycsv, read_gene_sets_tidycsv, validate_gene_sets
from backend.common.utils.data_locator import DataLocator
from backend.common.utils.utils import path_join
class Annotations:
"""baseclass for annotations and genesets"""
def __init__(self, config={}):
self.config = config
def user_annotations_enabled(self):
return self.config.get("user-annotations", False)
def check_user_annotations_enabled(self):
if not self.user_annotations_enabled():
raise DisabledFeatureError("User annotations are disabled.")
def get_schema(self, data_adaptor):
schema = []
labels = self.read_labels(data_adaptor)
if labels is not None and not labels.empty:
for col in labels.columns:
col_schema = dict(name=col, writable=True)
col_schema.update(get_schema_type_hint_of_array(labels[col]))
schema.append(col_schema)
return schema
def set_collection(self, name):
"""set or create a new annotation collection"""
raise NotImplementedError
def read_labels(self, data_adaptor):
"""Return the labels as a pandas.DataFrame"""
raise NotImplementedError
def write_labels(self, df, data_adaptor):
"""Write the labels (df) to a persistent storage such that it can later be read"""
raise NotImplementedError
def update_parameters(self, parameters, data_adaptor):
"""Update configuration parameters that describe information about the annotations feature"""
params = {}
params["annotations_genesets_readonly"] = True
params["annotations_genesets_name_is_read_only"] = True
parameters.update(params)
@staticmethod
def gene_sets_to_csv(genesets):
"""
Convert the internal genesets format (returned by read_gene_set) into
the simple Tidy CSV.
"""
from io import StringIO
if isinstance(genesets, dict):
genesets = genesets.values()
with StringIO() as sio:
write_gene_sets_tidycsv(sio, genesets)
return sio.getvalue()
@staticmethod
def gene_sets_to_response(genesets):
"""
Convert the internal genesets format (returned by read_gene_set) into
the dict expected by the JSON REST API
"""
return list(genesets.values())
def read_gene_sets(self, data_adaptor, context=None):
if has_request_context():
if not current_app.auth.is_user_authenticated():
return ({}, 0)
gene_sets_uri_or_path = dataset_uri_to_geneset_uri(data_adaptor.data_locator.uri_or_path)
server_config = data_adaptor.server_config
region_name = None if server_config is None else server_config.data_locator__s3__region_name
gene_sets_locator = DataLocator(gene_sets_uri_or_path, region_name=region_name)
if not gene_sets_locator.exists():
return ({}, 0)
gene_sets = read_gene_sets_tidycsv(gene_sets_locator, context)
schema = data_adaptor.get_schema()
var_index = schema["annotations"]["var"].get("index", "index")
var_names = set(data_adaptor.query_var_array(var_index))
gene_sets = validate_gene_sets(gene_sets, var_names)
return (gene_sets, 0)
def dataset_uri_to_geneset_uri(data_uri_or_path):
"""given a dataset URI, return the associated gene set URI"""
data_basename = os.path.basename(data_uri_or_path)
base, ext = os.path.splitext(data_basename)
if ext is not None: # strip extension, if any
data_basename = base
genesets_basename = f"{data_basename}-genesets.csv"
gene_sets_uri_or_path = path_join(data_uri_or_path, "..", genesets_basename)
return gene_sets_uri_or_path