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# Copyright (c) 2016. Mount Sinai School of Medicine
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
'''
Load predictors
'''
import pickle
import pandas
from ..downloads import get_path
from ..common import normalize_allele_name
def from_allele_name(allele_name):
"""
Load a predictor for an allele.
Parameters
----------
allele_name : class I allele name
Returns
----------
Class1BindingPredictor
"""
global _ALLELE_PREDICTOR_CACHE
allele_name = normalize_allele_name(allele_name)
if allele_name in _ALLELE_PREDICTOR_CACHE:
return _ALLELE_PREDICTOR_CACHE[allele_name]
models_df = production_models_dataframe()
predictor_name = models_df.ix[allele_name].predictor_name
model_path = get_path(
"models_class1_allele_specific_single",
"models/%s.pickle" % predictor_name)
with open(model_path, 'rb') as fd:
predictor = pickle.load(fd)
_ALLELE_PREDICTOR_CACHE[allele_name] = predictor
return predictor
_ALLELE_PREDICTOR_CACHE = {}
def supported_alleles():
"""
Return a list of the names of the alleles for which there are trained
predictors.
"""
return list(sorted(production_models_dataframe().allele))
def production_models_dataframe():
"""
Return a pandas.DataFrame describing the currently available trained
predictors.
"""
global _PRODUCTION_MODELS_DATAFRAME
if _PRODUCTION_MODELS_DATAFRAME is None:
_PRODUCTION_MODELS_DATAFRAME = pandas.read_csv(
get_path("models_class1_allele_specific_single", "production.csv"))
_PRODUCTION_MODELS_DATAFRAME.index = (
_PRODUCTION_MODELS_DATAFRAME.allele)
return _PRODUCTION_MODELS_DATAFRAME
_PRODUCTION_MODELS_DATAFRAME = None