def setUp(self): DB = pm.MongoClient(port=22334)['ModelBehavior'] feature_name = 'IT' feature_split = [1, 2] features, meta = feature_loader.get_features_by_name(feature_name) decoder_model = decoder_models.get_decoder_model_by_name('StandardModel') gridfs_name = '_'.join([decoder_model['name'], feature_name, 'results'])+'TEST' fs = gridfs.GridFS(DB, gridfs_name) # Decide where to store things additional_info = {'feature_split': feature_split, 'test': True} self.F = features self.decoder_model = decoder_model self.meta = meta self.fs = fs self.feature_inds = feature_split self.additional_info = additional_info self.ids = []
def setUp(self): DB = pm.MongoClient(port=22334)['ModelBehavior'] feature_name = 'IT' feature_split = [1, 2] features, meta = feature_loader.get_features_by_name(feature_name) decoder_model = decoder_models.get_decoder_model_by_name( 'StandardModel') gridfs_name = '_'.join( [decoder_model['name'], feature_name, 'results']) + 'TEST' fs = gridfs.GridFS(DB, gridfs_name) # Decide where to store things additional_info = {'feature_split': feature_split, 'test': True} self.F = features self.decoder_model = decoder_model self.meta = meta self.fs = fs self.feature_inds = feature_split self.additional_info = additional_info self.ids = []
__author__ = 'ardila' import sys import gridfs import pymongo as pm feature_name = sys.argv[1] decoder_model_name = sys.argv[3] # Can make this an option later feature_split = [int(ind) for ind in sys.argv[2].split(',')] # Load feature from name features, meta = feature_loader.get_features_by_name(feature_name) #Load decoder model from name decoder_model = decoder_models.get_decoder_model_by_name(decoder_model_name) fs = store_feature_results.get_gridfs(decoder_model_name=decoder_model_name, # Decide where to store things feature_name=feature_name) additional_info = {'feature_split': feature_split} store_feature_results.store_subsampled_feature_results(features, meta, decoder_model, fs, feature_split, additional_info)
from BehavioralBenchmark.ImageLevel import store_feature_results, feature_loader, decoder_models __author__ = 'ardila' import sys import gridfs import pymongo as pm feature_name = sys.argv[1] decoder_model_name = sys.argv[3] # Can make this an option later feature_split = [int(ind) for ind in sys.argv[2].split(',')] # Load feature from name features, meta = feature_loader.get_features_by_name(feature_name) #Load decoder model from name decoder_model = decoder_models.get_decoder_model_by_name(decoder_model_name) fs = store_feature_results.get_gridfs( decoder_model_name=decoder_model_name, # Decide where to store things feature_name=feature_name) additional_info = {'feature_split': feature_split} store_feature_results.store_subsampled_feature_results(features, meta, decoder_model, fs, feature_split, additional_info)