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)
