mongo_enabled_learning.py 文件源码

def sw_compute_features(learn_data, overwrite_existing=False, worker_id=None):

#     learn_data = db['learns'].find_one(learn_id)
    model_data = db[learn_data['Model'][-1]].find_one(learn_data['Model'][0])


#     sample_df = load_df_from_sample_notation(model_data['Initial Sample Location'])

    if not check_sample_exists(model_data['Feature Sample Location']) or overwrite_existing:

        feature_generating_function_code = marshal.loads(db[model_data['Feature Generation Function'][-1]]\
                                                  .find_one(model_data['Feature Generation Function'][0])['Code'])


        feature_generating_function = types.FunctionType(feature_generating_function_code, globals())

        # save_df_to_sample_notation(, model_data['Feature Sample Location'])
        learn_data = feature_generating_function(learn_data, model_data)

    learn_data['Status']['Features Computed'] = True
    db['learns'].update(learn_data['_id'], learn_data)