# set vd
vd = {'pkg': 'Content in .pkl'}
args.shell = True
# Analyze ------------------------------------------------------------------------------------------------------
if args.analyze:
from src.analysis import Analysis
if args.analyze == 'model':
# This analyze the training results stored with each model in the .pkl
if args.data:
analysis = Analysis(p_data=args.data)
else:
analysis = Analysis(p_data=_d_model_)
analysis.use_f1 = args.use_f1
data = analysis.compile_batch_train_results()
vd = {'data': 'Compiled training data (Pandas dataframe)'}
if args.analyze == 'precision' and args.pred_data and args.pred_data is not 'param':
# Generate a series of predictions with incremental rounding cutoff (greater precision)
Analysis().step_precisions(d_out=args.out,
model=m,
data=m.datas[-1],
predictions=res['pred'],
evaluations=res['eval'])
# Enable interaction \______________________________________________________________________________________________
if args.shell:
interact(var_desc=vd, local=locals())
