from importlib import import_module
import os
-import copy
import pickle
import xgboost
@@ -1195,7 +1194,7 @@ Source code for icenet.tools.process
with open(os.path.join(cache_directory, f'output_{i}.pkl'), 'rb') as handle:
X_, Y_, W_, ids, info, genesis_args = pickle.load(handle)
-
+
if i > 0:
X = np.concatenate((X, X_), axis=0) # awkward will cast numpy automatically
Y = np.concatenate((Y, Y_), axis=0)
@@ -1440,7 +1439,7 @@ Source code for icenet.tools.process
output['trn']['data'], imputer = impute_datasets(data=output['trn']['data'], features=impute_vars, args=args['imputation_param'], imputer=None)
output['val']['data'], imputer = impute_datasets(data=output['val']['data'], features=impute_vars, args=args['imputation_param'], imputer=imputer)
- fmodel = f'{args["modeldir"]}/imputer.pkl'
+ fmodel = os.path.join(args["modeldir"], f'imputer__{args["__hash_post_genesis__"]}.pkl')
print(f'Saving imputer to: {fmodel}', 'green')
pickle.dump(imputer, open(fmodel, 'wb'), protocol=pickle.HIGHEST_PROTOCOL)
@@ -1451,9 +1450,9 @@ Source code for icenet.tools.process
if args['reweight']:
if args["reweight_file"] is None:
- fmodel = f'{args["datadir"]}/reweighter_{args["__hash_genesis__"]}.pkl'
+ fmodel = os.path.join(args["datadir"], f'reweighter__{args["__hash_post_genesis__"]}.pkl')
else:
- fmodel = f'{args["datadir"]}/{args["reweight_file"]}'
+ fmodel = os.path.join(args["datadir"], args["reweight_file"])
if 'load' in args['reweight_mode']:
print(f'Loading reweighting model from: {fmodel} [runmode = {runmode}]', 'green')
@@ -1483,7 +1482,7 @@ Source code for icenet.tools.process
## Imputate
if args['imputation_param']['active']:
- fmodel = f'{args["modeldir"]}/imputer.pkl'
+ fmodel = os.path.join(args["modeldir"], f'imputer__{args["__hash_post_genesis__"]}.pkl')
print(f'Loading imputer from: {fmodel}', 'green')
imputer = pickle.load(open(fmodel, 'rb'))