add a Evaluator class for evaluation

README.md

@@ -93,7 +93,7 @@ $ python prepare_data.py --origin_data_dir <your_data_directory_for_hydromodel>
 To run calibration with CAMLES dataset, you can use the following code:
 
 ```Shell
-$ python calibrate_xaj.py --exp camels --warmup_length 365 --model {\"name\":\"xaj_mz\",\"source_type\":\"sources\",\"source_book\":\"HF\"} --algorithm {\"name\":\"SCE_UA\",\"random_seed\":1234,\"rep\":5000,\"ngs\":20,\"kstop\":3,\"peps\":0.1,\"pcento\":0.1}
+$ python calibrate_xaj.py --exp example --warmup_length 365 --model {\"name\":\"xaj_mz\",\"source_type\":\"sources\",\"source_book\":\"HF\"} --algorithm {\"name\":\"SCE_UA\",\"random_seed\":1234,\"rep\":5000,\"ngs\":20,\"kstop\":3,\"peps\":0.1,\"pcento\":0.1}
 ```
 
 To use your own data, run the following code:
@@ -105,12 +105,18 @@ $ python calibrate_xaj.py --exp example --warmup_length 365 --model {\"name\":\"
 # python calibrate_xaj.py --exp <name of directory of the prepared data> --warmup_length <hydromodel need some warm-up period> --model <model function parameters> --algorithm <calibration algorithm parameters>
 ```
 
+Then you can evaluate the calibrated model with the following code:
+
+```Shell
+$ python evaluate_xaj.py --exp example
+```
+
 ### See the results
 
-Run the following code:
+Run the following code to see the results of the evaluation:
 
 ```Shell
-$ python datapostprocess4calibrate.py --exp example
+$ python post_process.py --exp example
 ```
 
 You will get two metrics files in the "example" directory: "basins_test_metrics_mean_all_cases.csv" and "basins_test_metrics_median_all_cases.csv". The first one is the mean metrics of the testing period -- one row means the mean metrics of all basins in a case, and the second one is the median metrics.

hydromodel/datasets/data_preprocess.py

@@ -467,7 +467,7 @@ def get_ts_from_diffsource(data_type, data_dir, periods, basin_ids):
     return ts_data
 
 
-def get_pe_q_from_ts(ts_xr_dataset):
+def _get_pe_q_from_ts(ts_xr_dataset):
     """Transform the time series data to the format that can be used in the calibration process
 
     Parameters

hydromodel/trainers/calibrate_ga.py

@@ -20,10 +20,9 @@
 from hydroutils import hydro_file, hydro_stat
 
 
-from datasets.data_postprocess import plot_sim_and_obs
+from hydromodel.datasets.data_postprocess import plot_sim_and_obs, plot_train_iteration
 from hydromodel.models.model_config import MODEL_PARAM_DICT
 from hydromodel.models.model_dict import MODEL_DICT, rmse43darr
-from datasets.data_postprocess import plot_train_iteration
 
 
 def evaluate(individual, x_input, y_true, warmup_length, model):