Output files¶

Monte Carlo class will generate at least four different type of files on the path ./logs/montecarlo/<year>/<month>/<day>/run_<time>/

run_data.csv: Raw results with the loss, epoch, model, etc.
<model_name>_statistical_result.csv: One file is generated for each model in the monte carlo simulation. It contains the statistical results per epoch of the model.
models_details.json: A full detailed description of each model to be trained.
run/iteration<iteration>_model<model index and name>/<model_name>_results_fit.csv: Inside the run folder there is information of the result for each model at each iteration.

There are many other optional files that can be controled using the output_config dictionary variable of booleans:

output_config = {
        'plot_all': False,
        'confusion_matrix': False,
        'excel_summary': True,
        'summary_of_run': True,
        'tensorboard': False,
        'save_weights': False,
        'safety_checkpoints': False
    }

A complementary file test_results.csv can be generated if test_data is passed run() (None by default).

Usage example:

monte_carlo = MonteCarlo()
monte_carlo.output_config['plot_all'] = True      # Tell monte carlo to save the plots

Output files¶
Variable	Generated File(s)	Description
‘excel_summary’	.logs/*.xlsx	Adds a row to an excel file with information of the monte carlo run
	./logs/montecarlo/<year>/<month>/<day>/run_<time>/run_data.csv	Always generated. All monte carlo raw results.
	./logs/montecarlo/<year>/<month>/<day>/run_<time>/<model_name>_statistical_result.csv	Always generated. Statistical results per model.
	./logs/montecarlo/<year>/<month>/<day>/run_<time>/models_details.json	Always generated. A full detailed description of each model to be trained.
‘plot_all’	./logs/montecarlo/<year>/<month>/<day>/run_<time>/plots/	Plots generated using MonteCarloAnalyzer.do_all()
‘confusion_matrix’	./logs/montecarlo/<year>/<month>/<day>/run_<time>/<model_name>_confusion_matrix.csv	Generates a confusion matrix file per model
‘summary_of_run’	./logs/montecarlo/<year>/<month>/<day>/run_<time>/run_summary.txt	Generates a user friendly monte carlo text summary
‘safety_checkpoints’	./logs/montecarlo/<year>/<month>/<day>/run_<time>/run_data.csv	Creates the run_data.csv as data is obtained not to lose information if an unexpected exit happens.
	./logs/montecarlo/<year>/<month>/<day>/run_<time>/test_results.csv	This is generated if a test_data is passed to the `run()` method of MonteCarlo.
‘tensorboard’	./logs/montecarlo/<year>/<month>/<day>/run_<time>/tensorboard/	Saves tensorboard results like graph, loss and accuracy.