6. CLI reference#
This page has reference information about Maud’s command line interface.
6.1. sample#
Generate MCMC samples given a user input directory.
This function creates a new directory in output_dir with a name starting with “maud_output”. It first copies the directory at data_path into the new this directory at new_dir/user_input, then runs the running_stan.sample function to write samples in new_dir/samples. Finally it prints the results of cmdstanpy’s diagnose and summary methods.
Run the sample function as a click command.
sample [OPTIONS] DATA_PATH
Options
- --output_dir <output_dir>#
Where to save Maud’s output
Arguments
- DATA_PATH#
Required argument
6.2. simulate#
Generate draws from the initial values.
simulate [OPTIONS] DATA_PATH
Options
- --output_dir <output_dir>#
Where to save the output
- -n <n>#
Number of simulations
Arguments
- DATA_PATH#
Required argument
6.3. variational#
Generate MCMC samples given a user input directory.
This function creates a new directory in output_dir with a name starting with “maud_output”. It first copies the directory at data_path into the new this directory at new_dir/user_input, then runs the running_stan.sample function to write samples in new_dir/samples. Finally it prints the results of cmdstanpy’s diagnose and summary methods.
variational [OPTIONS] DATA_PATH
Options
- --output_dir <output_dir>#
Where to save Maud’s output
Arguments
- DATA_PATH#
Required argument
6.4. optimize#
Optimize the model parameters.
optimize [OPTIONS] DATA_PATH
Options
- --output_dir <output_dir>#
Where to save the output
Arguments
- DATA_PATH#
Required argument
6.5. predict#
Generate MCMC samples given a Maud output folder at train_path.
This function creates a new directory in output_dir with a name starting with “maud-predict-output”. It first copies the testing directory at train_path into the new this directory at new_dir/user_input, then runs the running_stan.predict_out_of_sample function to write samples in new_dir/oos_samples.
The trained output is stored in the new_dir/trained_samples folder along with the user input required to generate the trained samples.
predict [OPTIONS] DATA_PATH
Arguments
- DATA_PATH#
Required argument