from pathlib import Path
from typing import Optional
from metaDMG.filters import load_results
# Needed for sphinx to include load_results
__all__ = ["compute_config", "run_dashboard", "load_results"]
[docs]def compute_config(
config_file: Path = Path("config.yaml"),
force: bool = False,
) -> None:
"""Run the LCA and fit on the config file.
Parameters
----------
config_file
The config file to run the computations on, by default Path("config.yaml")
force
Force the computation, i.e. do not load (intermediate) results, by default False
"""
from metaDMG import utils
utils.check_metaDMG_fit()
from metaDMG.fit import run_workflow
configs = utils.make_configs(config_file=config_file, force=force)
run_workflow(configs)
[docs]def run_dashboard(
config_file: Path = Path("config.yaml"),
results: Optional[Path] = None,
debug: bool = False,
server: bool = False,
port: int = 8050,
host: str = "0.0.0.0",
) -> None:
"""Visualise the results in an interactive dashboard
Parameters
----------
config_file
The the config file to use to locate the results directory, by default Path("config.yaml")
results
The results directory, by default None
debug
Whether or not the debug-button should be displayed, by default False
server
Whether or not it should behave as running on a server, by default False
port
Dashboard port, by default 8050
host
Dashboard host address, by default "0.0.0.0"
"""
from metaDMG import utils
utils.check_metaDMG_viz()
from metaDMG.viz import start_dashboard
results_dir = utils.get_results_dir(
config_file=config_file,
results_dir=results,
)
start_dashboard(
results_dir=results_dir,
debug=debug,
server=server,
host=host,
port=port,
)
