def test_CSVMarshall_uses_same_paths_as_paths_module(tmpdir):
"""
Runs the gamut of paths produced by paths.py and compares to CSVMarshall
path computation.
"""
from covid_model_seiir_pipeline.paths import (
RegressionPaths,
ForecastPaths,
)
root = pathlib.Path(tmpdir)
m = CSVMarshall(root)
r = RegressionPaths(root)
f = ForecastPaths(root, scenarios=["happy"])
dargs = {'draw_id': 4}
sdargs = {'scenario': "happy", 'draw_id': 4}
# forecasting/data.py
# load_regression_coefficients
assert r.get_coefficient_file(**dargs) == m.resolve_key(
Keys.coefficient(**dargs))
# load_dates_df
assert r.get_date_file(**dargs) == m.resolve_key(Keys.date(**dargs))
# load_beta_regression
assert r.get_beta_regression_file(**dargs) == m.resolve_key(
Keys.regression_beta(**dargs))
# load_infection_data
assert r.get_data_file(**dargs) == m.resolve_key(
Keys.location_data(**dargs))
# load_beta_params
assert r.get_beta_param_file(**dargs) == m.resolve_key(
Keys.parameter(**dargs))
# save_components
assert f.get_components_path(**sdargs) == m.resolve_key(
Keys.components(**sdargs))
# save_beta_scales
assert f.get_beta_scaling_path(**sdargs) == m.resolve_key(
Keys.beta_scales(**sdargs))
# save_outputs
assert f.get_outputs_path(**sdargs) == m.resolve_key(
Keys.forecast_raw_outputs(**sdargs))
# regression/data.py
# save_beta_param_file
assert r.get_beta_param_file(**dargs) == m.resolve_key(
Keys.parameter(**dargs))
# save_date_file
assert r.get_date_file(**dargs) == m.resolve_key(Keys.date(**dargs))
# save_regression_coefficients
assert r.get_coefficient_file(**dargs) == m.resolve_key(
Keys.coefficient(**dargs))
# save_regression_betas
assert r.get_beta_regression_file(**dargs) == m.resolve_key(
Keys.regression_beta(**dargs))
# save_location_data
assert r.get_data_file(**dargs) == m.resolve_key(
Keys.location_data(**dargs))
def test_beta_scales_marshall(self, instance, beta_scales):
self.assert_load_dump_workflow_correct(
instance,
beta_scales,
key=Keys.beta_scales(scenario='happy', draw_id=4))
def load_beta_scales(self, scenario: str, draw_id: int):
return self.forecast_marshall.load(
MKeys.beta_scales(scenario=scenario, draw_id=draw_id))
def save_beta_scales(self, scales: pd.DataFrame, scenario: str,
draw_id: int):
self.forecast_marshall.dump(scales,
key=MKeys.beta_scales(scenario=scenario,
draw_id=draw_id))