Results

Simulation output for a single model run.

Usage

Source

Results(model)

Methods

Name Description
__init__() Create instance of Results.
mean_by_category() Find mean of metric by response category, and then also by outcome.
patient_df() Return per-patient results as a DataFrame.
summary_df() Return run-level summary in long format.
utilisation() Return mean time-weighted ambulance utilisation.
utilisation_df() Return time-weighted ambulance utilisation intervals.

__init__()

Create instance of Results.

Usage

Source

__init__(model)
Parameters
model: Model
A model instance that has already been executed (model.run())

mean_by_category()

Find mean of metric by response category, and then also by outcome.

Usage

Source

mean_by_category(df, col, name)
Parameters
df: pd.DataFrame

Patient-level dataframe.

col: str

Column to aggregate.

name: str
Name to assign in the metric column.
Returns
pd.DataFrame
Long-format dataframe with aggregated results.

patient_df()

Return per-patient results as a DataFrame.

Usage

Source

patient_df()

Each row represents one patient. Patients who had not completed their full pathway by the end of the run will have NaN for unset time attributes.

Returns
pd.DataFrame
Dataframe with patient-level results.

summary_df()

Return run-level summary in long format.

Usage

Source

summary_df()
Returns
pd.DataFrame
Run-level summary.

utilisation()

Return mean time-weighted ambulance utilisation.

Usage

Source

utilisation()
Returns
float
Mean time-weighted ambulance utilisation.

utilisation_df()

Return time-weighted ambulance utilisation intervals.

Usage

Source

utilisation_df()
Returns
pd.DataFrame
Columns: time, busy, interval_duration, utilisation.