data

Data loading and preparation utilities for LOS estimation.

class los_estimator.data.DataLoader(data_config: DataConfig)

Bases: object

Data loader for LOS estimation datasets.

load_icu_data(start_day, end_day) → pandas.DataFrame

Load incidence and ICU occupancy data.

load_init_parameters(file) → pandas.DataFrame

Load initial parameters for the model.

read_csv(path, *args, **kwargs)

Read CSV file from packaged data.

read_excel(path, *args, **kwargs) → pandas.DataFrame

Read Excel file from packaged data.

class los_estimator.data.DataPackage(df_occupancy: pandas.DataFrame, real_los: pandas.Series, df_init: pandas.DataFrame, xtick_pos: list, xtick_label: list)

Bases: object

Container for all loaded data required for LOS estimation.

df_occupancy

ICU occupancy data over time.

Type:

pd.DataFrame

real_los

Real length of stay values for validation.

Type:

pd.Series

df_init

Initial condition data.

Type:

pd.DataFrame

xtick_pos

Positions for x-axis tick marks in plots.

Type:

list

xtick_label

Labels for x-axis tick marks in plots.

Type:

list

class los_estimator.data.DataUtils

Bases: object

Utility functions for data processing and manipulation.

Provides static methods for common data operations like date conversions and generating axis labels for time series plots.

generate_xticks()

Generate x-axis tick positions and labels for time series plots.

Creates tick marks at the first day of each month, with year labels added for January or the first data point.

Parameters:

df (pd.DataFrame) – DataFrame with datetime index.

Returns:

(xtick_pos, xtick_label) lists for plot formatting.

Return type:

tuple