pearl.population

Module for population initialization in PEARL.

Functions

`add_age_categories`(population)	Add an age_cat column corresponding to the decade age of the agent, truncated at a maximum age category of 7.
`add_default_columns`(population)	Add default values for columns necessary for simulation to all agents that are in the population at the start of simulation.
`add_default_columns_new`(population)	Add default columns for new agents that are added to the population after the start of simulation.
`add_id`(population)	Add an id column to the population DataFrame.
`add_multimorbidity`(population)	Calculate the multimorbidity for each agent.
`cast_type`(population)	Cast population columns to save memory.
`delta_bmi`(population)	Calculate the change in BMI for each agent.
`sort_alphabetically`(population)	Sort columns alphabetically.

Classes

`ApplyComorbidities`(paramaters, user, new_init)	Apply all comorbidities sequentially
`BasePopulation`(parameters, population_size)	Base population object.
`Bmi`(parameters)	Calculate all BMI related variables.
`Cd4Increase`(parameters)	Calculate the increase in CD4 count for the population.
`Comorbidity`(parameters, comorbidity, user, ...)	Assign comorbidities for a random subset of the population based on each agents characteristics.
`H1yy`(parameters)	Assign diagnosis date (H1yy) to the population.
`Ltfu`(parameters, population_size)	Lost to follow up event.
`NewAges`(parameters)	Simulate ages for new initiators.
`NewPopulation`(parameters)	Population generator for new initiators.
`NonUserPopInit`(parameters, population_size)	Population generator for ART non-users.
`PearlPopulation`(parameters)	Base PEARL population generator
`PostArtBMI`(parameters)	Calculate Post-ART BMI for the population.
`PreArtBMI`(parameters)	Calculate pre-ART BMI for the population.
`SimulateAges`(parameters, population_size[, h1yy])	Simulate ages for the given popeulation size and conditions.
`SqrtCd4nInit`(parameters)	Assign initial sqrtCD4 counts to the population.
`SqrtCd4nNew`(parameters)	Assign sqrtCD4 counts to new agents.
`Status`(parameters, status)	Assign a status to the populaton.
`UserPopInit`(parameters, population_size)	Population generator for ART users.
`YearsOutCare`(parameters)	Calculate years out of care for delayed start agents.

pearl.population.add_id(population: pandas.DataFrame) → pandas.DataFrame[source]

Add an id column to the population DataFrame.

Parameters:: population (pd.DataFrame) – Population Dataframe.
Returns:: Population DataFrame with id column added.
Return type:: pd.DataFrame

pearl.population.add_age_categories(population: pandas.DataFrame) → pandas.DataFrame[source]

Add an age_cat column corresponding to the decade age of the agent, truncated at a maximum age category of 7.

Parameters:: population (pd.DataFrame) – Population with an age column.
Returns:: Population with age_cat column added.
Return type:: pd.DataFrame

pearl.population.add_default_columns(population: pandas.DataFrame) → pandas.DataFrame[source]

Add default values for columns necessary for simulation to all agents that are in the population at the start of simulation.

Parameters:: population (pd.DataFrame) – Population DataFrame to add default columns to.
Returns:: Population with added default columns.
Return type:: pd.DataFrame

pearl.population.add_default_columns_new(population: pandas.DataFrame) → pandas.DataFrame[source]

Add default columns for new agents that are added to the population after the start of simulation.

Parameters:: population (pd.DataFrame) – Population DataFrame to add default columns to.
Returns:: Population with added default columns.
Return type:: pd.DataFrame

pearl.population.delta_bmi(population: pandas.DataFrame) → pandas.DataFrame[source]

Calculate the change in BMI for each agent.

Parameters:: population (pd.DataFrame) – Population Dataframe.
Returns:: Population DataFrame with delta_bmi column added.
Return type:: pd.DataFrame

pearl.population.add_multimorbidity(population: pandas.DataFrame) → pandas.DataFrame[source]

Calculate the multimorbidity for each agent.

Parameters:: population (pd.DataFrame) – Population Dataframe.
Returns:: Population DataFrame with mm column added.
Return type:: pd.DataFrame

pearl.population.sort_alphabetically(population: pandas.DataFrame) → pandas.DataFrame[source]

Sort columns alphabetically.

Parameters:: population (pd.DataFrame) – Population Dataframe.
Returns:: Population DataFrame with columns sorted alphabetically.
Return type:: pd.DataFrame

pearl.population.cast_type(population: pandas.DataFrame) → pandas.DataFrame[source]

Cast population columns to save memory.

Parameters:: population (pd.DataFrame) – Population Dataframe.
Returns:: Type cast population Dataframe.
Return type:: pd.DataFrame

class pearl.population.Status(parameters: Parameters, status: int)[source]

Bases: Event

Assign a status to the populaton.

class pearl.population.SimulateAges(parameters: Parameters, population_size: int, h1yy: bool | None = None)[source]

Bases: Event

Simulate ages for the given popeulation size and conditions.

class pearl.population.H1yy(parameters: Parameters)[source]

Bases: Event

Assign diagnosis date (H1yy) to the population.

class pearl.population.SqrtCd4nInit(parameters: Parameters)[source]

Bases: Event

Assign initial sqrtCD4 counts to the population.

class pearl.population.SqrtCd4nNew(parameters: Parameters)[source]

Bases: Event

Assign sqrtCD4 counts to new agents.

class pearl.population.Cd4Increase(parameters: Parameters)[source]

Bases: Event

Calculate the increase in CD4 count for the population.

class pearl.population.PreArtBMI(parameters: Parameters)[source]

Bases: Event

Calculate pre-ART BMI for the population.

class pearl.population.PostArtBMI(parameters: Parameters)[source]

Bases: Event

Calculate Post-ART BMI for the population.

class pearl.population.BasePopulation(parameters: Parameters, population_size: int)[source]

Bases: Event

Base population object.

class pearl.population.Bmi(parameters: Parameters)[source]

Bases: Event

Calculate all BMI related variables.

class pearl.population.Comorbidity(parameters: Parameters, comorbidity: str, user: bool, new_init: bool)[source]

Bases: Event

Assign comorbidities for a random subset of the population based on each agents characteristics.

class pearl.population.ApplyComorbidities(paramaters: Parameters, user: bool, new_init: bool)[source]

Bases: Event

Apply all comorbidities sequentially

class pearl.population.Ltfu(parameters: Parameters, population_size: int)[source]

Bases: Event

Lost to follow up event.

class pearl.population.YearsOutCare(parameters: Parameters)[source]

Bases: Event

Calculate years out of care for delayed start agents.

class pearl.population.NewAges(parameters: Parameters)[source]

Bases: Event

Simulate ages for new initiators.

class pearl.population.UserPopInit(parameters: Parameters, population_size: int)[source]

Bases: Event

Population generator for ART users.

class pearl.population.NonUserPopInit(parameters: Parameters, population_size: int)[source]

Bases: Event

Population generator for ART non-users.

class pearl.population.NewPopulation(parameters: Parameters)[source]

Bases: Event

Population generator for new initiators.

class pearl.population.PearlPopulation(parameters: Parameters)[source]

Bases: Event

Base PEARL population generator