laser.measles.abm.utils

utils

This module provides utility functions for the laser-measles project.

Functions:

Name	Description
calc_distances	np.ndarray, longitudes: np.ndarray, verbose: bool = False) -> np.ndarray: Calculate the pairwise distances between points given their latitudes and longitudes.
calc_capacity	np.uint32, nticks: np.uint32, cbr: np.float32, verbose: bool = False) -> np.uint32: Calculate the population capacity after a given number of ticks based on a constant birth rate.
seed_infections_randomly	int = 100) -> None: Seed initial infections in random locations at the start of the simulation.
seed_infections_in_patch	int, ninfections: int = 100) -> None: Seed initial infections in a specific location at the start of the simulation.
set_initial_susceptibility_randomly	float = 1.0) -> None: Set the population susceptibility level at the start of the simulation.
set_initial_susceptibility_in_patch	int, susc_frac: float = 1.0) -> None: Set the population susceptibility level at the start of the simulation in a specific patch.

add_at(A, indices, B)

Accumulate rows of B into A at the given indices (scatter-add).

Parameters:

Name	Type	Description	Default
A	ndarray	Destination array that is updated in-place.	required
indices	ndarray	Index into A for each row of B.	required
B	ndarray	Source values to accumulate.	required

calc_capacity(population, nticks, cbr, verbose=False)

Calculate the population capacity after a given number of ticks based on a constant birth rate (CBR).

Parameters:

Name	Type	Description	Default
population	uint32	The initial population.	required
nticks	uint32	The number of ticks (time steps) to simulate.	required
cbr	float32	The constant birth rate per 1000 people per year.	required
verbose	bool	If True, prints detailed population growth information. Defaults to False.	False

Returns:

Type	Description
uint32	np.uint32: The estimated population capacity after the given number of ticks.

calc_distances(latitudes, longitudes, verbose=False)

Calculate the pairwise distances between points given their latitudes and longitudes.

Parameters:

Name	Type	Description	Default
latitudes	ndarray	A 1-dimensional array of latitudes.	required
longitudes	ndarray	A 1-dimensional array of longitudes with the same shape as latitudes.	required
verbose	bool	If True, prints the upper left corner of the distance matrix. Default is False.	False

Returns:

Type	Description
ndarray	np.ndarray: A 2-dimensional array where the element at [i, j] represents the distance between the i-th and j-th points.

Raises:

Type	Description
AssertionError	If latitudes is not 1-dimensional or if latitudes and longitudes do not have the same shape.

seed_infections_in_patch(model, ipatch, ninfections=1)

Seed initial infections in a specific patch of the population at the start of the simulation. This function randomly selects individuals from the specified patch and sets their infection timer to the mean infection duration, effectively marking them as infected. The process continues until the desired number of initial infections is reached.

Parameters:

Name	Type	Description	Default
model		The simulation model containing the population and parameters.	required
ipatch	int	The identifier of the patch where infections should be seeded.	required
ninfections	int	The number of initial infections to seed. Defaults to 100.	1

Returns:

Type	Description
None	None

seed_infections_randomly(model, ninfections=100)

Seed initial infections in random locations at the start of the simulation. This function randomly selects individuals from the population and seeds them with an infection, based on the specified number of initial infections.

Parameters:

Name	Type	Description	Default
model		The simulation model containing the population and parameters.	required
ninfections	int	The number of initial infections to seed. Defaults to 100.	100

Returns:

Type	Description
ndarray	np.ndarray: The nodeids of the individuals seeded with an infection.

seed_infections_randomly_SI(model, ninfections=100)

Seed initial infections in random locations at the start of the simulation. This function randomly selects individuals from the population and seeds them with an infection, based on the specified number of initial infections.

Parameters:

Name	Type	Description	Default
model		The simulation model containing the population and parameters.	required
ninfections	int	The number of initial infections to seed. Defaults to 100.	100

Returns:

Type	Description
None	None

set_initial_susceptibility_in_patch(model, ipatch, susc_frac=1.0)

Set the population susceptibility level at the start of the simulation, in a specific patch. This function randomly selects individuals from the patch and changes their susceptibility to zero, according to the parameter susc_frac.

Parameters:

Name	Type	Description	Default
model		The simulation model containing the population and parameters.	required
ipatch	int	The patch to set susceptibility in	required
susc_frac	float	The fraction of individuals to keep susceptible.	1.0

Returns:

Type	Description
None	None

set_initial_susceptibility_randomly(model, susc_frac=1.0)

Set the population susceptibility level at the start of the simulation. This function randomly selects individuals from the population and changes their susceptibility to zero, according to the parameter susc_frac.

Parameters:

Name	Type	Description	Default
model		The simulation model containing the population and parameters.	required
susc_frac	float	The fraction of individuals to keep susceptible.	1.0

Returns:

Type	Description
None	None