spatiocoexistence.model module

class spatiocoexistence.model.SpatioCoexistenceModel

Bases: object

Initialize the model with parameters from a dictionary or a file. If neither is provided, use default parameters.

Parameters:

parameter_filePath, optional

Path to a parameter file

paramsdict, optional

Dictionary of model parameters

initial_inventorynp.ndarray | Path, optional

Initial inventory data or path to file containing it

use_initial_as_referencebool, default=False

If True, the initial_inventory is only used for plotting comparison and a new inventory is created for simulation

__init__(parameter_file=None, params=None, initial_inventory=None, use_initial_as_reference=False, reference_inventory=None, threads=1)

Initialize the model with parameters from a dictionary or a file. If neither is provided, use default parameters.

Parameters:

parameter_filePath, optional

Path to a parameter file

paramsdict, optional

Dictionary of model parameters

initial_inventorynp.ndarray | Path, optional

Initial inventory data or path to file containing it

use_initial_as_referencebool, default=False

If True, the initial_inventory is only used for plotting comparison and a new inventory is created for simulation

step()

One simulation timestep consists of these processes in the same order.

cy_run(n_steps)

run(n_steps)

get_inventory()

Return type:

ndarray

get_params()

Return the current model parameters as a dictionary.

Return type:

dict

update_params(params)

Set the model parameters from a dictionary and update radius if present.

plot(title, initial_plot=False, axs=None, threshold=50, filter=1.0, abundances=None, figsize=(22, 10))

Plot the current state of the model.

run_with_plotting(n_steps=1000, plot_interval=50, threshold=50, figsize=(24, 12))

Run simulation with interactive plotting.

optimize_parameters(start_params, lower, upper, rhobeg, rhoend, param_names, stat_funcs, stat_indices=None, n_init=50, n_iter=10, iter_steps=5, reference_inventory=None)

Generic optimizer for model parameters to fit arbitrary statistics using log_likelihood.

Parameters

start_paramsnp.ndarray

Initial guess for parameters.

lowernp.ndarray

Lower bounds for parameters.

uppernp.ndarray

Upper bounds for parameters.

param_nameslist[str]

Names of parameters to optimize (order matches start_params).

stat_funcslist of (func, func_kwargs)

Each tuple: (statistic function, kwargs for function).

stat_indiceslist of slices or lists, optional

For each stat_func, which indices to use (default: use all).

n_initint

Initial run steps.

n_iterint

Number of iterations for averaging.

iter_stepsint

Steps per iteration.