natcap.invest.fisheries.fisheries_model

The Fisheries Model module contains functions for running the model

Variable Suffix Notation: t: time x: area/region a: age/class s: sex

natcap.invest.fisheries.fisheries_model.initialize_vars(vars_dict)

Initializes variables for model run

Parameters

vars_dict (dictionary) – verified arguments and variables

Returns

modified vars_dict with additional variables

Return type

vars_dict (dictionary)

Example Returns:

vars_dict = {
    # (original vars)

    'Survtotalfrac': np.array([...]),  # a,s,x
    'G_survtotalfrac': np.array([...]),  # (same)
    'P_survtotalfrac': np.array([...]),  # (same)
    'N_tasx': np.array([...]),  # Index Order: t,a,s,x
    'H_tx': np.array([...]), # t,x
    'V_tx': np.array([...]), # t,x
    'Spawners_t': np.array([...]),
}

natcap.invest.fisheries.fisheries_model.run_population_model(vars_dict, init_cond_func, cycle_func, harvest_func)

Runs the model

Parameters

• vars_dict (dictionary) –

• init_cond_func (lambda function) – sets initial conditions

• cycle_func (lambda function) – computes numbers for the next time step

• harvest_func (lambda function) – computes harvest and valuation

Returns

vars_dict (dictionary)

Example Returned Dictionary:

{
    # (other items)
    ...
    'N_tasx': np.array([...]),  # Index Order: time, class, sex, region
    'H_tx': np.array([...]),  # Index Order: time, region
    'V_tx': np.array([...]),  # Index Order: time, region
    'Spawners_t': np,array([...]),
    'equilibrate_timestep': <int>,
}

natcap.invest.fisheries.fisheries_model.set_cycle_func(vars_dict, rec_func)

Creates a function to run a single cycle in the model

Parameters

• vars_dict (dictionary) –

• rec_func (lambda function) – recruitment function

Example Output of Returned Cycle Function:

N_asx = np.array([...])
spawners = <int>

N_next, spawners = cycle_func(N_prev)

natcap.invest.fisheries.fisheries_model.set_harvest_func(vars_dict)

Creates harvest function that calculates the given harvest and valuation of the fisheries population over each time step for a given region. Returns None if harvest isn’t selected by user.

Example Outputs of Returned Harvest Function:

H_x, V_x = harv_func(N_tasx)

H_x = np.array([3.0, 4.5, 2.5, ...])
V_x = np.array([6.0, 9.0, 5.0, ...])

natcap.invest.fisheries.fisheries_model.set_init_cond_func(vars_dict)

Creates a function to set the initial conditions of the model

Parameters

vars_dict (dictionary) – variables

Returns

initial conditions function

Return type

init_cond_func (lambda function)

Example Return Array:

N_asx = np.ndarray([...])

natcap.invest.fisheries.fisheries_model.set_recru_func(vars_dict)

Creates recruitment function that calculates the number of recruits for class 0 at time t for each region (currently sex agnostic). Also returns number of spawners

Parameters

vars_dict (dictionary) –

Returns

recruitment function

Return type

rec_func (function)

Example Output of Returned Recruitment Function:

N_next[0], spawners = rec_func(N_prev)