def max_gut():
"""
Create the max_gut model
Returns:
a functional mathematical model for the simulation
"""
return models.MaxGut()
def adlibitum(forage_steps: int):
"""
Create a true adlibitum plant consume model
Args:
forage_steps: the number of steps that forage takes place over
Returns:
a functional mathematical model for the simulation
"""
max_gut = bio.MaxGut()
return models.PlantAdLibitum(forage_steps, max_gut)
def starvation(forage_steps: int, theta: float, sig_starve: float):
"""
Create a starvation plat consume model
Args:
forage_steps: the number of steps that forage takes place over
theta: starvation factor
sig_starve: std in food amounts
Returns:
a functional mathematical model for the simulation
"""
max_gut = bio.MaxGut()
return models.PlantStarve(forage_steps, theta, sig_starve, max_gut)
def loss(loss_slope: float, mid: hint.variable, egg_factor: float,
larva_factor: float):
"""
Create a mathematical model for loss
Args:
loss_slope: slope of transition
mid: equality probability factors
egg_factor: the factor for how much of egg can be eaten
larva_factor: the factor for how much of larva can be eaten
Returns:
a functional mathematical model for the simulation
"""
max_gut = bio.MaxGut()
forage_egg = egg(egg_factor)
forage_larva = larva(larva_factor)
return models.Loss(loss_slope, mid, max_gut, forage_egg, forage_larva)
def biomass_models(number, mass, factor, degree, mass_middle_homo_s,
time_middle_homo_s, mass_middle_homo_r, time_middle_homo_r,
mass_final_homo_s, time_final_homo_s, mass_final_homo_r,
time_final_homo_r, mass_sigma):
"""
Create the biomass models
Args:
number: data on numbers of eggs in egg_mass
mass: data on mass of egg_mass
factor: factor of how resistant relates to susceptible
degree: degree of dominance
mass_middle_homo_s: susceptible mid point mass
time_middle_homo_s: susceptible mid point time
mass_middle_homo_r: resistant mid point mass
time_middle_homo_r: resistant mid point time
mass_final_homo_s: susceptible final mass
time_final_homo_s: susceptible final time
mass_final_homo_r: resistant final mass
time_final_homo_r: resistant final time
mass_sigma: standard deviation in adult mass
Returns:
max_gut model,
growth model,
init_num model,
init_mass model,
init_juvenile model,
init_mature model
"""
# Egg fit
mass_data = egg_mass(number, mass)
init_mass_homo_s = mass_data[3]
init_mass_homo_r = mass_data[3] * factor
# Larva fit
biomass_data_homo_s = biomass(init_mass_homo_s, mass_middle_homo_s,
time_middle_homo_s, mass_final_homo_s,
time_final_homo_s)
biomass_data_homo_r = biomass(init_mass_homo_r, mass_middle_homo_r,
time_middle_homo_r, mass_final_homo_r,
time_final_homo_r)
# Create the max_gut model
max_gut = models.MaxGut()
# Create the growth model
growth_alpha_homo_s = biomass_data_homo_s[0]
growth_alpha_homo_r = biomass_data_homo_r[0]
growth_alpha_hetero = hetero(growth_alpha_homo_s, growth_alpha_homo_r,
degree)
growth_alpha = {
keyword.homo_s: growth_alpha_homo_s,
keyword.homo_r: growth_alpha_homo_r,
keyword.hetero: growth_alpha_hetero
}
growth_beta_homo_s = biomass_data_homo_s[1]
growth_beta_homo_r = biomass_data_homo_r[1]
growth_beta_hetero = hetero(growth_beta_homo_s, growth_beta_homo_r, degree)
growth_beta = {
keyword.homo_s: growth_beta_homo_s,
keyword.homo_r: growth_beta_homo_r,
keyword.hetero: growth_beta_hetero
}
growth = models.Growth(growth_alpha, growth_beta)
# Create the initial mass models
# init_num
init_num_lam = mass_data[0]
init_num = models.InitNum(init_num_lam)
# init_mass
init_mass_mu_homo_s = mass_data[1]
init_mass_mu_homo_r = mass_data[1] * factor
init_mass_mu_hetero = hetero(init_mass_mu_homo_s, init_mass_mu_homo_r,
degree)
init_mass_mu = {
keyword.homo_s: init_mass_mu_homo_s,
keyword.homo_r: init_mass_mu_homo_r,
keyword.hetero: init_mass_mu_hetero
}
init_mass_sigma = mass_data[2]
init_mass_max_homo_s = biomass_data_homo_s[2]
init_mass_max_homo_r = biomass_data_homo_r[2]
init_mass_max_hetero = hetero(init_mass_max_homo_s, init_mass_max_homo_r,
degree)
init_mass_maximum = {
keyword.homo_s: init_mass_max_homo_s,
keyword.homo_r: init_mass_max_homo_r,
keyword.hetero: init_mass_max_hetero
}
init_mass = models.InitMass(init_mass_mu, init_mass_sigma,
init_mass_maximum)
# init_juvenile
init_juvenile_lam = init_num_lam
init_juvenile_mu = init_mass_mu
init_juvenile_sigma = init_mass_sigma
init_juvenile_maximum = init_mass_maximum
init_juvenile = models.InitJuvenile(init_juvenile_lam, init_juvenile_mu,
init_juvenile_sigma,
init_juvenile_maximum)
# init_mature
init_mature_mu_homo_s = mass_final_homo_s
init_mature_mu_homo_r = mass_final_homo_r
init_mature_mu_hetero = hetero(init_mature_mu_homo_s,
init_mature_mu_homo_r, degree)
init_mature_mu = {
keyword.homo_s: init_mature_mu_homo_s,
keyword.homo_r: init_mature_mu_homo_r,
keyword.hetero: init_mature_mu_hetero
}
init_mature_sigma = mass_sigma
init_mature_maximum = init_mass_maximum
init_mature = models.InitMature(init_mature_mu, init_mature_sigma,
init_mature_maximum)
return max_gut, growth, init_num, init_mass, init_juvenile, init_mature
mass_const_homo_r)
mass_constant = {keyword.homo_s: mass_const_homo_s,
keyword.homo_r: mass_const_homo_r,
keyword.hetero: mass_const_hetero}
# Create the data points
mid_point_r = (input_data.time_middle_r, input_data.mass_middle_r)
mid_point_s = (input_data.time_middle_s, input_data.mass_middle_s)
fin_point_r = (input_data.time_final_r, input_data.mass_final_r)
fin_point_s = (input_data.time_final_s, input_data.mass_final_s)
# Generate the input models
# max_gut
max_gut = models.MaxGut()
# growth
growth_alpha_homo_s = biomass_data_homo_s[0]
growth_alpha_homo_r = biomass_data_homo_r[0]
growth_alpha_hetero = input_data.hetero(growth_alpha_homo_s,
growth_alpha_homo_r)
growth_alpha = {keyword.homo_s: growth_alpha_homo_s,
keyword.homo_r: growth_alpha_homo_r,
keyword.hetero: growth_alpha_hetero}
growth_beta_homo_s = biomass_data_homo_s[1]
growth_beta_homo_r = biomass_data_homo_r[1]
growth_beta_hetero = input_data.hetero(growth_beta_homo_s,
growth_beta_homo_r)
growth_beta = {keyword.homo_s: growth_beta_homo_s,
keyword.homo_r: growth_beta_homo_r,
keyword.hetero: growth_beta_hetero}
def setUp(self):
"""Setup the tests"""
self.MaxGut = model.MaxGut()