def input_models(fight_slope:    float,
                     move_scale:     float,
                     move_shape:     float,
                     encounter_rate: float,
                     alpha_ss:       float,
                     alpha_rr:       float,
                     beta_ss:        float,
                     beta_rr:        float) -> list:
        """
        Create the input models
        Args:
            fight_slope:    slope of a fight
            move_scale:     movement scale parameter
            move_shape:     movement shape parameter
            encounter_rate: encounter rate constant
            alpha_ss:       growth rate ss
            alpha_rr:       growth rate rr
            beta_ss:        cost ss
            beta_rr:        cost rr

        Returns:

        """

        return [
            growth.max_gut(),
            growth.growth(alpha_ss,
                          alpha_rr,
                          beta_ss,
                          beta_rr,
                          dominance),
            init_bio.init_num(param.lam_0_egg),
            init_bio.init_mass(param.mu_0_egg_ss,
                               param.mu_0_egg_rr,
                               param.sig_0_egg_ss,
                               param.sig_0_egg_rr,
                               dominance),
            init_bio.init_juvenile(44.194,
                                   18.947,
                                   0.552,
                                   0.17,
                                   dominance),
            init_bio.init_mature(param.mu_0_mature_ss,
                                 param.mu_0_mature_rr,
                                 param.sig_0_mature_ss,
                                 param.sig_0_mature_rr,
                                 dominance),
            init_bio.init_plant(param.mu_leaf,
                                param.sig_leaf),
            repro.init_sex(param.female_prob),
            move.larva(move_scale,
                       move_shape),
            forage.adlibitum(param.forage_steps),
            forage.egg(param.egg_factor),
            forage.larva(param.larva_factor),
            forage.fight(fight_slope),
            forage.radius(param.cannibalism_radius),
            forage.encounter(encounter_rate)
        ]
                      param.mu_0_mature_rr,
                      param.sig_0_mature_ss,
                      param.sig_0_mature_rr,
                      dominance),
 init_bio.init_plant(param.mu_leaf,
                     param.sig_leaf),
 develop.egg_dev(param.mu_egg_dev,
                 param.sig_egg_dev),
 develop.larva_dev(param.mu_larva_dev_ss,
                   param.mu_larva_dev_rr,
                   param.sig_larva_dev_ss,
                   param.sig_larva_dev_rr,
                   dominance),
 develop.pupa_dev(param.mu_pupa_dev,
                  param.sig_pupa_dev),
 forage.adlibitum(param.forage_steps),
 forage.egg(param.egg_factor),
 forage.larva(param.larva_factor),
 forage.fight(param.fight_slope),
 forage.encounter(cannib),
 forage.radius(param.cannibalism_radius),
 move.larva(param.larva_scale,
            param.larva_shape),
 move.adult(param.adult_scale,
            param.adult_shape),
 repro.mating(param.mate_encounter),
 repro.radius(param.mate_radius),
 repro.fecundity(param.fecundity_maximum,
                 param.fecundity_decay),
 repro.density(param.eta,
               param.gamma),
Exemple #3
0
class Simulator(object):
    """
    Class to setup and run a simulation of only biomass growth:

    Variables:
        nums:   initial population numbers
        forage: the plant forage model
    """

    grid        = [(keyword.hexagon, 1, 1, True),
                   (keyword.hexagon, 1, 1, True)]
    attrs       = {1: tracking.genotype_attrs}
    data        = (np.inf,)
    emigration  = []
    immigration = []

    input_models = [growth.max_gut(),
                    growth.growth(param.alpha_ss,
                                  param.alpha_rr,
                                  param.beta_ss,
                                  param.beta_rr,
                                  dominance),
                    init_bio.init_num(param.lam_0_egg),
                    init_bio.init_mass(param.mu_0_egg_ss,
                                       param.mu_0_egg_rr,
                                       param.sig_0_egg_ss,
                                       param.sig_0_egg_rr,
                                       dominance),
                    init_bio.init_juvenile(param.mu_0_larva_ss,
                                           param.mu_0_larva_rr,
                                           param.sig_0_larva_ss,
                                           param.sig_0_larva_rr,
                                           dominance),
                    init_bio.init_mature(param.mu_0_mature_ss,
                                         param.mu_0_mature_rr,
                                         param.sig_0_mature_ss,
                                         param.sig_0_mature_rr,
                                         dominance),
                    init_bio.init_plant(param.mu_leaf,
                                        param.sig_leaf),
                    forage.adlibitum(1),
                    sex_model,
                    dev.egg_dev(param.mu_egg_dev,
                                param.sig_egg_dev),
                    dev.pupa_dev(param.mu_pupa_dev,
                                 param.sig_pupa_dev)]
    input_variables = param.repro_values

    nums:       hint.init_pops
    bt_prop:    float
    steps:      hint.step_tuples
    offset_ss:  float           = 0
    offset_rr:  float           = 0
    simulation: hint.simulation = None

    def __post_init__(self):

        larva_dev = dev.larva_dev(param.mu_larva_dev_ss - self.offset_ss,
                                  param.mu_larva_dev_rr - self.offset_rr,
                                  param.sig_larva_dev_ss,
                                  param.sig_larva_dev_rr,
                                  dominance)

        input_models = self.input_models.copy()
        input_models.append(larva_dev)

        self.simulation = main_simulation.Simulation. \
            setup(self.nums,
                  self.grid,
                  self.attrs,
                  self.data,
                  self.bt_prop,
                  self.steps,
                  self.emigration,
                  self.immigration,
                  *input_models,
                  **self.input_variables)

    def collect(self) -> dict:
        """
        Collect a list of masses

        Returns:
            list of all masses in system
        """

        larvae = self.simulation.agents.agents(keyword.pupa)

        values = {
            keyword.homo_r: [],
            keyword.hetero: [],
            keyword.homo_s: [],
        }

        for agent in larvae:
            # noinspection PyUnresolvedReferences
            values[agent.genotype].append(agent.mass)

        return values

    def run(self, times: list) -> None:
        """
        Run the simulation for each time

        Args:
            times: the times for the simulation

        Returns:
            biomass data
        """

        for _ in times[1:]:
            self.simulation.step()
Exemple #4
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fin_time_homo_s = mdl.Span(location=fin_point_ss[0],
                           dimension='height',
                           line_color=colors[1],
                           line_width=line_width,
                           line_dash='dotted')
fin_mass_homo_s = mdl.Span(location=fin_point_ss[1],
                           dimension='width',
                           line_color=colors[1],
                           line_width=line_width,
                           line_dash='dotted')

t = list(range(num_steps))
initial_pops = ((0, 0, 0), (1, 1, 1), (0, 0, 0), (0, 0, 0), (0, 0, 0))
print('{} Running Dominance: {}'.format(datetime.datetime.now(),
                                        param.dominance_0))
simulator_dom_0 = Simulator(initial_pops, 1, forage.adlibitum(1),
                            param.alpha_ss, param.alpha_rr, param.beta_ss,
                            param.beta_rr, param.dominance_0)
bio_dom_0 = simulator_dom_0.run(t)
bio_dom_0_homo_r = bio_dom_0[:, 0]
bio_dom_0_hetero = bio_dom_0[:, 1]
bio_dom_0_homo_s = bio_dom_0[:, 2]
print('{} Running Dominance: {}'.format(datetime.datetime.now(),
                                        param.dominance_1))
simulator_dom_1 = Simulator(initial_pops, 1, forage.adlibitum(1),
                            param.alpha_ss, param.alpha_rr, param.beta_ss,
                            param.beta_rr, param.dominance_1)
bio_dom_1 = simulator_dom_1.run(t)
bio_dom_1_homo_r = bio_dom_1[:, 0]
bio_dom_1_hetero = bio_dom_1[:, 1]
bio_dom_1_homo_s = bio_dom_1[:, 2]
Exemple #5
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class Simulator(object):
    """
    Class to setup and run a simulation of only biomass growth:

    Variables:
        nums:   initial population numbers
        forage: the plant forage model
    """

    grid = [(keyword.hexagon, 1, 1, True), graph.graph(10)]
    attrs = {1: tracking.genotype_attrs}
    data = (np.inf, )
    steps = [({
        keyword.larva: [keyword.move, keyword.consume]
    }, param.forage_steps), ({
        keyword.larva: [keyword.grow, keyword.reset]
    }, )]
    emigration = []
    immigration = []

    input_models = [
        growth.max_gut(),
        growth.growth(param.alpha_ss, param.alpha_rr, param.beta_ss,
                      param.beta_rr, dominance),
        init_bio.init_num(param.lam_0_egg),
        init_bio.init_mass(param.mu_0_egg_ss, param.mu_0_egg_rr,
                           param.sig_0_egg_ss, param.sig_0_egg_rr, dominance),
        init_bio.init_juvenile(44.194, 18.947, 0.552, 0.17, dominance),
        init_bio.init_mature(param.mu_0_mature_ss, param.mu_0_mature_rr,
                             param.sig_0_mature_ss, param.sig_0_mature_rr,
                             dominance),
        init_bio.init_plant(param.mu_leaf, param.sig_leaf),
        repro.init_sex(param.female_prob),
        move.larva(param.larva_scale, param.larva_shape),
        forage.adlibitum(param.forage_steps),
        forage.egg(param.egg_factor),
        forage.larva(param.larva_factor),
        forage.fight(param.fight_slope),
        forage.radius(param.cannibalism_radius),
        # forage.loss(param.loss_slope,
        #             param.mid,
        #             param.egg_factor,
        #             param.larva_factor)
    ]
    input_variables = param.repro_values

    nums: hint.init_pops
    bt_prop: float
    encounter: float
    simulation: hint.simulation = None

    def __post_init__(self):

        input_models = self.input_models.copy()
        input_models.append(forage.encounter(self.encounter))

        self.simulation = main_simulation.Simulation. \
            setup(self.nums,
                  self.grid,
                  self.attrs,
                  self.data,
                  self.bt_prop,
                  self.steps,
                  self.emigration,
                  self.immigration,
                  *input_models,
                  **self.input_variables)

    def run_sim(self, times: list) -> None:
        """
        Run the simulation for each time

        Args:
            times: the times for the simulation

        Returns:
            biomass data
        """

        for _ in times[1:]:
            self.simulation.step()

    def get_start_data(self, data_key: str) -> int:
        """
        Get the start population of larvae

        Args:
            data_key: the genotype table key

        Returns:
            the number of larvae at start
        """

        dataframes = self.simulation.agents.dataframes()

        larva = dataframes['(0, 0)_larva']
        column = larva[data_key]

        return int(column[0])

    def get_final_data(self, data_key: str) -> int:
        """
        Get the final population of larvae

        Args:
            data_key: the genotype table key

        Returns:
            the number of larvae at the end
        """

        dataframes = self.simulation.agents.dataframes()

        timestep = self.simulation.timestep
        pupa = dataframes['(0, 0)_larva']
        column = pupa[data_key]
        value = column[timestep]

        return int(value)

    @classmethod
    def run(cls, rho: float, times: list, data_key: str,
            nums: hint.init_pops) -> tuple:
        """
        Run a bunch of trials
        Args:
            rho:        encounter constant
            times:      time interval
            data_key:   column key
            nums:       init_population

        Returns:
            value of cannibalism rate constant
        """

        print('    {} Starting run for rho: {}'.format(datetime.datetime.now(),
                                                       rho))
        start_data = []
        end_data = []
        for trial_num in range(trials):
            print('        {} running trial: {}'.format(
                datetime.datetime.now(), trial_num))
            sim = cls(nums, 1, rho)
            sim.run_sim(times)
            start_data.append(sim.get_start_data(data_key))
            end_data.append(sim.get_final_data(data_key))

        start_pop = np.mean(start_data)
        end_pop = np.mean(end_data)

        start_lower = np.percentile(start_data, 2.5)
        start_upper = np.percentile(start_data, 97.5)
        end_lower = np.percentile(end_data, 2.5)
        end_upper = np.percentile(end_data, 97.5)

        prop = end_pop / start_pop
        prop_lower = end_lower / start_lower
        prop_upper = end_upper / start_upper

        rate = 1 - prop
        rate_lower = 1 - prop_lower
        rate_upper = 1 - prop_upper

        return prop, prop_lower, prop_upper, rate, rate_lower, rate_upper

    @classmethod
    def rho(cls, rhos: np.array, times: list, data_key: str,
            nums: hint.init_pops) -> tuple:
        """
        Run trials for each rho value

        Args:
            rhos:     list of encounter constants
            times:    time interval
            data_key: data key
            nums:     init population

        Returns:
            list of corresponding values for cannibalism
        """

        prop = []
        prop_lower = []
        prop_upper = []
        rate = []
        rate_lower = []
        rate_upper = []
        for rho in rhos:
            rho_prop, rho_prop_lower, rho_prop_upper, \
                rho_rate, rho_rate_lower, rho_rate_upper = \
                cls.run(rho, times, data_key, nums)

            prop.append(rho_prop)
            prop_lower.append(rho_prop_lower)
            prop_upper.append(rho_prop_upper)
            rate.append(rho_rate)
            rate_lower.append(rho_rate_lower)
            rate_upper.append(rho_rate_upper)

        return prop, prop_lower, prop_upper, rate, rate_lower, rate_upper
Exemple #6
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euler_plot.legend.location = "bottom_right"

euler_plot.title.text_font_size = title_font_size
euler_plot.legend.label_text_font_size = legend_font_size
euler_plot.yaxis.axis_line_width = axis_line_width
euler_plot.xaxis.axis_line_width = axis_line_width
euler_plot.yaxis.axis_label_text_font_size = axis_font_size
euler_plot.xaxis.axis_label_text_font_size = axis_font_size
euler_plot.yaxis.major_label_text_font_size = axis_tick_font_size
euler_plot.xaxis.major_label_text_font_size = axis_tick_font_size
euler_plot.ygrid.grid_line_width = grid_line_width
euler_plot.xgrid.grid_line_width = grid_line_width

initial_pops = ((0, 0, 0), (1, 1, 1), (0, 0, 0), (0, 0, 0), (0, 0, 0))
simulator_bt = Simulator(initial_pops, 1, forage.adlibitum(1))
biomass_bt = simulator_bt.run(t)
biomass_bt_homo_r = biomass_bt[:, 0]
biomass_bt_hetero = biomass_bt[:, 1]
biomass_bt_homo_s = biomass_bt[:, 2]

rk4_plot = plt.figure(plot_width=plot_width, plot_height=plot_height)
rk4_plot.title.text = 'Simulation of Growth, Runge-Kutta 4'
rk4_plot.yaxis.axis_label = 'biomass (mg)'
rk4_plot.xaxis.axis_label = 'time (days)'

rk4_plot.add_layout(fin_time_homo_r)
rk4_plot.add_layout(fin_mass_homo_r)
rk4_plot.add_layout(fin_time_homo_s)
rk4_plot.add_layout(fin_mass_homo_s)