Module fwdpy11.conditional_models

Defining models with specific outcomes.

The API of this module may be subjet to change. Hence, the documentation is minimal.

exception fwdpy11.conditional_models.AddMutationFailure

class fwdpy11.conditional_models.AlleleCount(count)

Specify a number of copies of a mutation.

Parameters:

count (int) – Initial number of copies of a mutation. This value must be > 0.

count

class fwdpy11.conditional_models.AlleleCountRange(minimum, maximum)

Specify a range for a number of copies of a mutation.

Parameters:

• minimum (int) – Minimum number of copies of a mutation. This value must be > 0.

• maximum (int) – Maximum number of copies of a mutation. This value must be > minimum.

maximum

minimum

class fwdpy11.conditional_models.AncientSamplePolicy(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

When to record “preserved” or “ancient” samples:

COMPLETION = 2

Only record the generation when the terminiation condition is first met.

DURATION = 1

During the entire sojourn of the mutation from when it is first added to when the terminiation condition is first met.

NEVER = 0

Never.

class fwdpy11.conditional_models.ConditionalModelOutput(*, pop, params, mutation_index, fixation_index, num_descendant_nodes)

fixation_index

The index of the new mutation in pop.fixations

mutation_index

The index of the new mutation in pop.mutations

num_descendant_nodes

The number of alive nodes initially containing the new mutation

params

The evolved model parameters

pop

The population with the added mutation

class fwdpy11.conditional_models.EvolveOptions(simplification_interval=100, suppress_table_indexing=True, record_gvalue_matrix=False, preserve_first_generation=False)

Options to pass on too fwdpy11.evolvets().

asdict()

Return dict representation

classmethod fromdict(d)

Build an instance from a dictionary

preserve_first_generation

record_gvalue_matrix

simplification_interval

suppress_table_indexing

class fwdpy11.conditional_models.FocalDemeFixation(deme)

A terminiation condition checking for fixation in a specific deme.

deme

class fwdpy11.conditional_models.FrequencyRange(minimum, maximum)

Specify a range for the initial frequency of a mutation

Parameters:

• minimum (float) – Minimum frequency of a mutation. This value must be > 0.0 and < 1.0.

• maximum (float) – Maximum frequency of a mutation. This value must be > minimum.

maximum

minimum

class fwdpy11.conditional_models.GlobalFixation

A terminiation condition monitoring for global fixation of the mutation.

class fwdpy11.conditional_models.NewMutationParameters(*, deme=None, frequency, position, data)

Details of a new mutation to add to a population.

Class instances are created via keyword arguments that become attribute names:

Parameters:

• deme (Optional[int]) – The id of the deme in which to add the mutation

• frequency (Union[AlleleCount, AlleleCountRange, FrequencyRange]) – The frequency of the new mutation.

• position (PositionRange) – Where to put the new mutation

• data (fwdpy11.NewMutationData) – The specifics of the new mutation

data

deme

frequency

position

exception fwdpy11.conditional_models.OutOfAttempts

class fwdpy11.conditional_models.PositionRange(*, left, right)

Specify a half-open interval within which to place a mutation.

Parameters:

• left (float) – The left edge, inclusive, of the interval

• right (float) – The right edge, exclusive, of the interval

left

right

class fwdpy11.conditional_models.SimulationStatus(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Continue = 1

Restart = 0

Success = 2

fwdpy11.conditional_models.track_added_mutation(rng, pop, params, mutation_parameters, *, when=None, until=None, max_attempts=None, sampling_policy=None, stopping_condition=None, evolvets_options=None, return_when_stopping_condition_met=False)

Track the fate of a specific mutation added to the population.

Parameters:

• rng (fwdpy11.GSLrng) – A random number generator

• pop (fwdpy11.DiploidPopulation) – The input population

• params (fwdpy11.ModelParams) – Input simulation parameters

• mutation_parameters (NewMutationParameters) – Details of the new mutation

• when (int) – Time to add the new mutation

• until (int) – Time stop monitoring the new mutation

• max_attempts (int) – Maximum number of attempts to satisfy stopping_condition

• sampling_policy (AncientSamplePolicy) – Enumeration specifying the recording of ancient samples.

• stopping_condition (Optional[Callable[ [fwdpy11.DiploidPopulation, int, Tuple[float, float, int]], SimulationStatus,]) – An optional callable that specifies a TODO

• evolvets_options (EvolveOptions) – Options to fwdpy11.evolvets()

• return_when_stopping_condition_met – If True, return to calling environment once stopping_condition is satisfied. If False, simulate to the end of the model.

fwdpy11.conditional_models.selective_sweep(rng, pop, params, mutation_parameters, stopping_condition, **kwargs)

This function is a wrapper around fwdpy11.conditional_models.track_added_mutation().

This function requires a stopping_condition. If when is not given as a keyword argument, it is assumed to be 0. The keyword argument until is not allowed.