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Formats:
parquet
Size:
100K - 1M
Tags:
population-genetics
demographic-inference
effective-population-size
coalescent
msprime
simulation
License:
File size: 7,618 Bytes
ee5b44c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 | from __future__ import annotations
from typing import Optional
import numpy as np
from .config import (
DEMOGRAPHY_TYPE_IDS,
GENERATOR_RECIPE_IDS,
Config,
)
from .demography import summarize_demography
from .utils import bin_average_log10_ne, time_grid
class StdpopsimSimulationError(RuntimeError):
"""Raised when a requested stdpopsim anchor cannot be generated."""
def _extract_single_population_trajectory(dem) -> tuple[list[float], list[float], list[float]]:
"""Extract first-population size and growth-rate epochs from msprime.
This remains a proxy for structured models, but it exactly preserves native
exponential growth for genuinely single-population stdpopsim models.
"""
first_pop = dem.populations[0]
pop_name = first_pop.name
pop_id = getattr(first_pop, "id", 0)
current_size = float(first_pop.initial_size)
current_rate = float(first_pop.growth_rate)
previous_time = 0.0
breaks: list[float] = []
values = [current_size]
growth_rates = [current_rate]
events = sorted(getattr(dem, "events", []), key=lambda event: getattr(event, "time", 0))
for event in events:
if event.__class__.__name__ != "PopulationParametersChange":
continue
population = getattr(event, "population", None)
population_id = getattr(event, "population_id", None)
if population is not None:
applies = population in {-1, 0, pop_id, pop_name}
elif population_id is not None:
applies = population_id in {-1, 0, pop_id}
else:
applies = True
if not applies:
continue
event_time = float(event.time)
current_size *= float(np.exp(-current_rate * (event_time - previous_time)))
if getattr(event, "initial_size", None) is not None:
current_size = float(event.initial_size)
if getattr(event, "growth_rate", None) is not None:
current_rate = float(event.growth_rate)
if event_time <= 0:
values[0] = current_size
growth_rates[0] = current_rate
elif breaks and np.isclose(event_time, breaks[-1], rtol=0.0, atol=1e-12):
values[-1] = current_size
growth_rates[-1] = current_rate
else:
breaks.append(event_time)
values.append(current_size)
growth_rates.append(current_rate)
previous_time = event_time
return breaks, values, growth_rates
def validate_stdpopsim_setup(cfg: Config) -> None:
"""Fail before generation if an explicitly enabled anchor setup is unusable."""
if not cfg.enable_stdpopsim or cfg.p_stdpopsim_anchor <= 0.0:
return
try:
import stdpopsim # type: ignore
species = stdpopsim.get_species(cfg.stdpopsim_species)
model_ids = [model.strip() for model in cfg.stdpopsim_models.split(",") if model.strip()]
if model_ids:
for model_id in model_ids:
species.get_demographic_model(model_id)
elif not getattr(species, "demographic_models", None):
raise ValueError(f"species {cfg.stdpopsim_species!r} has no demographic models")
stdpopsim.get_engine("msprime")
except Exception as exc:
raise StdpopsimSimulationError(
"stdpopsim anchors are enabled but the dependency, species, models, "
f"or engine are unavailable: {exc}"
) from exc
def try_stdpopsim_sample(
rng: np.random.Generator,
cfg: Config,
) -> Optional[tuple[object, np.ndarray, dict, object]]:
if not cfg.enable_stdpopsim:
return None
try:
import stdpopsim # type: ignore
species = stdpopsim.get_species(cfg.stdpopsim_species)
model_ids = [m.strip() for m in cfg.stdpopsim_models.split(",") if m.strip()]
if not model_ids:
model_ids = [m.id for m in species.demographic_models[: min(5, len(species.demographic_models))]]
model_id = str(rng.choice(model_ids))
model = species.get_demographic_model(model_id)
contig_length = cfg.stdpopsim_contig_length if cfg.stdpopsim_contig_length > 0 else cfg.seq_len
contig = species.get_contig(
length=contig_length,
mutation_rate=cfg.baseline_mu,
recombination_rate=cfg.baseline_rec,
)
pop_id = model.populations[0].id if getattr(model, "populations", None) else "pop_0"
n_dip = max(1, cfg.n_haplotypes // 2)
try:
samples = model.get_samples(n_dip, *([0] * max(0, len(model.populations) - 1)))
except Exception:
samples = {pop_id: n_dip}
engine = stdpopsim.get_engine("msprime")
ts = engine.simulate(model, contig, samples, seed=int(rng.integers(1, 2**31 - 2)))
try:
ts = ts.trim()
except Exception:
pass
edges, _ = time_grid(cfg)
breaks: list[float] = []
values: list[float] = []
growth_rates: list[float] = []
dem = getattr(model, "model", None)
if dem is None:
raise ValueError(
f"stdpopsim model {model_id!r} exposes no msprime demography"
)
breaks, values, growth_rates = _extract_single_population_trajectory(dem)
if not values:
raise ValueError(
f"stdpopsim model {model_id!r} has no extractable population trajectory"
)
if not growth_rates:
raise ValueError(
f"stdpopsim model {model_id!r} has no extractable growth-rate trajectory"
)
y = bin_average_log10_ne(edges, breaks, values, growth_rates)
trajectory_meta = {
"source_type": "stdpopsim_anchor",
"target_quality": "heuristic_single_population",
"native_continuous_growth": any(
float(rate) != 0.0 for rate in growth_rates
),
}
meta = {
**trajectory_meta,
**summarize_demography(
edges,
breaks,
values,
growth_rates,
trajectory_meta,
generator_recipe="stdpopsim",
demography_type="stdpopsim",
),
"scenario": "stdpopsim",
"generator_recipe": "stdpopsim",
"generator_recipe_id": GENERATOR_RECIPE_IDS["stdpopsim"],
"demography_type": "stdpopsim",
"demography_type_id": DEMOGRAPHY_TYPE_IDS["stdpopsim"],
"demography_mixture_version": cfg.demography_mixture_version,
"stdpopsim_species": cfg.stdpopsim_species,
"stdpopsim_model_id": model_id,
"stdpopsim_population": pop_id,
"stdpopsim_contig_length": int(contig_length),
"target_scale": "log10_Ne",
"target_aggregation": "log_time_bin_average",
"target_time_bins": int(cfg.time_bins),
"demography_resolution_log10": float(cfg.demography_resolution_log10),
"demography_breaks": [float(x) for x in breaks],
"demography_values": [float(x) for x in values],
"demography_growth_rates": [float(x) for x in growth_rates],
"demography_function": (
"piecewise_exponential_linear_time"
if any(float(rate) != 0.0 for rate in growth_rates)
else "piecewise_constant"
),
}
return ts, y, meta, contig
except Exception as exc:
raise StdpopsimSimulationError(f"failed to generate a stdpopsim anchor: {exc}") from exc
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