Module dadi.Demographics1D

Single population demographic models.

Expand source code 
"""
Single population demographic models.
"""
import numpy

from dadi import Numerics, PhiManip, Integration
from dadi.Spectrum_mod import Spectrum

def snm_1d(notused, ns, pts):
    """
    Standard neutral model.

    ns = (n1,)

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
snm_1d.__param_names__ = []
snm = snm_1d

def two_epoch(params, ns, pts):
    """
    Instantaneous size change some time ago.

    params = (nu,T)
    ns = (n1,)

    nu: Ratio of contemporary to ancient population size
    T: Time in the past at which size change happened (in units of 2*Na 
       generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    
    phi = Integration.one_pop(phi, xx, T, nu)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
two_epoch.__param_names__ = ['nu', 'T']

def growth(params, ns, pts):
    """
    Exponential growth beginning some time ago.

    params = (nu,T)
    ns = (n1,)

    nu: Ratio of contemporary to ancient population size
    T: Time in the past at which growth began (in units of 2*Na 
       generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    nu_func = lambda t: numpy.exp(numpy.log(nu) * t/T)
    phi = Integration.one_pop(phi, xx, T, nu_func)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
growth.__param_names__ = ['nu', 'T']

def bottlegrowth_1d(params, ns, pts):
    """
    Instantanous size change followed by exponential growth.

    params = (nuB,nuF,T)
    ns = (n1,)

    nuB: Ratio of population size after instantanous change to ancient
         population size
    nuF: Ratio of contemporary to ancient population size
    T: Time in the past at which instantaneous change happened and growth began
       (in units of 2*Na generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    nu_func = lambda t: nuB*numpy.exp(numpy.log(nuF/nuB) * t/T)
    phi = Integration.one_pop(phi, xx, T, nu_func)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
bottlegrowth_1d.__param_names__ = ['nuB', 'nuF', 'T']
bottlegrowth = bottlegrowth_1d

def three_epoch(params, ns, pts):
    """
    params = (nuB,nuF,TB,TF)
    ns = (n1,)

    nuB: Ratio of bottleneck population size to ancient pop size
    nuF: Ratio of contemporary to ancient pop size
    TB: Length of bottleneck (in units of 2*Na generations) 
    TF: Time since bottleneck recovery (in units of 2*Na generations) 

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,TB,TF = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    phi = Integration.one_pop(phi, xx, TB, nuB)
    phi = Integration.one_pop(phi, xx, TF, nuF)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
three_epoch.__param_names__ = ['nuB', 'nuF', 'TB', 'TF']

def three_epoch_inbreeding(params, ns, pts):
    """
    params = (nuB,nuF,TB,TF,F)
    ns = (n1,)

    nuB: Ratio of bottleneck population size to ancient pop size
    nuF: Ratio of contemporary to ancient pop size
    TB: Length of bottleneck (in units of 2*Na generations) 
    TF: Time since bottleneck recovery (in units of 2*Na generations) 
    F: Inbreeding coefficent

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,TB,TF,F = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    phi = Integration.one_pop(phi, xx, TB, nuB)
    phi = Integration.one_pop(phi, xx, TF, nuF)

    fs = Spectrum.from_phi_inbreeding(phi, ns, (xx,), (F,), (2,))
    return fs
three_epoch_inbreeding.__param_names__ = ['nuB', 'nuF', 'TB', 'TF', 'F']

Functions

def bottlegrowth(params, ns, pts)

Instantanous size change followed by exponential growth.

params = (nuB,nuF,T) ns = (n1,)

nuB: Ratio of population size after instantanous change to ancient population size nuF: Ratio of contemporary to ancient population size T: Time in the past at which instantaneous change happened and growth began (in units of 2*Na generations) n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def bottlegrowth_1d(params, ns, pts):
    """
    Instantanous size change followed by exponential growth.

    params = (nuB,nuF,T)
    ns = (n1,)

    nuB: Ratio of population size after instantanous change to ancient
         population size
    nuF: Ratio of contemporary to ancient population size
    T: Time in the past at which instantaneous change happened and growth began
       (in units of 2*Na generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    nu_func = lambda t: nuB*numpy.exp(numpy.log(nuF/nuB) * t/T)
    phi = Integration.one_pop(phi, xx, T, nu_func)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def bottlegrowth_1d(params, ns, pts)

Instantanous size change followed by exponential growth.

params = (nuB,nuF,T) ns = (n1,)

nuB: Ratio of population size after instantanous change to ancient population size nuF: Ratio of contemporary to ancient population size T: Time in the past at which instantaneous change happened and growth began (in units of 2*Na generations) n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def bottlegrowth_1d(params, ns, pts):
    """
    Instantanous size change followed by exponential growth.

    params = (nuB,nuF,T)
    ns = (n1,)

    nuB: Ratio of population size after instantanous change to ancient
         population size
    nuF: Ratio of contemporary to ancient population size
    T: Time in the past at which instantaneous change happened and growth began
       (in units of 2*Na generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    nu_func = lambda t: nuB*numpy.exp(numpy.log(nuF/nuB) * t/T)
    phi = Integration.one_pop(phi, xx, T, nu_func)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def growth(params, ns, pts)

Exponential growth beginning some time ago.

params = (nu,T) ns = (n1,)

nu: Ratio of contemporary to ancient population size T: Time in the past at which growth began (in units of 2*Na generations) n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def growth(params, ns, pts):
    """
    Exponential growth beginning some time ago.

    params = (nu,T)
    ns = (n1,)

    nu: Ratio of contemporary to ancient population size
    T: Time in the past at which growth began (in units of 2*Na 
       generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    nu_func = lambda t: numpy.exp(numpy.log(nu) * t/T)
    phi = Integration.one_pop(phi, xx, T, nu_func)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def snm(notused, ns, pts)

Standard neutral model.

ns = (n1,)

n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def snm_1d(notused, ns, pts):
    """
    Standard neutral model.

    ns = (n1,)

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def snm_1d(notused, ns, pts)

Standard neutral model.

ns = (n1,)

n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def snm_1d(notused, ns, pts):
    """
    Standard neutral model.

    ns = (n1,)

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def three_epoch(params, ns, pts)

params = (nuB,nuF,TB,TF) ns = (n1,)

nuB: Ratio of bottleneck population size to ancient pop size nuF: Ratio of contemporary to ancient pop size TB: Length of bottleneck (in units of 2Na generations) TF: Time since bottleneck recovery (in units of 2Na generations)

n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def three_epoch(params, ns, pts):
    """
    params = (nuB,nuF,TB,TF)
    ns = (n1,)

    nuB: Ratio of bottleneck population size to ancient pop size
    nuF: Ratio of contemporary to ancient pop size
    TB: Length of bottleneck (in units of 2*Na generations) 
    TF: Time since bottleneck recovery (in units of 2*Na generations) 

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,TB,TF = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    phi = Integration.one_pop(phi, xx, TB, nuB)
    phi = Integration.one_pop(phi, xx, TF, nuF)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
def three_epoch_inbreeding(params, ns, pts)

params = (nuB,nuF,TB,TF,F) ns = (n1,)

nuB: Ratio of bottleneck population size to ancient pop size nuF: Ratio of contemporary to ancient pop size TB: Length of bottleneck (in units of 2Na generations) TF: Time since bottleneck recovery (in units of 2Na generations) F: Inbreeding coefficent

n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def three_epoch_inbreeding(params, ns, pts):
    """
    params = (nuB,nuF,TB,TF,F)
    ns = (n1,)

    nuB: Ratio of bottleneck population size to ancient pop size
    nuF: Ratio of contemporary to ancient pop size
    TB: Length of bottleneck (in units of 2*Na generations) 
    TF: Time since bottleneck recovery (in units of 2*Na generations) 
    F: Inbreeding coefficent

    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,TB,TF,F = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    phi = Integration.one_pop(phi, xx, TB, nuB)
    phi = Integration.one_pop(phi, xx, TF, nuF)

    fs = Spectrum.from_phi_inbreeding(phi, ns, (xx,), (F,), (2,))
    return fs
def two_epoch(params, ns, pts)

Instantaneous size change some time ago.

params = (nu,T) ns = (n1,)

nu: Ratio of contemporary to ancient population size T: Time in the past at which size change happened (in units of 2*Na generations) n1: Number of samples in resulting Spectrum pts: Number of grid points to use in integration.

Expand source code 
def two_epoch(params, ns, pts):
    """
    Instantaneous size change some time ago.

    params = (nu,T)
    ns = (n1,)

    nu: Ratio of contemporary to ancient population size
    T: Time in the past at which size change happened (in units of 2*Na 
       generations) 
    n1: Number of samples in resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu,T = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    
    phi = Integration.one_pop(phi, xx, T, nu)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs