예제 #1
0
def No_mig(params, ns, pts):
    """
    params = (nuPre,TPre,s,nu1,nu2,T)
    ns = (n1,n2)

    Isolation-with-migration model with exponential pop growth and a size change
    prior to split.

    nuPre: Size after first size change
    TPre: Time before split of first size change.
    s: Fraction of nuPre that goes to pop1. (Pop 2 has size nuPre*(1-s).)
    nu1: Final size of pop 1.
    nu2: Final size of pop 2.
    T: Time in the past of split (in units of 2*Na generations)
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuPre, TPre, s, nu1, nu2, T = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, TPre, nu=nuPre)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    nu1_0 = nuPre * s
    nu2_0 = nuPre * (1 - s)
    nu1_func = lambda t: nu1_0 * (nu1 / nu1_0)**(t / T)
    nu2_func = lambda t: nu2_0 * (nu2 / nu2_0)**(t / T)
    phi = Integration.two_pops(phi, xx, T, nu1_func, nu2_func, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #2
0
def CMG(params, ns, pts):
    nu1, nu2, b1, b2, m, T = params
    """
    Model with migration during the divergence.
    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    b: Population growth coefficient
    m: Migration rate between populations (2*Na*m)
    T: The scaled time between the split (in units of 2*Na generations).
    """
    # Define the grid we'll use
    xx = Numerics.default_grid(pts)

    # phi for the equilibrium ancestral population
    phi = PhiManip.phi_1D(xx)
    # Now do the divergence event
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    # We start the population size change after the split and set the migration rates to m12 and m21
    bnu1_func = lambda t: nu1 * b1**(t / T)
    bnu2_func = lambda t: nu2 * b2**(t / T)
    phi = Integration.two_pops(phi, xx, T, bnu1_func, bnu2_func, m12=m, m21=m)
    ###
    ## Finally, calculate the spectrum.
    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #3
0
def ancmig_adj_2(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), with gene flow. Split 
    between pops 2 and 3, and all gene flow ceases.
    shorter isolation
    """
    #7 parameters
    nu1, nuA, nu2, nu3, mA, T1, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1=nu1, nu2=nuA, m12=mA, m21=mA)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=0,
                                 m21=0,
                                 m23=0,
                                 m32=0,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #4
0
def split_symmig_all(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), then split between 2 and 3.
    Migration is symmetrical between all population pairs (ie 1<->2, 2<->3, and 1<->3).
    """
    #10 parameters
    nu1, nuA, nu2, nu3, mA, m1, m2, m3, T1, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1=nu1, nu2=nuA, m12=mA, m21=mA)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=m1,
                                 m21=m1,
                                 m23=m2,
                                 m32=m2,
                                 m13=m3,
                                 m31=m3)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #5
0
def refugia_adj_3(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), gene flow does not occur, but then 
    secondary contact occurs. Split between pops 2 and 3 occurs with gene flow, and gene flow
    happens between 1 and 2 as well.
    shortest isolation
    """
    #10 parameters
    nu1, nuA, nu2, nu3, mA, m1, m2, T1a, T1b, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1a, nu1=nu1, nu2=nuA, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T1b, nu1=nu1, nu2=nuA, m12=mA, m21=mA)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=m1,
                                 m21=m1,
                                 m23=m2,
                                 m32=m2,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #6
0
def ancmig_adj_3(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), with gene flow, which then stops. Split 
    between pops 2 and 3, gene flow does not occur at all.
    longest isolation
    """
    #8 parameters
    nu1, nuA, nu2, nu3, mA, T1a, T1b, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1a, nu1=nu1, nu2=nuA, m12=mA, m21=mA)

    phi = Integration.two_pops(phi, xx, T1b, nu1=nu1, nu2=nuA, m12=0, m21=0)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=0,
                                 m21=0,
                                 m23=0,
                                 m32=0,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #7
0
def refugia_adj_2(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), gene flow does not occur. Split between pops
    2 and 3, with gene flow. After appearance of 2 and 3, gene flow also occurs between 1 
    and 2.
    shorter isolation
    """
    #8 parameters
    nu1, nuA, nu2, nu3, m1, m2, T1, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1=nu1, nu2=nuA, m12=0, m21=0)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=m1,
                                 m21=m1,
                                 m23=m2,
                                 m32=m2,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #8
0
def split_nomig(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), then split between 2 and 3.
    Migration does not occur between any population pair.
    """
    #6 parameters
    nu1, nuA, nu2, nu3, T1, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1=nu1, nu2=nuA, m12=0, m21=0)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=0,
                                 m21=0,
                                 m23=0,
                                 m32=0,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #9
0
def split_ancient_symmig_size(params, ns, pts):
    """
    Model with split and no gene flow, followed by period of size change and symmetrical gene flow.

    nu1b: Size of population 1 after split.
    nu2b: Size of population 2 after split.
    T1: Time in the past of split (in units of 2*Na generations)
    nu1r: Size of population 1 after time interval.
    nu2r: Size of population 2 after time interval.
    T2: The scale time between the ancient migration and present.
    m: Migration between pop 2 and pop 1.
    ns: Size of fs to generate.
    pts: Number of points to use in grid for evaluation.
    """
    nu1b, nu2b, nu1r, nu2r, T1, T2, m = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1b, nu2b, m12=m, m21=m)

    phi = Integration.two_pops(phi, xx, T2, nu1r, nu2r, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #10
0
def split_secondary_contact_sym_size(params, ns, pts):
    """
    Model with split, complete isolation, followed by secondary contact with asymmetrical gene flow

    nu1b: Size of population 1 after split.
    nu2b: Size of population 2 after split.
    T1: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    nu1r: Size of population 1 after time interval.
    nu2r: Size of population 2 after time interval.
    T2: The scale time between the secondary contact and present.
    m: Migration between pop 2 and pop 1.
    ns: Size of fs to generate.
    pts: Number of points to use in grid for evaluation.
    """
    nu1b, nu2b, nu1r, nu2r, T1, T2, m = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1b, nu2b, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1r, nu2r, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #11
0
def split_no_mig_size(params, ns, pts):
    """
    params = (nu1b,nu2b,nu1r,nu2r,T1,T2)
    ns = (n1,n2)

    Split into two populations of specifed size, with no migration, period of size change and no migration.

    nu1b: Size of population 1 after split.
    nu2b: Size of population 2 after split.
    T1: Time in the past of split (in units of 2*Na generations)
    nu1r: Size of population 1 after time interval.
    nu2r: Size of population 2 after time interval.
    T2: Time of population size change.
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu1b, nu2b, nu1r, nu2r, T1, T2 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1b, nu2b, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1r, nu2r, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #12
0
def split_secondary_contact_sym(params, ns, pts):
    """
    Model with split and no gene flow, followed by period of no size change and symmetrical gene flow

    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    m: Migration between pop 2 and pop 1.
    T: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    Tsc: The scale time between the secondary contact and present.
    ns: Size of fs to generate.
    pts: Number of points to use in grid for evaluation.
    """
    nu1, nu2, m, T, Tsc = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T, nu1, nu2, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, Tsc, nu1, nu2, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #13
0
def split_mig(params, ns, pts):
    """
    params = (nu1,nu2,T,m)
    ns = (n1,n2)

    Split into two populations of specifed size, with migration.

    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    T: Time in the past of split (in units of 2*Na generations) 
    m: Migration rate between populations (2*Na*m)
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu1,nu2,T,m = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T, nu1, nu2, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #14
0
def split_symmig_adjacent(params, ns, pts):
    """
    Model with split between pop 1 and (2,3), then split between 2 and 3. Assume 2 occurs
    in between populations 1 and 3, which do not come in to contact with one another.
    Migration is symmetrical between 'adjacent' population pairs (ie 1<->2, 2<->3, but not 1<->3).
    """
    #9 parameters
    nu1, nuA, nu2, nu3, mA, m1, m2, T1, T2 = params

    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1=nu1, nu2=nuA, m12=mA, m21=mA)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    phi = Integration.three_pops(phi,
                                 xx,
                                 T2,
                                 nu1=nu1,
                                 nu2=nu2,
                                 nu3=nu3,
                                 m12=m1,
                                 m21=m1,
                                 m23=m2,
                                 m32=m2,
                                 m13=0,
                                 m31=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx, xx))
    return fs
예제 #15
0
def priorsize_asym_mig(params, ns, pts):
    """
    Size change followed by split with asymmetric migration

    nua: First Size of population before split.
    T1: Duration of first time before split
    nu1b: Size of population 1 after split.
    nu2b: Size of population 2 after split.
    T2: Time in the past of split (units of 2*Na generations)
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
    """
    nua, T1,nu1b, nu2b, T2, m12, m21 = params
    xx = Numerics.default_grid(pts)
    
    phi = PhiManip.phi_1D(xx)

    phi = Integration.one_pop(phi, xx, T1, nua)

    phi = PhiManip.phi_1D_to_2D(xx, phi)
    
    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m12, m21=m21)
    
    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    
    return fs
예제 #16
0
def sec_contact_asym_mig_size_three_epoch(params, ns, pts):
    """
    Split with no gene flow, followed by size change with asymmetrical gene flow, then isolation.

    nu1a: Size of population 1 after split.
    nu2a: Size of population 2 after split.
    T1: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    nu1b: Size of population 1 after time interval.
    nu2b: Size of population 2 after time interval.
    T2: The scale time between the secondary contact and isolation.
    T3: The scaled time between the isolation and present.
    m12: Migration from pop 2 to pop 1 (2*Na*m12).
    m21: Migration from pop 1 to pop 2.
    """
    nu1a, nu2a, nu1b, nu2b, m12, m21, T1, T2, T3 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m12, m21=m21)

    phi = Integration.two_pops(phi, xx, T3, nu1b, nu2b, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #17
0
def vic_sec_contact_asym_mig(params, ns, pts):
    """
    Split with no gene flow, followed by period of asymmetrical gene flow. Populations are 
    fractions of ancient population, where population 2 is represented by nuA*(s), and 
    population 1 is represented by nuA*(1-s).
	nuA: Ancient population size
    s: Fraction of nuA that goes to pop2. (Pop 1 has size nuA*(1-s).)
    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    m12: Migration from pop 2 to pop 1 (2*Na*m12).
    m21: Migration from pop 1 to pop 2.
    T1: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    T2: The scaled time between the secondary contact and present.
    """
    nuA, nu1, nu2, m12, m21, T1, T2, s = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    nu1 = nuA * (1 - s)
    nu2 = nuA * s

    phi = Integration.two_pops(phi, xx, T1, nu1, nu2, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1, nu2, m12=m12, m21=m21)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #18
0
def isolation_asym_mig_base(nu1a, nu2a, T1,nu1b, nu2b, T2, m12, m21, ns, pts):
    """
    Split followed by two size changes with continuous asymmetric migration

    nu1a: Size of population 1 after split in first time interval.
    nu2a: Size of population 2 after split.
    T1:  First time interval after split (units of 2*Na generations)
    nu1b: Size of population 1 after split in second time interval.
    nu2b: Size of population 2 after split.
    T2:  Second time interval after split (units of 2*Na generations)
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
    """
    xx = Numerics.default_grid(pts)
    
    phi = PhiManip.phi_1D(xx)

    phi = PhiManip.phi_1D_to_2D(xx, phi)
    
    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m12, m21=m21)
    
    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    
    return fs    
예제 #19
0
def simple_iso(params, ns, pts):
    """
    params = (nuPre,TPre,nu1,nu2,T)
    ns = (n1,n2)

    Simple migration model, the population size is constant

    nuPre: Size after first size change
    TPre: Time before split of first size change.
    nu1: size of pop 1.
    nu2: size of pop 2.
    T1: Time from divergence to migration end (in units of 2*Na generations)
    T2: Time from migration end to present
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuPre,TPre,nu1,nu2,T = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, TPre, nu=nuPre)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T, nu1, nu2, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #20
0
def vic_two_epoch_admix(params, ns, pts):
    """
    Split with no gene flow, followed by no migration but a discrete admixture 
    event from pop 1 into pop 2 occurs. Populations are fractions of ancient population, where population 2 is 
    represented by nuA*(s), and population 1 is represented by nuA*(1-s).
	nuA: Ancient population size
    s: Fraction of nuA that goes to pop2. (Pop 1 has size nuA*(1-s).)
    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    T1: The scaled time between the split and admixture event (in units of 2*Na generations).
    T2: The scaled time between the admixture event and present.
    f: Fraction of updated population 2 to be derived from population 1. 
    """
    nuA, nu1, nu2, T1, T2, s, f = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    nu1 = nuA * (1 - s)
    nu2 = nuA * s

    phi = Integration.two_pops(phi, xx, T1, nu1, nu2, m12=0, m21=0)
    phi = PhiManip.phi_2D_admix_1_into_2(phi, f, xx, xx)

    phi = Integration.two_pops(phi, xx, T2, nu1, nu2, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
def IM(params, ns, pts):
    """
    ns = (n1,n2)
    params = (s,nu1,nu2,T,m12,m21)

    Isolation-with-migration model with exponential pop growth.

    s: Size of pop 1 after split. (Pop 2 has size 1-s.)
    nu1: Final size of pop 1.
    nu2: Final size of pop 2.
    T: Time in the past of split (in units of 2*Na generations) 
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    s, nu1, nu2, T, m12, m21 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    nu1_func = lambda t: s * (nu1 / s)**(t / T)
    nu2_func = lambda t: (1 - s) * (nu2 / (1 - s))**(t / T)
    phi = Integration.two_pops(phi,
                               xx,
                               T,
                               nu1_func,
                               nu2_func,
                               m12=m12,
                               m21=m21)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #22
0
def sec_contact_sym_mig_size(params, ns, pts):
    """
    Split with no gene flow, followed by size change with symmetrical gene flow.

    nu1a: Size of population 1 after split.
    nu2a: Size of population 2 after split.
    T1: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    nu1b: Size of population 1 after time interval.
    nu2b: Size of population 2 after time interval.
    T2: The scale time between the secondary contact and present.
    m: Migration between pop 2 and pop 1.
    """
    nu1a, nu2a, nu1b, nu2b, m, T1, T2 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #23
0
def sec_contact_sym_mig_three_epoch(params, ns, pts):
    """
    Split with no gene flow, followed by period of symmetrical gene flow, then isolation.

    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    m: Migration between pop 2 and pop 1.
    T1: The scaled time between the split and the secondary contact (in units of 2*Na generations).
    T2: The scaled time between the secondary contact and third epoch.
    T3: The scaled time between the isolation and present.
    """
    nu1, nu2, m, T1, T2, T3 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1, nu2, m12=0, m21=0)

    phi = Integration.two_pops(phi, xx, T2, nu1, nu2, m12=m, m21=m)

    phi = Integration.two_pops(phi, xx, T3, nu1, nu2, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #24
0
def asym_mig_size(params, ns, pts):
    """
    Split with different migration rates, then size change with different migration rates.

    nu1a: Size of population 1 after split.
    nu2a: Size of population 2 after split.
    T1: Time in the past of split (in units of 2*Na generations)
    nu1b: Size of population 1 after time interval.
    nu2b: Size of population 2 after time interval.
    T2: Time of population size change.
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
	"""
    nu1a, nu2a, nu1b, nu2b, m12, m21, T1, T2 = params
    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=m12, m21=m21)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m12, m21=m21)

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

    return fs
예제 #25
0
def anc_asym_mig_size(params, ns, pts):
    """
    Split with asymmetrical gene flow, followed by size change with no gene flow.

    nu1a: Size of population 1 after split.
    nu2a: Size of population 2 after split.
    T1: Time in the past of split (in units of 2*Na generations)
    nu1b: Size of population 1 after time interval.
    nu2b: Size of population 2 after time interval.
    T2: The scale time between the ancient migration and present.
    m12: Migration from pop 2 to pop 1 (2*Na*m12).
    m21: Migration from pop 1 to pop 2.
    """
    nu1a, nu2a, nu1b, nu2b, m12, m21, T1, T2 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=m12, m21=m21)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #26
0
def founder_asym(params, ns, pts):
    """
    Split into two populations, with two migration rates. Populations are fractions of ancient
    population, where population 2 is represented by nuA*(s), and population 1 is represented by nuA*(1-s).
    Population two undergoes an exponential growth event, while population one is constant. 
	
	nuA: Ancient population size
    s: Fraction of nuA that goes to pop2. (Pop 1 has size nuA*(1-s).)
    nu1: Final size of pop 1.
    nu2: Final size of pop 2.
    T: Time in the past of split (in units of 2*Na generations) 
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
    """
    nuA, nu1, nu2, m12, m21, T, s = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx, nu=nuA)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    nu1 = nuA * (1 - s)
    nu2_0 = nuA * s
    nu2_func = lambda t: nu2_0 * (nu2 / nu2_0)**(t / T)
    #note, the nu2_0 can be eliminated and the function can appear as:
    #nu2_func = lambda t: (nuA*(1-s)) * (nu2/(nuA*(1-s)))**(t/T)
    phi = Integration.two_pops(phi, xx, T, nu1, nu2_func, m12=m12, m21=m21)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #27
0
def sym_mig_size(params, ns, pts):
    """
    Split with symmetric migration, then size change with symmetric migration.

    nu1a: Size of population 1 after split.
    nu2a: Size of population 2 after split.
    T1: Time in the past of split (in units of 2*Na generations)
    nu1b: Size of population 1 after time interval.
    nu2b: Size of population 2 after time interval.
    T2: Time of population size change.
    m: Migration rate between populations (2*Na*m)
    """
    nu1a, nu2a, nu1b, nu2b, m, T1, T2 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T1, nu1a, nu2a, m12=m, m21=m)

    phi = Integration.two_pops(phi, xx, T2, nu1b, nu2b, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #28
0
def IM(params, ns, pts):
    """
        ns = (n1,n2)
        params = (s,nu1,nu2,T,m12,m21)
        
        Isolation-with-migration model with exponential pop growth.
        
        s: Size of pop 1 after split. (Pop 2 has size 1-s.)
        nu1: Final size of pop 1.
        nu2: Final size of pop 2.
        T: Time in the past of split (in units of 2*Na generations)
        m12: Migration from pop 2 to pop 1 (2*Na*m12)
        m21: Migration from pop 1 to pop 2
        n1,n2: Sample sizes of resulting Spectrum
        pts: Number of grid points to use in integration.
        """
    s,nu1,nu2,T,m12,m21 = params
    
    xx = Numerics.default_grid(pts)
    
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    
    nu1_func = lambda t: s * (nu1/s)**(t/T)
    nu2_func = lambda t: (1-s) * (nu2/(1-s))**(t/T)
    phi = Integration.two_pops(phi, xx, T, nu1_func, nu2_func,
                               m12=m12, m21=m21)
    
    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #29
0
def vic_no_mig_admix_late(params, ns, pts):
    """
    Split into two populations, no migration but a discrete admixture event from pop 1 into
    pop 2 occurs. Populations are fractions of ancient population, where population 2 is 
    represented by nuA*(s), and population 1 is represented by nuA*(1-s).
	nuA: Ancient population size
    s: Fraction of nuA that goes to pop2. (Pop 1 has size nuA*(1-s).)
    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    T: Time in the past of split (in units of 2*Na generations) 
    f: Fraction of updated population 2 to be derived from population 1. 
    """
    nuA, nu1, nu2, T, s, f = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    nu1 = nuA * (1 - s)
    nu2 = nuA * s

    phi = Integration.two_pops(phi, xx, T, nu1, nu2, m12=0, m21=0)
    phi = PhiManip.phi_2D_admix_1_into_2(phi, f, xx, xx)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #30
0
def founder_nomig_admix_two_epoch(params, ns, pts):
    """
    Split into two populations, with no migration. Populations are fractions of ancient
    population, where population 2 is represented by nuA*(s), and population 1 is represented by nuA*(1-s).
    Population two undergoes an exponential growth event, while population one is constant. 
	
	nuA: Ancient population size
    s: Fraction of nuA that goes to pop2. (Pop 1 has size nuA*(1-s).)
    nu1: Final size of pop 1.
    nu2: Final size of pop 2.
    T1: Time in the past of split (in units of 2*Na generations)
    T2: The scaled time between the admixture event and present.
    f: Fraction of updated population 2 to be derived from population 1.
    """
    nuA, nu1, nu2, T1, T2, s, f = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx, nu=nuA)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    nu1 = nuA * (1 - s)
    nu2_0 = nuA * s
    nu2_func = lambda t: nu2_0 * (nu2 / nu2_0)**(t / T1)
    #note, the nu2_0 can be eliminated and the function can appear as:
    #nu2_func = lambda t: (nuA*(1-s)) * (nu2/(nuA*(1-s)))**(t/T)
    phi = Integration.two_pops(phi, xx, T1, nu1, nu2_func, m12=0, m21=0)
    phi = PhiManip.phi_2D_admix_1_into_2(phi, f, xx, xx)

    phi = Integration.two_pops(phi, xx, T2, nu1, nu2, m12=0, m21=0)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
def split_mig(params, ns, pts):
    """
    params = (nu1,nu2,T,m)
    ns = (n1,n2)

    Split into two populations of specifed size, with migration.

    nu1: Size of population 1 after split.
    nu2: Size of population 2 after split.
    T: Time in the past of split (in units of 2*Na generations) 
    m: Migration rate between populations (2*Na*m)
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nu1, nu2, T, m = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T, nu1, nu2, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
def bottlegrowth_split_mig(params, ns, pts):
    """
    params = (nuB,nuF,m,T,Ts)
    ns = (n1,n2)

    Instantanous size change followed by exponential growth then split with
    migration.

    nuB: Ratio of population size after instantanous change to ancient
         population size
    nuF: Ratio of contempoary to ancient population size
    m: Migration rate between the two populations (2*Na*m).
    T: Time in the past at which instantaneous change happened and growth began
       (in units of 2*Na generations) 
    Ts: Time in the past at which the two populations split.
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB, nuF, m, T, Ts = 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 - Ts, nu_func)

    phi = PhiManip.phi_1D_to_2D(xx, phi)
    nu0 = nu_func(T - Ts)
    nu_func = lambda t: nu0 * numpy.exp(numpy.log(nuF / nu0) * t / Ts)
    phi = Integration.two_pops(phi, xx, Ts, nu_func, nu_func, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx, xx))
    return fs
예제 #33
0
def bottlegrowth_split_mig(params, ns, pts):
    """
    params = (nuB,nuF,m,T,Ts)
    ns = (n1,n2)

    Instantanous size change followed by exponential growth then split with
    migration.

    nuB: Ratio of population size after instantanous change to ancient
         population size
    nuF: Ratio of contempoary to ancient population size
    m: Migration rate between the two populations (2*Na*m).
    T: Time in the past at which instantaneous change happened and growth began
       (in units of 2*Na generations) 
    Ts: Time in the past at which the two populations split.
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuB,nuF,m,T,Ts = 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-Ts, nu_func)

    phi = PhiManip.phi_1D_to_2D(xx, phi)
    nu0 = nu_func(T-Ts)
    nu_func = lambda t: nu0*numpy.exp(numpy.log(nuF/nu0) * t/Ts)
    phi = Integration.two_pops(phi, xx, Ts, nu_func, nu_func, m12=m, m21=m)

    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #34
0
def snm2(notused, ns, pts):
    """
        ns = (n1,n2)
        
        Standard neutral model, populations never diverge.
        """
    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)
    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #35
0
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.
    """
    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 bottleneck_1d(params, n1, pts):
    nuC, T = params
    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, T, nuC)

    model_sfs = Spectrum.from_phi(phi, n1, (xx,))
    return model_sfs
예제 #37
0
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.
    """
    xx = Numerics.default_grid(pts)
    phi = PhiManip.phi_1D(xx)

    fs = Spectrum.from_phi(phi, ns, (xx,))
    return fs
예제 #38
0
def IM_pre(params, ns, pts):
    """
    params = (nuPre,TPre,s,nu1,nu2,T,m12,m21)
    ns = (n1,n2)

    Isolation-with-migration model with exponential pop growth and a size change
    prior to split.

    nuPre: Size after first size change
    TPre: Time before split of first size change.
    s: Fraction of nuPre that goes to pop1. (Pop 2 has size nuPre*(1-s).)
    nu1: Final size of pop 1.
    nu2: Final size of pop 2.
    T: Time in the past of split (in units of 2*Na generations) 
    m12: Migration from pop 2 to pop 1 (2*Na*m12)
    m21: Migration from pop 1 to pop 2
    n1,n2: Sample sizes of resulting Spectrum
    pts: Number of grid points to use in integration.
    """
    nuPre,TPre,s,nu1,nu2,T,m12,m21 = params

    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, TPre, nu=nuPre)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    nu1_0 = nuPre*s
    nu2_0 = nuPre*(1-s)
    nu1_func = lambda t: nu1_0 * (nu1/nu1_0)**(t/T)
    nu2_func = lambda t: nu2_0 * (nu2/nu2_0)**(t/T)
    phi = Integration.two_pops(phi, xx, T, nu1_func, nu2_func,
                               m12=m12, m21=m21)

    fs = Spectrum.from_phi(phi, ns, (xx,xx))
    return fs
예제 #39
0
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
예제 #40
0
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
예제 #41
0
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
"""
Dadi demographic models for WY and CO populations of E. gillettii.
"""
import numpy
from dadi import Numerics, PhiManip, Integration
from dadi.Spectrum_mod import Spectrum

#one ancestral population splits at time T ago with no migration
def bottleneck_split(params, (n1,n2), pts):
    nuW, nuC, T = params
    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = PhiManip.phi_1D_to_2D(xx, phi)

    phi = Integration.two_pops(phi, xx, T, nuW, nuC)

    model_sfs = Spectrum.from_phi(phi, (n1,n2), (xx,xx))
    return model_sfs


#one dimensional demographic inference of bottlneck size and timing
def bottleneck_1d(params, n1, pts):
    nuC, T = params
    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, T, nuC)

    model_sfs = Spectrum.from_phi(phi, n1, (xx,))
    return model_sfs
예제 #43
0
import numpy
from dadi import Numerics, PhiManip, Integration, Spectrum

def OutOfAfrica((nuAf, nuB, nuEu0, nuEu, nuAs0, nuAs, 
                 mAfB, mAfEu, mAfAs, mEuAs, TAf, TB, TEuAs), (n1,n2,n3), pts):
    xx = Numerics.default_grid(pts)

    phi = PhiManip.phi_1D(xx)
    phi = Integration.one_pop(phi, xx, TAf, nu=nuAf)

    phi = PhiManip.phi_1D_to_2D(xx, phi)
    phi = Integration.two_pops(phi, xx, TB, nu1=nuAf, nu2=nuB, 
                               m12=mAfB, m21=mAfB)

    phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)

    nuEu_func = lambda t: nuEu0*(nuEu/nuEu0)**(t/TEuAs)
    nuAs_func = lambda t: nuAs0*(nuAs/nuAs0)**(t/TEuAs)
    phi = Integration.three_pops(phi, xx, TEuAs, nu1=nuAf, 
                                 nu2=nuEu_func, nu3=nuAs_func, 
                                 m12=mAfEu, m13=mAfAs, m21=mAfEu, m23=mEuAs,
                                 m31=mAfAs, m32=mEuAs)

    fs = Spectrum.from_phi(phi, (n1,n2,n3), (xx,xx,xx))
    return fs

def OutOfAfrica_mscore((nuAf, nuB, nuEu0, nuEu, nuAs0, nuAs,
                        mAfB, mAfEu, mAfAs, mEuAs, TAf, TB, TEuAs)):

    alphaEu = numpy.log(nuEu/nuEu0)/TEuAs
    alphaAs = numpy.log(nuAs/nuAs0)/TEuAs