def IM2(params, ns, pts):
"""
ns = (n1,n2)
params = (nu01,nu02,nu1,nu2,T,m12,m21)
Isolation-with-migration model with exponential pop growth.
Populations split into sizes nu01 and nu02.
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.
"""
nu01, nu02, 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: nu01 * (nu1 / nu01)**(t / T)
nu2_func = lambda t: nu02 * (nu2 / nu02)**(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
def bottleneck(params, ns, pts):
nuB,nuF,TB,TF = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, TB, nuB) # bottleneck
phi = Integration.one_pop(phi, xx, TF, nuF) # recovery
fs = Spectrum.from_phi(phi, ns, (xx,))
return fs
def s2mM(params, ns, pts):
nu1, nu2, T, M12, M21 = 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=M12, m21=M21)
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def twoEpochFixedT(params, ns, pts):
nu = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(
phi, xx, 0.001, nu) # contraction for set duration of ~10 generations
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def fourEpoch(params, ns, pts):
nu2, t2 = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.25, 2)
phi = Integration.one_pop(phi, xx, t2, nu2)
phi = Integration.one_pop(phi, xx, 0.036, 8)
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def fourEpoch(params, ns, pts):
nuREC, nuCUR, tREC, tCUR = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.015, 0.23)
phi = Integration.one_pop(phi, xx, tREC, nuREC)
phi = Integration.one_pop(phi, xx, tCUR, nuCUR)
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def split_3epoch_nomig(params, ns, pts):
nu1,t1,nuIR,nuMN = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, t1, nu1)
phi = PhiManip.phi_1D_to_2D(xx, phi) # split into two pops
phi = Integration.two_pops(phi, xx, 0.0008, nuIR, nuMN, m12=0, m21=0) # two pops at diff sizes with symmetric migration
fs = Spectrum.from_phi(phi, ns, (xx,xx))
return fs
def fourEpoch(params, ns, pts):
nuBOT, nuREC, nuCUR = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.013, nuBOT) # bottleneck 1
phi = Integration.one_pop(phi, xx, 0.024, nuREC) # recovery 1
phi = Integration.one_pop(phi, xx, 0.0013, nuCUR) # contraction
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def fourEpoch(params, ns, pts):
t3, nu3 = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.00675, 0.05)
phi = Integration.one_pop(phi, xx, 0.045, 26)
phi = Integration.one_pop(phi, xx, t3, nu3)
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def bottleneck_fixedDur(params, ns, pts):
TB, TF = params # removed TB because that is fixed at fixed DUR
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(
phi, xx, TB, 0.01) # replace TB with fixed duration fors bottleneck
phi = Integration.one_pop(phi, xx, TF, 0.1) # recovery
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def fiveEpoch(params, ns, pts):
nu3,t4,nu4 = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx,theta0 = theta1) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.26, 1.87, theta0 = theta1)
phi = Integration.one_pop(phi, xx, 0.0055, 0.04, theta0 = theta1)
phi = Integration.one_pop(phi, xx, 0.037,nu3, theta0 = theta1)
phi = Integration.one_pop(phi, xx, t4, nu4, theta0 = theta1)
fs = Spectrum.from_phi(phi, ns, (xx,))
return fs
def fourEpoch(params, ns, pts):
nuBOT, nuREC, nuCUR = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.00002,
nuBOT) # NA colonization bottleneck
phi = Integration.one_pop(phi, xx, 0.03, nuREC) # recovery
phi = Integration.one_pop(phi, xx, 0.0006, nuCUR) # IR founding bottleneck
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def double_bottleneck(params, ns, pts):
nuB1, nuF1, nuB2, nuF2, TB1, TF1, TB2, TF2 = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.005, nuB1) # bottleneck 1
phi = Integration.one_pop(phi, xx, TF1, nuF1) # recovery 1
phi = Integration.one_pop(phi, xx, 0.005, nuB2) # bottleneck 2
phi = Integration.one_pop(phi, xx, TF2, nuF2) # recovery 2
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def sandbox(params, ns, pts):
nuBOT, nuREC = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = Integration.one_pop(phi, xx, 0.0005, nuBOT) # contraction 1
phi = Integration.one_pop(phi, xx, 0.02, nuREC) # recovery
phi = Integration.one_pop(
phi, xx, 0.0005, 0.005) # contraction 2 -fix at 20 inds for 4 gen
# no recovery in between
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
def split_Wmig(params, ns, pts):
nu1, nu2, TDiv, m = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = PhiManip.phi_1D_to_2D(xx, phi) # split into two pops
phi = Integration.two_pops(
phi, xx, TDiv, nu1, nu2, m12=m,
m21=m) # two pops at diff sizes with symmetric migration
# allow for another size change; fix time at 35 gen
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def pop_split(params, ns, pts):
N1, N2, 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, N1, N2, m12=0, m21=0)
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def bottleneck(params, ns, pts):
nu1, nuB, nuF, Tb, Tf = 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, Tb, nu1, nuB, m12=0, m21=0)
phi = Integration.two_pops(phi, xx, Tf, nu1, nuF, m12=0, m21=0)
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def split_Wmig_wBot(params, ns, pts):
nu1, nu2, TDiv, m = params
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = PhiManip.phi_1D_to_2D(xx, phi) # split into two pops
phi = Integration.two_pops(
phi, xx, TDiv, nu1, nu2, m12=m,
m21=m) # two pops at diff sizes with symmetric migration
# allow for another size change; fix time at 35 gen
phi = Integration.two_pops(
phi, xx, 0.004, 0.05, 0.05, m12=0, m21=0
) # fixing time at 35/(2*4000) to represent 35 gen ago and am fixing migraiton to be 0 during the bottleneck
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def pop_splitExp(params, ns, pts):
s, nu1, nu2, T = 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=0, m21=0)
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
def IM(params, ns, pts):
"""
Split into two populations, with different migration rates.
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)
m12: Migration from pop 2 to pop 1 (2*Na*m12)
m21: Migration from pop 1 to pop 2
"""
nu1, nu2, m12, m21, 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, nu1, nu2, m12=m12, m21=m21)
fs = Spectrum.from_phi(phi, ns, (xx,xx))
return fs
def sso_model_trim_27_plusContraction_forOptimization(params,ns,pts): nu,T=params xx = Numerics.default_grid(pts) # intialize phi with ancestral pop: (nu0 = 1) phi = PhiManip.phi_1D(xx,nu=1) # stays at nu0=1 for T0 duration of time: # followed by a number of time steps, with associated pop changes: phi = Integration.one_pop(phi, xx, 0.0881712197999992, 1) phi = Integration.one_pop(phi, xx, 0.0820773125999968, 0.836551538729166) phi = Integration.one_pop(phi, xx, 0.0767768829000064, 0.836551538729166) phi = Integration.one_pop(phi, xx, 0.072122872869994, 0.761765214135537) phi = Integration.one_pop(phi, xx, 0.0679989058100032, 0.761765214135537) phi = Integration.one_pop(phi, xx, 0.0643224600599991, 0.738213027247672) phi = Integration.one_pop(phi, xx, 0.0610215936600004, 0.738213027247672) phi = Integration.one_pop(phi, xx, 0.0580444660799995, 0.750983120146509) phi = Integration.one_pop(phi, xx, 0.05534346867, 0.750983120146509) phi = Integration.one_pop(phi, xx, 0.0528826304500005, 0.795226999398677) phi = Integration.one_pop(phi, xx, 0.0506312702899994, 0.795226999398677) phi = Integration.one_pop(phi, xx, 0.0485650548800005, 0.869604885707006) phi = Integration.one_pop(phi, xx, 0.04665859294, 0.869604885707006) phi = Integration.one_pop(phi, xx, 0.0448991888299998, 0.968579772770968) phi = Integration.one_pop(phi, xx, 0.0432646251800001, 0.968579772770968) phi = Integration.one_pop(phi, xx, 0.0417474961999999, 1.07023813979649) phi = Integration.one_pop(phi, xx, 0.0403308743700001, 1.07023813979649) phi = Integration.one_pop(phi, xx, 0.03900946984, 1.12274330685933) phi = Integration.one_pop(phi, xx, 0.0377705869699996, 1.12514450221579) phi = Integration.one_pop(phi, xx, 0.0366078779399999, 1.09213414017289) phi = Integration.one_pop(phi, xx, 0.0355149949300004, 1.01928801965413) phi = Integration.one_pop(phi, xx, 0.0344855901200002, 0.91011303614748) phi = Integration.one_pop(phi, xx, 0.0335133156900004, 0.774150824662306) phi = Integration.one_pop(phi, xx, 0.0325958441059994, 0.609784494435127) phi = Integration.one_pop(phi, xx, 0.0317262985630002, 0.386870175412936) phi = Integration.one_pop(phi, xx, 0.030902139933, 0.141422067280315) phi = Integration.one_pop(phi, xx, 0.030119771118, 0.36675344664418) ### add contraction: phi = Integration.one_pop(phi, xx,T, nu) # get expected SFS: fs = Spectrum.from_phi(phi,ns,(xx,)) return fs
def SC(params, ns, pts):
"""
Split with no gene flow, followed by period of asymmetrical gene flow.
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.
"""
nu1, nu2, 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, 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
phi = Integration.one_pop(phi, xx, T25, nu25)
phi = Integration.one_pop(phi, xx, T26, nu26)
phi = Integration.one_pop(phi, xx, T27, nu27)
phi = Integration.one_pop(phi, xx, T28, nu28)
phi = Integration.one_pop(phi, xx, T29, nu29)
phi = Integration.one_pop(phi, xx, T30, nu30)
phi = Integration.one_pop(phi, xx, T31, nu31)
phi = Integration.one_pop(phi, xx, T32, nu32)
phi = Integration.one_pop(phi, xx, T33, nu33)
phi = Integration.one_pop(phi, xx, T34, nu34)
phi = Integration.one_pop(phi, xx, T35, nu35)
phi = Integration.one_pop(phi, xx, T36, nu36)
phi = Integration.one_pop(phi, xx, T37, nu37)
phi = Integration.one_pop(phi, xx, T38, nu38)
# get expected SFS:
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
# wrap your function in Numerics.make_extrap_log_func to make extrapolation version of your function
extrap_nso_model_trim_39_function = Numerics.make_extrap_log_func(
nso_model_trim_39)
# Version of model with nu and T values plugged in plus one more epoch for dadi to optimize
def nso_model_trim_39_plusContraction_forOptimization(
(contractionGen_RescBy2Nanc, contractionSize_RescByNanc), ns, pts):
xx = Numerics.default_grid(pts)
# intialize phi with ancestral pop: (nu0 = 1)
phi = PhiManip.phi_1D(xx, nu=1)
# stays at nu0=1 for T0 duration of time:
def psmc_100steps(params, ns, pts_l):
nu99, nu98, nu97, nu96, nu95, nu94, nu93, nu92, nu91, nu90, nu89, nu88, nu87, nu86, nu85, nu84, nu83, nu82, nu81, nu80, nu79, nu78, nu77, nu76, nu75, nu74, nu73, nu72, nu71, nu70, nu69, nu68, nu67, nu66, nu65, nu64, nu63, nu62, nu61, nu60, nu59, nu58, nu57, nu56, nu55, nu54, nu53, nu52, nu51, nu50, nu49, nu48, nu47, nu46, nu45, nu44, nu43, nu42, nu41, nu40, nu39, nu38, nu37, nu36, nu35, nu34, nu33, nu32, nu31, nu30, nu29, nu28, nu27, nu26, nu25, nu24, nu23, nu22, nu21, nu20, nu19, nu18, nu17, nu16, nu15, nu14, nu13, nu12, nu11, nu10, nu9, nu8, nu7, nu6, nu5, nu4, nu3, nu2, nu1, nuA, T99, T98, T97, T96, T95, T94, T93, T92, T91, T90, T89, T88, T87, T86, T85, T84, T83, T82, T81, T80, T79, T78, T77, T76, T75, T74, T73, T72, T71, T70, T69, T68, T67, T66, T65, T64, T63, T62, T61, T60, T59, T58, T57, T56, T55, T54, T53, T52, T51, T50, T49, T48, T47, T46, T45, T44, T43, T42, T41, T40, T39, T38, T37, T36, T35, T34, T33, T32, T31, T30, T29, T28, T27, T26, T25, T24, T23, T22, T21, T20, T19, T18, T17, T16, T15, T14, T13, T12, T11, T10, T9, T8, T7, T6, T5, T4, T3, T2, T1, T0 = params
xx = Numerics.default_grid(pts_l)
# initial phi with ancestral pop: (nuA = 1)
phi = PhiManip.phi_1D(xx, nu=nuA)
# stays at nuA for T0 duration of time:
phi = Integration.one_pop(phi, xx, T0, nuA)
# followed by a number of time steps, with associated pop changes:
phi = Integration.one_pop(phi, xx, T1, nu1)
phi = Integration.one_pop(phi, xx, T2, nu2)
phi = Integration.one_pop(phi, xx, T3, nu3)
phi = Integration.one_pop(phi, xx, T4, nu4)
phi = Integration.one_pop(phi, xx, T5, nu5)
phi = Integration.one_pop(phi, xx, T6, nu6)
phi = Integration.one_pop(phi, xx, T7, nu7)
phi = Integration.one_pop(phi, xx, T8, nu8)
phi = Integration.one_pop(phi, xx, T9, nu9)
phi = Integration.one_pop(phi, xx, T10, nu10)
phi = Integration.one_pop(phi, xx, T11, nu11)
phi = Integration.one_pop(phi, xx, T12, nu12)
phi = Integration.one_pop(phi, xx, T13, nu13)
phi = Integration.one_pop(phi, xx, T14, nu14)
phi = Integration.one_pop(phi, xx, T15, nu15)
phi = Integration.one_pop(phi, xx, T16, nu16)
phi = Integration.one_pop(phi, xx, T17, nu17)
phi = Integration.one_pop(phi, xx, T18, nu18)
phi = Integration.one_pop(phi, xx, T19, nu19)
phi = Integration.one_pop(phi, xx, T20, nu20)
phi = Integration.one_pop(phi, xx, T21, nu21)
phi = Integration.one_pop(phi, xx, T22, nu22)
phi = Integration.one_pop(phi, xx, T23, nu23)
phi = Integration.one_pop(phi, xx, T24, nu24)
phi = Integration.one_pop(phi, xx, T25, nu25)
phi = Integration.one_pop(phi, xx, T26, nu26)
phi = Integration.one_pop(phi, xx, T27, nu27)
phi = Integration.one_pop(phi, xx, T28, nu28)
phi = Integration.one_pop(phi, xx, T29, nu29)
phi = Integration.one_pop(phi, xx, T30, nu30)
phi = Integration.one_pop(phi, xx, T31, nu31)
phi = Integration.one_pop(phi, xx, T32, nu32)
phi = Integration.one_pop(phi, xx, T33, nu33)
phi = Integration.one_pop(phi, xx, T34, nu34)
phi = Integration.one_pop(phi, xx, T35, nu35)
phi = Integration.one_pop(phi, xx, T36, nu36)
phi = Integration.one_pop(phi, xx, T37, nu37)
phi = Integration.one_pop(phi, xx, T38, nu38)
phi = Integration.one_pop(phi, xx, T39, nu39)
phi = Integration.one_pop(phi, xx, T40, nu40)
phi = Integration.one_pop(phi, xx, T41, nu41)
phi = Integration.one_pop(phi, xx, T42, nu42)
phi = Integration.one_pop(phi, xx, T43, nu43)
phi = Integration.one_pop(phi, xx, T44, nu44)
phi = Integration.one_pop(phi, xx, T45, nu45)
phi = Integration.one_pop(phi, xx, T46, nu46)
phi = Integration.one_pop(phi, xx, T47, nu47)
phi = Integration.one_pop(phi, xx, T48, nu48)
phi = Integration.one_pop(phi, xx, T49, nu49)
phi = Integration.one_pop(phi, xx, T50, nu50)
phi = Integration.one_pop(phi, xx, T51, nu51)
phi = Integration.one_pop(phi, xx, T52, nu52)
phi = Integration.one_pop(phi, xx, T53, nu53)
phi = Integration.one_pop(phi, xx, T54, nu54)
phi = Integration.one_pop(phi, xx, T55, nu55)
phi = Integration.one_pop(phi, xx, T56, nu56)
phi = Integration.one_pop(phi, xx, T57, nu57)
phi = Integration.one_pop(phi, xx, T58, nu58)
phi = Integration.one_pop(phi, xx, T59, nu59)
phi = Integration.one_pop(phi, xx, T60, nu60)
phi = Integration.one_pop(phi, xx, T61, nu61)
phi = Integration.one_pop(phi, xx, T62, nu62)
phi = Integration.one_pop(phi, xx, T63, nu63)
phi = Integration.one_pop(phi, xx, T64, nu64)
phi = Integration.one_pop(phi, xx, T65, nu65)
phi = Integration.one_pop(phi, xx, T66, nu66)
phi = Integration.one_pop(phi, xx, T67, nu67)
phi = Integration.one_pop(phi, xx, T68, nu68)
phi = Integration.one_pop(phi, xx, T69, nu69)
phi = Integration.one_pop(phi, xx, T70, nu70)
phi = Integration.one_pop(phi, xx, T71, nu71)
phi = Integration.one_pop(phi, xx, T72, nu72)
phi = Integration.one_pop(phi, xx, T73, nu73)
phi = Integration.one_pop(phi, xx, T74, nu74)
phi = Integration.one_pop(phi, xx, T75, nu75)
phi = Integration.one_pop(phi, xx, T76, nu76)
phi = Integration.one_pop(phi, xx, T77, nu77)
phi = Integration.one_pop(phi, xx, T78, nu78)
phi = Integration.one_pop(phi, xx, T79, nu79)
phi = Integration.one_pop(phi, xx, T80, nu80)
phi = Integration.one_pop(phi, xx, T81, nu81)
phi = Integration.one_pop(phi, xx, T82, nu82)
phi = Integration.one_pop(phi, xx, T83, nu83)
phi = Integration.one_pop(phi, xx, T84, nu84)
phi = Integration.one_pop(phi, xx, T85, nu85)
phi = Integration.one_pop(phi, xx, T86, nu86)
phi = Integration.one_pop(phi, xx, T87, nu87)
phi = Integration.one_pop(phi, xx, T88, nu88)
phi = Integration.one_pop(phi, xx, T89, nu89)
phi = Integration.one_pop(phi, xx, T90, nu90)
phi = Integration.one_pop(phi, xx, T91, nu91)
phi = Integration.one_pop(phi, xx, T92, nu92)
phi = Integration.one_pop(phi, xx, T93, nu93)
phi = Integration.one_pop(phi, xx, T94, nu94)
phi = Integration.one_pop(phi, xx, T95, nu95)
phi = Integration.one_pop(phi, xx, T96, nu96)
phi = Integration.one_pop(phi, xx, T97, nu97)
phi = Integration.one_pop(phi, xx, T98, nu98)
phi = Integration.one_pop(phi, xx, T99, nu99)
# get sfs:
fs = Spectrum.from_phi(phi, ns, (xx, ))
return fs
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
command = "-n 1 %(nuAf)f -n 2 %(nuEu)f -n 3 %(nuAs)f "\
"-eg 0 2 %(alphaEu)f -eg 0 3 %(alphaAs)f "\
"-ma x %(mAfEu)f %(mAfAs)f %(mAfEu)f x %(mEuAs)f %(mAfAs)f %(mEuAs)f x "\
"-ej %(TEuAs)f 3 2 -en %(TEuAs)f 2 %(nuB)f "\
"-ema %(TEuAs)f 3 x %(mAfB)f x %(mAfB)f x x x x x "\
"-ej %(TB)f 2 1 "\
"-en %(TAf)f 1 1"
dd = Misc.make_data_dict(infile)
data = Spectrum.from_data_dict(dd, pop_ids, projections, polarized=True)
ns = data.sample_sizes
pts = [65, 80, 95]
np.set_printoptions(precision=3)
#-------------------
def two_growths((nu1, nu2, T1, T2), (n1, ), pts):
xx = Numerics.default_grid(pts)
phi = PhiManip.phi_1D(xx)
nu_func1 = lambda t: np.exp(np.log(nu1) * t / T1)
phi = Integration.one_pop(phi, xx, T1, nu_func1)
nu_func2 = lambda t: nu1 * np.exp(np.log(nu2 / nu1) * t / T2)
phi = Integration.one_pop(phi, xx, T2, nu_func2)
sfs = Spectrum.from_phi(phi, (n1, ), (xx, ))
return sfs
twog = Numerics.make_extrap_log_func(two_growths)
params = array([1, 1, 1, 0.1])
upper_bound = [100, 100, 100, 10]
lower_bound = [0.01, 0.01, 0.01, 0.001]
poptg = dadi.Inference.optimize_log(params,
data,
twog,
pts,
lower_bound=lower_bound,
upper_bound=upper_bound,
verbose=len(params),
TMoCa: split time for Moroccan and Canary island populations
TF: simulation ending time
"""
xx = Numerics.default_grid(pts)
phi = PhiManip.phi_1D(xx)
phi = Integration.one_pop(phi, xx, TIbMo, nu=nuIb0)
phi = PhiManip.phi_1D_to_2D(xx, phi)
phi = Integration.two_pops(phi, xx, TMoCa, nu1=nuIb, nu2=nuMo0)
phi = PhiManip.phi_2D_to_3D_split_2(xx, phi)
phi = Integration.three_pops(phi, xx, TF, nu1=nuIb, nu2=nuMo, nu3=nuCa0)
fs = Spectrum.from_phi(phi, ns, (xx,xx,xx))
return fs
def simple_canary_migration((nuIb0, nuIb, nuMo0, nuMo, nuCa0, TIbMo, TMoCa, mIbCa, TF),
ns, pts):
"""
nuIb0: starting Iberian population size
nuIb: ending Iberian population size
nuMo0: starting Moroccan population size
nuMo: ending Morrocan population size
nuCa0: starting Canary island population size
TIbMo: split time for Iberian and Moroccan populations
TMoCa: split time for Moroccan and Canary island populations
mIbCa: migration rate from Ib to Ca
TF: simulation ending time
]
def pooneh2DModel_ABMod((TDiv, nu1, nu2, m12, m21), ns, pts):
xx = Numerics.default_grid(pts) # sets up grid
phi = PhiManip.phi_1D(xx) # sets up initial phi for population
phi = PhiManip.phi_1D_to_2D(xx, phi) # split into two pops
phi = Integration.two_pops(
phi, xx, TDiv, nu1, nu2, m12=m12,
m21=m21) # two pops at diff sizes with symmetric migration
# allow for another size change; fix time at 35 gen
# fix these at my bneck sizes (not pooneh's)
phi = Integration.two_pops(
phi, xx, 0.004, 0.05, 0.05, m12=0, m21=0
) # fixing time at 35/(2*4000) to represent 35 gen ago and am fixing migraiton to be 0 during the bottleneck
fs = Spectrum.from_phi(phi, ns, (xx, xx))
return fs
func = pooneh2DModel_ABMod
modelName = "pooneh2DModel_ABMod"
# wrap your function in Numerics.make_extrap_log_func to make extrapolation version of your function
func_ex = Numerics.make_extrap_log_func(func)
modelPooneh = func_ex(paramsPooneh, ns, pts_l) # this is relative to theta =1
ll_modelPooneh = dadi.Inference.ll_multinom(modelPooneh, fs)
ll_modelPooneh
modelAnnabel = func_ex(paramsAnnabel, ns,
pts_l) # this is relative to theta =1
ll_modelAnnabel = dadi.Inference.ll_multinom(modelAnnabel, fs)
