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 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 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 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):
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 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 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 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 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 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 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 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 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
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
]
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)
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"
from dadi import Misc, Spectrum, Numerics, PhiManip, Integration, Demographics1D, Demographics2D
import sys
infile = sys.argv[1]
pop_ids = sys.argv[2]
projections = [int(sys.argv[3])]
#infile="5kA_dadi.data"
#pop_ids=["O1"]
#projections=[32]
import os
# replace this with your appropriate dir name
# os.chdir("/Users/c-monstr/Documents/allRAD_august2015/digitifera/dadi")
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)
#-------------------
gr = Numerics.make_extrap_log_func(Demographics1D.growth)
params = array([3, 1])
upper_bound = [100, 100]
lower_bound = [0.01, 0.01]
poptg = dadi.Inference.optimize_log(params,
data,
gr,
pts,
lower_bound=lower_bound,
#!/usr/bin/env python
import dadi
import pylab
import matplotlib.pyplot as plt
import numpy as np
from numpy import array
from dadi import Misc, Spectrum, Numerics, PhiManip, Integration, Demographics1D, Demographics2D
import sys
infile = sys.argv[1]
popid = [sys.argv[2]]
proj = range(int(sys.argv[3]), int(sys.argv[4]))
dd = Misc.make_data_dict(infile)
for p in range(len(proj)):
data = Spectrum.from_data_dict(dd,
pop_ids=popid,
projections=[proj[p]],
polarized=False)
print proj[p], data.S()
import matplotlib.pyplot as plt
import numpy as np
from numpy import array
from dadi import Misc, Spectrum, Numerics, PhiManip, Integration, Demographics1D, Demographics2D
import sys
infile = sys.argv[1]
pop_ids = sys.argv[2]
projections = [int(sys.argv[3])]
import os
# replace this with your appropriate dir name
# os.chdir("/Users/c-monstr/Documents/allRAD_august2015/digitifera/dadi")
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
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:
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