founder_nomig_admix_two_epoch model argument T2 not used about dadi_pipeline

[dportik]

You are correct, this was supposed to include T2 rather than T1. This mistake has been fixed in the updated code. Thanks for taking the time to read through the models carefully enough to catch this issue!

[dportik]

@hemstrow I just wanted to follow up on this and report that there were other issues I found with the original island model set, including mis-assigned and nonsense parameters. These models were incorrectly specified in addition to the issue you raised.

I discussed some better approaches to these models with Ryan (threads here and here). Afterwards, I completely re-wrote the original island model set. I released the revised island models as part of dadi_pipeline v3.1.1 in December 2019.

I'm not sure if you have seen these updates, but wanted to make you aware of them. If you plan to use the revised island models, please let me know if you find any other issues or discrepancies. These resources are a work in progress, and I always appreciate the feedback.

Thanks!

[xuefenfei712]

Dear dportik

To continue this question, I want to build 1D model that my population experienced first bottleneck and then a founder effect, I draft the code, while it shows error:
code:
def three_epoch_founder(params, ns, pts):
"""
params = (nuB,nuF,nuFd,TB,TF,TFe)
ns = (n1,)

nuB: Ratio of bottleneck population size to ancient pop size
nuF: Ratio of contemporary to ancient pop size ##Ratio of founder to ancient
nuFd: Ratio of contemporary to founder
TB: Length of bottleneck (in units of 2*Na generations)
TF: Time since bottleneck recovery (in units of 2*Na generations)
TFe: Time of founder effect
n1: Number of samples in resulting Spectrum
pts: Number of grid points to use in integration.
"""
nuB,nuF,nuFd,TB,TF,TFe = 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)
nuFd_func = lambda t: nuF * (nuFd/nuF)**(t/TFe)
phi = Integration.one_pop(phi, xx, TFe, nuFd=nuFd_func)
fs = Spectrum.from_phi(phi, ns, (xx,))
return fs

three_epoch_founder.param_names = ['nuB', 'nuF','nuFd', 'TB', 'TF', 'TFe']

Looking forward for your reply, thankyou
Best
Xue

[dportik]

Hi @xuefenfei712 ,
For questions related to model specification (and not the pipeline workflow), please post on the dadi user group:
https://groups.google.com/g/dadi-user