From 10c02177a756fba9501d5fccfd68c07bcb43e88d Mon Sep 17 00:00:00 2001 From: Shuvayan Das Date: Thu, 11 Jul 2024 18:03:46 +0530 Subject: [PATCH] Future-proof `prior_linearized` method call (#806) * modified: pymc_marketing/mmm/tvp.py * Update tvp.py Changed Xs to X in prior_linearized( as per the change in pymc) * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: sangeedutta Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Will Dean <57733339+wd60622@users.noreply.github.com> --- pymc_marketing/mmm/tvp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pymc_marketing/mmm/tvp.py b/pymc_marketing/mmm/tvp.py index 0d4537622..db434252d 100644 --- a/pymc_marketing/mmm/tvp.py +++ b/pymc_marketing/mmm/tvp.py @@ -161,7 +161,7 @@ def time_varying_prior( hsgp_dims = (dims[1], "m") gp = pm.gp.HSGP(m=[hsgp_kwargs.m], L=[hsgp_kwargs.L], cov_func=cov_func) - phi, sqrt_psd = gp.prior_linearized(Xs=X[:, None] - X_mid) + phi, sqrt_psd = gp.prior_linearized(X[:, None] - X_mid) hsgp_coefs = pm.Normal(f"{name}_hsgp_coefs", dims=hsgp_dims) f = phi @ (hsgp_coefs * sqrt_psd).T f = pt.softplus(f)