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Description
Describe the issue:
pm.gp.Marginal.conditional need a array-like type variable. I input a ndarray type variable,which raise a valueError (setting an array element with a sequence).I suppose it should be filled in a tensor variable?
Reproduceable code example:
import numpy as np
import pandas as pd
import pymc as pm
from sklearn.neighbors import KernelDensity
data = pd.read_csv('QDN_AC.csv')
X = data['Lon'].astype(float)
Y = data['Lat'].astype(float)
Z = data['AC production'].astype(float)
coords = np.vstack([X, Y]).T
kde = KernelDensity(kernel='gaussian', bandwidth=1.0).fit(coords)
density = kde.score_samples(coords)
with pm.Model() as model_kde_gp:
sigma = pm.HalfNormal('sigma', sigma=1)
length_scale = pm.Gamma('length_scale', alpha=2, beta=1)
mean_func = pm.gp.mean.Zero()
cov_func = pm.gp.cov.ExpQuad(input_dim=1, ls=length_scale)
gp = pm.gp.Marginal(mean_func=mean_func, cov_func=cov_func)
Y_obs = gp.marginal_likelihood('Y_obs', X=density[:, None], y=Z, noise=sigma)
trace_kde_gp = pm.sample(10, return_inferencedata=True)
grid_x, grid_y = np.meshgrid(
np.linspace(X.min(), X.max(), 100),
np.linspace(Y.min(), Y.max(), 100),
)
grid_coords = np.vstack([grid_x.ravel(), grid_y.ravel()]).T
grid_density = kde.score_samples(grid_coords)
grid_coords = np.array(grid_coords)
with model_kde_gp:
p = 0.1
gp_pred = gp.conditional('gp_pred', Xnew=grid_coords)
pred_samples = pm.sample_posterior_predictive(trace_kde_gp, var_names=['gp_pred'], random_seed=42)
pred_mean = pred_samples['gp_pred'].mean(axis=0)
pred_lower = np.percentile(pred_samples['gp_pred'], 2.5, axis=0)
pred_upper = np.percentile(pred_samples['gp_pred'], 97.5, axis=0)
grid_density = np.exp(grid_density).reshape(grid_x.shape)
pred_mean = pred_mean.reshape(grid_x.shape)
pred_lower = pred_lower.reshape(grid_x.shape)
pred_upper = pred_upper.reshape(grid_x.shape)Error message:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
TypeError: float() argument must be a string or a real number, not 'TensorVariable'
The above exception was the direct cause of the following exception:
ValueError Traceback (most recent call last)
Cell In[9], line 37
35 with model_kde_gp:
36 p = 0.1
---> 37 gp_pred = gp.conditional('gp_pred', Xnew=grid_coords)
38 pred_samples = pm.sample_posterior_predictive(trace_kde_gp, var_names=['gp_pred'], random_seed=42)
40 pred_mean = pred_samples['gp_pred'].mean(axis=0)
File ~/miniconda3/envs/ai/lib/python3.10/site-packages/pymc/gp/gp.py:624, in Marginal.conditional(self, name, Xnew, pred_noise, given, jitter, **kwargs)
591 R"""
592 Return the conditional distribution evaluated over new input locations `Xnew`.
593
(...)
621 constructor.
622 """
623 givens = self._get_given_vals(given)
--> 624 mu, cov = self._build_conditional(Xnew, pred_noise, False, *givens, jitter)
625 return pm.MvNormal(name, mu=mu, cov=cov, **kwargs)
...
--> 820 subarr = np.asarray(arr, dtype=dtype)
821 else:
822 subarr = np.array(arr, dtype=dtype, copy=copy)
ValueError: setting an array element with a sequence.PyMC version information:
PyMC version: 5.18.2
Context for the issue:
No response