import pkg_resources
import pandas as pd
import numpy as np
import torch
[docs]def load_grm():
r"""Return data-generating parameters and sampled data for a graded response model.
The generating model has four correlated latent factors and twelve items with
three categories each.
Returns
_______
res : dict
A dictionary containing sampled data and data-generating parameters.
The returned dictionary includes the following key-value pairs:
* \"data\", the sampled data set of item responses;
* \"loadings\", the data-generating factor loadings;
* \"intercepts\", the data-generating category intercepts;
* \"cov_mat\", the data-generating factor covariance matrix; and
* \"factor_scores\", the sampled factor scores.
"""
keys = ["data", "loadings", "intercepts", "cov_mat", "factor_scores"]
res = {}
for k in keys:
stream = pkg_resources.resource_stream(__name__, "data/" + k + ".csv")
res[k] = torch.from_numpy(pd.read_csv(stream, sep = ",", header = None).to_numpy())
return res