def model_repr(model):
assert type(model) == ModelDesc
out = []
def write(s):
out.append(s)
write('=' * 40)
write('Population')
write('-' * 40)
write('Coef Priors:')
for (coef, prior) in zip(model.population.coefs, model.population.priors):
write('{:<15} | {}'.format(coef, family_repr(prior)))
for i, group in enumerate(model.groups):
write('=' * 40)
write('Group {}'.format(i))
write('-' * 40)
write('Factors: {}\nNum Levels: {}'.format(', '.join(group.columns), len(group.levels)))
write('Corr. Prior: {}'.format(None if group.corr_prior is None else family_repr(group.corr_prior)))
write('S.D. Priors:')
for (coef, sd_prior) in zip(group.coefs, group.sd_priors):
write('{:<15} | {}'.format(coef, family_repr(sd_prior)))
write('=' * 40)
write('Response')
write('-' * 40)
write('Family: {}'.format(family_repr(model.response.family)))
write('Link:')
write(' Parameter: {}'.format(model.response.family.link.param))
write(' Function: {}'.format(model.response.family.link.fn.name))
write('Priors:')
for (param, prior) in zip(model.response.nonlocparams, model.response.priors):
write('{:<15} | {}'.format(param.name, family_repr(prior)))
write('=' * 40)
return '\n'.join(out)
def check_family_matches_response(formula, metadata, family):
assert type(metadata) == Metadata
if not family_matches_response(formula, metadata, family):
# TODO: This could be more informative. e.g. If choosing
# Bernoulli fails, is the problem that the response is
# numeric, or that it has more than two levels?
error = 'The response distribution "{}" is not compatible with the type or contents of the response column "{}".'
raise Exception(error.format(family_repr(family), formula.response))