void CExactInferenceMethod::check_members()
{
if (!m_labels)
SG_ERROR("No labels set\n")
if (m_labels->get_label_type() != LT_REGRESSION)
SG_ERROR("Expected RegressionLabels\n")
if (!m_features)
SG_ERROR("No features set!\n")
if (m_labels->get_num_labels() != m_features->get_num_vectors())
SG_ERROR("Number of training vectors does not match number of labels\n")
if(m_features->get_feature_class() == C_COMBINED)
{
CDotFeatures* feat =
(CDotFeatures*)((CCombinedFeatures*)m_features)->
get_first_feature_obj();
if (!feat->has_property(FP_DOT))
SG_ERROR("Specified features are not of type CFeatures\n")
if (feat->get_feature_class() != C_DENSE)
SG_ERROR("Expected Simple Features\n")
if (feat->get_feature_type() != F_DREAL)
SG_ERROR("Expected Real Features\n")
SG_UNREF(feat);
}
CRegressionLabels* CGaussianProcessRegression::apply_regression(CFeatures* data)
{
if (data)
{
if(data->get_feature_class() == C_COMBINED)
{
CDotFeatures* feat =
(CDotFeatures*)((CCombinedFeatures*)data)->
get_first_feature_obj();
if (!feat->has_property(FP_DOT))
SG_ERROR("Specified features are not of type CFeatures\n")
if (feat->get_feature_class() != C_DENSE)
SG_ERROR("Expected Simple Features\n")
if (feat->get_feature_type() != F_DREAL)
SG_ERROR("Expected Real Features\n")
SG_UNREF(feat);
}
else
{
if (!data->has_property(FP_DOT))
CRegressionLabels* CGaussianProcessRegression::apply_regression(CFeatures* data)
{
if (data)
{
if(data->get_feature_class() == C_COMBINED)
{
CDotFeatures* feat =
(CDotFeatures*)((CCombinedFeatures*)data)->
get_first_feature_obj();
if (!feat->has_property(FP_DOT))
SG_ERROR("Specified features are not of type CFeatures\n");
if (feat->get_feature_class() != C_DENSE)
SG_ERROR("Expected Simple Features\n");
if (feat->get_feature_type() != F_DREAL)
SG_ERROR("Expected Real Features\n");
SG_UNREF(feat);
}
else
{
if (!data->has_property(FP_DOT))
SG_ERROR("Specified features are not of type CFeatures\n");
if (data->get_feature_class() != C_DENSE)
SG_ERROR("Expected Simple Features\n");
if (data->get_feature_type() != F_DREAL)
SG_ERROR("Expected Real Features\n");
}
SG_UNREF(m_data);
SG_REF(data);
m_data = (CFeatures*)data;
update_kernel_matrices();
}
else if (!m_data)
SG_ERROR("No testing features!\n");
else if (update_parameter_hash())
update_kernel_matrices();
if (m_return == GP_RETURN_COV)
{
CRegressionLabels* result =
new CRegressionLabels(getCovarianceVector());
return result;
}
if (m_return == GP_RETURN_MEANS)
{
CRegressionLabels* result =
new CRegressionLabels(getMeanVector());
return result;
}
else
{
SGVector<float64_t> mean_vector = getMeanVector();
SGVector<float64_t> cov_vector = getCovarianceVector();
index_t size = mean_vector.vlen+cov_vector.vlen;
SGVector<float64_t> result_vector(size);
for (index_t i = 0; i < size; i++)
{
if (i < mean_vector.vlen)
result_vector[i] = mean_vector[i];
else
result_vector[i] = cov_vector[i-mean_vector.vlen];
}
CRegressionLabels* result =
new CRegressionLabels(result_vector);
return result;
}
}