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Use Eigen::placeholders::all over Eigen::all #424

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6 changes: 3 additions & 3 deletions include/stochtree/random_effects.h
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Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ class MultivariateRegressionRandomEffectsModel {
group_parameters_ = group_parameters;
}
void SetGroupParameter(Eigen::VectorXd& group_parameter, int32_t group_id) {
group_parameters_(Eigen::all, group_id) = group_parameter;
group_parameters_(Eigen::placeholders::all, group_id) = group_parameter;
}
void SetWorkingParameterCovariance(Eigen::MatrixXd& working_parameter_covariance) {
working_parameter_covariance_ = working_parameter_covariance;
Expand Down Expand Up @@ -211,7 +211,7 @@ class MultivariateRegressionRandomEffectsModel {
std::int32_t group_ind;
for (int i = 0; i < n; i++) {
group_ind = tracker.CategoryNumber(group_labels[i]);
output[i] = X(i, Eigen::all) * alpha_diag * group_parameters_(Eigen::all, group_ind);
output[i] = X(i, Eigen::placeholders::all) * alpha_diag * group_parameters_(Eigen::placeholders::all, group_ind);
}
}

Expand All @@ -238,7 +238,7 @@ class MultivariateRegressionRandomEffectsModel {
std::int32_t group_ind;
for (int i = 0; i < n; i++) {
group_ind = tracker.CategoryNumber(group_labels[i]);
new_pred = X(i, Eigen::all) * alpha_diag * group_parameters_(Eigen::all, group_ind);
new_pred = X(i, Eigen::placeholders::all) * alpha_diag * group_parameters_(Eigen::placeholders::all, group_ind);
new_resid = residual.GetElement(i) - new_pred;
residual.SetElement(i, new_resid);
tracker.SetPrediction(i, new_pred);
Expand Down
24 changes: 12 additions & 12 deletions src/random_effects.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -54,7 +54,7 @@ void RandomEffectsTracker::ResetFromSample(MultivariateRegressionRandomEffectsMo
for (int i = 0; i < n; i++) {
group_ind = CategoryNumber(group_labels[i]);
prev_pred = GetPrediction(i);
new_pred = X(i, Eigen::all) * alpha_diag * xi(Eigen::all, group_ind);
new_pred = X(i, Eigen::placeholders::all) * alpha_diag * xi(Eigen::placeholders::all, group_ind);
new_resid = residual.GetElement(i) - new_pred + prev_pred;
residual.SetElement(i, new_resid);
SetPrediction(i, new_pred);
Expand Down Expand Up @@ -123,7 +123,7 @@ void MultivariateRegressionRandomEffectsModel::SampleGroupParameters(RandomEffec
for (int i = 0; i < num_groups; i++) {
posterior_mean = GroupParameterMean(dataset, residual, rfx_tracker, global_variance, i);
posterior_covariance = GroupParameterVariance(dataset, residual, rfx_tracker, global_variance, i);
group_parameters_(Eigen::all, i) = normal_sampler_.SampleEigen(posterior_mean, posterior_covariance, gen);
group_parameters_(Eigen::placeholders::all, i) = normal_sampler_.SampleEigen(posterior_mean, posterior_covariance, gen);
}
}

Expand Down Expand Up @@ -155,9 +155,9 @@ Eigen::VectorXd MultivariateRegressionRandomEffectsModel::WorkingParameterMean(R
Eigen::MatrixXd xi = group_parameters_;
for (int i = 0; i < num_groups; i++) {
observation_indices = rfx_tracker.NodeIndicesInternalIndex(i);
X_group = X(observation_indices, Eigen::all);
y_group = y(observation_indices, Eigen::all);
xi_group = xi(Eigen::all, i);
X_group = X(observation_indices, Eigen::placeholders::all);
y_group = y(observation_indices, Eigen::placeholders::all);
xi_group = xi(Eigen::placeholders::all, i);
posterior_denominator += ((xi_group).asDiagonal() * X_group.transpose() * X_group * (xi_group).asDiagonal()) / global_variance;
posterior_numerator += (xi_group).asDiagonal() * X_group.transpose() * y_group / global_variance;
}
Expand All @@ -178,9 +178,9 @@ Eigen::MatrixXd MultivariateRegressionRandomEffectsModel::WorkingParameterVarian
Eigen::MatrixXd xi = group_parameters_;
for (int i = 0; i < num_groups; i++) {
observation_indices = rfx_tracker.NodeIndicesInternalIndex(i);
X_group = X(observation_indices, Eigen::all);
y_group = y(observation_indices, Eigen::all);
xi_group = xi(Eigen::all, i);
X_group = X(observation_indices, Eigen::placeholders::all);
y_group = y(observation_indices, Eigen::placeholders::all);
xi_group = xi(Eigen::placeholders::all, i);
posterior_denominator += ((xi_group).asDiagonal() * X_group.transpose() * X_group * (xi_group).asDiagonal()) / (global_variance);
}
return posterior_denominator.inverse();
Expand All @@ -195,8 +195,8 @@ Eigen::VectorXd MultivariateRegressionRandomEffectsModel::GroupParameterMean(Ran
Eigen::MatrixXd posterior_denominator = group_parameter_covariance_.inverse();
Eigen::VectorXd posterior_numerator = Eigen::VectorXd::Zero(num_components);
std::vector<data_size_t> observation_indices = rfx_tracker.NodeIndicesInternalIndex(group_id);
Eigen::MatrixXd X_group = X(observation_indices, Eigen::all);
Eigen::VectorXd y_group = y(observation_indices, Eigen::all);
Eigen::MatrixXd X_group = X(observation_indices, Eigen::placeholders::all);
Eigen::VectorXd y_group = y(observation_indices, Eigen::placeholders::all);
posterior_denominator += ((alpha).asDiagonal() * X_group.transpose() * X_group * (alpha).asDiagonal()) / (global_variance);
posterior_numerator += (alpha).asDiagonal() * X_group.transpose() * y_group / global_variance;
return posterior_denominator.inverse() * posterior_numerator;
Expand All @@ -211,8 +211,8 @@ Eigen::MatrixXd MultivariateRegressionRandomEffectsModel::GroupParameterVariance
Eigen::MatrixXd posterior_denominator = group_parameter_covariance_.inverse();
// Eigen::VectorXd posterior_numerator = Eigen::VectorXd::Zero(num_components);
std::vector<data_size_t> observation_indices = rfx_tracker.NodeIndicesInternalIndex(group_id);
Eigen::MatrixXd X_group = X(observation_indices, Eigen::all);
// Eigen::VectorXd y_group = y(observation_indices, Eigen::all);
Eigen::MatrixXd X_group = X(observation_indices, Eigen::placeholders::all);
// Eigen::VectorXd y_group = y(observation_indices, Eigen::placeholders::all);
posterior_denominator += ((alpha).asDiagonal() * X_group.transpose() * X_group * (alpha).asDiagonal()) / (global_variance);
// posterior_numerator += (alpha).asDiagonal() * X_group.transpose() * y_group;
return posterior_denominator.inverse();
Expand Down
30 changes: 15 additions & 15 deletions test/cpp/test_random_effects.cpp
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Expand Up @@ -58,8 +58,8 @@ TEST(RandomEffects, Construction) {
Eigen::MatrixXd sigma(test_dataset.rfx_basis_cols, test_dataset.rfx_basis_cols);
alpha << 1.5;
xi << 2, 4;
Eigen::VectorXd xi0 = xi(Eigen::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::all, 1);
Eigen::VectorXd xi0 = xi(Eigen::placeholders::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand All @@ -72,8 +72,8 @@ TEST(RandomEffects, Construction) {
// Change values and push a second "sample" to the container
alpha << 2.0;
xi << 1, 3;
xi0 = xi(Eigen::all, 0);
xi1 = xi(Eigen::all, 1);
xi0 = xi(Eigen::placeholders::all, 0);
xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand Down Expand Up @@ -124,9 +124,9 @@ TEST(RandomEffects, Computation) {
Eigen::MatrixXd sigma(test_dataset.rfx_basis_cols, test_dataset.rfx_basis_cols);
alpha << 1., 1.;
xi << 1., 1., 1., 1., 1., 1.;
Eigen::VectorXd xi0 = xi(Eigen::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::all, 1);
Eigen::VectorXd xi2 = xi(Eigen::all, 2);
Eigen::VectorXd xi0 = xi(Eigen::placeholders::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::placeholders::all, 1);
Eigen::VectorXd xi2 = xi(Eigen::placeholders::all, 2);
sigma << 1, 0, 0, 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand Down Expand Up @@ -180,8 +180,8 @@ TEST(RandomEffects, Predict) {
Eigen::MatrixXd sigma(test_dataset.rfx_basis_cols, test_dataset.rfx_basis_cols);
alpha << 1.5;
xi << 2, 4;
Eigen::VectorXd xi0 = xi(Eigen::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::all, 1);
Eigen::VectorXd xi0 = xi(Eigen::placeholders::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand All @@ -194,8 +194,8 @@ TEST(RandomEffects, Predict) {
// Change values and push a second "sample" to the container
alpha << 2.0;
xi << 1, 3;
xi0 = xi(Eigen::all, 0);
xi1 = xi(Eigen::all, 1);
xi0 = xi(Eigen::placeholders::all, 0);
xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand Down Expand Up @@ -242,8 +242,8 @@ TEST(RandomEffects, Serialization) {
Eigen::MatrixXd sigma(test_dataset.rfx_basis_cols, test_dataset.rfx_basis_cols);
alpha << 1.5;
xi << 2, 4;
Eigen::VectorXd xi0 = xi(Eigen::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::all, 1);
Eigen::VectorXd xi0 = xi(Eigen::placeholders::all, 0);
Eigen::VectorXd xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand All @@ -256,8 +256,8 @@ TEST(RandomEffects, Serialization) {
// Change values and push a second "sample" to the container
alpha << 2.0;
xi << 1, 3;
xi0 = xi(Eigen::all, 0);
xi1 = xi(Eigen::all, 1);
xi0 = xi(Eigen::placeholders::all, 0);
xi1 = xi(Eigen::placeholders::all, 1);
sigma << 1;
model.SetWorkingParameter(alpha);
model.SetGroupParameter(xi0, 0);
Expand Down
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