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remove prints

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This commit is contained in:
Hannes Signer 2025-12-10 23:36:59 +01:00
parent 3be8cc1cb4
commit 5c5c328b0b
1 changed files with 2 additions and 33 deletions
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35
src/poet.cpp
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@ -397,14 +397,11 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
std::string("field <- setNames(data.frame(matrix(TMP, nrow=" +
std::to_string(chem.getField().GetRequestedVecSize()) +
")), TMP_PROPS)"));
R.parseEval("print(head(field))");
R.parseEval("validity_vector <- rep(FALSE, nrow(field))");
R.parseEval("length(validity_vector)");
R.parseEval("print(length(validity_vector))");
if (params.copy_non_reactive_regions) {
R.parseEval(
"validity_vector <- field[[threshold$species]] < threshold$value");
@ -418,8 +415,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
// deep copy field
R.parseEval("predictors <- field");
// get only ai related species
R.parseEval("print(head(predictors))");
R.parseEval("print(ai_surrogate_species_input)");
R.parseEval("predictors <- predictors[ai_surrogate_species_input]");
// remove already copied values
@ -430,7 +425,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
R.parseEval("predictors_scaled <- preprocess(predictors)");
R.parseEval("print(head(predictors_scaled))");
std::vector<std::vector<float>> predictors_scaled =
R["predictors_scaled"];
@ -442,13 +436,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
std::vector<double> predictions_scaled_double(predictions_scaled.begin(),
predictions_scaled.end());
std::cout << "First elements of predictions_scaled_double: ";
for (size_t i = 0;
i < std::min(size_t(10), predictions_scaled_double.size()); i++) {
std::cout << predictions_scaled_double[i] << " ";
}
std::cout << std::endl;
R["TMP"] = predictions_scaled_double;
R["n_samples"] = n_samples;
R["n_output"] = n_output_features;
@ -456,8 +443,7 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
R.parseEval("predictions_scaled <- setNames(data.frame(matrix(TMP, "
"nrow=n_samples, ncol=n_output, byrow=TRUE)), "
"ai_surrogate_species_output)");
// R.parseEval("print(head(predictions_scaled))");
// R.parseEval("print(head(predictions_scaled))");
R.parseEval("predictions <- postprocess(predictions_scaled)");
MSG("AI Validation");
@ -465,8 +451,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
R.parseEval("ai_validity_vector <- validate_predictions(predictors, "
"predictions) ");
R.parseEval("print(length(ai_validity_vector))");
// get only indices where prediction was valid
R.parseEval("predictor_idx <- predictor_idx[ai_validity_vector]");
@ -474,8 +458,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
// was possible
R.parseEval("validity_vector[as.numeric(predictor_idx)] <- TRUE");
R.parseEval("print(length(validity_vector))");
MSG("AI TempField");
// maybe row.names was overwritten by function calls ??
R.parseEval("row.names(predictions) <- row.names(predictors)");
@ -502,7 +484,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
MSG("Set copied or predicted values for the workers");
R.parseEval(
"print(paste('Number of valid cells:', sum(validity_vector)))");
R.parseEval("print(head(validity_vector))");
chem.set_ai_surrogate_validity_vector(R.parseEval("validity_vector"));
}
@ -517,22 +498,15 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
std::string("targets <- setNames(data.frame(matrix(TMP, nrow=" +
std::to_string(chem.getField().GetRequestedVecSize()) +
")), TMP_PROPS)"));
R.parseEval("print(paste('Length of validity_vector:', "
"length(ai_validity_vector)))");
R.parseEval("predictors_retraining <- "
"get_invalid_values(predictors_scaled, ai_validity_vector)");
R.parseEval("targets <- "
"targets[as.numeric(row.names(predictors_retraining)), "
"ai_surrogate_species_output]");
R.parseEval("print(length(predictors_scaled$H))");
R.parseEval("print(length(ai_validity_vector))");
R.parseEval("targets_retraining <- preprocess(targets)");
R.parseEval("print(head(predictors_retraining))");
R.parseEval("print(head(targets_retraining))");
std::vector<std::vector<float>> predictors_retraining =
R["predictors_retraining"];
std::vector<std::vector<float>> targets_retraining =
@ -540,11 +514,6 @@ static Rcpp::List RunMasterLoop(RInsidePOET &R, const RuntimeParameters &params,
MSG("AI: add invalid data to buffer");
std::cout << "size of predictors " << predictors_retraining[0].size()
<< std::endl;
std::cout << "size of targets " << targets_retraining[0].size()
<< std::endl;
ai_ctx->data_semaphore_write.acquire();
if (predictors_retraining[0].size() > 0 &&