From 40a9f26d239fb828d8ab7ca2693b84997ed2ae93 Mon Sep 17 00:00:00 2001
From: Martin Beseda <martin.beseda@vsb.cz>
Date: Wed, 23 Jan 2019 13:58:34 +0100
Subject: [PATCH] ENH: Modified output from MSE evaluation functions
---
src/ErrorFunction/ErrorFunctions.cpp | 48 +++++++++++++++-------------
1 file changed, 25 insertions(+), 23 deletions(-)
diff --git a/src/ErrorFunction/ErrorFunctions.cpp b/src/ErrorFunction/ErrorFunctions.cpp
index 29d8fa34..59323bd8 100644
--- a/src/ErrorFunction/ErrorFunctions.cpp
+++ b/src/ErrorFunction/ErrorFunctions.cpp
@@ -105,7 +105,7 @@ namespace lib4neuro {
size_t dim_in = data_set->get_input_dim();
size_t dim_out = data_set->get_output_dim();
- double error = 0.0, val, output_norm;
+ double error = 0.0, val, output_norm = 0;
std::vector<std::pair<std::vector<double>, std::vector<double>>>* data = data_set->get_data();
size_t n_elements = data->size();
@@ -168,20 +168,22 @@ namespace lib4neuro {
output_norm += denormalized_output * denormalized_output;
}
+
#ifdef L4N_DEBUG
- COUT_DEBUG(i << ": "
- << ss_input.str() << " ; "
- << ss_real_output.str() << " ; "
- << ss_predicted_output.str() << "; "
- << std::sqrt(error) << "; "
- << 2 * std::sqrt(error) / (std::sqrt(error) + std::sqrt(output_norm)) <<
- std::endl);
-
- *results_file_path << i << ": "
- << ss_input.str() << " ; "
- << ss_real_output.str() << " ; "
- << ss_predicted_output.str() << "; "
- << std::sqrt(error) << "; "
+ COUT_DEBUG("[" << i << "] "
+ << ss_input.str() << " "
+ << ss_real_output.str() << " "
+ << ss_predicted_output.str() << " "
+ << std::sqrt(error) << " "
+ << 2 * std::sqrt(error) / (std::sqrt(error) + std::sqrt(output_norm))
+ << std::endl);
+
+ *results_file_path << "["
+ << i << "] "
+ << ss_input.str() << " "
+ << ss_real_output.str() << " "
+ << ss_predicted_output.str() << " "
+ << std::sqrt(error) << " "
<< 2 * std::sqrt(error) / (std::sqrt(error) + std::sqrt(output_norm)) <<
std::endl;
#endif
@@ -214,7 +216,7 @@ namespace lib4neuro {
THROW_RUNTIME_ERROR("File path: " + results_file_path + " was not successfully opened!");
}
- ofs << "[Input] [Real output] [Predicted output]" << std::endl;
+ ofs << "[Index ][Input] [Real output] [Predicted output]" << std::endl;
for (auto i = 0; i < data->size(); i++) { // Iterate through every element in the test set
@@ -241,10 +243,10 @@ namespace lib4neuro {
} else {
denormalized_output = outputs.at(i).at(j);
}
- COUT_DEBUG("Element " << i << ": "
- << data->at(i).first.at(j) << " "
- << data->at(i).second.at(j) << " "
- << denormalized_output << std::endl);
+ COUT_DEBUG("[" << i << "] "
+ << data->at(i).first.at(j) << " "
+ << data->at(i).second.at(j) << " "
+ << denormalized_output << std::endl);
ofs << data->at(i).first.at(j) << " "
<< data->at(i).second.at(j) << " "
@@ -306,10 +308,10 @@ namespace lib4neuro {
} else {
denormalized_output = outputs.at(i).at(j);
}
- COUT_DEBUG("Element " << i << ": "
- << data->at(i).first.at(j) << " "
- << data->at(i).second.at(j) << " "
- << denormalized_output << std::endl);
+ COUT_DEBUG("[" << i << "] "
+ << data->at(i).first.at(j) << " "
+ << data->at(i).second.at(j) << " "
+ << denormalized_output << std::endl);
val = denormalized_output - data->at(i).second.at(j);
error += val * val;
--
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