fixed probabilities

build/default/Testing/20240619-1525/Test.xml

@@ -24,11 +24,11 @@
 	ProcessorClockFrequency="2600"
 	>
 	<Testing>
-		<StartDateTime>Jun 19 10:25 CDT</StartDateTime>
-		<StartTestTime>1718810754</StartTestTime>
+		<StartDateTime>Jun 19 11:23 CDT</StartDateTime>
+		<StartTestTime>1718814217</StartTestTime>
 		<TestList/>
-		<EndDateTime>Jun 19 10:25 CDT</EndDateTime>
-		<EndTestTime>1718810754</EndTestTime>
+		<EndDateTime>Jun 19 11:23 CDT</EndDateTime>
+		<EndTestTime>1718814217</EndTestTime>
 		<ElapsedMinutes>0</ElapsedMinutes>
 	</Testing>
 </Site>

build/default/Testing/20240625-1924/Test.xml

@@ -0,0 +1,34 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Site BuildName="Linux-c++"
+	BuildStamp="20240625-1924-Experimental"
+	Name="CASLabLinux"
+	Generator="ctest-3.16.3"
+	CompilerName="/usr/bin/c++"
+	CompilerVersion="9.4.0"
+	OSName="Linux"
+	Hostname="CASLabLinux"
+	OSRelease="5.15.0-107-generic"
+	OSVersion="#117~20.04.1-Ubuntu SMP Tue Apr 30 10:35:57 UTC 2024"
+	OSPlatform="x86_64"
+	Is64Bits="1"
+	VendorString="GenuineIntel"
+	VendorID="Intel Corporation"
+	FamilyID="6"
+	ModelID="158"
+	ProcessorCacheSize="12288"
+	NumberOfLogicalCPU="12"
+	NumberOfPhysicalCPU="6"
+	TotalVirtualMemory="2047"
+	TotalPhysicalMemory="31732"
+	LogicalProcessorsPerPhysical="2"
+	ProcessorClockFrequency="3159.87"
+	>
+	<Testing>
+		<StartDateTime>Jun 25 14:24 CDT</StartDateTime>
+		<StartTestTime>1719343490</StartTestTime>
+		<TestList/>
+		<EndDateTime>Jun 25 14:24 CDT</EndDateTime>
+		<EndTestTime>1719343490</EndTestTime>
+		<ElapsedMinutes>0</ElapsedMinutes>
+	</Testing>
+</Site>

build/default/Testing/TAG

@@ -1,3 +1,3 @@
-20240619-1525
+20240625-1924
 Experimental
 Experimental

build/default/Testing/Temporary/LastTest_20240619-1525.log

@@ -1,3 +1,3 @@
-Start testing: Jun 19 10:25 CDT
+Start testing: Jun 19 11:23 CDT
 ----------------------------------------------------------
-End testing: Jun 19 10:25 CDT
+End testing: Jun 19 11:23 CDT

build/default/Testing/Temporary/LastTest_20240625-1924.log

@@ -0,0 +1,3 @@
+Start testing: Jun 25 14:24 CDT
+----------------------------------------------------------
+End testing: Jun 25 14:24 CDT

include/bernstein_probability.h

@@ -7,6 +7,10 @@
 #include "../../BeBOT_cpp/include/bernsteinpoly.h"
 #include "../../BeBOT_cpp/include/bernsteinmatrix_a2b.h"
 
+std::vector<std::vector<double>> convertTo2D(const std::vector<double>& flatMatrix,
+                                             size_t rows,
+                                             size_t cols);
+
 std::vector<std::vector<double>> bernstein_probability(const std::vector<double>& x, 
                                                        const std::vector<double>& x_cdf, 
                                                        const std::vector<double>& P);

src/bernstein_estimator.cpp

@@ -10,16 +10,23 @@
 #include "../include/bernstein_estimator.h"
 
 // Function to calculate ECDF (Empirical Cumulative Distribution Function)
+
 std::pair<std::vector<double>, std::vector<double>> ecdf(const std::vector<double>& data) {
+    // Sort the data
     std::vector<double> sorted_data = data;
     std::sort(sorted_data.begin(), sorted_data.end());
 
-    std::vector<double> cdf(data.size());
-    std::iota(cdf.begin(), cdf.end(), 1);
-    for (auto& val : cdf) {
-        val /= data.size();
+    // Compute the ECDF values
+    std::vector<double> cdf(sorted_data.size() + 1);
+    cdf[0] = 0.0; // First element is 0
+    for (size_t i = 1; i < sorted_data.size(); ++i) {
+        cdf[i] = static_cast<double>(i) / sorted_data.size();
     }
-
+    cdf.back() = 1.0; // Last element is 1
+
+    // Include the first element in sorted_data to match the cdf size
+    sorted_data.insert(sorted_data.begin(), sorted_data.front());
+
     return {cdf, sorted_data};
 }
 

src/bernstein_probability.cpp

@@ -1,6 +1,18 @@
 #include "../include/bernstein_probability.h"
 #include <vector>
 #include <algorithm>
+#include <cblas.h>
+
+// Helper function to convert a 1D vector to a 2D vector
+std::vector<std::vector<double>> convertTo2D(const std::vector<double>& flatMatrix, size_t rows, size_t cols) {
+    std::vector<std::vector<double>> matrix(rows, std::vector<double>(cols));
+    for (size_t i = 0; i < rows; ++i) {
+        for (size_t j = 0; j < cols; ++j) {
+            matrix[i][j] = flatMatrix[i * cols + j];
+        }
+    }
+    return matrix;
+}
 
 std::vector<std::vector<double>> bernstein_probability(const std::vector<double>& x, 
                                                        const std::vector<double>& x_cdf, 
@@ -10,8 +22,7 @@ std::vector<std::vector<double>> bernstein_probability(const std::vector<double>
 
     for (size_t k = 0; k < n; ++k) {
         // Find the last index in x_cdf where x_cdf[index] <= x[k]
-        auto it = std::find_if(x_cdf.rbegin(), x_cdf.rend(), 
-                               [&](double val) { return val <= x[k]; });
+        auto it = std::find_if(x_cdf.rbegin(), x_cdf.rend(), [&](double val) { return val <= x[k]; });
 
         if (it == x_cdf.rend()) {
             prob[k] = P[0];
@@ -24,16 +35,14 @@ std::vector<std::vector<double>> bernstein_probability(const std::vector<double>
     // Assuming BeBOT class is defined and has methods `calculate()` and `getDifferentiationMatrix()`
     Bebot bebot(n-1, 1);
     bebot.calculate();
-    std::vector<std::vector<double>> Dm = bebot.getDifferentiationMatrix();
+    const auto& Dm = bebot.getDifferentiationMatrix();
 
+    // Output vector
     std::vector<double> pdf(n, 0.0);
-    for (size_t i = 0; i < n; ++i) {
-        for (size_t j = 0; j < n; ++j) {
-            pdf[i] += prob[j] * Dm[j][i];
-        }
-    }
+    cblas_dgemv(CblasColMajor, CblasTrans, n, n, 1.0, Dm.data(), n, prob.data(), 1, 0.0, pdf.data(), 1);
 
     // Assuming BernsteinPoly function is defined
-    std::vector<std::vector<double>> BP_dot = BernsteinPoly({pdf}, x, 0, 1);
+    std::vector<std::vector<double>> pdf_2d(1, pdf);
+    std::vector<std::vector<double>> BP_dot = BernsteinPoly(pdf_2d, x, 0, 1);
     return BP_dot;
 }