Added further documentation for generating-docs/compiling/testing and…

… fixed test
abicco · Mar 27, 2020 · 8f729bf · 8f729bf
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diff --git a/c++_implementation/README.md b/c++_implementation/README.md
@@ -1,3 +1,5 @@
 # Kalman Filter
 
+To generate doxygen run `doxygen` in this directory. Copy `png`s from `assets/` into `html/`.
+
 
diff --git a/c++_implementation/examples/README.md b/c++_implementation/examples/README.md
@@ -0,0 +1,3 @@
+##
+
+`cd` into this directory and `g++ <file>` such as `g++ basicExample.cpp` to compile.
diff --git a/c++_implementation/tests/README.md b/c++_implementation/tests/README.md
@@ -0,0 +1,18 @@
+## Tests
+To compile tests you need GTest. Run
+
+```
+$ mkdir build
+$ cd build
+$ cmake ..
+$ make
+$./runTests
+$./runTests2
+$./runTests3
+$./runTests4
+```
+
+ - `runTests` tests continuos solvers
+ - `runTests2` tests `predict` method of discrete Kalman filter and then the update phase method
+ - `runTests3` compare the output of discrete Kalman filter using three different types for template. Results should all be the same.
+ - `runTests4` tests 'randomVector' functions
diff --git a/c++_implementation/tests/test.txt b/c++_implementation/tests/test.txt
diff --git a/c++_implementation/tests/tests.cpp b/c++_implementation/tests/tests.cpp
@@ -47,9 +47,6 @@ TEST(continuousSolverRK4, RK4Test){
 	ASSERT_THROW(testModelSolver.solve(-1),std::out_of_range);
 }
 
-
-
-
 //CUSTOM VECTOR CLASS	
 class customVector{
 	private:
@@ -85,8 +82,6 @@ class customVector{
 			}
 			entries = std::vector<double>(size);
 		}
-
-
 };
 
 
@@ -186,7 +181,6 @@ TEST(continuousSolverRK4,differentLibraryTest){
 		ASSERT_NEAR(testModelSolver.getCurrentState().getValueAtIndex(1),tmp4,1e-9);
 	}
 	ASSERT_THROW(testModelSolver.solve(-1),std::out_of_range);
-
 }
 
 int main(int argc, char **argv){

diff --git a/c++_implementation/tests/tests2.cpp b/c++_implementation/tests/tests2.cpp
@@ -9,8 +9,6 @@
 #include <boost/numeric/ublas/vector.hpp>
 #include <boost/numeric/ublas/matrix.hpp>
 #include <boost/operators.hpp>
-
-
 #include <iostream>
 
 
@@ -89,24 +87,19 @@ TEST(discreteDiscreteKalmanFilter, test){
 		filter.predict(1);
 	}
 
-
-
 	for(int i = 0; i < 10; i++){
 		vectorDouble measurement(i);	
 
 		double sk = 1*filter.getCurrentCovariance().getSystemValue()*1 + 0.01;
 		double kk = filter.getCurrentCovariance().getSystemValue()*(1.0/sk);
 		double curEst = filter.getCurrentEstimate().getSystemValue(); 
 
-
 		filter.update(measurement);
 
-
 		ASSERT_NEAR(filter.getCurrentEstimate().getSystemValue(),curEst+kk*(double(i) - curEst),1e-9);
 		//ASSERT_NEAR(filter.getCurrentCovariance().getSystemValue(),1+0.01*i,1e-9);
 		//ASSERT_NEAR(filter.getCurrentTime(),i,1e-9);
 	}
-
 }
 
 int main(int argc, char **argv){

diff --git a/c++_implementation/tests/tests3.cpp b/c++_implementation/tests/tests3.cpp
@@ -7,16 +7,10 @@
 #include "../include/mathWrapper/boost.h"
 #include <boost/numeric/ublas/vector.hpp>
 #include <boost/numeric/ublas/matrix.hpp>
-
-
-
 #include <math.h>
 #include "../include/Eigen.h" 
-
-
 #include <iostream>
 
-
 TEST(discreteDiscreteKalmanFilter, test){
 
 	int stateCount = 1;
@@ -38,9 +32,6 @@ TEST(discreteDiscreteKalmanFilter, test){
 	Eigen::VectorXd initialEstimateEigenSimple(1);initialEstimateEigenSimple<<1;	
 	Eigen::MatrixXd initialCovarianceEigenSimple(1,1);initialCovarianceEigenSimple<<1;
 
-
-
-
 	class stateModel: public discreteModel<vectorDouble>{
 		public:
 			vectorDouble function(const vectorDouble & val, const int time) const override{

diff --git a/c++_implementation/tests/tests4.cpp b/c++_implementation/tests/tests4.cpp
@@ -3,11 +3,9 @@
 #include "../include/mathWrapper/boost.h"
 #include "../include/Eigen.h"
 #include "../include/mathWrapper/eigen.h"
-
 #include <boost/numeric/ublas/vector.hpp>
 #include <boost/numeric/ublas/matrix.hpp>
 
-
 #include <iostream>
 
 TEST(discreteDiscreteKalmanFilter, test){
@@ -27,16 +25,16 @@ TEST(discreteDiscreteKalmanFilter, test){
 	cholCov2(0,0)=1;cholCov2(0,1)=0.2;cholCov2(1,0)=0.0;cholCov2(1,1)=1.4;
 	matrixEigen cholCov3(cholCov);vectorEigen mean3(mean1);
 	for(int i = 0; i < totalCount; i++){
-		vectorDouble vdR = vectorDouble::randomVector(1);
+		vectorDouble vdR = vectorDouble::randomVector(1,i*i);
 		vdR_arr[i] = vdR*matrixDouble(0.1) + vectorDouble(5.0);
 
-		Eigen::VectorXd vesR = Eigen::VectorXd::randomVector(2); 
+		Eigen::VectorXd vesR = Eigen::VectorXd::randomVector(2,i*i); 
 		vesR_arr[i] = cholCov*vesR + mean1;
 
-		vectorBoost vbR = vectorBoost::randomVector(2);
+		vectorBoost vbR = vectorBoost::randomVector(2,i*i);
 		vbR_arr[i] = matrixBoost(cholCov2)*vbR + mean2;
 
-		vectorEigen veR = vectorEigen::randomVector(2);
+		vectorEigen veR = vectorEigen::randomVector(2,i*i);
 		veR_arr[i] = cholCov3*veR + mean3;
 	}
 
@@ -61,10 +59,6 @@ TEST(discreteDiscreteKalmanFilter, test){
 	}
 	vdCovariance = vdCovariance/totalCount;
 	ASSERT_NEAR(vdCovariance/0.01,1,0.01);
-
-
-
-
 }
 
 int main(int argc, char **argv){

diff --git a/matlab_implementation/README.md b/matlab_implementation/README.md
@@ -1 +1,3 @@
 # Matlab Kalman Filter
+
+To generate doxygen run `doxygen` in this directory. Copy  from all Kalman filter subdirectories `kalman_subdirectory/examples/*.png` into `Doc/html/assets/kalman_subdirectory/examples/*.png`.
Original file line number	Diff line number	Diff line change
		@@ -1,3 +1,5 @@
		# Kalman Filter

		To generate doxygen run `doxygen` in this directory. Copy `png`s from `assets/` into `html/`.
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,3 @@
		##

		`cd` into this directory and `g++ <file>` such as `g++ basicExample.cpp` to compile.
Original file line number	Diff line number	Diff line change
		@@ -1 +1,3 @@
		# Matlab Kalman Filter

		To generate doxygen run `doxygen` in this directory. Copy from all Kalman filter subdirectories `kalman_subdirectory/examples/.png` into `Doc/html/assets/kalman_subdirectory/examples/.png`.