parallel_model can be compiled

Battery-Intelligence-Lab · Aug 1, 2024 · a4651f9 · a4651f9
1 parent 6275765
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diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt
@@ -1 +1,2 @@
-add_subdirectory(unit)
+add_subdirectory(unit)
+add_subdirectory(integration)
diff --git a/tests/integration/CMakeLists.txt b/tests/integration/CMakeLists.txt
@@ -0,0 +1,12 @@
+cmake_minimum_required(VERSION 3.21)
+
+add_executable(parallel_model
+  parallel_model_sln.cpp
+)
+
+target_link_libraries(parallel_model
+  PRIVATE
+  src
+  project_warnings
+  project_options
+)
diff --git a/tests/integration/parallel_model_sln.cpp b/tests/integration/parallel_model_sln.cpp
@@ -1,3 +1,13 @@
+/*
+ * parallel_model_sln.cpp
+ *
+ * Example for integration test of the analytical parallel model solution.
+ *
+ * Created on: 01 Aug 2024
+ * Author(s): Nilsu Atlan, Volkan Kumtepeli
+ */
+
+
 #include <iostream>
 #include <Eigen/Dense>
 #include <random>
@@ -12,96 +22,105 @@
 using namespace std; // bu yerine fonksiyonun içine ekle
 using namespace Eigen;
 
-double ocv_eval(const vector<double>& ocv_coefs, double z) {
-    double ocv = 0.0;
-    for (size_t i = 0; i < ocv_coefs.size(); ++i) {
-        ocv += ocv_coefs[i] * pow(z, ocv_coefs.size() - 1 - i);
-    }
-    return ocv;
+double ocv_eval(const vector<double> &ocv_coefs, double z)
+{
+  double ocv = 0.0;
+  for (size_t i = 0; i < ocv_coefs.size(); ++i) {
+    ocv += ocv_coefs[i] * pow(z, ocv_coefs.size() - 1 - i);
+  }
+  return ocv;
 } // already existing function --> otomatik olarak değer fonksiyona gelecek
 
-void new_compute_A11_A12_A21_A22(int n_par, VectorXd R, VectorXd C, VectorXd Q, VectorXd tau, VectorXd r, MatrixXd &A11, MatrixXd &A12, MatrixXd &A21, MatrixXd &A22, MatrixXd &m) {
-    // Initialize A11 and A12
-    A11 = MatrixXd::Zero(2 * n_par, 2 * n_par);
-    A12 = MatrixXd::Zero(2 * n_par, 2 * n_par);
-
-    A11.block(0, 0, 2, 2) << 0, 0, 0, -tau(0);
-    A12.block(0, 0, 2, 2) << 1/Q(0), 0, 0, 1/C(0);
-
-    for (int i = 1; i < n_par; ++i) {
-        A11.block(2 * i, 2 * i, 2, 2) << 0, 0, 0, -tau(i);
-        A12.block(2 * i, 2 * i, 2, 2) << 1/Q(i), 0, 0, 1/C(i);
-    }
+void new_compute_A11_A12_A21_A22(int n_par, VectorXd R, VectorXd C, VectorXd Q, VectorXd tau, VectorXd r, MatrixXd &A11, MatrixXd &A12, MatrixXd &A21, MatrixXd &A22, MatrixXd &m)
+{
+  // Initialize A11 and A12
+  A11 = MatrixXd::Zero(2 * n_par, 2 * n_par);
+  A12 = MatrixXd::Zero(2 * n_par, 2 * n_par);
 
-    // Initialize A22
-    A22 = MatrixXd::Zero(n_par, n_par);
-    VectorXd main_diag = -(r + R);
-    main_diag(0) = r(0);
+  A11.block(0, 0, 2, 2) << 0, 0, 0, -tau(0);
+  A12.block(0, 0, 2, 2) << 1 / Q(0), 0, 0, 1 / C(0);
 
-    VectorXd lower_diag = r.head(n_par - 1);
-    lower_diag(0) = r(0);
+  for (int i = 1; i < n_par; ++i) {
+    A11.block(2 * i, 2 * i, 2, 2) << 0, 0, 0, -tau(i);
+    A12.block(2 * i, 2 * i, 2, 2) << 1 / Q(i), 0, 0, 1 / C(i);
+  }
 
-    A22.diagonal() = main_diag;
-    A22.diagonal(-1) = lower_diag;
+  // Initialize A22
+  A22 = MatrixXd::Zero(n_par, n_par);
+  VectorXd main_diag = -(r + R);
+  main_diag(0) = r(0);
 
-    for (int i = 1; i < n_par; ++i) {
-        for (int j = i + 1; j < n_par; ++j) {
-            A22(i, j) = -R(i);
-        }
-    }
-
-    A22.row(0).setOnes();
-    cout << "A22:\n" << A22 << endl;
+  VectorXd lower_diag = r.head(n_par - 1);
+  lower_diag(0) = r(0);
 
-    // Initialize A21
-    A21 = MatrixXd::Zero((n_par - 1) * 2, n_par);
-    for (int i = 0; i < n_par - 1; ++i) {
-        A21.block(2 * i, 0, 2, n_par) = MatrixXd::Identity(2, n_par);
-    }
+  A22.diagonal() = main_diag;
+  A22.diagonal(-1) = lower_diag;
 
-    // Calculate m (inverse of A22)
-    m = MatrixXd::Zero(n_par, n_par);
-    double Rsum_inv = 1 / R.sum();
-
-    for (int ktil = 0; ktil < n_par; ++ktil) {
-        for (int i = 0; i < n_par - 1; ++i) {
-            if (ktil - i - 1 == 0) {
-                m(i + 1, i) = pow(1 / R(i + 1), 2) * Rsum_inv - 1 / R(i + 1);
-            } else {
-                m(ktil, i) = 1 / (R(ktil) * R(i + 1)) * Rsum_inv;
-            }
-        }
+  for (int i = 1; i < n_par; ++i) {
+    for (int j = i + 1; j < n_par; ++j) {
+      A22(i, j) = -R(i);
     }
+  }
 
-    m(n_par - 1, n_par - 1) = 1 / (R(n_par - 1) * Rsum_inv);
-    for (int i = 0; i < n_par - 1; ++i) {
-        m(i, n_par - 1) = 1 / (R(i) * Rsum_inv);
-    }
+  A22.row(0).setOnes();
+  cout << "A22:\n"
+       << A22 << endl;
 
-    MatrixXd inv_A22 = A22.inverse();
-    double error = (inv_A22 - m).norm();
+  // Initialize A21
+  A21 = MatrixXd::Zero((n_par - 1) * 2, n_par);
+  for (int i = 0; i < n_par - 1; ++i) {
+    A21.block(2 * i, 0, 2, n_par) = MatrixXd::Identity(2, n_par);
+  }
 
-    cout << "Error: " << error << endl;
-}
+  // Calculate m (inverse of A22)
+  m = MatrixXd::Zero(n_par, n_par);
+  double Rsum_inv = 1 / R.sum();
 
-int main() {
-    int n_par = 3;
-    VectorXd R(n_par), C(n_par), Q(n_par), tau(n_par), r(n_par);
+  for (int ktil = 0; ktil < n_par; ++ktil) {
+    for (int i = 0; i < n_par - 1; ++i) {
+      if (ktil - i - 1 == 0) {
+        m(i + 1, i) = pow(1 / R(i + 1), 2) * Rsum_inv - 1 / R(i + 1);
+      } else {
+        m(ktil, i) = 1 / (R(ktil) * R(i + 1)) * Rsum_inv;
+      }
+    }
+  }
 
-    R << 0, 0, 0;
-    C << 634.0, 634.0, 634.0;
-    Q << 9000.0, 9000.0, 9000.0;
-    tau << 0.04, 0.04, 0.04;
-    r << 0.029, 0.029, 0.029;
+  m(n_par - 1, n_par - 1) = 1 / (R(n_par - 1) * Rsum_inv);
+  for (int i = 0; i < n_par - 1; ++i) {
+    m(i, n_par - 1) = 1 / (R(i) * Rsum_inv);
+  }
 
-    MatrixXd A11, A12, A21, A22, m;
-    new_compute_A11_A12_A21_A22(n_par, R, C, Q, tau, r, A11, A12, A21, A22, m);
+  MatrixXd inv_A22 = A22.inverse();
+  double error = (inv_A22 - m).norm();
 
-    cout << "A11:\n" << A11 << endl;
-    cout << "A12:\n" << A12 << endl;
-    cout << "A21:\n" << A21 << endl;
-    cout << "A22:\n" << A22 << endl;
-    cout << "m:\n" << m << endl;
+  cout << "Error: " << error << endl;
+}
 
-    return 0;
+int main()
+{
+  int n_par = 3;
+  VectorXd R(n_par), C(n_par), Q(n_par), tau(n_par), r(n_par);
+
+  R << 0, 0, 0;
+  C << 634.0, 634.0, 634.0;
+  Q << 9000.0, 9000.0, 9000.0;
+  tau << 0.04, 0.04, 0.04;
+  r << 0.029, 0.029, 0.029;
+
+  MatrixXd A11, A12, A21, A22, m;
+  new_compute_A11_A12_A21_A22(n_par, R, C, Q, tau, r, A11, A12, A21, A22, m);
+
+  cout << "A11:\n"
+       << A11 << endl;
+  cout << "A12:\n"
+       << A12 << endl;
+  cout << "A21:\n"
+       << A21 << endl;
+  cout << "A22:\n"
+       << A22 << endl;
+  cout << "m:\n"
+       << m << endl;
+
+  return 0;
 }