CI: Show all compiler warnings and treat as error

include/amici/abstract_model.h

@@ -626,7 +626,7 @@ class AbstractModel {
     virtual void fdJydy(realtype *dJydy, int iy, const realtype *p,
                         const realtype *k, const realtype *y,
                         const realtype *sigmay, const realtype *my);
-                        
+
     /**
      * @brief Model-specific implementation of fdJydy colptrs
      * @param dJydy sparse matrix to which colptrs will be written
@@ -800,15 +800,15 @@ class AbstractModel {
      * @param dwdx sparse matrix to which rowvals will be written
      */
     virtual void fdwdx_rowvals(SUNMatrixWrapper &dwdx);
-    
+
     /**
      * @brief Model specific implementation of fdwdw, no w chainrule (Py)
      * @param dwdw partial derivative w wrt w
      * @param t timepoint
      * @param x Vector with the states
      * @param p parameter vector
      * @param k constants vector
-     * @param h heavyside vector
+     * @param h Heaviside vector
      * @param w vector with helper variables
      * @param tcl Total abundances for conservation laws
      */

include/amici/edata.h

@@ -174,7 +174,7 @@ class ExpData {
      * @brief set function that copies observed data for specific observable
      *
      * @param observedData observed data (dimension: nt)
-     * @param iy oberved data index
+     * @param iy observed data index
      */
     void setObservedData(const std::vector<realtype> &observedData, int iy);
 

include/amici/hdf5.h

@@ -243,7 +243,7 @@ void createAndWriteDouble3DDataset(H5::H5File const &file,
 /**
  * @brief Read scalar native double attribute from HDF5 object.
  * @param file HDF5 file
- * @param optionsObject Object to read attribute frin
+ * @param optionsObject Object to read attribute from
  * @param attributeName Name of attribute to read
  * @return Attribute value
  */

include/amici/model.h

@@ -210,7 +210,7 @@ class Model : public AbstractModel {
     using AbstractModel::fx0_fixedParameters;
     using AbstractModel::fy;
     using AbstractModel::fz;
-    
+
     /**
      * @brief Initialize model properties.
      * @param x Reference to state variables
@@ -597,7 +597,7 @@ class Model : public AbstractModel {
      * @return Observable IDs
      */
     virtual std::vector<std::string> getObservableIds() const;
-    
+
     /**
      * @brief Checks whether the defined noise model is gaussian, i.e., the nllh is quadratic
      * @return boolean flag
@@ -1298,13 +1298,13 @@ class Model : public AbstractModel {
 
     /** Flag indicating Matlab- or Python-based model generation */
     bool pythonGenerated;
-    
+
     /**
      * @brief getter for dxdotdp (matlab generated)
      * @return dxdotdp
      */
     const AmiVectorArray &get_dxdotdp() const;
-    
+
     /**
      * @brief getter for dxdotdp (python generated)
      * @return dxdotdp
@@ -1642,7 +1642,7 @@ class Model : public AbstractModel {
      * @param x Array with the states
      */
     void fdwdx(realtype t, const realtype *x);
-    
+
     /**
      * @brief Compute self derivative for recurring terms in xdot.
      * @param t Timepoint
@@ -1736,7 +1736,7 @@ class Model : public AbstractModel {
      * @return State vector with negative values replaced by `0` according to
      * stateIsNonNegative
      */
-    N_Vector computeX_pos(const_N_Vector x);
+    const_N_Vector computeX_pos(const_N_Vector x);
 
     /** All variables necessary for function evaluation */
     ModelState state_;
@@ -1752,13 +1752,13 @@ class Model : public AbstractModel {
 
     /** Sparse dwdx temporary storage (dimension: `ndwdx`) */
     mutable SUNMatrixWrapper dwdx_;
-    
+
     /** Sparse dwdp temporary storage (dimension: `ndwdp`) */
     mutable SUNMatrixWrapper dwdp_;
-    
+
     /** Dense Mass matrix (dimension: `nx_solver` x `nx_solver`) */
     mutable SUNMatrixWrapper M_;
-    
+
     /**
      * Temporary storage of `dxdotdp_full` data across functions (Python only)
      * (dimension: `nplist` x `nx_solver`, nnz: dynamic,
@@ -1780,7 +1780,7 @@ class Model : public AbstractModel {
      * type `CSC_MAT`)
      */
     mutable SUNMatrixWrapper dxdotdp_implicit;
-    
+
     /**
      * Temporary storage of `dxdotdx_explicit` data across functions (Python only)
      * (dimension: `nplist` x `nx_solver`, nnz: 'nxdotdotdx_explicit',
@@ -2005,10 +2005,10 @@ class Model : public AbstractModel {
 
     /** Sparse dwdw temporary storage (dimension: `ndwdw`) */
     mutable SUNMatrixWrapper dwdw_;
-    
+
     /** Sparse dwdx implicit temporary storage (dimension: `ndwdx`) */
     mutable std::vector<SUNMatrixWrapper> dwdx_hierarchical_;
-    
+
     /** Recursion */
     int w_recursion_depth_ {0};
 };

include/amici/model_dae.h

@@ -96,8 +96,8 @@ class Model_DAE : public Model {
      * @param xdot Vector with the right hand side
      * @param J Matrix to which the Jacobian will be written
      **/
-    void fJ(realtype t, realtype cj, N_Vector x, N_Vector dx, N_Vector xdot,
-            SUNMatrix J);
+    void fJ(realtype t, realtype cj, const_N_Vector x, const_N_Vector dx,
+            const_N_Vector xdot, SUNMatrix J);
 
     void fJB(const realtype t, realtype cj, const AmiVector &x,
              const AmiVector &dx, const AmiVector &xB, const AmiVector &dxB,
@@ -113,8 +113,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param JB Matrix to which the Jacobian will be written
      **/
-    void fJB(realtype t, realtype cj, N_Vector x, N_Vector dx, N_Vector xB,
-             N_Vector dxB, SUNMatrix JB);
+    void fJB(realtype t, realtype cj, const_N_Vector x, const_N_Vector dx,
+             const_N_Vector xB, const_N_Vector dxB, SUNMatrix JB);
 
     void fJSparse(realtype t, realtype cj, const AmiVector &x,
                   const AmiVector &dx, const AmiVector &xdot,
@@ -128,7 +128,7 @@ class Model_DAE : public Model {
      * @param dx Vector with the derivative states
      * @param J Matrix to which the Jacobian will be written
      */
-    void fJSparse(realtype t, realtype cj, N_Vector x, N_Vector dx,
+    void fJSparse(realtype t, realtype cj, const_N_Vector x, const_N_Vector dx,
                   SUNMatrix J);
 
     void fJSparseB(const realtype t, realtype cj, const AmiVector &x,
@@ -146,8 +146,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param JB Matrix to which the Jacobian will be written
      */
-    void fJSparseB(realtype t, realtype cj, N_Vector x, N_Vector dx,
-                   N_Vector xB, N_Vector dxB, SUNMatrix JB);
+    void fJSparseB(realtype t, realtype cj, const_N_Vector x, const_N_Vector dx,
+                   const_N_Vector xB, const_N_Vector dxB, SUNMatrix JB);
 
     /**
      * @brief Diagonal of the Jacobian (for preconditioning)
@@ -175,8 +175,8 @@ class Model_DAE : public Model {
      * @param Jv Vector to which the Jacobian vector product will be
      * written
      **/
-    void fJv(realtype t, N_Vector x, N_Vector dx, N_Vector v, N_Vector Jv,
-             realtype cj);
+    void fJv(realtype t, const_N_Vector x, const_N_Vector dx, const_N_Vector v,
+             N_Vector Jv, realtype cj);
 
     /**
      * @brief Matrix vector product of JB with a vector v (for iterative solvers)
@@ -186,13 +186,13 @@ class Model_DAE : public Model {
      * @param xB Vector with the adjoint states
      * @param dxB Vector with the adjoint derivative states
      * @param vB Vector with which the Jacobian is multiplied
-     * @param JvB Vector to which the Jacobian vector product will be
-     *written
+     * @param JvB Vector to which the Jacobian vector product will be written
      * @param cj scalar in Jacobian (inverse stepsize)
      **/
 
-    void fJvB(realtype t, N_Vector x, N_Vector dx, N_Vector xB, N_Vector dxB,
-              N_Vector vB, N_Vector JvB, realtype cj);
+    void fJvB(realtype t, const_N_Vector x, const_N_Vector dx,
+              const_N_Vector xB, const_N_Vector dxB,
+              const_N_Vector vB, N_Vector JvB, realtype cj);
 
     void froot(realtype t, const AmiVector &x, const AmiVector &dx,
                gsl::span<realtype> root) override;
@@ -204,7 +204,7 @@ class Model_DAE : public Model {
      * @param dx Vector with the derivative states
      * @param root array with root function values
      */
-    void froot(realtype t, N_Vector x, N_Vector dx, gsl::span<realtype> root);
+    void froot(realtype t, const_N_Vector x, const_N_Vector dx, gsl::span<realtype> root);
 
     void fxdot(realtype t, const AmiVector &x, const AmiVector &dx,
                AmiVector &xdot) override;
@@ -216,7 +216,7 @@ class Model_DAE : public Model {
      * @param dx Vector with the derivative states
      * @param xdot Vector with the right hand side
      */
-    void fxdot(realtype t, N_Vector x, N_Vector dx, N_Vector xdot);
+    void fxdot(realtype t, const_N_Vector x, const_N_Vector dx, N_Vector xdot);
 
     /**
      * @brief Right hand side of differential equation for adjoint state xB
@@ -227,8 +227,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param xBdot Vector with the adjoint right hand side
      */
-    void fxBdot(realtype t, N_Vector x, N_Vector dx, N_Vector xB, N_Vector dxB,
-                N_Vector xBdot);
+    void fxBdot(realtype t, const_N_Vector x, const_N_Vector dx,
+                const_N_Vector xB, const_N_Vector dxB, N_Vector xBdot);
 
     /**
      * @brief Right hand side of integral equation for quadrature states qB
@@ -239,7 +239,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param qBdot Vector with the adjoint quadrature right hand side
      */
-    void fqBdot(realtype t, N_Vector x, N_Vector dx, N_Vector xB, N_Vector dxB,
+    void fqBdot(realtype t, const_N_Vector x, const_N_Vector dx,
+                const_N_Vector xB, const_N_Vector dxB,
                 N_Vector qBdot);
 
     void fxBdot_ss(const realtype t, const AmiVector &xB,
@@ -252,7 +253,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param xBdot Vector with the adjoint right hand side
      */
-    void fxBdot_ss(realtype t, N_Vector xB, N_Vector dxB, N_Vector xBdot) const;
+    void fxBdot_ss(realtype t, const_N_Vector xB, const_N_Vector dxB,
+                   N_Vector xBdot) const;
 
     /**
      * @brief Implementation of fqBdot for steady state at the N_Vector level
@@ -261,7 +263,8 @@ class Model_DAE : public Model {
      * @param dxB Vector with the adjoint derivative states
      * @param qBdot Vector with the adjoint quadrature right hand side
      */
-    void fqBdot_ss(realtype t, N_Vector xB, N_Vector dxB, N_Vector qBdot) const;
+    void fqBdot_ss(realtype t, const_N_Vector xB, const_N_Vector dxB,
+                   N_Vector qBdot) const;
 
     /**
      * @brief Sparse Jacobian function backward, steady state case
@@ -291,7 +294,7 @@ class Model_DAE : public Model {
      * @param x Vector with the states
      * @param dx Vector with the derivative states
      */
-    void fdxdotdp(realtype t, const N_Vector x, const N_Vector dx);
+    void fdxdotdp(realtype t, const const_N_Vector x, const const_N_Vector dx);
     void fdxdotdp(const realtype t, const AmiVector &x,
                   const AmiVector &dx) override {
         fdxdotdp(t, x.getNVector(), dx.getNVector());
@@ -310,15 +313,15 @@ class Model_DAE : public Model {
      * @param sdx Vector with the derivative state sensitivities
      * @param sxdot Vector with the sensitivity right hand side
      */
-    void fsxdot(realtype t, N_Vector x, N_Vector dx, int ip, N_Vector sx,
-                N_Vector sdx, N_Vector sxdot);
+    void fsxdot(realtype t, const_N_Vector x, const_N_Vector dx, int ip,
+                const_N_Vector sx, const_N_Vector sdx, N_Vector sxdot);
 
     /**
      * @brief Mass matrix for DAE systems
      * @param t timepoint
      * @param x Vector with the states
      */
-    void fM(realtype t, const N_Vector x);
+    void fM(realtype t, const_N_Vector x);
 
     std::unique_ptr<Solver> getSolver() override;