dweindl

def ensure_amici_compatible():
    minimum_amici_version = (0, 8, 4)
    current_amici_version = \
        tuple([int(x) for x in amici.__version__.split('.')])
    if current_amici_version < minimum_amici_version:
        raise RuntimeError(f'Must use AMICI version {minimum_amici_version}'
                           ' or newer')

dweindl

def globalize_parameters(sbml_model):
    """Turn all local parameters into global parameters"""
    for reaction in sbml_model.getListOfReactions():
        law = reaction.getKineticLaw()
        # copy first so we can delete in the following loop
        local_parameters = [local_parameter for local_parameter
                            in law.getListOfParameters()]
        for lp in local_parameters:
            # Create global parameter assuming names are globalized already
            p = sbml_model.createParameter()

dweindl

typedef int (*objectiveFunction)(const double *, double *);
typedef int (*objectiveFunctionGradient)(const double *, double *);

int checkGradient(objectiveFunction objFun, objectiveFunctionGradient objFunGrad, int nParams, double *theta, double epsilon, int *indices, int nIndices);


int checkGradient(objectiveFunction objFun, objectiveFunctionGradient objFunGrad, int nParams, double *theta, double epsilon, int *indices, int nIndices) {
    double gradient[nParams];
    objFunGrad(theta, gradient);

dweindl

void getLatinHyperCubeSamples(int numParameters, int numSamples, double *sample);

int doubleSort(const void *x, const void *y);

void rank(const double *in, double *out, int length);


void getLatinHyperCubeSamples(int numParameters, int numSamples, double *sample) {
    for(int i = 0; i < numParameters; ++i) {
        double tmpSample[numSamples];

dweindl

#include "ceres/ceres.h"

class X2 : public ceres::FirstOrderFunction {
 public:
  virtual ~X2() {}

  virtual bool Evaluate(const double* parameters,
                        double* cost,
                        double* gradient) const {