perturbation_fold.h File Reference
Find a vector of perturbation energies that minimizes the discripancies between predicted and observed pairing probabilities and the amount of neccessary adjustments. More...
Include dependency graph for perturbation_fold.h:Go to the source code of this file.
Macros | |
| #define | VRNA_OBJECTIVE_FUNCTION_QUADRATIC 0 |
| Use the sum of squared aberrations as objective function. More... | |
| #define | VRNA_OBJECTIVE_FUNCTION_ABSOLUTE 1 |
| Use the sum of absolute aberrations as objective function. More... | |
| #define | VRNA_MINIMIZER_DEFAULT 0 |
| Use a custom implementation of the gradient descent algorithm to minimize the objective function. | |
| #define | VRNA_MINIMIZER_CONJUGATE_FR 1 |
| Use the GNU Scientific Library implementation of the Fletcher-Reeves conjugate gradient algorithm to minimize the objective function. More... | |
| #define | VRNA_MINIMIZER_CONJUGATE_PR 2 |
| Use the GNU Scientific Library implementation of the Polak-Ribiere conjugate gradient algorithm to minimize the objective function. More... | |
| #define | VRNA_MINIMIZER_VECTOR_BFGS 3 |
| Use the GNU Scientific Library implementation of the vector Broyden-Fletcher-Goldfarb-Shanno algorithm to minimize the objective function. More... | |
| #define | VRNA_MINIMIZER_VECTOR_BFGS2 4 |
| Use the GNU Scientific Library implementation of the vector Broyden-Fletcher-Goldfarb-Shanno algorithm to minimize the objective function. More... | |
| #define | VRNA_MINIMIZER_STEEPEST_DESCENT 5 |
| Use the GNU Scientific Library implementation of the steepest descent algorithm to minimize the objective function. More... | |
Typedefs | |
| typedef void(* | progress_callback) (int iteration, double score, double *epsilon) |
| Callback for following the progress of the minimization process. More... | |
Functions | |
| void | vrna_sc_minimize_pertubation (vrna_fold_compound_t *vc, const double *q_prob_unpaired, int objective_function, double sigma_squared, double tau_squared, int algorithm, int sample_size, double *epsilon, double initialStepSize, double minStepSize, double minImprovement, double minimizerTolerance, progress_callback callback) |
| Find a vector of perturbation energies that minimizes the discripancies between predicted and observed pairing probabilities and the amount of neccessary adjustments. More... | |
Detailed Description
Find a vector of perturbation energies that minimizes the discripancies between predicted and observed pairing probabilities and the amount of neccessary adjustments.
