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| author | Gertjan van den Burg <burg@ese.eur.nl> | 2016-10-06 17:08:57 +0200 |
|---|---|---|
| committer | Gertjan van den Burg <burg@ese.eur.nl> | 2016-10-06 17:08:57 +0200 |
| commit | 5c58431646f05637d801c671a5f55a11903b37a5 (patch) | |
| tree | c4c7f6b2d5b3f9234db580b7d56d8a391d137594 /src/gensvm_kernel.c | |
| parent | Switch to using dsyrk instead of dsyr for speed. (diff) | |
| download | gensvm-5c58431646f05637d801c671a5f55a11903b37a5.tar.gz gensvm-5c58431646f05637d801c671a5f55a11903b37a5.zip | |
Coding style - set all pointers to NULL initially and after free
Diffstat (limited to 'src/gensvm_kernel.c')
| -rw-r--r-- | src/gensvm_kernel.c | 19 |
1 files changed, 14 insertions, 5 deletions
diff --git a/src/gensvm_kernel.c b/src/gensvm_kernel.c index 7ca58da..97328d2 100644 --- a/src/gensvm_kernel.c +++ b/src/gensvm_kernel.c @@ -46,13 +46,18 @@ void gensvm_kernel_preprocess(struct GenModel *model, struct GenData *data) gensvm_make_trainfactor(data, P, Sigma, r); // Set Sigma to data->Sigma (need it again for prediction) - if (data->Sigma != NULL) + if (data->Sigma != NULL) { free(data->Sigma); + data->Sigma = NULL; + } data->Sigma = Sigma; // write kernel params to data data->kerneltype = model->kerneltype; + free(data->kernelparam); + data->kernelparam = NULL; + switch (model->kerneltype) { case K_LINEAR: break; @@ -99,7 +104,8 @@ void gensvm_make_kernel(struct GenModel *model, struct GenData *data, long i, j; long n = data->n; double value; - double *x1, *x2; + double *x1 = NULL, + *x2 = NULL; for (i=0; i<n; i++) { for (j=i; j<n; j++) { @@ -134,9 +140,11 @@ void gensvm_make_kernel(struct GenModel *model, struct GenData *data, */ long gensvm_make_eigen(double *K, long n, double **P, double **Sigma) { - int M, status, LWORK, *IWORK, *IFAIL; + int M, status, LWORK, + *IWORK = NULL, + *IFAIL = NULL; long i, j, num_eigen, cutoff_idx; - double max_eigen, abstol, *WORK; + double max_eigen, abstol, *WORK = NULL; double *tempSigma = Malloc(double, n); double *tempP = Malloc(double, n*n); @@ -210,7 +218,8 @@ void gensvm_make_crosskernel(struct GenModel *model, long n_test = data_test->n; long m = data_test->m; double value; - double *x1, *x2; + double *x1 = NULL, + *x2 = NULL; *K2 = Calloc(double, n_test*n_train); |