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| author | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2019-12-04 12:30:51 +0000 |
|---|---|---|
| committer | Gertjan van den Burg <gertjanvandenburg@gmail.com> | 2019-12-04 12:30:51 +0000 |
| commit | 8a3846d155f90acf850a0de2f02202a6064e0e81 (patch) | |
| tree | a4b426a762567495803f0dac7aee8be4591c3fa5 /gensvm | |
| parent | Remove 'with nogil' everywhere (diff) | |
| download | pygensvm-8a3846d155f90acf850a0de2f02202a6064e0e81.tar.gz pygensvm-8a3846d155f90acf850a0de2f02202a6064e0e81.zip | |
Use np.int_, since we expect longs
Diffstat (limited to 'gensvm')
| -rw-r--r-- | gensvm/cython_wrapper/wrapper.pyx | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/gensvm/cython_wrapper/wrapper.pyx b/gensvm/cython_wrapper/wrapper.pyx index 3d7b87d..cdc54f2 100644 --- a/gensvm/cython_wrapper/wrapper.pyx +++ b/gensvm/cython_wrapper/wrapper.pyx @@ -133,7 +133,7 @@ def predict_wrap( # output vector cdef np.ndarray[np.int_t, ndim=1, mode='c'] predictions - predictions = np.empty((n_test_obs, ), dtype=np.int) + predictions = np.empty((n_test_obs, ), dtype=np.int_) # do the prediction gensvm_predict(X.data, V.data, n_test_obs, n_var, n_class, @@ -259,7 +259,7 @@ def grid_wrap( results['params'].append(candidate_params[ID]) results['scores'].append(get_task_performance(tasks[ID])) if store_predictions: - pred = np.zeros((n_obs, ), dtype=np.int) + pred = np.zeros((n_obs, ), dtype=np.int_) copy_task_predictions(tasks[ID], pred.data, n_obs) results['predictions'].append(pred.copy()) dur = np.zeros((n_folds, ), dtype=np.double) |