I found the following lines in the scikit-learn package:
if is_sparse:
problem = csr_set_problem(
(<np.ndarray[np.float64_t, ndim=1, mode='c']>X.data).data,
(<np.ndarray[np.int32_t, ndim=1, mode='c']>X.indices).shape,
(<np.ndarray[np.int32_t, ndim=1, mode='c']>X.indices).data,
(<np.ndarray[np.int32_t, ndim=1, mode='c']>X.indptr).shape,
(<np.ndarray[np.int32_t, ndim=1, mode='c']>X.indptr).data,
Y.data, (<np.int32_t>X.shape[1]), bias,
sample_weight.data)
else:
...
All my searches for "angle brackets in Python" give answers about documentation or decorator syntax, which I am pretty sure this is neither because it looks like actual logic.
What do the angle brackets in the above Python code do and where can I learn more about them?