Continuum Analytics: Documentation

# Utilities

## Dealing with pointers

These functions can be called from pure Python as well as in nopython mode.

`numba.``carray`(ptr, shape, dtype=None)

  Return a Numpy array view over the data pointed to by ptr with the given shape, in C order. If dtype is given, it is used as the array’s dtype, otherwise the array’s dtype is inferred from ptr‘s type. As the returned array is a view, not a copy, writing to it will modify the original data.

  ptr should be a ctypes pointer object (either a typed pointer as created using `POINTER()`, or a `c_void_p`).

  shape should be an integer or a tuple of integers.

  dtype should be a Numpy dtype or scalar class (i.e. both `np.dtype('int8')` and `np.int8` are accepted).

`numba.``farray`(ptr, shape, dtype=None)

  Same as `carray()`, but the data is assumed to be laid out in Fortran order, and the array view is constructed accordingly.