### Navigation

- index
- modules |
- next |
- previous |
- NumPy v1.3 Manual (DRAFT) »
- NumPy Reference »
- Routines »
- Functional programming »

# numpy.vectorize

class `numpy.``vectorize`(pyfunc, otypes='', doc=None)

  Generalized function class.

  Define a vectorized function which takes nested sequence of objects or numpy arrays as inputs and returns a numpy array as output, evaluating the function over successive tuples of the input arrays like the python map function except it uses the broadcasting rules of numpy.

  Data-type of output of vectorized is determined by calling the function with the first element of the input. This can be avoided by specifying the otypes argument as either a string of typecode characters or a list of data-types specifiers. There should be one data-type specifier for each output.

  Parameters: | f : callable A Python function or method.

  Examples

      >>> def myfunc(a, b):
      ...    if a > b:
      ...        return a-b
      ...    else:
      ...        return a+b

      >>> vfunc = np.vectorize(myfunc)

      >>> vfunc([1, 2, 3, 4], 2)
      array([3, 4, 1, 2])

### Navigation

- index
- modules |
- next |
- previous |
- NumPy v1.3 Manual (DRAFT) »
- NumPy Reference »
- Routines »
- Functional programming »