diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/function_base.py | 65 | ||||
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 55 |
2 files changed, 11 insertions, 109 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 5e1309dfd..f0f374f97 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -2117,10 +2117,10 @@ def _create_arrays(broadcast_shape, dim_sizes, list_of_core_dims, dtypes, @set_module('numpy') class vectorize: """ - vectorize(pyfunc=np._NoValue, otypes=None, doc=None, excluded=None, - cache=False, signature=None) + vectorize(pyfunc, otypes=None, doc=None, excluded=None, cache=False, + signature=None) - Returns an object that acts like pyfunc, but takes arrays as input. + Generalized function class. Define a vectorized function which takes a nested sequence of objects or numpy arrays as inputs and returns a single numpy array or a tuple of numpy @@ -2134,9 +2134,8 @@ class vectorize: Parameters ---------- - pyfunc : callable, optional + pyfunc : callable A python function or method. - Can be omitted to produce a decorator with keyword arguments. otypes : str or list of dtypes, optional The output data type. It must be specified as either a string of typecode characters or a list of data type specifiers. There should @@ -2168,9 +2167,8 @@ class vectorize: Returns ------- - out : callable - A vectorized function if ``pyfunc`` was provided, - a decorator otherwise. + vectorized : callable + Vectorized function. See Also -------- @@ -2267,44 +2265,18 @@ class vectorize: [0., 0., 1., 2., 1., 0.], [0., 0., 0., 1., 2., 1.]]) - Decorator syntax is supported. The decorator can be called as - a function to provide keyword arguments. - >>>@np.vectorize - ...def identity(x): - ... return x - ... - >>>identity([0, 1, 2]) - array([0, 1, 2]) - >>>@np.vectorize(otypes=[float]) - ...def as_float(x): - ... return x - ... - >>>as_float([0, 1, 2]) - array([0., 1., 2.]) """ - def __init__(self, pyfunc=np._NoValue, otypes=None, doc=None, - excluded=None, cache=False, signature=None): - - if (pyfunc != np._NoValue) and (not callable(pyfunc)): - #Splitting the error message to keep - #the length below 79 characters. - part1 = "When used as a decorator, " - part2 = "only accepts keyword arguments." - raise TypeError(part1 + part2) - + def __init__(self, pyfunc, otypes=None, doc=None, excluded=None, + cache=False, signature=None): self.pyfunc = pyfunc self.cache = cache self.signature = signature - if pyfunc != np._NoValue: - self.__name__ = pyfunc.__name__ - self._ufunc = {} # Caching to improve default performance - self._doc = None - self.__doc__ = doc + if doc is None: self.__doc__ = pyfunc.__doc__ else: - self._doc = doc + self.__doc__ = doc if isinstance(otypes, str): for char in otypes: @@ -2326,15 +2298,7 @@ class vectorize: else: self._in_and_out_core_dims = None - def _init_stage_2(self, pyfunc, *args, **kwargs): - self.__name__ = pyfunc.__name__ - self.pyfunc = pyfunc - if self._doc is None: - self.__doc__ = pyfunc.__doc__ - else: - self.__doc__ = self._doc - - def _call_as_normal(self, *args, **kwargs): + def __call__(self, *args, **kwargs): """ Return arrays with the results of `pyfunc` broadcast (vectorized) over `args` and `kwargs` not in `excluded`. @@ -2364,13 +2328,6 @@ class vectorize: return self._vectorize_call(func=func, args=vargs) - def __call__(self, *args, **kwargs): - if self.pyfunc is np._NoValue: - self._init_stage_2(*args, **kwargs) - return self - - return self._call_as_normal(*args, **kwargs) - def _get_ufunc_and_otypes(self, func, args): """Return (ufunc, otypes).""" # frompyfunc will fail if args is empty diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 97ca13bfb..3ec46735c 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -1787,61 +1787,6 @@ class TestVectorize: assert_equal(type(r), subclass) assert_equal(r, m * v) - def test_name(self): - #See gh-23021 - @np.vectorize - def f2(a, b): - return a + b - - assert f2.__name__ == 'f2' - - def test_decorator(self): - @vectorize - def addsubtract(a, b): - if a > b: - return a - b - else: - return a + b - - r = addsubtract([0, 3, 6, 9], [1, 3, 5, 7]) - assert_array_equal(r, [1, 6, 1, 2]) - - def test_docstring(self): - @vectorize - def f(x): - """Docstring""" - return x - - assert f.__doc__ == "Docstring" - - def test_signature_otypes_decorator(self): - @vectorize(signature='(n)->(n)', otypes=['float64']) - def f(x): - return x - - r = f([1, 2, 3]) - assert_equal(r.dtype, np.dtype('float64')) - assert_array_equal(r, [1, 2, 3]) - assert f.__name__ == 'f' - - def test_bad_input(self): - with assert_raises(TypeError): - A = np.vectorize(pyfunc = 3) - - def test_no_keywords(self): - with assert_raises(TypeError): - @np.vectorize("string") - def foo(): - return "bar" - - def test_positional_regression_9477(self): - # This supplies the first keyword argument as a positional, - # to ensure that they are still properly forwarded after the - # enhancement for #9477 - f = vectorize((lambda x: x), ['float64']) - r = f([2]) - assert_equal(r.dtype, np.dtype('float64')) - class TestLeaks: class A: |