diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 52 |
1 files changed, 30 insertions, 22 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 783d45c2f..fdbe698d6 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -88,8 +88,11 @@ def rot90(m, k=1, axes=(0, 1)): Notes ----- - rot90(m, k=1, axes=(1,0)) is the reverse of rot90(m, k=1, axes=(0,1)) - rot90(m, k=1, axes=(1,0)) is equivalent to rot90(m, k=-1, axes=(0,1)) + ``rot90(m, k=1, axes=(1,0))`` is the reverse of + ``rot90(m, k=1, axes=(0,1))`` + + ``rot90(m, k=1, axes=(1,0))`` is equivalent to + ``rot90(m, k=-1, axes=(0,1))`` Examples -------- @@ -1519,7 +1522,7 @@ def unwrap(p, discont=None, axis=-1, *, period=2*pi): p : array_like Input array. discont : float, optional - Maximum discontinuity between values, default is ``period/2``. + Maximum discontinuity between values, default is ``period/2``. Values below ``period/2`` are treated as if they were ``period/2``. To have an effect different from the default, `discont` should be larger than ``period/2``. @@ -1528,7 +1531,7 @@ def unwrap(p, discont=None, axis=-1, *, period=2*pi): period: float, optional Size of the range over which the input wraps. By default, it is ``2 pi``. - + .. versionadded:: 1.21.0 Returns @@ -1542,8 +1545,8 @@ def unwrap(p, discont=None, axis=-1, *, period=2*pi): Notes ----- - If the discontinuity in `p` is smaller than ``period/2``, - but larger than `discont`, no unwrapping is done because taking + If the discontinuity in `p` is smaller than ``period/2``, + but larger than `discont`, no unwrapping is done because taking the complement would only make the discontinuity larger. Examples @@ -1576,7 +1579,7 @@ def unwrap(p, discont=None, axis=-1, *, period=2*pi): slice1 = tuple(slice1) dtype = np.result_type(dd, period) if _nx.issubdtype(dtype, _nx.integer): - interval_high, rem = divmod(period, 2) + interval_high, rem = divmod(period, 2) boundary_ambiguous = rem == 0 else: interval_high = period / 2 @@ -1940,11 +1943,19 @@ def _calculate_shapes(broadcast_shape, dim_sizes, list_of_core_dims): for core_dims in list_of_core_dims] -def _create_arrays(broadcast_shape, dim_sizes, list_of_core_dims, dtypes): +def _create_arrays(broadcast_shape, dim_sizes, list_of_core_dims, dtypes, + results=None): """Helper for creating output arrays in vectorize.""" shapes = _calculate_shapes(broadcast_shape, dim_sizes, list_of_core_dims) - arrays = tuple(np.empty(shape, dtype=dtype) - for shape, dtype in zip(shapes, dtypes)) + if dtypes is None: + dtypes = [None] * len(shapes) + if results is None: + arrays = tuple(np.empty(shape=shape, dtype=dtype) + for shape, dtype in zip(shapes, dtypes)) + else: + arrays = tuple(np.empty_like(result, shape=shape, dtype=dtype) + for result, shape, dtype + in zip(results, shapes, dtypes)) return arrays @@ -2290,11 +2301,8 @@ class vectorize: for result, core_dims in zip(results, output_core_dims): _update_dim_sizes(dim_sizes, result, core_dims) - if otypes is None: - otypes = [asarray(result).dtype for result in results] - outputs = _create_arrays(broadcast_shape, dim_sizes, - output_core_dims, otypes) + output_core_dims, otypes, results) for output, result in zip(outputs, results): output[index] = result @@ -4133,13 +4141,13 @@ def trapz(y, x=None, dx=1.0, axis=-1): If `x` is provided, the integration happens in sequence along its elements - they are not sorted. - + Integrate `y` (`x`) along each 1d slice on the given axis, compute :math:`\int y(x) dx`. When `x` is specified, this integrates along the parametric curve, computing :math:`\int_t y(t) dt = \int_t y(t) \left.\frac{dx}{dt}\right|_{x=x(t)} dt`. - + Parameters ---------- y : array_like @@ -4160,7 +4168,7 @@ def trapz(y, x=None, dx=1.0, axis=-1): a single axis by the trapezoidal rule. If 'y' is a 1-dimensional array, then the result is a float. If 'n' is greater than 1, then the result is an 'n-1' dimensional array. - + See Also -------- sum, cumsum @@ -4189,16 +4197,16 @@ def trapz(y, x=None, dx=1.0, axis=-1): 8.0 >>> np.trapz([1,2,3], dx=2) 8.0 - + Using a decreasing `x` corresponds to integrating in reverse: - - >>> np.trapz([1,2,3], x=[8,6,4]) + + >>> np.trapz([1,2,3], x=[8,6,4]) -8.0 - + More generally `x` is used to integrate along a parametric curve. This finds the area of a circle, noting we repeat the sample which closes the curve: - + >>> theta = np.linspace(0, 2 * np.pi, num=1000, endpoint=True) >>> np.trapz(np.cos(theta), x=np.sin(theta)) 3.141571941375841 |