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1"""
2Module of functions that are like ufuncs in acting on arrays and optionally
3storing results in an output array.
5"""
6__all__ = ['fix', 'isneginf', 'isposinf']
8import numpy._core.numeric as nx
9from numpy._core.overrides import array_function_dispatch
12def _dispatcher(x, out=None):
13 return (x, out)
16@array_function_dispatch(_dispatcher, verify=False, module='numpy')
17def fix(x, out=None):
18 """
19 Round to nearest integer towards zero.
21 Round an array of floats element-wise to nearest integer towards zero.
22 The rounded values have the same data-type as the input.
24 Parameters
25 ----------
26 x : array_like
27 An array to be rounded
28 out : ndarray, optional
29 A location into which the result is stored. If provided, it must have
30 a shape that the input broadcasts to. If not provided or None, a
31 freshly-allocated array is returned.
33 Returns
34 -------
35 out : ndarray of floats
36 An array with the same dimensions and data-type as the input.
37 If second argument is not supplied then a new array is returned
38 with the rounded values.
40 If a second argument is supplied the result is stored there.
41 The return value ``out`` is then a reference to that array.
43 See Also
44 --------
45 rint, trunc, floor, ceil
46 around : Round to given number of decimals
48 Examples
49 --------
50 >>> import numpy as np
51 >>> np.fix(3.14)
52 3.0
53 >>> np.fix(3)
54 3
55 >>> np.fix([2.1, 2.9, -2.1, -2.9])
56 array([ 2., 2., -2., -2.])
58 """
59 return nx.trunc(x, out=out)
62@array_function_dispatch(_dispatcher, verify=False, module='numpy')
63def isposinf(x, out=None):
64 """
65 Test element-wise for positive infinity, return result as bool array.
67 Parameters
68 ----------
69 x : array_like
70 The input array.
71 out : array_like, optional
72 A location into which the result is stored. If provided, it must have a
73 shape that the input broadcasts to. If not provided or None, a
74 freshly-allocated boolean array is returned.
76 Returns
77 -------
78 out : ndarray
79 A boolean array with the same dimensions as the input.
80 If second argument is not supplied then a boolean array is returned
81 with values True where the corresponding element of the input is
82 positive infinity and values False where the element of the input is
83 not positive infinity.
85 If a second argument is supplied the result is stored there. If the
86 type of that array is a numeric type the result is represented as zeros
87 and ones, if the type is boolean then as False and True.
88 The return value `out` is then a reference to that array.
90 See Also
91 --------
92 isinf, isneginf, isfinite, isnan
94 Notes
95 -----
96 NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
97 (IEEE 754).
99 Errors result if the second argument is also supplied when x is a scalar
100 input, if first and second arguments have different shapes, or if the
101 first argument has complex values
103 Examples
104 --------
105 >>> import numpy as np
106 >>> np.isposinf(np.inf)
107 True
108 >>> np.isposinf(-np.inf)
109 False
110 >>> np.isposinf([-np.inf, 0., np.inf])
111 array([False, False, True])
113 >>> x = np.array([-np.inf, 0., np.inf])
114 >>> y = np.array([2, 2, 2])
115 >>> np.isposinf(x, y)
116 array([0, 0, 1])
117 >>> y
118 array([0, 0, 1])
120 """
121 is_inf = nx.isinf(x)
122 try:
123 signbit = ~nx.signbit(x)
124 except TypeError as e:
125 dtype = nx.asanyarray(x).dtype
126 raise TypeError(f'This operation is not supported for {dtype} values '
127 'because it would be ambiguous.') from e
128 else:
129 return nx.logical_and(is_inf, signbit, out)
132@array_function_dispatch(_dispatcher, verify=False, module='numpy')
133def isneginf(x, out=None):
134 """
135 Test element-wise for negative infinity, return result as bool array.
137 Parameters
138 ----------
139 x : array_like
140 The input array.
141 out : array_like, optional
142 A location into which the result is stored. If provided, it must have a
143 shape that the input broadcasts to. If not provided or None, a
144 freshly-allocated boolean array is returned.
146 Returns
147 -------
148 out : ndarray
149 A boolean array with the same dimensions as the input.
150 If second argument is not supplied then a numpy boolean array is
151 returned with values True where the corresponding element of the
152 input is negative infinity and values False where the element of
153 the input is not negative infinity.
155 If a second argument is supplied the result is stored there. If the
156 type of that array is a numeric type the result is represented as
157 zeros and ones, if the type is boolean then as False and True. The
158 return value `out` is then a reference to that array.
160 See Also
161 --------
162 isinf, isposinf, isnan, isfinite
164 Notes
165 -----
166 NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic
167 (IEEE 754).
169 Errors result if the second argument is also supplied when x is a scalar
170 input, if first and second arguments have different shapes, or if the
171 first argument has complex values.
173 Examples
174 --------
175 >>> import numpy as np
176 >>> np.isneginf(-np.inf)
177 True
178 >>> np.isneginf(np.inf)
179 False
180 >>> np.isneginf([-np.inf, 0., np.inf])
181 array([ True, False, False])
183 >>> x = np.array([-np.inf, 0., np.inf])
184 >>> y = np.array([2, 2, 2])
185 >>> np.isneginf(x, y)
186 array([1, 0, 0])
187 >>> y
188 array([1, 0, 0])
190 """
191 is_inf = nx.isinf(x)
192 try:
193 signbit = nx.signbit(x)
194 except TypeError as e:
195 dtype = nx.asanyarray(x).dtype
196 raise TypeError(f'This operation is not supported for {dtype} values '
197 'because it would be ambiguous.') from e
198 else:
199 return nx.logical_and(is_inf, signbit, out)