Repository navigation
Expand file tree
/
Copy pathNDarray.aliases.cs
More file actions
129 lines (126 loc) · 5.92 KB
/
Copy pathNDarray.aliases.cs
File metadata and controls
129 lines (126 loc) · 5.92 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
using System;
using System.Collections.Generic;
using System.Text;
namespace Numpy
{
public partial class NDarray
{
/// <summary>
/// Calculate the absolute value element-wise.
///
/// np.abs is a shorthand for this function.
/// </summary>
/// <param name="@out">
/// A location into which the result is stored. If provided, it must have
/// a shape that the inputs broadcast to. If not provided or None,
/// a freshly-allocated array is returned. A tuple (possible only as a
/// keyword argument) must have length equal to the number of outputs.
/// </param>
/// <param name="@where">
/// Values of True indicate to calculate the ufunc at that position, values
/// of False indicate to leave the value in the output alone.
/// </param>
/// <returns>
/// An ndarray containing the absolute value of
/// each element in x. For complex input, a + ib, the
/// absolute value is .
/// This is a scalar if x is a scalar.
/// </returns>
public NDarray abs(NDarray @out = null, NDarray @where = null)
=> this.absolute(@out, @where);
/// <summary>
/// Return the minimum of an array or minimum along an axis.
///
/// Notes
///
/// NaN values are propagated, that is if at least one item is NaN, the
/// corresponding min value will be NaN as well. To ignore NaN values
/// (MATLAB behavior), please use nanmin.
///
/// Don’t use amin for element-wise comparison of 2 arrays; when
/// a.shape[0] is 2, minimum(a[0], a[1]) is faster than
/// amin(a, axis=0).
/// </summary>
/// <param name="axis">
/// Axis or axes along which to operate. By default, flattened input is
/// used.
///
/// If this is a tuple of ints, the minimum is selected over multiple axes,
/// instead of a single axis or all the axes as before.
/// </param>
/// <param name="@out">
/// Alternative output array in which to place the result. Must
/// be of the same shape and buffer length as the expected output.
/// See doc.ufuncs (Section “Output arguments”) for more details.
/// </param>
/// <param name="keepdims">
/// If this is set to True, the axes which are reduced are left
/// in the result as dimensions with size one. With this option,
/// the result will broadcast correctly against the input array.
///
/// If the default value is passed, then keepdims will not be
/// passed through to the amin method of sub-classes of
/// ndarray, however any non-default value will be. If the
/// sub-class’ method does not implement keepdims any
/// exceptions will be raised.
/// </param>
/// <param name="initial">
/// The maximum value of an output element. Must be present to allow
/// computation on empty slice. See reduce for details.
/// </param>
/// <returns>
/// Minimum of a. If axis is None, the result is a scalar value.
/// If axis is given, the result is an array of dimension
/// a.ndim - 1.
/// </returns>
public NDarray min(int[] axis = null, NDarray @out = null, bool? keepdims = null, ValueType initial = null)
=> np.amin(this, axis: axis, @out: @out, keepdims: keepdims, initial: initial);
/// <summary>
/// Return the maximum of an array or maximum along an axis.
///
/// Notes
///
/// NaN values are propagated, that is if at least one item is NaN, the
/// corresponding max value will be NaN as well. To ignore NaN values
/// (MATLAB behavior), please use nanmax.
///
/// Don’t use amax for element-wise comparison of 2 arrays; when
/// a.shape[0] is 2, maximum(a[0], a[1]) is faster than
/// amax(a, axis=0).
/// </summary>
/// <param name="axis">
/// Axis or axes along which to operate. By default, flattened input is
/// used.
///
/// If this is a tuple of ints, the maximum is selected over multiple axes,
/// instead of a single axis or all the axes as before.
/// </param>
/// <param name="@out">
/// Alternative output array in which to place the result. Must
/// be of the same shape and buffer length as the expected output.
/// See doc.ufuncs (Section “Output arguments”) for more details.
/// </param>
/// <param name="keepdims">
/// If this is set to True, the axes which are reduced are left
/// in the result as dimensions with size one. With this option,
/// the result will broadcast correctly against the input array.
///
/// If the default value is passed, then keepdims will not be
/// passed through to the amax method of sub-classes of
/// ndarray, however any non-default value will be. If the
/// sub-class’ method does not implement keepdims any
/// exceptions will be raised.
/// </param>
/// <param name="initial">
/// The minimum value of an output element. Must be present to allow
/// computation on empty slice. See reduce for details.
/// </param>
/// <returns>
/// Maximum of a. If axis is None, the result is a scalar value.
/// If axis is given, the result is an array of dimension
/// a.ndim - 1.
/// </returns>
public NDarray max(int[] axis = null, NDarray @out = null, bool? keepdims = null, ValueType initial = null)
=> np.amax(this, axis: axis, @out: @out, keepdims: keepdims, initial: initial);
}
}