Repository navigation
Expand file tree
/
Copy pathNumPy.padding.gen.cs
More file actions
130 lines (126 loc) · 5.19 KB
/
Copy pathNumPy.padding.gen.cs
File metadata and controls
130 lines (126 loc) · 5.19 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
130
// Copyright (c) 2019 by the SciSharp Team
// Code generated by CodeMinion: https://github.com/SciSharp/CodeMinion
using System;
using System.Collections;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Runtime.InteropServices;
using System.Text;
using Python.Runtime;
using Numpy.Models;
namespace Numpy
{
public partial class NumPy
{
/// <summary>
/// Pads an array.<br></br>
///
/// Notes
///
/// For an array with rank greater than 1, some of the padding of later
/// axes is calculated from padding of previous axes.<br></br>
/// This is easiest to
/// think about with a rank 2 array where the corners of the padded array
/// are calculated by using padded values from the first axis.<br></br>
///
/// The padding function, if used, should return a rank 1 array equal in
/// length to the vector argument with padded values replaced.<br></br>
/// It has the
/// following signature:
///
/// where
/// </summary>
/// <param name="array">
/// Input array
/// </param>
/// <param name="pad_width">
/// Number of values padded to the edges of each axis.<br></br>
///
/// ((before_1, after_1), … (before_N, after_N)) unique pad widths
/// for each axis.<br></br>
///
/// ((before, after),) yields same before and after pad for each axis.<br></br>
///
/// (pad,) or int is a shortcut for before = after = pad width for all
/// axes.
/// </param>
/// <param name="mode">
/// One of the following string values or a user supplied function.
/// </param>
/// <param name="stat_length">
/// Used in ‘maximum’, ‘mean’, ‘median’, and ‘minimum’. Number of
/// values at edge of each axis used to calculate the statistic value.<br></br>
///
/// ((before_1, after_1), … (before_N, after_N)) unique statistic
/// lengths for each axis.<br></br>
///
/// ((before, after),) yields same before and after statistic lengths
/// for each axis.<br></br>
///
/// (stat_length,) or int is a shortcut for before = after = statistic
/// length for all axes.<br></br>
///
/// Default is None, to use the entire axis.
/// </param>
/// <param name="constant_values">
/// Used in ‘constant’. The values to set the padded values for each
/// axis.<br></br>
///
/// ((before_1, after_1), … (before_N, after_N)) unique pad constants
/// for each axis.<br></br>
///
/// ((before, after),) yields same before and after constants for each
/// axis.<br></br>
///
/// (constant,) or int is a shortcut for before = after = constant for
/// all axes.<br></br>
///
/// Default is 0.
/// </param>
/// <param name="end_values">
/// Used in ‘linear_ramp’. The values used for the ending value of the
/// linear_ramp and that will form the edge of the padded array.<br></br>
///
/// ((before_1, after_1), … (before_N, after_N)) unique end values
/// for each axis.<br></br>
///
/// ((before, after),) yields same before and after end values for each
/// axis.<br></br>
///
/// (constant,) or int is a shortcut for before = after = end value for
/// all axes.<br></br>
///
/// Default is 0.
/// </param>
/// <param name="reflect_type">
/// Used in ‘reflect’, and ‘symmetric’. The ‘even’ style is the
/// default with an unaltered reflection around the edge value.<br></br>
/// For
/// the ‘odd’ style, the extended part of the array is created by
/// subtracting the reflected values from two times the edge value.
/// </param>
/// <returns>
/// Padded array of rank equal to array with shape increased
/// according to pad_width.
/// </returns>
public NDarray pad(NDarray array, NDarray pad_width, string mode, int[] stat_length = null, int[] constant_values = null, int[] end_values = null, string reflect_type = null)
{
//auto-generated code, do not change
var __self__=self;
var pyargs=ToTuple(new object[]
{
array,
pad_width,
mode,
});
var kwargs=new PyDict();
if (stat_length!=null) kwargs["stat_length"]=ToPython(stat_length);
if (constant_values!=null) kwargs["constant_values"]=ToPython(constant_values);
if (end_values!=null) kwargs["end_values"]=ToPython(end_values);
if (reflect_type!=null) kwargs["reflect_type"]=ToPython(reflect_type);
dynamic py = __self__.InvokeMethod("pad", pyargs, kwargs);
return ToCsharp<NDarray>(py);
}
}
}