File: Mean.cpp

package info (click to toggle)
freemat 4.0-5
  • links: PTS, VCS
  • area: main
  • in suites: jessie, jessie-kfreebsd, wheezy
  • size: 174,736 kB
  • ctags: 67,053
  • sloc: cpp: 351,060; ansic: 255,892; sh: 40,590; makefile: 4,323; perl: 4,058; asm: 3,313; pascal: 2,718; fortran: 1,722; ada: 1,681; ml: 1,360; cs: 879; csh: 795; python: 430; sed: 162; lisp: 160; awk: 5
file content (142 lines) | stat: -rw-r--r-- 4,362 bytes parent folder | download | duplicates (2)
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
131
132
133
134
135
136
137
138
139
140
141
142
/*
 * Copyright (c) 2009 Samit Basu
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 *
 */

#include "Array.hpp"
#include "Operators.hpp"

struct OpVecMean {
  template <typename T>
  static inline void func(ConstSparseIterator<T> & src, 
			  SparseSlice<T>& dest) {
    T accum = 0;
    index_t col = src.col();
    while (src.col() == col) {
      accum += src.value();
      src.next();
    }
    dest[1] = accum/src.rows();
  }
  template <typename T>
  static inline void func(ConstComplexSparseIterator<T> & src, 
			  SparseSlice<T>& dest_real,
			  SparseSlice<T>& dest_imag) {
    T accum_real = 0;
    T accum_imag = 0;
    index_t col = src.col();
    while (src.col() == col) {
      accum_real += src.realValue();
      accum_imag += src.imagValue();
      src.next();
    }
    dest_real[1] = accum_real/src.rows();
    dest_imag[1] = accum_imag/src.rows();
  }
  template <typename T>
  static inline void func(const BasicArray<T> & src, 
			  BasicArray<T>& dest) {
    T accum = 0;
    for (index_t i=1;i<=src.length();i++)
      accum += src[i];
    dest[1] = accum/src.rows();
  }
  template <typename T>
  static inline void func(const BasicArray<T> & src_real,
			  const BasicArray<T> & src_imag,
			  BasicArray<T>& dest_real,
			  BasicArray<T>& dest_imag) {
    T accum_real = 0;
    T accum_imag = 0;
    for (index_t i=1;i<=src_real.length();i++) {
      accum_real += src_real[i];
      accum_imag += src_imag[i];
    }
    dest_real[1] = accum_real/src_real.length();
    dest_imag[1] = accum_imag/src_imag.length();
  }
};

//!
//@Module MEAN Mean Function
//@@Section ELEMENTARY
//@@Usage
//Computes the mean of an array along a given dimension.  The general
//syntax for its use is
//@[
//  y = mean(x,d)
//@]
//where @|x| is an @|n|-dimensions array of numerical type.
//The output is of the same numerical type as the input.  The argument
//@|d| is optional, and denotes the dimension along which to take
//the mean.  The output @|y| is the same size as @|x|, except
//that it is singular along the mean direction.  So, for example,
//if @|x| is a @|3 x 3 x 4| array, and we compute the mean along
//dimension @|d=2|, then the output is of size @|3 x 1 x 4|.
//@@Function Internals
//The output is computed via
//\[
//y(m_1,\ldots,m_{d-1},1,m_{d+1},\ldots,m_{p}) = \frac{1}{N}
//\sum_{k=1}^{N} x(m_1,\ldots,m_{d-1},k,m_{d+1},\ldots,m_{p})
//\]
//If @|d| is omitted, then the mean is taken along the 
//first non-singleton dimension of @|x|. 
//@@Example
//The following piece of code demonstrates various uses of the mean
//function
//@<
//A = [5,1,3;3,2,1;0,3,1]
//@>
//We start by calling @|mean| without a dimension argument, in which 
//case it defaults to the first nonsingular dimension (in this case, 
//along the columns or @|d = 1|).
//@<
//mean(A)
//@>
//Next, we take the mean along the rows.
//@<
//mean(A,2)
//@>
//@@Tests
//@$near#y1=mean(x1)
//@$near#y1=mean(x1,2)#(any(loopi==[4,21]))
//@@Signature
//function mean MeanFunction
//inputs x dim
//outputs y
//!
ArrayVector MeanFunction(int nargout, const ArrayVector& arg) {
  // Get the data argument
  if (arg.size() < 1)
    throw Exception("mean requires at least one argument");
  Array input(arg[0]);
  int dim;
  if (arg.size() > 1)
    dim = arg[1].asInteger()-1;
  else
    dim = input.dimensions().firstNonsingular();
  if (input.dimensions() == NTuple(0,0))
    return ArrayVector(Array(NaN()));
  if (input.isEmpty()) {
    NTuple dims(input.dimensions());
    if (dims == NTuple(0,0)) return ArrayVector(Array(NaN()));
    if (dims[dim] != 0) 
      dims[dim] = 1;
    return ArrayVector(Array(input.dataClass(),dims));
  }
  return ArrayVector(VectorOp<OpVecMean>(input,1,dim));
}