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
|
// Scilab ( http://www.scilab.org/ ) - This file is part of Scilab
// Copyright (C) 2013 - A. Khorshidi
//
// This file must be used under the terms of the CeCILL.
// This source file is licensed as described in the file COPYING, which
// you should have received as part of this distribution. The terms
// are also available at
// http://www.cecill.info/licences/Licence_CeCILL_V2.1-en.txt
function [cf, ind] = histc(n, data, normalization)
// Example:
// n = 10;
// data = rand(1, 1000, "normal");
// [class_freq, ind] = histc(n, data)
rhs = argn(2);
if rhs < 2
error(msprintf(_("%s: Wrong number of input argument(s): At least %d expected.\n"), "histc", 2));
end
if rhs == 3 & exists("normalization", "local") then
if type(normalization) ~= 4 | size(normalization, "*") ~= 1 then
error(msprintf(_("%s: Wrong type of input argument #%d: A single boolean expected.\n"), "histc", 3));
end
else
// By default, normalize the result
normalization = %t
end
if type(n) ~= 1 & type(n) ~= 8
error(msprintf(_("%s: Wrong type for input argument #%d: A real matrix expected.\n"),"histc",1));
end
if type(n) == 8 then
n = iconvert(n, 0); // To pass to dsearch
end
if type(data) ~= 1 & type(data) ~= 8
error(msprintf(_("%s: Wrong type for input argument #%d: A real matrix expected.\n"),"histc",2))
end
if type(data) == 8 then
data = iconvert(data, 0); // To pass to dsearch
end
nd = length(data); // Number of data values
if length(n) == 1 then // The number of classes is provided
if n < 1
error(msprintf(_("%s: Wrong value for input argument #%d: Must be in the interval %s.\n"),"histc",1,"[1, oo)"));
elseif n ~= floor(n)
error(msprintf(_("%s: Wrong type for input argument #%d: Integer expected.\n"),"histc",1))
end
mind = min(data);
maxd = max(data);
if (mind == maxd) then
mind = mind - floor(n/2);
maxd = maxd + ceil(n/2);
end
cb = linspace(mind, maxd, n+1); // Class boundary
else // The classes are provided
cb = matrix(n, 1, -1); // Force row form
if min(diff(cb)) <= 0 then
error(msprintf(_("%s: Wrong values for input argument #%d: Elements must be in increasing order.\n"),"histc",1))
end
end
[ind, cf, info] = dsearch(data, cb); // cf: class frequency, ind: class number of each count
// Normalization
if normalization == %t then
cw = cb(2:$)-cb(1:$-1); // Bin width
cf = cf./(nd*cw);
end
endfunction
|
