1 /* ClassificationTable.cpp
2 *
3 * Copyright (C) 1993-2019 David Weenink
4 *
5 * This code is free software; you can redistribute it and/or modify
6 * it under the terms of the GNU General Public License as published by
7 * the Free Software Foundation; either version 2 of the License, or (at
8 * your option) any later version.
9 *
10 * This code is distributed in the hope that it will be useful, but
11 * WITHOUT ANY WARRANTY; without even the implied warranty of
12 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
13 * General Public License for more details.
14 *
15 * You should have received a copy of the GNU General Public License
16 * along with this work. If not, see <http://www.gnu.org/licenses/>.
17 */
18
19 /*
20 djmw 1998
21 djmw 20020315 GPL header
22 djmw 20040422 Added ClassificationTable_to_Categories_maximumProbability
23 djmw 20040623 Added ClassificationTable_to_Strings_maximumProbability
24 djmw 20040824 Added Strings_extensions.h header
25 djmw 20101122 ClassificationTable_to_Correlation_columns
26 djmw 20110304 Thing_new
27 */
28
29 #include "ClassificationTable.h"
30 #include "Distributions_and_Strings.h"
31 #include "Strings_extensions.h"
32 #include "NUM2.h"
33
34 Thing_implement (ClassificationTable, TableOfReal, 0);
35
ClassificationTable_create(integer numberOfRows,integer numberOfClasses)36 autoClassificationTable ClassificationTable_create (integer numberOfRows, integer numberOfClasses) {
37 try {
38 autoClassificationTable me = Thing_new (ClassificationTable);
39 TableOfReal_init (me.get(), numberOfRows, numberOfClasses);
40 return me;
41 } catch (MelderError) {
42 Melder_throw (U"ClassificationTable not created.");
43 }
44 }
45
ClassificationTable_to_Confusion(ClassificationTable me,bool onlyClassLabels)46 autoConfusion ClassificationTable_to_Confusion (ClassificationTable me, bool onlyClassLabels) {
47 try {
48 autoStrings responses = TableOfReal_extractColumnLabelsAsStrings (me);
49 autoStrings s2 = TableOfReal_extractRowLabelsAsStrings (me);
50 autoDistributions d2 = Strings_to_Distributions (s2.get());
51 autoStrings stimuli = TableOfReal_extractRowLabelsAsStrings (d2.get());
52 autoConfusion thee = Confusion_createFromStringses (( onlyClassLabels ? responses.get() : stimuli.get() ), responses.get());
53 Confusion_ClassificationTable_increase (thee.get(), me);
54 return thee;
55 } catch (MelderError) {
56 Melder_throw (me, U": confusions cannot be calculated.");
57 }
58 }
59
Confusion_ClassificationTable_increase(Confusion me,ClassificationTable thee)60 void Confusion_ClassificationTable_increase (Confusion me, ClassificationTable thee) {
61 Melder_require (my numberOfColumns == thy numberOfColumns,
62 U"The number of columns should be equal.");
63 for (integer irow = 1; irow <= thy numberOfRows; irow ++) {
64 const integer index = TableOfReal_getColumnIndexAtMaximumInRow (thee, irow);
65 Confusion_increase (me, thy rowLabels [irow].get(), my columnLabels [index].get());
66 }
67 }
68
ClassificationTable_to_Strings_maximumProbability(ClassificationTable me)69 autoStrings ClassificationTable_to_Strings_maximumProbability (ClassificationTable me) {
70 try {
71 autoStrings thee = Strings_createFixedLength (my numberOfRows);
72 Melder_assert (my numberOfColumns > 0);
73 for (integer i = 1; i <= my numberOfRows; i ++) {
74 const integer col = NUMmaxPos (my data.row (i));
75 if (my columnLabels [col])
76 Strings_replace (thee.get(), i, my columnLabels [col].get());
77 }
78 return thee;
79 } catch (MelderError) {
80 Melder_throw (me, U": strings cannot be created.");
81 }
82 }
83
ClassificationTable_to_Categories_maximumProbability(ClassificationTable me)84 autoCategories ClassificationTable_to_Categories_maximumProbability (ClassificationTable me) {
85 try {
86 autoCategories thee = Categories_create ();
87 Melder_assert (my numberOfColumns > 0);
88 for (integer i = 1; i <= my numberOfRows; i ++) {
89 const integer col = NUMmaxPos (my data.row (i));
90 OrderedOfString_append (thee.get(), my columnLabels [col].get());
91 }
92 return thee;
93 } catch (MelderError) {
94 Melder_throw (me, U": no Categories created.");
95 }
96 }
97
ClassificationTable_to_Correlation_columns(ClassificationTable me)98 autoCorrelation ClassificationTable_to_Correlation_columns (ClassificationTable me) {
99 try {
100 autoCorrelation thee = Correlation_create (my numberOfColumns);
101 for (integer icol = 1; icol <= thy numberOfColumns; icol ++) {
102 const conststring32 label = my columnLabels [icol].get();
103 TableOfReal_setRowLabel (thee.get(), icol, label);
104 TableOfReal_setColumnLabel (thee.get(), icol, label);
105 }
106 for (integer irow = 1; irow <= thy numberOfColumns; irow ++) {
107 thy data [irow] [irow] = 1.0;
108 for (integer icol = irow + 1; icol <= thy numberOfColumns; icol ++) {
109 const double n12 = NUMinner (my data.column (irow), my data.column (icol));
110 const double n11 = NUMinner (my data.column (irow), my data.column (irow));
111 const double n22 = NUMinner (my data.column (icol), my data.column (icol));
112 // probabilities might be very low!
113 if (n12 > 0.0 && n22 > 0.0) {
114 thy data [irow] [icol] = thy data [icol] [irow] = n12 / sqrt (n11 * n22);
115 }
116 }
117 }
118 thy numberOfObservations = my numberOfRows;
119 return thee;
120 } catch (MelderError) {
121 Melder_throw (me, U": no correlation created.");
122 }
123 }
124
125 /* End of file ClassificationTable.cpp */
126