diff options
Diffstat (limited to 'src/statisticsFunctions/mean')
18 files changed, 0 insertions, 2518 deletions
diff --git a/src/statisticsFunctions/mean/Makefile.am b/src/statisticsFunctions/mean/Makefile.am deleted file mode 100644 index a855ef33..00000000 --- a/src/statisticsFunctions/mean/Makefile.am +++ /dev/null @@ -1,69 +0,0 @@ -## -## Scilab ( http://www.scilab.org/ ) - This file is part of Scilab -## Copyright (C) 2006-2008 - INRIA - Bruno JOFRET -## -## 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-en.txt -## -## - -libMean_la_CFLAGS = -I $(top_builddir)/type \ - -I $(top_builddir)/operations/includes \ - -I ../includes - -instdir = $(top_builddir)/lib - -pkglib_LTLIBRARIES = libMean.la - -libMean_la_SOURCES = $(HEAD) $(SRC) - -SRC = smeana.c \ - srowmeana.c \ - scolumnmeana.c \ - dmeana.c \ - drowmeana.c \ - dcolumnmeana.c \ - cmeana.c \ - crowmeana.c \ - ccolumnmeana.c \ - zmeana.c \ - zrowmeana.c \ - zcolumnmeana.c - -HEAD = ../includes/mean.h - -#### -# Checking Part -#### - -check_INCLUDES = -I $(top_builddir)/statisticsFunctions/includes \ - -I $(top_builddir)/operations/includes \ - -I $(top_builddir)/type - -check_LDADD = $(top_builddir)/type/libDoubleComplex.la \ - $(top_builddir)/type/libFloatComplex.la \ - $(top_builddir)/operations/addition/libAddition.la \ - $(top_builddir)/statisticsFunctions/mean/libMean.la \ - $(top_builddir)/statisticsFunctions/sum/libSum.la \ - $(top_builddir)/operations/division/libDivision.la \ - 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The terms - * are also available at - * http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void ccolumnmeana(floatComplex *in, int lines, int columns, floatComplex *out) { - int i = 0; - - ccolumnsuma(in, lines, columns, out); - for (i = 0; i < lines; ++i) - { - out[i] = crdivs(out[i] , FloatComplex((float) columns, 0.0f)); - } -} diff --git a/src/statisticsFunctions/mean/cmeana.c b/src/statisticsFunctions/mean/cmeana.c deleted file mode 100644 index ad2a66fc..00000000 --- a/src/statisticsFunctions/mean/cmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" - -floatComplex cmeana(floatComplex *in, int size) { - floatComplex accumulate = FloatComplex(0.0f, 0.0f); - int i = 0; - - for (i = 0; i < size; ++i) - { - accumulate = cadds(accumulate, in[i]); - } - return FloatComplex(creals(accumulate) / (float) size, cimags(accumulate) / (float) size); -} diff --git a/src/statisticsFunctions/mean/crowmeana.c b/src/statisticsFunctions/mean/crowmeana.c deleted file mode 100644 index 0b073c41..00000000 --- a/src/statisticsFunctions/mean/crowmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void crowmeana(floatComplex *in, int lines, int columns, floatComplex *out) { - int i = 0; - - crowsuma(in, lines, columns, out); - for (i = 0; i < columns; ++i) - { - out[i] = crdivs(out[i], FloatComplex((float)lines, 0.0f)); - } -} diff --git a/src/statisticsFunctions/mean/dcolumnmeana.c b/src/statisticsFunctions/mean/dcolumnmeana.c deleted file mode 100644 index 90d7863b..00000000 --- a/src/statisticsFunctions/mean/dcolumnmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void dcolumnmeana(double *in, int lines, int columns, double *out) { - int i = 0; - - dcolumnsuma(in, lines, columns, out); - for (i = 0; i < lines; ++i) - { - out[i] /= (double) columns; - } -} diff --git a/src/statisticsFunctions/mean/dmeana.c b/src/statisticsFunctions/mean/dmeana.c deleted file mode 100644 index db11766a..00000000 --- a/src/statisticsFunctions/mean/dmeana.c +++ /dev/null @@ -1,25 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" - -double dmeana(double *in, int size) { - double accumulate = 0.0; - int i = 0; - - for (i = 0; i < size; ++i) - { - accumulate += in[i]; - } - return accumulate / (double) size; - -} diff --git a/src/statisticsFunctions/mean/drowmeana.c b/src/statisticsFunctions/mean/drowmeana.c deleted file mode 100644 index aec1b31a..00000000 --- a/src/statisticsFunctions/mean/drowmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void drowmeana(double *in, int lines, int columns, double *out) { - int i = 0; - - drowsuma(in, lines, columns, out); - for (i = 0; i < columns; ++i) - { - out[i] /= (double) lines; - } -} diff --git a/src/statisticsFunctions/mean/scolumnmeana.c b/src/statisticsFunctions/mean/scolumnmeana.c deleted file mode 100644 index 59985d5e..00000000 --- a/src/statisticsFunctions/mean/scolumnmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void scolumnmeana(float *in, int lines, int columns, float *out) { - int i = 0; - - scolumnsuma(in, lines, columns, out); - for (i = 0; i < lines; ++i) - { - out[i] /= (float) columns; - } -} diff --git a/src/statisticsFunctions/mean/smeana.c b/src/statisticsFunctions/mean/smeana.c deleted file mode 100644 index f4b1cd10..00000000 --- a/src/statisticsFunctions/mean/smeana.c +++ /dev/null @@ -1,25 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" - -float smeana(float *in, int size) { - float accumulate = 0.0f; - int i = 0; - - for (i = 0; i < size; ++i) - { - accumulate += in[i]; - } - return accumulate / (float) size; - -} diff --git a/src/statisticsFunctions/mean/srowmeana.c b/src/statisticsFunctions/mean/srowmeana.c deleted file mode 100644 index 3fb799f0..00000000 --- a/src/statisticsFunctions/mean/srowmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void srowmeana(float *in, int lines, int columns, float *out) { - int i = 0; - - srowsuma(in, lines, columns, out); - for (i = 0; i < columns; ++i) - { - out[i] /= (float) lines; - } -} diff --git a/src/statisticsFunctions/mean/testDoubleMean.c b/src/statisticsFunctions/mean/testDoubleMean.c deleted file mode 100644 index 1e1b2576..00000000 --- a/src/statisticsFunctions/mean/testDoubleMean.c +++ /dev/null @@ -1,493 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include <assert.h> -#include <stdio.h> -#include <math.h> -#include "mean.h" - -/* #define LOCAL_DEBUG */ - -#define ERROR(x) printf("diff = %e\n", x) - -static int dmeansTest(void) { - double value1 = 3.0; - double value2 = 1.123456789; - - printf("\n>>>> Mean Double Scalar Test\n"); - assert( ( fabs(dmeans(value1) ) - ( 3.0 ) ) / fabs ( dmeans(value1) ) < 3e-16 ); - assert( ( fabs(dmeans(value2) ) - ( 1.123456789 ) ) / fabs ( dmeans(value2) ) < 3e-16 ); - - return 0; -} - -static int dmeanaTest(void) { - double table1[3] = {3.0, 3.0, 3.0}; - double table2[5] = {9.186784563, - 9.186784563, - 9.186784563, - 9.186784563, - 9.186784563}; - - printf("\n>>>> Mean Double Array Test\n"); - assert( ( fabs(dmeana(table1, 3) ) - ( 9.0 / 3.0 ) ) / fabs ( dmeana(table1, 3) ) < 3e-16 ); - assert(( ( fabs(dmeana(table2, 5) ) - ( (9.186784563 + 9.186784563 + 9.186784563 + 9.186784563 + 9.186784563) / 5.0) ) ) / fabs ( dmeana(table2, 5) ) < 3e-16 ); - return 0; -} - -static int dcolumnmeanaTest(void) { - int i = 0; - double table1[9] = {1.0, 4.0, 7.0, 2.0 , 5.0, 8.0, 3.0, 6.0, 9.0}; - double table2[10] = {1.0, 2.0, 3.0, 4.0 , 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}; - double columnMeanmedTable1_3_3[3] = {0}; - double columnMeanmedTable1_1_9[1] = {0}; - double columnMeanmedTable1_9_1[9] = {0}; - double columnMeanmedTable2_2_5[2] = {0}; - double columnMeanmedTable2_5_2[5] = {0}; - - printf("\n>>>> Column Mean Double Array Test\n"); - /* - [ 1 2 3 ] - [ 4 5 6 ] => [ 6 15 24 ] - [ 7 8 9 ] - */ - dcolumnmeana(table1, 3, 3,columnMeanmedTable1_3_3); - assert( ( fabs(columnMeanmedTable1_3_3[0] ) - ( 6.0 / 3.0 ) ) / fabs ( columnMeanmedTable1_3_3[0] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable1_3_3[1] ) - ( 15.0 / 3.0 ) ) / fabs ( columnMeanmedTable1_3_3[1] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable1_3_3[2] ) - ( 24.0 / 3.0 ) ) / fabs ( columnMeanmedTable1_3_3[2] ) < 3e-16 ); - - /* - [ 1 2 3 4 5 6 7 8 9 ] => [ 45 ] - */ - dcolumnmeana(table1, 1, 9,columnMeanmedTable1_1_9); - assert( ( fabs(columnMeanmedTable1_1_9[0] ) - ( 45.0 / 9.0 ) ) / fabs ( columnMeanmedTable1_1_9[0] ) < 3e-16 ); - - /* - [ 1 ] - [ 2 ] - [ 3 ] - [ 4 ] - [ 5 ] => [ 1 2 3 4 5 6 7 8 9 ] - [ 6 ] - [ 7 ] - [ 8 ] - [ 9 ] - */ - dcolumnmeana(table1, 9, 1,columnMeanmedTable1_9_1); - for ( i = 0 ; i < 9 ; ++i) { - printf("columnMeanmedTable1_9_1[%d] = %e\n", i, columnMeanmedTable1_9_1[i]); - assert(columnMeanmedTable1_9_1[i] == table1[i]); - } - - /* - [ 1 3 5 7 9 ] - [ 2 4 6 8 10 ] => [ 25 30 ] - */ - dcolumnmeana(table2, 2, 5,columnMeanmedTable2_2_5); - assert( ( fabs(columnMeanmedTable2_2_5[0] ) - ( 25.0 / 5.0 ) ) / fabs ( columnMeanmedTable2_2_5[0] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable2_2_5[1] ) - ( 30.0 / 5.0 ) ) / fabs ( columnMeanmedTable2_2_5[1] ) < 3e-16 ); - for ( i = 0 ; i < 2 ; ++i) { - printf("columnMeanmedTable2_2_5[%d] = %e\n", i, columnMeanmedTable2_2_5[i]); - } - - /* - [ 1 6 ] - [ 2 7 ] => [ 7 9 11 13 15 ] - [ 3 8 ] - [ 4 9 ] - [ 5 10 ] - */ - dcolumnmeana(table2, 5, 2,columnMeanmedTable2_5_2); - assert( ( fabs(columnMeanmedTable2_5_2[0] ) - ( 7.0 / 2.0 ) ) / fabs ( columnMeanmedTable2_5_2[0] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable2_5_2[1] ) - ( 9.0 / 2.0 ) ) / fabs ( columnMeanmedTable2_5_2[1] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable2_5_2[2] ) - ( 11.0 / 2.0 ) ) / fabs ( columnMeanmedTable2_5_2[2] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable2_5_2[3] ) - ( 13.0 / 2.0 ) ) / fabs ( columnMeanmedTable2_5_2[3] ) < 3e-16 ); - assert( ( fabs(columnMeanmedTable2_5_2[4] ) - ( 15.0 / 2.0 ) ) / fabs ( columnMeanmedTable2_5_2[4] ) < 3e-16 ); - for ( i = 0 ; i < 5 ; ++i) { - printf("columnMeanmedTable2_5_2[%d] = %e\n", i, columnMeanmedTable2_5_2[i]); - } - - return 0; -} - -static int drowmeanaTest(void) { - int i = 0; - double table1[9] = {1.0, 4.0, 7.0, 2.0 , 5.0, 8.0, 3.0, 6.0, 9.0}; - double table2[10] = {1.0, 2.0, 3.0, 4.0 , 5.0, 6.0, 7.0, 8.0, 9.0, 10.0}; - double rowMeanmedTable1_3_3[3] = {0}; - double rowMeanmedTable1_1_9[9] = {0}; - double rowMeanmedTable1_9_1[1] = {0}; - double rowMeanmedTable2_2_5[5] = {0}; - double rowMeanmedTable2_5_2[2] = {0}; - - printf("\n>>>> Row Mean Double Array Test\n"); - /* - [ 1 2 3 ] - [ 4 5 6 ] => [ 12 15 18 ] - [ 7 8 9 ] - */ - drowmeana(table1, 3, 3,rowMeanmedTable1_3_3); - for ( i = 0 ; i < 3 ; ++i) { - printf("rowMeanmedTable1_3_3[%d] = %e\n", i, rowMeanmedTable1_3_3[i]); - } - assert( ( fabs(rowMeanmedTable1_3_3[0] ) - ( 12.0 / 3.0 ) ) / fabs ( rowMeanmedTable1_3_3[0] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable1_3_3[1] ) - ( 15.0 / 3.0 ) ) / fabs ( rowMeanmedTable1_3_3[1] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable1_3_3[2] ) - ( 18.0 / 3.0 ) ) / fabs ( rowMeanmedTable1_3_3[2] ) < 3e-16 ); - - /* - [ 1 ] - [ 2 ] - [ 3 ] - [ 4 ] - [ 5 ] => [ 1 2 3 4 5 6 7 8 9 ] - [ 6 ] - [ 7 ] - [ 8 ] - [ 9 ] - */ - drowmeana(table1, 1, 9,rowMeanmedTable1_1_9); - for ( i = 0 ; i < 9 ; ++i) { - printf("rowMeanmedTable1_1_9[%d] = %e\n", i, rowMeanmedTable1_1_9[i]); - assert(rowMeanmedTable1_1_9[i] == table1[i]); - } - - /* - [ 1 2 3 4 5 6 7 8 9 ] => [ 45 ] - */ - drowmeana(table1, 9, 1,rowMeanmedTable1_9_1); - assert( ( fabs(rowMeanmedTable1_9_1[0] ) - ( 45.0 / 9.0 ) ) / fabs ( rowMeanmedTable1_9_1[0] ) < 3e-16 ); - - /* - [ 1 3 5 7 9 ] - [ 2 4 6 8 10 ] => [ 3 7 11 15 19 ] - */ - drowmeana(table2, 2, 5,rowMeanmedTable2_2_5); - for ( i = 0 ; i < 5 ; ++i) { - printf("rowMeanmedTable2_2_5[%d] = %e\n", i, rowMeanmedTable2_2_5[i]); - } - assert( ( fabs(rowMeanmedTable2_2_5[0] ) - ( 3.0 / 2.0 ) ) / fabs ( rowMeanmedTable2_2_5[0] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable2_2_5[1] ) - ( 7.0 / 2.0 ) ) / fabs ( rowMeanmedTable2_2_5[1] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable2_2_5[2] ) - ( 11.0 / 2.0 ) ) / fabs ( rowMeanmedTable2_2_5[2] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable2_2_5[3] ) - ( 15.0 / 2.0 ) ) / fabs ( rowMeanmedTable2_2_5[3] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable2_2_5[4] ) - ( 19.0 / 2.0 ) ) / fabs ( rowMeanmedTable2_2_5[4] ) < 3e-16 ); - - /* - [ 1 6 ] - [ 2 7 ] => [ 15 40 ] - [ 3 8 ] - [ 4 9 ] - [ 5 10 ] - */ - drowmeana(table2, 5, 2,rowMeanmedTable2_5_2); - assert( ( fabs(rowMeanmedTable2_5_2[0] ) - ( 15.0 / 5.0 ) ) / fabs ( rowMeanmedTable2_5_2[0] ) < 3e-16 ); - assert( ( fabs(rowMeanmedTable2_5_2[1] ) - ( 40.0 / 5.0 ) ) / fabs ( rowMeanmedTable2_5_2[1] ) < 3e-16 ); - for ( i = 0 ; i < 2 ; ++i) { - printf("rowMeanmedTable2_5_2[%d] = %e\n", i, rowMeanmedTable2_5_2[i]); - } - - return 0; -} - -static int zmeansTest(void) { - doubleComplex value1 = DoubleComplex(3.0, 3.0); - doubleComplex value2 = DoubleComplex(1.123456789, 1.123456789); - - printf("\n>>>> Mean Double Complex Scalar Test\n"); - assert( ( fabs(zreals(zmeans(value1)) ) - ( 3.0 ) ) / fabs ( zreals(zmeans(value1)) ) < 3e-16 ); - assert( ( fabs(zimags(zmeans(value1)) ) - ( 3.0 ) ) / fabs ( zimags(zmeans(value1)) ) < 3e-16 ); - assert( ( fabs(zreals(zmeans(value2)) ) - ( 1.123456789 ) ) / fabs ( zreals(zmeans(value2)) ) < 3e-16 ); - assert( ( fabs(zimags(zmeans(value2)) ) - ( 1.123456789 ) ) / fabs ( zimags(zmeans(value2)) ) < 3e-16 ); - return 0; -} - -static int zmeanaTest(void) { - doubleComplex value1 = DoubleComplex(3.0, 3.0); - doubleComplex table1[3]; - doubleComplex value2 = DoubleComplex(9.186784563,9.186784563); - doubleComplex table2[5]; - - printf("\n>>>> Mean Double Complex Array Test\n"); - table1[0] = value1; - table1[1] = value1; - table1[2] = value1; - - table2[0] = value2; - table2[1] = value2; - table2[2] = value2; - table2[3] = value2; - table2[4] = value2; - -#ifdef LOCAL_DEBUG - printf("--------\n"); - printf("%e\n", zimags(zmeana(table1, 3))); - printf("%e\n", zreals(zmeana(table2, 5))); - printf("%e\n", zimags(zmeana(table2, 5))); - printf("%e\n", zreals(zmeana(table2, 5))); - printf("%e\n", zimags(zmeana(table2, 5))); - printf("--------\n"); -#endif - assert( ( fabs(zreals(zmeana(table1, 3)) ) - ( 9.0 / 3.0 ) ) / fabs ( zreals(zmeana(table1, 3)) ) < 3e-16 ); - assert( ( fabs(zimags(zmeana(table1, 3)) ) - ( 9.0 / 3.0 ) ) / fabs ( zimags(zmeana(table1, 3)) ) < 3e-16 ); - assert( ( fabs(zreals(zmeana(table2, 5)) ) - ( (9.186784563 + 9.186784563 + 9.186784563 + 9.186784563 + 9.186784563) / 5.0 ) ) / fabs ( zreals(zmeana(table2, 5)) ) < 3e-16 ); - assert( ( fabs(zimags(zmeana(table2, 5)) ) - ( (9.186784563 + 9.186784563 + 9.186784563 + 9.186784563 + 9.186784563) / 5.0 ) ) / fabs ( zimags(zmeana(table2, 5)) ) < 3e-16 ); - - return 0; -} - -static int zrowmeanaTest(void) { - int i = 0; - doubleComplex in[12]; - doubleComplex rowMeanmedIn_4_3[3]; - doubleComplex rowMeanmedIn_3_4[4]; - doubleComplex rowMeanmedIn_6_2[2]; - doubleComplex rowMeanmedIn_2_6[6]; - doubleComplex rowMeanmedIn_1_12[12]; - doubleComplex rowMeanmedIn_12_1[1]; - - printf("\n>>>> Row Mean Double Complex Array Test\n"); - /* Init input var */ - for (i = 0 ; i < 12 ; ++i) - { - in[i] = DoubleComplex((double) i / 10.0, (11.0 - (double) i) / 10.0); - } - - /* - [ 1.1i 0.4+0.7i 0.8+0.3i ] - [ 0.1+i 0.5+0.6i 0.9+0.2i ] => [ 0.6+3.8i 2.2+2.2i 3.8+0.6i ] - [ 0.2+0.9i 0.6+0.5i 1+0.1i ] - [ 0.3+0.8i 0.7+0.4i 1.1 ] - */ - zrowmeana(in, 4, 3, rowMeanmedIn_4_3); - for (i = 0 ; i < 3 ; ++i) { - printf("rowMeanmedIn_4_3[%d] = %e + %ei\n", i, zreals(rowMeanmedIn_4_3[i]), zimags(rowMeanmedIn_4_3[i])); - } - assert(fabs(zreals(rowMeanmedIn_4_3[0]) - 0.6 / 4.0) < 1e-16); - assert( ( fabs(zimags(rowMeanmedIn_4_3[0]) ) - ( 3.8 / 4.0 ) ) / fabs ( zimags(rowMeanmedIn_4_3[0]) ) < 3e-16 ); - assert( ( fabs(zreals(rowMeanmedIn_4_3[1]) ) - ( 2.2 / 4.0 ) ) / fabs ( zreals(rowMeanmedIn_4_3[1]) ) < 3e-16 ); - assert(fabs(zimags(rowMeanmedIn_4_3[1]) - 2.2 / 4.0) < 3e-16); - assert(fabs(zreals(rowMeanmedIn_4_3[2]) - 3.8 / 4.0) < 3e-16); - assert( ( fabs(zimags(rowMeanmedIn_4_3[2]) ) - ( 0.6 / 4.0 ) ) / fabs ( zimags(rowMeanmedIn_4_3[2]) ) < 3e-16 ); - - /* - [ 1.1i 0.3+0.8i 0.6+0.5i 0.9+0.2i ] - [ 0.1+i 0.4+0.7i 0.7+0.4i 1+0.1i ] => [ 0.3+3.i 1.2+2.1i 2.1+1.2i 3.+0.3i] - [ 0.2+0.9i 0.5+0.6i 0.8+0.3i 1.1 ] - */ - zrowmeana(in, 3, 4, rowMeanmedIn_3_4); - for (i = 0 ; i < 4 ; ++i) { - printf("rowMeanmedIn_3_4[%d] = %e + %ei\n", i, zreals(rowMeanmedIn_3_4[i]), zimags(rowMeanmedIn_3_4[i])); - } - assert(fabs(zreals(rowMeanmedIn_3_4[0]) - 0.3 / 3.0) < 1e-16); - assert( ( fabs(zimags(rowMeanmedIn_3_4[0]) ) - ( 3.0 / 3.0 ) ) / fabs ( zimags(rowMeanmedIn_3_4[0]) ) < 3e-16 ); - assert(zreals(rowMeanmedIn_3_4[1]) == 1.2 / 3.0 && zimags(rowMeanmedIn_3_4[1]) == 2.1 / 3.0); - assert(fabs(zreals(rowMeanmedIn_3_4[2]) - 2.1 / 3.0) < 3e-16); - assert( ( fabs(zimags(rowMeanmedIn_3_4[2]) ) - ( 1.2 / 3.0 ) ) / fabs ( zimags(rowMeanmedIn_3_4[2]) ) < 3e-16 ); - assert( ( fabs(zreals(rowMeanmedIn_3_4[3]) ) - ( 3.0 / 3.0 ) ) / fabs ( zreals(rowMeanmedIn_3_4[3]) ) < 3e-16 ); - assert(fabs(zimags(rowMeanmedIn_3_4[3]) - 0.3 / 3.0) < 1e-16); - - /* - [ 1.1i 0.6+0.5i ] - [ 0.1+i 0.7+0.4i ] - [ 0.2+0.9i 0.8+0.3i ] => [ 1.5+5.1i 5.1+1.5i ] - [ 0.3+0.8i 0.9+0.2i ] - [ 0.4+0.7i 1+0.1i ] - [ 0.5+0.6i 1.1 ] - */ - zrowmeana(in, 6, 2, rowMeanmedIn_6_2); - for (i = 0 ; i < 2 ; ++i) { - printf("rowMeanmedIn_6_2[%d] = %e + %ei\n", i, zreals(rowMeanmedIn_6_2[i]), zimags(rowMeanmedIn_6_2[i])); - } - assert(zreals(rowMeanmedIn_6_2[0]) == 1.5 / 6.0 && zimags(rowMeanmedIn_6_2[0]) == 5.1 / 6.0); - assert(zreals(rowMeanmedIn_6_2[1]) == 5.1 / 6.0 && zimags(rowMeanmedIn_6_2[1]) == 1.5 / 6.0); - - /* - [ 1.1i 0.2+0.9i 0.4+0.7i 0.6+0.5i 0.8+0.3i 1+0.1i ] - [ 0.1+i 0.3+0.8i 0.5+0.6i 0.7+0.4i 0.9+0.2i 1.1 ] => [ 0.1+2.1i 0.5+1.7i 0.9+1.3i 1.3+0.9i 1.7+0.5i 2.1+0.1i ] - */ - zrowmeana(in, 2, 6, rowMeanmedIn_2_6); - for (i = 0 ; i < 6 ; ++i) { - printf("rowMeanmedIn_2_6[%d] = %e + %ei\n", i, zreals(rowMeanmedIn_2_6[i]), zimags(rowMeanmedIn_2_6[i])); - } - assert(zreals(rowMeanmedIn_2_6[0]) == 0.1 / 2.0 && zimags(rowMeanmedIn_2_6[0]) == 2.1 / 2.0); - assert( ( fabs(zreals(rowMeanmedIn_2_6[1]) ) - ( 0.5 / 2.0 ) ) / fabs ( zreals(rowMeanmedIn_2_6[1]) ) < 3e-16 ); - assert(fabs(double(zimags(rowMeanmedIn_2_6[1]) == 1.7 / 2.0)) < 1e-16); - assert( ( fabs(zreals(rowMeanmedIn_2_6[2]) ) - ( 0.9 / 2.0 ) ) / fabs ( zreals(rowMeanmedIn_2_6[2]) ) < 3e-16 ); - assert(fabs(double(zimags(rowMeanmedIn_2_6[2]) == 1.3 / 2.0)) < 1e-16); - assert(fabs(double(zreals(rowMeanmedIn_2_6[3]) == 1.3 / 2.0)) < 1e-16); - assert( ( fabs(zimags(rowMeanmedIn_2_6[3]) ) - ( 0.9 / 2.0 ) ) / fabs ( zimags(rowMeanmedIn_2_6[3]) ) < 3e-16 ); - assert(fabs(double(zreals(rowMeanmedIn_2_6[4]) == 1.7 / 2.0)) < 1e-16); - assert( ( fabs(zimags(rowMeanmedIn_2_6[4]) ) - ( 0.5 / 2.0 ) ) / fabs ( zimags(rowMeanmedIn_2_6[4]) ) < 3e-16 ); - assert(zreals(rowMeanmedIn_2_6[5]) == 2.1 / 2.0 && zimags(rowMeanmedIn_2_6[5]) == 0.1 / 2.0); - - /* - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - => - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - */ - zrowmeana(in, 1, 12, rowMeanmedIn_1_12); - for (i = 0 ; i < 12 ; ++i) { - printf("rowMeanmedIn_1_12[%d] = %e + %ei\n", i, zreals(rowMeanmedIn_1_12[i]), zimags(rowMeanmedIn_1_12[i])); - assert(zreals(rowMeanmedIn_1_12[i]) == zreals(in[i]) && zimags(rowMeanmedIn_1_12[i]) == zimags(in[i])); - } - - /* - [ 1.1i ] - [ 0.1+i ] - [ 0.2+0.9i ] - [ 0.3+0.8i ] - [ 0.4+0.7i ] - [ 0.5+0.6i ] - [ 0.6+0.5i ] => [ 6.6+6.6i ] - [ 0.7+0.4i ] - [ 0.8+0.3i ] - [ 0.9+0.2i ] - [ 1+0.1i ] - [ 1.1 ] - */ - zrowmeana(in, 12, 1, rowMeanmedIn_12_1); - printf("rowMeanmedIn_12_1[%d] = %e + %ei\n", 0, zreals(rowMeanmedIn_12_1[0]), zimags(rowMeanmedIn_12_1[0])); - assert(zreals(rowMeanmedIn_12_1[0]) == 6.6 / 12.0 && zimags(rowMeanmedIn_12_1[0]) == 6.6 / 12.0); - - return 0; -} - -static int zcolumnmeanaTest(void) { - int i = 0; - doubleComplex in[12]; - doubleComplex columnMeanmedIn_4_3[4]; - doubleComplex columnMeanmedIn_3_4[3]; - doubleComplex columnMeanmedIn_6_2[6]; - doubleComplex columnMeanmedIn_2_6[2]; - doubleComplex columnMeanmedIn_1_12[1]; - doubleComplex columnMeanmedIn_12_1[12]; - - printf("\n>>>> ColumnMean Double Complex Array Test\n"); - /* Init input var */ - for (i = 0 ; i < 12 ; ++i) - { - in[i] = DoubleComplex((double) i / 10.0, (11.0 - (double) i) / 10.0); - } - - /* - [ 1.1i 0.4+0.7i 0.8+0.3i ] - [ 0.1+i 0.5+0.6i 0.9+0.2i ] => [ 1.2+2.1i 1.5+1.8i 1.8+1.5i 2.1+1.2i ] - [ 0.2+0.9i 0.6+0.5i 1+0.1i ] - [ 0.3+0.8i 0.7+0.4i 1.1 ] - */ - zcolumnmeana(in, 4, 3, columnMeanmedIn_4_3); - for (i = 0 ; i < 4 ; ++i) { - printf("columnMeanmedIn_4_3[%d] = %e + %ei\n", i, zreals(columnMeanmedIn_4_3[i]), zimags(columnMeanmedIn_4_3[i])); - } - assert(fabs(zreals(columnMeanmedIn_4_3[0]) - 1.2 / 3.0) < 3e-16); - assert(zimags(columnMeanmedIn_4_3[0]) == 2.1 / 3.0); - assert(zreals(columnMeanmedIn_4_3[1]) == 1.5 / 3.0 && zimags(columnMeanmedIn_4_3[1]) == 1.8 / 3.0); - assert(zreals(columnMeanmedIn_4_3[2]) == 1.8 / 3.0&& zimags(columnMeanmedIn_4_3[2]) == 1.5 / 3.0); - assert(zreals(columnMeanmedIn_4_3[3]) == 2.1 / 3.0); - assert(fabs(zimags(columnMeanmedIn_4_3[3]) - 1.2 / 3.0) < 3e-16); - - /* - [ 1.1i 0.3+0.8i 0.6+0.5i 0.9+0.2i ] - [ 0.1+i 0.4+0.7i 0.7+0.4i 1+0.1i ] => [ 1.8+2.6i 2.2+2.2i 2.6+1.8i ] - [ 0.2+0.9i 0.5+0.6i 0.8+0.3i 1.1 ] - */ - zcolumnmeana(in, 3, 4, columnMeanmedIn_3_4); - for (i = 0 ; i < 3 ; ++i) { - printf("columnMeanmedIn_3_4[%d] = %e + %ei\n", i, zreals(columnMeanmedIn_3_4[i]), zimags(columnMeanmedIn_3_4[i])); - } - assert(fabs(zreals(columnMeanmedIn_3_4[0]) - 1.8 / 4.0) < 3e-16); - assert(fabs(zimags(columnMeanmedIn_3_4[0]) - 2.6 / 4.0) < 3e-16); - assert(zreals(columnMeanmedIn_3_4[1]) == 2.2 / 4.0 && zimags(columnMeanmedIn_3_4[1]) == 2.2 / 4.0); - assert(zreals(columnMeanmedIn_3_4[2]) == 2.6 / 4.0 && zimags(columnMeanmedIn_3_4[2]) == 1.8 / 4.0); - - /* - [ 1.1i 0.6+0.5i ] - [ 0.1+i 0.7+0.4i ] - [ 0.2+0.9i 0.8+0.3i ] => [ 0.6+1.6i 0.8+1.4i 1+1.2i 1.2+i 1.4+0.8i 1.6+0.6i ] - [ 0.3+0.8i 0.9+0.2i ] - [ 0.4+0.7i 1+0.1i ] - [ 0.5+0.6i 1.1 ] - */ - zcolumnmeana(in, 6, 2, columnMeanmedIn_6_2); - for (i = 0 ; i < 6 ; ++i) { - printf("columnMeanmedIn_6_2[%d] = %e + %ei\n", i, zreals(columnMeanmedIn_6_2[i]), zimags(columnMeanmedIn_6_2[i])); - } - assert(zreals(columnMeanmedIn_6_2[0]) == 0.6 / 2.0 && zimags(columnMeanmedIn_6_2[0]) == 1.6 / 2.0); - assert(fabs(zreals(columnMeanmedIn_6_2[1]) - 0.8 / 2.0) < 3e-16); - assert(zimags(columnMeanmedIn_6_2[1]) == 1.4 / 2.0); - assert(zreals(columnMeanmedIn_6_2[2]) == 1.0 / 2.0 && zimags(columnMeanmedIn_6_2[2]) == 1.2 / 2.0); - assert(zreals(columnMeanmedIn_6_2[3]) == 1.2 / 2.0 && zimags(columnMeanmedIn_6_2[3]) == 1.0 / 2.0); - assert(zreals(columnMeanmedIn_6_2[4]) == 1.4 / 2.0); - assert(fabs(zimags(columnMeanmedIn_6_2[4]) - 0.8 / 2.0) < 3e-16); - assert(zreals(columnMeanmedIn_6_2[5]) == 1.6 / 2.0 && zimags(columnMeanmedIn_6_2[5]) == 0.6 / 2.0); - - /* - [ 1.1i 0.2+0.9i 0.4+0.7i 0.6+0.5i 0.8+0.3i 1+0.1i ] - [ 0.1+i 0.3+0.8i 0.5+0.6i 0.7+0.4i 0.9+0.2i 1.1 ] => [ 3+3.6i 3.6+3i ] - */ - zcolumnmeana(in, 2, 6, columnMeanmedIn_2_6); - for (i = 0 ; i < 2 ; ++i) { - printf("columnMeanmedIn_2_6[%d] = %e + %ei\n", i, zreals(columnMeanmedIn_2_6[i]), zimags(columnMeanmedIn_2_6[i])); - } - assert(zreals(columnMeanmedIn_2_6[0]) == 3.0 / 6.0 && zimags(columnMeanmedIn_2_6[0]) == 3.6 / 6.0); - assert(zreals(columnMeanmedIn_2_6[1]) == 3.6 / 6.0 && zimags(columnMeanmedIn_2_6[1]) == 3.0 / 6.0); - - /* - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - => - [ 6.6+6.6i ] - */ - zcolumnmeana(in, 1, 12, columnMeanmedIn_1_12); - printf("columnMeanmedIn_1_12[%d] = %e + %ei\n", 0, zreals(columnMeanmedIn_1_12[0]), zimags(columnMeanmedIn_1_12[0])); - assert(zreals(columnMeanmedIn_1_12[0]) == 6.6 / 12.0 && zimags(columnMeanmedIn_1_12[0]) == 6.6 / 12.0); - - - /* - [ 1.1i ] - [ 0.1+i ] - [ 0.2+0.9i ] - [ 0.3+0.8i ] - [ 0.4+0.7i ] - [ 0.5+0.6i ] - [ 0.6+0.5i ] => [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - [ 0.7+0.4i ] - [ 0.8+0.3i ] - [ 0.9+0.2i ] - [ 1+0.1i ] - [ 1.1 ] - */ - zcolumnmeana(in, 12, 1, columnMeanmedIn_12_1); - for (i = 0 ; i < 12 ; ++i) { - printf("columnMeanmedIn_12_1[%d] = %e + %ei\n", i, zreals(columnMeanmedIn_12_1[i]), zimags(columnMeanmedIn_12_1[i])); - assert(zreals(columnMeanmedIn_12_1[i]) == zreals(in[i]) && zimags(columnMeanmedIn_12_1[i]) == zimags(in[i])); - } - - return 0; -} - -static int testMean(void) { - - dmeansTest(); - dmeanaTest(); - drowmeanaTest(); - dcolumnmeanaTest(); - zmeansTest(); - zmeanaTest(); - zrowmeanaTest(); - zcolumnmeanaTest(); - - return 0; -} - -int main(void) { - assert(testMean() == 0); - return 0; -} diff --git a/src/statisticsFunctions/mean/testFloatMean.c b/src/statisticsFunctions/mean/testFloatMean.c deleted file mode 100644 index e5c6d9d8..00000000 --- a/src/statisticsFunctions/mean/testFloatMean.c +++ /dev/null @@ -1,481 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include <assert.h> -#include <stdio.h> -#include <math.h> -#include "mean.h" - -/* #define LOCAL_DEBUG */ - -static int smeansTest(void) { - float value1 = 3.0f; - float value2 = 1.123456789f; - - printf("\n>>>> Mean Float Scalar Test\n"); - assert(smeans(value1) == 3.0f); - assert(smeans(value2) == 1.123456789f); - - return 0; -} - -static int smeanaTest(void) { - float table1[3] = {3.0f, 3.0f, 3.0f}; - float table2[5] = {9.186784563f, - 9.186784563f, - 9.186784563f, - 9.186784563f, - 9.186784563f}; - - printf("\n>>>> Mean Float Array Test\n"); - assert(smeana(table1, 3) == 9.0f / 3.0f); - assert((smeana(table2, 5) - (9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f) / 5.0f) / smeana(table2, 5) < 1e-6); - return 0; -} - -static int scolumnmeanaTest(void) { - int i = 0; - float table1[9] = {1.0f, 4.0f, 7.0f, 2.0f , 5.0f, 8.0f, 3.0f, 6.0f, 9.0f}; - float table2[10] = {1.0f, 2.0f, 3.0f, 4.0f , 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f}; - float columnMeanmedTable1_3_3[3] = {0}; - float columnMeanmedTable1_1_9[1] = {0}; - float columnMeanmedTable1_9_1[9] = {0}; - float columnMeanmedTable2_2_5[2] = {0}; - float columnMeanmedTable2_5_2[5] = {0}; - - printf("\n>>>> Column Mean Float Array Test\n"); - /* - [ 1 2 3 ] - [ 4 5 6 ] => [ 6 15 24 ] - [ 7 8 9 ] - */ - scolumnmeana(table1, 3, 3,columnMeanmedTable1_3_3); - assert(columnMeanmedTable1_3_3[0] == 6.0f / 3.0f); - assert(columnMeanmedTable1_3_3[1] == 15.0f / 3.0f); - assert(columnMeanmedTable1_3_3[2] == 24.0f / 3.0f); - - /* - [ 1 2 3 4 5 6 7 8 9 ] => [ 45 ] - */ - scolumnmeana(table1, 1, 9,columnMeanmedTable1_1_9); - assert(columnMeanmedTable1_1_9[0] == 45.0f / 9.0f); - - /* - [ 1 ] - [ 2 ] - [ 3 ] - [ 4 ] - [ 5 ] => [ 1 2 3 4 5 6 7 8 9 ] - [ 6 ] - [ 7 ] - [ 8 ] - [ 9 ] - */ - scolumnmeana(table1, 9, 1,columnMeanmedTable1_9_1); - for ( i = 0 ; i < 9 ; ++i) { - printf("columnMeanmedTable1_9_1[%d] = %e\n", i, columnMeanmedTable1_9_1[i]); - assert(columnMeanmedTable1_9_1[i] == table1[i]); - } - - /* - [ 1 3 5 7 9 ] - [ 2 4 6 8 10 ] => [ 25 30 ] - */ - scolumnmeana(table2, 2, 5,columnMeanmedTable2_2_5); - assert(columnMeanmedTable2_2_5[0] == 25.0f / 5.0f); - assert(columnMeanmedTable2_2_5[1] == 30.0f / 5.0f); - for ( i = 0 ; i < 2 ; ++i) { - printf("columnMeanmedTable2_2_5[%d] = %e\n", i, columnMeanmedTable2_2_5[i]); - } - - /* - [ 1 6 ] - [ 2 7 ] => [ 7 9 11 13 15 ] - [ 3 8 ] - [ 4 9 ] - [ 5 10 ] - */ - scolumnmeana(table2, 5, 2,columnMeanmedTable2_5_2); - assert(columnMeanmedTable2_5_2[0] == 7.0f / 2.0f); - assert(columnMeanmedTable2_5_2[1] == 9.0f / 2.0f); - assert(columnMeanmedTable2_5_2[2] == 11.0f / 2.0f); - assert(columnMeanmedTable2_5_2[3] == 13.0f / 2.0f); - assert(columnMeanmedTable2_5_2[4] == 15.0f / 2.0f); - for ( i = 0 ; i < 5 ; ++i) { - printf("columnMeanmedTable2_5_2[%d] = %e\n", i, columnMeanmedTable2_5_2[i]); - } - - return 0; -} - -static int srowmeanaTest(void) { - int i = 0; - float table1[9] = {1.0f, 4.0f, 7.0f, 2.0f , 5.0f, 8.0f, 3.0f, 6.0f, 9.0f}; - float table2[10] = {1.0f, 2.0f, 3.0f, 4.0f , 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f}; - float rowMeanmedTable1_3_3[3] = {0}; - float rowMeanmedTable1_1_9[9] = {0}; - float rowMeanmedTable1_9_1[1] = {0}; - float rowMeanmedTable2_2_5[5] = {0}; - float rowMeanmedTable2_5_2[2] = {0}; - - printf("\n>>>> Row Mean Float Array Test\n"); - /* - [ 1 2 3 ] - [ 4 5 6 ] => [ 12 15 18 ] - [ 7 8 9 ] - */ - srowmeana(table1, 3, 3,rowMeanmedTable1_3_3); - for ( i = 0 ; i < 3 ; ++i) { - printf("rowMeanmedTable1_3_3[%d] = %e\n", i, rowMeanmedTable1_3_3[i]); - } - assert(rowMeanmedTable1_3_3[0] == 12.0f / 3.0f); - assert(rowMeanmedTable1_3_3[1] == 15.0f / 3.0f); - assert(rowMeanmedTable1_3_3[2] == 18.0f / 3.0f); - - /* - [ 1 ] - [ 2 ] - [ 3 ] - [ 4 ] - [ 5 ] => [ 1 2 3 4 5 6 7 8 9 ] - [ 6 ] - [ 7 ] - [ 8 ] - [ 9 ] - */ - srowmeana(table1, 1, 9,rowMeanmedTable1_1_9); - for ( i = 0 ; i < 9 ; ++i) { - printf("rowMeanmedTable1_1_9[%d] = %e\n", i, rowMeanmedTable1_1_9[i]); - assert(rowMeanmedTable1_1_9[i] == table1[i]); - } - - /* - [ 1 2 3 4 5 6 7 8 9 ] => [ 45 ] - */ - srowmeana(table1, 9, 1,rowMeanmedTable1_9_1); - assert(rowMeanmedTable1_9_1[0] == 45.0f / 9.0f); - - /* - [ 1 3 5 7 9 ] - [ 2 4 6 8 10 ] => [ 3 7 11 15 19 ] - */ - srowmeana(table2, 2, 5,rowMeanmedTable2_2_5); - assert(rowMeanmedTable2_2_5[0] == 3.0f / 2.0f); - assert(rowMeanmedTable2_2_5[1] == 7.0f / 2.0f); - assert(rowMeanmedTable2_2_5[2] == 11.0f / 2.0f); - assert(rowMeanmedTable2_2_5[3] == 15.0f / 2.0f); - assert(rowMeanmedTable2_2_5[4] == 19.0f / 2.0f); - for ( i = 0 ; i < 5 ; ++i) { - printf("rowMeanmedTable2_2_5[%d] = %e\n", i, rowMeanmedTable2_2_5[i]); - } - - /* - [ 1 6 ] - [ 2 7 ] => [ 15 40 ] - [ 3 8 ] - [ 4 9 ] - [ 5 10 ] - */ - srowmeana(table2, 5, 2,rowMeanmedTable2_5_2); - assert(rowMeanmedTable2_5_2[0] == 15.0f / 5.0f); - assert(rowMeanmedTable2_5_2[1] == 40.0f / 5.0f); - for ( i = 0 ; i < 2 ; ++i) { - printf("rowMeanmedTable2_5_2[%d] = %e\n", i, rowMeanmedTable2_5_2[i]); - } - - return 0; -} - -static int cmeansTest(void) { - floatComplex value1 = FloatComplex(3.0f, 3.0f); - floatComplex value2 = FloatComplex(1.123456789f, 1.123456789f); - - printf("\n>>>> Mean Float Complex Scalar Test\n"); - assert(creals(cmeans(value1)) == 3.0f); - assert(cimags(cmeans(value1)) == 3.0f); - assert(creals(cmeans(value2)) == 1.123456789f); - assert(cimags(cmeans(value2)) == 1.123456789f); - return 0; -} - -static int cmeanaTest(void) { - floatComplex value1 = FloatComplex(3.0f, 3.0f); - floatComplex table1[3]; - floatComplex value2 = FloatComplex(9.186784563f,9.186784563f); - floatComplex table2[5]; - - printf("\n>>>> Mean Float Complex Array Test\n"); - table1[0] = value1; - table1[1] = value1; - table1[2] = value1; - - table2[0] = value2; - table2[1] = value2; - table2[2] = value2; - table2[3] = value2; - table2[4] = value2; - -#ifdef LOCAL_DEBUG - printf("--------\n"); - printf("%e\n", cimags(cmeana(table1, 3))); - printf("%e\n", creals(cmeana(table2, 5))); - printf("%e\n", cimags(cmeana(table2, 5))); - printf("%e\n", creals(cmeana(table2, 5))); - printf("%e\n", cimags(cmeana(table2, 5))); - printf("--------\n"); -#endif - assert(creals(cmeana(table1, 3)) == 9.0f / 3.0f); - assert(cimags(cmeana(table1, 3)) == 9.0f / 3.0f); - assert(creals(cmeana(table2, 5)) == (9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f) / 5.0f); - assert(cimags(cmeana(table2, 5)) == (9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f + 9.186784563f) / 5.0f); - - return 0; -} - -static int crowmeanaTest(void) { - int i = 0; - floatComplex in[12]; - floatComplex rowMeanmedIn_4_3[3]; - floatComplex rowMeanmedIn_3_4[4]; - floatComplex rowMeanmedIn_6_2[2]; - floatComplex rowMeanmedIn_2_6[6]; - floatComplex rowMeanmedIn_1_12[12]; - floatComplex rowMeanmedIn_12_1[1]; - - printf("\n>>>> Row Mean Float Complex Array Test\n"); - /* Init input var */ - for (i = 0 ; i < 12 ; ++i) - { - in[i] = FloatComplex((float) i / 10.0f, (11.0f - (float) i) / 10.0f); - } - - /* - [ 1.1i 0.4+0.7i 0.8+0.3i ] - [ 0.1+i 0.5+0.6i 0.9+0.2i ] => [ 0.6+3.8i 2.2+2.2i 3.8+0.6i ] - [ 0.2+0.9i 0.6+0.5i 1+0.1i ] - [ 0.3+0.8i 0.7+0.4i 1.1 ] - */ - crowmeana(in, 4, 3, rowMeanmedIn_4_3); - for (i = 0 ; i < 3 ; ++i) { - printf("rowMeanmedIn_4_3[%d] = %e + %ei\n", i, creals(rowMeanmedIn_4_3[i]), cimags(rowMeanmedIn_4_3[i])); - } - assert(creals(rowMeanmedIn_4_3[0]) == 0.6f / 4.0f && cimags(rowMeanmedIn_4_3[0]) == 3.8f / 4.0f); - assert(creals(rowMeanmedIn_4_3[1]) == 2.2f / 4.0f && cimags(rowMeanmedIn_4_3[1]) == 2.2f / 4.0f); - assert(fabs(creals(rowMeanmedIn_4_3[2]) - 3.8f / 4.0f) < 1e-06); - assert(cimags(rowMeanmedIn_4_3[2]) == 0.6f / 4.0f); - - /* - [ 1.1i 0.3+0.8i 0.6+0.5i 0.9+0.2i ] - [ 0.1+i 0.4+0.7i 0.7+0.4i 1+0.1i ] => [ 0.3+3.i 1.2+2.1i 2.1+1.2i 3.+0.3i] - [ 0.2+0.9i 0.5+0.6i 0.8+0.3i 1.1 ] - */ - crowmeana(in, 3, 4, rowMeanmedIn_3_4); - for (i = 0 ; i < 4 ; ++i) { - printf("rowMeanmedIn_3_4[%d] = %e + %ei\n", i, creals(rowMeanmedIn_3_4[i]), cimags(rowMeanmedIn_3_4[i])); - } - assert(creals(rowMeanmedIn_3_4[0]) == 0.3f / 3.0f && cimags(rowMeanmedIn_3_4[0]) == 3.0f / 3.0f); - assert(creals(rowMeanmedIn_3_4[1]) == 1.2f / 3.0f && cimags(rowMeanmedIn_3_4[1]) == 2.1f / 3.0f); - assert(creals(rowMeanmedIn_3_4[2]) == 2.1f / 3.0f && cimags(rowMeanmedIn_3_4[2]) == 1.2f / 3.0f); - assert(creals(rowMeanmedIn_3_4[3]) == 3.0f / 3.0f && cimags(rowMeanmedIn_3_4[3]) == 0.3f / 3.0f); - - /* - [ 1.1i 0.6+0.5i ] - [ 0.1+i 0.7+0.4i ] - [ 0.2+0.9i 0.8+0.3i ] => [ 1.5+5.1i 5.1+1.5i ] - [ 0.3+0.8i 0.9+0.2i ] - [ 0.4+0.7i 1+0.1i ] - [ 0.5+0.6i 1.1 ] - */ - crowmeana(in, 6, 2, rowMeanmedIn_6_2); - for (i = 0 ; i < 2 ; ++i) { - printf("rowMeanmedIn_6_2[%d] = %e + %ei\n", i, creals(rowMeanmedIn_6_2[i]), cimags(rowMeanmedIn_6_2[i])); - } - assert(creals(rowMeanmedIn_6_2[0]) == 1.5f / 6.0f && cimags(rowMeanmedIn_6_2[0]) == 5.1f / 6.0f); - assert(creals(rowMeanmedIn_6_2[1]) == 5.1f / 6.0f); - assert(fabs(cimags(rowMeanmedIn_6_2[1]) - 1.5f / 6.0f) < 1e-06); - - /* - [ 1.1i 0.2+0.9i 0.4+0.7i 0.6+0.5i 0.8+0.3i 1+0.1i ] - [ 0.1+i 0.3+0.8i 0.5+0.6i 0.7+0.4i 0.9+0.2i 1.1 ] => [ 0.1+2.1i 0.5+1.7i 0.9+1.3i 1.3+0.9i 1.7+0.5i 2.1+0.1i ] - */ - crowmeana(in, 2, 6, rowMeanmedIn_2_6); - for (i = 0 ; i < 6 ; ++i) { - printf("rowMeanmedIn_2_6[%d] = %e + %ei\n", i, creals(rowMeanmedIn_2_6[i]), cimags(rowMeanmedIn_2_6[i])); - } - assert(creals(rowMeanmedIn_2_6[0]) == 0.1f / 2.0f && cimags(rowMeanmedIn_2_6[0]) == 2.1f / 2.0f); - assert(creals(rowMeanmedIn_2_6[1]) == 0.5f / 2.0f && cimags(rowMeanmedIn_2_6[1]) == 1.7f / 2.0f); - assert(creals(rowMeanmedIn_2_6[2]) == 0.9f / 2.0f && cimags(rowMeanmedIn_2_6[2]) == 1.3f / 2.0f); - assert(creals(rowMeanmedIn_2_6[3]) == 1.3f / 2.0f && cimags(rowMeanmedIn_2_6[3]) == 0.9f / 2.0f); - assert(creals(rowMeanmedIn_2_6[4]) == 1.7f / 2.0f && cimags(rowMeanmedIn_2_6[4]) == 0.5f / 2.0f); - assert(creals(rowMeanmedIn_2_6[5]) == 2.1f / 2.0f && cimags(rowMeanmedIn_2_6[5]) == 0.1f / 2.0f); - - /* - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - => - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - */ - crowmeana(in, 1, 12, rowMeanmedIn_1_12); - for (i = 0 ; i < 12 ; ++i) { - printf("rowMeanmedIn_1_12[%d] = %e + %ei\n", i, creals(rowMeanmedIn_1_12[i]), cimags(rowMeanmedIn_1_12[i])); - assert(creals(rowMeanmedIn_1_12[i]) == creals(in[i]) && cimags(rowMeanmedIn_1_12[i]) == cimags(in[i])); - } - - /* - [ 1.1i ] - [ 0.1+i ] - [ 0.2+0.9i ] - [ 0.3+0.8i ] - [ 0.4+0.7i ] - [ 0.5+0.6i ] - [ 0.6+0.5i ] => [ 6.6+6.6i ] - [ 0.7+0.4i ] - [ 0.8+0.3i ] - [ 0.9+0.2i ] - [ 1+0.1i ] - [ 1.1 ] - */ - crowmeana(in, 12, 1, rowMeanmedIn_12_1); - printf("rowMeanmedIn_12_1[%d] = %e + %ei\n", 0, creals(rowMeanmedIn_12_1[0]), cimags(rowMeanmedIn_12_1[0])); - assert(creals(rowMeanmedIn_12_1[0]) == 6.6f / 12.0f && cimags(rowMeanmedIn_12_1[0]) == 6.6f / 12.0f); - - return 0; -} - -static int ccolumnmeanaTest(void) { - int i = 0; - floatComplex in[12]; - floatComplex columnMeanmedIn_4_3[4]; - floatComplex columnMeanmedIn_3_4[3]; - floatComplex columnMeanmedIn_6_2[6]; - floatComplex columnMeanmedIn_2_6[2]; - floatComplex columnMeanmedIn_1_12[1]; - floatComplex columnMeanmedIn_12_1[12]; - - printf("\n>>>> ColumnMean Float Complex Array Test\n"); - /* Init input var */ - for (i = 0 ; i < 12 ; ++i) - { - in[i] = FloatComplex((float) i / 10.0f, (11.0f - (float) i) / 10.0f); - } - - /* - [ 1.1i 0.4+0.7i 0.8+0.3i ] - [ 0.1+i 0.5+0.6i 0.9+0.2i ] => [ 1.2+2.1i 1.5+1.8i 1.8+1.5i 2.1+1.2i ] - [ 0.2+0.9i 0.6+0.5i 1+0.1i ] - [ 0.3+0.8i 0.7+0.4i 1.1 ] - */ - ccolumnmeana(in, 4, 3, columnMeanmedIn_4_3); - for (i = 0 ; i < 4 ; ++i) { - printf("columnMeanmedIn_4_3[%d] = %e + %ei\n", i, creals(columnMeanmedIn_4_3[i]), cimags(columnMeanmedIn_4_3[i])); - } - assert(creals(columnMeanmedIn_4_3[0]) == 1.2f / 3.0f && cimags(columnMeanmedIn_4_3[0]) == 2.1f / 3.0f); - assert(creals(columnMeanmedIn_4_3[1]) == 1.5f / 3.0f); - assert(fabs(cimags(columnMeanmedIn_4_3[1]) - 1.8f / 3.0f) < 1e-06); - assert(creals(columnMeanmedIn_4_3[2]) == 1.8f / 3.0f && cimags(columnMeanmedIn_4_3[2]) == 1.5f / 3.0f); - assert(creals(columnMeanmedIn_4_3[3]) == 2.1f / 3.0f && cimags(columnMeanmedIn_4_3[3]) == 1.2f / 3.0f); - - /* - [ 1.1i 0.3+0.8i 0.6+0.5i 0.9+0.2i ] - [ 0.1+i 0.4+0.7i 0.7+0.4i 1+0.1i ] => [ 1.8+2.6i 2.2+2.2i 2.6+1.8i ] - [ 0.2+0.9i 0.5+0.6i 0.8+0.3i 1.1 ] - */ - ccolumnmeana(in, 3, 4, columnMeanmedIn_3_4); - for (i = 0 ; i < 3 ; ++i) { - printf("columnMeanmedIn_3_4[%d] = %e + %ei\n", i, creals(columnMeanmedIn_3_4[i]), cimags(columnMeanmedIn_3_4[i])); - } - assert(creals(columnMeanmedIn_3_4[0]) == 1.8f / 4.0f); - assert(fabs(cimags(columnMeanmedIn_3_4[0]) - 2.6f / 4.0f) < 1e-06); - assert(creals(columnMeanmedIn_3_4[1]) == 2.2f / 4.0f && cimags(columnMeanmedIn_3_4[1]) == 2.2f / 4.0f); - assert(creals(columnMeanmedIn_3_4[2]) == 2.6f / 4.0f && cimags(columnMeanmedIn_3_4[2]) == 1.8f / 4.0f); - - /* - [ 1.1i 0.6+0.5i ] - [ 0.1+i 0.7+0.4i ] - [ 0.2+0.9i 0.8+0.3i ] => [ 0.6+1.6i 0.8+1.4i 1+1.2i 1.2+i 1.4+0.8i 1.6+0.6i ] - [ 0.3+0.8i 0.9+0.2i ] - [ 0.4+0.7i 1+0.1i ] - [ 0.5+0.6i 1.1 ] - */ - ccolumnmeana(in, 6, 2, columnMeanmedIn_6_2); - for (i = 0 ; i < 6 ; ++i) { - printf("columnMeanmedIn_6_2[%d] = %e + %ei\n", i, creals(columnMeanmedIn_6_2[i]), cimags(columnMeanmedIn_6_2[i])); - } - assert(creals(columnMeanmedIn_6_2[0]) == 0.6f / 2.0f && cimags(columnMeanmedIn_6_2[0]) == 1.6f / 2.0f); - assert(creals(columnMeanmedIn_6_2[1]) == 0.8f / 2.0f && cimags(columnMeanmedIn_6_2[1]) == 1.4f / 2.0f); - assert(creals(columnMeanmedIn_6_2[2]) == 1.0f / 2.0f && cimags(columnMeanmedIn_6_2[2]) == 1.2f / 2.0f); - assert(creals(columnMeanmedIn_6_2[3]) == 1.2f / 2.0f && cimags(columnMeanmedIn_6_2[3]) == 1.0f / 2.0f); - assert(creals(columnMeanmedIn_6_2[4]) == 1.4f / 2.0f && cimags(columnMeanmedIn_6_2[4]) == 0.8f / 2.0f); - assert(creals(columnMeanmedIn_6_2[5]) == 1.6f / 2.0f && cimags(columnMeanmedIn_6_2[5]) == 0.6f / 2.0f); - - /* - [ 1.1i 0.2+0.9i 0.4+0.7i 0.6+0.5i 0.8+0.3i 1+0.1i ] - [ 0.1+i 0.3+0.8i 0.5+0.6i 0.7+0.4i 0.9+0.2i 1.1 ] => [ 3+3.6i 3.6+3i ] - */ - ccolumnmeana(in, 2, 6, columnMeanmedIn_2_6); - for (i = 0 ; i < 2 ; ++i) { - printf("columnMeanmedIn_2_6[%d] = %e + %ei\n", i, creals(columnMeanmedIn_2_6[i]), cimags(columnMeanmedIn_2_6[i])); - } - assert(creals(columnMeanmedIn_2_6[0]) == 3.0f / 6.0f && cimags(columnMeanmedIn_2_6[0]) == 3.6f / 6.0f); - assert(creals(columnMeanmedIn_2_6[1]) == 3.6f / 6.0f); - assert(fabs(cimags(columnMeanmedIn_2_6[1]) -3.0f / 6.0f) < 1e-06); - - /* - [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - => - [ 6.6+6.6i ] - */ - ccolumnmeana(in, 1, 12, columnMeanmedIn_1_12); - printf("columnMeanmedIn_1_12[%d] = %e + %ei\n", 0, creals(columnMeanmedIn_1_12[0]), cimags(columnMeanmedIn_1_12[0])); - assert(creals(columnMeanmedIn_1_12[0]) == 6.6f / 12.0f && cimags(columnMeanmedIn_1_12[0]) == 6.6f / 12.0f); - - - /* - [ 1.1i ] - [ 0.1+i ] - [ 0.2+0.9i ] - [ 0.3+0.8i ] - [ 0.4+0.7i ] - [ 0.5+0.6i ] - [ 0.6+0.5i ] => [ 1.1i 0.1+i 0.2+0.9i 0.3+0.8i 0.4+0.7i 0.5+0.6i 0.6+0.5i 0.7+0.4i 0.8+0.3i 0.9+0.2i 1+0.1i 1.1 ] - [ 0.7+0.4i ] - [ 0.8+0.3i ] - [ 0.9+0.2i ] - [ 1+0.1i ] - [ 1.1 ] - */ - ccolumnmeana(in, 12, 1, columnMeanmedIn_12_1); - for (i = 0 ; i < 12 ; ++i) { - printf("columnMeanmedIn_12_1[%d] = %e + %ei\n", i, creals(columnMeanmedIn_12_1[i]), cimags(columnMeanmedIn_12_1[i])); 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diff --git a/src/statisticsFunctions/mean/zcolumnmeana.c b/src/statisticsFunctions/mean/zcolumnmeana.c deleted file mode 100644 index 8cc38fc7..00000000 --- a/src/statisticsFunctions/mean/zcolumnmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void zcolumnmeana(doubleComplex *in, int lines, int columns, doubleComplex *out) { - int i = 0; - - zcolumnsuma(in, lines, columns, out); - for (i = 0; i < lines; ++i) - { - out[i] = zrdivs(out[i] , DoubleComplex((double) columns, 0.0f)); - } -} diff --git a/src/statisticsFunctions/mean/zmeana.c b/src/statisticsFunctions/mean/zmeana.c deleted file mode 100644 index aae80ffc..00000000 --- a/src/statisticsFunctions/mean/zmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" - -doubleComplex zmeana(doubleComplex *in, int size) { - doubleComplex accumulate = DoubleComplex(0.0f, 0.0f); - int i = 0; - - for (i = 0; i < size; ++i) - { - accumulate = zadds(accumulate, in[i]); - } - return DoubleComplex(zreals(accumulate) / (double) size, zimags(accumulate) / (double) size); -} diff --git a/src/statisticsFunctions/mean/zrowmeana.c b/src/statisticsFunctions/mean/zrowmeana.c deleted file mode 100644 index 8e19bf9e..00000000 --- a/src/statisticsFunctions/mean/zrowmeana.c +++ /dev/null @@ -1,24 +0,0 @@ -/* - * Scilab ( http://www.scilab.org/ ) - This file is part of Scilab - * Copyright (C) 2008-2008 - INRIA - Bruno JOFRET - * - * 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-en.txt - * - */ - -#include "mean.h" -#include "sum.h" - -void zrowmeana(doubleComplex *in, int lines, int columns, doubleComplex *out) { - int i = 0; - - zrowsuma(in, lines, columns, out); - for (i = 0; i < columns; ++i) - { - out[i] = zrdivs(out[i], DoubleComplex((double)lines, 0.0f)); - } -} |