Initial commit
This commit is contained in:
Julien Chevalley
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CMSIS DSP_Lib example arm_class_marks_example for
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Cortex-M0, Cortex-M3, Cortex-M4 with FPU and Cortex-M7 with single precision FPU.
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The example is configured for uVision Simulator
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/* ----------------------------------------------------------------------
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* Copyright (C) 2010-2012 ARM Limited. All rights reserved.
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*
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* $Date: 17. January 2013
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* $Revision: V1.4.0
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*
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* Project: CMSIS DSP Library
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* Title: arm_class_marks_example_f32.c
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*
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* Description: Example code to calculate Minimum, Maximum
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* Mean, std and variance of marks obtained in a class
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*
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* Target Processor: Cortex-M4/Cortex-M3
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* - Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* - Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* - Neither the name of ARM LIMITED nor the names of its contributors
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* may be used to endorse or promote products derived from this
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* software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* -------------------------------------------------------------------- */
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/**
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* @ingroup groupExamples
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*/
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/**
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* @defgroup ClassMarks Class Marks Example
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*
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* \par Description:
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* \par
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* Demonstrates the use the Maximum, Minimum, Mean, Standard Deviation, Variance
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* and Matrix functions to calculate statistical values of marks obtained in a class.
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*
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* \note This example also demonstrates the usage of static initialization.
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*
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* \par Variables Description:
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* \par
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* \li \c testMarks_f32 points to the marks scored by 20 students in 4 subjects
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* \li \c max_marks Maximum of all marks
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* \li \c min_marks Minimum of all marks
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* \li \c mean Mean of all marks
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* \li \c var Variance of the marks
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* \li \c std Standard deviation of the marks
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* \li \c numStudents Total number of students in the class
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*
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* \par CMSIS DSP Software Library Functions Used:
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* \par
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* - arm_mat_init_f32()
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* - arm_mat_mult_f32()
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* - arm_max_f32()
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* - arm_min_f32()
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* - arm_mean_f32()
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* - arm_std_f32()
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* - arm_var_f32()
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*
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* <b> Refer </b>
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* \link arm_class_marks_example_f32.c \endlink
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*
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*/
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/** \example arm_class_marks_example_f32.c
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*/
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#include "arm_math.h"
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#define USE_STATIC_INIT
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/* ----------------------------------------------------------------------
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** Global defines
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** ------------------------------------------------------------------- */
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#define TEST_LENGTH_SAMPLES (20*4)
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/* ----------------------------------------------------------------------
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** List of Marks scored by 20 students for 4 subjects
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** ------------------------------------------------------------------- */
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const float32_t testMarks_f32[TEST_LENGTH_SAMPLES] =
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{
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42.000000, 37.000000, 81.000000, 28.000000,
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83.000000, 72.000000, 36.000000, 38.000000,
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32.000000, 51.000000, 63.000000, 64.000000,
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97.000000, 82.000000, 95.000000, 90.000000,
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66.000000, 51.000000, 54.000000, 42.000000,
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67.000000, 56.000000, 45.000000, 57.000000,
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67.000000, 69.000000, 35.000000, 52.000000,
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29.000000, 81.000000, 58.000000, 47.000000,
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38.000000, 76.000000, 100.000000, 29.000000,
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33.000000, 47.000000, 29.000000, 50.000000,
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34.000000, 41.000000, 61.000000, 46.000000,
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52.000000, 50.000000, 48.000000, 36.000000,
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47.000000, 55.000000, 44.000000, 40.000000,
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100.000000, 94.000000, 84.000000, 37.000000,
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32.000000, 71.000000, 47.000000, 77.000000,
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31.000000, 50.000000, 49.000000, 35.000000,
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63.000000, 67.000000, 40.000000, 31.000000,
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29.000000, 68.000000, 61.000000, 38.000000,
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31.000000, 28.000000, 28.000000, 76.000000,
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55.000000, 33.000000, 29.000000, 39.000000
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};
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/* ----------------------------------------------------------------------
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* Number of subjects X 1
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* ------------------------------------------------------------------- */
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const float32_t testUnity_f32[4] =
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{
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1.000, 1.000, 1.000, 1.000
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};
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/* ----------------------------------------------------------------------
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** f32 Output buffer
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** ------------------------------------------------------------------- */
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static float32_t testOutput[TEST_LENGTH_SAMPLES];
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/* ------------------------------------------------------------------
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* Global defines
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*------------------------------------------------------------------- */
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#define NUMSTUDENTS 20
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#define NUMSUBJECTS 4
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/* ------------------------------------------------------------------
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* Global variables
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*------------------------------------------------------------------- */
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uint32_t numStudents = 20;
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uint32_t numSubjects = 4;
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float32_t max_marks, min_marks, mean, std, var;
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uint32_t student_num;
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/* ----------------------------------------------------------------------------------
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* Main f32 test function. It returns maximum marks secured and student number
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* ------------------------------------------------------------------------------- */
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int32_t main()
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{
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#ifndef USE_STATIC_INIT
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arm_matrix_instance_f32 srcA;
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arm_matrix_instance_f32 srcB;
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arm_matrix_instance_f32 dstC;
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/* Input and output matrices initializations */
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arm_mat_init_f32(&srcA, numStudents, numSubjects, (float32_t *)testMarks_f32);
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arm_mat_init_f32(&srcB, numSubjects, 1, (float32_t *)testUnity_f32);
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arm_mat_init_f32(&dstC, numStudents, 1, testOutput);
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#else
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/* Static Initializations of Input and output matrix sizes and array */
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arm_matrix_instance_f32 srcA = {NUMSTUDENTS, NUMSUBJECTS, (float32_t *)testMarks_f32};
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arm_matrix_instance_f32 srcB = {NUMSUBJECTS, 1, (float32_t *)testUnity_f32};
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arm_matrix_instance_f32 dstC = {NUMSTUDENTS, 1, testOutput};
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#endif
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/* ----------------------------------------------------------------------
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*Call the Matrix multiplication process function
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* ------------------------------------------------------------------- */
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arm_mat_mult_f32(&srcA, &srcB, &dstC);
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/* ----------------------------------------------------------------------
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** Call the Max function to calculate max marks among numStudents
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** ------------------------------------------------------------------- */
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arm_max_f32(testOutput, numStudents, &max_marks, &student_num);
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/* ----------------------------------------------------------------------
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** Call the Min function to calculate min marks among numStudents
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** ------------------------------------------------------------------- */
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arm_min_f32(testOutput, numStudents, &min_marks, &student_num);
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/* ----------------------------------------------------------------------
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** Call the Mean function to calculate mean
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** ------------------------------------------------------------------- */
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arm_mean_f32(testOutput, numStudents, &mean);
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/* ----------------------------------------------------------------------
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** Call the std function to calculate standard deviation
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** ------------------------------------------------------------------- */
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arm_std_f32(testOutput, numStudents, &std);
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/* ----------------------------------------------------------------------
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** Call the var function to calculate variance
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** ------------------------------------------------------------------- */
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arm_var_f32(testOutput, numStudents, &var);
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while (1); /* main function does not return */
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}
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