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