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 */
}
void FloatArray::getMin(float* value, int* index){
/// @note When built for ARM Cortex-M processor series, this method uses the optimized <a href="http://www.keil.com/pack/doc/CMSIS/General/html/index.html">CMSIS library</a>
#ifdef ARM_CORTEX
unsigned long idx;
arm_min_f32(data, size, value, &idx);
*index = (int)idx;
#else
*value=data[0];
*index=0;
for(int n=1; n<size; n++){
float currentValue=data[n];
if(currentValue<*value){
*value=currentValue;
*index=n;
}
}
#endif
}
int32_t main(void)
{
uint32_t i;
arm_status status;
uint32_t index;
float32_t minValue;
/* Initialize the LMSNorm data structure */
arm_lms_norm_init_f32(&lmsNorm_instance, NUMTAPS, lmsNormCoeff_f32, lmsStateF32, MU, BLOCKSIZE);
/* Initialize the FIR data structure */
arm_fir_init_f32(&LPF_instance, NUMTAPS, (float32_t *)FIRCoeff_f32, firStateF32, BLOCKSIZE);
/* ----------------------------------------------------------------------
* Loop over the frames of data and execute each of the processing
* functions in the system.
* ------------------------------------------------------------------- */
for(i=0; i < NUMFRAMES; i++)
{
/* Read the input data - uniformly distributed random noise - into wire1 */
arm_copy_f32(testInput_f32 + (i * BLOCKSIZE), wire1, BLOCKSIZE);
/* Execute the FIR processing function. Input wire1 and output wire2 */
arm_fir_f32(&LPF_instance, wire1, wire2, BLOCKSIZE);
/* Execute the LMS Norm processing function*/
arm_lms_norm_f32(&lmsNorm_instance, /* LMSNorm instance */
wire1, /* Input signal */
wire2, /* Reference Signal */
wire3, /* Converged Signal */
err_signal, /* Error Signal, this will become small as the signal converges */
BLOCKSIZE); /* BlockSize */
/* apply overall gain */
arm_scale_f32(wire3, 5, wire3, BLOCKSIZE); /* in-place buffer */
}
status = ARM_MATH_SUCCESS;
/* -------------------------------------------------------------------------------
* Test whether the error signal has reached towards 0.
* ----------------------------------------------------------------------------- */
arm_abs_f32(err_signal, err_signal, BLOCKSIZE);
arm_min_f32(err_signal, BLOCKSIZE, &minValue, &index);
if (minValue > DELTA_ERROR)
{
status = ARM_MATH_TEST_FAILURE;
}
/* ----------------------------------------------------------------------
* Test whether the filter coefficients have converged.
* ------------------------------------------------------------------- */
arm_sub_f32((float32_t *)FIRCoeff_f32, lmsNormCoeff_f32, lmsNormCoeff_f32, NUMTAPS);
arm_abs_f32(lmsNormCoeff_f32, lmsNormCoeff_f32, NUMTAPS);
arm_min_f32(lmsNormCoeff_f32, NUMTAPS, &minValue, &index);
if (minValue > DELTA_COEFF)
{
status = ARM_MATH_TEST_FAILURE;
}
/* ----------------------------------------------------------------------
* Loop here if the signals did not pass the convergence check.
* This denotes a test failure
* ------------------------------------------------------------------- */
if( status != ARM_MATH_SUCCESS)
{
while(1);
}
}
