Add tests for decimate_f64 and add the function to the pack list of functions.

#include "arm_correlate_q31.c"

#include "arm_correlate_q7.c"

#include "arm_fir_decimate_f32.c"

#include "arm_fir_decimate_f64.c"

#include "arm_fir_decimate_fast_q15.c"

#include "arm_fir_decimate_fast_q31.c"

#include "arm_fir_decimate_init_f32.c"

#include "arm_fir_decimate_init_f64.c"

#include "arm_fir_decimate_init_q15.c"

#include "arm_fir_decimate_init_q31.c"

#include "arm_fir_decimate_q15.c"

  @ingroup groupFilters

 */

/**

  @defgroup FIR_decimate Finite Impulse Response (FIR) Decimator

  These functions combine an FIR filter together with a decimator.

  They are used in multirate systems for reducing the sample rate of a signal without introducing aliasing distortion.

  Conceptually, the functions are equivalent to the block diagram below:

  \image html FIRDecimator.gif "Components included in the FIR Decimator functions"

  When decimating by a factor of <code>M</code>, the signal should be prefiltered by a lowpass filter with a normalized

  cutoff frequency of <code>1/M</code> in order to prevent aliasing distortion.

  The user of the function is responsible for providing the filter coefficients.

  The FIR decimator functions provided in the CMSIS DSP Library combine the FIR filter and the decimator in an efficient manner.

  Instead of calculating all of the FIR filter outputs and discarding <code>M-1</code> out of every <code>M</code>, only the

  samples output by the decimator are computed.

  The functions operate on blocks of input and output data.

  <code>pSrc</code> points to an array of <code>blockSize</code> input values and

  <code>pDst</code> points to an array of <code>blockSize/M</code> output values.

  In order to have an integer number of output samples <code>blockSize</code>

  must always be a multiple of the decimation factor <code>M</code>.

  The library provides separate functions for Q15, Q31 and floating-point data types.

  @par           Algorithm:

                   The FIR portion of the algorithm uses the standard form filter:

  <pre>

      y[n] = b[0] * x[n] + b[1] * x[n-1] + b[2] * x[n-2] + ...+ b[numTaps-1] * x[n-numTaps+1]

  </pre>

                   where, <code>b[n]</code> are the filter coefficients.

  @par

                   The <code>pCoeffs</code> points to a coefficient array of size <code>numTaps</code>.

                   Coefficients are stored in time reversed order.

  @par

  <pre>

      {b[numTaps-1], b[numTaps-2], b[N-2], ..., b[1], b[0]}

  </pre>

  @par

                   <code>pState</code> points to a state array of size <code>numTaps + blockSize - 1</code>.

                   Samples in the state buffer are stored in the order:

  @par

  <pre>

      {x[n-numTaps+1], x[n-numTaps], x[n-numTaps-1], x[n-numTaps-2]....x[0], x[1], ..., x[blockSize-1]}

  </pre>

                   The state variables are updated after each block of data is processed, the coefficients are untouched.

  @par           Instance Structure

                   The coefficients and state variables for a filter are stored together in an instance data structure.

                   A separate instance structure must be defined for each filter.

                   Coefficient arrays may be shared among several instances while state variable array should be allocated separately.

                   There are separate instance structure declarations for each of the 3 supported data types.

 @par            Initialization Functions

                   There is also an associated initialization function for each data type.

                   The initialization function performs the following operations:

                   - Sets the values of the internal structure fields.

                   - Zeros out the values in the state buffer.

                   - Checks to make sure that the size of the input is a multiple of the decimation factor.

                   To do this manually without calling the init function, assign the follow subfields of the instance structure:

                   numTaps, pCoeffs, M (decimation factor), pState. Also set all of the values in pState to zero.

  @par

                   Use of the initialization function is optional.

                   However, if the initialization function is used, then the instance structure cannot be placed into a const data section.

                   To place an instance structure into a const data section, the instance structure must be manually initialized.

                   The code below statically initializes each of the 3 different data type filter instance structures

  <pre>

      arm_fir_decimate_instance_f64 S = {M, numTaps, pCoeffs, pState};

      arm_fir_decimate_instance_q31 S = {M, numTaps, pCoeffs, pState};

      arm_fir_decimate_instance_q15 S = {M, numTaps, pCoeffs, pState};

  </pre>

                   where <code>M</code> is the decimation factor; <code>numTaps</code> is the number of filter coefficients in the filter;

                   <code>pCoeffs</code> is the address of the coefficient buffer;

                   <code>pState</code> is the address of the state buffer.

                   Be sure to set the values in the state buffer to zeros when doing static initialization.

  @par           Fixed-Point Behavior

                   Care must be taken when using the fixed-point versions of the FIR decimate filter functions.

                   In particular, the overflow and saturation behavior of the accumulator used in each function must be considered.

                   Refer to the function specific documentation below for usage guidelines.

 */

/**

  @addtogroup FIR_decimate

  @{

    } while (--i);

    /* Set accumulators to zero */

    acc0 = 0.0f;

    acc1 = 0.0f;

    acc2 = 0.0f;

    acc3 = 0.0f;

    acc0 = 0.0;

    acc1 = 0.0;

    acc2 = 0.0;

    acc3 = 0.0;

    /* Initialize state pointer for all the samples */

    px0 = pState;

    } while (--i);

    /* Set accumulator to zero */

    acc0 = 0.0f;

    acc0 = 0.0;

    /* Initialize state pointer */

    px0 = pState;

#include "Test.h"

#include "Pattern.h"

#include "dsp/filtering_functions.h"

class DECIMF64:public Client::Suite

    {

        public:

            DECIMF64(Testing::testID_t id);

            virtual void setUp(Testing::testID_t,std::vector<Testing::param_t>& params,Client::PatternMgr *mgr);

            virtual void tearDown(Testing::testID_t,Client::PatternMgr *mgr);

        private:

            #include "DECIMF64_decl.h"

            Client::Pattern<float64_t> input;

            Client::Pattern<float64_t> coefs;

            Client::Pattern<uint32_t> config;

            Client::LocalPattern<float64_t> output;

            Client::LocalPattern<float64_t> state;

            // Reference patterns are not loaded when we are in dump mode

            Client::RefPattern<float64_t> ref;

            arm_fir_decimate_instance_f64 S;

            //arm_fir_interpolate_instance_f64 SI;

            int q;

            int numTaps;

            int blocksize;

            int refsize;

            arm_status status;

    };

    configq31=Tools.Config(PATTERNDIR,PARAMDIR,"q31")

    configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")

    configf32.setOverwrite(False)

    configf16.setOverwrite(False)

    configq31.setOverwrite(False)

    configq15.setOverwrite(False)

    writeBenchmarks(configf32)

        ref += [q,len(b),len(samples),len(output)]

    config.writeInput(startNb, allsamples)

    config.writeInput(startNb, allcoefs,"Coefs")

    config.writeReference(startNb, alloutput)

    PATTERNDIR = os.path.join("Patterns","DSP","Filtering","DECIM","DECIM")

    PARAMDIR = os.path.join("Parameters","DSP","Filtering","DECIM","DECIM")

    configf64=Tools.Config(PATTERNDIR,PARAMDIR,"f64")

    configf32=Tools.Config(PATTERNDIR,PARAMDIR,"f32")

    configf16=Tools.Config(PATTERNDIR,PARAMDIR,"f16")

    configq31=Tools.Config(PATTERNDIR,PARAMDIR,"q31")

    configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")

    writeTests(configf32,0)

    writeTests(configf16,16)

    writeTests(configq31,31)

    writeTests(configq15,15)

    configf64.setOverwrite(False)

    configf32.setOverwrite(False)

    configf16.setOverwrite(False)

    configq31.setOverwrite(False)

    configq15.setOverwrite(False)

    writeTests(configf64,Tools.F64)

    #writeTests(configf32,0)

    #writeTests(configf16,16)

    #writeTests(configq31,31)

    #writeTests(configq15,15)

if __name__ == '__main__':

  generateBenchmarkPatterns()

    configq15=Tools.Config(PATTERNDIR,PARAMDIR,"q15")

    configq7=Tools.Config(PATTERNDIR,PARAMDIR,"q7")

    configf64.setOverwrite(False)

    configf32.setOverwrite(False)

    configf16.setOverwrite(False)

    configq31.setOverwrite(False)