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%%%%  File           : cordic_iterative_test.m                          %%%%

%%%%  Project        : YAC (Yet Another CORDIC Core)                    %%%%

%%%%  Creation       : Feb. 2014                                        %%%%

%%%%  Limitations    :                                                  %%%%

%%%%  Platform       : Linux, Mac, Windows                              %%%%

%%%%  Target         : Octave, Matlab                                   %%%%

%%%%                                                                    %%%%

%%%%  Author(s):     : Christian Haettich                               %%%%

%%%%  Email          : feddischson@opencores.org                        %%%%

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%%%%                                                                    %%%%

%%%%  Description                                                       %%%%

%%%%        Script to test/analyze the cordic C implementation          %%%%

%%%%        and to generate stimulus data for RTL simulation.           %%%%

%%%%        This created data is used to ensure, that the C             %%%%

%%%%        implementation behaves the same than the VHDL               %%%%

%%%%        implementation.                                             %%%%

%%%%                                                                    %%%%

<<<<<<< HEAD

<<<<<<< HEAD

=======

>>>>>>> Updated C and RTL model as well as the documentation

%%%%        Three tests are implemented:                                %%%%

%%%%          - Random test values                                      %%%%

%%%%          - Linear increasing values                                %%%%

%%%%          - Limit values                                            %%%%

%%%%                                                                    %%%%

%%%%                                                                    %%%%

%%%%        Please do  'mex cordic_iterative.c' to create               %%%%

%%%%        the cordic_iterative.mex.                                   %%%%

<<<<<<< HEAD

=======

>>>>>>> initial commit

=======

>>>>>>> Updated C and RTL model as well as the documentation

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%%%%%                                                                  %%%%%

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%%%%  TODO                                                              %%%%

<<<<<<< HEAD

<<<<<<< HEAD

%%%%        The linear test is not complete                             %%%%

=======

%%%%        Some documentation and function description                 %%%%

>>>>>>> initial commit

=======

%%%%        The linear test is not complete                             %%%%

>>>>>>> Updated C and RTL model as well as the documentation

%%%%                                                                    %%%%

%%%%                                                                    %%%%

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%%%%                                                                    %%%%

%%%%                  Copyright Notice                                  %%%%

%%%%                                                                    %%%%

%%%% This file is part of YAC - Yet Another CORDIC Core                 %%%%

%%%% Copyright (c) 2014, Author(s), All rights reserved.                %%%%

%%%%                                                                    %%%%

%%%% YAC is free software; you can redistribute it and/or               %%%%

%%%% modify it under the terms of the GNU Lesser General Public         %%%%

%%%% License as published by the Free Software Foundation; either       %%%%

%%%% version 3.0 of the License, or (at your option) any later version. %%%%

%%%%                                                                    %%%%

%%%% YAC is distributed in the hope that it will be useful,             %%%%

%%%% but WITHOUT ANY WARRANTY; without even the implied warranty of     %%%%

%%%% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU  %%%%

%%%% Lesser General Public License for more details.                    %%%%

%%%%                                                                    %%%%

%%%% You should have received a copy of the GNU Lesser General Public   %%%%

%%%% License along with this library. If not, download it from          %%%%

%%%% http://www.gnu.org/licenses/lgpl                                   %%%%

%%%%                                                                    %%%%

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<<<<<<< HEAD

<<<<<<< HEAD

function cordic_iterative_test( )

=======

=======

>>>>>>> Updated C and RTL model as well as the documentation

function cordic_iterative_test( )

>>>>>>> initial commit

% global flags/values, they are static

% through the whole script and defined below

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

%

% flags: they are also define in cordic_iterative.c and

%        cordic_iterative_pkg.vhd

C_FLAG_VEC_ROT  = 2^3;

C_FLAG_ATAN_3   = 2^2;

C_MODE_CIRC     = 0;

C_MODE_LIN      = 1;

C_MODE_HYP      = 2;

% initialize the random-generator's seed

rand('seed', 1633);

% cordic setup:

% this must fit to the testbench

XY_WIDTH   = 25;

ANGLEWIDTH = 25;

GUARDBITS  = 2;

RM_GAIN    = 5;

% Number of tests, which are run

N_TESTS    = 10000;

% open test file

tb_fid = fopen( './tb_data.txt', 'w' );

<<<<<<< HEAD

<<<<<<< HEAD

%tb_fid = 0;

%

% run test, which uses random values

run_random_test( N_TESTS, tb_fid );

%

% run tests, which test limits

run_limit_test( tb_fid );

%

% run linear value test

run_linear_test( 1000, tb_fid );

% close file

if tb_fid > 0

    fclose( tb_fid );

end

end

function run_limit_test( tb_fid )

%RUN_LIMIT_TEST Test the range limit

%

% run_limit_test( fid )

%

% This function is used to generate a test pattern

% with values, which are at the range limit.

% This values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file.

%

% The argument fid is the file-descriptor of the testbench pattern

% file.

%

data_a = [ 0 1 0 1 -1  0 -1  1 -1 ];

data_b = [ 0 0 1 1  0 -1 -1 -1  1 ];

data_c = [ 0 0 0 0  0  0  0  0  0 ...

           1 1 1 1  1  1  1  1  1 ...

           -1 -1 -1 -1 -1 -1 -1 -1 -1 ];

data_d = data_a * pi;

data_a_div = [ 0.5 ,1 -0.5, -1, -0.5, -1 ];

data_b_div = [ 1   ,1,  1,   1,   -1, -1 ];

[ ~, ~, atan_err, abs_err, it_1 ]   = ccart2pol( data_a, data_b, tb_fid );

[ ~, ~, sin_err,  cos_err, it_2 ]   = cpol2cart( data_d, data_b, tb_fid );

[ ~, ~, x_err, y_err, it_3 ]        = crot( [ data_a, data_a, data_a], ...

                                            [ data_b, data_b, data_b], ...

                                              data_c, tb_fid );

[ ~, div_err, it_4 ]                = cdiv( data_a_div, data_b_div, tb_fid );

[ ~, mul_err, it_5 ]                = cmul( data_a, data_b, tb_fid  );

print_result_info(    ...

    atan_err,   it_1, ...

    abs_err,    it_1, ...

    sin_err,    it_2, ...

    cos_err,    it_2, ...

    x_err,      it_3, ...

    y_err,      it_3, ...

    div_err,    it_4, ...

    mul_err,    it_5, ...

    0,  0, ...

    0,  0, ...

    0,  0, ...

    0,  0, ...

    'Limit Value Test' );

=======

=======

%tb_fid = 0;

>>>>>>> Updated C and RTL model as well as the documentation

%

% run test, which uses random values

run_random_test( N_TESTS, tb_fid );

%

% run tests, which test limits

run_limit_test( tb_fid );

%

% run linear value test

run_linear_test( 1000, tb_fid );

% close file

if tb_fid > 0

    fclose( tb_fid );

end

end

function run_limit_test( tb_fid )

%RUN_LIMIT_TEST Test the range limit

%

% run_limit_test( fid )

%

% This function is used to generate a test pattern

% with values, which are at the range limit.

% This values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file.

%

% The argument fid is the file-descriptor of the testbench pattern

% file.

%

<<<<<<< HEAD

>>>>>>> initial commit

end

<<<<<<< HEAD

function run_linear_test( N_TESTS, tb_fid )

%RUN_LINEAR_TEST Generates a linear test pattern

%

% run_linear_test( N, fid )

%

% This function is used to generate linear increasing test

% values.

% These values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file. In addition, the result is plotted.

%

% NOTE: only the hyperbolic functions are processed at the moment.

% This function needs to be extended in future.

%

%

% The argument fid is the file-descriptor of the testbench pattern

% file. The argument N defines the number of values, which are processed.

%

%

data_a_h = ones( 1, N_TESTS );

data_b_h = linspace( -1, 1, N_TESTS ) * 0.78;

data_c_h = linspace( -1, 1, N_TESTS );

[ atanh_res, sqrt_res, atanh_err, sqrt_err, it_6 ] = catanh( data_a_h, data_b_h, tb_fid );

[ sinh_res, cosh_res, sinh_err, cosh_err, it_7 ]   = csinhcosh( data_c_h, tb_fid );

=======

data_a = [ 0 1 0 1 -1  0 -1  1 -1 ];

data_b = [ 0 0 1 1  0 -1 -1 -1  1 ];

data_c = [ 0 0 0 0  0  0  0  0  0 ...

           1 1 1 1  1  1  1  1  1 ...

           -1 -1 -1 -1 -1 -1 -1 -1 -1 ];

data_d = data_a * pi;

data_a_div = [ 0.5 ,1 -0.5, -1, -0.5, -1 ];

data_b_div = [ 1   ,1,  1,   1,   -1, -1 ];

[ ~, ~, atan_err, abs_err, it_1 ]   = ccart2pol( data_a, data_b, tb_fid );

[ ~, ~, sin_err,  cos_err, it_2 ]   = cpol2cart( data_d, data_b, tb_fid );

[ ~, ~, x_err, y_err, it_3 ]        = crot( [ data_a, data_a, data_a], ...

                                            [ data_b, data_b, data_b], ...

                                              data_c, tb_fid );

[ ~, div_err, it_4 ]                = cdiv( data_a_div, data_b_div, tb_fid );

[ ~, mul_err, it_5 ]                = cmul( data_a, data_b, tb_fid  );

print_result_info(    ...

    atan_err,   it_1, ...

    abs_err,    it_1, ...

    sin_err,    it_2, ...

    cos_err,    it_2, ...

    x_err,      it_3, ...

    y_err,      it_3, ...

    div_err,    it_4, ...

    mul_err,    it_5, ...

    0,  0, ...

    0,  0, ...

    0,  0, ...

    0,  0, ...

    'Limit Value Test' );

>>>>>>> Updated C and RTL model as well as the documentation

figure; plot( data_b_h, atanh_res ); title( 'atanh' );

figure; plot( data_b_h, atanh_err ); title( 'atanh-error' );

figure; plot( data_c_h, sinh_res, data_c_h, cosh_res ); title( 'sinh and cosh' );

figure; plot( data_c_h, sinh_err, data_c_h, cosh_err ); title( 'sinh and cosh errors' );

end

<<<<<<< HEAD

function run_random_test( N_TESTS, tb_fid )

%RUN_RANDOM_TEST Generates a random test pattern

%

% run_random_test( N, fid )

%

% This function is used to generate random test

% values (uniform distributed).

% These values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file.

=======

function run_linear_test( N_TESTS, tb_fid )

%RUN_LINEAR_TEST Generates a linear test pattern

%

% run_linear_test( N, fid )

%

% This function is used to generate linear increasing test

% values.

% These values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file. In addition, the result is plotted.

%

% NOTE: only the hyperbolic functions are processed at the moment.

% This function needs to be extended in future.

>>>>>>> Updated C and RTL model as well as the documentation

%

%

% The argument fid is the file-descriptor of the testbench pattern

% file. The argument N defines the number of values, which are processed.

%

%

<<<<<<< HEAD

data_a = -1 + 2 .* rand( 1, N_TESTS );

data_b = -1 + 2 .* rand( 1, N_TESTS );

data_c = -1 + 2 .* rand( 1, N_TESTS );

data_d = -pi + 2*pi .* rand( 1, N_TESTS );

=======

function run_random_test( N_TESTS, tb_fid )

=======

data_a_h = ones( 1, N_TESTS );

data_b_h = linspace( -1, 1, N_TESTS ) * 0.78;

data_c_h = linspace( -1, 1, N_TESTS );

[ atanh_res, sqrt_res, atanh_err, sqrt_err, it_6 ] = catanh( data_a_h, data_b_h, tb_fid );

[ sinh_res, cosh_res, sinh_err, cosh_err, it_7 ]   = csinhcosh( data_c_h, tb_fid );

figure; plot( data_b_h, atanh_res ); title( 'atanh' );

figure; plot( data_b_h, atanh_err ); title( 'atanh-error' );

figure; plot( data_c_h, sinh_res, data_c_h, cosh_res ); title( 'sinh and cosh' );

figure; plot( data_c_h, sinh_err, data_c_h, cosh_err ); title( 'sinh and cosh errors' );

end

>>>>>>> Updated C and RTL model as well as the documentation

function run_random_test( N_TESTS, tb_fid )

%RUN_RANDOM_TEST Generates a random test pattern

%

% run_random_test( N, fid )

%

% This function is used to generate random test

% values (uniform distributed).

% These values are then processed by the fixed-point YAC

% implementation. All input and outputs are logged into

% a testbench pattern file.

%

%

% The argument fid is the file-descriptor of the testbench pattern

% file. The argument N defines the number of values, which are processed.

%

%

data_a = -1 + 2 .* rand( 1, N_TESTS );

data_b = -1 + 2 .* rand( 1, N_TESTS );

<<<<<<< HEAD

>>>>>>> initial commit

=======

data_c = -1 + 2 .* rand( 1, N_TESTS );

data_d = -pi + 2*pi .* rand( 1, N_TESTS );

>>>>>>> Updated C and RTL model as well as the documentation

% adapat data for division

data_a_div = data_a;

data_b_div = data_b;

swap_div   = ( data_b ./ data_a ) >= 2 | ( data_b ./ data_a ) < -2 ;

data_a_div( swap_div ) = data_b( swap_div );

data_b_div( swap_div ) = data_a( swap_div );

data_a_h   = ones( size( data_a ) );

<<<<<<< HEAD

<<<<<<< HEAD

data_b_h   = data_b .* 0.80694; %0.78;

=======

data_b_h   = data_b .* 0.78;

>>>>>>> initial commit

=======

data_b_h   = data_b .* 0.80694; %0.78;

>>>>>>> Updated C and RTL model as well as the documentation

[ ~, ~, atan_err, abs_err, it_1 ]   = ccart2pol( data_a, data_b, tb_fid );

<<<<<<< HEAD

<<<<<<< HEAD

=======

>>>>>>> Updated C and RTL model as well as the documentation

[ ~, ~, sin_err,  cos_err, it_2 ]   = cpol2cart( data_d, data_b, tb_fid );

[ ~, ~, x_err, y_err, it_3 ]        = crot( data_a, data_b, data_c, tb_fid );

[ ~, div_err, it_4 ]                = cdiv( data_a_div, data_b_div, tb_fid );

[ ~, mul_err, it_5 ]                = cmul( data_a, data_b, tb_fid  );

[ ~, ~, atanh_err, sqrt_err, it_6 ] = catanh( data_a_h, data_b_h, tb_fid );

[ ~, ~, sinh_err, cosh_err, it_7 ]  = csinhcosh( data_a, tb_fid );

print_result_info(  atan_err,   it_1, ...

                    abs_err,    it_1, ...

                    sin_err,    it_2, ...

                    cos_err,    it_2, ...

                    x_err,      it_3, ...

                    y_err,      it_3, ...

                    div_err,    it_4, ...

                    mul_err,    it_5, ...

                    atanh_err,  it_6, ...

                    sqrt_err,   it_6, ...

                    sinh_err,   it_7, ...

                    cosh_err,   it_7, ...

                    'Random Value Test' );

end

function print_result_info( ...

    atan_err,   atan_it,    ...

    abs_err,    abs_it,     ...

    sin_err,    sin_it,     ...

    cos_err,    cos_it,     ...

    x_err,      x_it,       ...

    y_err,      y_it,       ...

    div_err,    div_it,     ...

    mul_err,    mul_it,     ...

    atanh_err,  atanh_it,   ...

    sqrt_err,   sqrt_it,    ...

    sinh_err,   sinh_it,    ...

    cosh_err,   cosh_it,    ...

    title )

<<<<<<< HEAD

fprintf( ' ___________________________________________________________________\n' );

fprintf( '                  %s\n', title);

fprintf( ' -----+-------------------+--------------------+-------------------\n'   );

fprintf( '      |     max error     |   mean error       |  max iterations  \n'   );

fprintf( ' atan | % .14f | % .14f  | %.5f \n', max( atan_err  ), mean( atan_err  ), max( atan_it   ) );

fprintf( ' abs  | % .14f | % .14f  | %.5f \n', max( abs_err   ), mean( abs_err   ), max( abs_it    ) );

fprintf( ' sin  | % .14f | % .14f  | %.5f \n', max( sin_err   ), mean( sin_err   ), max( sin_it    ) );

fprintf( ' cos  | % .14f | % .14f  | %.5f \n', max( cos_err   ), mean( cos_err   ), max( cos_it    ) );

fprintf( ' x    | % .14f | % .14f  | %.5f \n', max( x_err     ), mean( x_err     ), max( x_it      ) );

fprintf( ' y    | % .14f | % .14f  | %.5f \n', max( y_err     ), mean( y_err     ), max( y_it      ) );

fprintf( ' div  | % .14f | % .14f  | %.5f \n', max( div_err   ), mean( div_err   ), max( div_it    ) );

fprintf( ' mul  | % .14f | % .14f  | %.5f \n', max( mul_err   ), mean( mul_err   ), max( mul_it    ) );

fprintf( ' atanh| % .14f | % .14f  | %.5f \n', max( atanh_err ), mean( atanh_err ), max( atanh_it  ) );

fprintf( ' sqrt | % .14f | % .14f  | %.5f \n', max( sqrt_err  ), mean( sqrt_err  ), max( sqrt_it   ) );

fprintf( ' sinh | % .14f | % .14f  | %.5f \n', max( sinh_err  ), mean( sinh_err  ), max( sinh_it   ) );

fprintf( ' cosh | % .14f | % .14f  | %.5f \n', max( cosh_err  ), mean( cosh_err  ), max( cosh_it   ) );

end

=======

[ ~, ~, sin_err,  cos_err, it_2 ]   = cpol2cart( data_a, data_b, tb_fid );

[ ~, div_err, it_3 ]                = cdiv( data_a_div, data_b_div, tb_fid );

[ ~, mul_err, it_4 ]                = cmul( data_a, data_b, tb_fid  );

[ ~, ~, atanh_err, sqrt_err, it_5 ] = catanh( data_a_h, data_b_h, tb_fid );

[ ~, ~, sinh_err, cosh_err, it_6 ]  = csinhcosh( data_a, tb_fid );

=======

>>>>>>> Updated C and RTL model as well as the documentation

fprintf( ' ___________________________________________________________________\n' );

fprintf( '                  %s\n', title);

fprintf( ' -----+-------------------+--------------------+-------------------\n'   );

fprintf( '      |     max error     |   mean error       |  max iterations  \n'   );

fprintf( ' atan | % .14f | % .14f  | %.5f \n', max( atan_err  ), mean( atan_err  ), max( atan_it   ) );

fprintf( ' abs  | % .14f | % .14f  | %.5f \n', max( abs_err   ), mean( abs_err   ), max( abs_it    ) );

fprintf( ' sin  | % .14f | % .14f  | %.5f \n', max( sin_err   ), mean( sin_err   ), max( sin_it    ) );

fprintf( ' cos  | % .14f | % .14f  | %.5f \n', max( cos_err   ), mean( cos_err   ), max( cos_it    ) );

fprintf( ' x    | % .14f | % .14f  | %.5f \n', max( x_err     ), mean( x_err     ), max( x_it      ) );

fprintf( ' y    | % .14f | % .14f  | %.5f \n', max( y_err     ), mean( y_err     ), max( y_it      ) );

fprintf( ' div  | % .14f | % .14f  | %.5f \n', max( div_err   ), mean( div_err   ), max( div_it    ) );

fprintf( ' mul  | % .14f | % .14f  | %.5f \n', max( mul_err   ), mean( mul_err   ), max( mul_it    ) );

fprintf( ' atanh| % .14f | % .14f  | %.5f \n', max( atanh_err ), mean( atanh_err ), max( atanh_it  ) );

fprintf( ' sqrt | % .14f | % .14f  | %.5f \n', max( sqrt_err  ), mean( sqrt_err  ), max( sqrt_it   ) );

fprintf( ' sinh | % .14f | % .14f  | %.5f \n', max( sinh_err  ), mean( sinh_err  ), max( sinh_it   ) );

fprintf( ' cosh | % .14f | % .14f  | %.5f \n', max( cosh_err  ), mean( cosh_err  ), max( cosh_it   ) );

end

>>>>>>> initial commit

function [sinh_res, cosh_res, sinh_err, cosh_err, it ]= csinhcosh( th, fid )

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

xi = repmat( (2^(XY_WIDTH-1)-1), size( th ) );

yi = zeros( 1, length( th ) );

ai = round( th .* (2^(ANGLEWIDTH-1)-1) );

mode = C_MODE_HYP;

% cordic version

[ rcosh rsinh ra, it ] = cordic_iterative( ...

                                           xi,          ...

                                           yi,          ...

                                           ai,          ...

                                           mode,        ...

                                           XY_WIDTH,    ...

                                           ANGLEWIDTH,  ...

                                           GUARDBITS,   ...

                                           RM_GAIN );

cosh_res = rcosh  ./ (   2^(XY_WIDTH-1)-1 );

sinh_res = rsinh  ./ (   2^(XY_WIDTH-1)-1 );

cosh_m = cosh( th );

sinh_m = sinh( th );

sinh_err = abs(sinh_res - sinh_m );

cosh_err = abs(cosh_res - cosh_m );

% write TB data

write_tb( fid, xi, yi, ai, rcosh, rsinh, ra, mode );

end

function [atan_res, abs_res, atan_err, abs_err, it ]  = catanh( x, y, fid )

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

if( size( x ) ~= size( y ) )

    error( 'size error' )

end

ai = zeros( size( x ) );

xi = round( x * (2^(XY_WIDTH-1)-1) );

yi = round( y * (2^(XY_WIDTH-1)-1) );

mode = C_FLAG_VEC_ROT + C_MODE_HYP;

% cordic version

[ rx, ry, ra, it ] = cordic_iterative( xi,          ...

                                  yi,          ...

                                  ai,          ...

                                  mode,        ...

                                  XY_WIDTH,    ...

                                  ANGLEWIDTH,  ...

                                  GUARDBITS,   ...

                                  RM_GAIN );

% matlab version

m_th = atanh( y ./ x );

m_r  = sqrt( x.^2 - y.^2 );

% comparison

atan_res = ra ./ 2^( (ANGLEWIDTH)-1);

abs_res  = rx ./ ( 2^(XY_WIDTH-1) -1 );

atan_err = abs( m_th - atan_res );

abs_err  = abs( m_r  -  abs_res );

% write TB data

write_tb( fid, xi, yi, ai, rx, ry, ra, mode );

end

function [mul_res, mul_err, it ] = cmul( x, y, fid )

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

if( size( x ) ~= size( y ) )

    error( 'size error' )

end

xi = round( x * ( 2^(XY_WIDTH-1) -1 ) );

ai = round( y * ( 2^(XY_WIDTH-1) -1 ) );

yi = zeros( size( x ) );

mode = C_MODE_LIN;

% cordic version

[ rx, rmul, ra, it ] = cordic_iterative( xi,          ...

                                        yi,          ...

                                        ai,          ...

                                        mode,        ...

                                        XY_WIDTH,    ...

                                        ANGLEWIDTH,  ...

                                        GUARDBITS,   ...

                                        RM_GAIN );

mul_res  = rmul ./ (2^(ANGLEWIDTH-1)-1);

mul_err  = abs( y.*x -  mul_res );

% write TB data

write_tb( fid, xi, yi, ai, rx, rmul, ra, mode )

end

function [div_res, div_err, it ] = cdiv( x, y, fid )

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

if( size( x ) ~= size( y ) )

    error( 'size error' )

end

xi = round( x * ( 2^(XY_WIDTH-1) -1 ) );

yi = round( y * ( 2^(XY_WIDTH-1) -1 ) );

ai = zeros( size( x ) );

mode = C_FLAG_VEC_ROT + C_MODE_LIN;

% cordic version

[ rx, ry, rdiv, it ] = cordic_iterative( xi,          ...

                                  yi,          ...

                                  ai,          ...

                                  mode,        ...

                                  XY_WIDTH,    ...

                                  ANGLEWIDTH,  ...

                                  GUARDBITS,   ...

                                  RM_GAIN );

div_res  = rdiv ./ (2^(ANGLEWIDTH-1)-1);

div_err  = abs( y./x -  div_res );

% write TB data

write_tb( fid, xi, yi, ai, rx, ry, rdiv, mode )

end

<<<<<<< HEAD

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=======

>>>>>>> Updated C and RTL model as well as the documentation

function [x_res, y_res, x_err, y_err, it ] = crot( x, y, th, fid )

%

% does a multiplication with exp( th * i )

% and therefore, a rotation of the complex input value x + yi where th

% defines the rotation angle

%

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

xi = round( x * ( 2^(XY_WIDTH-1) -1 ) );

yi = round( y * ( 2^(XY_WIDTH-1) -1 ) );

ai = round( th .* (2^(ANGLEWIDTH-1)-1) );

mode = C_MODE_CIRC;

[ rx ry ra, it ] = cordic_iterative( ...

                                  xi,          ...

                                  yi,          ...

                                  ai,          ...

                                  mode,        ...

                                  XY_WIDTH,    ...

                                  ANGLEWIDTH,  ...

                                  GUARDBITS,   ...

                                  RM_GAIN );

tmp = ( x + 1i * y ) .* exp( i * th );

x_res = rx  ./ (   2^(XY_WIDTH-1)-1 );

y_res = ry  ./ (   2^(XY_WIDTH-1)-1 );

y_err = abs(x_res - real(tmp) );

x_err = abs(y_res - imag(tmp) );

% write TB data

write_tb( fid, xi, yi, ai, rx, ry, ra, mode )

end

function [sin_res, cos_res, sin_err, cos_err, it ]= cpol2cart( th, r, fid )

%

% does the Matlab equivalent pol2cart

%

<<<<<<< HEAD

=======

function [sin_res, cos_res, sin_err, cos_err, it ]= cpol2cart( th, r, fid )

>>>>>>> initial commit

=======

>>>>>>> Updated C and RTL model as well as the documentation

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

xi = r .* (2^(XY_WIDTH-1)-1);

yi = zeros( 1, length( th ) );

ai = round( th .* (2^(ANGLEWIDTH-1)-1) );

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mode = C_MODE_CIRC;

=======

mode = C_MODE_CIRC;

% cordic version

>>>>>>> initial commit

=======

mode = C_MODE_CIRC;

>>>>>>> Updated C and RTL model as well as the documentation

[ rcos rsin ra, it ] = cordic_iterative( ...

                                  xi,          ...

                                  yi,          ...

                                  ai,          ...

                                  mode,        ...

                                  XY_WIDTH,    ...

                                  ANGLEWIDTH,  ...

                                  GUARDBITS,   ...

                                  RM_GAIN );

cos_res = rcos  ./ (   2^(XY_WIDTH-1)-1 );

sin_res = rsin  ./ (   2^(XY_WIDTH-1)-1 );

[ cos_m, sin_m ] = pol2cart( th, r );

sin_err = abs(sin_res - sin_m );

cos_err = abs(cos_res - cos_m );

% write TB data

write_tb( fid, xi, yi, ai, rcos, rsin, ra, mode )

end

<<<<<<< HEAD

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=======

>>>>>>> initial commit

=======

>>>>>>> Updated C and RTL model as well as the documentation

function [atan_res, abs_res, atan_err, abs_err, it ]  = ccart2pol( x, y, fid )

global C_FLAG_VEC_ROT C_FLAG_ATAN_3 C_MODE_CIRC C_MODE_LIN C_MODE_HYP

global XY_WIDTH ANGLEWIDTH GUARDBITS RM_GAIN

if( size( x ) ~= size( y ) )

    error( 'size error' )

end

ai = zeros( size( x ) );

xi = round( x * (2^(XY_WIDTH-1)-1) );

yi = round( y * (2^(XY_WIDTH-1)-1) );

mode = C_FLAG_VEC_ROT + C_MODE_CIRC;

% cordic version

[ rx, ry, ra, it ] = cordic_iterative( xi,          ...

                                  yi,          ...

                                  ai,          ...

                                  mode,        ...

                                  XY_WIDTH,    ...

                                  ANGLEWIDTH,  ...

                                  GUARDBITS,   ...

                                  RM_GAIN );

<<<<<<< HEAD

<<<<<<< HEAD

=======

>>>>>>> Updated C and RTL model as well as the documentation

% matlab version:

m_th = atan2( y,  x );

m_r  = sqrt( x.^2 + y.^2 );

<<<<<<< HEAD

=======

% matlab version

[m_th, m_r ] = cart2pol( x, y );

>>>>>>> initial commit

=======

>>>>>>> Updated C and RTL model as well as the documentation

% comparison

atan_res = ra ./ 2^( (ANGLEWIDTH)-1);

abs_res  = rx ./ ( 2^(XY_WIDTH-1) -1 );

atan_err = abs( m_th - atan_res );

abs_err  = abs( m_r  -  abs_res );

<<<<<<< HEAD

<<<<<<< HEAD

% TODO: ATAN oder ATAN2  atan( 0 / x ) != atan2( 0, x )!!!!

=======

>>>>>>> initial commit

=======

% TODO: ATAN oder ATAN2  atan( 0 / x ) != atan2( 0, x )!!!!

>>>>>>> Updated C and RTL model as well as the documentation

% write TB data

write_tb( fid, xi, yi, ai, rx, ry, ra, mode )

end