3Copyright (C) 1996, 1997, 1999, 2000, 2002, 2004, 2005, 2006, 2007,
4 2008, 2009 John W. Eaton
6This file is part of Octave.
8Octave is free software; you can redistribute it and/or modify it
9under the terms of the GNU General Public License as published by the
10Free Software Foundation; either version 3 of the License, or (at your
11option) any later version.
13Octave is distributed in the hope that it will be useful, but WITHOUT
14ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
15FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
18You should have received a copy of the GNU General Public License
19along with Octave; see the file COPYING. If not, see
20<http://www.gnu.org/licenses/>.
24// Based on Tony Richardson's filter.m.
26// Originally translated to C++ by KH (Kurt.Hornik@wu-wien.ac.at)
27// with help from Fritz Leisch and Andreas Weingessel on Oct 20, 1994.
29// Rewritten to use templates to handle both real and complex cases by
30// jwe, Wed Nov 1 19:15:29 1995.
42#if !defined (CXX_NEW_FRIEND_TEMPLATE_DECL)
44filter (MArray<double>&, MArray<double>&, MArrayN<double>&, int dim);
46extern MArrayN<Complex>
47filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&, int dim);
50filter (MArray<float>&, MArray<float>&, MArrayN<float>&, int dim);
52extern MArrayN<FloatComplex>
53filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&, int dim);
58filter (MArray<T>& b, MArray<T>& a, MArrayN<T>& x, MArrayN<T>& si,
63 octave_idx_type a_len = a.length ();
64 octave_idx_type b_len = b.length ();
66 octave_idx_type ab_len = a_len > b_len ? a_len : b_len;
68 b.resize (ab_len, 0.0);
70 a.resize (ab_len, 0.0);
74 if (norm == static_cast<T>(0.0))
76 error ("filter: the first element of a must be non-zero");
80 dim_vector x_dims = x.dims ();
81 if (dim < 0 || dim > x_dims.length ())
83 error ("filter: filtering over invalid dimension");
87 octave_idx_type x_len = x_dims(dim);
89 dim_vector si_dims = si.dims ();
90 octave_idx_type si_len = si_dims(0);
92 if (si_len != ab_len - 1)
94 error ("filter: first dimension of si must be of length max (length (a), length (b)) - 1");
98 if (si_dims.length () != x_dims.length ())
100 error ("filter: dimensionality of si and x must agree");
104 octave_idx_type si_dim = 0;
105 for (octave_idx_type i = 0; i < x_dims.length (); i++)
113 if (si_dims(++si_dim) != x_dims(i))
115 error ("filter: dimensionality of si and x must agree");
120 if (norm != static_cast<T>(1.0))
126 if (a_len <= 1 && si_len <= 0)
129 y.resize (x_dims, 0.0);
132 for (int i = 0; i < dim; i++)
133 x_stride *= x_dims(i);
135 octave_idx_type x_num = x_dims.numel () / x_len;
136 for (octave_idx_type num = 0; num < x_num; num++)
138 octave_idx_type x_offset;
140 x_offset = num * x_len;
143 octave_idx_type x_offset2 = 0;
145 while (x_offset >= x_stride)
147 x_offset -= x_stride;
150 x_offset += x_offset2 * x_stride * x_len;
152 octave_idx_type si_offset = num * si_len;
156 T *py = y.fortran_vec ();
157 T *psi = si.fortran_vec ();
159 const T *pa = a.data ();
160 const T *pb = b.data ();
161 const T *px = x.data ();
165 for (octave_idx_type i = 0, idx = x_offset; i < x_len; i++, idx += x_stride)
167 py[idx] = psi[0] + pb[0] * px[idx];
171 for (octave_idx_type j = 0; j < si_len - 1; j++)
175 psi[j] = psi[j+1] - pa[j+1] * py[idx] + pb[j+1] * px[idx];
178 psi[si_len-1] = pb[si_len] * px[idx] - pa[si_len] * py[idx];
184 psi[0] = pb[si_len] * px[idx] - pa[si_len] * py[idx];
190 T *py = y.fortran_vec ();
191 T *psi = si.fortran_vec ();
193 const T *pb = b.data ();
194 const T *px = x.data ();
198 for (octave_idx_type i = 0, idx = x_offset; i < x_len; i++, idx += x_stride)
200 py[idx] = psi[0] + pb[0] * px[idx];
204 for (octave_idx_type j = 0; j < si_len - 1; j++)
208 psi[j] = psi[j+1] + pb[j+1] * px[idx];
211 psi[si_len-1] = pb[si_len] * px[idx];
217 psi[0] = pb[1] * px[idx];
226#if !defined (CXX_NEW_FRIEND_TEMPLATE_DECL)
227extern MArrayN<double>
228filter (MArray<double>&, MArray<double>&, MArrayN<double>&,
229 MArrayN<double>&, int dim);
231extern MArrayN<Complex>
232filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&,
233 MArrayN<Complex>&, int dim);
236filter (MArray<float>&, MArray<float>&, MArrayN<float>&,
237 MArrayN<float>&, int dim);
239extern MArrayN<FloatComplex>
240filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&,
241 MArrayN<FloatComplex>&, int dim);
246filter (MArray<T>& b, MArray<T>& a, MArrayN<T>& x, int dim = -1)
248 dim_vector x_dims = x.dims();
252 // Find first non-singleton dimension
253 while (dim < x_dims.length () && x_dims(dim) <= 1)
256 // All dimensions singleton, pick first dimension
257 if (dim == x_dims.length ())
261 if (dim < 0 || dim > x_dims.length ())
263 error ("filter: filtering over invalid dimension");
264 return MArrayN<T> ();
267 octave_idx_type a_len = a.length ();
268 octave_idx_type b_len = b.length ();
270 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
271 dim_vector si_dims = x.dims ();
272 for (int i = dim; i > 0; i--)
273 si_dims(i) = si_dims(i-1);
276 MArrayN<T> si (si_dims, T (0.0));
278 return filter (b, a, x, si, dim);
281DEFUN_DLD (filter, args, nargout,
283@deftypefn {Loadable Function} {y =} filter (@var{b}, @var{a}, @var{x})\n\
284@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si})\n\
285@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, [], @var{dim})\n\
286@deftypefnx {Loadable Function} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si}, @var{dim})\n\
287Return the solution to the following linear, time-invariant difference\n\
291\\sum_{k=0}^N a_{k+1} y_{n-k} = \\sum_{k=0}^M b_{k+1} x_{n-k}, \\qquad\n\
297@c Set example in small font to prevent overfull line\n\
300 SUM a(k+1) y(n-k) = SUM b(k+1) x(n-k) for 1<=n<=length(x)\n\
308 N=length(a)-1 and M=length(b)-1.\n\
311 $a \\in \\Re^{N-1}$, $b \\in \\Re^{M-1}$, and $x \\in \\Re^P$.\n\
313over the first non-singleton dimension of @var{x} or over @var{dim} if\n\
314supplied. An equivalent form of this equation is:\n\
317y_n = -\\sum_{k=1}^N c_{k+1} y_{n-k} + \\sum_{k=0}^M d_{k+1} x_{n-k}, \\qquad\n\
323@c Set example in small font to prevent overfull line\n\
326 y(n) = - SUM c(k+1) y(n-k) + SUM d(k+1) x(n-k) for 1<=n<=length(x)\n\
334 c = a/a(1) and d = b/a(1).\n\
337$c = a/a_1$ and $d = b/a_1$.\n\
340If the fourth argument @var{si} is provided, it is taken as the\n\
341initial state of the system and the final state is returned as\n\
342@var{sf}. The state vector is a column vector whose length is\n\
343equal to the length of the longest coefficient vector minus one.\n\
344If @var{si} is not supplied, the initial state vector is set to all\n\
347In terms of the z-transform, y is the result of passing the discrete-\n\
348time signal x through a system characterized by the following rational\n\
352H(z) = {\\displaystyle\\sum_{k=0}^M d_{k+1} z^{-k}\n\
353 \\over 1 + \\displaystyle\\sum_{k+1}^N c_{k+1} z^{-k}}\n\
363 H(z) = ----------------------\n\
365 1 + SUM c(k+1) z^(-k)\n\
372 octave_value_list retval;
374 int nargin = args.length ();
376 if (nargin < 3 || nargin > 5)
382 const char *errmsg = "filter: arguments a and b must be vectors";
385 dim_vector x_dims = args(2).dims ();
389 dim = args(4).nint_value() - 1;
390 if (dim < 0 || dim >= x_dims.length ())
392 error ("filter: filtering over invalid dimension");
398 // Find first non-singleton dimension
400 while (dim < x_dims.length () && x_dims(dim) <= 1)
403 // All dimensions singleton, pick first dimension
404 if (dim == x_dims.length ())
408 bool isfloat = (args(0).is_single_type ()
409 || args(1).is_single_type ()
410 || args(2).is_single_type ()
411 || (nargin >= 4 && args(3).is_single_type ()));
413 if (args(0).is_complex_type ()
414 || args(1).is_complex_type ()
415 || args(2).is_complex_type ()
416 || (nargin >= 4 && args(3).is_complex_type ()))
420 FloatComplexColumnVector b (args(0).float_complex_vector_value ());
421 FloatComplexColumnVector a (args(1).float_complex_vector_value ());
423 FloatComplexNDArray x (args(2).float_complex_array_value ());
427 FloatComplexNDArray si;
429 if (nargin == 3 || args(3).is_empty ())
431 octave_idx_type a_len = a.length ();
432 octave_idx_type b_len = b.length ();
434 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
436 dim_vector si_dims = x.dims ();
437 for (int i = dim; i > 0; i--)
438 si_dims(i) = si_dims(i-1);
441 si.resize (si_dims, 0.0);
445 dim_vector si_dims = args (3).dims ();
446 bool si_is_vector = true;
447 for (int i = 0; i < si_dims.length (); i++)
448 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
450 si_is_vector = false;
454 si = args(3).float_complex_array_value ();
457 si = si.reshape (dim_vector (si.numel (), 1));
462 FloatComplexNDArray y (filter (b, a, x, si, dim));
477 ComplexColumnVector b (args(0).complex_vector_value ());
478 ComplexColumnVector a (args(1).complex_vector_value ());
480 ComplexNDArray x (args(2).complex_array_value ());
486 if (nargin == 3 || args(3).is_empty ())
488 octave_idx_type a_len = a.length ();
489 octave_idx_type b_len = b.length ();
491 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
493 dim_vector si_dims = x.dims ();
494 for (int i = dim; i > 0; i--)
495 si_dims(i) = si_dims(i-1);
498 si.resize (si_dims, 0.0);
502 dim_vector si_dims = args (3).dims ();
503 bool si_is_vector = true;
504 for (int i = 0; i < si_dims.length (); i++)
505 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
507 si_is_vector = false;
511 si = args(3).complex_array_value ();
514 si = si.reshape (dim_vector (si.numel (), 1));
519 ComplexNDArray y (filter (b, a, x, si, dim));
537 FloatColumnVector b (args(0).float_vector_value ());
538 FloatColumnVector a (args(1).float_vector_value ());
540 FloatNDArray x (args(2).float_array_value ());
546 if (nargin == 3 || args(3).is_empty ())
548 octave_idx_type a_len = a.length ();
549 octave_idx_type b_len = b.length ();
551 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
553 dim_vector si_dims = x.dims ();
554 for (int i = dim; i > 0; i--)
555 si_dims(i) = si_dims(i-1);
558 si.resize (si_dims, 0.0);
562 dim_vector si_dims = args (3).dims ();
563 bool si_is_vector = true;
564 for (int i = 0; i < si_dims.length (); i++)
565 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
567 si_is_vector = false;
571 si = args(3).float_array_value ();
574 si = si.reshape (dim_vector (si.numel (), 1));
579 FloatNDArray y (filter (b, a, x, si, dim));
594 ColumnVector b (args(0).vector_value ());
595 ColumnVector a (args(1).vector_value ());
597 NDArray x (args(2).array_value ());
603 if (nargin == 3 || args(3).is_empty ())
605 octave_idx_type a_len = a.length ();
606 octave_idx_type b_len = b.length ();
608 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
610 dim_vector si_dims = x.dims ();
611 for (int i = dim; i > 0; i--)
612 si_dims(i) = si_dims(i-1);
615 si.resize (si_dims, 0.0);
619 dim_vector si_dims = args (3).dims ();
620 bool si_is_vector = true;
621 for (int i = 0; i < si_dims.length (); i++)
622 if (si_dims(i) != 1 && si_dims(i) < si_dims.numel ())
624 si_is_vector = false;
628 si = args(3).array_value ();
631 si = si.reshape (dim_vector (si.numel (), 1));
636 NDArray y (filter (b, a, x, si, dim));
654template MArrayN<double>
655filter (MArray<double>&, MArray<double>&, MArrayN<double>&,
656 MArrayN<double>&, int dim);
658template MArrayN<double>
659filter (MArray<double>&, MArray<double>&, MArrayN<double>&, int dim);
661template MArrayN<Complex>
662filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&,
663 MArrayN<Complex>&, int dim);
665template MArrayN<Complex>
666filter (MArray<Complex>&, MArray<Complex>&, MArrayN<Complex>&, int dim);
668template MArrayN<float>
669filter (MArray<float>&, MArray<float>&, MArrayN<float>&,
670 MArrayN<float>&, int dim);
672template MArrayN<float>
673filter (MArray<float>&, MArray<float>&, MArrayN<float>&, int dim);
675template MArrayN<FloatComplex>
676filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&,
677 MArrayN<FloatComplex>&, int dim);
679template MArrayN<FloatComplex>
680filter (MArray<FloatComplex>&, MArray<FloatComplex>&, MArrayN<FloatComplex>&, int dim);
687%! x = zeros(1,10); x(1) = 1;
688%! assert(all(filter(b, [1], x ) == [1 1 0 0 0 0 0 0 0 0] ))
689%! assert(all(filter(b, [1], x.') == [1 1 0 0 0 0 0 0 0 0].'))
690%! assert(all(filter(b.', [1], x ) == [1 1 0 0 0 0 0 0 0 0] ))
691%! assert(all(filter(b.', [1], x.') == [1 1 0 0 0 0 0 0 0 0].'))
692%! assert(all(filter([1], a, x ) == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ))
693%! assert(all(filter([1], a, x.') == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'))
694%! assert(all(filter([1], a.', x ) == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] ))
695%! assert(all(filter([1], a.', x.') == [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].'))
696%! assert(all(filter(b, a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
697%! assert(all(filter(b.', a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
698%! assert(all(filter(b, a.', x ) == [1 0 0 0 0 0 0 0 0 0] ))
699%! assert(all(filter(b.', a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
700%! assert(all(filter(b, a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
701%! assert(all(filter(b.', a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
702%! assert(all(filter(b, a.', x.') == [1 0 0 0 0 0 0 0 0 0].'))
703%! assert(all(filter(b.', a, x.') == [1 0 0 0 0 0 0 0 0 0].'))
706%! r = sqrt(1/2)*(1+i);
709%! assert(all(filter(b, [1], x ) == r*[1 1 0 0 0 0 0 0 0 0] ))
710%! assert(all(filter(b, [1], r*x ) == r*r*[1 1 0 0 0 0 0 0 0 0] ))
711%! assert(all(filter(b, [1], x.' ) == r*[1 1 0 0 0 0 0 0 0 0].' ))
712%! assert(all(filter(b, a, x ) == [1 0 0 0 0 0 0 0 0 0] ))
713%! assert(all(filter(b, a, r*x ) == r*[1 0 0 0 0 0 0 0 0 0] ))
715%!shared a, b, x, y, so
717%! a = [1,1]; b=[1,1];
718%! x = zeros(1,10); x(1) = 1;
719%! [y, so] = filter(b, [1], x, [-1]);
720%! assert(all(y == [0 1 0 0 0 0 0 0 0 0]))
724%! x = zeros(10,3); x(1,1)=-1; x(1,2)=1;
725%! y0 = zeros(10,3); y0(1:2,1)=-1; y0(1:2,2)=1;
726%! y = filter(b,[1],x);
727%! assert(all(all(y==y0)))
730%! a = [1,1]; b=[1,1];
731%! x = zeros(4,4,2); x(1,1:4,1) = +1; x(1,1:4,2) = -1;
732%! y0 = zeros(4,4,2); y0(1:2,1:4,1) = +1; y0(1:2,1:4,2) = -1;
733%! y = filter(b, [1], x);
734%! assert(all(all(all(y==y0))))
736%% Should put some tests of the "DIM" parameter in here.
741;;; Local Variables: ***