Module: Convolver

Defined in:
lib/convolver-light.rb,
lib/convolver/version.rb,
ext/convolver/convolver.c

Constant Summary collapse

VERSION = 
"0.3.3"

Class Method Summary collapse

Class Method Details

.convolve(signal, kernel) ⇒ NArray

The two parameters must have the same rank. The output has same rank, its size in each dimension d is given by

signal.shape[d] - kernel.shape[d] + 1

Parameters:

  • signal (NArray) —

    must be same size or larger than kernel in each dimension

  • kernel (NArray) —

    must be same size or smaller than signal in each dimension

Returns:

  • (NArray) —

    result of convolving signal with kernel



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# File 'lib/convolver-light.rb', line 12

def self.convolve(signal, kernel)
  convolve_basic signal, kernel
end

.convolve_basic(signal, kernel) ⇒ NArray

Calculates convolution of an array of floats representing a signal, with a second array representing a kernel. The two parameters must have the same rank. The output has same rank, its size in each dimension d is given by

signal.shape[d] - kernel.shape[d] + 1

Parameters:

  • signal (NArray) —

    must be same size or larger than kernel in each dimension

  • kernel (NArray) —

    must be same size or smaller than signal in each dimension

Returns:

  • (NArray) —

    result of convolving signal with kernel



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# File 'ext/convolver/convolver.c', line 79

static VALUE narray_convolve( VALUE self, VALUE a, VALUE b ) {
  struct NARRAY *na_a, *na_b, *na_c;
  volatile VALUE val_a, val_b, val_c;
  int target_rank, i;
  int target_shape[LARGEST_RANK];

  val_a = na_cast_object(a, NA_SFLOAT);
  GetNArray( val_a, na_a );

  val_b = na_cast_object(b, NA_SFLOAT);
  GetNArray( val_b, na_b );

  if ( na_a->rank != na_b->rank ) {
    rb_raise( rb_eArgError, "narray a must have equal rank to narray b (a rack %d, b rank %d)", na_a->rank,  na_b->rank );
  }

  if ( na_a->rank > LARGEST_RANK ) {
    rb_raise( rb_eArgError, "exceeded maximum narray rank for convolve of %d", LARGEST_RANK );
  }

  target_rank = na_a->rank;

  for ( i = 0; i < target_rank; i++ ) {
    target_shape[i] = na_a->shape[i] - na_b->shape[i] + 1;
    if ( target_shape[i] < 1 ) {
      rb_raise( rb_eArgError, "narray b is bigger in one or more dimensions than narray a" );
    }
  }

  val_c = na_make_object( NA_SFLOAT, target_rank, target_shape, CLASS_OF( val_a ) );
  GetNArray( val_c, na_c );

  convolve_raw(
    target_rank, na_a->shape, (float*) na_a->ptr,
    target_rank, na_b->shape, (float*) na_b->ptr,
    target_rank, target_shape, (float*) na_c->ptr );

  return val_c;
}