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ch_convolve.hh
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26 
27 #ifndef MLN_LINEAR_CH_CONVOLVE_HH
28 # define MLN_LINEAR_CH_CONVOLVE_HH
29 
33 
34 # include <mln/core/concept/image.hh>
35 # include <mln/core/concept/window.hh>
36 # include <mln/core/concept/weighted_window.hh>
37 # include <mln/trait/ch_value.hh>
38 # include <mln/value/ops.hh>
39 
40 # include <mln/algebra/vec.hh>
41 
42 
45 # define mln_ch_convolve(I, W) \
46  typename mln::linear::ch_convolve<I, W>::ret
47 
48 # define mln_ch_convolve_(I, W) \
49  mln::linear::ch_convolve<I, W>::ret
50 
51 
52 # define mln_ch_convolve_grad(I, W) \
53  typename mln::trait::ch_value< I, algebra::vec< I::site::dim, typename mln::linear::ch_convolve<I,W>::ret::value > >::ret
54 
55 # define mln_ch_convolve_grad_(I, W) \
56  mln::trait::ch_value< I, algebra::vec< I::site::dim, mln::linear::ch_convolve<I,W>::ret::value > >::ret
57 
58 
59 namespace mln
60 {
61 
62  namespace linear
63  {
64 
65  namespace internal
66  {
67 
68  template <bool b, /* = true, i.e., W is a Weighted_Window */
69  typename I, typename W>
71  {
72  typedef mln_sum_product(mln_value(I), mln_weight(W)) V;
73  typedef mln_ch_value(I, V) ret;
74  };
75 
76  template <typename I, typename W>
77  struct ch_convolve_helper<false, I, W>
78  {
79  typedef mln_sum_product(mln_value(I), W) V;
80  typedef mln_ch_value(I, V) ret;
81  };
82 
83  } // end of namespace mln::linear::internal
84 
85 
86  template <typename I, typename W>
87  struct ch_convolve
88  : private mlc_and( mlc_is_a(I, Image),
89  mlc_is_not_a(W, Window) )::check_t
90  {
91  protected:
92  enum { is_w_win = mlc_is_a(W, Weighted_Window)::value };
94  public:
95  typedef mlc_ret(helper) ret;
96  };
97 
98  } // end of namespace mln::linear
99 
100 } // end of namespace mln
101 
102 
103 #endif // ! MLN_LINEAR_CH_CONVOLVE_HH