Mercurial > hg > octave-nkf
diff src/data.cc @ 10315:57a59eae83cc
untabify src C++ source files
| author | John W. Eaton <jwe@octave.org> |
|---|---|
| date | Thu, 11 Feb 2010 12:41:46 -0500 |
| parents | e4899d6320b6 |
| children | 12884915a8e4 |
line wrap: on
line diff
--- a/src/data.cc +++ b/src/data.cc @@ -92,9 +92,9 @@ if (! error_state) \ { \ if (dim >= -1) \ - retval = args(0).FCN (dim); \ + retval = args(0).FCN (dim); \ else \ - error (#FCN ": invalid dimension argument = %d", dim + 1); \ + error (#FCN ": invalid dimension argument = %d", dim + 1); \ } \ else \ error (#FCN ": expecting dimension argument to be an integer"); \ @@ -330,11 +330,11 @@ retval = SparseMatrix (nr, nc, f_zero); for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) - { - octave_quit (); - retval.data (y.ridx(i) + j * nr) = f (x, y.data (i)); - } + for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) + { + octave_quit (); + retval.data (y.ridx(i) + j * nr) = f (x, y.data (i)); + } retval.maybe_compress (true); } @@ -346,20 +346,20 @@ retval.cidx (ii) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) - { - octave_quit (); - double val = f (x, y.data (i)); - - if (val != 0.0) - { - retval.data (ii) = val; - retval.ridx (ii++) = y.ridx (i); - } - } - retval.cidx (j + 1) = ii; - } + { + for (octave_idx_type i = y.cidx (j); i < y.cidx (j+1); i++) + { + octave_quit (); + double val = f (x, y.data (i)); + + if (val != 0.0) + { + retval.data (ii) = val; + retval.ridx (ii++) = y.ridx (i); + } + } + retval.cidx (j + 1) = ii; + } retval.maybe_compress (false); } @@ -380,11 +380,11 @@ retval = SparseMatrix (nr, nc, f_zero); for (octave_idx_type j = 0; j < nc; j++) - for (octave_idx_type i = x.cidx (j); i < x.cidx (j+1); i++) - { - octave_quit (); - retval.data (x.ridx(i) + j * nr) = f (x.data (i), y); - } + for (octave_idx_type i = x.cidx (j); i < x.cidx (j+1); i++) + { + octave_quit (); + retval.data (x.ridx(i) + j * nr) = f (x.data (i), y); + } retval.maybe_compress (true); } @@ -396,20 +396,20 @@ retval.cidx (ii) = 0; for (octave_idx_type j = 0; j < nc; j++) - { - for (octave_idx_type i = x.cidx (j); i < x.cidx (j+1); i++) - { - octave_quit (); - double val = f (x.data (i), y); - - if (val != 0.0) - { - retval.data (ii) = val; - retval.ridx (ii++) = x.ridx (i); - } - } - retval.cidx (j + 1) = ii; - } + { + for (octave_idx_type i = x.cidx (j); i < x.cidx (j+1); i++) + { + octave_quit (); + double val = f (x.data (i), y); + + if (val != 0.0) + { + retval.data (ii) = val; + retval.ridx (ii++) = x.ridx (i); + } + } + retval.cidx (j + 1) = ii; + } retval.maybe_compress (false); } @@ -437,44 +437,44 @@ octave_idx_type k1 = 0, k2 = 0; for (octave_idx_type j = 0; j < nc; j++) - { - while (k1 < x.cidx(j+1) && k2 < y.cidx(j+1)) - { - octave_quit (); - if (k1 >= x.cidx(j+1)) - { - retval.data (y.ridx(k2) + j * nr) = f (0.0, y.data (k2)); - k2++; - } - else if (k2 >= y.cidx(j+1)) - { - retval.data (x.ridx(k1) + j * nr) = f (x.data (k1), 0.0); - k1++; - } - else - { - octave_idx_type rx = x.ridx(k1); - octave_idx_type ry = y.ridx(k2); - - if (rx < ry) - { - retval.data (rx + j * nr) = f (x.data (k1), 0.0); - k1++; - } - else if (rx > ry) - { - retval.data (ry + j * nr) = f (0.0, y.data (k2)); - k2++; - } - else - { - retval.data (ry + j * nr) = f (x.data (k1), y.data (k2)); - k1++; - k2++; - } - } - } - } + { + while (k1 < x.cidx(j+1) && k2 < y.cidx(j+1)) + { + octave_quit (); + if (k1 >= x.cidx(j+1)) + { + retval.data (y.ridx(k2) + j * nr) = f (0.0, y.data (k2)); + k2++; + } + else if (k2 >= y.cidx(j+1)) + { + retval.data (x.ridx(k1) + j * nr) = f (x.data (k1), 0.0); + k1++; + } + else + { + octave_idx_type rx = x.ridx(k1); + octave_idx_type ry = y.ridx(k2); + + if (rx < ry) + { + retval.data (rx + j * nr) = f (x.data (k1), 0.0); + k1++; + } + else if (rx > ry) + { + retval.data (ry + j * nr) = f (0.0, y.data (k2)); + k2++; + } + else + { + retval.data (ry + j * nr) = f (x.data (k1), y.data (k2)); + k1++; + k2++; + } + } + } + } retval.maybe_compress (true); } @@ -487,51 +487,51 @@ octave_idx_type k1 = 0, k2 = 0; for (octave_idx_type j = 0; j < nc; j++) - { - while (k1 < x.cidx(j+1) && k2 < y.cidx(j+1)) - { - octave_quit (); - double val; - octave_idx_type r; - if (k1 >= x.cidx(j+1)) - { - r = y.ridx (k2); - val = f (0.0, y.data (k2++)); - } - else if (k2 >= y.cidx(j+1)) - { - r = x.ridx (k1); - val = f (x.data (k1++), 0.0); - } - else - { - octave_idx_type rx = x.ridx(k1); - octave_idx_type ry = y.ridx(k2); - - if (rx < ry) - { - r = x.ridx (k1); - val = f (x.data (k1++), 0.0); - } - else if (rx > ry) - { - r = y.ridx (k2); - val = f (0.0, y.data (k2++)); - } - else - { - r = y.ridx (k2); - val = f (x.data (k1++), y.data (k2++)); - } - } - if (val != 0.0) - { - retval.data (ii) = val; - retval.ridx (ii++) = r; - } - } - retval.cidx (j + 1) = ii; - } + { + while (k1 < x.cidx(j+1) && k2 < y.cidx(j+1)) + { + octave_quit (); + double val; + octave_idx_type r; + if (k1 >= x.cidx(j+1)) + { + r = y.ridx (k2); + val = f (0.0, y.data (k2++)); + } + else if (k2 >= y.cidx(j+1)) + { + r = x.ridx (k1); + val = f (x.data (k1++), 0.0); + } + else + { + octave_idx_type rx = x.ridx(k1); + octave_idx_type ry = y.ridx(k2); + + if (rx < ry) + { + r = x.ridx (k1); + val = f (x.data (k1++), 0.0); + } + else if (rx > ry) + { + r = y.ridx (k2); + val = f (0.0, y.data (k2++)); + } + else + { + r = y.ridx (k2); + val = f (x.data (k1++), y.data (k2++)); + } + } + if (val != 0.0) + { + retval.data (ii) = val; + retval.ridx (ii++) = r; + } + } + retval.cidx (j + 1) = ii; + } retval.maybe_compress (false); } @@ -554,158 +554,158 @@ if (nargin == 2 && args(0).is_defined () && args(1).is_defined ()) { if (args(0).is_integer_type () || args(1).is_integer_type ()) - error ("atan2: not defined for integer types"); + error ("atan2: not defined for integer types"); else - { - octave_value arg_y = args(0); - octave_value arg_x = args(1); - - dim_vector y_dims = arg_y.dims (); - dim_vector x_dims = arg_x.dims (); - - bool y_is_scalar = y_dims.all_ones (); - bool x_is_scalar = x_dims.all_ones (); - - bool is_float = arg_y.is_single_type () || arg_x.is_single_type (); - - if (y_is_scalar && x_is_scalar) - { - if (is_float) - { - float y = arg_y.float_value (); - - if (! error_state) - { - float x = arg_x.float_value (); - - if (! error_state) - retval = atan2f (y, x); - } - } - else - { - double y = arg_y.double_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = atan2 (y, x); - } - } - } - else if (y_is_scalar) - { - if (is_float) - { - float y = arg_y.float_value (); - - if (! error_state) - { - // Even if x is sparse return a full matrix here - FloatNDArray x = arg_x.float_array_value (); - - if (! error_state) - retval = map_f_fm (atan2f, y, x); - } - } - else - { - double y = arg_y.double_value (); - - if (! error_state) - { - // Even if x is sparse return a full matrix here - NDArray x = arg_x.array_value (); - - if (! error_state) - retval = map_d_m (atan2, y, x); - } - } - } - else if (x_is_scalar) - { - if (arg_y.is_sparse_type ()) - { - SparseMatrix y = arg_y.sparse_matrix_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = map_s_d (atan2, y, x); - } - } - else if (is_float) - { - FloatNDArray y = arg_y.float_array_value (); - - if (! error_state) - { - float x = arg_x.float_value (); - - if (! error_state) - retval = map_fm_f (atan2f, y, x); - } - } - else - { - NDArray y = arg_y.array_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = map_m_d (atan2, y, x); - } - } - } - else if (y_dims == x_dims) - { - // Even if y is sparse return a full matrix here - if (arg_x.is_sparse_type ()) - { - SparseMatrix y = arg_y.sparse_matrix_value (); - - if (! error_state) - { - SparseMatrix x = arg_x.sparse_matrix_value (); - - if (! error_state) - retval = map_s_s (atan2, y, x); - } - } - else if (is_float) - { - FloatNDArray y = arg_y.array_value (); - - if (! error_state) - { - FloatNDArray x = arg_x.array_value (); - - if (! error_state) - retval = map_fm_fm (atan2f, y, x); - } - } - else - { - NDArray y = arg_y.array_value (); - - if (! error_state) - { - NDArray x = arg_x.array_value (); - - if (! error_state) - retval = map_m_m (atan2, y, x); - } - } - } - else - error ("atan2: nonconformant matrices"); - } + { + octave_value arg_y = args(0); + octave_value arg_x = args(1); + + dim_vector y_dims = arg_y.dims (); + dim_vector x_dims = arg_x.dims (); + + bool y_is_scalar = y_dims.all_ones (); + bool x_is_scalar = x_dims.all_ones (); + + bool is_float = arg_y.is_single_type () || arg_x.is_single_type (); + + if (y_is_scalar && x_is_scalar) + { + if (is_float) + { + float y = arg_y.float_value (); + + if (! error_state) + { + float x = arg_x.float_value (); + + if (! error_state) + retval = atan2f (y, x); + } + } + else + { + double y = arg_y.double_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = atan2 (y, x); + } + } + } + else if (y_is_scalar) + { + if (is_float) + { + float y = arg_y.float_value (); + + if (! error_state) + { + // Even if x is sparse return a full matrix here + FloatNDArray x = arg_x.float_array_value (); + + if (! error_state) + retval = map_f_fm (atan2f, y, x); + } + } + else + { + double y = arg_y.double_value (); + + if (! error_state) + { + // Even if x is sparse return a full matrix here + NDArray x = arg_x.array_value (); + + if (! error_state) + retval = map_d_m (atan2, y, x); + } + } + } + else if (x_is_scalar) + { + if (arg_y.is_sparse_type ()) + { + SparseMatrix y = arg_y.sparse_matrix_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = map_s_d (atan2, y, x); + } + } + else if (is_float) + { + FloatNDArray y = arg_y.float_array_value (); + + if (! error_state) + { + float x = arg_x.float_value (); + + if (! error_state) + retval = map_fm_f (atan2f, y, x); + } + } + else + { + NDArray y = arg_y.array_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = map_m_d (atan2, y, x); + } + } + } + else if (y_dims == x_dims) + { + // Even if y is sparse return a full matrix here + if (arg_x.is_sparse_type ()) + { + SparseMatrix y = arg_y.sparse_matrix_value (); + + if (! error_state) + { + SparseMatrix x = arg_x.sparse_matrix_value (); + + if (! error_state) + retval = map_s_s (atan2, y, x); + } + } + else if (is_float) + { + FloatNDArray y = arg_y.array_value (); + + if (! error_state) + { + FloatNDArray x = arg_x.array_value (); + + if (! error_state) + retval = map_fm_fm (atan2f, y, x); + } + } + else + { + NDArray y = arg_y.array_value (); + + if (! error_state) + { + NDArray x = arg_x.array_value (); + + if (! error_state) + retval = map_m_m (atan2, y, x); + } + } + } + else + error ("atan2: nonconformant matrices"); + } } else print_usage (); @@ -759,215 +759,215 @@ if (nargin == 2 && args(0).is_defined () && args(1).is_defined ()) { if (args(0).is_integer_type () || args(1).is_integer_type ()) - error ("hypot: not defined for integer types"); + error ("hypot: not defined for integer types"); else - { - octave_value arg_x = args(0); - octave_value arg_y = args(1); - - dim_vector x_dims = arg_x.dims (); - dim_vector y_dims = arg_y.dims (); - - bool x_is_scalar = x_dims.all_ones (); - bool y_is_scalar = y_dims.all_ones (); - - bool is_float = arg_y.is_single_type () || arg_x.is_single_type (); - - if (y_is_scalar && x_is_scalar) - { - if (is_float) - { - float x; - if (arg_x.is_complex_type ()) - x = abs (arg_x.float_complex_value ()); - else - x = arg_x.float_value (); - - if (! error_state) - { - float y; - if (arg_y.is_complex_type ()) - y = abs (arg_y.float_complex_value ()); - else - y = arg_y.float_value (); - - if (! error_state) - retval = hypotf (x, y); - } - } - else - { - double x; - if (arg_x.is_complex_type ()) - x = abs (arg_x.complex_value ()); - else - x = arg_x.double_value (); - - if (! error_state) - { - double y; - if (arg_y.is_complex_type ()) - y = abs (arg_y.complex_value ()); - else - y = arg_y.double_value (); - - if (! error_state) - retval = hypot (x, y); - } - } - } - else if (y_is_scalar) - { - if (is_float) - { - FloatNDArray x; - if (arg_x.is_complex_type ()) - x = arg_x.float_complex_array_value ().abs (); - else - x = arg_x.float_array_value (); - - if (! error_state) - { - float y; - if (arg_y.is_complex_type ()) - y = abs (arg_y.float_complex_value ()); - else - y = arg_y.float_value (); - - if (! error_state) - retval = map_fm_f (hypotf, x, y); - } - } - else - { - NDArray x; - if (arg_x.is_complex_type ()) - x = arg_x.complex_array_value ().abs (); - else - x = arg_x.array_value (); - - if (! error_state) - { - double y; - if (arg_y.is_complex_type ()) - y = abs (arg_y.complex_value ()); - else - y = arg_y.double_value (); - - if (! error_state) - retval = map_m_d (hypot, x, y); - } - } - } - else if (x_is_scalar) - { - if (is_float) - { - float x; - if (arg_x.is_complex_type ()) - x = abs (arg_x.float_complex_value ()); - else - x = arg_x.float_value (); - - if (! error_state) - { - FloatNDArray y; - if (arg_y.is_complex_type ()) - y = arg_y.float_complex_array_value ().abs (); - else - y = arg_y.float_array_value (); - - if (! error_state) - retval = map_f_fm (hypotf, x, y); - } - } - else - { - double x; - if (arg_x.is_complex_type ()) - x = abs (arg_x.complex_value ()); - else - x = arg_x.double_value (); - - if (! error_state) - { - NDArray y; - if (arg_y.is_complex_type ()) - y = arg_y.complex_array_value ().abs (); - else - y = arg_y.array_value (); - - if (! error_state) - retval = map_d_m (hypot, x, y); - } - } - } - else if (y_dims == x_dims) - { - if (arg_x.is_sparse_type () && arg_y.is_sparse_type ()) - { - SparseMatrix x; - if (arg_x.is_complex_type ()) - x = arg_x.sparse_complex_matrix_value ().abs (); - else - x = arg_x.sparse_matrix_value (); - - if (! error_state) - { - SparseMatrix y; - if (arg_y.is_complex_type ()) - y = arg_y.sparse_complex_matrix_value ().abs (); - else - y = arg_y.sparse_matrix_value (); - - if (! error_state) - retval = map_s_s (hypot, x, y); - } - } - else if (is_float) - { - FloatNDArray x; - if (arg_x.is_complex_type ()) - x = arg_x.float_complex_array_value ().abs (); - else - x = arg_x.float_array_value (); - - if (! error_state) - { - FloatNDArray y; - if (arg_y.is_complex_type ()) - y = arg_y.float_complex_array_value ().abs (); - else - y = arg_y.float_array_value (); - - if (! error_state) - retval = map_fm_fm (hypotf, x, y); - } - } - else - { - NDArray x; - if (arg_x.is_complex_type ()) - x = arg_x.complex_array_value ().abs (); - else - x = arg_x.array_value (); - - if (! error_state) - { - NDArray y; - if (arg_y.is_complex_type ()) - y = arg_y.complex_array_value ().abs (); - else - y = arg_y.array_value (); - - if (! error_state) - retval = map_m_m (hypot, x, y); - } - } - } - else - error ("hypot: nonconformant matrices"); - } + { + octave_value arg_x = args(0); + octave_value arg_y = args(1); + + dim_vector x_dims = arg_x.dims (); + dim_vector y_dims = arg_y.dims (); + + bool x_is_scalar = x_dims.all_ones (); + bool y_is_scalar = y_dims.all_ones (); + + bool is_float = arg_y.is_single_type () || arg_x.is_single_type (); + + if (y_is_scalar && x_is_scalar) + { + if (is_float) + { + float x; + if (arg_x.is_complex_type ()) + x = abs (arg_x.float_complex_value ()); + else + x = arg_x.float_value (); + + if (! error_state) + { + float y; + if (arg_y.is_complex_type ()) + y = abs (arg_y.float_complex_value ()); + else + y = arg_y.float_value (); + + if (! error_state) + retval = hypotf (x, y); + } + } + else + { + double x; + if (arg_x.is_complex_type ()) + x = abs (arg_x.complex_value ()); + else + x = arg_x.double_value (); + + if (! error_state) + { + double y; + if (arg_y.is_complex_type ()) + y = abs (arg_y.complex_value ()); + else + y = arg_y.double_value (); + + if (! error_state) + retval = hypot (x, y); + } + } + } + else if (y_is_scalar) + { + if (is_float) + { + FloatNDArray x; + if (arg_x.is_complex_type ()) + x = arg_x.float_complex_array_value ().abs (); + else + x = arg_x.float_array_value (); + + if (! error_state) + { + float y; + if (arg_y.is_complex_type ()) + y = abs (arg_y.float_complex_value ()); + else + y = arg_y.float_value (); + + if (! error_state) + retval = map_fm_f (hypotf, x, y); + } + } + else + { + NDArray x; + if (arg_x.is_complex_type ()) + x = arg_x.complex_array_value ().abs (); + else + x = arg_x.array_value (); + + if (! error_state) + { + double y; + if (arg_y.is_complex_type ()) + y = abs (arg_y.complex_value ()); + else + y = arg_y.double_value (); + + if (! error_state) + retval = map_m_d (hypot, x, y); + } + } + } + else if (x_is_scalar) + { + if (is_float) + { + float x; + if (arg_x.is_complex_type ()) + x = abs (arg_x.float_complex_value ()); + else + x = arg_x.float_value (); + + if (! error_state) + { + FloatNDArray y; + if (arg_y.is_complex_type ()) + y = arg_y.float_complex_array_value ().abs (); + else + y = arg_y.float_array_value (); + + if (! error_state) + retval = map_f_fm (hypotf, x, y); + } + } + else + { + double x; + if (arg_x.is_complex_type ()) + x = abs (arg_x.complex_value ()); + else + x = arg_x.double_value (); + + if (! error_state) + { + NDArray y; + if (arg_y.is_complex_type ()) + y = arg_y.complex_array_value ().abs (); + else + y = arg_y.array_value (); + + if (! error_state) + retval = map_d_m (hypot, x, y); + } + } + } + else if (y_dims == x_dims) + { + if (arg_x.is_sparse_type () && arg_y.is_sparse_type ()) + { + SparseMatrix x; + if (arg_x.is_complex_type ()) + x = arg_x.sparse_complex_matrix_value ().abs (); + else + x = arg_x.sparse_matrix_value (); + + if (! error_state) + { + SparseMatrix y; + if (arg_y.is_complex_type ()) + y = arg_y.sparse_complex_matrix_value ().abs (); + else + y = arg_y.sparse_matrix_value (); + + if (! error_state) + retval = map_s_s (hypot, x, y); + } + } + else if (is_float) + { + FloatNDArray x; + if (arg_x.is_complex_type ()) + x = arg_x.float_complex_array_value ().abs (); + else + x = arg_x.float_array_value (); + + if (! error_state) + { + FloatNDArray y; + if (arg_y.is_complex_type ()) + y = arg_y.float_complex_array_value ().abs (); + else + y = arg_y.float_array_value (); + + if (! error_state) + retval = map_fm_fm (hypotf, x, y); + } + } + else + { + NDArray x; + if (arg_x.is_complex_type ()) + x = arg_x.complex_array_value ().abs (); + else + x = arg_x.array_value (); + + if (! error_state) + { + NDArray y; + if (arg_y.is_complex_type ()) + y = arg_y.complex_array_value ().abs (); + else + y = arg_y.array_value (); + + if (! error_state) + retval = map_m_m (hypot, x, y); + } + } + } + else + error ("hypot: nonconformant matrices"); + } } else print_usage (); @@ -1030,28 +1030,28 @@ if (nargout < 2) retval(0) = args(0).log2 (); else if (args(0).is_single_type ()) - { - if (args(0).is_real_type ()) - { - FloatNDArray f; - FloatNDArray x = args(0).float_array_value (); - // FIXME -- should E be an int value? - FloatMatrix e; - map_2_xlog2 (x, f, e); - retval (1) = e; - retval (0) = f; - } - else if (args(0).is_complex_type ()) - { - FloatComplexNDArray f; - FloatComplexNDArray x = args(0).float_complex_array_value (); - // FIXME -- should E be an int value? - FloatNDArray e; - map_2_xlog2 (x, f, e); - retval (1) = e; - retval (0) = f; - } - } + { + if (args(0).is_real_type ()) + { + FloatNDArray f; + FloatNDArray x = args(0).float_array_value (); + // FIXME -- should E be an int value? + FloatMatrix e; + map_2_xlog2 (x, f, e); + retval (1) = e; + retval (0) = f; + } + else if (args(0).is_complex_type ()) + { + FloatComplexNDArray f; + FloatComplexNDArray x = args(0).float_complex_array_value (); + // FIXME -- should E be an int value? + FloatNDArray e; + map_2_xlog2 (x, f, e); + retval (1) = e; + retval (0) = f; + } + } else if (args(0).is_real_type ()) { NDArray f; @@ -1126,149 +1126,149 @@ bool is_float = arg_y.is_single_type () || arg_x.is_single_type (); if (y_is_scalar && x_is_scalar) - { - if (is_float) - { - float y = arg_y.float_value (); - - if (! error_state) - { - float x = arg_x.float_value (); - - if (! error_state) - retval = fmod (x, y); - } - } - else - { - double y = arg_y.double_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = fmod (x, y); - } - } - } + { + if (is_float) + { + float y = arg_y.float_value (); + + if (! error_state) + { + float x = arg_x.float_value (); + + if (! error_state) + retval = fmod (x, y); + } + } + else + { + double y = arg_y.double_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = fmod (x, y); + } + } + } else if (y_is_scalar) - { - if (is_float) - { - float y = arg_y.float_value (); - - if (! error_state) - { - FloatNDArray x = arg_x.float_array_value (); - - if (! error_state) - retval = map_fm_f (fmodf, x, y); - } - } - else - { - double y = arg_y.double_value (); - - if (! error_state) - { - if (arg_x.is_sparse_type ()) - { - SparseMatrix x = arg_x.sparse_matrix_value (); - - if (! error_state) - retval = map_s_d (fmod, x, y); - } - else - { - NDArray x = arg_x.array_value (); - - if (! error_state) - retval = map_m_d (fmod, x, y); - } - } - } - } + { + if (is_float) + { + float y = arg_y.float_value (); + + if (! error_state) + { + FloatNDArray x = arg_x.float_array_value (); + + if (! error_state) + retval = map_fm_f (fmodf, x, y); + } + } + else + { + double y = arg_y.double_value (); + + if (! error_state) + { + if (arg_x.is_sparse_type ()) + { + SparseMatrix x = arg_x.sparse_matrix_value (); + + if (! error_state) + retval = map_s_d (fmod, x, y); + } + else + { + NDArray x = arg_x.array_value (); + + if (! error_state) + retval = map_m_d (fmod, x, y); + } + } + } + } else if (x_is_scalar) - { - if (arg_y.is_sparse_type ()) - { - SparseMatrix y = arg_y.sparse_matrix_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = map_d_s (fmod, x, y); - } - } - else if (is_float) - { - FloatNDArray y = arg_y.float_array_value (); - - if (! error_state) - { - float x = arg_x.float_value (); - - if (! error_state) - retval = map_f_fm (fmodf, x, y); - } - } - else - { - NDArray y = arg_y.array_value (); - - if (! error_state) - { - double x = arg_x.double_value (); - - if (! error_state) - retval = map_d_m (fmod, x, y); - } - } - } + { + if (arg_y.is_sparse_type ()) + { + SparseMatrix y = arg_y.sparse_matrix_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = map_d_s (fmod, x, y); + } + } + else if (is_float) + { + FloatNDArray y = arg_y.float_array_value (); + + if (! error_state) + { + float x = arg_x.float_value (); + + if (! error_state) + retval = map_f_fm (fmodf, x, y); + } + } + else + { + NDArray y = arg_y.array_value (); + + if (! error_state) + { + double x = arg_x.double_value (); + + if (! error_state) + retval = map_d_m (fmod, x, y); + } + } + } else if (y_dims == x_dims) - { - if (arg_y.is_sparse_type () || arg_x.is_sparse_type ()) - { - SparseMatrix y = arg_y.sparse_matrix_value (); - - if (! error_state) - { - SparseMatrix x = arg_x.sparse_matrix_value (); - - if (! error_state) - retval = map_s_s (fmod, x, y); - } - } - else if (is_float) - { - FloatNDArray y = arg_y.float_array_value (); - - if (! error_state) - { - FloatNDArray x = arg_x.float_array_value (); - - if (! error_state) - retval = map_fm_fm (fmodf, x, y); - } - } - else - { - NDArray y = arg_y.array_value (); - - if (! error_state) - { - NDArray x = arg_x.array_value (); - - if (! error_state) - retval = map_m_m (fmod, x, y); - } - } - } + { + if (arg_y.is_sparse_type () || arg_x.is_sparse_type ()) + { + SparseMatrix y = arg_y.sparse_matrix_value (); + + if (! error_state) + { + SparseMatrix x = arg_x.sparse_matrix_value (); + + if (! error_state) + retval = map_s_s (fmod, x, y); + } + } + else if (is_float) + { + FloatNDArray y = arg_y.float_array_value (); + + if (! error_state) + { + FloatNDArray x = arg_x.float_array_value (); + + if (! error_state) + retval = map_fm_fm (fmodf, x, y); + } + } + else + { + NDArray y = arg_y.array_value (); + + if (! error_state) + { + NDArray x = arg_x.array_value (); + + if (! error_state) + retval = map_m_m (fmod, x, y); + } + } + } else - error ("fmod: nonconformant matrices"); + error ("fmod: nonconformant matrices"); } else print_usage (); @@ -1318,15 +1318,15 @@ std::string str = args(nargin - 1).string_value (); \ \ if (! error_state) \ - { \ - if (str == "native") \ - isnative = true; \ - else if (str == "double") \ + { \ + if (str == "native") \ + isnative = true; \ + else if (str == "double") \ isdouble = true; \ else \ - error ("sum: unrecognized string argument"); \ + error ("sum: unrecognized string argument"); \ nargin --; \ - } \ + } \ } \ \ if (nargin == 1 || nargin == 2) \ @@ -1336,32 +1336,32 @@ int dim = (nargin == 1 ? -1 : args(1).int_value (true) - 1); \ \ if (! error_state) \ - { \ - if (dim >= -1) \ - { \ - if (arg.is_sparse_type ()) \ - { \ - if (arg.is_real_type ()) \ - { \ - SparseMatrix tmp = arg.sparse_matrix_value (); \ - \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else \ - { \ - SparseComplexMatrix tmp = arg.sparse_complex_matrix_value (); \ + { \ + if (dim >= -1) \ + { \ + if (arg.is_sparse_type ()) \ + { \ + if (arg.is_real_type ()) \ + { \ + SparseMatrix tmp = arg.sparse_matrix_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - } \ - else \ - { \ - if (isnative) \ - { \ - if NATIVE_REDUCTION_1 (FCN, uint8, dim) \ - else if NATIVE_REDUCTION_1 (FCN, uint16, dim) \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else \ + { \ + SparseComplexMatrix tmp = arg.sparse_complex_matrix_value (); \ + \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + } \ + else \ + { \ + if (isnative) \ + { \ + if NATIVE_REDUCTION_1 (FCN, uint8, dim) \ + else if NATIVE_REDUCTION_1 (FCN, uint16, dim) \ else if NATIVE_REDUCTION_1 (FCN, uint32, dim) \ else if NATIVE_REDUCTION_1 (FCN, uint64, dim) \ else if NATIVE_REDUCTION_1 (FCN, int8, dim) \ @@ -1376,45 +1376,45 @@ } \ else if (arg.is_char_matrix ()) \ { \ - error (#FCN, ": invalid char type"); \ - } \ - else if (!isdouble && arg.is_single_type ()) \ + error (#FCN, ": invalid char type"); \ + } \ + else if (!isdouble && arg.is_single_type ()) \ { \ - if (arg.is_complex_type ()) \ - { \ - FloatComplexNDArray tmp = \ - arg.float_complex_array_value (); \ + if (arg.is_complex_type ()) \ + { \ + FloatComplexNDArray tmp = \ + arg.float_complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_real_type ()) \ - { \ - FloatNDArray tmp = arg.float_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_real_type ()) \ + { \ + FloatNDArray tmp = arg.float_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - } \ - else if (arg.is_complex_type ()) \ - { \ - ComplexNDArray tmp = arg.complex_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + } \ + else if (arg.is_complex_type ()) \ + { \ + ComplexNDArray tmp = arg.complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_real_type ()) \ - { \ - NDArray tmp = arg.array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_real_type ()) \ + { \ + NDArray tmp = arg.array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ else \ - { \ - gripe_wrong_type_arg (#FCN, arg); \ - return retval; \ - } \ + { \ + gripe_wrong_type_arg (#FCN, arg); \ + return retval; \ + } \ } \ else if (arg.is_bool_type ()) \ { \ @@ -1422,48 +1422,48 @@ if (! error_state) \ retval = tmp.FCN (dim); \ } \ - else if (!isdouble && arg.is_single_type ()) \ - { \ - if (arg.is_real_type ()) \ - { \ - FloatNDArray tmp = arg.float_array_value (); \ + else if (!isdouble && arg.is_single_type ()) \ + { \ + if (arg.is_real_type ()) \ + { \ + FloatNDArray tmp = arg.float_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_complex_type ()) \ - { \ - FloatComplexNDArray tmp = \ - arg.float_complex_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_complex_type ()) \ + { \ + FloatComplexNDArray tmp = \ + arg.float_complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - } \ - else if (arg.is_real_type ()) \ - { \ - NDArray tmp = arg.array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + } \ + else if (arg.is_real_type ()) \ + { \ + NDArray tmp = arg.array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_complex_type ()) \ - { \ - ComplexNDArray tmp = arg.complex_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_complex_type ()) \ + { \ + ComplexNDArray tmp = arg.complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else \ - { \ - gripe_wrong_type_arg (#FCN, arg); \ - return retval; \ - } \ - } \ - } \ - else \ - error (#FCN ": invalid dimension argument = %d", dim + 1); \ - } \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else \ + { \ + gripe_wrong_type_arg (#FCN, arg); \ + return retval; \ + } \ + } \ + } \ + else \ + error (#FCN ": invalid dimension argument = %d", dim + 1); \ + } \ \ } \ else \ @@ -1484,66 +1484,66 @@ int dim = (nargin == 1 ? -1 : args(1).int_value (true) - 1); \ \ if (! error_state) \ - { \ - if (dim >= -1) \ - { \ - if (arg.is_real_type ()) \ - { \ - if (arg.is_sparse_type ()) \ - { \ - SparseMatrix tmp = arg.sparse_matrix_value (); \ + { \ + if (dim >= -1) \ + { \ + if (arg.is_real_type ()) \ + { \ + if (arg.is_sparse_type ()) \ + { \ + SparseMatrix tmp = arg.sparse_matrix_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_single_type ()) \ - { \ - FloatNDArray tmp = arg.float_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_single_type ()) \ + { \ + FloatNDArray tmp = arg.float_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else \ - { \ - NDArray tmp = arg.array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else \ + { \ + NDArray tmp = arg.array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - } \ - else if (arg.is_complex_type ()) \ - { \ - if (arg.is_sparse_type ()) \ - { \ - SparseComplexMatrix tmp = arg.sparse_complex_matrix_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + } \ + else if (arg.is_complex_type ()) \ + { \ + if (arg.is_sparse_type ()) \ + { \ + SparseComplexMatrix tmp = arg.sparse_complex_matrix_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else if (arg.is_single_type ()) \ - { \ - FloatComplexNDArray tmp = arg.float_complex_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else if (arg.is_single_type ()) \ + { \ + FloatComplexNDArray tmp = arg.float_complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - else \ - { \ - ComplexNDArray tmp = arg.complex_array_value (); \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + else \ + { \ + ComplexNDArray tmp = arg.complex_array_value (); \ \ - if (! error_state) \ - retval = tmp.FCN (dim); \ - } \ - } \ - else \ - { \ - gripe_wrong_type_arg (#FCN, arg); \ - return retval; \ - } \ - } \ - else \ - error (#FCN ": invalid dimension argument = %d", dim + 1); \ - } \ + if (! error_state) \ + retval = tmp.FCN (dim); \ + } \ + } \ + else \ + { \ + gripe_wrong_type_arg (#FCN, arg); \ + return retval; \ + } \ + } \ + else \ + error (#FCN ": invalid dimension argument = %d", dim + 1); \ + } \ } \ else \ print_usage (); \ @@ -1611,15 +1611,15 @@ std::string str = args(nargin - 1).string_value (); if (! error_state) - { - if (str == "native") - isnative = true; - else if (str == "double") + { + if (str == "native") + isnative = true; + else if (str == "double") isdouble = true; else - error ("sum: unrecognized string argument"); + error ("sum: unrecognized string argument"); nargin --; - } + } } if (error_state) @@ -1634,11 +1634,11 @@ { dim = args(1).int_value () - 1; if (dim < 0) - error ("cumsum: invalid dimension argument = %d", dim + 1); + error ("cumsum: invalid dimension argument = %d", dim + 1); } if (! error_state) - { + { switch (arg.builtin_type ()) { case btyp_double: @@ -1705,7 +1705,7 @@ default: gripe_wrong_type_arg ("cumsum", arg); } - } + } } else print_usage (); @@ -1770,9 +1770,9 @@ octave_idx_type k = args(1).int_value (); if (error_state) - error ("diag: invalid second argument"); + error ("diag: invalid second argument"); else - retval = args(0).diag(k); + retval = args(0).diag(k); } else if (nargin == 3) { @@ -1895,30 +1895,30 @@ Array<octave_idx_type> ra_idx (dv_len > 1 ? dv_len : 2, 0); \ \ for (int j = 1; j < n_args; j++) \ - { \ - octave_quit (); \ - \ - TYPE ra = args(j).EXTRACTOR (); \ - \ - if (! error_state) \ - { \ - result.insert (ra, ra_idx); \ - \ - if (error_state) \ - return retval; \ - \ - dim_vector dv_tmp = args (j).dims (); \ - \ - if (dim >= dv_len) \ - { \ - if (j > 1) \ - error ("%s: indexing error", fname.c_str ()); \ - break; \ - } \ - else \ - ra_idx (dim) += (dim < dv_tmp.length () ? dv_tmp (dim) : 1); \ - } \ - } \ + { \ + octave_quit (); \ + \ + TYPE ra = args(j).EXTRACTOR (); \ + \ + if (! error_state) \ + { \ + result.insert (ra, ra_idx); \ + \ + if (error_state) \ + return retval; \ + \ + dim_vector dv_tmp = args (j).dims (); \ + \ + if (dim >= dv_len) \ + { \ + if (j > 1) \ + error ("%s: indexing error", fname.c_str ()); \ + break; \ + } \ + else \ + ra_idx (dim) += (dim < dv_tmp.length () ? dv_tmp (dim) : 1); \ + } \ + } \ } \ while (0) @@ -1949,166 +1949,166 @@ octave_idx_type dim = args(0).int_value () - 1; if (error_state) - { - error ("cat: expecting first argument to be a integer"); - return retval; - } + { + error ("cat: expecting first argument to be a integer"); + return retval; + } if (dim >= 0) - { - - dim_vector dv = args(1).dims (); - std::string result_type = args(1).class_name (); - - bool all_sq_strings_p = args(1).is_sq_string (); - bool all_dq_strings_p = args(1).is_dq_string (); - bool all_real_p = args(1).is_real_type (); - bool any_sparse_p = args(1).is_sparse_type(); - - for (int i = 2; i < args.length (); i++) - { - // add_dims constructs a dimension vector which holds the - // dimensions of the final array after concatenation. - - if (! dv.concat (args(i).dims (), dim)) - { - // Dimensions do not match. - error ("cat: dimension mismatch"); - return retval; - } - - result_type = - get_concat_class (result_type, args(i).class_name ()); - - if (all_sq_strings_p && ! args(i).is_sq_string ()) - all_sq_strings_p = false; - if (all_dq_strings_p && ! args(i).is_dq_string ()) - all_dq_strings_p = false; - if (all_real_p && ! args(i).is_real_type ()) - all_real_p = false; - if (!any_sparse_p && args(i).is_sparse_type ()) - any_sparse_p = true; - } - - if (result_type == "double") - { - if (any_sparse_p) - { - if (all_real_p) - DO_SINGLE_TYPE_CONCAT (SparseMatrix, sparse_matrix_value); - else - DO_SINGLE_TYPE_CONCAT (SparseComplexMatrix, sparse_complex_matrix_value); - } - else - { - if (all_real_p) - DO_SINGLE_TYPE_CONCAT (NDArray, array_value); - else - DO_SINGLE_TYPE_CONCAT (ComplexNDArray, complex_array_value); - } - } - else if (result_type == "single") - { - if (all_real_p) - DO_SINGLE_TYPE_CONCAT (FloatNDArray, float_array_value); - else - DO_SINGLE_TYPE_CONCAT (FloatComplexNDArray, - float_complex_array_value); - } - else if (result_type == "char") - { - char type = all_dq_strings_p ? '"' : '\''; - - maybe_warn_string_concat (all_dq_strings_p, all_sq_strings_p); - - charNDArray result (dv, Vstring_fill_char); - - SINGLE_TYPE_CONCAT (charNDArray, char_array_value); - - retval = octave_value (result, type); - } - else if (result_type == "logical") - { - if (any_sparse_p) - DO_SINGLE_TYPE_CONCAT (SparseBoolMatrix, sparse_bool_matrix_value); - else - DO_SINGLE_TYPE_CONCAT (boolNDArray, bool_array_value); - } - else if (result_type == "int8") - DO_SINGLE_TYPE_CONCAT (int8NDArray, int8_array_value); - else if (result_type == "int16") - DO_SINGLE_TYPE_CONCAT (int16NDArray, int16_array_value); - else if (result_type == "int32") - DO_SINGLE_TYPE_CONCAT (int32NDArray, int32_array_value); - else if (result_type == "int64") - DO_SINGLE_TYPE_CONCAT (int64NDArray, int64_array_value); - else if (result_type == "uint8") - DO_SINGLE_TYPE_CONCAT (uint8NDArray, uint8_array_value); - else if (result_type == "uint16") - DO_SINGLE_TYPE_CONCAT (uint16NDArray, uint16_array_value); - else if (result_type == "uint32") - DO_SINGLE_TYPE_CONCAT (uint32NDArray, uint32_array_value); - else if (result_type == "uint64") - DO_SINGLE_TYPE_CONCAT (uint64NDArray, uint64_array_value); - else - { - // The lines below might seem crazy, since we take a copy - // of the first argument, resize it to be empty and then resize - // it to be full. This is done since it means that there is no - // recopying of data, as would happen if we used a single resize. - // It should be noted that resize operation is also significantly - // slower than the do_cat_op function, so it makes sense to have - // an empty matrix and copy all data. - // - // We might also start with a empty octave_value using - // tmp = octave_value_typeinfo::lookup_type - // (args(1).type_name()); - // and then directly resize. However, for some types there might - // be some additional setup needed, and so this should be avoided. - - octave_value tmp = args (1); - tmp = tmp.resize (dim_vector (0,0)).resize (dv); - - if (error_state) - return retval; - - int dv_len = dv.length (); - Array<octave_idx_type> ra_idx (dv_len, 0); - - for (int j = 1; j < n_args; j++) - { - // Can't fast return here to skip empty matrices as something - // like cat(1,[],single([])) must return an empty matrix of - // the right type. - tmp = do_cat_op (tmp, args (j), ra_idx); - - if (error_state) - return retval; - - dim_vector dv_tmp = args (j).dims (); - - if (dim >= dv_len) - { - if (j > 1) - error ("%s: indexing error", fname.c_str ()); - break; - } - else - ra_idx (dim) += (dim < dv_tmp.length () ? - dv_tmp (dim) : 1); - } - retval = tmp; - } - - if (! error_state) - { - // Reshape, chopping trailing singleton dimensions - dv.chop_trailing_singletons (); - retval = retval.reshape (dv); - } - } + { + + dim_vector dv = args(1).dims (); + std::string result_type = args(1).class_name (); + + bool all_sq_strings_p = args(1).is_sq_string (); + bool all_dq_strings_p = args(1).is_dq_string (); + bool all_real_p = args(1).is_real_type (); + bool any_sparse_p = args(1).is_sparse_type(); + + for (int i = 2; i < args.length (); i++) + { + // add_dims constructs a dimension vector which holds the + // dimensions of the final array after concatenation. + + if (! dv.concat (args(i).dims (), dim)) + { + // Dimensions do not match. + error ("cat: dimension mismatch"); + return retval; + } + + result_type = + get_concat_class (result_type, args(i).class_name ()); + + if (all_sq_strings_p && ! args(i).is_sq_string ()) + all_sq_strings_p = false; + if (all_dq_strings_p && ! args(i).is_dq_string ()) + all_dq_strings_p = false; + if (all_real_p && ! args(i).is_real_type ()) + all_real_p = false; + if (!any_sparse_p && args(i).is_sparse_type ()) + any_sparse_p = true; + } + + if (result_type == "double") + { + if (any_sparse_p) + { + if (all_real_p) + DO_SINGLE_TYPE_CONCAT (SparseMatrix, sparse_matrix_value); + else + DO_SINGLE_TYPE_CONCAT (SparseComplexMatrix, sparse_complex_matrix_value); + } + else + { + if (all_real_p) + DO_SINGLE_TYPE_CONCAT (NDArray, array_value); + else + DO_SINGLE_TYPE_CONCAT (ComplexNDArray, complex_array_value); + } + } + else if (result_type == "single") + { + if (all_real_p) + DO_SINGLE_TYPE_CONCAT (FloatNDArray, float_array_value); + else + DO_SINGLE_TYPE_CONCAT (FloatComplexNDArray, + float_complex_array_value); + } + else if (result_type == "char") + { + char type = all_dq_strings_p ? '"' : '\''; + + maybe_warn_string_concat (all_dq_strings_p, all_sq_strings_p); + + charNDArray result (dv, Vstring_fill_char); + + SINGLE_TYPE_CONCAT (charNDArray, char_array_value); + + retval = octave_value (result, type); + } + else if (result_type == "logical") + { + if (any_sparse_p) + DO_SINGLE_TYPE_CONCAT (SparseBoolMatrix, sparse_bool_matrix_value); + else + DO_SINGLE_TYPE_CONCAT (boolNDArray, bool_array_value); + } + else if (result_type == "int8") + DO_SINGLE_TYPE_CONCAT (int8NDArray, int8_array_value); + else if (result_type == "int16") + DO_SINGLE_TYPE_CONCAT (int16NDArray, int16_array_value); + else if (result_type == "int32") + DO_SINGLE_TYPE_CONCAT (int32NDArray, int32_array_value); + else if (result_type == "int64") + DO_SINGLE_TYPE_CONCAT (int64NDArray, int64_array_value); + else if (result_type == "uint8") + DO_SINGLE_TYPE_CONCAT (uint8NDArray, uint8_array_value); + else if (result_type == "uint16") + DO_SINGLE_TYPE_CONCAT (uint16NDArray, uint16_array_value); + else if (result_type == "uint32") + DO_SINGLE_TYPE_CONCAT (uint32NDArray, uint32_array_value); + else if (result_type == "uint64") + DO_SINGLE_TYPE_CONCAT (uint64NDArray, uint64_array_value); + else + { + // The lines below might seem crazy, since we take a copy + // of the first argument, resize it to be empty and then resize + // it to be full. This is done since it means that there is no + // recopying of data, as would happen if we used a single resize. + // It should be noted that resize operation is also significantly + // slower than the do_cat_op function, so it makes sense to have + // an empty matrix and copy all data. + // + // We might also start with a empty octave_value using + // tmp = octave_value_typeinfo::lookup_type + // (args(1).type_name()); + // and then directly resize. However, for some types there might + // be some additional setup needed, and so this should be avoided. + + octave_value tmp = args (1); + tmp = tmp.resize (dim_vector (0,0)).resize (dv); + + if (error_state) + return retval; + + int dv_len = dv.length (); + Array<octave_idx_type> ra_idx (dv_len, 0); + + for (int j = 1; j < n_args; j++) + { + // Can't fast return here to skip empty matrices as something + // like cat(1,[],single([])) must return an empty matrix of + // the right type. + tmp = do_cat_op (tmp, args (j), ra_idx); + + if (error_state) + return retval; + + dim_vector dv_tmp = args (j).dims (); + + if (dim >= dv_len) + { + if (j > 1) + error ("%s: indexing error", fname.c_str ()); + break; + } + else + ra_idx (dim) += (dim < dv_tmp.length () ? + dv_tmp (dim) : 1); + } + retval = tmp; + } + + if (! error_state) + { + // Reshape, chopping trailing singleton dimensions + dv.chop_trailing_singletons (); + retval = retval.reshape (dv); + } + } else - error ("%s: invalid dimension argument", fname.c_str ()); + error ("%s: invalid dimension argument", fname.c_str ()); } else print_usage (); @@ -2349,12 +2349,12 @@ int n = vec.length (); for (int i = 0; i < n; i++) - vec(i)--; + vec(i)--; octave_value ret = args(0).permute (vec, inv); if (! error_state) - retval = ret; + retval = ret; } else print_usage (); @@ -2502,44 +2502,44 @@ const dim_vector dimensions = args(0).dims (); if (nargout > 1) - { + { const dim_vector rdims = dimensions.redim (nargout); retval.resize (nargout); for (int i = 0; i < nargout; i++) retval(i) = rdims(i); - } + } else - { + { int ndims = dimensions.length (); NoAlias<Matrix> m (1, ndims); - for (int i = 0; i < ndims; i++) - m(i) = dimensions(i); - - retval(0) = m; - } + for (int i = 0; i < ndims; i++) + m(i) = dimensions(i); + + retval(0) = m; + } } else if (nargin == 2 && nargout < 2) { octave_idx_type nd = args(1).int_value (true); if (error_state) - error ("size: expecting scalar as second argument"); + error ("size: expecting scalar as second argument"); else - { - const dim_vector dv = args(0).dims (); - - if (nd > 0) - { - if (nd <= dv.length ()) - retval(0) = dv(nd-1); - else - retval(0) = 1; - } - else - error ("size: requested dimension (= %d) out of range", nd); - } + { + const dim_vector dv = args(0).dims (); + + if (nd > 0) + { + if (nd <= dv.length ()) + retval(0) = dv(nd-1); + else + retval(0) = 1; + } + else + error ("size: requested dimension (= %d) out of range", nd); + } } else print_usage (); @@ -2571,10 +2571,10 @@ dim_vector b_dims = args(i).dims (); if (a_dims != b_dims) - { - retval = false; - break; - } + { + retval = false; + break; + } } } @@ -2698,17 +2698,17 @@ std::string str = args(nargin - 1).string_value (); if (! error_state) - { - if (str == "native") - isnative = true; - else if (str == "double") + { + if (str == "native") + isnative = true; + else if (str == "double") isdouble = true; else if (str == "extra") isextra = true; else - error ("sum: unrecognized string argument"); + error ("sum: unrecognized string argument"); nargin --; - } + } } if (error_state) @@ -2723,11 +2723,11 @@ { dim = args(1).int_value () - 1; if (dim < 0) - error ("sum: invalid dimension argument = %d", dim + 1); + error ("sum: invalid dimension argument = %d", dim + 1); } if (! error_state) - { + { switch (arg.builtin_type ()) { case btyp_double: @@ -2801,7 +2801,7 @@ default: gripe_wrong_type_arg ("sum", arg); } - } + } } else print_usage (); @@ -3023,54 +3023,54 @@ octave_value arg = args(0); if (arg.is_complex_type ()) - retval = arg; + retval = arg; else - { - if (arg.is_sparse_type ()) - { - SparseComplexMatrix val = arg.sparse_complex_matrix_value (); - - if (! error_state) - retval = octave_value (new octave_sparse_complex_matrix (val)); - } - else if (arg.is_single_type ()) - { - if (arg.numel () == 1) - { - FloatComplex val = arg.float_complex_value (); - - if (! error_state) - retval = octave_value (new octave_float_complex (val)); - } - else - { - FloatComplexNDArray val = arg.float_complex_array_value (); - - if (! error_state) - retval = octave_value (new octave_float_complex_matrix (val)); - } - } - else - { - if (arg.numel () == 1) - { - Complex val = arg.complex_value (); - - if (! error_state) - retval = octave_value (new octave_complex (val)); - } - else - { - ComplexNDArray val = arg.complex_array_value (); - - if (! error_state) - retval = octave_value (new octave_complex_matrix (val)); - } - } - - if (error_state) - error ("complex: invalid conversion"); - } + { + if (arg.is_sparse_type ()) + { + SparseComplexMatrix val = arg.sparse_complex_matrix_value (); + + if (! error_state) + retval = octave_value (new octave_sparse_complex_matrix (val)); + } + else if (arg.is_single_type ()) + { + if (arg.numel () == 1) + { + FloatComplex val = arg.float_complex_value (); + + if (! error_state) + retval = octave_value (new octave_float_complex (val)); + } + else + { + FloatComplexNDArray val = arg.float_complex_array_value (); + + if (! error_state) + retval = octave_value (new octave_float_complex_matrix (val)); + } + } + else + { + if (arg.numel () == 1) + { + Complex val = arg.complex_value (); + + if (! error_state) + retval = octave_value (new octave_complex (val)); + } + else + { + ComplexNDArray val = arg.complex_array_value (); + + if (! error_state) + retval = octave_value (new octave_complex_matrix (val)); + } + } + + if (error_state) + error ("complex: invalid conversion"); + } } else if (nargin == 2) { @@ -3078,205 +3078,205 @@ octave_value im = args(1); if (re.is_sparse_type () && im.is_sparse_type ()) - { - const SparseMatrix re_val = re.sparse_matrix_value (); - const SparseMatrix im_val = im.sparse_matrix_value (); - - if (!error_state) - { - if (re.numel () == 1) - { - SparseComplexMatrix result; - if (re_val.nnz () == 0) - result = Complex(0, 1) * SparseComplexMatrix (im_val); - else - { - result = SparseComplexMatrix (im_val.dims (), re_val (0)); - octave_idx_type nr = im_val.rows (); - octave_idx_type nc = im_val.cols (); - - for (octave_idx_type j = 0; j < nc; j++) - { - octave_idx_type off = j * nr; - for (octave_idx_type i = im_val.cidx(j); - i < im_val.cidx(j + 1); i++) - result.data (im_val.ridx(i) + off) = - result.data (im_val.ridx(i) + off) + - Complex (0, im_val.data (i)); - } - } - retval = octave_value (new octave_sparse_complex_matrix (result)); - } - else if (im.numel () == 1) - { - SparseComplexMatrix result; - if (im_val.nnz () == 0) - result = SparseComplexMatrix (re_val); - else - { - result = SparseComplexMatrix (re_val.rows(), re_val.cols(), Complex(0, im_val (0))); - octave_idx_type nr = re_val.rows (); - octave_idx_type nc = re_val.cols (); - - for (octave_idx_type j = 0; j < nc; j++) - { - octave_idx_type off = j * nr; - for (octave_idx_type i = re_val.cidx(j); - i < re_val.cidx(j + 1); i++) - result.data (re_val.ridx(i) + off) = - result.data (re_val.ridx(i) + off) + - re_val.data (i); - } - } - retval = octave_value (new octave_sparse_complex_matrix (result)); - } - else - { - if (re_val.dims () == im_val.dims ()) - { - SparseComplexMatrix result = SparseComplexMatrix(re_val) - + Complex(0, 1) * SparseComplexMatrix (im_val); - retval = octave_value (new octave_sparse_complex_matrix (result)); - } - else - error ("complex: dimension mismatch"); - } - } - } + { + const SparseMatrix re_val = re.sparse_matrix_value (); + const SparseMatrix im_val = im.sparse_matrix_value (); + + if (!error_state) + { + if (re.numel () == 1) + { + SparseComplexMatrix result; + if (re_val.nnz () == 0) + result = Complex(0, 1) * SparseComplexMatrix (im_val); + else + { + result = SparseComplexMatrix (im_val.dims (), re_val (0)); + octave_idx_type nr = im_val.rows (); + octave_idx_type nc = im_val.cols (); + + for (octave_idx_type j = 0; j < nc; j++) + { + octave_idx_type off = j * nr; + for (octave_idx_type i = im_val.cidx(j); + i < im_val.cidx(j + 1); i++) + result.data (im_val.ridx(i) + off) = + result.data (im_val.ridx(i) + off) + + Complex (0, im_val.data (i)); + } + } + retval = octave_value (new octave_sparse_complex_matrix (result)); + } + else if (im.numel () == 1) + { + SparseComplexMatrix result; + if (im_val.nnz () == 0) + result = SparseComplexMatrix (re_val); + else + { + result = SparseComplexMatrix (re_val.rows(), re_val.cols(), Complex(0, im_val (0))); + octave_idx_type nr = re_val.rows (); + octave_idx_type nc = re_val.cols (); + + for (octave_idx_type j = 0; j < nc; j++) + { + octave_idx_type off = j * nr; + for (octave_idx_type i = re_val.cidx(j); + i < re_val.cidx(j + 1); i++) + result.data (re_val.ridx(i) + off) = + result.data (re_val.ridx(i) + off) + + re_val.data (i); + } + } + retval = octave_value (new octave_sparse_complex_matrix (result)); + } + else + { + if (re_val.dims () == im_val.dims ()) + { + SparseComplexMatrix result = SparseComplexMatrix(re_val) + + Complex(0, 1) * SparseComplexMatrix (im_val); + retval = octave_value (new octave_sparse_complex_matrix (result)); + } + else + error ("complex: dimension mismatch"); + } + } + } else if (re.is_single_type () || im.is_single_type ()) - { - if (re.numel () == 1) - { - float re_val = re.float_value (); - - if (im.numel () == 1) - { - float im_val = im.double_value (); - - if (! error_state) - retval = octave_value (new octave_float_complex (FloatComplex (re_val, im_val))); - } - else - { - const FloatNDArray im_val = im.float_array_value (); - - if (! error_state) - { - FloatComplexNDArray result (im_val.dims (), FloatComplex ()); - - for (octave_idx_type i = 0; i < im_val.numel (); i++) - result.xelem (i) = FloatComplex (re_val, im_val(i)); - - retval = octave_value (new octave_float_complex_matrix (result)); - } - } - } - else - { - const FloatNDArray re_val = re.float_array_value (); - - if (im.numel () == 1) - { - float im_val = im.float_value (); - - if (! error_state) - { - FloatComplexNDArray result (re_val.dims (), FloatComplex ()); - - for (octave_idx_type i = 0; i < re_val.numel (); i++) - result.xelem (i) = FloatComplex (re_val(i), im_val); - - retval = octave_value (new octave_float_complex_matrix (result)); - } - } - else - { - const FloatNDArray im_val = im.float_array_value (); - - if (! error_state) - { - if (re_val.dims () == im_val.dims ()) - { - FloatComplexNDArray result (re_val.dims (), FloatComplex ()); - - for (octave_idx_type i = 0; i < re_val.numel (); i++) - result.xelem (i) = FloatComplex (re_val(i), im_val(i)); - - retval = octave_value (new octave_float_complex_matrix (result)); - } - else - error ("complex: dimension mismatch"); - } - } - } - } + { + if (re.numel () == 1) + { + float re_val = re.float_value (); + + if (im.numel () == 1) + { + float im_val = im.double_value (); + + if (! error_state) + retval = octave_value (new octave_float_complex (FloatComplex (re_val, im_val))); + } + else + { + const FloatNDArray im_val = im.float_array_value (); + + if (! error_state) + { + FloatComplexNDArray result (im_val.dims (), FloatComplex ()); + + for (octave_idx_type i = 0; i < im_val.numel (); i++) + result.xelem (i) = FloatComplex (re_val, im_val(i)); + + retval = octave_value (new octave_float_complex_matrix (result)); + } + } + } + else + { + const FloatNDArray re_val = re.float_array_value (); + + if (im.numel () == 1) + { + float im_val = im.float_value (); + + if (! error_state) + { + FloatComplexNDArray result (re_val.dims (), FloatComplex ()); + + for (octave_idx_type i = 0; i < re_val.numel (); i++) + result.xelem (i) = FloatComplex (re_val(i), im_val); + + retval = octave_value (new octave_float_complex_matrix (result)); + } + } + else + { + const FloatNDArray im_val = im.float_array_value (); + + if (! error_state) + { + if (re_val.dims () == im_val.dims ()) + { + FloatComplexNDArray result (re_val.dims (), FloatComplex ()); + + for (octave_idx_type i = 0; i < re_val.numel (); i++) + result.xelem (i) = FloatComplex (re_val(i), im_val(i)); + + retval = octave_value (new octave_float_complex_matrix (result)); + } + else + error ("complex: dimension mismatch"); + } + } + } + } else if (re.numel () == 1) - { - double re_val = re.double_value (); - - if (im.numel () == 1) - { - double im_val = im.double_value (); - - if (! error_state) - retval = octave_value (new octave_complex (Complex (re_val, im_val))); - } - else - { - const NDArray im_val = im.array_value (); - - if (! error_state) - { - ComplexNDArray result (im_val.dims (), Complex ()); - - for (octave_idx_type i = 0; i < im_val.numel (); i++) - result.xelem (i) = Complex (re_val, im_val(i)); - - retval = octave_value (new octave_complex_matrix (result)); - } - } - } + { + double re_val = re.double_value (); + + if (im.numel () == 1) + { + double im_val = im.double_value (); + + if (! error_state) + retval = octave_value (new octave_complex (Complex (re_val, im_val))); + } + else + { + const NDArray im_val = im.array_value (); + + if (! error_state) + { + ComplexNDArray result (im_val.dims (), Complex ()); + + for (octave_idx_type i = 0; i < im_val.numel (); i++) + result.xelem (i) = Complex (re_val, im_val(i)); + + retval = octave_value (new octave_complex_matrix (result)); + } + } + } else - { - const NDArray re_val = re.array_value (); - - if (im.numel () == 1) - { - double im_val = im.double_value (); - - if (! error_state) - { - ComplexNDArray result (re_val.dims (), Complex ()); - - for (octave_idx_type i = 0; i < re_val.numel (); i++) - result.xelem (i) = Complex (re_val(i), im_val); - - retval = octave_value (new octave_complex_matrix (result)); - } - } - else - { - const NDArray im_val = im.array_value (); - - if (! error_state) - { - if (re_val.dims () == im_val.dims ()) - { - ComplexNDArray result (re_val.dims (), Complex ()); - - for (octave_idx_type i = 0; i < re_val.numel (); i++) - result.xelem (i) = Complex (re_val(i), im_val(i)); - - retval = octave_value (new octave_complex_matrix (result)); - } - else - error ("complex: dimension mismatch"); - } - } - } + { + const NDArray re_val = re.array_value (); + + if (im.numel () == 1) + { + double im_val = im.double_value (); + + if (! error_state) + { + ComplexNDArray result (re_val.dims (), Complex ()); + + for (octave_idx_type i = 0; i < re_val.numel (); i++) + result.xelem (i) = Complex (re_val(i), im_val); + + retval = octave_value (new octave_complex_matrix (result)); + } + } + else + { + const NDArray im_val = im.array_value (); + + if (! error_state) + { + if (re_val.dims () == im_val.dims ()) + { + ComplexNDArray result (re_val.dims (), Complex ()); + + for (octave_idx_type i = 0; i < re_val.numel (); i++) + result.xelem (i) = Complex (re_val(i), im_val(i)); + + retval = octave_value (new octave_complex_matrix (result)); + } + else + error ("complex: dimension mismatch"); + } + } + } if (error_state) - error ("complex: invalid conversion"); + error ("complex: invalid conversion"); } else print_usage (); @@ -3403,7 +3403,7 @@ dt = oct_data_conv::string_to_data_type (nm); if (error_state) - return retval; + return retval; } switch (nargin) @@ -3417,18 +3417,18 @@ default: { - dims.resize (nargin); - - for (int i = 0; i < nargin; i++) - { - dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); - - if (error_state) - { - error ("%s: expecting scalar integer arguments", fcn); - break; - } - } + dims.resize (nargin); + + for (int i = 0; i < nargin; i++) + { + dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); + + if (error_state) + { + error ("%s: expecting scalar integer arguments", fcn); + break; + } + } } break; } @@ -3447,63 +3447,63 @@ // NDArray to scalar. if (! error_state) - { - switch (dt) - { - case oct_data_conv::dt_int8: - retval = int8NDArray (dims, val); - break; - - case oct_data_conv::dt_uint8: - retval = uint8NDArray (dims, val); - break; - - case oct_data_conv::dt_int16: - retval = int16NDArray (dims, val); - break; - - case oct_data_conv::dt_uint16: - retval = uint16NDArray (dims, val); - break; - - case oct_data_conv::dt_int32: - retval = int32NDArray (dims, val); - break; - - case oct_data_conv::dt_uint32: - retval = uint32NDArray (dims, val); - break; - - case oct_data_conv::dt_int64: - retval = int64NDArray (dims, val); - break; - - case oct_data_conv::dt_uint64: - retval = uint64NDArray (dims, val); - break; - - case oct_data_conv::dt_single: - retval = FloatNDArray (dims, val); - break; - - case oct_data_conv::dt_double: + { + switch (dt) + { + case oct_data_conv::dt_int8: + retval = int8NDArray (dims, val); + break; + + case oct_data_conv::dt_uint8: + retval = uint8NDArray (dims, val); + break; + + case oct_data_conv::dt_int16: + retval = int16NDArray (dims, val); + break; + + case oct_data_conv::dt_uint16: + retval = uint16NDArray (dims, val); + break; + + case oct_data_conv::dt_int32: + retval = int32NDArray (dims, val); + break; + + case oct_data_conv::dt_uint32: + retval = uint32NDArray (dims, val); + break; + + case oct_data_conv::dt_int64: + retval = int64NDArray (dims, val); + break; + + case oct_data_conv::dt_uint64: + retval = uint64NDArray (dims, val); + break; + + case oct_data_conv::dt_single: + retval = FloatNDArray (dims, val); + break; + + case oct_data_conv::dt_double: { if (val == 1 && dims.length () == 2 && dims (0) == 1) retval = Range (1.0, 0.0, dims (1)); // packed form else retval = NDArray (dims, val); } - break; - - case oct_data_conv::dt_logical: - retval = boolNDArray (dims, val); - break; - - default: - error ("%s: invalid class name", fcn); - break; - } - } + break; + + case oct_data_conv::dt_logical: + retval = boolNDArray (dims, val); + break; + + default: + error ("%s: invalid class name", fcn); + break; + } + } } return retval; @@ -3511,7 +3511,7 @@ static octave_value fill_matrix (const octave_value_list& args, double val, float fval, - const char *fcn) + const char *fcn) { octave_value retval; @@ -3529,7 +3529,7 @@ dt = oct_data_conv::string_to_data_type (nm); if (error_state) - return retval; + return retval; } switch (nargin) @@ -3543,18 +3543,18 @@ default: { - dims.resize (nargin); - - for (int i = 0; i < nargin; i++) - { - dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); - - if (error_state) - { - error ("%s: expecting scalar integer arguments", fcn); - break; - } - } + dims.resize (nargin); + + for (int i = 0; i < nargin; i++) + { + dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); + + if (error_state) + { + error ("%s: expecting scalar integer arguments", fcn); + break; + } + } } break; } @@ -3569,22 +3569,22 @@ // NDArray to scalar. if (! error_state) - { - switch (dt) - { - case oct_data_conv::dt_single: - retval = FloatNDArray (dims, fval); - break; - - case oct_data_conv::dt_double: - retval = NDArray (dims, val); - break; - - default: - error ("%s: invalid class name", fcn); - break; - } - } + { + switch (dt) + { + case oct_data_conv::dt_single: + retval = FloatNDArray (dims, fval); + break; + + case oct_data_conv::dt_double: + retval = NDArray (dims, val); + break; + + default: + error ("%s: invalid class name", fcn); + break; + } + } } return retval; @@ -3609,7 +3609,7 @@ dt = oct_data_conv::string_to_data_type (nm); if (error_state) - return retval; + return retval; } switch (nargin) @@ -3623,18 +3623,18 @@ default: { - dims.resize (nargin); - - for (int i = 0; i < nargin; i++) - { - dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); - - if (error_state) - { - error ("%s: expecting scalar integer arguments", fcn); - break; - } - } + dims.resize (nargin); + + for (int i = 0; i < nargin; i++) + { + dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); + + if (error_state) + { + error ("%s: expecting scalar integer arguments", fcn); + break; + } + } } break; } @@ -3649,22 +3649,22 @@ // NDArray to scalar. if (! error_state) - { - switch (dt) - { - case oct_data_conv::dt_single: - retval = FloatNDArray (dims, static_cast <float> (val)); - break; - - case oct_data_conv::dt_double: - retval = NDArray (dims, val); - break; - - default: - error ("%s: invalid class name", fcn); - break; - } - } + { + switch (dt) + { + case oct_data_conv::dt_single: + retval = FloatNDArray (dims, static_cast <float> (val)); + break; + + case oct_data_conv::dt_double: + retval = NDArray (dims, val); + break; + + default: + error ("%s: invalid class name", fcn); + break; + } + } } return retval; @@ -3672,7 +3672,7 @@ static octave_value fill_matrix (const octave_value_list& args, const Complex& val, - const char *fcn) + const char *fcn) { octave_value retval; @@ -3690,7 +3690,7 @@ dt = oct_data_conv::string_to_data_type (nm); if (error_state) - return retval; + return retval; } switch (nargin) @@ -3704,18 +3704,18 @@ default: { - dims.resize (nargin); - - for (int i = 0; i < nargin; i++) - { - dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); - - if (error_state) - { - error ("%s: expecting scalar integer arguments", fcn); - break; - } - } + dims.resize (nargin); + + for (int i = 0; i < nargin; i++) + { + dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); + + if (error_state) + { + error ("%s: expecting scalar integer arguments", fcn); + break; + } + } } break; } @@ -3730,22 +3730,22 @@ // NDArray to scalar. if (! error_state) - { - switch (dt) - { - case oct_data_conv::dt_single: - retval = FloatComplexNDArray (dims, static_cast<FloatComplex> (val)); - break; - - case oct_data_conv::dt_double: - retval = ComplexNDArray (dims, val); - break; - - default: - error ("%s: invalid class name", fcn); - break; - } - } + { + switch (dt) + { + case oct_data_conv::dt_single: + retval = FloatComplexNDArray (dims, static_cast<FloatComplex> (val)); + break; + + case oct_data_conv::dt_double: + retval = ComplexNDArray (dims, val); + break; + + default: + error ("%s: invalid class name", fcn); + break; + } + } } return retval; @@ -3771,18 +3771,18 @@ default: { - dims.resize (nargin); - - for (int i = 0; i < nargin; i++) - { - dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); - - if (error_state) - { - error ("%s: expecting scalar integer arguments", fcn); - break; - } - } + dims.resize (nargin); + + for (int i = 0; i < nargin; i++) + { + dims(i) = args(i).is_empty () ? 0 : args(i).idx_type_value (); + + if (error_state) + { + error ("%s: expecting scalar integer arguments", fcn); + break; + } + } } break; } @@ -3797,7 +3797,7 @@ // NDArray to scalar. if (! error_state) - retval = boolNDArray (dims, val); + retval = boolNDArray (dims, val); } return retval; @@ -3923,7 +3923,7 @@ @end deftypefn") { return fill_matrix (args, lo_ieee_inf_value (), - lo_ieee_float_inf_value (), "Inf"); + lo_ieee_float_inf_value (), "Inf"); } DEFALIAS (inf, Inf); @@ -3981,7 +3981,7 @@ @end deftypefn") { return fill_matrix (args, lo_ieee_nan_value (), - lo_ieee_float_nan_value (), "NaN"); + lo_ieee_float_nan_value (), "NaN"); } DEFALIAS (nan, NaN); @@ -4075,55 +4075,55 @@ if (nargin == 1 && ! args(0).is_string ()) { if (args(0).is_single_type ()) - { - float val = args(0).float_value (); - - if (! error_state) - { - val = ::fabsf(val); - if (xisnan (val) || xisinf (val)) - retval = fill_matrix (octave_value ("single"), - lo_ieee_nan_value (), - lo_ieee_float_nan_value (), "eps"); - else if (val < FLT_MIN) - retval = fill_matrix (octave_value ("single"), 0e0, - powf (2.0, -149e0), "eps"); - else - { - int expon; - frexpf (val, &expon); - val = std::pow (static_cast <float> (2.0), - static_cast <float> (expon - 24)); - retval = fill_matrix (octave_value ("single"), DBL_EPSILON, - val, "eps"); - } - } - } + { + float val = args(0).float_value (); + + if (! error_state) + { + val = ::fabsf(val); + if (xisnan (val) || xisinf (val)) + retval = fill_matrix (octave_value ("single"), + lo_ieee_nan_value (), + lo_ieee_float_nan_value (), "eps"); + else if (val < FLT_MIN) + retval = fill_matrix (octave_value ("single"), 0e0, + powf (2.0, -149e0), "eps"); + else + { + int expon; + frexpf (val, &expon); + val = std::pow (static_cast <float> (2.0), + static_cast <float> (expon - 24)); + retval = fill_matrix (octave_value ("single"), DBL_EPSILON, + val, "eps"); + } + } + } else - { - double val = args(0).double_value (); - - if (! error_state) - { - val = ::fabs(val); - if (xisnan (val) || xisinf (val)) - retval = fill_matrix (octave_value_list (), - lo_ieee_nan_value (), - lo_ieee_float_nan_value (), "eps"); - else if (val < DBL_MIN) - retval = fill_matrix (octave_value_list (), - pow (2.0, -1074e0), 0e0, "eps"); - else - { - int expon; - frexp (val, &expon); - val = std::pow (static_cast <double> (2.0), - static_cast <double> (expon - 53)); - retval = fill_matrix (octave_value_list (), val, - FLT_EPSILON, "eps"); - } - } - } + { + double val = args(0).double_value (); + + if (! error_state) + { + val = ::fabs(val); + if (xisnan (val) || xisinf (val)) + retval = fill_matrix (octave_value_list (), + lo_ieee_nan_value (), + lo_ieee_float_nan_value (), "eps"); + else if (val < DBL_MIN) + retval = fill_matrix (octave_value_list (), + pow (2.0, -1074e0), 0e0, "eps"); + else + { + int expon; + frexp (val, &expon); + val = std::pow (static_cast <double> (2.0), + static_cast <double> (expon - 53)); + retval = fill_matrix (octave_value_list (), val, + FLT_EPSILON, "eps"); + } + } + } } else retval = fill_matrix (args, DBL_EPSILON, FLT_EPSILON, "eps"); @@ -4320,7 +4320,7 @@ @end deftypefn") { return fill_matrix (args, lo_ieee_na_value (), - lo_ieee_float_na_value (), "NA"); + lo_ieee_float_na_value (), "NA"); } /* @@ -4373,12 +4373,12 @@ MT m (dims, zero); if (nr > 0 && nc > 0) - { - int n = std::min (nr, nc); - - for (int i = 0; i < n; i++) - m(i,i) = one; - } + { + int n = std::min (nr, nc); + + for (int i = 0; i < n; i++) + m(i,i) = one; + } retval = m; } @@ -4413,55 +4413,55 @@ if (! error_state) { switch (dt) - { - case oct_data_conv::dt_int8: - retval = identity_matrix<int8NDArray> (nr, nc); - break; - - case oct_data_conv::dt_uint8: - retval = identity_matrix<uint8NDArray> (nr, nc); - break; - - case oct_data_conv::dt_int16: - retval = identity_matrix<int16NDArray> (nr, nc); - break; - - case oct_data_conv::dt_uint16: - retval = identity_matrix<uint16NDArray> (nr, nc); - break; - - case oct_data_conv::dt_int32: - retval = identity_matrix<int32NDArray> (nr, nc); - break; - - case oct_data_conv::dt_uint32: - retval = identity_matrix<uint32NDArray> (nr, nc); - break; - - case oct_data_conv::dt_int64: - retval = identity_matrix<int64NDArray> (nr, nc); - break; - - case oct_data_conv::dt_uint64: - retval = identity_matrix<uint64NDArray> (nr, nc); - break; - - case oct_data_conv::dt_single: - retval = FloatDiagMatrix (nr, nc, 1.0f); - break; - - case oct_data_conv::dt_double: - retval = DiagMatrix (nr, nc, 1.0); - break; - - case oct_data_conv::dt_logical: - retval = identity_matrix<boolNDArray> (nr, nc); - break; - - default: - error ("eye: invalid class name"); - break; - } + { + case oct_data_conv::dt_int8: + retval = identity_matrix<int8NDArray> (nr, nc); + break; + + case oct_data_conv::dt_uint8: + retval = identity_matrix<uint8NDArray> (nr, nc); + break; + + case oct_data_conv::dt_int16: + retval = identity_matrix<int16NDArray> (nr, nc); + break; + + case oct_data_conv::dt_uint16: + retval = identity_matrix<uint16NDArray> (nr, nc); + break; + + case oct_data_conv::dt_int32: + retval = identity_matrix<int32NDArray> (nr, nc); + break; + + case oct_data_conv::dt_uint32: + retval = identity_matrix<uint32NDArray> (nr, nc); + break; + + case oct_data_conv::dt_int64: + retval = identity_matrix<int64NDArray> (nr, nc); + break; + + case oct_data_conv::dt_uint64: + retval = identity_matrix<uint64NDArray> (nr, nc); + break; + + case oct_data_conv::dt_single: + retval = FloatDiagMatrix (nr, nc, 1.0f); + break; + + case oct_data_conv::dt_double: + retval = DiagMatrix (nr, nc, 1.0); + break; + + case oct_data_conv::dt_logical: + retval = identity_matrix<boolNDArray> (nr, nc); + break; + + default: + error ("eye: invalid class name"); + break; + } } return retval; @@ -4530,7 +4530,7 @@ dt = oct_data_conv::string_to_data_type (nm); if (error_state) - return retval; + return retval; } switch (nargin) @@ -4541,21 +4541,21 @@ case 1: { - octave_idx_type nr, nc; - get_dimensions (args(0), "eye", nr, nc); - - if (! error_state) - retval = identity_matrix (nr, nc, dt); + octave_idx_type nr, nc; + get_dimensions (args(0), "eye", nr, nc); + + if (! error_state) + retval = identity_matrix (nr, nc, dt); } break; case 2: { - octave_idx_type nr, nc; - get_dimensions (args(0), args(1), "eye", nr, nc); - - if (! error_state) - retval = identity_matrix (nr, nc, dt); + octave_idx_type nr, nc; + get_dimensions (args(0), args(1), "eye", nr, nc); + + if (! error_state) + retval = identity_matrix (nr, nc, dt); } break; @@ -4666,20 +4666,20 @@ octave_value arg_2 = args(1); if (arg_1.is_single_type () || arg_2.is_single_type ()) - { - if (arg_1.is_complex_type () || arg_2.is_complex_type ()) + { + if (arg_1.is_complex_type () || arg_2.is_complex_type ()) retval = do_linspace<FloatComplexMatrix> (arg_1, arg_2, npoints); - else + else retval = do_linspace<FloatMatrix> (arg_1, arg_2, npoints); - - } + + } else - { - if (arg_1.is_complex_type () || arg_2.is_complex_type ()) + { + if (arg_1.is_complex_type () || arg_2.is_complex_type ()) retval = do_linspace<ComplexMatrix> (arg_1, arg_2, npoints); - else + else retval = do_linspace<Matrix> (arg_1, arg_2, npoints); - } + } } else error ("linspace: expecting third argument to be an integer"); @@ -4764,20 +4764,20 @@ Array<double> vec = args(1).vector_value (); int ndim = vec.length (); if (ndim == 1) - { - octave_idx_type m = static_cast<octave_idx_type> (vec(0)); - retval = args(0); - retval = retval.resize (dim_vector (m, m), true); - } + { + octave_idx_type m = static_cast<octave_idx_type> (vec(0)); + retval = args(0); + retval = retval.resize (dim_vector (m, m), true); + } else - { - dim_vector dv; - dv.resize (ndim); - for (int i = 0; i < ndim; i++) - dv(i) = static_cast<octave_idx_type> (vec(i)); - retval = args(0); - retval = retval.resize (dv, true); - } + { + dim_vector dv; + dv.resize (ndim); + for (int i = 0; i < ndim; i++) + dv(i) = static_cast<octave_idx_type> (vec(i)); + retval = args(0); + retval = retval.resize (dv, true); + } } else if (nargin > 2) { @@ -4786,10 +4786,10 @@ for (octave_idx_type i = 1; i < nargin; i++) dv(i-1) = static_cast<octave_idx_type> (args(i).scalar_value ()); if (!error_state) - { - retval = args(0); - retval = retval.resize (dv, true); - } + { + retval = args(0); + retval = retval.resize (dv, true); + } } else @@ -4839,45 +4839,45 @@ int empty_dim = -1; for (int i = 1; i < nargin; i++) - { - if (args(i).is_empty ()) - if (empty_dim > 0) - { - error ("reshape: only a single dimension can be unknown"); - break; - } - else - { - empty_dim = i; - new_size(i-1) = 1; - } - else - { - new_size(i-1) = args(i).idx_type_value (); - - if (error_state) - break; - } - } + { + if (args(i).is_empty ()) + if (empty_dim > 0) + { + error ("reshape: only a single dimension can be unknown"); + break; + } + else + { + empty_dim = i; + new_size(i-1) = 1; + } + else + { + new_size(i-1) = args(i).idx_type_value (); + + if (error_state) + break; + } + } if (! error_state && (empty_dim > 0)) - { - int nel = 1; - for (int i = 0; i < nargin - 1; i++) - nel *= new_size(i); - - if (nel == 0) - new_size(empty_dim-1) = 0; - else - { - int size_empty_dim = args(0).numel () / nel; - - if (args(0).numel () != size_empty_dim * nel) - error ("reshape: size is not divisble by the product of known dimensions (= %d)", nel); - else - new_size(empty_dim-1) = size_empty_dim; - } - } + { + int nel = 1; + for (int i = 0; i < nargin - 1; i++) + nel *= new_size(i); + + if (nel == 0) + new_size(empty_dim-1) = 0; + else + { + int size_empty_dim = args(0).numel () / nel; + + if (args(0).numel () != size_empty_dim * nel) + error ("reshape: size is not divisble by the product of known dimensions (= %d)", nel); + else + new_size(empty_dim-1) = size_empty_dim; + } + } } else { @@ -4899,9 +4899,9 @@ while (n > 2) { if (new_size(n-1) == 1) - n--; + n--; else - break; + break; } new_size.resize (n); @@ -4931,7 +4931,7 @@ std::string new_dims_str = new_dims.str (); error ("reshape: can't reshape %s array to %s array", - dims_str.c_str (), new_dims_str.c_str ()); + dims_str.c_str (), new_dims_str.c_str ()); } return retval; @@ -5060,7 +5060,7 @@ octave_value x_arg = args(0); if (x_arg.ndims () == 2) - { + { enum { sfmatrix, sfcols, sfrows, sffrob, sfinf } strflag = sfmatrix; if (nargin > 1 && args(nargin-1).is_string ()) { @@ -5103,9 +5103,9 @@ break; } } - } + } else - error ("norm: only valid for 2-D objects"); + error ("norm: only valid for 2-D objects"); } else print_usage (); @@ -5614,7 +5614,7 @@ { warning ("toc called before timer set"); if (nargout > 0) - retval = Matrix (); + retval = Matrix (); } else { @@ -5623,9 +5623,9 @@ double tmp = now.double_value () - tic_toc_timestamp; if (nargout > 0) - retval = tmp; + retval = tmp; else - octave_stdout << "Elapsed time is " << tmp << " seconds.\n"; + octave_stdout << "Elapsed time is " << tmp << " seconds.\n"; } return retval; @@ -5768,45 +5768,45 @@ if (nargin > 1) { if (args(1).is_string ()) - { - std::string mode = args(1).string_value(); - if (mode == "ascend") - smode = ASCENDING; - else if (mode == "descend") - smode = DESCENDING; - else - { - error ("sort: mode must be either \"ascend\" or \"descend\""); - return retval; - } - } + { + std::string mode = args(1).string_value(); + if (mode == "ascend") + smode = ASCENDING; + else if (mode == "descend") + smode = DESCENDING; + else + { + error ("sort: mode must be either \"ascend\" or \"descend\""); + return retval; + } + } else - dim = args(1).nint_value () - 1; + dim = args(1).nint_value () - 1; } if (nargin > 2) { if (args(1).is_string ()) - { - print_usage (); - return retval; - } + { + print_usage (); + return retval; + } if (! args(2).is_string ()) - { - error ("sort: mode must be a string"); - return retval; - } + { + error ("sort: mode must be a string"); + return retval; + } std::string mode = args(2).string_value(); if (mode == "ascend") - smode = ASCENDING; + smode = ASCENDING; else if (mode == "descend") - smode = DESCENDING; + smode = DESCENDING; else - { - error ("sort: mode must be either \"ascend\" or \"descend\""); - return retval; - } + { + error ("sort: mode must be either \"ascend\" or \"descend\""); + return retval; + } } const dim_vector dv = arg.dims (); @@ -5818,10 +5818,10 @@ else { if (dim < 0 || dim > dv.length () - 1) - { - error ("sort: dim must be a valid dimension"); - return retval; - } + { + error ("sort: dim must be a valid dimension"); + return retval; + } } if (return_idx) @@ -6125,22 +6125,22 @@ octave_value mode_arg; if (nargin == 3) - smode = get_sort_mode_option (args(2), "third"); + smode = get_sort_mode_option (args(2), "third"); std::string tmp = args(1).string_value (); if (! error_state) - { - if (tmp == "rows") - by_rows = true; - else - smode = get_sort_mode_option (args(1), "second"); - } + { + if (tmp == "rows") + by_rows = true; + else + smode = get_sort_mode_option (args(1), "second"); + } else - error ("expecting second argument to be character string"); + error ("expecting second argument to be character string"); if (error_state) - return retval; + return retval; } octave_value arg = args(0); @@ -6148,16 +6148,16 @@ if (by_rows) { if (arg.is_sparse_type ()) - error ("issorted: sparse matrices not yet supported"); + error ("issorted: sparse matrices not yet supported"); if (arg.ndims () == 2) - retval = arg.is_sorted_rows (smode) != UNSORTED; + retval = arg.is_sorted_rows (smode) != UNSORTED; else - error ("issorted: needs a 2-dimensional object"); + error ("issorted: needs a 2-dimensional object"); } else { if (arg.dims ().is_vector ()) - retval = args(0).is_sorted (smode) != UNSORTED; + retval = args(0).is_sorted (smode) != UNSORTED; else error ("issorted: needs a vector"); }