Mercurial > hg > octave-nkf
view liboctave/Array.cc @ 4642:7a83d52d2aed
[project @ 2003-11-22 12:19:34 by jwe]
author | jwe |
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date | Sat, 22 Nov 2003 12:20:33 +0000 |
parents | f2cd320cbf6e |
children | b868b39534b0 |
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// Template array classes /* Copyright (C) 1996, 1997 John W. Eaton This file is part of Octave. Octave is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2, or (at your option) any later version. Octave is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with Octave; see the file COPYING. If not, write to the Free Software Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. */ #if defined (__GNUG__) && defined (USE_PRAGMA_INTERFACE_IMPLEMENTATION) #pragma implementation #endif #ifdef HAVE_CONFIG_H #include <config.h> #endif #include <cassert> #include <climits> #include <iostream> #include "Array.h" #include "Array-flags.h" #include "Array-util.h" #include "Range.h" #include "idx-vector.h" #include "lo-error.h" // One dimensional array class. Handles the reference counting for // all the derived classes. template <class T> Array<T>::~Array (void) { if (--rep->count <= 0) delete rep; delete [] idx; } template <class T> Array<T> Array<T>::squeeze (void) const { Array<T> retval = *this; bool dims_changed = false; dim_vector new_dimensions = dimensions; int k = 0; for (int i = 0; i < ndims (); i++) { if (dimensions(i) == 1) dims_changed = true; else new_dimensions(k++) = dimensions(i); } if (dims_changed) { if (k == 0) new_dimensions = dim_vector (1); else new_dimensions.resize (k); retval.make_unique (); retval.dimensions = new_dimensions; } return retval; } // A guess (should be quite conservative). #define MALLOC_OVERHEAD 1024 template <class T> int Array<T>::get_size (int r, int c) { // XXX KLUGE XXX // If an allocation of an array with r * c elements of type T // would cause an overflow in the allocator when computing the // size of the allocation, then return a value which, although // not equivalent to the actual request, should be too large for // most current hardware, but not so large to cause the // allocator to barf on computing retval * sizeof (T). static int nl; static double dl = frexp (static_cast<double> (INT_MAX - MALLOC_OVERHEAD) / sizeof (T), &nl); // This value should be an integer. If we return this value and // things work the way we expect, we should be paying a visit to // new_handler in no time flat. static int max_items = static_cast<int> (ldexp (dl, nl)); int nr, nc; double dr = frexp (static_cast<double> (r), &nr); double dc = frexp (static_cast<double> (c), &nc); int nt = nr + nc; double dt = dr * dc; if (dt < 0.5) { nt--; dt *= 2; } return (nt < nl || (nt == nl && dt < dl)) ? r * c : max_items; } template <class T> int Array<T>::get_size (int r, int c, int p) { // XXX KLUGE XXX // If an allocation of an array with r * c * p elements of type T // would cause an overflow in the allocator when computing the // size of the allocation, then return a value which, although // not equivalent to the actual request, should be too large for // most current hardware, but not so large to cause the // allocator to barf on computing retval * sizeof (T). static int nl; static double dl = frexp (static_cast<double> (INT_MAX - MALLOC_OVERHEAD) / sizeof (T), &nl); // This value should be an integer. If we return this value and // things work the way we expect, we should be paying a visit to // new_handler in no time flat. static int max_items = static_cast<int> (ldexp (dl, nl)); int nr, nc, np; double dr = frexp (static_cast<double> (r), &nr); double dc = frexp (static_cast<double> (c), &nc); double dp = frexp (static_cast<double> (p), &np); int nt = nr + nc + np; double dt = dr * dc * dp; if (dt < 0.5) { nt--; dt *= 2; if (dt < 0.5) { nt--; dt *= 2; } } return (nt < nl || (nt == nl && dt < dl)) ? r * c * p : max_items; } template <class T> int Array<T>::get_size (const dim_vector& ra_idx) { // XXX KLUGE XXX // If an allocation of an array with r * c elements of type T // would cause an overflow in the allocator when computing the // size of the allocation, then return a value which, although // not equivalent to the actual request, should be too large for // most current hardware, but not so large to cause the // allocator to barf on computing retval * sizeof (T). static int nl; static double dl = frexp (static_cast<double> (INT_MAX - MALLOC_OVERHEAD) / sizeof (T), &nl); // This value should be an integer. If we return this value and // things work the way we expect, we should be paying a visit to // new_handler in no time flat. static int max_items = static_cast<int> (ldexp (dl, nl)); int retval = max_items; int n = ra_idx.length (); int nt = 0; double dt = 1; for (int i = 0; i < n; i++) { int nra_idx; double dra_idx = frexp (static_cast<double> (ra_idx(i)), &nra_idx); nt += nra_idx; dt *= dra_idx; if (dt < 0.5) { nt--; dt *= 2; } } if (nt < nl || (nt == nl && dt < dl)) { retval = 1; for (int i = 0; i < n; i++) retval *= ra_idx(i); } return retval; } #undef MALLOC_OVERHEAD template <class T> int Array<T>::compute_index (const Array<int>& ra_idx) const { int retval = -1; int n = dimensions.length (); if (n > 0 && n == ra_idx.length ()) { retval = ra_idx(--n); while (--n >= 0) { retval *= dimensions(n); retval += ra_idx(n); } } else (*current_liboctave_error_handler) ("Array<T>::compute_index: invalid ra_idxing operation"); return retval; } template <class T> T Array<T>::range_error (const char *fcn, int n) const { (*current_liboctave_error_handler) ("%s (%d): range error", fcn, n); return T (); } template <class T> T& Array<T>::range_error (const char *fcn, int n) { (*current_liboctave_error_handler) ("%s (%d): range error", fcn, n); static T foo; return foo; } template <class T> T Array<T>::range_error (const char *fcn, int i, int j) const { (*current_liboctave_error_handler) ("%s (%d, %d): range error", fcn, i, j); return T (); } template <class T> T& Array<T>::range_error (const char *fcn, int i, int j) { (*current_liboctave_error_handler) ("%s (%d, %d): range error", fcn, i, j); static T foo; return foo; } template <class T> T Array<T>::range_error (const char *fcn, int i, int j, int k) const { (*current_liboctave_error_handler) ("%s (%d, %d, %d): range error", fcn, i, j, k); return T (); } template <class T> T& Array<T>::range_error (const char *fcn, int i, int j, int k) { (*current_liboctave_error_handler) ("%s (%d, %d, %d): range error", fcn, i, j, k); static T foo; return foo; } template <class T> T Array<T>::range_error (const char *fcn, const Array<int>& ra_idx) const { // XXX FIXME XXX -- report index values too! (*current_liboctave_error_handler) ("range error in Array"); return T (); } template <class T> T& Array<T>::range_error (const char *fcn, const Array<int>& ra_idx) { // XXX FIXME XXX -- report index values too! (*current_liboctave_error_handler) ("range error in Array"); static T foo; return foo; } template <class T> Array<T> Array<T>::reshape (const dim_vector& new_dims) const { Array<T> retval; if (dimensions != new_dims) { if (dimensions.numel () == new_dims.numel ()) retval = Array<T> (*this, new_dims); else (*current_liboctave_error_handler) ("reshape: size mismatch"); } return retval; } template <class T> Array<T> Array<T>::permute (const Array<int>& perm_vec, bool inv) const { Array<T> retval; dim_vector dv = dims (); dim_vector dv_new; int nd = dv.length (); dv_new.resize (nd); // Need this array to check for identical elements in permutation array. Array<bool> checked (nd, false); // Find dimension vector of permuted array. for (int i = 0; i < nd; i++) { int perm_el = perm_vec.elem (i); if (perm_el > dv.length () || perm_el < 1) { (*current_liboctave_error_handler) ("permutation vector contains an invalid element"); return retval; } if (checked.elem(perm_el - 1)) { (*current_liboctave_error_handler) ("PERM cannot contain identical elements"); return retval; } else checked.elem(perm_el - 1) = true; dv_new (i) = dv (perm_el - 1); } retval.resize (dv_new); // Index array to the original array. Array<int> old_idx (nd, 0); // Number of elements in Array (should be the same for // both the permuted array and original array). int n = retval.length (); // Permute array. for (int i = 0; i < n; i++) { // Get the idx of permuted array. Array<int> new_idx = calc_permutated_idx (old_idx, perm_vec, inv); retval.elem (new_idx) = elem (old_idx); increment_index (old_idx, dv); } return retval; } template <class T> void Array<T>::resize_no_fill (int n) { if (n < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } if (n == length ()) return; typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); int old_len = length (); rep = new typename Array<T>::ArrayRep (n); dimensions = dim_vector (n); if (old_data && old_len > 0) { int min_len = old_len < n ? old_len : n; for (int i = 0; i < min_len; i++) xelem (i) = old_data[i]; } if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_no_fill (const dim_vector& dv) { int n = dv.length (); for (int i = 0; i < n; i++) { if (dv(i) < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } } bool same_size = true; if (dimensions.length () != n) { same_size = false; } else { for (int i = 0; i < n; i++) { if (dv(i) != dimensions(i)) { same_size = false; break; } } } if (same_size) return; int old_len = length (); typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); rep = new typename Array<T>::ArrayRep (get_size (dv)); dimensions = dv; Array<int> ra_idx (dimensions.length (), 0); for (int i = 0; i < old_len; i++) { if (index_in_bounds (ra_idx, dimensions)) xelem (ra_idx) = old_data[i]; increment_index (ra_idx, dimensions); } if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_no_fill (int r, int c) { if (r < 0 || c < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } int n = ndims (); if (n == 0) dimensions = dim_vector (0, 0); assert (ndims () == 2); if (r == dim1 () && c == dim2 ()) return; typename Array<T>::ArrayRep *old_rep = Array<T>::rep; const T *old_data = data (); int old_d1 = dim1 (); int old_d2 = dim2 (); int old_len = length (); rep = new typename Array<T>::ArrayRep (get_size (r, c)); dimensions = dim_vector (r, c); if (old_data && old_len > 0) { int min_r = old_d1 < r ? old_d1 : r; int min_c = old_d2 < c ? old_d2 : c; for (int j = 0; j < min_c; j++) for (int i = 0; i < min_r; i++) xelem (i, j) = old_data[old_d1*j+i]; } if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_no_fill (int r, int c, int p) { if (r < 0 || c < 0 || p < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } int n = ndims (); if (n == 0) dimensions = dim_vector (0, 0, 0); assert (ndims () == 3); if (r == dim1 () && c == dim2 () && p == dim3 ()) return; typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); int old_d1 = dim1 (); int old_d2 = dim2 (); int old_d3 = dim3 (); int old_len = length (); int ts = get_size (get_size (r, c), p); rep = new typename Array<T>::ArrayRep (ts); dimensions = dim_vector (r, c, p); if (old_data && old_len > 0) { int min_r = old_d1 < r ? old_d1 : r; int min_c = old_d2 < c ? old_d2 : c; int min_p = old_d3 < p ? old_d3 : p; for (int k = 0; k < min_p; k++) for (int j = 0; j < min_c; j++) for (int i = 0; i < min_r; i++) xelem (i, j, k) = old_data[old_d1*(old_d2*k+j)+i]; } if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_and_fill (int n, const T& val) { if (n < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } if (n == length ()) return; typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); int old_len = length (); rep = new typename Array<T>::ArrayRep (n); dimensions = dim_vector (n); int min_len = old_len < n ? old_len : n; if (old_data && old_len > 0) { for (int i = 0; i < min_len; i++) xelem (i) = old_data[i]; } for (int i = old_len; i < n; i++) xelem (i) = val; if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_and_fill (int r, int c, const T& val) { if (r < 0 || c < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } if (ndims () == 0) dimensions = dim_vector (0, 0); assert (ndims () == 2); if (r == dim1 () && c == dim2 ()) return; typename Array<T>::ArrayRep *old_rep = Array<T>::rep; const T *old_data = data (); int old_d1 = dim1 (); int old_d2 = dim2 (); int old_len = length (); rep = new typename Array<T>::ArrayRep (get_size (r, c)); dimensions = dim_vector (r, c); int min_r = old_d1 < r ? old_d1 : r; int min_c = old_d2 < c ? old_d2 : c; if (old_data && old_len > 0) { for (int j = 0; j < min_c; j++) for (int i = 0; i < min_r; i++) xelem (i, j) = old_data[old_d1*j+i]; } for (int j = 0; j < min_c; j++) for (int i = min_r; i < r; i++) xelem (i, j) = val; for (int j = min_c; j < c; j++) for (int i = 0; i < r; i++) xelem (i, j) = val; if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_and_fill (int r, int c, int p, const T& val) { if (r < 0 || c < 0 || p < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } if (ndims () == 0) dimensions = dim_vector (0, 0, 0); assert (ndims () == 3); if (r == dim1 () && c == dim2 () && p == dim3 ()) return; typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); int old_d1 = dim1 (); int old_d2 = dim2 (); int old_d3 = dim3 (); int old_len = length (); int ts = get_size (get_size (r, c), p); rep = new typename Array<T>::ArrayRep (ts); dimensions = dim_vector (r, c, p); int min_r = old_d1 < r ? old_d1 : r; int min_c = old_d2 < c ? old_d2 : c; int min_p = old_d3 < p ? old_d3 : p; if (old_data && old_len > 0) for (int k = 0; k < min_p; k++) for (int j = 0; j < min_c; j++) for (int i = 0; i < min_r; i++) xelem (i, j, k) = old_data[old_d1*(old_d2*k+j)+i]; // XXX FIXME XXX -- if the copy constructor is expensive, this may // win. Otherwise, it may make more sense to just copy the value // everywhere when making the new ArrayRep. for (int k = 0; k < min_p; k++) for (int j = min_c; j < c; j++) for (int i = 0; i < min_r; i++) xelem (i, j, k) = val; for (int k = 0; k < min_p; k++) for (int j = 0; j < c; j++) for (int i = min_r; i < r; i++) xelem (i, j, k) = val; for (int k = min_p; k < p; k++) for (int j = 0; j < c; j++) for (int i = 0; i < r; i++) xelem (i, j, k) = val; if (--old_rep->count <= 0) delete old_rep; } template <class T> void Array<T>::resize_and_fill (const dim_vector& dv, const T& val) { int n = dv.length (); for (int i = 0; i < n; i++) { if (dv(i) < 0) { (*current_liboctave_error_handler) ("can't resize to negative dimension"); return; } } bool same_size = true; if (dimensions.length () != n) { same_size = false; } else { for (int i = 0; i < n; i++) { if (dv(i) != dimensions(i)) { same_size = false; break; } } } if (same_size) return; typename Array<T>::ArrayRep *old_rep = rep; const T *old_data = data (); int old_len = length (); int len = get_size (dv); rep = new typename Array<T>::ArrayRep (len); dimensions = dv; Array<int> ra_idx (dimensions.length (), 0); // XXX FIXME XXX -- it is much simpler to fill the whole array // first, but probably slower for large arrays, or if the assignment // operator for the type T is expensive. OTOH, the logic for // deciding whether an element needs the copied value or the filled // value might be more expensive. for (int i = 0; i < len; i++) rep->elem (i) = val; for (int i = 0; i < old_len; i++) { if (index_in_bounds (ra_idx, dimensions)) xelem (ra_idx) = old_data[i]; increment_index (ra_idx, dimensions); } if (--old_rep->count <= 0) delete old_rep; } template <class T> Array<T>& Array<T>::insert (const Array<T>& a, int r, int c) { int a_rows = a.rows (); int a_cols = a.cols (); if (r < 0 || r + a_rows > rows () || c < 0 || c + a_cols > cols ()) { (*current_liboctave_error_handler) ("range error for insert"); return *this; } for (int j = 0; j < a_cols; j++) for (int i = 0; i < a_rows; i++) elem (r+i, c+j) = a.elem (i, j); return *this; } template <class T> Array<T>& Array<T>::insert (const Array<T>& a, const Array<int>& ra_idx) { int n = ra_idx.length (); if (n == dimensions.length ()) { dim_vector a_dims = a.dims (); for (int i = 0; i < n; i++) { if (ra_idx(i) < 0 || ra_idx(i) + a_dims(i) > dimensions(i)) { (*current_liboctave_error_handler) ("Array<T>::insert: range error for insert"); return *this; } } #if 0 // XXX FIXME XXX -- need to copy elements for (int j = 0; j < a_cols; j++) for (int i = 0; i < a_rows; i++) elem (r+i, c+j) = a.elem (i, j); #endif } else (*current_liboctave_error_handler) ("Array<T>::insert: invalid indexing operation"); return *this; } template <class T> Array<T> Array<T>::transpose (void) const { assert (ndims () == 2); int nr = dim1 (); int nc = dim2 (); if (nr > 1 && nc > 1) { Array<T> result (dim_vector (nc, nr)); for (int j = 0; j < nc; j++) for (int i = 0; i < nr; i++) result.xelem (j, i) = xelem (i, j); return result; } else { // Fast transpose for vectors and empty matrices return Array<T> (*this, dim_vector (nc, nr)); } } template <class T> T * Array<T>::fortran_vec (void) { if (rep->count > 1) { --rep->count; rep = new typename Array<T>::ArrayRep (*rep); } return rep->data; } template <class T> void Array<T>::maybe_delete_dims (void) { int nd = dimensions.length (); dim_vector new_dims (1, 1); bool delete_dims = true; for (int i = nd - 1; i >= 0; i--) { if (delete_dims) { if (dimensions(i) != 1) { delete_dims = false; new_dims = dim_vector (i + 1, dimensions(i)); } } else new_dims(i) = dimensions(i); } if (nd != new_dims.length ()) dimensions = new_dims; } template <class T> void Array<T>::clear_index (void) { delete [] idx; idx = 0; idx_count = 0; } template <class T> void Array<T>::set_index (const idx_vector& idx_arg) { int nd = ndims (); if (! idx && nd > 0) idx = new idx_vector [nd]; if (idx_count < nd) { idx[idx_count++] = idx_arg; } else { idx_vector *new_idx = new idx_vector [idx_count+1]; for (int i = 0; i < idx_count; i++) new_idx[i] = idx[i]; new_idx[idx_count++] = idx_arg; delete [] idx; idx = new_idx; } } template <class T> void Array<T>::maybe_delete_elements (idx_vector& idx_arg) { switch (ndims ()) { case 1: maybe_delete_elements_1 (idx_arg); break; case 2: maybe_delete_elements_2 (idx_arg); break; default: (*current_liboctave_error_handler) ("Array<T>::maybe_delete_elements: invalid operation"); break; } } template <class T> void Array<T>::maybe_delete_elements_1 (idx_vector& idx_arg) { int len = length (); if (len == 0) return; if (idx_arg.is_colon_equiv (len, 1)) resize_no_fill (0); else { int num_to_delete = idx_arg.length (len); if (num_to_delete != 0) { int new_len = len; int iidx = 0; for (int i = 0; i < len; i++) if (i == idx_arg.elem (iidx)) { iidx++; new_len--; if (iidx == num_to_delete) break; } if (new_len > 0) { T *new_data = new T [new_len]; int ii = 0; iidx = 0; for (int i = 0; i < len; i++) { if (iidx < num_to_delete && i == idx_arg.elem (iidx)) iidx++; else { new_data[ii] = elem (i); ii++; } } if (--rep->count <= 0) delete rep; rep = new typename Array<T>::ArrayRep (new_data, new_len); dimensions.resize (1); dimensions(0) = new_len; } else (*current_liboctave_error_handler) ("A(idx) = []: index out of range"); } } } template <class T> void Array<T>::maybe_delete_elements_2 (idx_vector& idx_arg) { assert (ndims () == 2); int nr = dim1 (); int nc = dim2 (); if (nr == 0 && nc == 0) return; int n; if (nr == 1) n = nc; else if (nc == 1) n = nr; else { (*current_liboctave_error_handler) ("A(idx) = []: expecting A to be row or column vector or scalar"); return; } if (idx_arg.is_colon_equiv (n, 1)) { // Either A(:) = [] or A(idx) = [] with idx enumerating all // elements, so we delete all elements and return [](0x0). To // preserve the orientation of the vector, you have to use // A(idx,:) = [] (delete rows) or A(:,idx) (delete columns). resize_no_fill (0, 0); return; } idx_arg.sort (true); int num_to_delete = idx_arg.length (n); if (num_to_delete != 0) { int new_n = n; int iidx = 0; for (int i = 0; i < n; i++) if (i == idx_arg.elem (iidx)) { iidx++; new_n--; if (iidx == num_to_delete) break; } if (new_n > 0) { T *new_data = new T [new_n]; int ii = 0; iidx = 0; for (int i = 0; i < n; i++) { if (iidx < num_to_delete && i == idx_arg.elem (iidx)) iidx++; else { if (nr == 1) new_data[ii] = elem (0, i); else new_data[ii] = elem (i, 0); ii++; } } if (--(Array<T>::rep)->count <= 0) delete Array<T>::rep; Array<T>::rep = new typename Array<T>::ArrayRep (new_data, new_n); dimensions.resize (2); if (nr == 1) { dimensions(0) = 1; dimensions(1) = new_n; } else { dimensions(0) = new_n; dimensions(1) = 1; } } else (*current_liboctave_error_handler) ("A(idx) = []: index out of range"); } } template <class T> void Array<T>::maybe_delete_elements (idx_vector& idx_i, idx_vector& idx_j) { assert (ndims () == 2); int nr = dim1 (); int nc = dim2 (); if (nr == 0 && nc == 0) return; if (idx_i.is_colon ()) { if (idx_j.is_colon ()) { // A(:,:) -- We are deleting columns and rows, so the result // is [](0x0). resize_no_fill (0, 0); return; } if (idx_j.is_colon_equiv (nc, 1)) { // A(:,j) -- We are deleting columns by enumerating them, // If we enumerate all of them, we should have zero columns // with the same number of rows that we started with. resize_no_fill (nr, 0); return; } } if (idx_j.is_colon () && idx_i.is_colon_equiv (nr, 1)) { // A(i,:) -- We are deleting rows by enumerating them. If we // enumerate all of them, we should have zero rows with the // same number of columns that we started with. resize_no_fill (0, nc); return; } if (idx_i.is_colon_equiv (nr, 1)) { if (idx_j.is_colon_equiv (nc, 1)) resize_no_fill (0, 0); else { idx_j.sort (true); int num_to_delete = idx_j.length (nc); if (num_to_delete != 0) { if (nr == 1 && num_to_delete == nc) resize_no_fill (0, 0); else { int new_nc = nc; int iidx = 0; for (int j = 0; j < nc; j++) if (j == idx_j.elem (iidx)) { iidx++; new_nc--; if (iidx == num_to_delete) break; } if (new_nc > 0) { T *new_data = new T [nr * new_nc]; int jj = 0; iidx = 0; for (int j = 0; j < nc; j++) { if (iidx < num_to_delete && j == idx_j.elem (iidx)) iidx++; else { for (int i = 0; i < nr; i++) new_data[nr*jj+i] = elem (i, j); jj++; } } if (--(Array<T>::rep)->count <= 0) delete Array<T>::rep; Array<T>::rep = new typename Array<T>::ArrayRep (new_data, nr * new_nc); dimensions.resize (2); dimensions(1) = new_nc; } else (*current_liboctave_error_handler) ("A(idx) = []: index out of range"); } } } } else if (idx_j.is_colon_equiv (nc, 1)) { if (idx_i.is_colon_equiv (nr, 1)) resize_no_fill (0, 0); else { idx_i.sort (true); int num_to_delete = idx_i.length (nr); if (num_to_delete != 0) { if (nc == 1 && num_to_delete == nr) resize_no_fill (0, 0); else { int new_nr = nr; int iidx = 0; for (int i = 0; i < nr; i++) if (i == idx_i.elem (iidx)) { iidx++; new_nr--; if (iidx == num_to_delete) break; } if (new_nr > 0) { T *new_data = new T [new_nr * nc]; int ii = 0; iidx = 0; for (int i = 0; i < nr; i++) { if (iidx < num_to_delete && i == idx_i.elem (iidx)) iidx++; else { for (int j = 0; j < nc; j++) new_data[new_nr*j+ii] = elem (i, j); ii++; } } if (--(Array<T>::rep)->count <= 0) delete Array<T>::rep; Array<T>::rep = new typename Array<T>::ArrayRep (new_data, new_nr * nc); dimensions.resize (2); dimensions(0) = new_nr; } else (*current_liboctave_error_handler) ("A(idx) = []: index out of range"); } } } } } template <class T> void Array<T>::maybe_delete_elements (idx_vector&, idx_vector&, idx_vector&) { assert (0); } template <class T> void Array<T>::maybe_delete_elements (Array<idx_vector>& ra_idx, const T& rfv) { int n_idx = ra_idx.length (); dim_vector lhs_dims = dims (); dim_vector idx_is_colon; idx_is_colon.resize (n_idx); dim_vector idx_is_colon_equiv; idx_is_colon_equiv.resize (n_idx); // Initialization of colon arrays. for (int i = 0; i < n_idx; i++) { idx_is_colon_equiv(i) = ra_idx(i).is_colon_equiv (lhs_dims(i), 1); idx_is_colon(i) = ra_idx(i).is_colon (); } if (all_ones (idx_is_colon) || all_ones (idx_is_colon_equiv)) { // A(:,:,:) -- we are deleting elements in all dimensions, so // the result is [](0x0x0). dim_vector zeros; zeros.resize (n_idx); for (int i = 0; i < n_idx; i++) zeros(i) = 0; resize (zeros, rfv); } else if (num_ones (idx_is_colon) == n_idx - 1 && num_ones (idx_is_colon_equiv) == n_idx) { // A(:,:,j) -- we are deleting elements in one dimension by // enumerating them. // // If we enumerate all of the elements, we should have zero // elements in that dimension with the same number of elements // in the other dimensions that we started with. dim_vector temp_dims; temp_dims.resize (n_idx); for (int i = 0; i < n_idx; i++) { if (idx_is_colon (i)) temp_dims (i) = lhs_dims (i); else temp_dims (i) = 0; } resize (temp_dims); } else if (num_ones (idx_is_colon) == n_idx - 1) { // We have colons in all indices except for one. // This index tells us which slice to delete int non_col = 0; // Find the non-colon column. for (int i = 0; i < n_idx; i++) { if (! idx_is_colon (i)) non_col = i; } // The length of the non-colon dimension. int non_col_dim = lhs_dims (non_col); ra_idx(non_col).sort (true); int num_to_delete = ra_idx(non_col).length (lhs_dims (non_col)); if (num_to_delete > 0) { int temp = lhs_dims.num_ones (); if (non_col_dim == 1) temp--; if (temp == n_idx - 1 && num_to_delete == non_col_dim) { // We have A with (1x1x4), where A(1,:,1:4) // Delete all (0x0x0) dim_vector zero_dims (n_idx, 0); resize (zero_dims, rfv); } else { // New length of non-colon dimension // (calculated in the next for loop) int new_dim = non_col_dim; int iidx = 0; for (int j = 0; j < non_col_dim; j++) if (j == ra_idx(non_col).elem (iidx)) { iidx++; new_dim--; if (iidx == num_to_delete) break; } // Creating the new nd array after deletions. if (new_dim > 0) { // Calculate number of elements in new array. int num_new_elem=1; for (int i = 0; i < n_idx; i++) { if (i == non_col) num_new_elem *= new_dim; else num_new_elem *= lhs_dims(i); } T *new_data = new T [num_new_elem]; Array<int> result_idx (lhs_dims.length (), 0); dim_vector lhs_inc; lhs_inc.resize (lhs_dims.length ()); for (int i = 0; i < lhs_dims.length (); i++) lhs_inc(i) = lhs_dims(i) + 1; dim_vector new_lhs_dim = lhs_dims; new_lhs_dim(non_col) = new_dim; int num_elem = 1; int numidx = 0; int n = length (); for (int i =0; i < lhs_dims.length (); i++) if (i != non_col) num_elem *= lhs_dims (i); num_elem *= ra_idx(non_col).capacity (); for (int i = 0; i < n; i++) { if (numidx < num_elem && is_in (result_idx(non_col), ra_idx(non_col))) numidx++; else { Array<int> temp_result_idx = result_idx; int num_lgt = how_many_lgt (result_idx(non_col), ra_idx(non_col)); temp_result_idx(non_col) -= num_lgt; int kidx = ::compute_index (temp_result_idx, new_lhs_dim); new_data[kidx] = elem (result_idx); } increment_index (result_idx, lhs_dims); } if (--rep->count <= 0) delete rep; rep = new typename Array<T>::ArrayRep (new_data, num_new_elem); dimensions = new_lhs_dim; } } } } else if (num_ones (idx_is_colon) < n_idx) { (*current_liboctave_error_handler) ("A null assignment can have only one non-colon index"); } } template <class T> Array<T> Array<T>::value (void) { Array<T> retval; int n_idx = index_count (); if (n_idx == 2) { idx_vector *tmp = get_idx (); idx_vector idx_i = tmp[0]; idx_vector idx_j = tmp[1]; retval = index (idx_i, idx_j); } else if (n_idx == 1) { retval = index (idx[0]); } else (*current_liboctave_error_handler) ("Array<T>::value: invalid number of indices specified"); clear_index (); return retval; } template <class T> Array<T> Array<T>::index (idx_vector& idx_arg, int resize_ok, const T& rfv) const { Array<T> retval; switch (ndims ()) { case 1: retval = index1 (idx_arg, resize_ok, rfv); break; case 2: retval = index2 (idx_arg, resize_ok, rfv); break; default: retval = indexN (idx_arg, resize_ok, rfv); break; } return retval; } template <class T> Array<T> Array<T>::index1 (idx_vector& idx_arg, int resize_ok, const T& rfv) const { Array<T> retval; int len = length (); int n = idx_arg.freeze (len, "vector", resize_ok); if (idx_arg) { if (idx_arg.is_colon_equiv (len)) { retval = *this; } else if (n == 0) { retval.resize_no_fill (0); } else if (len == 1 && n > 1 && idx_arg.one_zero_only () && idx_arg.ones_count () == n) { retval.resize_and_fill (n, elem (0)); } else { retval.resize_no_fill (n); for (int i = 0; i < n; i++) { int ii = idx_arg.elem (i); if (ii >= len) retval.elem (i) = rfv; else retval.elem (i) = elem (ii); } } } // idx_vector::freeze() printed an error message for us. return retval; } template <class T> Array<T> Array<T>::index2 (idx_vector& idx_arg, int resize_ok, const T& rfv) const { Array<T> retval; assert (ndims () == 2); int nr = dim1 (); int nc = dim2 (); int orig_len = nr * nc; int idx_orig_rows = idx_arg.orig_rows (); int idx_orig_columns = idx_arg.orig_columns (); if (idx_arg.is_colon ()) { // Fast magic colon processing. int result_nr = nr * nc; int result_nc = 1; retval = Array<T> (*this, dim_vector (result_nr, result_nc)); } else if (nr == 1 && nc == 1) { Array<T> tmp = Array<T>::index1 (idx_arg, resize_ok); if (tmp.length () != 0) retval = Array<T> (tmp, dim_vector (idx_orig_rows, idx_orig_columns)); else retval = Array<T> (tmp, dim_vector (0, 0)); } else if (nr == 1 || nc == 1) { // If indexing a vector with a matrix, return value has same // shape as the index. Otherwise, it has same orientation as // indexed object. Array<T> tmp = index1 (idx_arg, resize_ok); int len = tmp.length (); if (len == 0) { if (idx_orig_rows == 0 || idx_orig_columns == 0) retval = Array<T> (dim_vector (idx_orig_rows, idx_orig_columns)); else if (nr == 1) retval = Array<T> (dim_vector (1, 0)); else retval = Array<T> (dim_vector (0, 1)); } else { if (idx_arg.one_zero_only () || idx_orig_rows == 1 || idx_orig_columns == 1) { if (nr == 1) retval = Array<T> (tmp, dim_vector (1, len)); else retval = Array<T> (tmp, dim_vector (len, 1)); } else retval = Array<T> (tmp, dim_vector (idx_orig_rows, idx_orig_columns)); } } else { if (liboctave_wfi_flag && ! (idx_arg.one_zero_only () && idx_orig_rows == nr && idx_orig_columns == nc)) (*current_liboctave_warning_handler) ("single index used for matrix"); // This code is only for indexing matrices. The vector // cases are handled above. idx_arg.freeze (nr * nc, "matrix", resize_ok); if (idx_arg) { int result_nr = idx_orig_rows; int result_nc = idx_orig_columns; if (idx_arg.one_zero_only ()) { result_nr = idx_arg.ones_count (); result_nc = (result_nr > 0 ? 1 : 0); } retval.resize_no_fill (result_nr, result_nc); int k = 0; for (int j = 0; j < result_nc; j++) { for (int i = 0; i < result_nr; i++) { int ii = idx_arg.elem (k++); if (ii >= orig_len) retval.elem (i, j) = rfv; else { int fr = ii % nr; int fc = (ii - fr) / nr; retval.elem (i, j) = elem (fr, fc); } } } } // idx_vector::freeze() printed an error message for us. } return retval; } template <class T> Array<T> Array<T>::indexN (idx_vector& ra_idx, int resize_ok, const T& rfv) const { Array<T> retval; int n_dims = dims ().length (); int orig_len = number_of_elements (dims ()); Array<int> idx_orig_dimsXXX = ra_idx.orig_dimensions (); dim_vector idx_orig_dims; idx_orig_dims.resize (idx_orig_dimsXXX.length ()); for (int i = 0; i < idx_orig_dimsXXX.length (); i++) idx_orig_dims(i) = idx_orig_dimsXXX(i); if (ra_idx.is_colon ()) { dim_vector iidx (orig_len); retval = Array<T> (*this, iidx); } else if (length () == 1) { // Only one element in array. Array<T> tmp = Array<T>::index (ra_idx, resize_ok); if (tmp.length () != 0) retval = Array<T> (tmp, idx_orig_dims); else retval = Array<T> (tmp, dim_vector (0)); } else if (vector_equivalent (dims ())) { // We're getting elements from a vector equivalent i.e. (1x4x1). Array<T> tmp = Array<T>::index (ra_idx, resize_ok); int len = tmp.length (); if (len == 0) { if (any_zero_len (idx_orig_dims)) retval = Array<T> (idx_orig_dims); else { dim_vector new_dims; new_dims.resize (n_dims); for (int i = 0; i < n_dims; i++) { if ((dims ())(i) == 1) new_dims(i) = 1; } retval = Array<T> (new_dims); } } else { if (vector_equivalent(idx_orig_dims)) { // Array<int> index (n_dims, len); dim_vector new_dims; new_dims.resize (n_dims); for (int i = 0; i < n_dims; i++) { if ((dims ())(i) == 1) new_dims(i) = 1; } retval = Array<T> (tmp, new_dims); } else retval = Array<T> (tmp, idx_orig_dims); (*current_liboctave_error_handler) ("I do not know what to do here yet!"); } } else if (liboctave_wfi_flag || (ra_idx.one_zero_only () && equal_arrays (idx_orig_dims, dims ()))) { // This code is only for indexing nd-arrays. The vector // cases are handled above. ra_idx.freeze (orig_len, "nd-array", resize_ok); if (ra_idx) { dim_vector result_dims (idx_orig_dims); if (ra_idx.one_zero_only ()) { for (int i = 0; i < result_dims.length(); i++) { if (i == 0) result_dims(i) = ra_idx.ones_count (); else if (result_dims(0) > 0) result_dims(i) = 1; else result_dims(i) = 0; } } retval.resize (result_dims); int n = number_of_elements (result_dims); int r_dims = result_dims.length (); Array<int> iidx (r_dims, 0); int k = 0; for (int i = 0; i < n; i++) { int ii = ra_idx.elem (k++); if (ii >= orig_len) retval.elem (iidx) = rfv; else { Array<int> temp = get_ra_idx (ii, dims ()); retval.elem (iidx) = elem (temp); } if (i != n - 1) increment_index (iidx, result_dims); } } } else if (ra_idx.capacity () == 1) { // i.e. A(8) for A(3x3x3) ra_idx.freeze (orig_len, "nd-array", resize_ok); if (ra_idx) { int r_idx = ra_idx(0); Array<int> iidx = get_ra_idx (r_idx, dims ()); dim_vector new_dims (1); // This shouldn't be needed. Array<int> e (iidx.length ()); for (int i = 0; i < iidx.length();i++) e(i) = iidx(i); // Should be able to call elem (iidx). retval = Array<T> (new_dims, elem (e)); } } else (*current_liboctave_error_handler) ("single index only valid for row or column vector. ra_idx.cap () = &d", ra_idx.capacity ()); return retval; } template <class T> Array<T> Array<T>::index (idx_vector& idx_i, idx_vector& idx_j, int resize_ok, const T& rfv) const { Array<T> retval; assert (ndims () == 2); int nr = dim1 (); int nc = dim2 (); int n = idx_i.freeze (nr, "row", resize_ok); int m = idx_j.freeze (nc, "column", resize_ok); if (idx_i && idx_j) { if (idx_i.orig_empty () || idx_j.orig_empty () || n == 0 || m == 0) { retval.resize_no_fill (n, m); } else if (idx_i.is_colon_equiv (nr) && idx_j.is_colon_equiv (nc)) { retval = *this; } else { retval.resize_no_fill (n, m); for (int j = 0; j < m; j++) { int jj = idx_j.elem (j); for (int i = 0; i < n; i++) { int ii = idx_i.elem (i); if (ii >= nr || jj >= nc) retval.elem (i, j) = rfv; else retval.elem (i, j) = elem (ii, jj); } } } } // idx_vector::freeze() printed an error message for us. return retval; } template <class T> Array<T> Array<T>::index (Array<idx_vector>& ra_idx, int resize_ok, const T& rfv) const { // This function handles all calls with more than one idx. // For (3x3x3), the call can be A(2,5), A(2,:,:), A(3,2,3) etc. Array<T> retval; int n_dims = dimensions.length (); if (n_dims < ra_idx.length ()) { (*current_liboctave_error_handler) ("index exceeds N-d array dimensions"); return retval; } dim_vector frozen_lengths = short_freeze (ra_idx, dimensions, resize_ok); if (frozen_lengths.length () <= n_dims) { if (all_ok (ra_idx)) { if (any_orig_empty (ra_idx)) { retval.resize (frozen_lengths); } else if (any_zero_len (frozen_lengths)) { retval.resize (get_zero_len_size (frozen_lengths, dimensions)); } else if (all_colon_equiv (ra_idx, dimensions) && frozen_lengths.length () == n_dims) { retval = *this; } else { retval.resize (frozen_lengths); int n = number_of_elements (frozen_lengths); Array<int> result_idx (ra_idx.length (), 0); dim_vector this_dims = dims (); Array<int> elt_idx; for (int i = 0; i < n; i++) { elt_idx = get_elt_idx (ra_idx, result_idx); int numelem_result = get_scalar_idx (result_idx, frozen_lengths); int numelem_elt = get_scalar_idx (elt_idx, this_dims); if (numelem_result > length () || numelem_result < 0 || numelem_elt > length () || numelem_elt < 0) (*current_liboctave_error_handler) ("attempt to grow array along ambiguous dimension"); else retval.checkelem (numelem_result) = checkelem (numelem_elt); increment_index (result_idx, frozen_lengths); } } } } else (*current_liboctave_error_handler) ("invalid number of dimensions for N-dimensional array index"); return retval; } // XXX FIXME XXX -- this is a mess. template <class LT, class RT> int assign (Array<LT>& lhs, const Array<RT>& rhs, const LT& rfv) { int retval = 0; switch (lhs.ndims ()) { case 0: { if (lhs.index_count () < 3) { // kluge... lhs.resize_no_fill (0, 0); retval = assign2 (lhs, rhs, rfv); } else retval = assignN (lhs, rhs, rfv); } break; case 1: { if (lhs.index_count () > 1) retval = assignN (lhs, rhs, rfv); else retval = assign1 (lhs, rhs, rfv); } break; case 2: { if (lhs.index_count () > 2) retval = assignN (lhs, rhs, rfv); else retval = assign2 (lhs, rhs, rfv); } break; default: retval = assignN (lhs, rhs, rfv); break; } return retval; } template <class LT, class RT> int assign1 (Array<LT>& lhs, const Array<RT>& rhs, const LT& rfv) { int retval = 1; idx_vector *tmp = lhs.get_idx (); idx_vector lhs_idx = tmp[0]; int lhs_len = lhs.length (); int rhs_len = rhs.length (); int n = lhs_idx.freeze (lhs_len, "vector", true, liboctave_wrore_flag); if (n != 0) { if (rhs_len == n || rhs_len == 1) { int max_idx = lhs_idx.max () + 1; if (max_idx > lhs_len) lhs.resize_and_fill (max_idx, rfv); } if (rhs_len == n) { for (int i = 0; i < n; i++) { int ii = lhs_idx.elem (i); lhs.elem (ii) = rhs.elem (i); } } else if (rhs_len == 1) { RT scalar = rhs.elem (0); for (int i = 0; i < n; i++) { int ii = lhs_idx.elem (i); lhs.elem (ii) = scalar; } } else { (*current_liboctave_error_handler) ("A(I) = X: X must be a scalar or a vector with same length as I"); retval = 0; } } else if (lhs_idx.is_colon ()) { if (lhs_len == 0) { lhs.resize_no_fill (rhs_len); for (int i = 0; i < rhs_len; i++) lhs.elem (i) = rhs.elem (i); } else (*current_liboctave_error_handler) ("A(:) = X: A must be the same size as X"); } else if (! (rhs_len == 1 || rhs_len == 0)) { (*current_liboctave_error_handler) ("A([]) = X: X must also be an empty matrix or a scalar"); retval = 0; } lhs.clear_index (); return retval; } #define MAYBE_RESIZE_LHS \ do \ { \ int max_row_idx = idx_i_is_colon ? rhs_nr : idx_i.max () + 1; \ int max_col_idx = idx_j_is_colon ? rhs_nc : idx_j.max () + 1; \ \ int new_nr = max_row_idx > lhs_nr ? max_row_idx : lhs_nr; \ int new_nc = max_col_idx > lhs_nc ? max_col_idx : lhs_nc; \ \ lhs.resize_and_fill (new_nr, new_nc, rfv); \ } \ while (0) template <class LT, class RT> int assign2 (Array<LT>& lhs, const Array<RT>& rhs, const LT& rfv) { int retval = 1; int n_idx = lhs.index_count (); int lhs_nr = lhs.rows (); int lhs_nc = lhs.cols (); int rhs_nr = rhs.rows (); int rhs_nc = rhs.cols (); idx_vector *tmp = lhs.get_idx (); idx_vector idx_i; idx_vector idx_j; if (n_idx > 1) idx_j = tmp[1]; if (n_idx > 0) idx_i = tmp[0]; if (n_idx == 2) { int n = idx_i.freeze (lhs_nr, "row", true, liboctave_wrore_flag); int m = idx_j.freeze (lhs_nc, "column", true, liboctave_wrore_flag); int idx_i_is_colon = idx_i.is_colon (); int idx_j_is_colon = idx_j.is_colon (); if (idx_i_is_colon) n = lhs_nr > 0 ? lhs_nr : rhs_nr; if (idx_j_is_colon) m = lhs_nc > 0 ? lhs_nc : rhs_nc; if (idx_i && idx_j) { if (rhs_nr == 0 && rhs_nc == 0) { lhs.maybe_delete_elements (idx_i, idx_j); } else { if (rhs_nr == 1 && rhs_nc == 1 && n >= 0 && m >= 0) { // No need to do anything if either of the indices // are empty. if (n > 0 && m > 0) { MAYBE_RESIZE_LHS; RT scalar = rhs.elem (0, 0); for (int j = 0; j < m; j++) { int jj = idx_j.elem (j); for (int i = 0; i < n; i++) { int ii = idx_i.elem (i); lhs.elem (ii, jj) = scalar; } } } } else if (n == rhs_nr && m == rhs_nc) { if (n > 0 && m > 0) { MAYBE_RESIZE_LHS; for (int j = 0; j < m; j++) { int jj = idx_j.elem (j); for (int i = 0; i < n; i++) { int ii = idx_i.elem (i); lhs.elem (ii, jj) = rhs.elem (i, j); } } } } else if (n == 0 && m == 0) { if (! ((rhs_nr == 1 && rhs_nc == 1) || (rhs_nr == 0 && rhs_nc == 0))) { (*current_liboctave_error_handler) ("A([], []) = X: X must be an empty matrix or a scalar"); retval = 0; } } else { (*current_liboctave_error_handler) ("A(I, J) = X: X must be a scalar or the number of elements in I must"); (*current_liboctave_error_handler) ("match the number of rows in X and the number of elements in J must"); (*current_liboctave_error_handler) ("match the number of columns in X"); retval = 0; } } } // idx_vector::freeze() printed an error message for us. } else if (n_idx == 1) { int lhs_is_empty = lhs_nr == 0 || lhs_nc == 0; if (lhs_is_empty || (lhs_nr == 1 && lhs_nc == 1)) { int lhs_len = lhs.length (); int n = idx_i.freeze (lhs_len, 0, true, liboctave_wrore_flag); if (idx_i) { if (rhs_nr == 0 && rhs_nc == 0) { if (n != 0 && (lhs_nr != 0 || lhs_nc != 0)) lhs.maybe_delete_elements (idx_i); } else { if (liboctave_wfi_flag) { if (lhs_is_empty && idx_i.is_colon () && ! (rhs_nr == 1 || rhs_nc == 1)) { (*current_liboctave_warning_handler) ("A(:) = X: X is not a vector or scalar"); } else { int idx_nr = idx_i.orig_rows (); int idx_nc = idx_i.orig_columns (); if (! (rhs_nr == idx_nr && rhs_nc == idx_nc)) (*current_liboctave_warning_handler) ("A(I) = X: X does not have same shape as I"); } } if (assign1 ((Array<LT>&) lhs, (Array<RT>&) rhs, rfv)) { int len = lhs.length (); if (len > 0) { // The following behavior is much simplified // over previous versions of Octave. It // seems to be compatible with Matlab. lhs.dimensions = dim_vector (1, lhs.length ()); } else lhs.dimensions = dim_vector (0, 0); } else retval = 0; } } // idx_vector::freeze() printed an error message for us. } else if (lhs_nr == 1) { idx_i.freeze (lhs_nc, "vector", true, liboctave_wrore_flag); if (idx_i) { if (rhs_nr == 0 && rhs_nc == 0) lhs.maybe_delete_elements (idx_i); else { if (assign1 ((Array<LT>&) lhs, (Array<RT>&) rhs, rfv)) lhs.dimensions = dim_vector (1, lhs.length ()); else retval = 0; } } // idx_vector::freeze() printed an error message for us. } else if (lhs_nc == 1) { idx_i.freeze (lhs_nr, "vector", true, liboctave_wrore_flag); if (idx_i) { if (rhs_nr == 0 && rhs_nc == 0) lhs.maybe_delete_elements (idx_i); else { if (assign1 ((Array<LT>&) lhs, (Array<RT>&) rhs, rfv)) lhs.dimensions = dim_vector (lhs.length (), 1); else retval = 0; } } // idx_vector::freeze() printed an error message for us. } else { if (liboctave_wfi_flag && ! (idx_i.is_colon () || (idx_i.one_zero_only () && idx_i.orig_rows () == lhs_nr && idx_i.orig_columns () == lhs_nc))) (*current_liboctave_warning_handler) ("single index used for matrix"); int len = idx_i.freeze (lhs_nr * lhs_nc, "matrix"); if (idx_i) { if (len == 0) { if (! ((rhs_nr == 1 && rhs_nc == 1) || (rhs_nr == 0 && rhs_nc == 0))) (*current_liboctave_error_handler) ("A([]) = X: X must be an empty matrix or scalar"); } else if (len == rhs_nr * rhs_nc) { int k = 0; for (int j = 0; j < rhs_nc; j++) { for (int i = 0; i < rhs_nr; i++) { int ii = idx_i.elem (k++); int fr = ii % lhs_nr; int fc = (ii - fr) / lhs_nr; lhs.elem (fr, fc) = rhs.elem (i, j); } } } else if (rhs_nr == 1 && rhs_nc == 1 && len <= lhs_nr * lhs_nc) { RT scalar = rhs.elem (0, 0); for (int i = 0; i < len; i++) { int ii = idx_i.elem (i); int fr = ii % lhs_nr; int fc = (ii - fr) / lhs_nr; lhs.elem (fr, fc) = scalar; } } else { (*current_liboctave_error_handler) ("A(I) = X: X must be a scalar or a matrix with the same size as I"); retval = 0; } } // idx_vector::freeze() printed an error message for us. } } else { (*current_liboctave_error_handler) ("invalid number of indices for matrix expression"); retval = 0; } lhs.clear_index (); return retval; } #define MAYBE_RESIZE_ND_DIMS \ do \ { \ if (n_idx >= lhs_dims.length () && ! rhs_is_empty) \ { \ Array<int> max_idx (n_idx); \ dim_vector new_dims; \ new_dims.resize (n_idx); \ \ for (int i = 0; i < n_idx; i++) \ { \ if (lhs_dims.length () == 0 || i >= lhs_dims.length ()) \ new_dims(i) = idx(i).max () + 1; \ else \ { \ if (i < rhs_dims.length ()) \ max_idx(i) = idx(i).is_colon () ? rhs_dims(i) : idx(i).max () + 1; \ else \ max_idx(i) = idx(i).max () + 1; \ \ new_dims(i) = max_idx(i) > lhs_dims(i) ? max_idx(i) : lhs_dims(i); \ } \ } \ \ lhs.resize_and_fill (new_dims, rfv); \ lhs_dims = lhs.dims (); \ } \ } \ while (0) template <class LT, class RT> int assignN (Array<LT>& lhs, const Array<RT>& rhs, const LT& rfv) { int retval = 1; int n_idx = lhs.index_count (); dim_vector lhs_dims = lhs.dims (); dim_vector rhs_dims = rhs.dims (); idx_vector *tmp = lhs.get_idx (); Array<idx_vector> idx = conv_to_array (tmp, n_idx); // This needs to be defined before MAYBE_RESIZE_ND_DIMS. bool rhs_is_empty = rhs_dims.length () == 0 ? true : any_zero_len (rhs_dims); // Maybe expand to more dimensions. MAYBE_RESIZE_ND_DIMS; Array<int> idx_is_colon (n_idx, 0); Array<int> idx_is_colon_equiv (n_idx, 0); for (int i = 0; i < n_idx; i++) { idx_is_colon_equiv(i) = idx(i).is_colon_equiv (lhs_dims(i), 1); idx_is_colon(i) = idx(i).is_colon (); } int resize_ok = 1; dim_vector frozen_len; if (n_idx == lhs_dims.length ()) frozen_len = freeze (idx, lhs_dims, resize_ok); bool rhs_is_scalar = is_scalar (rhs_dims); bool idx_is_empty = any_zero_len (frozen_len); if (rhs_is_empty) { lhs.maybe_delete_elements (idx, rfv); } else if (rhs_is_scalar) { if (n_idx == 0) (*current_liboctave_error_handler) ("number of indices is zero"); else if (n_idx == 1) { Array<int> one_arg_temp (1, 0); RT scalar = rhs.elem (one_arg_temp); lhs.fill (scalar); } else if (n_idx < lhs_dims.length ()) { // Number of indices is less than dimensions. if (any_ones (idx_is_colon)|| any_ones (idx_is_colon_equiv)) { (*current_liboctave_error_handler) ("number of indices is less than number of dimensions, one or more indices are colons"); } else { // Fewer indices than dimensions, no colons. bool resize = false; // Subtract one since the last idx do not tell us // anything about dimensionality. for (int i = 0; i < idx.length () - 1; i++) { // Subtract one since idx counts from 0 while dims // count from 1. if (idx(i).elem (0) + 1 > lhs_dims(i)) resize = true; } if (resize) { dim_vector new_dims; new_dims.resize (lhs_dims.length ()); for (int i = 0; i < lhs_dims.length (); i++) { if (i < idx.length () - 1 && idx(i).elem (0) + 1 > lhs_dims(i)) new_dims(i) = idx(i).elem (0)+1; else new_dims(i) = lhs_dims(i); } lhs.resize (new_dims, rfv); lhs_dims = lhs.dims (); } Array<int> one_arg_temp (1, 0); RT scalar = rhs.elem (one_arg_temp); Array<int> int_arr = conv_to_int_array (idx); int numelem = get_scalar_idx (int_arr, lhs_dims); if (numelem > lhs.length () || numelem < 0) (*current_liboctave_error_handler) ("attempt to grow array along ambiguous dimension"); else lhs.checkelem (numelem) = scalar; } } else { // Scalar to matrix assignment with as many indices as lhs // dimensions. int n = Array<LT>::get_size (frozen_len); Array<int> result_idx (lhs_dims.length (), 0); Array<int> elt_idx; RT scalar = rhs.elem (0); for (int i = 0; i < n; i++) { elt_idx = get_elt_idx (idx, result_idx); dim_vector lhs_inc; lhs_inc.resize (lhs_dims.length ()); for (int j = 0; j < lhs_dims.length (); j++) lhs_inc(j) = lhs_dims(j) + 1; if (index_in_bounds(elt_idx, lhs_inc)) lhs.checkelem (elt_idx) = scalar; else lhs.checkelem (elt_idx) = rfv; increment_index (result_idx, frozen_len); } } } else if (rhs_dims.length () > 1) { // RHS is matrix or higher dimension. bool dim_ok = true; int jj = 0; // Check that RHS dimensions are the same length as the // corresponding LHS dimensions. int rhs_dims_len = rhs_dims.length (); for (int j = 0; j < idx_is_colon.length (); j++) { if (idx_is_colon(j)) { if (jj > rhs_dims_len || rhs_dims(jj) < lhs_dims(j)) { dim_ok = false; break; } jj++; } } if (! dim_ok) (*current_liboctave_error_handler) ("subscripted assignment dimension mismatch"); else { dim_vector new_dims; new_dims.resize (n_idx); bool resize = false; int ii = 0; // Update idx vectors. for (int i = 0; i < n_idx; i++) { if (idx(i).is_colon ()) { // Add appropriate idx_vector to idx(i) since // index with : contains no indexes. frozen_len(i) = lhs_dims(i) > rhs_dims(ii) ? lhs_dims(i) : rhs_dims(ii); new_dims(i) = lhs_dims(i) > rhs_dims(ii) ? lhs_dims(i) : rhs_dims(ii); ii++; Range idxrange (1, frozen_len(i), 1); idx_vector idxv (idxrange); idx(i) = idxv; } else { new_dims(i) = lhs_dims(i) > idx(i).max () + 1 ? lhs_dims(i) : idx(i).max () + 1; if (frozen_len(i) > 1) ii++; } if (new_dims(i) != lhs_dims(i)) resize = true; } // Resize LHS if dimensions have changed. if (resize) { lhs.resize (new_dims, rfv); lhs_dims = lhs.dims (); } // Number of elements which need to be set. int n = Array<LT>::get_size (frozen_len); Array<int> result_idx (lhs_dims.length (), 0); Array<int> elt_idx; Array<int> result_rhs_idx (rhs_dims.length (), 0); dim_vector frozen_rhs; frozen_rhs.resize (rhs_dims.length ()); for (int i = 0; i < rhs_dims.length (); i++) frozen_rhs(i) = rhs_dims(i); dim_vector lhs_inc; lhs_inc.resize (lhs_dims.length ()); for (int i = 0; i < lhs_dims.length (); i++) lhs_inc(i) = lhs_dims(i) + 1; for (int i = 0; i < n; i++) { elt_idx = get_elt_idx (idx, result_idx); if (index_in_bounds (elt_idx, lhs_inc)) { int s = compute_index (result_rhs_idx,rhs_dims); lhs.checkelem (elt_idx) = rhs.elem (s); increment_index (result_rhs_idx, frozen_rhs); } else lhs.checkelem (elt_idx) = rfv; increment_index (result_idx, frozen_len); } } } else if (idx_is_empty) { // Assignment to matrix with at least one empty index. if (! rhs_is_empty || ! rhs_is_scalar) { (*current_liboctave_error_handler) ("A([], []) = X: X must be an empty matrix or a scalar"); retval = 0; } } else if (lhs_dims.length () != rhs_dims.length ()) { (*current_liboctave_error_handler) ("A(I) = X: X must be a scalar or a matrix with the same size as I"); retval = 0; } lhs.clear_index (); return retval; } template <class T> void Array<T>::print_info (std::ostream& os, const std::string& prefix) const { os << prefix << "rep address: " << rep << "\n" << prefix << "rep->len: " << rep->len << "\n" << prefix << "rep->data: " << static_cast<void *> (rep->data) << "\n" << prefix << "rep->count: " << rep->count << "\n"; // 2D info: // // << prefix << "rows: " << rows () << "\n" // << prefix << "cols: " << cols () << "\n"; } /* ;;; Local Variables: *** ;;; mode: C++ *** ;;; End: *** */