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doc: Grammarcheck documentation ahead of 3.6.0 release. * basics.txi, container.txi, contrib.txi, debug.txi, expr.txi, func.txi, install.txi, io.txi, package.txi, polyarea.m, ezcontour.m, ezcontourf.m, ezmesh.m, ezmeshc.m, ezplot.m, ezplot3.m, ezpolar.m, ezsurf.m, ezsurfc.m, assert.m, amd.cc, chol.cc, colamd.cc, rand.cc: Grammarcheck documentation.
author Rik <octave@nomad.inbox5.com>
date Mon, 12 Dec 2011 21:01:27 -0800
parents dfbf6a49847c
children 951eacaf9381
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14037:4228c102eca9 14038:b0cdd60db5e5
60 or @math{N} indices where @math{N} is the dimension of the array. 60 or @math{N} indices where @math{N} is the dimension of the array.
61 When using a single index expression to index 2-D or higher data the 61 When using a single index expression to index 2-D or higher data the
62 elements of the array are taken in column-first order (like Fortran). 62 elements of the array are taken in column-first order (like Fortran).
63 63
64 The output from indexing assumes the dimensions of the index 64 The output from indexing assumes the dimensions of the index
65 expression. For example, 65 expression. For example:
66 66
67 @example 67 @example
68 @group 68 @group
69 a(2) # result is a scalar 69 a(2) # result is a scalar
70 a(1:2) # result is a row vector 70 a(1:2) # result is a row vector
75 As a special case, when a colon is used as a single index, the output 75 As a special case, when a colon is used as a single index, the output
76 is a column vector containing all the elements of the vector or 76 is a column vector containing all the elements of the vector or
77 matrix. For example: 77 matrix. For example:
78 78
79 @example 79 @example
80 @group
80 a(:) # result is a column vector 81 a(:) # result is a column vector
81 a(:)' # result is a row vector 82 a(:)' # result is a row vector
83 @end group
82 @end example 84 @end example
83 85
84 The above two code idioms are often used in place of @code{reshape} 86 The above two code idioms are often used in place of @code{reshape}
85 when a simple vector, rather than an arbitrarily sized array, is 87 when a simple vector, rather than an arbitrarily sized array, is
86 needed. 88 needed.
147 are folded into a single dimension with an extent equal to the product 149 are folded into a single dimension with an extent equal to the product
148 of extents of the original dimensions. This is easiest to understand 150 of extents of the original dimensions. This is easiest to understand
149 with an example. 151 with an example.
150 152
151 @example 153 @example
152 @group
153 a = reshape (1:8, 2, 2, 2) # Create 3-D array 154 a = reshape (1:8, 2, 2, 2) # Create 3-D array
154 a = 155 a =
155 156
156 ans(:,:,1) = 157 ans(:,:,1) =
157 158
167 a(2,1); # Case (m < n), idx within array: 168 a(2,1); # Case (m < n), idx within array:
168 # equivalent to a(2,1,1), ans = 2 169 # equivalent to a(2,1,1), ans = 2
169 a(2,4); # Case (m < n), idx outside array: 170 a(2,4); # Case (m < n), idx outside array:
170 # Dimension 2 & 3 folded into new dimension of size 2x2 = 4 171 # Dimension 2 & 3 folded into new dimension of size 2x2 = 4
171 # Select 2nd row, 4th element of [2, 4, 6, 8], ans = 8 172 # Select 2nd row, 4th element of [2, 4, 6, 8], ans = 8
172 @end group
173 @end example 173 @end example
174 174
175 One advanced use of indexing is to create arrays filled with a single 175 One advanced use of indexing is to create arrays filled with a single
176 value. This can be done by using an index of ones on a scalar value. 176 value. This can be done by using an index of ones on a scalar value.
177 The result is an object with the dimensions of the index expression 177 The result is an object with the dimensions of the index expression