Mercurial > hg > octave-lyh
view doc/interpreter/expr.txi @ 17504:326af26556ea
surfl.m: Overhaul function.
* scripts/plot/surfl.m: Improve docstring. Don't use mixed case variable
names. Use in-place operators for performance.
author | Rik <rik@octave.org> |
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date | Wed, 25 Sep 2013 13:31:43 -0700 |
parents | bc924baa2c4e |
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@c Copyright (C) 1996-2012 John W. Eaton @c @c This file is part of Octave. @c @c Octave is free software; you can redistribute it and/or modify it @c under the terms of the GNU General Public License as published by the @c Free Software Foundation; either version 3 of the License, or (at @c your option) any later version. @c @c Octave is distributed in the hope that it will be useful, but WITHOUT @c ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or @c FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License @c for more details. @c @c You should have received a copy of the GNU General Public License @c along with Octave; see the file COPYING. If not, see @c <http://www.gnu.org/licenses/>. @node Expressions @chapter Expressions @cindex expressions Expressions are the basic building block of statements in Octave. An expression evaluates to a value, which you can print, test, store in a variable, pass to a function, or assign a new value to a variable with an assignment operator. An expression can serve as a statement on its own. Most other kinds of statements contain one or more expressions which specify data to be operated on. As in other languages, expressions in Octave include variables, array references, constants, and function calls, as well as combinations of these with various operators. @menu * Index Expressions:: * Calling Functions:: * Arithmetic Ops:: * Comparison Ops:: * Boolean Expressions:: * Assignment Ops:: * Increment Ops:: * Operator Precedence:: @end menu @node Index Expressions @section Index Expressions @opindex ( @opindex ) @opindex : An @dfn{index expression} allows you to reference or extract selected elements of a matrix or vector. Indices may be scalars, vectors, ranges, or the special operator @samp{:}, which may be used to select entire rows or columns. Vectors are indexed using a single index expression. Matrices (2-D) and higher multi-dimensional arrays are indexed using either one index or @math{N} indices where @math{N} is the dimension of the array. When using a single index expression to index 2-D or higher data the elements of the array are taken in column-first order (like Fortran). The output from indexing assumes the dimensions of the index expression. For example: @example @group a(2) # result is a scalar a(1:2) # result is a row vector a([1; 2]) # result is a column vector @end group @end example As a special case, when a colon is used as a single index, the output is a column vector containing all the elements of the vector or matrix. For example: @example @group a(:) # result is a column vector a(:)' # result is a row vector @end group @end example The above two code idioms are often used in place of @code{reshape} when a simple vector, rather than an arbitrarily sized array, is needed. Given the matrix @example a = [1, 2; 3, 4] @end example @noindent all of the following expressions are equivalent and select the first row of the matrix. @example @group a(1, [1, 2]) # row 1, columns 1 and 2 a(1, 1:2) # row 1, columns in range 1-2 a(1, :) # row 1, all columns @end group @end example @cindex @code{end}, indexing @cindex :end In index expressions the keyword @code{end} automatically refers to the last entry for a particular dimension. This magic index can also be used in ranges and typically eliminates the needs to call @code{size} or @code{length} to gather array bounds before indexing. For example: @example @group a = [1, 2, 3, 4]; a(1:end/2) # first half of a => [1, 2] a(end + 1) = 5; # append element a(end) = []; # delete element a(1:2:end) # odd elements of a => [1, 3] a(2:2:end) # even elements of a => [2, 4] a(end:-1:1) # reversal of a => [4, 3, 2 , 1] @end group @end example @menu * Advanced Indexing:: @end menu @node Advanced Indexing @subsection Advanced Indexing An array with @samp{n} dimensions can be indexed using @samp{m} indices. More generally, the set of index tuples determining the result is formed by the Cartesian product of the index vectors (or ranges or scalars). For the ordinary and most common case, @w{@code{m == n}}, and each index corresponds to its respective dimension. If @w{@code{m < n}} and every index is less than the size of the array in the @math{i^{th}} dimension, @code{m(i) < n(i)}, then the index expression is padded with trailing singleton dimensions (@code{[ones (m-n, 1)]}). If @w{@code{m < n}} but one of the indices @code{m(i)} is outside the size of the current array, then the last @w{@code{n-m+1}} dimensions are folded into a single dimension with an extent equal to the product of extents of the original dimensions. This is easiest to understand with an example. @example a = reshape (1:8, 2, 2, 2) # Create 3-D array a = ans(:,:,1) = 1 3 2 4 ans(:,:,2) = 5 7 6 8 a(2,1,2); # Case (m == n): ans = 6 a(2,1); # Case (m < n), idx within array: # equivalent to a(2,1,1), ans = 2 a(2,4); # Case (m < n), idx outside array: # Dimension 2 & 3 folded into new dimension of size 2x2 = 4 # Select 2nd row, 4th element of [2, 4, 6, 8], ans = 8 @end example One advanced use of indexing is to create arrays filled with a single value. This can be done by using an index of ones on a scalar value. The result is an object with the dimensions of the index expression and every element equal to the original scalar. For example, the following statements @example @group a = 13; a(ones (1, 4)) @end group @end example @noindent produce a vector whose four elements are all equal to 13. Similarly, by indexing a scalar with two vectors of ones it is possible to create a matrix. The following statements @example @group a = 13; a(ones (1, 2), ones (1, 3)) @end group @end example @noindent create a 2x3 matrix with all elements equal to 13. The last example could also be written as @example @group 13(ones (2, 3)) @end group @end example It is more efficient to use indexing rather than the code construction @code{scalar * ones (N, M, @dots{})} because it avoids the unnecessary multiplication operation. Moreover, multiplication may not be defined for the object to be replicated whereas indexing an array is always defined. The following code shows how to create a 2x3 cell array from a base unit which is not itself a scalar. @example @group @{"Hello"@}(ones (2, 3)) @end group @end example It should be, noted that @code{ones (1, n)} (a row vector of ones) results in a range (with zero increment). A range is stored internally as a starting value, increment, end value, and total number of values; hence, it is more efficient for storage than a vector or matrix of ones whenever the number of elements is greater than 4. In particular, when @samp{r} is a row vector, the expressions @example r(ones (1, n), :) @end example @example r(ones (n, 1), :) @end example @noindent will produce identical results, but the first one will be significantly faster, at least for @samp{r} and @samp{n} large enough. In the first case the index is held in compressed form as a range which allows Octave to choose a more efficient algorithm to handle the expression. A general recommendation, for a user unaware of these subtleties, is to use the function @code{repmat} for replicating smaller arrays into bigger ones. A second use of indexing is to speed up code. Indexing is a fast operation and judicious use of it can reduce the requirement for looping over individual array elements which is a slow operation. Consider the following example which creates a 10-element row vector @math{a} containing the values @tex $a_i = \sqrt{i}$. @end tex @ifnottex a(i) = sqrt (i). @end ifnottex @example @group for i = 1:10 a(i) = sqrt (i); endfor @end group @end example @noindent It is quite inefficient to create a vector using a loop like this. In this case, it would have been much more efficient to use the expression @example a = sqrt (1:10); @end example @noindent which avoids the loop entirely. In cases where a loop cannot be avoided, or a number of values must be combined to form a larger matrix, it is generally faster to set the size of the matrix first (pre-allocate storage), and then insert elements using indexing commands. For example, given a matrix @code{a}, @example @group [nr, nc] = size (a); x = zeros (nr, n * nc); for i = 1:n x(:,(i-1)*nc+1:i*nc) = a; endfor @end group @end example @noindent is considerably faster than @example @group x = a; for i = 1:n-1 x = [x, a]; endfor @end group @end example @noindent because Octave does not have to repeatedly resize the intermediate result. @DOCSTRING(sub2ind) @DOCSTRING(ind2sub) @DOCSTRING(isindex) @DOCSTRING(allow_noninteger_range_as_index) @node Calling Functions @section Calling Functions A @dfn{function} is a name for a particular calculation. Because it has a name, you can ask for it by name at any point in the program. For example, the function @code{sqrt} computes the square root of a number. A fixed set of functions are @dfn{built-in}, which means they are available in every Octave program. The @code{sqrt} function is one of these. In addition, you can define your own functions. @xref{Functions and Scripts}, for information about how to do this. @cindex arguments in function call The way to use a function is with a @dfn{function call} expression, which consists of the function name followed by a list of @dfn{arguments} in parentheses. The arguments are expressions which give the raw materials for the calculation that the function will do. When there is more than one argument, they are separated by commas. If there are no arguments, you can omit the parentheses, but it is a good idea to include them anyway, to clearly indicate that a function call was intended. Here are some examples: @example @group sqrt (x^2 + y^2) # @r{One argument} ones (n, m) # @r{Two arguments} rand () # @r{No arguments} @end group @end example Each function expects a particular number of arguments. For example, the @code{sqrt} function must be called with a single argument, the number to take the square root of: @example sqrt (@var{argument}) @end example Some of the built-in functions take a variable number of arguments, depending on the particular usage, and their behavior is different depending on the number of arguments supplied. Like every other expression, the function call has a value, which is computed by the function based on the arguments you give it. In this example, the value of @code{sqrt (@var{argument})} is the square root of the argument. A function can also have side effects, such as assigning the values of certain variables or doing input or output operations. Unlike most languages, functions in Octave may return multiple values. For example, the following statement @example [u, s, v] = svd (a) @end example @noindent computes the singular value decomposition of the matrix @code{a} and assigns the three result matrices to @code{u}, @code{s}, and @code{v}. The left side of a multiple assignment expression is itself a list of expressions, and is allowed to be a list of variable names or index expressions. See also @ref{Index Expressions}, and @ref{Assignment Ops}. @menu * Call by Value:: * Recursion:: @end menu @node Call by Value @subsection Call by Value In Octave, unlike Fortran, function arguments are passed by value, which means that each argument in a function call is evaluated and assigned to a temporary location in memory before being passed to the function. There is currently no way to specify that a function parameter should be passed by reference instead of by value. This means that it is impossible to directly alter the value of a function parameter in the calling function. It can only change the local copy within the function body. For example, the function @example @group function f (x, n) while (n-- > 0) disp (x); endwhile endfunction @end group @end example @noindent displays the value of the first argument @var{n} times. In this function, the variable @var{n} is used as a temporary variable without having to worry that its value might also change in the calling function. Call by value is also useful because it is always possible to pass constants for any function parameter without first having to determine that the function will not attempt to modify the parameter. The caller may use a variable as the expression for the argument, but the called function does not know this: it only knows what value the argument had. For example, given a function called as @example @group foo = "bar"; fcn (foo) @end group @end example @noindent you should not think of the argument as being ``the variable @code{foo}.'' Instead, think of the argument as the string value, @qcode{"bar"}. Even though Octave uses pass-by-value semantics for function arguments, values are not copied unnecessarily. For example, @example @group x = rand (1000); f (x); @end group @end example @noindent does not actually force two 1000 by 1000 element matrices to exist @emph{unless} the function @code{f} modifies the value of its argument. Then Octave must create a copy to avoid changing the value outside the scope of the function @code{f}, or attempting (and probably failing!) to modify the value of a constant or the value of a temporary result. @node Recursion @subsection Recursion @cindex factorial function With some restrictions@footnote{Some of Octave's functions are implemented in terms of functions that cannot be called recursively. For example, the ODE solver @code{lsode} is ultimately implemented in a Fortran subroutine that cannot be called recursively, so @code{lsode} should not be called either directly or indirectly from within the user-supplied function that @code{lsode} requires. Doing so will result in an error.}, recursive function calls are allowed. A @dfn{recursive function} is one which calls itself, either directly or indirectly. For example, here is an inefficient@footnote{It would be much better to use @code{prod (1:n)}, or @code{gamma (n+1)} instead, after first checking to ensure that the value @code{n} is actually a positive integer.} way to compute the factorial of a given integer: @example @group function retval = fact (n) if (n > 0) retval = n * fact (n-1); else retval = 1; endif endfunction @end group @end example This function is recursive because it calls itself directly. It eventually terminates because each time it calls itself, it uses an argument that is one less than was used for the previous call. Once the argument is no longer greater than zero, it does not call itself, and the recursion ends. The built-in variable @code{max_recursion_depth} specifies a limit to the recursion depth and prevents Octave from recursing infinitely. @DOCSTRING(max_recursion_depth) @node Arithmetic Ops @section Arithmetic Operators @cindex arithmetic operators @cindex operators, arithmetic @cindex addition @cindex subtraction @cindex multiplication @cindex matrix multiplication @cindex division @cindex quotient @cindex negation @cindex unary minus @cindex exponentiation @cindex transpose @cindex Hermitian operator @cindex transpose, complex-conjugate @cindex complex-conjugate transpose The following arithmetic operators are available, and work on scalars and matrices. The element-by-element operators and functions broadcast (@pxref{Broadcasting}). @table @asis @item @var{x} + @var{y} @opindex + Addition. If both operands are matrices, the number of rows and columns must both agree, or they must be broadcastable to the same shape. @item @var{x} .+ @var{y} @opindex .+ Element-by-element addition. This operator is equivalent to @code{+}. @item @var{x} - @var{y} @opindex - Subtraction. If both operands are matrices, the number of rows and columns of both must agree, or they must be broadcastable to the same shape. @item @var{x} .- @var{y} Element-by-element subtraction. This operator is equivalent to @code{-}. @item @var{x} * @var{y} @opindex * Matrix multiplication. The number of columns of @var{x} must agree with the number of rows of @var{y}, or they must be broadcastable to the same shape. @item @var{x} .* @var{y} @opindex .* Element-by-element multiplication. If both operands are matrices, the number of rows and columns must both agree, or they must be broadcastable to the same shape. @item @var{x} / @var{y} @opindex / Right division. This is conceptually equivalent to the expression @example (inverse (y') * x')' @end example @noindent but it is computed without forming the inverse of @var{y'}. If the system is not square, or if the coefficient matrix is singular, a minimum norm solution is computed. @item @var{x} ./ @var{y} @opindex ./ Element-by-element right division. @item @var{x} \ @var{y} @opindex \ Left division. This is conceptually equivalent to the expression @example inverse (x) * y @end example @noindent but it is computed without forming the inverse of @var{x}. If the system is not square, or if the coefficient matrix is singular, a minimum norm solution is computed. @item @var{x} .\ @var{y} @opindex .\ Element-by-element left division. Each element of @var{y} is divided by each corresponding element of @var{x}. @item @var{x} ^ @var{y} @itemx @var{x} ** @var{y} @opindex ** @opindex ^ Power operator. If @var{x} and @var{y} are both scalars, this operator returns @var{x} raised to the power @var{y}. If @var{x} is a scalar and @var{y} is a square matrix, the result is computed using an eigenvalue expansion. If @var{x} is a square matrix, the result is computed by repeated multiplication if @var{y} is an integer, and by an eigenvalue expansion if @var{y} is not an integer. An error results if both @var{x} and @var{y} are matrices. The implementation of this operator needs to be improved. @item @var{x} .^ @var{y} @itemx @var{x} .** @var{y} @opindex .** @opindex .^ Element-by-element power operator. If both operands are matrices, the number of rows and columns must both agree, or they must be broadcastable to the same shape. If several complex results are possible, the one with smallest non-negative argument (angle) is taken. This rule may return a complex root even when a real root is also possible. Use @code{realpow}, @code{realsqrt}, @code{cbrt}, or @code{nthroot} if a real result is preferred. @item -@var{x} @opindex - Negation. @item +@var{x} @opindex + Unary plus. This operator has no effect on the operand. @item @var{x}' @opindex ' Complex conjugate transpose. For real arguments, this operator is the same as the transpose operator. For complex arguments, this operator is equivalent to the expression @example conj (x.') @end example @item @var{x}.' @opindex .' Transpose. @end table Note that because Octave's element-by-element operators begin with a @samp{.}, there is a possible ambiguity for statements like @example 1./m @end example @noindent because the period could be interpreted either as part of the constant or as part of the operator. To resolve this conflict, Octave treats the expression as if you had typed @example (1) ./ m @end example @noindent and not @example (1.) / m @end example @noindent Although this is inconsistent with the normal behavior of Octave's lexer, which usually prefers to break the input into tokens by preferring the longest possible match at any given point, it is more useful in this case. @opindex ' @DOCSTRING(ctranspose) @opindex .\ @DOCSTRING(ldivide) @opindex - @DOCSTRING(minus) @opindex \ @DOCSTRING(mldivide) @opindex ** @opindex ^ @DOCSTRING(mpower) @opindex / @DOCSTRING(mrdivide) @opindex * @DOCSTRING(mtimes) @opindex + @DOCSTRING(plus) @opindex .** @opindex .^ @DOCSTRING(power) @opindex ./ @DOCSTRING(rdivide) @opindex .* @DOCSTRING(times) @opindex .' @DOCSTRING(transpose) @opindex - @DOCSTRING(uminus) @opindex + @DOCSTRING(uplus) @node Comparison Ops @section Comparison Operators @cindex comparison expressions @cindex expressions, comparison @cindex relational operators @cindex operators, relational @cindex less than operator @cindex greater than operator @cindex equality operator @cindex tests for equality @cindex equality, tests for @dfn{Comparison operators} compare numeric values for relationships such as equality. They are written using @emph{relational operators}. All of Octave's comparison operators return a value of 1 if the comparison is true, or 0 if it is false. For matrix values, they all work on an element-by-element basis. Broadcasting rules apply. @xref{Broadcasting}. For example: @example @group [1, 2; 3, 4] == [1, 3; 2, 4] @result{} 1 0 0 1 @end group @end example According to broadcasting rules, if one operand is a scalar and the other is a matrix, the scalar is compared to each element of the matrix in turn, and the result is the same size as the matrix. @table @code @item @var{x} < @var{y} @opindex < True if @var{x} is less than @var{y}. @item @var{x} <= @var{y} @opindex <= True if @var{x} is less than or equal to @var{y}. @item @var{x} == @var{y} @opindex == True if @var{x} is equal to @var{y}. @item @var{x} >= @var{y} @opindex >= True if @var{x} is greater than or equal to @var{y}. @item @var{x} > @var{y} @opindex > True if @var{x} is greater than @var{y}. @item @var{x} != @var{y} @itemx @var{x} ~= @var{y} @opindex != @opindex ~= True if @var{x} is not equal to @var{y}. @end table For complex numbers, the following ordering is defined: @var{z1} < @var{z2} if and only if @example @group abs (@var{z1}) < abs (@var{z2}) || (abs (@var{z1}) == abs (@var{z2}) && arg (@var{z1}) < arg (@var{z2})) @end group @end example This is consistent with the ordering used by @dfn{max}, @dfn{min} and @dfn{sort}, but is not consistent with @sc{matlab}, which only compares the real parts. String comparisons may also be performed with the @code{strcmp} function, not with the comparison operators listed above. @xref{Strings}. @opindex == @DOCSTRING(eq) @opindex >= @DOCSTRING(ge) @opindex > @DOCSTRING(gt) @DOCSTRING(isequal) @DOCSTRING(isequaln) @opindex <= @DOCSTRING(le) @opindex < @DOCSTRING(lt) @opindex != @opindex ~= @DOCSTRING(ne) @node Boolean Expressions @section Boolean Expressions @cindex expressions, boolean @cindex boolean expressions @cindex expressions, logical @cindex logical expressions @cindex operators, boolean @cindex boolean operators @cindex logical operators @cindex operators, logical @cindex and operator @cindex or operator @cindex not operator @menu * Element-by-element Boolean Operators:: * Short-circuit Boolean Operators:: @end menu @node Element-by-element Boolean Operators @subsection Element-by-element Boolean Operators @cindex element-by-element evaluation An @dfn{element-by-element boolean expression} is a combination of comparison expressions using the boolean operators ``or'' (@samp{|}), ``and'' (@samp{&}), and ``not'' (@samp{!}), along with parentheses to control nesting. The truth of the boolean expression is computed by combining the truth values of the corresponding elements of the component expressions. A value is considered to be false if it is zero, and true otherwise. Element-by-element boolean expressions can be used wherever comparison expressions can be used. They can be used in @code{if} and @code{while} statements. However, a matrix value used as the condition in an @code{if} or @code{while} statement is only true if @emph{all} of its elements are nonzero. Like comparison operations, each element of an element-by-element boolean expression also has a numeric value (1 if true, 0 if false) that comes into play if the result of the boolean expression is stored in a variable, or used in arithmetic. Here are descriptions of the three element-by-element boolean operators. @table @code @item @var{boolean1} & @var{boolean2} @opindex & Elements of the result are true if both corresponding elements of @var{boolean1} and @var{boolean2} are true. @item @var{boolean1} | @var{boolean2} @opindex | Elements of the result are true if either of the corresponding elements of @var{boolean1} or @var{boolean2} is true. @item ! @var{boolean} @itemx ~ @var{boolean} @opindex ~ @opindex ! Each element of the result is true if the corresponding element of @var{boolean} is false. @end table These operators work on an element-by-element basis. For example, the expression @example [1, 0; 0, 1] & [1, 0; 2, 3] @end example @noindent returns a two by two identity matrix. For the binary operators, broadcasting rules apply. @xref{Broadcasting}. In particular, if one of the operands is a scalar and the other a matrix, the operator is applied to the scalar and each element of the matrix. For the binary element-by-element boolean operators, both subexpressions @var{boolean1} and @var{boolean2} are evaluated before computing the result. This can make a difference when the expressions have side effects. For example, in the expression @example a & b++ @end example @noindent the value of the variable @var{b} is incremented even if the variable @var{a} is zero. This behavior is necessary for the boolean operators to work as described for matrix-valued operands. @opindex & @DOCSTRING(and) @opindex ~ @opindex ! @DOCSTRING(not) @opindex | @DOCSTRING(or) @node Short-circuit Boolean Operators @subsection Short-circuit Boolean Operators @cindex short-circuit evaluation Combined with the implicit conversion to scalar values in @code{if} and @code{while} conditions, Octave's element-by-element boolean operators are often sufficient for performing most logical operations. However, it is sometimes desirable to stop evaluating a boolean expression as soon as the overall truth value can be determined. Octave's @dfn{short-circuit} boolean operators work this way. @table @code @item @var{boolean1} && @var{boolean2} @opindex && The expression @var{boolean1} is evaluated and converted to a scalar using the equivalent of the operation @code{all (@var{boolean1}(:))}. If it is false, the result of the overall expression is 0. If it is true, the expression @var{boolean2} is evaluated and converted to a scalar using the equivalent of the operation @code{all (@var{boolean1}(:))}. If it is true, the result of the overall expression is 1. Otherwise, the result of the overall expression is 0. @strong{Warning:} there is one exception to the rule of evaluating @code{all (@var{boolean1}(:))}, which is when @code{boolean1} is the empty matrix. The truth value of an empty matrix is always @code{false} so @code{[] && true} evaluates to @code{false} even though @code{all ([])} is @code{true}. @item @var{boolean1} || @var{boolean2} @opindex || The expression @var{boolean1} is evaluated and converted to a scalar using the equivalent of the operation @code{all (@var{boolean1}(:))}. If it is true, the result of the overall expression is 1. If it is false, the expression @var{boolean2} is evaluated and converted to a scalar using the equivalent of the operation @code{all (@var{boolean1}(:))}. If it is true, the result of the overall expression is 1. Otherwise, the result of the overall expression is 0. @strong{Warning:} the truth value of an empty matrix is always @code{false}, see the previous list item for details. @end table The fact that both operands may not be evaluated before determining the overall truth value of the expression can be important. For example, in the expression @example a && b++ @end example @noindent the value of the variable @var{b} is only incremented if the variable @var{a} is nonzero. This can be used to write somewhat more concise code. For example, it is possible write @example @group function f (a, b, c) if (nargin > 2 && ischar (c)) @dots{} @end group @end example @noindent instead of having to use two @code{if} statements to avoid attempting to evaluate an argument that doesn't exist. For example, without the short-circuit feature, it would be necessary to write @example @group function f (a, b, c) if (nargin > 2) if (ischar (c)) @dots{} @end group @end example @noindent Writing @example @group function f (a, b, c) if (nargin > 2 & ischar (c)) @dots{} @end group @end example @noindent would result in an error if @code{f} were called with one or two arguments because Octave would be forced to try to evaluate both of the operands for the operator @samp{&}. @sc{matlab} has special behavior that allows the operators @samp{&} and @samp{|} to short-circuit when used in the truth expression for @code{if} and @code{while} statements. The Octave parser may be instructed to behave in the same manner, but its use is strongly discouraged. @DOCSTRING(do_braindead_shortcircuit_evaluation) Finally, the ternary operator (?:) is not supported in Octave. If short-circuiting is not important, it can be replaced by the @code{ifelse} function. @DOCSTRING(merge) @node Assignment Ops @section Assignment Expressions @cindex assignment expressions @cindex assignment operators @cindex operators, assignment @cindex expressions, assignment @opindex = An @dfn{assignment} is an expression that stores a new value into a variable. For example, the following expression assigns the value 1 to the variable @code{z}: @example z = 1 @end example @noindent After this expression is executed, the variable @code{z} has the value 1. Whatever old value @code{z} had before the assignment is forgotten. The @samp{=} sign is called an @dfn{assignment operator}. Assignments can store string values also. For example, the following expression would store the value @qcode{"this food is good"} in the variable @code{message}: @example @group thing = "food" predicate = "good" message = [ "this " , thing , " is " , predicate ] @end group @end example @noindent (This also illustrates concatenation of strings.) @cindex side effect Most operators (addition, concatenation, and so on) have no effect except to compute a value. If you ignore the value, you might as well not use the operator. An assignment operator is different. It does produce a value, but even if you ignore the value, the assignment still makes itself felt through the alteration of the variable. We call this a @dfn{side effect}. @cindex lvalue The left-hand operand of an assignment need not be a variable (@pxref{Variables}). It can also be an element of a matrix (@pxref{Index Expressions}) or a list of return values (@pxref{Calling Functions}). These are all called @dfn{lvalues}, which means they can appear on the left-hand side of an assignment operator. The right-hand operand may be any expression. It produces the new value which the assignment stores in the specified variable, matrix element, or list of return values. It is important to note that variables do @emph{not} have permanent types. The type of a variable is simply the type of whatever value it happens to hold at the moment. In the following program fragment, the variable @code{foo} has a numeric value at first, and a string value later on: @example @group octave:13> foo = 1 foo = 1 octave:13> foo = "bar" foo = bar @end group @end example @noindent When the second assignment gives @code{foo} a string value, the fact that it previously had a numeric value is forgotten. Assignment of a scalar to an indexed matrix sets all of the elements that are referenced by the indices to the scalar value. For example, if @code{a} is a matrix with at least two columns, @example @group a(:, 2) = 5 @end group @end example @noindent sets all the elements in the second column of @code{a} to 5. Assigning an empty matrix @samp{[]} works in most cases to allow you to delete rows or columns of matrices and vectors. @xref{Empty Matrices}. For example, given a 4 by 5 matrix @var{A}, the assignment @example A (3, :) = [] @end example @noindent deletes the third row of @var{A}, and the assignment @example A (:, 1:2:5) = [] @end example @noindent deletes the first, third, and fifth columns. An assignment is an expression, so it has a value. Thus, @code{z = 1} as an expression has the value 1. One consequence of this is that you can write multiple assignments together: @example x = y = z = 0 @end example @noindent stores the value 0 in all three variables. It does this because the value of @code{z = 0}, which is 0, is stored into @code{y}, and then the value of @code{y = z = 0}, which is 0, is stored into @code{x}. This is also true of assignments to lists of values, so the following is a valid expression @example [a, b, c] = [u, s, v] = svd (a) @end example @noindent that is exactly equivalent to @example @group [u, s, v] = svd (a) a = u b = s c = v @end group @end example In expressions like this, the number of values in each part of the expression need not match. For example, the expression @example [a, b] = [u, s, v] = svd (a) @end example @noindent is equivalent to @example @group [u, s, v] = svd (a) a = u b = s @end group @end example @noindent The number of values on the left side of the expression can, however, not exceed the number of values on the right side. For example, the following will produce an error. @example @group [a, b, c, d] = [u, s, v] = svd (a); @print{} error: element number 4 undefined in return list @end group @end example The symbol @code{~} may be used as a placeholder in the list of lvalues, indicating that the corresponding return value should be ignored and not stored anywhere: @example @group [~, s, v] = svd (a); @end group @end example This is cleaner and more memory efficient than using a dummy variable. The @code{nargout} value for the right-hand side expression is not affected. If the assignment is used as an expression, the return value is a comma-separated list with the ignored values dropped. @opindex += A very common programming pattern is to increment an existing variable with a given value, like this @example a = a + 2; @end example @noindent This can be written in a clearer and more condensed form using the @code{+=} operator @example a += 2; @end example @noindent @opindex -= @opindex *= @opindex /= Similar operators also exist for subtraction (@code{-=}), multiplication (@code{*=}), and division (@code{/=}). An expression of the form @example @var{expr1} @var{op}= @var{expr2} @end example @noindent is evaluated as @example @var{expr1} = (@var{expr1}) @var{op} (@var{expr2}) @end example @noindent where @var{op} can be either @code{+}, @code{-}, @code{*}, or @code{/}. So, the expression @example a *= b+1 @end example @noindent is evaluated as @example a = a * (b+1) @end example @noindent and @emph{not} @example a = a * b + 1 @end example You can use an assignment anywhere an expression is called for. For example, it is valid to write @code{x != (y = 1)} to set @code{y} to 1 and then test whether @code{x} equals 1. But this style tends to make programs hard to read. Except in a one-shot program, you should rewrite it to get rid of such nesting of assignments. This is never very hard. @cindex increment operator @cindex decrement operator @cindex operators, increment @cindex operators, decrement @node Increment Ops @section Increment Operators @emph{Increment operators} increase or decrease the value of a variable by 1. The operator to increment a variable is written as @samp{++}. It may be used to increment a variable either before or after taking its value. For example, to pre-increment the variable @var{x}, you would write @code{++@var{x}}. This would add one to @var{x} and then return the new value of @var{x} as the result of the expression. It is exactly the same as the expression @code{@var{x} = @var{x} + 1}. To post-increment a variable @var{x}, you would write @code{@var{x}++}. This adds one to the variable @var{x}, but returns the value that @var{x} had prior to incrementing it. For example, if @var{x} is equal to 2, the result of the expression @code{@var{x}++} is 2, and the new value of @var{x} is 3. For matrix and vector arguments, the increment and decrement operators work on each element of the operand. Here is a list of all the increment and decrement expressions. @table @code @item ++@var{x} @opindex ++ This expression increments the variable @var{x}. The value of the expression is the @emph{new} value of @var{x}. It is equivalent to the expression @code{@var{x} = @var{x} + 1}. @item --@var{x} @opindex @code{--} This expression decrements the variable @var{x}. The value of the expression is the @emph{new} value of @var{x}. It is equivalent to the expression @code{@var{x} = @var{x} - 1}. @item @var{x}++ @opindex ++ This expression causes the variable @var{x} to be incremented. The value of the expression is the @emph{old} value of @var{x}. @item @var{x}-- @opindex @code{--} This expression causes the variable @var{x} to be decremented. The value of the expression is the @emph{old} value of @var{x}. @end table @node Operator Precedence @section Operator Precedence @cindex operator precedence @dfn{Operator precedence} determines how operators are grouped, when different operators appear close by in one expression. For example, @samp{*} has higher precedence than @samp{+}. Thus, the expression @code{a + b * c} means to multiply @code{b} and @code{c}, and then add @code{a} to the product (i.e., @code{a + (b * c)}). You can overrule the precedence of the operators by using parentheses. You can think of the precedence rules as saying where the parentheses are assumed if you do not write parentheses yourself. In fact, it is wise to use parentheses whenever you have an unusual combination of operators, because other people who read the program may not remember what the precedence is in this case. You might forget as well, and then you too could make a mistake. Explicit parentheses will help prevent any such mistake. When operators of equal precedence are used together, the leftmost operator groups first, except for the assignment operators, which group in the opposite order. Thus, the expression @code{a - b + c} groups as @code{(a - b) + c}, but the expression @code{a = b = c} groups as @code{a = (b = c)}. The precedence of prefix unary operators is important when another operator follows the operand. For example, @code{-x^2} means @code{-(x^2)}, because @samp{-} has lower precedence than @samp{^}. Here is a table of the operators in Octave, in order of decreasing precedence. Unless noted, all operators group left to right. @table @code @item function call and array indexing, cell array indexing, and structure element indexing @samp{()} @samp{@{@}} @samp{.} @item postfix increment, and postfix decrement @samp{++} @samp{--} These operators group right to left. @item transpose and exponentiation @samp{'} @samp{.'} @samp{^} @samp{**} @samp{.^} @samp{.**} @item unary plus, unary minus, prefix increment, prefix decrement, and logical "not" @samp{+} @samp{-} @samp{++} @samp{--} @samp{~} @samp{!} @item multiply and divide @samp{*} @samp{/} @samp{\} @samp{.\} @samp{.*} @samp{./} @item add, subtract @samp{+} @samp{-} @item colon @samp{:} @item relational @samp{<} @samp{<=} @samp{==} @samp{>=} @samp{>} @samp{!=} @samp{~=} @item element-wise "and" @samp{&} @item element-wise "or" @samp{|} @item logical "and" @samp{&&} @item logical "or" @samp{||} @item assignment @samp{=} @samp{+=} @samp{-=} @samp{*=} @samp{/=} @samp{\=} @samp{^=} @samp{.*=} @samp{./=} @samp{.\=} @samp{.^=} @samp{|=} @samp{&=} These operators group right to left. @end table