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438 lines
17 KiB
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438 lines
17 KiB
Plaintext
NAME
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mat - keyword to create a matrix value
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SYNOPSIS
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mat [index-range-list] [ = {value_0. ...} ]
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mat [] [= {value_0, ...}]
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mat variable_1 ... [index-range-list] [ = {value_0, ...} ]
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mat variable_1 ... [] [ = {value_0, ...} ]
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mat [index-range-list_1[index-ranges-list_2] ... [ = { { ...} ...} ]
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decl id_1 id_2 ... [index-range-list] ...
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TYPES
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index-range-list range_1 [, range_2, ...] up to 4 ranges
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range_1, ... integer, or integer_1 : integer_2
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value, value_1, ... any
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variable_1 ... lvalue
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decl declarator = global, static or local
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id_1, ... identifier
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DESCRIPTION
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The expression mat [index-range-list] returns a matrix value.
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This may be assigned to one or more lvalues A, B, ... by either
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mat A B ... [index-range-list]
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or
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A = B = ... = mat[index-range-list]
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If a variable is specified by an expression that is not a symbol with
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possibly object element specifiers, the expression should be enclosed
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in parentheses. For example, parentheses are required in
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mat (A[2]) [3] and mat (*p) [3] but mat P.x [3] is acceptable.
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When an index-range is specified as integer_1 : integer_2, where
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integer_1 and integer_2 are expressions which evaluate to integers,
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the index-range consists of all integers from the minimum of the
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two integers to the maximum of the two integers. For example,
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mat[2:5, 0:4] and mat[5:2, 4:0] return the same matrix value.
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If an index-range is an expression which evaluates to an integer,
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the range is as if specified by 0 : integer - 1. For example,
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mat[4] and mat[0:3] return the same 4-element matrix; mat[-2] and
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mat[-3:0] return the same 4-element matrix.
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If the variable A has a matrix value, then for integer indices
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i_1, i_2, ..., equal in number to the number of ranges specified at
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its creation, and such that each index is in the corresponding range,
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the matrix element associated with those index list is given as an
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lvalue by the expressions A[i_1, i_2, ...].
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The elements of the matrix are stored internally as a linear array
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in which locations are arranged in order of increasing indices.
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For example, in order of location, the six element of A = mat [2,3]
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are:
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A[0,0], A[0,1], A[0,2], A[1,0], A[1,1], and A[1,2].
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These elements may also be specified using the double-bracket operator
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with a single integer index as in A[[0]], A[[1]], ..., A[[5]].
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If p is assigned the value &A[0,0], the address of A[[i]] for 0 <= i < 6
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is p + i as long as A exists and a new value is not assigned to A.
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When a matrix is created, each element is initially assigned the
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value zero. Other values may be assigned then or later using the
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"= {...}" assignment operation. Thus
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A = {value_0, value_1, ...}
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assigns the values value_0, value_1, ... to the elements A[[0]],
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A[[1]], ... Any blank "value" is passed over. For example,
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A = {1, , 2}
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will assign the value 1 to A[[0]], 2 to A[[2]] and leave all other
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elements unchanged. Values may also be assigned to elements by
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simple assignments, as in A[0,0] = 1, A[0,2] = 2;
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If the index-range is left blank but an initializer list is specified
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as in:
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; mat A[] = {1, 2 }
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; B = mat[] = {1, , 3, }
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the matrix created is one-dimensional. If the list contains a
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positive number n of values or blanks, the result is as if the
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range were specified by [n], i.e. the range of indices is from
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0 to n - 1. In the above examples, A is of size 2 with A[0] = 1
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and A[1] = 2; B is of size 4 with B[0] = 1, B[1] = B[3] = 0,
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B[2] = 3. The specification mat[] = { } creates the same as mat[1].
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If the index-range is left blank and no initializer list is specified,
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as in mat C[] or C = mat[], the matrix assigned to C has zero
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dimension; this has one element C[].
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To assign a value using "= { ...}" at the same time as creating C,
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parentheses are required as in (mat[]) = {value} or (mat C[]) =
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{value}. Later a value may be assigned to C[] by C[] = value or
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C = {value}.
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The value assigned at any time to any element of a matrix can be of
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any type - number, string, list, matrix, object of previously specified
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type, etc. For some matrix operations there are of course conditions
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that elements may have to satisfy: for example, addition of matrices
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requires that addition of corresponding elements be possible.
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If an element of a matrix is a structure for which indices or an
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object element specifier is required, an element of that structure is
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referred to by appropriate uses of [ ] or ., and so on if an element
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of that element is required.
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For example, one may have an expressions like:
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; A[1,2][3].alpha[2];
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if A[1,2][3].alpha is a list with at least three elements, A[1,2][3] is
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an object of a type like obj {alpha, beta}, A[1,2] is a matrix of
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type mat[4] and A is a mat[2,3] matrix. When an element of a matrix
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is a matrix and the total number of indices does not exceed 4, the
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indices can be combined into one list, e.g. the A[1,2][3] in the
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above example can be shortened to A[1,2,3]. (Unlike C, A[1,2] cannot
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be expressed as A[1][2].)
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The function ismat(V) returns 1 if V is a matrix, 0 otherwise.
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isident(V) returns 1 if V is a square matrix with diagonal elements 1,
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off-diagonal elements zero, or a zero- or one-dimensional matrix with
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every element 1; otherwise zero is returned. Thus isident(V) = 1
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indicates that for V * A and A * V where A is any matrix of
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for which either product is defined and the elements of A are real
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or complex numbers, that product will equal A.
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If V is matrix-valued, test(V) returns 0 if every element of V tests
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as zero; otherwise 1 is returned.
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The dimension of a matrix A, i.e. the number of index-ranges in the
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initial creation of the matrix, is returned by the function matdim(A).
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For 1 <= i <= matdim(A), the minimum and maximum values for the i-th
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index range are returned by matmin(A, i) and matmax(A,i), respectively.
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The total number of elements in the matrix is returned by size(A).
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The sum of the elements in the matrix is returned by matsum(A).
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The default method of printing matrices is to give a line of information
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about the matrix, and to list on separate lines up to 15 elements,
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the indices and either the value (for numbers, strings, objects) or
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some descriptive information for lists or matrices, etc.
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Numbers are displayed in the current number-printing mode.
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The maximum number of elements to be printed can be assigned
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any nonnegative integer value m by config("maxprint", m).
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Users may define another method of printing matrices by defining a
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function mat_print(M); for example, for a not too big 2-dimensional
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matrix A it is a common practice to use a loop like:
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define mat_print(A) {
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local i,j;
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for (i = matmin(A,1); i <= matmax(A,1); i++) {
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if (i != matmin(A,1))
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printf("\t");
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for (j = matmin(A,2); j <= matmax(A,2); j++)
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printf(" [%d,%d]: %e", i, j, A[i,j]);
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if (i != matmax(A,1))
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printf("\n");
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}
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}
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So that when one defines a 2D matrix such as:
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; mat X[2,3] = {1,2,3,4,5,6}
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then printing X results in:
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[0,0]: 1 [0,1]: 2 [0,2]: 3
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[1,0]: 4 [1,1]: 5 [1,2]: 6
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The default printing may be restored by
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; undefine mat_print;
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The keyword "mat" followed by two or more index-range-lists returns a
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matrix with indices specified by the first list, whose elements are
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matrices as determined by the later index-range-lists. For
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example mat[2][3] is a 2-element matrix, each of whose elements has
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as its value a 3-element matrix. Values may be assigned to the
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elements of the innermost matrices by nested = {...} operations as in
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; mat [2][3] = {{1,2,3},{4,5,6}}
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An example of the use of mat with a declarator is
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; global mat A B [2,3], C [4]
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This creates, if they do not already exist, three global variables with
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names A, B, C, and assigns to A and B the value mat[2,3] and to C mat[4].
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Some operations are defined for matrices.
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A == B
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Returns 1 if A and B are of the same "shape" and "corresponding"
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elements are equal; otherwise 0 is returned. Being of the same
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shape means they have the same dimension d, and for each i <= d,
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matmax(A,i) - matmin(A,i) == matmax(B,i) - matmin(B,i),
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One consequence of being the same shape is that the matrices will
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have the same size. Elements "correspond" if they have the same
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double-bracket indices; thus A == B implies that A[[i]] == B[[i]]
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for 0 <= i < size(A) == size(B).
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A + B
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A - B
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These are defined A and B have the same shape, the element
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with double-bracket index j being evaluated by A[[j]] + B[[j]] and
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A[[j]] - B[[j]], respectively. The index-ranges for the results
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are those for the matrix A.
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A[i,j]
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If A is two-dimensional, it is customary to speak of the indices
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i, j in A[i,j] as referring to rows and columns; the number of
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rows is matmax(A,1) - matmin(A,1) + 1; the number of columns if
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matmax(A,2) - matmin(A,2) + 1. A matrix is said to be square
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if it is two-dimensional and the number of rows is equal to the
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number of columns.
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A * B
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Multiplication is defined provided certain conditions by the
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dimensions and shapes of A and B are satisfied. If both have
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dimension 2 and the column-index-list for A is the same as
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the row-index-list for B, C = A * B is defined in the usual
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way so that for i in the row-index-list of A and j in the
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column-index-list for B,
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C[i,j] = Sum A[i,k] * B[k,j]
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the sum being over k in the column-index-list of A. The same
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formula is used so long as the number of columns in A is the same
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as the number of rows in B and k is taken to refer to the offset
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from matmin(A,2) and matmin(B,1), respectively, for A and B.
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If the multiplications and additions required cannot be performed,
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an execution error may occur or the result for C may contain
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one or more error-values as elements.
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If A or B has dimension zero, the result for A * B is simply
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that of multiplying the elements of the other matrix on the
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left by A[] or on the right by B[].
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If both A and B have dimension 1, A * B is defined if A and B
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have the same size; the result has the same index-list as A
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and each element is the product of corresponding elements of
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A and B. If A and B have the same index-list, this multiplication
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is consistent with multiplication of 2D matrices if A and B are
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taken to represent 2D matrices for which the off-diagonal elements
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are zero and the diagonal elements are those of A and B.
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the real and complex numbers.
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If A is of dimension 1 and B is of dimension 2, A * B is defined
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if the number of rows in B is the same as the size of A. The
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result has the same index-lists as B; each row of B is multiplied
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on the left by the corresponding element of A.
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If A is of dimension 2 and B is of dimension 1, A * B is defined
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if number of columns in A is the same as the size of A. The
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result has the same index-lists as A; each column of A is
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multiplied on the right by the corresponding element of B.
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The algebra of additions and multiplications involving both one-
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and two-dimensional matrices is particularly simple when all the
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elements are real or complex numbers and all the index-lists are
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the same, as occurs, for example, if for some positive integer n,
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all the matrices start as mat [n] or mat [n,n].
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det(A)
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If A is a square, det(A) is evaluated by an algorithm that returns
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the determinant of A if the elements of A are real or complex
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numbers, and if such an A is non-singular, inverse(A) returns
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the inverse of A indexed in the same way as A. For matrix A of
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dimension 0 or 1, det(A) is defined as the product of the elements
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of A in the order in which they occur in A, inverse(A) returns
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a matrix indexed in the same way as A with each element inverted.
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The following functions are defined to return matrices with the same
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index-ranges as A and the specified operations performed on all
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elements of A. Here num is an arbitrary complex number (nonzero
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when it is a divisor), int an integer, rnd a rounding-type
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specifier integer, real a real number.
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num * A
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A * num
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A / num
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- A
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conj(A)
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A << int, A >> int
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scale(A, int)
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round(A, int, rnd)
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bround(A, int, rnd)
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appr(A, real, rnd)
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int(A)
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frac(A)
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A // real
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A % real
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A ^ int
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If A and B are one-dimensional of the same size dp(A, B) returns
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their dot-product, i.e. the sum of the products of corresponding
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elements.
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If A and B are one-dimension and of size 3, cp(A, B) returns their
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cross-product.
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randperm(A) returns a matrix indexed the same as A in which the elements
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of A have been randomly permuted.
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sort(A) returns a matrix indexed the same as A in which the elements
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of A have been sorted.
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If A is an lvalue whose current value is a matrix, matfill(A, v)
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assigns the value v to every element of A, and if also, A is
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square, matfill(A, v1, v2) assigns v1 to the off-diagonal elements,
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v2 to the diagonal elements. To create and assign to A the unit
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n * n matrix, one may use matfill(mat A[n,n], 0, 1).
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For a square matrix A, mattrace(A) returns the trace of A, i.e. the
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sum of the diagonal elements. For zero- or one-dimensional A,
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mattrace(A) returns the sum of the elements of A.
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For a two-dimensional matrix A, mattrans(A) returns the transpose
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of A, i.e. if A is mat[m,n], it returns a mat[n,m] matrix with
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[i,j] element equal to A[j,i]. For zero- or one-dimensional A,
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mattrace(A) returns a matrix with the same value as A.
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The functions search(A, value, start, end]) and
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rsearch(A, value, start, end]) return the first or last index i
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for which A[[i]] == value and start <= i < end, or if there is
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no such index, the null value. For further information on default
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values and the use of an "accept" function, see the help files for
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search and rsearch.
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reverse(A) returns a matrix with the same index-lists as A but the
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elements in reversed order.
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The copy and blkcpy functions may be used to copy data to a matrix from
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a matrix or list, or from a matrix to a list. In copying from a
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matrix to a matrix the matrices need not have the same dimension;
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in effect they are treated as linear arrays.
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EXAMPLE
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; obj point {x,y}
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; mat A[5] = {1, 2+3i, "ab", mat[2] = {4,5}, obj point = {6,7}}
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; A
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mat [5] (5 elements, 5 nonzero):
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[0] = 1
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[1] = 2+3i
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[2] = "ab"
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[3] = mat [2] (2 elements, 2 nonzero)
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[4] = obj point {6, 7}
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; print A[0], A[1], A[2], A[3][0], A[4].x
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1 2+3i ab 4 6
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; define point_add(a,b) = obj point = {a.x + b.x, a.y + b.y}
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point_add(a,b) defined
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; mat [B] = {8, , "cd", mat[2] = {9,10}, obj point = {11,12}}
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; A + B
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mat [5] (5 elements, 5 nonzero):
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[0] = 9
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[1] = 2+3i
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[2] = "abcd"
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[3] = mat [2] (2 elements, 2 nonzero)
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[4] = obj point {17, 19}
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; mat C[2,2] = {1,2,3,4}
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; C^10
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mat [2,2] (4 elements, 4 nonzero):
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[0,0] = 4783807
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[0,1] = 6972050
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[1,0] = 10458075
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[1,1] = 15241882
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; C^-10
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mat [2,2] (4 elements, 4 nonzero):
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[0,0] = 14884.650390625
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[0,1] = -6808.642578125
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[1,0] = -10212.9638671875
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[1,1] = 4671.6865234375
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; mat A[4] = {1,2,3,4}, A * reverse(A);
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mat [4] (4 elements, 4 nonzero):
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[0] = 4
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[1] = 6
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[2] = 6
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[3] = 4
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LIMITS
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The theoretical upper bound for the absolute values of indices is
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2^31 - 1, but the size of matrices that can be handled in practice will
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be limited by the availability of memory and what is an acceptable
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runtime. For example, although it may take only a fraction of a
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second to invert a 10 * 10 matrix, it will probably take about 1000
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times as long to invert a 100 * 100 matrix.
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LINK LIBRARY
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none
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SEE ALSO
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ismat, matdim, matmax, matmin, mattrans, mattrace, matsum, matfill,
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det, inverse, isident, test, config, search, rsearch, reverse, copy,
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blkcpy, dp, cp, randperm, sort
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## Copyright (C) 1999-2006,2018,2021 Landon Curt Noll
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##
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## Calc is open software; you can redistribute it and/or modify it under
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## the terms of the version 2.1 of the GNU Lesser General Public License
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## as published by the Free Software Foundation.
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##
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## Calc is distributed in the hope that it will be useful, but WITHOUT
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## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
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## or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General
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## Public License for more details.
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##
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## A copy of version 2.1 of the GNU Lesser General Public License is
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## distributed with calc under the filename COPYING-LGPL. You should have
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## received a copy with calc; if not, write to Free Software Foundation, Inc.
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## 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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##
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## Under source code control: 1991/07/21 04:37:22
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## File existed as early as: 1991
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##
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## chongo <was here> /\oo/\ http://www.isthe.com/chongo/
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## Share and enjoy! :-) http://www.isthe.com/chongo/tech/comp/calc/
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