octave: Finding Elements and Checking Conditions
16.1 Finding Elements and Checking Conditions
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The functions ‘any’ and ‘all’ are useful for determining whether any or
all of the elements of a matrix satisfy some condition. The ‘find’
function is also useful in determining which elements of a matrix meet a
specified condition.
-- : any (X)
-- : any (X, DIM)
For a vector argument, return true (logical 1) if any element of
the vector is nonzero.
For a matrix argument, return a row vector of logical ones and
zeros with each element indicating whether any of the elements of
the corresponding column of the matrix are nonzero. For example:
any (eye (2, 4))
⇒ [ 1, 1, 0, 0 ]
If the optional argument DIM is supplied, work along dimension DIM.
For example:
any (eye (2, 4), 2)
⇒ [ 1; 1 ]
See also: all XREFall.
-- : all (X)
-- : all (X, DIM)
For a vector argument, return true (logical 1) if all elements of
the vector are nonzero.
For a matrix argument, return a row vector of logical ones and
zeros with each element indicating whether all of the elements of
the corresponding column of the matrix are nonzero. For example:
all ([2, 3; 1, 0])
⇒ [ 1, 0 ]
If the optional argument DIM is supplied, work along dimension DIM.
See also: any XREFany.
Since the comparison operators (Comparison Ops) return
matrices of ones and zeros, it is easy to test a matrix for many things,
not just whether the elements are nonzero. For example,
all (all (rand (5) < 0.9))
⇒ 0
tests a random 5 by 5 matrix to see if all of its elements are less than
0.9.
Note that in conditional contexts (like the test clause of ‘if’ and
‘while’ statements) Octave treats the test as if you had typed ‘all (all
(condition))’.
-- : Z = xor (X, Y)
-- : Z = xor (X1, X2, ...)
Return the “exclusive or” of X and Y.
For boolean expressions X and Y, ‘xor (X, Y)’ is true if and only
if one of X or Y is true. Otherwise, if X and Y are both true or
both false, ‘xor’ returns false.
The truth table for the xor operation is
X Y Z
- - -
0 0 0
1 0 1
0 1 1
1 1 0
If more than two arguments are given the xor operation is applied
cumulatively from left to right:
(...((x1 XOR x2) XOR x3) XOR ...)
See also: and XREFand, or XREFor, not XREFnot.
-- : diff (X)
-- : diff (X, K)
-- : diff (X, K, DIM)
If X is a vector of length n, ‘diff (X)’ is the vector of first
differences X(2) - X(1), ..., X(n) - X(n-1).
If X is a matrix, ‘diff (X)’ is the matrix of column differences
along the first non-singleton dimension.
The second argument is optional. If supplied, ‘diff (X, K)’, where
K is a non-negative integer, returns the K-th differences. It is
possible that K is larger than the first non-singleton dimension of
the matrix. In this case, ‘diff’ continues to take the differences
along the next non-singleton dimension.
The dimension along which to take the difference can be explicitly
stated with the optional variable DIM. In this case the K-th order
differences are calculated along this dimension. In the case where
K exceeds ‘size (X, DIM)’ an empty matrix is returned.
See also: sort XREFsort, merge XREFmerge.
-- : isinf (X)
Return a logical array which is true where the elements of X are
infinite and false where they are not.
For example:
isinf ([13, Inf, NA, NaN])
⇒ [ 0, 1, 0, 0 ]
See also: isfinite XREFisfinite, isnan XREFisnan,
isna XREFisna.
-- : isnan (X)
Return a logical array which is true where the elements of X are
NaN values and false where they are not.
NA values are also considered NaN values. For example:
isnan ([13, Inf, NA, NaN])
⇒ [ 0, 0, 1, 1 ]
DONTPRINTYET See also: isna XREFisna, isinf XREFisinf, *noteDONTPRINTYET See also: isna XREFisna, isinf XREFisinf,
isfinite XREFisfinite.
-- : isfinite (X)
Return a logical array which is true where the elements of X are
finite values and false where they are not.
For example:
isfinite ([13, Inf, NA, NaN])
⇒ [ 1, 0, 0, 0 ]
DONTPRINTYET See also: isinf XREFisinf, isnan XREFisnan, *noteDONTPRINTYET See also: isinf XREFisinf, isnan XREFisnan,
isna XREFisna.
-- : [ERR, YI, ...] = common_size (XI, ...)
Determine if all input arguments are either scalar or of common
size.
If true, ERR is zero, and YI is a matrix of the common size with
all entries equal to XI if this is a scalar or XI otherwise. If
the inputs cannot be brought to a common size, ERR is 1, and YI is
XI. For example:
[err, a, b] = common_size ([1 2; 3 4], 5)
⇒ err = 0
⇒ a = [ 1, 2; 3, 4 ]
⇒ b = [ 5, 5; 5, 5 ]
This is useful for implementing functions where arguments can
either be scalars or of common size.
See also: size XREFsize, size_equal XREFsize_equal,
numel XREFnumel, ndims XREFndims.
-- : IDX = find (X)
-- : IDX = find (X, N)
-- : IDX = find (X, N, DIRECTION)
-- : [i, j] = find (...)
-- : [i, j, v] = find (...)
Return a vector of indices of nonzero elements of a matrix, as a
row if X is a row vector or as a column otherwise.
To obtain a single index for each matrix element, Octave pretends
that the columns of a matrix form one long vector (like Fortran
arrays are stored). For example:
find (eye (2))
⇒ [ 1; 4 ]
If two inputs are given, N indicates the maximum number of elements
to find from the beginning of the matrix or vector.
If three inputs are given, DIRECTION should be one of "first" or
"last", requesting only the first or last N indices, respectively.
However, the indices are always returned in ascending order.
If two outputs are requested, ‘find’ returns the row and column
indices of nonzero elements of a matrix. For example:
[i, j] = find (2 * eye (2))
⇒ i = [ 1; 2 ]
⇒ j = [ 1; 2 ]
If three outputs are requested, ‘find’ also returns a vector
containing the nonzero values. For example:
[i, j, v] = find (3 * eye (2))
⇒ i = [ 1; 2 ]
⇒ j = [ 1; 2 ]
⇒ v = [ 3; 3 ]
Note that this function is particularly useful for sparse matrices,
as it extracts the nonzero elements as vectors, which can then be
used to create the original matrix. For example:
sz = size (a);
[i, j, v] = find (a);
b = sparse (i, j, v, sz(1), sz(2));
See also: nonzeros XREFnonzeros.
-- : IDX = lookup (TABLE, Y)
-- : IDX = lookup (TABLE, Y, OPT)
Lookup values in a sorted table.
This function is usually used as a prelude to interpolation.
If table is increasing and ‘idx = lookup (table, y)’, then
‘table(idx(i)) <= y(i) < table(idx(i+1))’ for all ‘y(i)’ within the
table. If ‘y(i) < table(1)’ then ‘idx(i)’ is 0. If ‘y(i) >=
table(end)’ or ‘isnan (y(i))’ then ‘idx(i)’ is ‘n’.
If the table is decreasing, then the tests are reversed. For
non-strictly monotonic tables, empty intervals are always skipped.
The result is undefined if TABLE is not monotonic, or if TABLE
contains a NaN.
The complexity of the lookup is O(M*log(N)) where N is the size of
TABLE and M is the size of Y. In the special case when Y is also
sorted, the complexity is O(min(M*log(N),M+N)).
TABLE and Y can also be cell arrays of strings (or Y can be a
single string). In this case, string lookup is performed using
lexicographical comparison.
If OPTS is specified, it must be a string with letters indicating
additional options.
‘m’
‘table(idx(i)) == y(i)’ if ‘y(i)’ occurs in table; otherwise,
‘idx(i)’ is zero.
‘b’
‘idx(i)’ is a logical 1 or 0, indicating whether ‘val(i)’ is
contained in table or not.
‘l’
For numeric lookups the leftmost subinterval shall be extended
to infinity (i.e., all indices at least 1)
‘r’
For numeric lookups the rightmost subinterval shall be
extended to infinity (i.e., all indices at most n-1).
If you wish to check if a variable exists at all, instead of
properties its elements may have, consult Status of Variables.