Ufunc(3) User Contributed Perl Documentation Ufunc(3)NAMEPDL::Ufunc - primitive ufunc operations for pdl
DESCRIPTION
This module provides some primitive and useful functions defined using
PDL::PP based on functionality of what are sometimes called ufuncs (for
example NumPY and Mathematica talk about these). It collects all the
functions generally used to "reduce" or "accumulate" along a dimension.
These all do their job across the first dimension but by using the
slicing functions you can do it on any dimension.
The PDL::Reduce module provides an alternative interface to many of the
functions in this module.
SYNOPSIS
use PDL::Ufunc;
FUNCTIONS
prodover
Signature: (a(n); int+ [o]b())
Project via product to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the product along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = prodover($b);
$spectrum = prodover $image->xchg(0,1)
prodover does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
dprodover
Signature: (a(n); double [o]b())
Project via product to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the product along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = dprodover($b);
$spectrum = dprodover $image->xchg(0,1)
Unlike prodover, the calculations are performed in double precision.
dprodover does handle bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
cumuprodover
Signature: (a(n); int+ [o]b(n))
Cumulative product
This function calculates the cumulative product along the 1st
dimension.
By using xchg etc. it is possible to use any dimension.
The sum is started so that the first element in the cumulative product
is the first element of the parameter.
$a = cumuprodover($b);
$spectrum = cumuprodover $image->xchg(0,1)
cumuprodover does handle bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
dcumuprodover
Signature: (a(n); double [o]b(n))
Cumulative product
This function calculates the cumulative product along the 1st
dimension.
By using xchg etc. it is possible to use any dimension.
The sum is started so that the first element in the cumulative product
is the first element of the parameter.
$a = cumuprodover($b);
$spectrum = cumuprodover $image->xchg(0,1)
Unlike cumuprodover, the calculations are performed in double
precision.
dcumuprodover does handle bad values. It will set the bad-value flag
of all output piddles if the flag is set for any of the input piddles.
sumover
Signature: (a(n); int+ [o]b())
Project via sum to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the sum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = sumover($b);
$spectrum = sumover $image->xchg(0,1)
sumover does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
dsumover
Signature: (a(n); double [o]b())
Project via sum to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the sum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = dsumover($b);
$spectrum = dsumover $image->xchg(0,1)
Unlike sumover, the calculations are performed in double precision.
dsumover does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
cumusumover
Signature: (a(n); int+ [o]b(n))
Cumulative sum
This function calculates the cumulative sum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
The sum is started so that the first element in the cumulative sum is
the first element of the parameter.
$a = cumusumover($b);
$spectrum = cumusumover $image->xchg(0,1)
cumusumover does handle bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
dcumusumover
Signature: (a(n); double [o]b(n))
Cumulative sum
This function calculates the cumulative sum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
The sum is started so that the first element in the cumulative sum is
the first element of the parameter.
$a = cumusumover($b);
$spectrum = cumusumover $image->xchg(0,1)
Unlike cumusumover, the calculations are performed in double precision.
dcumusumover does handle bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
orover
Signature: (a(n); int+ [o]b())
Project via or to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the or along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = orover($b);
$spectrum = orover $image->xchg(0,1)
If "a()" contains only bad data (and its bad flag is set), "b()" is set
bad. Otherwise "b()" will have its bad flag cleared, as it will not
contain any bad values.
bandover
Signature: (a(n); int+ [o]b())
Project via bitwise and to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the bitwise and along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = bandover($b);
$spectrum = bandover $image->xchg(0,1)
If "a()" contains only bad data (and its bad flag is set), "b()" is set
bad. Otherwise "b()" will have its bad flag cleared, as it will not
contain any bad values.
borover
Signature: (a(n); int+ [o]b())
Project via bitwise or to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the bitwise or along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = borover($b);
$spectrum = borover $image->xchg(0,1)
If "a()" contains only bad data (and its bad flag is set), "b()" is set
bad. Otherwise "b()" will have its bad flag cleared, as it will not
contain any bad values.
zcover
Signature: (a(n); int+ [o]b())
Project via == 0 to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the == 0 along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = zcover($b);
$spectrum = zcover $image->xchg(0,1)
If "a()" contains only bad data (and its bad flag is set), "b()" is set
bad. Otherwise "b()" will have its bad flag cleared, as it will not
contain any bad values.
andover
Signature: (a(n); int+ [o]b())
Project via and to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the and along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = andover($b);
$spectrum = andover $image->xchg(0,1)
If "a()" contains only bad data (and its bad flag is set), "b()" is set
bad. Otherwise "b()" will have its bad flag cleared, as it will not
contain any bad values.
intover
Signature: (a(n); int+ [o]b())
Project via integral to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the integral along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = intover($b);
$spectrum = intover $image->xchg(0,1)
Notes:
For "n > 3", these are all "O(h^4)" (like Simpson's rule), but are
integrals between the end points assuming the pdl gives values just at
these centres: for such `functions', sumover is correct to O(h), but is
the natural (and correct) choice for binned data, of course.
intover ignores the bad-value flag of the input piddles. It will set
the bad-value flag of all output piddles if the flag is set for any of
the input piddles.
average
Signature: (a(n); int+ [o]b())
Project via average to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the average along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = average($b);
$spectrum = average $image->xchg(0,1)
average does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
daverage
Signature: (a(n); double [o]b())
Project via average to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the average along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = daverage($b);
$spectrum = daverage $image->xchg(0,1)
Unlike average, the calculation is performed in double precision.
daverage does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
medover
Signature: (a(n); [o]b(); [t]tmp(n))
Project via median to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the median along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = medover($b);
$spectrum = medover $image->xchg(0,1)
medover does handle bad values. It will set the bad-value flag of all
output piddles if the flag is set for any of the input piddles.
oddmedover
Signature: (a(n); [o]b(); [t]tmp(n))
Project via oddmedian to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the oddmedian along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = oddmedover($b);
$spectrum = oddmedover $image->xchg(0,1)
The median is sometimes not a good choice as if the array has an even
number of elements it lies half-way between the two middle values -
thus it does not always correspond to a data value. The lower-odd
median is just the lower of these two values and so it ALWAYS sits on
an actual data value which is useful in some circumstances.
oddmedover does handle bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
pctover
Signature: (a(n); p(); [o]b(); [t]tmp(n))
Project via percentile to N-1 dimensions
This function reduces the dimensionality of a piddle by one by finding
the specified percentile (p) along the 1st dimension. The specified
percentile must be between 0.0 and 1.0. When the specified percentile
falls between data points, the result is interpolated. Values outside
the allowed range are clipped to 0.0 or 1.0 respectively. The
algorithm implemented here is based on the interpolation variant
described at <http://en.wikipedia.org/wiki/Percentile> as used by
Microsoft Excel and recommended by NIST.
By using xchg etc. it is possible to use any dimension.
$a = pctover($b, $p);
$spectrum = pctover $image->xchg(0,1) $p
pctover does not process bad values. It will set the bad-value flag of
all output piddles if the flag is set for any of the input piddles.
oddpctover
Signature: (a(n); p(); [o]b(); [t]tmp(n))
Project via percentile to N-1 dimensions
This function reduces the dimensionality of a piddle by one by finding
the specified percentile along the 1st dimension. The specified
percentile must be between 0.0 and 1.0. When the specified percentile
falls between two values, the nearest data value is the result. The
algorithm implemented is from the textbook version described first at
"/en.wikipedia.org/wiki/Percentile" in http:.
By using xchg etc. it is possible to use any dimension.
$a = oddpctover($b, $p);
$spectrum = oddpctover $image->xchg(0,1) $p
oddpctover does not process bad values. It will set the bad-value flag
of all output piddles if the flag is set for any of the input piddles.
pct
Return the specified percentile of all elements in a piddle. The
specified percentile (p) must be between 0.0 and 1.0. When the
specified percentile falls between data points, the result is
interpolated.
$x = pct($data, $pct);
oddpct
Return the specified percentile of all elements in a piddle. The
specified percentile must be between 0.0 and 1.0. When the specified
percentile falls between two values, the nearest data value is the
result.
$x = oddpct($data, $pct);
avg
Return the average of all elements in a piddle
$x = avg($data);
This routine handles bad values (see the documentation for average). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
sum
Return the sum of all elements in a piddle
$x = sum($data);
This routine handles bad values (see the documentation for sumover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
prod
Return the product of all elements in a piddle
$x = prod($data);
This routine handles bad values (see the documentation for prodover).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
davg
Return the average (in double precision) of all elements in a piddle
$x = davg($data);
This routine handles bad values (see the documentation for daverage).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
dsum
Return the sum (in double precision) of all elements in a piddle
$x = dsum($data);
This routine handles bad values (see the documentation for dsumover).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
dprod
Return the product (in double precision) of all elements in a piddle
$x = dprod($data);
This routine handles bad values (see the documentation for dprodover).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
zcheck
Return the check for zero of all elements in a piddle
$x = zcheck($data);
This routine handles bad values (see the documentation for zcover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
and
Return the logical and of all elements in a piddle
$x = and($data);
This routine handles bad values (see the documentation for andover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
band
Return the bitwise and of all elements in a piddle
$x = band($data);
This routine handles bad values (see the documentation for bandover).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
or
Return the logical or of all elements in a piddle
$x = or($data);
This routine handles bad values (see the documentation for orover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
bor
Return the bitwise or of all elements in a piddle
$x = bor($data);
This routine handles bad values (see the documentation for borover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
min
Return the minimum of all elements in a piddle
$x = min($data);
This routine handles bad values (see the documentation for minimum). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
max
Return the maximum of all elements in a piddle
$x = max($data);
This routine handles bad values (see the documentation for maximum). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
median
Return the median of all elements in a piddle
$x = median($data);
This routine handles bad values (see the documentation for medover). I
still need to decide how to handle the case when the return value is a
bad value (eg to make sure it has the same type as the input piddle OR
perhaps we should die - makes sense for the conditional ops but not
things like sum)
oddmedian
Return the oddmedian of all elements in a piddle
$x = oddmedian($data);
This routine handles bad values (see the documentation for oddmedover).
I still need to decide how to handle the case when the return value is
a bad value (eg to make sure it has the same type as the input piddle
OR perhaps we should die - makes sense for the conditional ops but not
things like sum)
any
Return true if any element in piddle set
Useful in conditional expressions:
if (any $a>15) { print "some values are greater than 15\n" }
See or for comments on what happens when all elements in the check are
bad.
all
Return true if all elements in piddle set
Useful in conditional expressions:
if (all $a>15) { print "all values are greater than 15\n" }
See and for comments on what happens when all elements in the check are
bad.
minmax
Returns an array with minimum and maximum values of a piddle.
($mn, $mx) = minmax($pdl);
This routine does not thread over the dimensions of $pdl; it returns
the minimum and maximum values of the whole array. See minmaximum if
this is not what is required. The two values are returned as Perl
scalars similar to min/max.
pdl> $x = pdl [1,-2,3,5,0]
pdl> ($min, $max) = minmax($x);
pdl> p "$min $max\n";
-2 5
qsort
Signature: (a(n); [o]b(n))
Quicksort a vector into ascending order.
print qsort random(10);
Bad values are moved to the end of the array:
pdl> p $b
[42 47 98 BAD 22 96 74 41 79 76 96 BAD 32 76 25 59 BAD 96 32 BAD]
pdl> p qsort($b)
[22 25 32 32 41 42 47 59 74 76 76 79 96 96 96 98 BAD BAD BAD BAD]
qsorti
Signature: (a(n); int [o]indx(n))
Quicksort a vector and return index of elements in ascending order.
$ix = qsorti $a;
print $a->index($ix); # Sorted list
Bad elements are moved to the end of the array:
pdl> p $b
[42 47 98 BAD 22 96 74 41 79 76 96 BAD 32 76 25 59 BAD 96 32 BAD]
pdl> p $b->index( qsorti($b) )
[22 25 32 32 41 42 47 59 74 76 76 79 96 96 96 98 BAD BAD BAD BAD]
qsortvec
Signature: (a(n,m); [o]b(n,m))
Sort a list of vectors lexicographically.
The 0th dimension of the source piddle is dimension in the vector; the
1st dimension is list order. Higher dimensions are threaded over.
print qsortvec pdl([[1,2],[0,500],[2,3],[4,2],[3,4],[3,5]]);
[
[ 0 500]
[ 1 2]
[ 2 3]
[ 3 4]
[ 3 5]
[ 4 2]
]
Vectors with bad components should be moved to the end of the array:
qsortveci
Signature: (a(n,m); int [o]indx(m))
Sort a list of vectors lexicographically, returning the indices of the
sorted vectors rather than the sorted list itself.
As with "qsortvec", the input PDL should be an NxM array containing M
separate N-dimensional vectors. The return value is an integer M-PDL
containing the M-indices of original array rows, in sorted order.
As with "qsortvec", the zeroth element of the vectors runs slowest in
the sorted list.
Additional dimensions are threaded over: each plane is sorted
separately, so qsortveci may be thought of as a collapse operator of
sorts (groan).
Vectors with bad components should be moved to the end of the array:
minimum
Signature: (a(n); [o]c())
Project via minimum to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the minimum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = minimum($b);
$spectrum = minimum $image->xchg(0,1)
Output is set bad if all elements of the input are bad, otherwise the
bad flag is cleared for the output piddle.
Note that "NaNs" are considered to be valid values; see isfinite and
badmask for ways of masking NaNs.
minimum_ind
Signature: (a(n); int [o] c())
Like minimum but returns the index rather than the value
Output is set bad if all elements of the input are bad, otherwise the
bad flag is cleared for the output piddle.
minimum_n_ind
Signature: (a(n); int[o]c(m))
Returns the index of "m" minimum elements
Not yet been converted to ignore bad values
maximum
Signature: (a(n); [o]c())
Project via maximum to N-1 dimensions
This function reduces the dimensionality of a piddle by one by taking
the maximum along the 1st dimension.
By using xchg etc. it is possible to use any dimension.
$a = maximum($b);
$spectrum = maximum $image->xchg(0,1)
Output is set bad if all elements of the input are bad, otherwise the
bad flag is cleared for the output piddle.
Note that "NaNs" are considered to be valid values; see isfinite and
badmask for ways of masking NaNs.
maximum_ind
Signature: (a(n); int [o] c())
Like maximum but returns the index rather than the value
Output is set bad if all elements of the input are bad, otherwise the
bad flag is cleared for the output piddle.
maximum_n_ind
Signature: (a(n); int[o]c(m))
Returns the index of "m" maximum elements
Not yet been converted to ignore bad values
minmaximum
Signature: (a(n); [o]cmin(); [o] cmax(); int [o]cmin_ind(); int [o]cmax_ind())
Find minimum and maximum and their indices for a given piddle;
pdl> $a=pdl [[-2,3,4],[1,0,3]]
pdl> ($min, $max, $min_ind, $max_ind)=minmaximum($a)
pdl> p $min, $max, $min_ind, $max_ind
[-2 0] [4 3] [0 1] [2 2]
See also minmax, which clumps the piddle together.
If "a()" contains only bad data, then the output piddles will be set
bad, along with their bad flag. Otherwise they will have their bad
flags cleared, since they will not contain any bad values.
AUTHOR
Copyright (C) Tuomas J. Lukka 1997 (lukka@husc.harvard.edu).
Contributions by Christian Soeller (c.soeller@auckland.ac.nz) and Karl
Glazebrook (kgb@aaoepp.aao.gov.au). All rights reserved. There is no
warranty. You are allowed to redistribute this software / documentation
under certain conditions. For details, see the file COPYING in the PDL
distribution. If this file is separated from the PDL distribution, the
copyright notice should be included in the file.
perl v5.14.1 2011-07-26 Ufunc(3)
