1Core(3) User Contributed Perl Documentation Core(3)
2
6 PDL::Core - fundamental PDL functionality and
7 vectorization/broadcasting
8
10 Methods and functions for type conversions, PDL creation, type
11 conversion, broadcasting etc.
12
14 use PDL::Core; # Normal routines
15 use PDL::Core ':Internal'; # Hairy routines
16
18 PDL provides vectorized operations via a built-in engine.
19 Vectorization in PDL is called "broadcasting" (formerly, up to 2.074,
20 "threading"). The broadcasting engine implements simple rules for each
21 operation.
22 Each PDL object has a "shape" that is a generalized N-dimensional
24 rectangle defined by a "dim list" of sizes in an arbitrary set of
25 dimensions. A PDL with shape 2x3 has 6 elements and is said to be two-
26 dimensional, or may be referred to as a 2x3-PDL. The dimensions are
27 indexed numerically starting at 0, so a 2x3-PDL has a dimension 0 (or
28 "dim 0") with size 2 and a 1 dimension (or "dim 1") with size 3.
29 PDL generalizes *all* mathematical operations with the notion of
31 "active dims": each operator has zero or more active dims that are used
32 in carrying out the operation. Simple scalar operations like scalar
33 multiplication ('*') have 0 active dims. More complicated operators
34 can have more active dims. For example, matrix multiplication ('x')
35 has 2 active dims. Additional dims are automatically vectorized across
36 -- e.g. multiplying a 2x5-PDL with a 2x5-PDL requires 10 simple
37 multiplication operations, and yields a 2x5-PDL result.
38 Broadcasting rules
40 In any PDL expression, the active dims appropriate for each operator
41 are used starting at the 0 dim and working forward through the dim list
42 of each object. All additional dims after the active dims are
43 "broadcast dims". The broadcast dims do not have to agree exactly:
44 they are coerced to agree according to simple rules:
45 • Null PDLs match any dim list (see below).
47 • Dims with sizes other than 1 must all agree in size.
49 • Dims of size 1 are silently repeated as necessary except for
51 "[phys]" PDLs.
52 • Missing dims are expanded appropriately.
54 A size-1 dim for "[phys]" PDLs causes an exception if the dim is used
56 in another parameter and has a size greater than 1.
57 The "size 1" rule implements "generalized scalar" operation, by analogy
59 to scalar multiplication. The "missing dims" rule acknowledges the
60 ambiguity between a missing dim and a dim of size 1.
61 Null PDLs
63 PDLs on the left-hand side of assignment can have the special value
64 "Null". A null PDL has no dim list and no set size; its shape is
65 determined by the computed shape of the expression being assigned to
66 it. Null PDLs contain no values and can only be assigned to. When
67 assigned to (e.g. via the ".=" operator), they cease to be null PDLs.
68 To create a null PDL, use "PDL->null()".
70 Empty PDLs
72 PDLs can represent the empty set using "structured Empty" variables.
73 An empty PDL is not a null PDL.
74 Any dim of a PDL can be set explicitly to size 0. If so, the PDL
76 contains zero values (because the total number of values is the product
77 of all the sizes in the PDL's shape or dimlist).
78 Scalar PDLs are zero-dimensional and have no entries in the dim list,
80 so they cannot be empty. 1-D and higher PDLs can be empty. Empty PDLs
81 are useful for set operations, and are most commonly encountered in the
82 output from selection operators such as which and whichND. Not all
83 empty PDLs have the same broadcasting properties -- e.g. a 2x0-PDL
84 represents a collection of 2-vectors that happens to contain no
85 elements, while a simple 0-PDL represents a collection of scalar values
86 (that also happens to contain no elements).
87 Note that 0 dims are not adjustable via the broadcasting rules -- a dim
89 with size 0 can only match a corresponding dim of size 0 or 1.
90 Broadcast rules and assignments
92 Versions of PDL through 2.4.10 have some irregularity with broadcasting
93 and assignments. Currently the broadcasting engine performs a full
94 expansion of both sides of the computed assignment operator ".=" (which
95 assigns values to a pre-existing PDL). This leads to counter-intuitive
96 behavior in some cases:
97 • Empty PDLs and generalized scalars
99 Generalized scalars (PDLs with a dim of size 1) can match any size
101 in the corresponding dim, including 0. Thus,
102 $x = ones(2,0);
104 $y = sequence(2,1);
105 $c = $x * $y;
106 print $c;
107 prints "Empty[2,0]".
109 This behavior is counterintuitive but desirable, and will be
111 preserved in future versions of PDL.
112
114 These are important variables of global scope and are placed in the PDL
115 namespace.
116 $PDL::debug
118 When true, PDL debugging information is printed.
120 $PDL::verbose
122 When true, PDL functions provide chatty information.
124 $PDL::use_commas
126 Whether to insert commas when printing pdls
128 $PDL::floatformat, $PDL::doubleformat, $PDL::indxformat
130 The default print format for floats, doubles, and indx values,
132 respectively. The default default values are:
133 $PDL::floatformat = "%7g";
135 $PDL::doubleformat = "%10.8g";
136 $PDL::indxformat = "%12d";
137 $PDL::undefval
139 The value to use instead of "undef" when creating pdls. If is
141 "undef", 0 will be used.
142 $PDL::toolongtoprint
144 The maximal size pdls to print (defaults to 10000 elements)
146
148 barf
149 Standard error reporting routine for PDL.
150 barf() is the routine PDL modules should call to report errors. This is
152 because barf() will report the error as coming from the correct line in
153 the module user's script rather than in the PDL module.
154 For now, barf just calls Carp::confess()
156 Remember barf() is your friend. *Use* it!
158 At the perl level:
160 barf("User has too low an IQ!");
162 In C or XS code:
164 barf("You have made %d errors", count);
166 Note: this is one of the few functions ALWAYS exported by PDL::Core
168 pdl
170 PDL constructor - creates new ndarray from perl scalars/arrays,
171 ndarrays, and strings
172 $double_pdl = pdl(SCALAR|ARRAY REFERENCE|ARRAY|STRING); # default type
174 $type_pdl = pdl(PDL::Type,SCALAR|ARRAY REFERENCE|ARRAY|STRING);
175 $x = pdl [1..10]; # 1D array of doubles
177 $x = pdl ([1..10]); # 1D array
178 $x = pdl (1,2,3,4); # Ditto
179 $y = pdl [[1,2,3],[4,5,6]]; # 2D 3x2 array
180 $y = pdl "[[1,2,3],[4,5,6]]"; # Ditto (slower)
181 $y = pdl "[1 2 3; 4 5 6]"; # Ditto
182 $y = pdl q[1 2 3; 4 5 6]; # Ditto, using the q quote operator
183 $y = pdl "1 2 3; 4 5 6"; # Ditto, less obvious, but still works
184 $y = pdl 42 # 0-dimensional scalar
185 $c = pdl $x; # Make a new copy
186 $u = pdl ushort(), 42 # 0-dimensional ushort scalar
188 $y = pdl(byte(),[[1,2,3],[4,5,6]]); # 2D byte ndarray
189 $n = pdl indx(), [1..5]; # 1D array of indx values
191 $n = pdl indx, [1..5]; # ... can leave off parens
192 $n = indx( [1..5] ); # ... still the same!
193 $n = pdl cdouble, 2, 3; # native complex numbers, zero imaginary
195 use Math::Complex qw(cplx);
196 $n = pdl cdouble, 2, cplx(2, 1)); # explicit type
197 $n = pdl 2, cplx(2, 1); # default cdouble if Math::Complex obj
198 $x = pdl([[1,2,3],[4,5,6]]); # 2D
200 $x = pdl([1,2,3],[4,5,6]); # 2D
201 Note the last two are equivalent - a list is automatically converted to
203 a list reference for syntactic convenience. i.e. you can omit the outer
204 "[]"
205 You can mix and match arrays, array refs, and PDLs in your argument
207 list, and "pdl" will sort them out. You get back a PDL whose last
208 (slowest running) dim runs across the top level of the list you hand
209 in, and whose first (fastest running) dim runs across the deepest level
210 that you supply.
211 At the moment, you cannot mix and match those arguments with string
213 arguments, though we can't imagine a situation in which you would
214 really want to do that.
215 The string version of pdl also allows you to use the strings "bad",
217 "inf", and "nan", and it will insert the values that you mean (and set
218 the bad flag if you use "bad"). You can mix and match case, though you
219 shouldn't. Here are some examples:
220 $bad = pdl q[1 2 3 bad 5 6]; # Set fourth element to the bad value
222 $bad = pdl q[1 2 3 BAD 5 6]; # ditto
223 $bad = pdl q[1 2 inf bad 5]; # now third element is IEEE infinite value
224 $bad = pdl q[nan 2 inf -inf]; # first value is IEEE nan value
225 The default constructor uses IEEE double-precision floating point
227 numbers. You can use other types, but you will get a warning if you try
228 to use "nan" with integer types (it will be replaced with the "bad"
229 value) and you will get a fatal error if you try to use "inf".
230 Throwing a PDL into the mix has the same effect as throwing in a list
232 ref:
233 pdl(pdl(1,2),[3,4])
235 is the same as
237 pdl([1,2],[3,4]).
239 All of the dimensions in the list are "padded-out" with undefval to
241 meet the widest dim in the list, so (e.g.)
242 $x = pdl([[1,2,3],[2]])
244 gives you the same answer as
246 $x = pdl([[1,2,3],[2,undef,undef]]);
248 If your PDL module has bad values compiled into it (see PDL::Bad), you
250 can pass BAD values into the constructor within pre-existing PDLs. The
251 BAD values are automatically kept BAD and propagated correctly.
252 pdl() is a functional synonym for the 'new' constructor, e.g.:
254 $x = PDL->new([1..10]);
256 In order to control how undefs are handled in converting from perl
258 lists to PDLs, one can set the variable $PDL::undefval. For example:
259 $foo = [[1,2,undef],[undef,3,4]];
261 $PDL::undefval = -999;
262 $f = pdl $foo;
263 print $f
264 [
265 [ 1 2 -999]
266 [-999 3 4]
267 ]
268 $PDL::undefval defaults to zero.
270 As a final note, if you include an Empty PDL in the list of objects to
272 construct into a PDL, it is kept as a placeholder pane -- so if you
273 feed in (say) 7 objects, you get a size of 7 in the 0th dim of the
274 output PDL. The placeholder panes are completely padded out. But if
275 you feed in only a single Empty PDL, you get back the Empty PDL (no
276 padding).
277 empty
279 Returns an empty ndarray, with a single zero-length dimension. Only
280 available as a function, not a method.
281 $x = empty; # defaults to lowest type so it can always be promoted up
283 $x = empty(float);
284 null
286 Returns a 'null' ndarray. It is an error to pass one of these as an
287 input to a function.
288 $x = null;
290 null() has a special meaning to PDL::PP. It is used to flag a special
292 kind of empty ndarray, which can grow to appropriate dimensions to
293 store a result (as opposed to storing a result in an existing ndarray).
294 pdl> sumover sequence(10,10), $ans=null;p $ans
296 [45 145 245 345 445 545 645 745 845 945]
297 nullcreate
299 Returns a 'null' ndarray.
300 $x = PDL->nullcreate($arg)
302 This is an routine used by many of the broadcasting primitives (i.e.
304 sumover, minimum, etc.) to generate a null ndarray for the function's
305 output that will behave properly for derived (or subclassed) PDL
306 objects.
307 For the above usage: If $arg is a PDL, or a derived PDL, then
309 "$arg->null" is returned. If $arg is a scalar (i.e. a zero-dimensional
310 PDL) then "PDL->null" is returned.
311 PDL::Derived->nullcreate(10)
313 returns PDL::Derived->null.
314 PDL->nullcreate($pdlderived)
315 returns $pdlderived->null.
316 nelem
318 Return the number of elements in an ndarray
319 $n = nelem($ndarray); $n = $ndarray->nelem;
321 $mean = sum($data)/nelem($data);
323 dims
325 Return ndarray dimensions as a perl list
326 @dims = $ndarray->dims; @dims = dims($ndarray);
328 pdl> p @tmp = dims zeroes 10,3,22
330 10 3 22
331 See also "shape" which returns an ndarray instead.
333 shape
335 Return ndarray dimensions as an ndarray
336 $shape = $ndarray->shape; $shape = shape($ndarray);
338 pdl> p $shape = shape zeroes 10,3,22
340 [10 3 22]
341 See also "dims" which returns a perl list.
343 ndims
345 Returns the number of dimensions in an ndarray. Alias for getndims.
346 getndims
348 Returns the number of dimensions in an ndarray
349 $ndims = $ndarray->getndims;
351 pdl> p zeroes(10,3,22)->getndims
353 3
354 dim
356 Returns the size of the given dimension of an ndarray. Alias for
357 getdim.
358 getdim
360 Returns the size of the given dimension.
361 $dim0 = $ndarray->getdim(0);
363 pdl> p zeroes(10,3,22)->getdim(1)
365 3
366 Negative indices count from the end of the dims array. Indices beyond
368 the end will return a size of 1. This reflects the idea that any pdl is
369 equivalent to an infinitely dimensional array in which only a finite
370 number of dimensions have a size different from one. For example, in
371 that sense a 3D ndarray of shape [3,5,2] is equivalent to a
372 [3,5,2,1,1,1,1,1,....] ndarray. Accordingly,
373 print $x->getdim(10000);
375 will print 1 for most practically encountered ndarrays.
377 topdl
379 alternate ndarray constructor - ensures arg is an ndarray
380 $x = topdl(SCALAR|ARRAY REFERENCE|ARRAY);
382 The difference between pdl() and topdl() is that the latter will just
384 'fall through' if the argument is already an ndarray. It will return a
385 reference and NOT a new copy.
386 This is particularly useful if you are writing a function which is
388 doing some fiddling with internals and assumes an ndarray argument
389 (e.g. for method calls). Using topdl() will ensure nothing breaks if
390 passed with '2'.
391 Note that topdl() is not exported by default (see example below for
393 usage).
394 use PDL::Core ':Internal'; # use the internal routines of
396 # the Core module
397 $x = topdl 43; # $x is ndarray with value '43'
399 $y = topdl $ndarray; # fall through
400 $x = topdl (1,2,3,4); # Convert 1D array
401 get_datatype
403 Internal: Return the numeric value identifying the ndarray datatype
404 $x = $ndarray->get_datatype;
406 Mainly used for internal routines.
408 NOTE: get_datatype returns 'just a number' not any special type object,
410 unlike "type".
411 howbig
413 Returns the sizeof an ndarray datatype in bytes.
414 Note that howbig() is not exported by default (see example below for
416 usage).
417 use PDL::Core ':Internal'; # use the internal routines of
419 # the Core module
420 $size = howbig($ndarray->get_datatype);
422 Mainly used for internal routines.
424 NOTE: NOT a method! This is because get_datatype returns 'just a
426 number' not any special object.
427 pdl> p howbig(ushort([1..10])->get_datatype)
429 2
430 get_dataref
432 Return the internal data for an ndarray, as a perl SCALAR ref.
433 Most ndarrays hold their internal data in a packed perl string, to take
435 advantage of perl's memory management. This gives you direct access to
436 the string, which is handy when you need to manipulate the binary data
437 directly (e.g. for file I/O). If you modify the string, you'll need to
438 call "upd_data" afterward, to make sure that the ndarray points to the
439 new location of the underlying perl variable.
440 Calling "get_dataref" automatically physicalizes your ndarray (see
442 "make_physical"). You definitely don't want to do anything to the SV
443 to truncate or deallocate the string, unless you correspondingly call
444 "reshape" to make the PDL match its new data dimension.
445 You definitely don't want to use get_dataref unless you know what you
447 are doing (or are trying to find out): you can end up scrozzling memory
448 if you shrink or eliminate the string representation of the variable.
449 Here be dragons.
450 upd_data
452 Update the data pointer in an ndarray to match its perl SV.
453 This is useful if you've been monkeying with the packed string
455 representation of the PDL, which you probably shouldn't be doing
456 anyway. (see "get_dataref".)
457 broadcastids
459 Returns the ndarray broadcast IDs as a perl list
460 Note that broadcastids() is not exported by default (see example below
462 for usage).
463 use PDL::Core ':Internal'; # use the internal routines of
465 # the Core module
466 @ids = broadcastids $ndarray;
468 doflow
470 Turn on dataflow, forward only. This means any transformations (a.k.a.
471 PDL operations) applied to this ndarray afterwards will have forward
472 dataflow:
473 $x = sequence 3;
475 $x->doflow;
476 $y = $x + 1;
477 $x += 3;
478 print "$y\n"; # [4 5 6]
479 As of 2.064, the core API does not automatically sever transformations
481 that have forward dataflow into them:
482 # following from the above
484 $y->set(1, 9); # value now [4 9 6]
485 $x += 11;
486 print "$y\n"; # [15 16 17] - previously would have been [4 9 6]
487 If you want to sever such transformations, call "sever" on the child
489 ndarray (above, $y).
490 $x->doflow; doflow($x);
492 flows
494 Whether or not an ndarray is indulging in dataflow
495 something if $x->flows; $hmm = flows($x);
497 new
499 new ndarray constructor method
500 $x = PDL->new(SCALAR|ARRAY|ARRAY REF|STRING);
502 $x = PDL->new(42); # new from a Perl scalar
504 $y = PDL->new(@list_of_vals); # new from Perl list
505 $z = PDL->new(\@list_of_vals); # new from Perl list reference
506 $w = PDL->new("[1 2 3]"); # new from Perl string, using
507 # Matlab constructor syntax
508 Constructs ndarray from perl numbers and lists and strings with
510 Matlab/Octave style constructor syntax.
511 The string input is fairly versatile though not performance optimized.
513 The goal is to make it easy to copy and paste code from PDL output and
514 to offer a familiar Matlab syntax for ndarray construction. As of May,
515 2010, it is a new feature, so feel free to report bugs or suggest new
516 features. See documentation for pdl for more examples of usage.
517 copy
519 Make a physical copy of an ndarray
520 $new = $old->copy;
522 Since "$new = $old" just makes a new reference, the "copy" method is
524 provided to allow real independent copies to be made.
525 hdr_copy
527 Return an explicit copy of the header of a PDL.
528 hdr_copy is just a wrapper for the internal routine _hdr_copy, which
530 takes the hash ref itself. That is the routine which is used to make
531 copies of the header during normal operations if the hdrcpy() flag of a
532 PDL is set.
533 General-purpose deep copies are expensive in perl, so some simple
535 optimization happens:
536 If the header is a tied array or a blessed hash ref with an associated
538 method called "copy", then that ->copy method is called. Otherwise,
539 all elements of the hash are explicitly copied. References are
540 recursively deep copied.
541 This routine seems to leak memory.
543 unwind
545 Return an ndarray which is the same as the argument except that all
546 broadcastids have been removed.
547 $y = $x->unwind;
549 make_physical
551 Make sure the data portion of an ndarray can be accessed from XS code.
552 $x->make_physical;
554 $x->call_my_xs_method;
555 Ensures that an ndarray gets its own allocated copy of data. This
557 obviously implies that there are certain ndarrays which do not have
558 their own data. These are so called virtual ndarrays that make use of
559 the vaffine optimisation (see PDL::Indexing). They do not have their
560 own copy of data but instead store only access information to some (or
561 all) of another ndarray's data.
562 Note: this function should not be used unless absolutely necessary
564 since otherwise memory requirements might be severely increased.
565 Instead of writing your own XS code with the need to call
566 "make_physical" you might want to consider using the PDL preprocessor
567 (see PDL::PP) which can be used to transparently access virtual
568 ndarrays without the need to physicalise them (though there are
569 exceptions).
570 dummy
572 Insert a 'dummy dimension' of given length (defaults to 1)
573 No relation to the 'Dungeon Dimensions' in Discworld!
575 Negative positions specify relative to last dimension, i.e. dummy(-1)
577 appends one dimension at end, dummy(-2) inserts a dummy dimension in
578 front of the last dim, etc.
579 If you specify a dimension position larger than the existing dimension
581 list of your PDL, the PDL gets automagically padded with extra dummy
582 dimensions so that you get the dim you asked for, in the slot you asked
583 for. This could cause you trouble if, for example, you ask for
584 $x->dummy(5000,1) because $x will get 5,000 dimensions, each of rank 1.
585 Because padding at the beginning of the dimension list moves existing
587 dimensions from slot to slot, it's considered unsafe, so automagic
588 padding doesn't work for large negative indices -- only for large
589 positive indices.
590 $y = $x->dummy($position[,$dimsize]);
592 pdl> p sequence(3)->dummy(0,3)
594 [
595 [0 0 0]
596 [1 1 1]
597 [2 2 2]
598 ]
599 pdl> p sequence(3)->dummy(3,2)
601 [
602 [
603 [0 1 2]
604 ]
605 [
606 [0 1 2]
607 ]
608 ]
609 pdl> p sequence(3)->dummy(-3,2)
611 Runtime error: PDL: For safety, <pos> < -(dims+1) forbidden in dummy. min=-2, pos=-3
612 dup
614 Duplicates an ndarray along a dimension
615 $x = sequence(3);
617 $y = $x->dup(0, 2); # doubles along first dimension
618 # $y now [0 1 2 0 1 2]
619 dupN
621 Duplicates an ndarray along several dimensions
622 $x = sequence(3,2);
624 $y = $x->dupN(2, 3); # doubles along first dimension, triples along second
625 # [
626 # [0 1 2 0 1 2]
627 # [3 4 5 3 4 5]
628 # [0 1 2 0 1 2]
629 # [3 4 5 3 4 5]
630 # ]
631 inflateN
633 Inflates an ndarray along several dimensions, useful for e.g. Kronecker
634 products
635 cf "dupN"
637 $x = sequence(3,2);
639 $y = $x->inflateN(2, 2); # doubles along first two dimensions
640 # [
641 # [0 0 1 1 2 2]
642 # [0 0 1 1 2 2]
643 # [3 3 4 4 5 5]
644 # [3 3 4 4 5 5]
645 # ]
646 clump
648 "clumps" several dimensions into one large dimension
649 If called with one argument $n clumps the first $n dimensions into one.
651 For example, if $x has dimensions "(5,3,4)" then after
652 $y = $x->clump(2); # Clump 2 first dimensions
654 the variable $y will have dimensions "(15,4)" and the element
656 "$y->at(7,3)" refers to the element "$x->at(1,2,3)".
657 Use clump(-1) to flatten an ndarray. The method flat is provided as a
659 convenient alias.
660 Clumping with a negative dimension in general leaves that many
662 dimensions behind -- e.g. clump(-2) clumps all of the first few
663 dimensions into a single one, leaving a 2-D ndarray.
664 If "clump" is called with an index list with more than one element it
666 is treated as a list of dimensions that should be clumped together into
667 one. The resulting clumped dim is placed at the position of the lowest
668 index in the list. This convention ensures that "clump" does the
669 expected thing in the usual cases. The following example demonstrates
670 typical usage:
671 $x = sequence 2,3,3,3,5; # 5D ndarray
673 $c = $x->clump(1..3); # clump all the dims 1 to 3 into one
674 print $c->info; # resulting 3D ndarray has clumped dim at pos 1
675 PDL: Double D [2,27,5]
676 broadcast_define
678 define functions that support broadcasting at the perl level
679 broadcast_define 'tline(a(n);b(n))', over {
681 line $_[0], $_[1]; # make line compliant with broadcasting
682 };
683 "broadcast_define" provides some support for broadcasting (see
685 PDL::Indexing) at the perl level. It allows you to do things for which
686 you normally would have resorted to PDL::PP (see PDL::PP); however, it
687 is most useful to wrap existing perl functions so that the new routine
688 supports PDL broadcasting.
689 "broadcast_define" is used to define new broadcasting aware functions.
691 Its first argument is a symbolic repesentation of the new function to
692 be defined. The string is composed of the name of the new function
693 followed by its signature (see PDL::Indexing and PDL::PP) in
694 parentheses. The second argument is a subroutine that will be called
695 with the slices of the actual runtime arguments as specified by its
696 signature. Correct dimension sizes and minimal number of dimensions for
697 all arguments will be checked (assuming the rules of PDL broadcasting,
698 see PDL::Indexing).
699 The actual work is done by the "signature" class which parses the
701 signature string, does runtime dimension checks and the routine
702 "broadcastover" that generates the loop over all appropriate slices of
703 pdl arguments and creates pdls as needed.
704 Similar to "pp_def" and its "OtherPars" option it is possible to define
706 the new function so that it accepts normal perl args as well as
707 ndarrays. You do this by using the "NOtherPars" parameter in the
708 signature. The number of "NOtherPars" specified will be passed
709 unaltered into the subroutine given as the second argument of
710 "broadcast_define". Let's illustrate this with an example:
711 PDL::broadcast_define 'triangles(inda();indb();indc()), NOtherPars => 2',
713 PDL::over {
714 ${$_[3]} .= $_[4].join(',',map {$_->at} @_[0..2]).",-1,\n";
715 };
716 This defines a function "triangles" that takes 3 ndarrays as input plus
718 2 arguments which are passed into the routine unaltered. This routine
719 is used to collect lists of indices into a perl scalar that is passed
720 by reference. Each line is preceded by a prefix passed as $_[4]. Here
721 is typical usage:
722 $txt = '';
724 triangles(pdl(1,2,3),pdl(1),pdl(0),\$txt," "x10);
725 print $txt;
726 resulting in the following output
728 1,1,0,-1,
730 2,1,0,-1,
731 3,1,0,-1,
732 which is used in PDL::Graphics::TriD::VRML to generate VRML output.
734 Currently, this is probably not much more than a POP (proof of
736 principle) but is hoped to be useful enough for some real life work.
737 Check PDL::PP for the format of the signature. Currently, the "[t]"
739 qualifier and all type qualifiers are ignored.
740 broadcast
742 Use explicit broadcasting over specified dimensions (see also
743 PDL::Indexing)
744 $y = $x->broadcast($dim,[$dim1,...])
746 $x = zeroes 3,4,5;
748 $y = $x->broadcast(2,0);
749 Same as "broadcast1", i.e. uses broadcast id 1.
751 broadcast1
753 Explicit broadcasting over specified dims using broadcast id 1.
754 $xx = $x->broadcast1(3,1)
756 Wibble
758 Convenience function interfacing to PDL::Slices::broadcastI.
760 broadcast2
762 Explicit broadcasting over specified dims using broadcast id 2.
763 $xx = $x->broadcast2(3,1)
765 Wibble
767 Convenience function interfacing to PDL::Slices::broadcastI.
769 broadcast3
771 Explicit broadcasting over specified dims using broadcast id 3.
772 $xx = $x->broadcast3(3,1)
774 Wibble
776 Convenience function interfacing to PDL::Slices::broadcastI.
778 sever
780 sever any links of this ndarray to parent ndarrays
781 In PDL it is possible for an ndarray to be just another view into
783 another ndarray's data. In that case we call this ndarray a virtual
784 ndarray and the original ndarray owning the data its parent. In other
785 languages these alternate views sometimes run by names such as alias or
786 smart reference.
787 Typical functions that return such ndarrays are "slice", "xchg",
789 "index", etc. Sometimes, however, you would like to separate the
790 virtual ndarray from its parent's data and just give it a life of its
791 own (so that manipulation of its data doesn't change the parent). This
792 is simply achieved by using "sever". For example,
793 $x = $pdl->index(pdl(0,3,7))->sever;
795 $x++; # important: $pdl is not modified!
796 In many (but not all) circumstances it acts therefore similar to copy.
798 However, in general performance is better with "sever" and secondly,
799 "sever" doesn't lead to futile copying when used on ndarrays that
800 already have their own data. On the other hand, if you really want to
801 make sure to work on a copy of an ndarray use copy.
802 $x = zeroes(20);
804 $x->sever; # NOOP since $x is already its own boss!
805 Again note: "sever" is not the same as copy! For example,
807 $x = zeroes(1); # $x does not have a parent, i.e. it is not a slice etc
809 $y = $x->sever; # $y is now pointing to the same ndarray as $x
810 $y++;
811 print $x;
812 [1]
813 but
815 $x = zeroes(1);
817 $y = $x->copy; # $y is now pointing to a new ndarray
818 $y++;
819 print $x;
820 [0]
821 info
823 Return formatted information about an ndarray.
824 $x->info($format_string);
826 print $x->info("Type: %T Dim: %-15D State: %S");
828 Returns a string with info about an ndarray. Takes an optional argument
830 to specify the format of information a la sprintf. Format specifiers
831 are in the form "%<width><letter>" where the width is optional and the
832 letter is one of
833 T Type
835 D Formatted Dimensions
837 F Dataflow status
839 S Some internal flags (P=physical,V=Vaffine,C=changed,B=may
841 contain bad data)
842 C Class of this ndarray, i.e. "ref $pdl"
844 A Address of the ndarray struct as a unique identifier
846 M Calculated memory consumption of this ndarray's data area
848 approx
850 test for approximately equal values (relaxed "==")
851 # ok if all corresponding values in
853 # ndarrays are within 1e-8 of each other
854 print "ok\n" if all approx $x, $y, 1e-8;
855 "approx" is a relaxed form of the "==" operator and often more
857 appropriate for floating point types ("float" and "double").
858 Usage:
860 $res = approx $x, $y [, $eps]
862 The optional parameter $eps is remembered across invocations and
864 initially set to 1e-6, e.g.
865 approx $x, $y; # last $eps used (1e-6 initially)
867 approx $x, $y, 1e-10; # 1e-10
868 approx $x, $y; # also 1e-10
869 mslice
871 Alias to "slice" in PDL::Slices.
872 nslice_if_pdl
874 If $self is a PDL, then calls "slice" with all but the last argument,
875 otherwise $self->($_[-1]) is called where $_[-1} is the original
876 argument string found during PDL::NiceSlice filtering.
877 DEVELOPER'S NOTE: this routine is found in Core.pm.PL but would be
879 better placed in Slices/slices.pd. It is likely to be moved there
880 and/or changed to "slice_if_pdl" for PDL 3.0.
881 $w = $x->nslice_if_pdl(...,'(args)');
883 inplace
885 Flag an ndarray so that the next operation is done 'in place'
886 somefunc($x->inplace); somefunc(inplace $x);
888 In most cases one likes to use the syntax "$y = f($x)", however in many
890 case the operation f() can be done correctly 'in place', i.e. without
891 making a new copy of the data for output. To make it easy to use this,
892 we write f() in such a way that it operates in-place, and use "inplace"
893 to hint that a new copy should be disabled. This also makes for clear
894 syntax.
895 Obviously this will not work for all functions, and if in doubt see the
897 function's documentation. However one can assume this is true for all
898 elemental functions (i.e. those which just operate array element by
899 array element like "log10").
900 pdl> $x = xvals zeroes 10;
902 pdl> log10(inplace $x)
903 pdl> p $x
904 [-inf 0 0.30103 0.47712125 0.60205999 0.69897 0.77815125 0.84509804 0.90308999 0.95424251]
905 is_inplace
907 Test the in-place flag on an ndarray
908 $out = ($in->is_inplace) ? $in : zeroes($in);
910 $in->set_inplace(0)
911 Provides access to the "inplace" hint flag, within the perl milieu.
913 That way functions you write can be inplace aware... If given an
914 argument the inplace flag will be set or unset depending on the value
915 at the same time. Can be used for shortcut tests that delete the
916 inplace flag while testing:
917 $out = ($in->is_inplace(0)) ? $in : zeroes($in); # test & unset!
919 set_inplace
921 Set the in-place flag on an ndarray
922 $out = ($in->is_inplace) ? $in : zeroes($in);
924 $in->set_inplace(0);
925 Provides access to the "inplace" hint flag, within the perl milieu.
927 Useful mainly for turning it OFF, as "inplace" turns it ON more
928 conveniently.
929 new_or_inplace
931 $w = new_or_inplace(shift());
932 $w = new_or_inplace(shift(),$preferred_type);
933 Return back either the argument pdl or a copy of it depending on
935 whether it be flagged in-place or no. Handy for building inplace-aware
936 functions.
937 If you specify a preferred type (must be one of the usual PDL type
939 strings, a list ref containing several of them, or a comma-separated
940 string containing several of them), then the copy is coerced into the
941 first preferred type listed if it is not already one of the preferred
942 types.
943 Note that if the inplace flag is set, no coercion happens even if you
945 specify a preferred type.
946 new_from_specification
948 Internal method: create ndarray by specification
949 This is the argument processing method called by "zeroes" and some
951 other functions which constructs ndarrays from argument lists of the
952 form:
953 [type], $nx, $ny, $nz,...
955 For $nx, $ny, etc. 0 and 1D ndarrays are allowed. Giving those has the
957 same effect as if saying "$arg->list", e.g.
958 1, pdl(5,2), 4
960 is equivalent to
962 1, 5, 2, 4
964 Note, however, that in all functions using "new_from_specification"
966 calling "func $ndarray" will probably not do what you want. So to play
967 safe use (e.g. with zeroes)
968 $pdl = zeroes $dimpdl->list;
970 Calling
972 $pdl = zeroes $dimpdl;
974 will rather be equivalent to
976 $pdl = zeroes $dimpdl->dims;
978 However,
980 $pdl = zeroes ushort, $dimpdl;
982 will again do what you intended since it is interpreted as if you had
984 said
985 $pdl = zeroes ushort, $dimpdl->list;
987 This is unfortunate and confusing but no good solution seems obvious
989 that would not break existing scripts.
990 isnull
992 Test whether an ndarray is null
993 croak("Input ndarray mustn't be null!")
995 if $input_ndarray->isnull;
996 This function returns 1 if the ndarray is null, zero if it is not. The
998 purpose of null ndarrays is to "tell" any PDL::PP methods to allocate
999 new memory for an output ndarray, but only when that PDL::PP method is
1000 called in full-arg form. Of course, there's no reason you couldn't
1001 commandeer the special value for your own purposes, for which this test
1002 function would prove most helpful. But in general, you shouldn't need
1003 to test for an ndarray's nullness.
1004 See "Null PDLs" for more information.
1006 isempty
1008 Test whether an ndarray is empty
1009 print "The ndarray has zero dimension\n" if $pdl->isempty;
1011 This function returns 1 if the ndarray has zero elements. This is
1013 useful in particular when using the indexing function which. In the
1014 case of no match to a specified criterion, the returned ndarray has
1015 zero dimension.
1016 pdl> $w=sequence(10)
1018 pdl> $i=which($w < -1)
1019 pdl> print "I found no matches!\n" if ($i->isempty);
1020 I found no matches!
1021 Note that having zero elements is rather different from the concept of
1023 being a null ndarray, see the PDL::FAQ and PDL::Indexing manpages for
1024 discussions of this.
1025 zeroes
1027 construct a zero filled ndarray from dimension list or template
1028 ndarray. If called with no arguments, returns a zero-dimension ndarray
1029 (a scalar).
1030 Various forms of usage,
1032 (i) by specification or (ii) by template ndarray:
1034 # usage type (i):
1036 $w = zeroes([type], $nx, $ny, $nz,...);
1037 $w = PDL->zeroes([type], $nx, $ny, $nz,...);
1038 $w = $pdl->zeroes([type], $nx, $ny, $nz,...); # all info about $pdl ignored
1039 # usage type (ii):
1040 $w = zeroes $y;
1041 $w = $y->zeroes
1042 zeroes inplace $w; # Equivalent to $w .= 0;
1043 $w->inplace->zeroes; # ""
1044 pdl> $z = zeroes 4,3
1046 pdl> p $z
1047 [
1048 [0 0 0 0]
1049 [0 0 0 0]
1050 [0 0 0 0]
1051 ]
1052 pdl> $z = zeroes ushort, 3,2 # Create ushort array
1053 [ushort() etc. with no arg returns a PDL::Types token]
1054 See also "new_from_specification" for details on using ndarrays in the
1056 dimensions list.
1057 zeros
1059 construct a zero filled ndarray (see zeroes for usage)
1060 ones
1062 construct a one filled ndarray. If called with no arguments, returns a
1063 zero-dimension ndarray (a scalar).
1064 $w = ones([type], $nx, $ny, $nz,...);
1066 etc. (see 'zeroes')
1067 see zeroes() and add one
1069 See also "new_from_specification" for details on using ndarrays in the
1071 dimensions list.
1072 nan
1074 construct a "NaN" filled ndarray. If called with no arguments, returns
1075 a zero-dimension ndarray (a scalar).
1076 $w = nan([type], $nx, $ny, $nz,...);
1078 etc. (see 'zeroes')
1079 see zeroes() and add NaN
1081 See also "new_from_specification" for details on using ndarrays in the
1083 dimensions list.
1084 inf
1086 construct an "Inf" filled ndarray. If called with no arguments,
1087 returns a zero-dimension ndarray (a scalar).
1088 $w = inf([type], $nx, $ny, $nz,...);
1090 etc. (see 'zeroes')
1091 see zeroes() and add Inf
1093 See also "new_from_specification" for details on using ndarrays in the
1095 dimensions list.
1096 i
1098 construct an ndarray filled with a native complex value equal to the
1099 imaginary number "i", the square root of -1. If called with no
1100 arguments, returns a zero-dimension ndarray (a scalar).
1101 $w = i([type], $nx, $ny, $nz,...);
1103 etc. (see 'zeroes')
1104 see zeroes() and add "i"
1106 See also "new_from_specification" for details on using ndarrays in the
1108 dimensions list.
1109 reshape
1111 Change the shape (i.e. dimensions) of an ndarray, preserving contents.
1112 $x->reshape(NEWDIMS); reshape($x, NEWDIMS);
1114 The data elements are preserved, obviously they will wrap differently
1116 and get truncated if the new array is shorter. If the new array is
1117 longer it will be zero-padded.
1118 ***Potential incompatibility with earlier versions of PDL**** If the
1120 list of "NEWDIMS" is empty "reshape" will just drop all dimensions of
1121 size 1 (preserving the number of elements):
1122 $w = sequence(3,4,5);
1124 $y = $w(1,3);
1125 $y->reshape();
1126 print $y->info;
1127 PDL: Double D [5]
1128 Dimensions of size 1 will also be dropped if "reshape" is invoked with
1130 the argument -1:
1131 $y = $w->reshape(-1);
1133 As opposed to "reshape" without arguments, reshape(-1) preserves
1135 dataflow:
1136 $w = ones(2,1,2);
1138 $y = $w(0)->reshape(-1);
1139 $y++;
1140 print $w;
1141 [
1142 [
1143 [2 1]
1144 ]
1145 [
1146 [2 1]
1147 ]
1148 ]
1149 Important: ndarrays are changed inplace!
1151 Note: If $x is connected to any other PDL (e.g. if it is a slice) then
1153 the connection is first severed.
1154 pdl> $x = sequence(10)
1156 pdl> reshape $x,3,4; p $x
1157 [
1158 [0 1 2]
1159 [3 4 5]
1160 [6 7 8]
1161 [9 0 0]
1162 ]
1163 pdl> reshape $x,5; p $x
1164 [0 1 2 3 4]
1165 squeeze
1167 eliminate all singleton dimensions (dims of size 1)
1168 $y = $w(0,0)->squeeze;
1170 Alias for reshape(-1). Removes all singleton dimensions and preserves
1172 dataflow. A more concise interface is provided by PDL::NiceSlice via
1173 modifiers:
1174 use PDL::NiceSlice;
1176 $y = $w(0,0;-); # same as $w(0,0)->squeeze
1177 flat
1179 flatten an ndarray (alias for "$pdl->clump(-1)")
1180 $srt = $pdl->flat->qsort;
1182 Useful method to make a 1D ndarray from an arbitrarily sized input
1184 ndarray. Data flows back and forth as usual with slicing routines.
1185 Falls through if argument already <= 1D.
1186 convert
1188 Generic datatype conversion function
1189 $y = convert($x, $newtype);
1191 $newtype is a type number or PDL::Type object, for convenience they are
1193 returned by long() etc when called without arguments.
1194 $y = convert $x, long;
1196 $y = convert $x, ushort;
1197 Datatype_conversions
1199 sbyte|byte|short|ushort|long|ulong|indx|longlong|ulonglong|float|double|ldouble|cfloat|cdouble|cldouble
1200 (shorthands to convert datatypes)
1201 $y = double $x; $y = ushort [1..10];
1203 # all of the above listed shorthands behave similarly
1204 When called with an ndarray argument, they convert to the specific
1206 datatype.
1207 When called with a numeric, list, listref, or string argument they
1209 construct a new ndarray. This is a convenience to avoid having to be
1210 long-winded and say "$x = long(pdl(42))"
1211 Thus one can say:
1213 $w = float(1,2,3,4); # 1D
1215 $w = float q[1 2 3; 4 5 6]; # 2D
1216 $w = float([1,2,3],[4,5,6]); # 2D
1217 $w = float([[1,2,3],[4,5,6]]); # 2D
1218 Note the last three give identical results, and the last two are
1220 exactly equivalent - a list is automatically converted to a list
1221 reference for syntactic convenience. i.e. you can omit the outer "[]"
1222 When called with no arguments, these functions return a special type
1224 token. This allows syntactical sugar like:
1225 $x = ones byte, 1000,1000;
1227 This example creates a large ndarray directly as byte datatype in order
1229 to save memory.
1230 In order to control how undefs are handled in converting from perl
1232 lists to PDLs, one can set the variable $PDL::undefval; see the
1233 function pdl() for more details.
1234 pdl> p $x=sqrt float [1..10]
1236 [1 1.41421 1.73205 2 2.23607 2.44949 2.64575 2.82843 3 3.16228]
1237 pdl> p byte $x
1238 [1 1 1 2 2 2 2 2 3 3]
1239 byte
1241 Convert to byte datatype
1242 short
1244 Convert to short datatype
1245 ushort
1247 Convert to ushort datatype
1248 long
1250 Convert to long datatype
1251 indx
1253 Convert to indx datatype
1254 longlong
1256 Convert to longlong datatype
1257 float
1259 Convert to float datatype
1260 double
1262 Convert to double datatype
1263 cfloat
1265 Convert to complex float datatype
1266 cdouble
1268 Convert to complex double datatype
1269 type
1271 return the type of an ndarray as a blessed type object
1272 A convenience function for use with the ndarray constructors, e.g.
1274 $y = PDL->zeroes($x->type,$x->dims,3);
1276 die "must be float" unless $x->type == float;
1277 See also the discussion of the "PDL::Type" class in PDL::Types. Note
1279 that the "PDL::Type" objects have overloaded comparison and stringify
1280 operators so that you can compare and print types:
1281 $x = $x->float if $x->type < float;
1283 $t = $x->type; print "Type is $t\n";
1284 list
1286 Convert ndarray to perl list
1287 @tmp = list $x;
1289 Obviously this is grossly inefficient for the large datasets PDL is
1291 designed to handle. This was provided as a get out while PDL matured.
1292 It should now be mostly superseded by superior constructs, such as
1293 PP/broadcasting. However it is still occasionally useful and is
1294 provided for backwards compatibility.
1295 for (list $x) {
1297 # Do something on each value...
1298 }
1299 list converts any bad values into the string 'BAD'.
1301 unpdl
1303 Convert ndarray to nested Perl array references
1304 $arrayref = unpdl $x;
1306 This function returns a reference to a Perl list-of-lists structure
1308 equivalent to the input ndarray (within the limitation that while
1309 values of elements should be preserved, the detailed datatypes will not
1310 as perl itself basically has "number" data rather than byte, short,
1311 int... E.g., "sum($x - pdl( $x->unpdl ))" should equal 0.
1312 Obviously this is grossly inefficient in memory and processing for the
1314 large datasets PDL is designed to handle. Sometimes, however, you
1315 really want to move your data back to Perl, and with proper
1316 dimensionality, unlike "list".
1317 If you want to round-trip data including the use of "PDL::undefval",
1319 "unpdl" does not support this. However, it is suggested you would
1320 generate an index-set with "$pdl->whereND($pdl == $PDL::undefval)",
1321 then loop over the Perl data, setting those locations to "undef".
1322 use JSON;
1324 my $json = encode_json unpdl $pdl;
1325 unpdl converts any bad values into the string 'BAD'.
1327 listindices
1329 Convert ndarray indices to perl list
1330 @tmp = listindices $x;
1332 @tmp now contains the values "0..nelem($x)".
1334 Obviously this is grossly inefficient for the large datasets PDL is
1336 designed to handle. This was provided as a get out while PDL matured.
1337 It should now be mostly superseded by superior constructs, such as
1338 PP/broadcasting. However it is still occasionally useful and is provied
1339 for backwards compatibility.
1340 for $i (listindices $x) {
1342 # Do something on each value...
1343 }
1344 set
1346 Set a single value inside an ndarray
1347 set $ndarray, @position, $value
1349 @position is a coordinate list, of size equal to the number of
1351 dimensions in the ndarray. Occasionally useful, mainly provided for
1352 backwards compatibility as superseded by use of slice and assignment
1353 operator ".=".
1354 pdl> $x = sequence 3,4
1356 pdl> set $x, 2,1,99
1357 pdl> p $x
1358 [
1359 [ 0 1 2]
1360 [ 3 4 99]
1361 [ 6 7 8]
1362 [ 9 10 11]
1363 ]
1364 at
1366 Returns a single value inside an ndarray as perl scalar. If the
1367 ndarray is a native complex value (cdouble, cfloat), it will be a
1368 PDL::Complex::Overloads object.
1369 $z = at($ndarray, @position); $z=$ndarray->at(@position);
1371 @position is a coordinate list, of size equal to the number of
1373 dimensions in the ndarray. Occasionally useful in a general context,
1374 quite useful too inside PDL internals.
1375 pdl> $x = sequence 3,4
1377 pdl> p $x->at(1,2)
1378 7
1379 at converts any bad values into the string 'BAD'.
1381 sclr
1383 return a single value from an ndarray as a scalar, ignoring whether it
1384 is bad.
1385 $val = $x(10)->sclr;
1387 $val = sclr inner($x,$y);
1388 The "sclr" method is useful to turn a single-element ndarray into a
1390 normal Perl scalar. Its main advantage over using "at" for this purpose
1391 is the fact that you do not need to worry if the ndarray is 0D, 1D or
1392 higher dimensional. Using "at" you have to supply the correct number
1393 of zeroes, e.g.
1394 $x = sequence(10);
1396 $y = $x->slice('4');
1397 print $y->sclr; # no problem
1398 print $y->at(); # error: needs at least one zero
1399 "sclr" is generally used when a Perl scalar is required instead of a
1401 one-element ndarray. As of 2.064, if the input is a multielement
1402 ndarray it will throw an exception.
1403 cat
1405 concatenate ndarrays to N+1 dimensional ndarray
1406 Takes a list of N ndarrays of same shape as argument, returns a single
1408 ndarray of dimension N+1.
1409 pdl> $x = cat ones(3,3),zeroes(3,3),rvals(3,3); p $x
1411 [
1412 [
1413 [1 1 1]
1414 [1 1 1]
1415 [1 1 1]
1416 ]
1417 [
1418 [0 0 0]
1419 [0 0 0]
1420 [0 0 0]
1421 ]
1422 [
1423 [1 1 1]
1424 [1 0 1]
1425 [1 1 1]
1426 ]
1427 ]
1428 The output ndarray is set bad if any input ndarrays have their bad flag
1430 set.
1431 Similar functions include append, which appends only two ndarrays along
1433 their first dimension, and glue, which can append more than two
1434 ndarrays along an arbitrary dimension.
1435 Also consider the generic constructor "pdl", which can handle ndarrays
1437 of different sizes (with zero-padding), and will return a ndarray of
1438 type 'double' by default, but may be considerably faster (up to 10x)
1439 than cat.
1440 dog
1442 Opposite of 'cat' :). Split N dim ndarray to list of N-1 dim ndarrays
1443 Takes a single N-dimensional ndarray and splits it into a list of N-1
1445 dimensional ndarrays. The breakup is done along the last dimension.
1446 Note the dataflowed connection is still preserved by default, e.g.:
1447 pdl> $p = ones 3,3,3
1449 pdl> ($x,$y,$c) = dog $p
1450 pdl> $y++; p $p
1451 [
1452 [
1453 [1 1 1]
1454 [1 1 1]
1455 [1 1 1]
1456 ]
1457 [
1458 [2 2 2]
1459 [2 2 2]
1460 [2 2 2]
1461 ]
1462 [
1463 [1 1 1]
1464 [1 1 1]
1465 [1 1 1]
1466 ]
1467 ]
1468 Break => 1 Break dataflow connection (new copy)
1470 The output ndarrays are set bad if the original ndarray has its bad
1472 flag set.
1473 gethdr
1475 Retrieve header information from an ndarray
1476 $pdl=rfits('file.fits');
1478 $h=$pdl->gethdr;
1479 print "Number of pixels in the X-direction=$$h{NAXIS1}\n";
1480 The "gethdr" function retrieves whatever header information is
1482 contained within an ndarray. The header can be set with "sethdr" and is
1483 always a hash reference or undef.
1484 "gethdr" returns undef if the ndarray has not yet had a header defined;
1486 compare with "hdr" and "fhdr", which are guaranteed to return a defined
1487 value.
1488 Note that gethdr() works by reference: you can modify the header in-
1490 place once it has been retrieved:
1491 $x = rfits($filename);
1493 $xh = $x->gethdr();
1494 $xh->{FILENAME} = $filename;
1495 It is also important to realise that in most cases the header is not
1497 automatically copied when you copy the ndarray. See "hdrcpy" to enable
1498 automatic header copying.
1499 Here's another example: a wrapper around rcols that allows your ndarray
1501 to remember the file it was read from and the columns could be easily
1502 written (here assuming that no regexp is needed, extensions are left as
1503 an exercise for the reader)
1504 sub ext_rcols {
1506 my ($file, @columns)=@_;
1507 my $header={};
1508 $$header{File}=$file;
1509 $$header{Columns}=\@columns;
1510 @ndarrays=rcols $file, @columns;
1512 foreach (@ndarrays) { $_->sethdr($header); }
1513 return @ndarrays;
1514 }
1515 hdr
1517 Retrieve or set header information from an ndarray
1518 $pdl->hdr->{CDELT1} = 1;
1520 The "hdr" function allows convenient access to the header of a ndarray.
1522 Unlike "gethdr" it is guaranteed to return a defined value, so you can
1523 use it in a hash dereference as in the example. If the header does not
1524 yet exist, it gets autogenerated as an empty hash.
1525 Note that this is usually -- but not always -- What You Want. If you
1527 want to use a tied Astro::FITS::Header hash, for example, you should
1528 either construct it yourself and use "sethdr" to put it into the
1529 ndarray, or use "fhdr" instead. (Note that you should be able to write
1530 out the FITS file successfully regardless of whether your PDL has a
1531 tied FITS header object or a vanilla hash).
1532 fhdr
1534 Retrieve or set FITS header information from an ndarray
1535 $pdl->fhdr->{CDELT1} = 1;
1537 The "fhdr" function allows convenient access to the header of a
1539 ndarray. Unlike "gethdr" it is guaranteed to return a defined value,
1540 so you can use it in a hash dereference as in the example. If the
1541 header does not yet exist, it gets autogenerated as a tied
1542 Astro::FITS::Header hash.
1543 Astro::FITS::Header tied hashes are better at matching the behavior of
1545 FITS headers than are regular hashes. In particular, the hash keys are
1546 CAsE INsEnSItiVE, unlike normal hash keys. See Astro::FITS::Header for
1547 details.
1548 If you do not have Astro::FITS::Header installed, you get back a normal
1550 hash instead of a tied object.
1551 sethdr
1553 Set header information of an ndarray
1554 $pdl = zeroes(100,100);
1556 $h = {NAXIS=>2, NAXIS1=>100, NAXIS=>100, COMMENT=>"Sample FITS-style header"};
1557 # add a FILENAME field to the header
1558 $$h{FILENAME} = 'file.fits';
1559 $pdl->sethdr( $h );
1560 The "sethdr" function sets the header information for an ndarray. You
1562 must feed in a hash ref or undef, and the header field of the PDL is
1563 set to be a new ref to the same hash (or undefined).
1564 The hash ref requirement is a speed bump put in place since the normal
1566 use of headers is to store fits header information and the like. Of
1567 course, if you want you can hang whatever ugly old data structure you
1568 want off of the header, but that makes life more complex.
1569 Remember that the hash is not copied -- the header is made into a ref
1571 that points to the same underlying data. To get a real copy without
1572 making any assumptions about the underlying data structure, you can use
1573 one of the following:
1574 use PDL::IO::Dumper;
1576 $pdl->sethdr( deep_copy($h) );
1577 (which is slow but general), or
1579 $pdl->sethdr( PDL::_hdr_copy($h) )
1581 (which uses the built-in sleazy deep copier), or (if you know that all
1583 the elements happen to be scalars):
1584 { my %a = %$h;
1586 $pdl->sethdr(\%a);
1587 }
1588 which is considerably faster but just copies the top level.
1590 The "sethdr" function must be given a hash reference or undef. For
1592 further information on the header, see "gethdr", "hdr", "fhdr" and
1593 "hdrcpy".
1594 hdrcpy
1596 switch on/off/examine automatic header copying
1597 print "hdrs will be copied" if $x->hdrcpy;
1599 $x->hdrcpy(1); # switch on automatic header copying
1600 $y = $x->sumover; # and $y will inherit $x's hdr
1601 $x->hdrcpy(0); # and now make $x non-infectious again
1602 "hdrcpy" without an argument just returns the current setting of the
1604 flag. See also "hcpy" which returns its PDL argument (and so is useful
1605 in method-call pipelines).
1606 Normally, the optional header of an ndarray is not copied automatically
1608 in pdl operations. Switching on the hdrcpy flag using the "hdrcpy"
1609 method will enable automatic hdr copying. Note that an actual deep copy
1610 gets made, which is rather processor-inefficient -- so avoid using
1611 header copying in tight loops!
1612 Most PDLs have the "hdrcpy" flag cleared by default; however, some
1614 routines (notably rfits) set it by default where that makes more sense.
1615 The "hdrcpy" flag is viral: if you set it for a PDL, then derived PDLs
1617 will get copies of the header and will also have their "hdrcpy" flags
1618 set. For example:
1619 $x = xvals(50,50);
1621 $x->hdrcpy(1);
1622 $x->hdr->{FOO} = "bar";
1623 $y = $x++;
1624 $c = $y++;
1625 print $y->hdr->{FOO}, " - ", $c->hdr->{FOO}, "\n";
1626 $y->hdr->{FOO} = "baz";
1627 print $x->hdr->{FOO}, " - ", $y->hdr->{FOO}, " - ", $c->hdr->{FOO}, "\n";
1628 will print:
1630 bar - bar
1632 bar - baz - bar
1633 Performing an operation in which more than one PDL has its hdrcpy flag
1635 causes the resulting PDL to take the header of the first PDL:
1636 ($x,$y) = sequence(5,2)->dog;
1638 $x->hdrcpy(1); $y->hdrcpy(1);
1639 $x->hdr->{foo} = 'a';
1640 $y->hdr->{foo} = 'b';
1641 print (($x+$y)->hdr->{foo} , ($y+$x)->hdr->{foo});
1642 will print:
1644 a b
1646 hcpy
1648 Switch on/off automatic header copying, with PDL pass-through
1649 $x = rfits('foo.fits')->hcpy(0);
1651 $x = rfits('foo.fits')->hcpy(1);
1652 "hcpy" sets or clears the hdrcpy flag of a PDL, and returns the PDL
1654 itself. That makes it convenient for inline use in expressions.
1655 online_cpus
1657 Returns the number of available processors cores. Used to set the
1658 number of threads with "set_autopthread_targ" if
1659 $ENV{PDL_AUTOPTHREAD_TARG} is not set.
1660 set_autopthread_targ
1662 Set the target number of processor threads (pthreads) for multi-
1663 threaded processing.
1664 set_autopthread_targ($num_pthreads);
1666 $num_pthreads is the target number of pthreads the auto-pthread process
1668 will try to achieve.
1669 See PDL::ParallelCPU for an overview of the auto-pthread process.
1671 # Example turning on auto-pthreading for a target of 2 pthreads and for functions involving
1673 # PDLs with greater than 1M elements
1674 set_autopthread_targ(2);
1675 set_autopthread_size(1);
1676 # Execute a pdl function, processing will split into two pthreads
1678 $x = minimum($y);
1679 # Get the actual number of pthreads that were run.
1681 $actual_pthread = get_autopthread_actual();
1682 get_autopthread_targ
1684 Get the current target number of processor threads (pthreads) for
1685 multi-threaded processing.
1686 $num_pthreads = get_autopthread_targ();
1688 $num_pthreads is the target number of pthreads the auto-pthread process
1690 will try to achieve.
1691 See PDL::ParallelCPU for an overview of the auto-pthread process.
1693 get_autopthread_actual
1695 Get the actual number of pthreads executed for the last pdl processing
1696 function.
1697 $autopthread_actual = get_autopthread_actual();
1699 $autopthread_actual is the actual number of pthreads executed for the
1701 last pdl processing function.
1702 See PDL::ParallelCPU for an overview of the auto-pthread process.
1704 get_autopthread_dim
1706 Get the actual dimension on which pthreads were used for the last pdl
1707 processing function.
1708 $autopthread_dim = get_autopthread_dim();
1710 $autopthread_dim is the actual dimension on which pthreads were used
1712 for the last pdl processing function.
1713 See PDL::ParallelCPU for an overview of the auto-pthread process.
1715 set_autopthread_size
1717 Set the minimum size (in M-elements or 2^20 elements) of the largest
1718 PDL involved in a function where auto-pthreading will be performed. For
1719 small PDLs, it probably isn't worth starting multiple pthreads, so this
1720 function is used to define a minimum threshold where auto-pthreading
1721 won't be attempted.
1722 set_autopthread_size($size);
1724 $size is the mimumum size, in M-elements or 2^20 elements (approx 1e6
1726 elements) for the largest PDL involved in a function.
1727 See PDL::ParallelCPU for an overview of the auto-pthread process.
1729 # Example turning on auto-pthreading for a target of 2 pthreads and for functions involving
1731 # PDLs with greater than 1M elements
1732 set_autopthread_targ(2);
1733 set_autopthread_size(1);
1734 # Execute a pdl function, processing will split into two pthreads as long as
1736 # one of the pdl-threaded dimensions is at least 2.
1737 $x = minimum($y);
1738 # Get the actual number of pthreads that were run.
1740 $actual_pthread = get_autopthread_actual();
1741 get_autopthread_size
1743 Get the current autopthread_size setting.
1744 $autopthread_size = get_autopthread_size();
1746 $autopthread_size is the mimumum size limit for auto_pthreading to
1748 occur, in M-elements or 2^20 elements (approx 1e6 elements) for the
1749 largest PDL involved in a function
1750 See PDL::ParallelCPU for an overview of the auto-pthread process.
1752
1754 Copyright (C) Karl Glazebrook (kgb@aaoepp.aao.gov.au), Tuomas J. Lukka,
1755 (lukka@husc.harvard.edu) and Christian Soeller
1756 (c.soeller@auckland.ac.nz) 1997. Modified, Craig DeForest
1757 (deforest@boulder.swri.edu) 2002. All rights reserved. There is no
1758 warranty. You are allowed to redistribute this software / documentation
1759 under certain conditions. For details, see the file COPYING in the PDL
1760 distribution. If this file is separated from the PDL distribution, the
1761 copyright notice should be included in the file.
1762perl v5.38.0 2023-07-21 Core(3)