Provided by: pdl_2.085-1ubuntu1_amd64 bug

NAME

       PDL::Core - fundamental PDL functionality and vectorization/broadcasting

DESCRIPTION

       Methods and functions for type conversions, PDL creation, type conversion, broadcasting etc.

SYNOPSIS

        use PDL::Core;             # Normal routines
        use PDL::Core ':Internal'; # Hairy routines

VECTORIZATION/BROADCASTING: METHOD AND NOMENCLATURE

       PDL provides vectorized operations via a built-in engine.  Vectorization in PDL is called "broadcasting"
       (formerly, up to 2.074, "threading").  The broadcasting engine implements simple rules for each
       operation.

       Each PDL object has a "shape" that is a generalized N-dimensional rectangle defined by a "dim list" of
       sizes in an arbitrary set of dimensions.  A PDL with shape 2x3 has 6 elements and is said to be two-
       dimensional, or may be referred to as a 2x3-PDL.  The dimensions are indexed numerically starting at 0,
       so a 2x3-PDL has a dimension 0 (or "dim 0") with size 2 and a 1 dimension (or "dim 1") with size 3.

       PDL generalizes *all* mathematical operations with the notion of "active dims": each operator has zero or
       more active dims that are used in carrying out the operation.  Simple scalar operations like scalar
       multiplication ('*') have 0 active dims.  More complicated operators can have more active dims.  For
       example, matrix multiplication ('x') has 2 active dims.  Additional dims are automatically vectorized
       across -- e.g. multiplying a 2x5-PDL with a 2x5-PDL requires 10 simple multiplication operations, and
       yields a 2x5-PDL result.

   Broadcasting rules
       In any PDL expression, the active dims appropriate for each operator are used starting at the 0 dim and
       working forward through the dim list of each object.  All additional dims after the active dims are
       "broadcast dims".  The broadcast dims do not have to agree exactly: they are coerced to agree according
       to simple rules:

       •  Null PDLs match any dim list (see below).

       •  Dims with sizes other than 1 must all agree in size.

       •  Dims of size 1 are silently repeated as necessary except for "[phys]" PDLs.

       •  Missing dims are expanded appropriately.

       A size-1 dim for "[phys]" PDLs causes an exception if the dim is used in another parameter and has a size
       greater than 1.

       The  "size  1"  rule implements "generalized scalar" operation, by analogy to scalar multiplication.  The
       "missing dims" rule acknowledges the ambiguity between a missing dim and a dim of size 1.

   Null PDLs
       PDLs on the left-hand side of assignment can have the special value "Null".  A null PDL has no  dim  list
       and  no  set  size; its shape is determined by the computed shape of the expression being assigned to it.
       Null PDLs contain no values and can only be assigned to.  When assigned to (e.g. via the ".="  operator),
       they cease to be null PDLs.

       To create a null PDL, use "PDL->null()".

   Empty PDLs
       PDLs can represent the empty set using "structured Empty" variables.  An empty PDL is not a null PDL.

       Any dim of a PDL can be set explicitly to size 0.  If so, the PDL contains zero values (because the total
       number of values is the product of all the sizes in the PDL's shape or dimlist).

       Scalar  PDLs  are zero-dimensional and have no entries in the dim list, so they cannot be empty.  1-D and
       higher PDLs can be empty.  Empty PDLs are useful for set operations, and are most commonly encountered in
       the output from selection operators such as which  and  whichND.   Not  all  empty  PDLs  have  the  same
       broadcasting properties -- e.g. a 2x0-PDL represents a collection of 2-vectors that happens to contain no
       elements,  while a simple 0-PDL represents a collection of scalar values (that also happens to contain no
       elements).

       Note that 0 dims are not adjustable via the broadcasting rules -- a dim with size  0  can  only  match  a
       corresponding dim of size 0 or 1.

   Broadcast rules and assignments
       Versions  of  PDL through 2.4.10 have some irregularity with broadcasting and assignments.  Currently the
       broadcasting engine performs a full expansion of both sides of  the  computed  assignment  operator  ".="
       (which assigns values to a pre-existing PDL).  This leads to counter-intuitive behavior in some cases:

       •  Empty PDLs and generalized scalars

          Generalized scalars (PDLs with a dim of size 1) can match any size in the corresponding dim, including
          0.  Thus,

              $x = ones(2,0);
              $y = sequence(2,1);
              $c = $x * $y;
              print $c;

          prints "Empty[2,0]".

          This behavior is counterintuitive but desirable, and will be preserved in future versions of PDL.

VARIABLES

       These are important variables of global scope and are placed in the PDL namespace.

       $PDL::debug

           When true, PDL debugging information is printed.

       $PDL::verbose

           When true, PDL functions provide chatty information.

       $PDL::use_commas

           Whether to insert commas when printing pdls

       $PDL::floatformat, $PDL::doubleformat, $PDL::indxformat

           The  default  print  format  for floats, doubles, and indx values, respectively.  The default default
           values are:

             $PDL::floatformat  = "%7g";
             $PDL::doubleformat = "%10.8g";
             $PDL::indxformat   = "%12d";

       $PDL::undefval

           The value to use instead of "undef" when creating pdls. If is "undef", 0 will be used.

       $PDL::toolongtoprint

           The maximal size pdls to print (defaults to 10000 elements)

FUNCTIONS

   barf
       Standard error reporting routine for PDL.

       barf() is the routine PDL modules should call to report errors. This is because barf()  will  report  the
       error as coming from the correct line in the module user's script rather than in the PDL module.

       For now, barf just calls Carp::confess()

       Remember barf() is your friend. *Use* it!

       At the perl level:

        barf("User has too low an IQ!");

       In C or XS code:

        barf("You have made %d errors", count);

       Note: this is one of the few functions ALWAYS exported by PDL::Core

   pdl
       PDL constructor - creates new ndarray from perl scalars/arrays, ndarrays, and strings

        $double_pdl = pdl(SCALAR|ARRAY REFERENCE|ARRAY|STRING);  # default type
        $type_pdl   = pdl(PDL::Type,SCALAR|ARRAY REFERENCE|ARRAY|STRING);

        $x = pdl [1..10];                    # 1D array of doubles
        $x = pdl ([1..10]);                  # 1D array
        $x = pdl (1,2,3,4);                  # Ditto
        $y = pdl [[1,2,3],[4,5,6]];          # 2D 3x2 array
        $y = pdl "[[1,2,3],[4,5,6]]";        # Ditto (slower)
        $y = pdl "[1 2 3; 4 5 6]";           # Ditto
        $y = pdl q[1 2 3; 4 5 6];            # Ditto, using the q quote operator
        $y = pdl "1 2 3; 4 5 6";             # Ditto, less obvious, but still works
        $y = pdl 42                          # 0-dimensional scalar
        $c = pdl $x;                         # Make a new copy

        $u = pdl ushort(), 42                # 0-dimensional ushort scalar
        $y = pdl(byte(),[[1,2,3],[4,5,6]]);  # 2D byte ndarray

        $n = pdl indx(), [1..5];             # 1D array of indx values
        $n = pdl indx, [1..5];               # ... can leave off parens
        $n = indx( [1..5] );                 # ... still the same!

        $n = pdl cdouble, 2, 3;              # native complex numbers, zero imaginary
        use Math::Complex qw(cplx);
        $n = pdl cdouble, 2, cplx(2, 1));    # explicit type
        $n = pdl 2, cplx(2, 1);              # default cdouble if Math::Complex obj

        $x = pdl([[1,2,3],[4,5,6]]);         # 2D
        $x = pdl([1,2,3],[4,5,6]);           # 2D

       Note  the  last  two are equivalent - a list is automatically converted to a list reference for syntactic
       convenience. i.e. you can omit the outer "[]"

       You can mix and match arrays, array refs, and PDLs in your argument list, and "pdl" will sort  them  out.
       You  get  back  a PDL whose last (slowest running) dim runs across the top level of the list you hand in,
       and whose first (fastest running) dim runs across the deepest level that you supply.

       At the moment, you cannot mix and match those arguments with string arguments, though we can't imagine  a
       situation in which you would really want to do that.

       The  string version of pdl also allows you to use the strings "bad", "inf", and "nan", and it will insert
       the values that you mean (and set the bad flag if you use "bad"). You can mix and match case, though  you
       shouldn't. Here are some examples:

        $bad = pdl q[1 2 3 bad 5 6];  # Set fourth element to the bad value
        $bad = pdl q[1 2 3 BAD 5 6];  # ditto
        $bad = pdl q[1 2 inf bad 5];  # now third element is IEEE infinite value
        $bad = pdl q[nan 2 inf -inf]; # first value is IEEE nan value

       The  default  constructor uses IEEE double-precision floating point numbers. You can use other types, but
       you will get a warning if you try to use "nan" with integer types (it will be  replaced  with  the  "bad"
       value) and you will get a fatal error if you try to use "inf".

       Throwing a PDL into the mix has the same effect as throwing in a list ref:

         pdl(pdl(1,2),[3,4])

       is the same as

         pdl([1,2],[3,4]).

       All  of  the dimensions in the list are "padded-out" with undefval to meet the widest dim in the list, so
       (e.g.)

         $x = pdl([[1,2,3],[2]])

       gives you the same answer as

         $x = pdl([[1,2,3],[2,undef,undef]]);

       If your PDL module has bad values compiled into it (see PDL::Bad), you  can  pass  BAD  values  into  the
       constructor  within  pre-existing  PDLs.   The  BAD  values  are  automatically  kept  BAD and propagated
       correctly.

       pdl() is a functional synonym for the 'new' constructor, e.g.:

        $x = PDL->new([1..10]);

       In order to control how undefs are handled in converting from  perl  lists  to  PDLs,  one  can  set  the
       variable $PDL::undefval.  For example:

        $foo = [[1,2,undef],[undef,3,4]];
        $PDL::undefval = -999;
        $f = pdl $foo;
        print $f
        [
         [   1    2 -999]
         [-999    3    4]
        ]

       $PDL::undefval defaults to zero.

       As  a  final note, if you include an Empty PDL in the list of objects to construct into a PDL, it is kept
       as a placeholder pane -- so if you feed in (say) 7 objects, you get a size of 7 in the  0th  dim  of  the
       output  PDL.   The  placeholder  panes are completely padded out.  But if you feed in only a single Empty
       PDL, you get back the Empty PDL (no padding).

   empty
       Returns an empty ndarray, with a single zero-length dimension.  Only  available  as  a  function,  not  a
       method.

        $x = empty; # defaults to lowest type so it can always be promoted up
        $x = empty(float);

   null
       Returns a 'null' ndarray.  It is an error to pass one of these as an input to a function.

        $x = null;

       null()  has  a  special meaning to PDL::PP. It is used to flag a special kind of empty ndarray, which can
       grow to appropriate dimensions to store a result (as opposed to storing a result in an existing ndarray).

        pdl> sumover sequence(10,10), $ans=null;p $ans
        [45 145 245 345 445 545 645 745 845 945]

   nullcreate
       Returns a 'null' ndarray.

        $x = PDL->nullcreate($arg)

       This is an routine used by many of the broadcasting primitives (i.e. sumover, minimum, etc.) to  generate
       a  null  ndarray  for  the  function's  output  that will behave properly for derived (or subclassed) PDL
       objects.

       For the above usage: If $arg is a PDL, or a derived PDL, then "$arg->null" is returned.   If  $arg  is  a
       scalar (i.e. a zero-dimensional PDL) then "PDL->null" is returned.

        PDL::Derived->nullcreate(10)
          returns PDL::Derived->null.
        PDL->nullcreate($pdlderived)
          returns $pdlderived->null.

   nelem
       Return the number of elements in an ndarray

        $n = nelem($ndarray); $n = $ndarray->nelem;

        $mean = sum($data)/nelem($data);

   dims
       Return ndarray dimensions as a perl list

        @dims = $ndarray->dims;  @dims = dims($ndarray);

        pdl> p @tmp = dims zeroes 10,3,22
        10 3 22

       See also "shape" which returns an ndarray instead.

   shape
       Return ndarray dimensions as an ndarray

        $shape = $ndarray->shape;  $shape = shape($ndarray);

        pdl> p $shape = shape zeroes 10,3,22
        [10 3 22]

       See also "dims" which returns a perl list.

   ndims
       Returns the number of dimensions in an ndarray. Alias for getndims.

   getndims
       Returns the number of dimensions in an ndarray

        $ndims = $ndarray->getndims;

        pdl> p zeroes(10,3,22)->getndims
        3

   dim
       Returns the size of the given dimension of an ndarray. Alias for getdim.

   getdim
       Returns the size of the given dimension.

        $dim0 = $ndarray->getdim(0);

        pdl> p zeroes(10,3,22)->getdim(1)
        3

       Negative  indices  count from the end of the dims array.  Indices beyond the end will return a size of 1.
       This reflects the idea that any pdl is equivalent to an infinitely dimensional  array  in  which  only  a
       finite  number  of  dimensions have a size different from one. For example, in that sense a 3D ndarray of
       shape [3,5,2] is equivalent to a [3,5,2,1,1,1,1,1,....]  ndarray. Accordingly,

         print $x->getdim(10000);

       will print 1 for most practically encountered ndarrays.

   topdl
       alternate ndarray constructor - ensures arg is an ndarray

        $x = topdl(SCALAR|ARRAY REFERENCE|ARRAY);

       The difference between pdl() and topdl() is that the latter will just 'fall through' if the  argument  is
       already an ndarray. It will return a reference and NOT a new copy.

       This is particularly useful if you are writing a function which is doing some fiddling with internals and
       assumes  an  ndarray argument (e.g. for method calls). Using topdl() will ensure nothing breaks if passed
       with '2'.

       Note that topdl() is not exported by default (see example below for usage).

        use PDL::Core ':Internal'; # use the internal routines of
                                   # the Core module

        $x = topdl 43;             # $x is ndarray with value '43'
        $y = topdl $ndarray;       # fall through
        $x = topdl (1,2,3,4);      # Convert 1D array

   set_datatype
       Sets the ndarray's data type to the given value (the integer identifier  for  the  type,  see  "enum"  in
       PDL::Types). See "get_datatype". Internal function.

   get_datatype
       Internal: Return the numeric value identifying the ndarray datatype

        $x = $ndarray->get_datatype;

       Mainly used for internal routines.

       NOTE: get_datatype returns 'just a number' not any special type object, unlike "type".

   howbig
       Returns the sizeof an ndarray datatype in bytes.

       Note that howbig() is not exported by default (see example below for usage).

        use PDL::Core ':Internal'; # use the internal routines of
                                   # the Core module

        $size = howbig($ndarray->get_datatype);

       Mainly used for internal routines.

       NOTE: NOT a method! This is because get_datatype returns 'just a number' not any special object.

        pdl> p howbig(ushort([1..10])->get_datatype)
        2

   get_dataref
       Return the internal data for an ndarray, as a perl SCALAR ref.

       Most  ndarrays  hold  their  internal  data  in  a packed perl string, to take advantage of perl's memory
       management.  This gives you direct access to the string, which is handy when you need to  manipulate  the
       binary  data  directly  (e.g.  for  file  I/O).  If you modify the string, you'll need to call "upd_data"
       afterward, to make sure that the ndarray points to the new location of the underlying perl variable.

       Calling "get_dataref" automatically physicalizes your  ndarray  (see  "make_physical").   You  definitely
       don't want to do anything to the SV to truncate or deallocate the string, unless you correspondingly call
       "reshape" to make the PDL match its new data dimension.

       You  definitely  don't  want to use get_dataref unless you know what you are doing (or are trying to find
       out): you can end up scrozzling memory if you shrink  or  eliminate  the  string  representation  of  the
       variable.  Here be dragons.

   upd_data
       Update the data pointer in an ndarray to match its perl SV.

       This  is  useful  if  you've  been  monkeying with the packed string representation of the PDL, which you
       probably shouldn't be doing anyway.  (see "get_dataref".)

   broadcastids
       Returns the ndarray broadcast IDs as a perl list

       Note that broadcastids() is not exported by default (see example below for usage).

        use PDL::Core ':Internal'; # use the internal routines of
                                   # the Core module

        @ids = broadcastids $ndarray;

   doflow
       Turn on dataflow, forward only. This means any transformations (a.k.a. PDL operations)  applied  to  this
       ndarray afterwards will have forward dataflow:

         $x = sequence 3;
         $x->doflow;
         $y = $x + 1;
         $x += 3;
         print "$y\n"; # [4 5 6]

       As  of  2.064,  the core API does not automatically sever transformations that have forward dataflow into
       them:

         # following from the above
         $y->set(1, 9); # value now [4 9 6]
         $x += 11;
         print "$y\n"; # [15 16 17] - previously would have been [4 9 6]

       If you want to sever such transformations, call "sever" on the child ndarray (above, $y).

        $x->doflow;  doflow($x);

   flows
       Whether or not an ndarray is indulging in dataflow

        something if $x->flows; $hmm = flows($x);

   fflows
       Returns whether the ndarray's "PDL_DATAFLOW_F" flag is set.

   bflows
       Returns whether the ndarray's "PDL_DATAFLOW_B" flag is set.

   new
       new ndarray constructor method

        $x = PDL->new(SCALAR|ARRAY|ARRAY REF|STRING);

        $x = PDL->new(42);             # new from a Perl scalar
        $y = PDL->new(@list_of_vals);  # new from Perl list
        $z = PDL->new(\@list_of_vals); # new from Perl list reference
        $w = PDL->new("[1 2 3]");      # new from Perl string, using
                                       # Matlab constructor syntax

       Constructs ndarray from perl numbers and lists and strings with Matlab/Octave style constructor syntax.

       The string input is fairly versatile though not performance optimized. The goal is to  make  it  easy  to
       copy and paste code from PDL output and to offer a familiar Matlab syntax for ndarray construction. As of
       May,  2010,  it is a new feature, so feel free to report bugs or suggest new features.  See documentation
       for pdl for more examples of usage.

   copy
       Make a physical copy of an ndarray

        $new = $old->copy;

       Since "$new = $old" just makes a new reference, the "copy" method is provided to allow  real  independent
       copies to be made.

   hdr_copy
       Return an explicit copy of the header of a PDL.

       hdr_copy  is just a wrapper for the internal routine _hdr_copy, which takes the hash ref itself.  That is
       the routine which is used to make copies of the header during normal operations if the hdrcpy() flag of a
       PDL is set.

       General-purpose deep copies are expensive in perl, so some simple optimization happens:

       If the header is a tied array or a blessed hash ref with an associated method called  "copy",  then  that
       ->copy  method  is  called.   Otherwise,  all elements of the hash are explicitly copied.  References are
       recursively deep copied.

       This routine seems to leak memory.

   unwind
       Return an ndarray which is the same as the argument except that all broadcastids have been removed.

        $y = $x->unwind;

   make_physical
       Make sure the data portion of an ndarray can be accessed from XS code.

        $x->make_physical;
        $x->call_my_xs_method;

       Ensures that an ndarray gets its own allocated copy of  data.  This  obviously  implies  that  there  are
       certain ndarrays which do not have their own data.  These are so called virtual ndarrays that make use of
       the  vaffine optimisation (see PDL::Indexing).  They do not have their own copy of data but instead store
       only access information to some (or all) of another ndarray's data.

       Note: this function should not be used unless absolutely necessary since  otherwise  memory  requirements
       might  be  severely  increased. Instead of writing your own XS code with the need to call "make_physical"
       you might want to consider using the PDL preprocessor (see PDL::PP) which can be  used  to  transparently
       access virtual ndarrays without the need to physicalise them (though there are exceptions).

   make_physvaffine
       A more "careful" function than "make_physical". For ndarrays without a vaffine transformations as parent,
       it will just call "make_physical". Otherwise, it will update the vaffine transformation bookkeeping.

   make_physdims
       Ensures  the  ndarray's  dimensions  are up to date including changes in parent's dimensions, and calling
       "redodims".

   trans_parent
       Returns a PDL::Trans object representing the transformation (PDL operation) that is the "parent" of  this
       ndarray, or "undef" if none.

       Such objects have these methods:

       parents
           Returns a list of ndarrays that are inputs to this trans.

       children
           Returns  a  list  of ndarrays that are outputs to this trans (specified as "[o]", "[oca]", "[io]", or
           "[t]" in "Pars").

       address
           The memory address of the struct.

       name
           The function name from the vtable.

       flags
           List of strings of flags set for this trans.

       flags_vtable
           List of strings of flags set for this trans's vtable.

       vaffine
           Whether the trans is affine.

       offs
           Affine-only: the offset into the parent's data.

       incs
           Affine-only: the dimincs for each of the child's dims.

       ind_sizes
           The size of each named dim.

       inc_sizes
           The size of the inc for each use of a named dim.

   trans_children
       Returns a list of PDL::Trans objects (see "trans_parent") representing each transformation that has  this
       ndarray as an input.

   address
       Returns the memory address of the ndarray's "struct".

   address_data
       Returns the value of the ndarray "struct"'s "data" member.

   freedata
       Frees the "datasv" if possible. Useful in memory-mapping functionality.

   set_donttouchdata
       Sets  the  "PDL_DONTTOUCHDATA"  flag  and  the  "nbytes"  to  the  given  value. Useful in memory-mapping
       functionality.

   set_data_by_offset
       Sets the ndarray's "data" and "datasv" to those of the given ndarray, but the "data" points to the  other
       ndarray's  "data"  plus  the  given  offset.  Sets the "PDL_DONTTOUCHDATA" flag. Useful in memory-mapping
       functionality.

   nbytes
       Returns the ndarray's "nbytes".

   seed
       Returns the random seed being used by PDL's RNG.

   set_debugging
       Sets whether PDL operations print lots of debugging info to standard output. Returns the old value.

         PDL::Core::set_debugging(1);
         # ... these operations will have debugging info printed to stdout
         PDL::Core::set_debugging(0); # turn it off again

   dummy
       Insert a 'dummy dimension' of given length (defaults to 1)

       No relation to the 'Dungeon Dimensions' in Discworld!

       Negative positions specify relative to last dimension, i.e.  dummy(-1)  appends  one  dimension  at  end,
       dummy(-2) inserts a dummy dimension in front of the last dim, etc.

       If  you  specify  a  dimension position larger than the existing dimension list of your PDL, the PDL gets
       automagically padded with extra dummy dimensions so that you get the dim you asked for, in the  slot  you
       asked  for.   This could cause you trouble if, for example, you ask for $x->dummy(5000,1) because $x will
       get 5,000 dimensions, each of rank 1.

       Because padding at the beginning of the dimension list moves existing dimensions from slot to slot,  it's
       considered  unsafe,  so  automagic  padding  doesn't  work  for  large negative indices -- only for large
       positive indices.

        $y = $x->dummy($position[,$dimsize]);

        pdl> p sequence(3)->dummy(0,3)
        [
         [0 0 0]
         [1 1 1]
         [2 2 2]
        ]

        pdl> p sequence(3)->dummy(3,2)
        [
         [
          [0 1 2]
         ]
         [
          [0 1 2]
         ]
        ]

        pdl> p sequence(3)->dummy(-3,2)
        Runtime error: PDL: For safety, <pos> < -(dims+1) forbidden in dummy.  min=-2, pos=-3

   dup
       Duplicates an ndarray along a dimension

        $x = sequence(3);
        $y = $x->dup(0, 2); # doubles along first dimension
        # $y now [0 1 2 0 1 2]

   dupN
       Duplicates an ndarray along several dimensions

        $x = sequence(3,2);
        $y = $x->dupN(2, 3); # doubles along first dimension, triples along second
        # [
        #  [0 1 2 0 1 2]
        #  [3 4 5 3 4 5]
        #  [0 1 2 0 1 2]
        #  [3 4 5 3 4 5]
        #  [0 1 2 0 1 2]
        #  [3 4 5 3 4 5]
        # ]

   inflateN
       Inflates an ndarray along several dimensions, useful for e.g. Kronecker products

       cf "dupN"

        $x = sequence(3,2);
        $y = $x->inflateN(2, 2); # doubles along first two dimensions
        # [
        #  [0 0 1 1 2 2]
        #  [0 0 1 1 2 2]
        #  [3 3 4 4 5 5]
        #  [3 3 4 4 5 5]
        # ]

   clump
       "clumps" several dimensions into one large dimension

       If called with one argument $n clumps the first $n dimensions into one. For example, if $x has dimensions
       "(5,3,4)" then after

        $y = $x->clump(2);   # Clump 2 first dimensions

       the variable $y will have dimensions "(15,4)"  and  the  element  "$y->at(7,3)"  refers  to  the  element
       "$x->at(1,2,3)".

       Use clump(-1) to flatten an ndarray. The method flat is provided as a convenient alias.

       Clumping with a negative dimension in general leaves that many dimensions behind -- e.g. clump(-2) clumps
       all of the first few dimensions into a single one, leaving a 2-D ndarray.

       If  "clump" is called with an index list with more than one element it is treated as a list of dimensions
       that should be clumped together into one. The resulting clumped dim is placed  at  the  position  of  the
       lowest  index  in  the  list.   This convention ensures that "clump" does the expected thing in the usual
       cases. The following example demonstrates typical usage:

         $x = sequence 2,3,3,3,5; # 5D ndarray
         $c = $x->clump(1..3);    # clump all the dims 1 to 3 into one
         print $c->info;          # resulting 3D ndarray has clumped dim at pos 1
        PDL: Double D [2,27,5]

   broadcast_define
       define functions that support broadcasting at the perl level

        broadcast_define 'tline(a(n);b(n))', over {
         line $_[0], $_[1]; # make line compliant with broadcasting
        };

       "broadcast_define" provides some support for broadcasting (see  PDL::Indexing)  at  the  perl  level.  It
       allows  you to do things for which you normally would have resorted to PDL::PP (see PDL::PP); however, it
       is most useful to wrap existing perl functions so that the new routine supports PDL broadcasting.

       "broadcast_define" is used to define new broadcasting aware functions. Its first argument is  a  symbolic
       repesentation  of  the new function to be defined. The string is composed of the name of the new function
       followed by its signature (see PDL::Indexing and PDL::PP)  in  parentheses.  The  second  argument  is  a
       subroutine  that  will  be  called  with  the  slices of the actual runtime arguments as specified by its
       signature. Correct dimension sizes and minimal number of dimensions for all  arguments  will  be  checked
       (assuming the rules of PDL broadcasting, see PDL::Indexing).

       The  actual  work  is  done  by  the  "signature"  class  which parses the signature string, does runtime
       dimension checks and the routine "broadcastover" that generates the loop over all appropriate  slices  of
       pdl arguments and creates pdls as needed.

       Similar  to  "pp_def"  and  its  "OtherPars"  option it is possible to define the new function so that it
       accepts normal perl args as well as ndarrays. You do this by using  the  "NOtherPars"  parameter  in  the
       signature. The number of "NOtherPars" specified will be passed unaltered into the subroutine given as the
       second argument of "broadcast_define". Let's illustrate this with an example:

        PDL::broadcast_define 'triangles(inda();indb();indc()), NOtherPars => 2',
         PDL::over {
           ${$_[3]} .= $_[4].join(',',map {$_->at} @_[0..2]).",-1,\n";
         };

       This defines a function "triangles" that takes 3 ndarrays as input plus 2 arguments which are passed into
       the routine unaltered. This routine is used to collect lists of indices into a perl scalar that is passed
       by reference. Each line is preceded by a prefix passed as $_[4]. Here is typical usage:

        $txt = '';
        triangles(pdl(1,2,3),pdl(1),pdl(0),\$txt," "x10);
        print $txt;

       resulting in the following output

        1,1,0,-1,
        2,1,0,-1,
        3,1,0,-1,

       which is used in PDL::Graphics::TriD::VRML to generate VRML output.

       Currently,  this  is  probably  not  much  more than a POP (proof of principle) but is hoped to be useful
       enough for some real life work.

       Check PDL::PP for the format of the signature. Currently, the "[t]" qualifier and all type qualifiers are
       ignored.

   broadcast
       Use explicit broadcasting over specified dimensions (see also PDL::Indexing)

        $y = $x->broadcast($dim,[$dim1,...])

        $x = zeroes 3,4,5;
        $y = $x->broadcast(2,0);

       Same as "broadcast1", i.e. uses broadcast id 1.

   broadcast1
       Explicit broadcasting over specified dims using broadcast id 1.

        $xx = $x->broadcast1(3,1)

        Wibble

       Convenience function interfacing to PDL::Slices::broadcastI.

   broadcast2
       Explicit broadcasting over specified dims using broadcast id 2.

        $xx = $x->broadcast2(3,1)

        Wibble

       Convenience function interfacing to PDL::Slices::broadcastI.

   broadcast3
       Explicit broadcasting over specified dims using broadcast id 3.

        $xx = $x->broadcast3(3,1)

        Wibble

       Convenience function interfacing to PDL::Slices::broadcastI.

   sever
       sever any links of this ndarray to parent ndarrays

       In PDL it is possible for an ndarray to be just another view into another ndarray's data. In that case we
       call this ndarray a virtual ndarray and the original  ndarray  owning  the  data  its  parent.  In  other
       languages these alternate views sometimes run by names such as alias or smart reference.

       Typical  functions  that  return such ndarrays are "slice", "xchg", "index", etc. Sometimes, however, you
       would like to separate the virtual ndarray from its parent's data and just give it a life of its own  (so
       that  manipulation of its data doesn't change the parent).  This is simply achieved by using "sever". For
       example,

          $x = $pdl->index(pdl(0,3,7))->sever;
          $x++;       # important: $pdl is not modified!

       In many (but not all) circumstances it acts therefore similar to copy.  However, in  general  performance
       is  better  with  "sever" and secondly, "sever" doesn't lead to futile copying when used on ndarrays that
       already have their own data. On the other hand, if you really want to make sure to work on a copy  of  an
       ndarray use copy.

          $x = zeroes(20);
          $x->sever;   # NOOP since $x is already its own boss!

       Again note: "sever" is not the same as copy!  For example,

          $x = zeroes(1); # $x does not have a parent, i.e. it is not a slice etc
          $y = $x->sever; # $y is now pointing to the same ndarray as $x
          $y++;
          print $x;
        [1]

       but

          $x = zeroes(1);
          $y = $x->copy; # $y is now pointing to a new ndarray
          $y++;
          print $x;
        [0]

   info
       Return formatted information about an ndarray.

        $x->info($format_string);

        print $x->info("Type: %T Dim: %-15D State: %S");

       Returns  a  string  with  info  about  an  ndarray.  Takes  an optional argument to specify the format of
       information a la sprintf.  Format specifiers are in  the  form  "%<width><letter>"  where  the  width  is
       optional and the letter is one of

       T      Type

       D      Formatted Dimensions

       F      Dataflow status

       S      Some internal flags (P=physical,V=Vaffine,C=changed,B=may contain bad data)

       C      Class of this ndarray, i.e. "ref $pdl"

       A      Address of the ndarray struct as a unique identifier

       M      Calculated memory consumption of this ndarray's data area

   pdump
       Returns  a  close  analogue  of the output of "$pdl->dump" as a string. Like that C function, it will not
       cause any physicalisation of the ndarray.

       Not exported, and not inserted into the "PDL" namespace.

         print PDL::Core::pdump($pdl);

   pdump_trans
       Returns a string representation of a "PDL::Trans" object, a close analogue  of  part  of  the  output  of
       "$pdl->dump".

       Not exported, and not inserted into the "PDL" namespace.

         print PDL::Core::pdump_trans($pdl_trans);

   pdumphash
       Returns  a  hash-ref  representing the information about a given object ("PDL::Trans" or ndarray) and all
       the objects of either type it is connected to. Includes similar information to that shown by "pdump"  and
       "pdump_trans".

       Not exported, and not inserted into the "PDL" namespace.

         $hashref = PDL::Core::pdumphash($pdl_trans); # or
         $hashref = PDL::Core::pdumphash($pdl);

   pdumpgraph
       Given a hash-ref returned by "pdumphash", returns a Graph object representing the same information.

       Not exported, and not inserted into the "PDL" namespace.

         $g = PDL::Core::pdumphash($hashref);

   pdumpgraphvizify
       Given  a  Graph  object  returned  by  "pdumpgraph",  modifies  it  suitable for input to "from_graph" in
       GraphViz2, then returns it. See example for how to use.

       Not exported, and not inserted into the "PDL" namespace.

         $g = PDL::Core::pdumpgraphvizify($g);

         # full example:
         $count = 1; $format = 'png'; sub output {
           $g = PDL::Core::pdumpgraph(PDL::Core::pdumphash($_[0]));
           require GraphViz2;
           $gv = GraphViz2->from_graph(PDL::Core::pdumpgraphvizify($g));
           $gv->run(format => $format, output_file => 'output'.$count++.".$format");
         }
         # keep changing ndarray, then calling this to show each state:
         output($pdl);

         # run the above script, then show the ndarray evolve over time, in a
         # left-to-right montage using ImageMagick tools:
         perl myscript.pl
         montage output* -tile "$(echo output*|wc -w)"x1 -geometry '1x1<' final.png
         display final.png

   approx
       test for approximately equal values (relaxed "==")

         # ok if all corresponding values in
         # ndarrays are within 1e-8 of each other
         print "ok\n" if all approx $x, $y, 1e-8;

       "approx" is a relaxed form of the "==" operator and often  more  appropriate  for  floating  point  types
       ("float" and "double").

       Usage:

         $res = approx $x, $y [, $eps]

       The optional parameter $eps is remembered across invocations and initially set to 1e-6, e.g.

         approx $x, $y;         # last $eps used (1e-6 initially)
         approx $x, $y, 1e-10;  # 1e-10
         approx $x, $y;         # also 1e-10

   mslice
       Alias to "slice" in PDL::Slices.

   nslice_if_pdl
       If $self is a PDL, then calls "slice" with all but the last argument, otherwise $self->($_[-1]) is called
       where $_[-1} is the original argument string found during PDL::NiceSlice filtering.

       DEVELOPER'S NOTE: this routine is found in Core.pm.PL but would be better placed in Slices/slices.pd.  It
       is likely to be moved there and/or changed to "slice_if_pdl" for PDL 3.0.

        $w = $x->nslice_if_pdl(...,'(args)');

   tracedebug
       Sets  whether  an  ndarray  will  have  debugging  info printed during use if a (Boolean) value is given.
       Returns the new value.

   donttouch
       Returns whether the ndarray's "PDL_DONTTOUCHDATA" flag is set.

   allocated
       Returns whether the ndarray's "PDL_ALLOCATED" flag is set.

   vaffine
       Returns whether the ndarray's "PDL_OPT_VAFFTRANSOK" flag is set.

   anychgd
       Returns whether the ndarray's "PDL_ANYCHANGED" flag is set.

   dimschgd
       Returns whether the ndarray's "PDL_PARENTDIMSCHANGED" flag is set.

   inplace
       Flag an ndarray so that the next operation is done 'in place', returning the ndarray.

        somefunc($x->inplace); somefunc(inplace $x);

       In most cases one likes to use the syntax "$y = f($x)", however in many case the  operation  f()  can  be
       done  correctly 'in place', i.e. without making a new copy of the data for output. To make it easy to use
       this, we write f() in such a way that it operates in-place, and use "inplace" to hint  that  a  new  copy
       should be disabled. This also makes for clear syntax.

       Obviously this will not work for all functions, and if in doubt see the function's documentation. However
       one  can  assume this is true for all elemental functions (i.e. those which just operate array element by
       array element like "log10").

        pdl> $x = xvals zeroes 10;
        pdl> log10(inplace $x)
        pdl> p $x
        [-inf 0    0.30103 0.47712125 0.60205999    0.69897 0.77815125 0.84509804 0.90308999 0.95424251]

   is_inplace
       Sets whether an ndarray will operate "in-place" for the next operation if a  (Boolean)  value  is  given.
       Returns the old value.

         $out = ($in->is_inplace) ? $in : zeroes($in);
         $in->set_inplace(0)

       Provides  access to the "inplace" hint flag, within the perl milieu.  That way functions you write can be
       inplace aware... If given an argument the inplace flag will be set or unset depending on the value at the
       same time. Can be used for shortcut tests that delete the inplace flag while testing:

         $out = ($in->is_inplace(0)) ? $in : zeroes($in); # test & unset!

   set_inplace
       Set the in-place flag on an ndarray

         $out = ($in->is_inplace) ? $in : zeroes($in);
         $in->set_inplace(0);

       Provides access to the "inplace" hint flag, within the perl milieu.  Useful mainly for turning it OFF, as
       "inplace" turns it ON more conveniently.

   new_or_inplace
           $w = new_or_inplace(shift());
           $w = new_or_inplace(shift(),$preferred_type);

       Return back either the argument pdl or a copy of it depending on whether it be flagged  in-place  or  no.
       Handy for building inplace-aware functions.

       If you specify a preferred type (must be one of the usual PDL type strings, a list ref containing several
       of them, or a comma-separated string containing several of them), then the copy is coerced into the first
       preferred type listed if it is not already one of the preferred types.

       Note that if the inplace flag is set, no coercion happens even if you specify a preferred type.

   new_from_specification
       Internal method: create ndarray by specification

       This  is  the  argument  processing  method  called by "zeroes" and some other functions which constructs
       ndarrays from argument lists of the form:

        [type], $nx, $ny, $nz,...

       For $nx, $ny, etc. 0 and 1D ndarrays are allowed.   Giving  those  has  the  same  effect  as  if  saying
       "$arg->list", e.g.

          1, pdl(5,2), 4

       is equivalent to

          1, 5, 2, 4

       Note, however, that in all functions using "new_from_specification" calling "func $ndarray" will probably
       not do what you want. So to play safe use (e.g. with zeroes)

         $pdl = zeroes $dimpdl->list;

       Calling

         $pdl = zeroes $dimpdl;

       will rather be equivalent to

         $pdl = zeroes $dimpdl->dims;

       However,

         $pdl = zeroes ushort, $dimpdl;

       will again do what you intended since it is interpreted as if you had said

         $pdl = zeroes ushort, $dimpdl->list;

       This  is  unfortunate  and  confusing  but  no  good solution seems obvious that would not break existing
       scripts.

   isnull
       Test whether an ndarray is null

        croak("Input ndarray mustn't be null!")
            if $input_ndarray->isnull;

       This function returns 1 if the ndarray is null, zero if it is not. The purpose of  null  ndarrays  is  to
       "tell"  any  PDL::PP  methods  to  allocate  new memory for an output ndarray, but only when that PDL::PP
       method is called in full-arg form. Of course, there's no reason you couldn't commandeer the special value
       for your own purposes, for which this test function would  prove  most  helpful.   But  in  general,  you
       shouldn't need to test for an ndarray's nullness.

       See "Null PDLs" for more information.

   isempty
       Test whether an ndarray is empty

        print "The ndarray has zero dimension\n" if $pdl->isempty;

       This  function  returns  1  if the ndarray has zero elements. This is useful in particular when using the
       indexing function which. In the case of no match to a specified criterion, the returned ndarray has  zero
       dimension.

        pdl> $w=sequence(10)
        pdl> $i=which($w < -1)
        pdl> print "I found no matches!\n" if ($i->isempty);
        I found no matches!

       Note  that  having  zero  elements  is rather different from the concept of being a null ndarray, see the
       PDL::FAQ and PDL::Indexing manpages for discussions of this.

   zeroes
       construct a zero filled ndarray from dimension list or template ndarray.  If called  with  no  arguments,
       returns a zero-dimension ndarray (a scalar).

       Various forms of usage,

       (i) by specification or (ii) by template ndarray:

        # usage type (i):
        $w = zeroes([type], $nx, $ny, $nz,...);
        $w = PDL->zeroes([type], $nx, $ny, $nz,...);
        $w = $pdl->zeroes([type], $nx, $ny, $nz,...); # all info about $pdl ignored
        # usage type (ii):
        $w = zeroes $y;
        $w = $y->zeroes
        zeroes inplace $w;     # Equivalent to   $w .= 0;
        $w->inplace->zeroes;   #  ""

        pdl> $z = zeroes 4,3
        pdl> p $z
        [
         [0 0 0 0]
         [0 0 0 0]
         [0 0 0 0]
        ]
        pdl> $z = zeroes ushort, 3,2 # Create ushort array
        [ushort() etc. with no arg returns a PDL::Types token]

       See also "new_from_specification" for details on using ndarrays in the dimensions list.

   zeros
       construct a zero filled ndarray (see zeroes for usage)

   ones
       construct  a  one  filled  ndarray.   If  called  with  no arguments, returns a zero-dimension ndarray (a
       scalar).

        $w = ones([type], $nx, $ny, $nz,...);
        etc. (see 'zeroes')

        see zeroes() and add one

       See also "new_from_specification" for details on using ndarrays in the dimensions list.

   nan
       construct a "NaN" filled ndarray.  If called with no  arguments,  returns  a  zero-dimension  ndarray  (a
       scalar).

        $w = nan([type], $nx, $ny, $nz,...);
        etc. (see 'zeroes')

        see zeroes() and add NaN

       See also "new_from_specification" for details on using ndarrays in the dimensions list.

   inf
       construct  an  "Inf"  filled  ndarray.   If called with no arguments, returns a zero-dimension ndarray (a
       scalar).

        $w = inf([type], $nx, $ny, $nz,...);
        etc. (see 'zeroes')

        see zeroes() and add Inf

       See also "new_from_specification" for details on using ndarrays in the dimensions list.

   i
       construct an ndarray filled with a native complex value equal to the imaginary  number  "i",  the  square
       root of -1.  If called with no arguments, returns a zero-dimension ndarray (a scalar).

        $w = i([type], $nx, $ny, $nz,...);
        etc. (see 'zeroes')

        see zeroes() and add "i"

       See also "new_from_specification" for details on using ndarrays in the dimensions list.

   reshape
       Change the shape (i.e. dimensions) of an ndarray, preserving contents.

        $x->reshape(NEWDIMS); reshape($x, NEWDIMS);

       The  data elements are preserved, obviously they will wrap differently and get truncated if the new array
       is shorter.  If the new array is longer it will be zero-padded.

       ***Potential incompatibility with earlier versions of PDL**** If the list of "NEWDIMS" is empty "reshape"
       will just drop all dimensions of size 1 (preserving the number of elements):

         $w = sequence(3,4,5);
         $y = $w(1,3);
         $y->reshape();
         print $y->info;
        PDL: Double D [5]

       Dimensions of size 1 will also be dropped if "reshape" is invoked with the argument -1:

         $y = $w->reshape(-1);

       As opposed to "reshape" without arguments, reshape(-1) preserves dataflow:

         $w = ones(2,1,2);
         $y = $w(0)->reshape(-1);
         $y++;
         print $w;
        [
         [
          [2 1]
         ]
         [
          [2 1]
         ]
        ]

       Important: ndarrays are changed inplace!

       Note: If $x is connected to any other PDL (e.g. if it is a slice) then the connection is first severed.

        pdl> $x = sequence(10)
        pdl> reshape $x,3,4; p $x
        [
         [0 1 2]
         [3 4 5]
         [6 7 8]
         [9 0 0]
        ]
        pdl> reshape $x,5; p $x
        [0 1 2 3 4]

   squeeze
       eliminate all singleton dimensions (dims of size 1)

        $y = $w(0,0)->squeeze;

       Alias for reshape(-1). Removes all singleton dimensions and preserves dataflow. A more concise  interface
       is provided by PDL::NiceSlice via modifiers:

        use PDL::NiceSlice;
        $y = $w(0,0;-); # same as $w(0,0)->squeeze

   flat
       flatten an ndarray (alias for "$pdl->clump(-1)")

         $srt = $pdl->flat->qsort;

       Useful  method to make a 1D ndarray from an arbitrarily sized input ndarray. Data flows back and forth as
       usual with slicing routines.  Falls through if argument already <= 1D.

   convert
       Generic datatype conversion function

        $y = convert($x, $newtype);

       $newtype is a type number or PDL::Type object, for convenience they  are  returned  by  long()  etc  when
       called without arguments.

        $y = convert $x, long;
        $y = convert $x, ushort;

   Datatype_conversions
       sbyte|byte|short|ushort|long|ulong|indx|longlong|ulonglong|float|double|ldouble|cfloat|cdouble|cldouble
       (shorthands to convert datatypes)

        $y = double $x; $y = ushort [1..10];
        # all of the above listed shorthands behave similarly

       When called with an ndarray argument, they convert to the specific datatype.

       When  called  with  a  numeric, list, listref, or string argument they construct a new ndarray. This is a
       convenience to avoid having to be long-winded and say "$x = long(pdl(42))"

       Thus one can say:

        $w = float(1,2,3,4);           # 1D
        $w = float q[1 2 3; 4 5 6];    # 2D
        $w = float([1,2,3],[4,5,6]);   # 2D
        $w = float([[1,2,3],[4,5,6]]); # 2D

       Note the last three give identical results, and  the  last  two  are  exactly  equivalent  -  a  list  is
       automatically converted to a list reference for syntactic convenience. i.e. you can omit the outer "[]"

       When  called  with  no  arguments,  these functions return a special type token.  This allows syntactical
       sugar like:

        $x = ones byte, 1000,1000;

       This example creates a large ndarray directly as byte datatype in order to save memory.

       In order to control how undefs are handled in converting from  perl  lists  to  PDLs,  one  can  set  the
       variable $PDL::undefval; see the function pdl() for more details.

        pdl> p $x=sqrt float [1..10]
        [1 1.41421 1.73205 2 2.23607 2.44949 2.64575 2.82843 3 3.16228]
        pdl> p byte $x
        [1 1 1 2 2 2 2 2 3 3]

   byte
       Convert to byte datatype

   short
       Convert to short datatype

   ushort
       Convert to ushort datatype

   long
       Convert to long datatype

   indx
       Convert to indx datatype

   longlong
       Convert to longlong datatype

   float
       Convert to float datatype

   double
       Convert to double datatype

   ldouble
       Convert to long double datatype

   cfloat
       Convert to complex float datatype

   cdouble
       Convert to complex double datatype

   cldouble
       Convert to complex long double datatype

   type
       return the type of an ndarray as a blessed type object

       A convenience function for use with the ndarray constructors, e.g.

        $y = PDL->zeroes($x->type,$x->dims,3);
        die "must be float" unless $x->type == float;

       See  also  the discussion of the "PDL::Type" class in PDL::Types.  Note that the "PDL::Type" objects have
       overloaded comparison and stringify operators so that you can compare and print types:

        $x = $x->float if $x->type < float;
        $t = $x->type; print "Type is $t\n";

   list
       Convert ndarray to perl list

        @tmp = list $x;

       Obviously this is grossly inefficient for the large datasets PDL is designed to handle. This was provided
       as a get out while PDL matured. It should now be  mostly  superseded  by  superior  constructs,  such  as
       PP/broadcasting. However it is still occasionally useful and is provided for backwards compatibility.

        for (list $x) {
          # Do something on each value...
        }

       list converts any bad values into the string 'BAD'.

   unpdl
       Convert ndarray to nested Perl array references

        $arrayref = unpdl $x;

       This  function  returns  a  reference  to  a Perl list-of-lists structure equivalent to the input ndarray
       (within the limitation that while values of elements should be preserved, the detailed datatypes will not
       as perl itself basically has "number" data  rather  than  byte,  short,  int...   E.g.,  "sum($x  -  pdl(
       $x->unpdl ))" should equal 0.

       Obviously  this is grossly inefficient in memory and processing for the large datasets PDL is designed to
       handle. Sometimes,  however,  you  really  want  to  move  your  data  back  to  Perl,  and  with  proper
       dimensionality, unlike "list".

       If  you  want  to  round-trip  data  including the use of "PDL::undefval", "unpdl" does not support this.
       However, it is suggested you would generate an index-set with  "$pdl->whereND($pdl  ==  $PDL::undefval)",
       then loop over the Perl data, setting those locations to "undef".

        use JSON;
        my $json = encode_json unpdl $pdl;

       unpdl converts any bad values into the string 'BAD'.

   listindices
       Convert ndarray indices to perl list

        @tmp = listindices $x;

       @tmp now contains the values "0..nelem($x)-1".

       Obviously this is grossly inefficient for the large datasets PDL is designed to handle. This was provided
       as  a  get  out  while  PDL  matured. It  should now be mostly superseded by superior constructs, such as
       PP/broadcasting. However it is still occasionally useful and is provied for backwards compatibility.

        for $i (listindices $x) {
          # Do something on each value...
        }

   set
       Set a single value inside an ndarray

        set $ndarray, @position, $value

       @position is a coordinate list, of size equal to the number of dimensions in  the  ndarray.  Occasionally
       useful, mainly provided for backwards compatibility as superseded by use of slice and assignment operator
       ".=".

        pdl> $x = sequence 3,4
        pdl> set $x, 2,1,99
        pdl> p $x
        [
         [ 0  1  2]
         [ 3  4 99]
         [ 6  7  8]
         [ 9 10 11]
        ]

   at
       Returns  a  single  value  inside  an  ndarray  as perl scalar.  If the ndarray is a native complex value
       (cdouble, cfloat), it will be a PDL::Complex::Overloads object.

        $z = at($ndarray, @position); $z=$ndarray->at(@position);

       @position is a coordinate list, of size equal to the number of dimensions in  the  ndarray.  Occasionally
       useful in a general context, quite useful too inside PDL internals.

        pdl> $x = sequence 3,4
        pdl> p $x->at(1,2)
        7

       at converts any bad values into the string 'BAD'.

   sclr
       return a single value from an ndarray as a scalar, ignoring whether it is bad.

         $val = $x(10)->sclr;
         $val = sclr inner($x,$y);

       The  "sclr"  method  is  useful  to  turn  a  single-element  ndarray into a normal Perl scalar. Its main
       advantage over using "at" for this purpose is the fact that you do not need to worry if  the  ndarray  is
       0D, 1D or higher dimensional.  Using "at" you have to supply the correct number of zeroes, e.g.

         $x = sequence(10);
         $y = $x->slice('4');
         print $y->sclr; # no problem
         print $y->at(); # error: needs at least one zero

       "sclr" is generally used when a Perl scalar is required instead of a one-element ndarray. As of 2.064, if
       the input is a multielement ndarray it will throw an exception.

   cat
       concatenate ndarrays to N+1 dimensional ndarray

       Takes a list of N ndarrays of same shape as argument, returns a single ndarray of dimension N+1.

        pdl> $x = cat ones(3,3),zeroes(3,3),rvals(3,3); p $x
        [
         [
          [1 1 1]
          [1 1 1]
          [1 1 1]
         ]
         [
          [0 0 0]
          [0 0 0]
          [0 0 0]
         ]
         [
          [1 1 1]
          [1 0 1]
          [1 1 1]
         ]
        ]

       The output ndarray is set bad if any input ndarrays have their bad flag set.

       Similar  functions include append, which appends only two ndarrays along their first dimension, and glue,
       which can append more than two ndarrays along an arbitrary dimension.

       Also consider the generic constructor "pdl", which can handle ndarrays of  different  sizes  (with  zero-
       padding),  and  will  return a ndarray of type 'double' by default, but may be considerably faster (up to
       10x) than cat.

   dog
       Opposite of 'cat' :). Split N dim ndarray to list of N-1 dim ndarrays

       Takes a single N-dimensional ndarray and splits it into a list of N-1 dimensional ndarrays.  The  breakup
       is done along the last dimension.  Note the dataflowed connection is still preserved by default, e.g.:

        pdl> $p = ones 3,3,3
        pdl> ($x,$y,$c) = dog $p
        pdl> $y++; p $p
        [
         [
          [1 1 1]
          [1 1 1]
          [1 1 1]
         ]
         [
          [2 2 2]
          [2 2 2]
          [2 2 2]
         ]
         [
          [1 1 1]
          [1 1 1]
          [1 1 1]
         ]
        ]

        Break => 1   Break dataflow connection (new copy)

       The output ndarrays are set bad if the original ndarray has its bad flag set.

   gethdr
       Retrieve header information from an ndarray

        $pdl=rfits('file.fits');
        $h=$pdl->gethdr;
        print "Number of pixels in the X-direction=$$h{NAXIS1}\n";

       The  "gethdr"  function  retrieves whatever header information is contained within an ndarray. The header
       can be set with "sethdr" and is always a hash reference or undef.

       "gethdr" returns undef if the ndarray has not yet had a header defined; compare with  "hdr"  and  "fhdr",
       which are guaranteed to return a defined value.

       Note that gethdr() works by reference: you can modify the header in-place once it has been retrieved:

         $x  = rfits($filename);
         $xh = $x->gethdr();
         $xh->{FILENAME} = $filename;

       It  is  also important to realise that in most cases the header is not automatically copied when you copy
       the ndarray.  See "hdrcpy" to enable automatic header copying.

       Here's another example: a wrapper around rcols that allows your ndarray to remember the file it was  read
       from and the columns could be easily written (here assuming that no regexp is needed, extensions are left
       as an exercise for the reader)

        sub ext_rcols {
           my ($file, @columns)=@_;
           my $header={};
           $$header{File}=$file;
           $$header{Columns}=\@columns;

           @ndarrays=rcols $file, @columns;
           foreach (@ndarrays) { $_->sethdr($header); }
           return @ndarrays;
        }

   hdr
       Retrieve or set header information from an ndarray

        $pdl->hdr->{CDELT1} = 1;

       The "hdr" function allows convenient access to the header of a ndarray.  Unlike "gethdr" it is guaranteed
       to return a defined value, so you can use it in a hash dereference as in the example.  If the header does
       not yet exist, it gets autogenerated as an empty hash.

       Note  that  this  is  usually  --  but  not  always  --  What  You  Want.   If  you  want  to  use a tied
       Astro::FITS::Header hash, for example, you should either construct it yourself and use "sethdr" to put it
       into the ndarray, or use "fhdr" instead.  (Note that you should be  able  to  write  out  the  FITS  file
       successfully regardless of whether your PDL has a tied FITS header object or a vanilla hash).

   fhdr
       Retrieve or set FITS header information from an ndarray

        $pdl->fhdr->{CDELT1} = 1;

       The  "fhdr"  function  allows  convenient  access  to  the  header  of  a ndarray.  Unlike "gethdr" it is
       guaranteed to return a defined value, so you can use it in a hash dereference as in the example.  If  the
       header does not yet exist, it gets autogenerated as a tied Astro::FITS::Header hash.

       Astro::FITS::Header  tied  hashes  are  better  at matching the behavior of FITS headers than are regular
       hashes.   In  particular,  the  hash  keys  are  CAsE  INsEnSItiVE,  unlike  normal   hash   keys.    See
       Astro::FITS::Header for details.

       If you do not have Astro::FITS::Header installed, you get back a normal hash instead of a tied object.

   sethdr
       Set header information of an ndarray

        $pdl = zeroes(100,100);
        $h = {NAXIS=>2, NAXIS1=>100, NAXIS=>100, COMMENT=>"Sample FITS-style header"};
        # add a FILENAME field to the header
        $$h{FILENAME} = 'file.fits';
        $pdl->sethdr( $h );

       The  "sethdr" function sets the header information for an ndarray.  You must feed in a hash ref or undef,
       and the header field of the PDL is set to be a new ref to the same hash (or undefined).

       The hash ref requirement is a speed bump put in place since the normal use of headers is  to  store  fits
       header  information  and  the like.  Of course, if you want you can hang whatever ugly old data structure
       you want off of the header, but that makes life more complex.

       Remember that the hash is not copied -- the header is made into a ref that points to the same  underlying
       data.  To get a real copy without making any assumptions about the underlying data structure, you can use
       one of the following:

         use PDL::IO::Dumper;
         $pdl->sethdr( deep_copy($h) );

       (which is slow but general), or

         $pdl->sethdr( PDL::_hdr_copy($h) )

       (which  uses  the  built-in  sleazy  deep  copier),  or  (if  you know that all the elements happen to be
       scalars):

         { my %a = %$h;
           $pdl->sethdr(\%a);
         }

       which is considerably faster but just copies the top level.

       The "sethdr" function must be given a hash reference or undef.  For further information  on  the  header,
       see "gethdr", "hdr", "fhdr" and "hdrcpy".

   hdrcpy
       switch on/off/examine automatic header copying

        print "hdrs will be copied" if $x->hdrcpy;
        $x->hdrcpy(1);       # switch on automatic header copying
        $y = $x->sumover;    # and $y will inherit $x's hdr
        $x->hdrcpy(0);       # and now make $x non-infectious again

       "hdrcpy" without an argument just returns the current setting of the flag.  See also "hcpy" which returns
       its PDL argument (and so is useful in method-call pipelines).

       Normally,  the  optional header of an ndarray is not copied automatically in pdl operations. Switching on
       the hdrcpy flag using the "hdrcpy" method will enable automatic hdr copying. Note  that  an  actual  deep
       copy gets made, which is rather processor-inefficient -- so avoid using header copying in tight loops!

       Most  PDLs  have  the  "hdrcpy" flag cleared by default; however, some routines (notably rfits) set it by
       default where that makes more sense.

       The "hdrcpy" flag is viral: if you set it for a PDL, then derived PDLs will get copies of the header  and
       will also have their "hdrcpy" flags set.  For example:

         $x = xvals(50,50);
         $x->hdrcpy(1);
         $x->hdr->{FOO} = "bar";
         $y = $x++;
         $c = $y++;
         print $y->hdr->{FOO}, " - ", $c->hdr->{FOO}, "\n";
         $y->hdr->{FOO} = "baz";
         print $x->hdr->{FOO}, " - ", $y->hdr->{FOO}, " - ", $c->hdr->{FOO}, "\n";

       will print:

         bar - bar
         bar - baz - bar

       Performing  an  operation in which more than one PDL has its hdrcpy flag causes the resulting PDL to take
       the header of the first PDL:

         ($x,$y) = sequence(5,2)->dog;
         $x->hdrcpy(1); $y->hdrcpy(1);
         $x->hdr->{foo} = 'a';
         $y->hdr->{foo} = 'b';
         print (($x+$y)->hdr->{foo} , ($y+$x)->hdr->{foo});

       will print:

         a b

   hcpy
       Switch on/off automatic header copying, with PDL pass-through

         $x = rfits('foo.fits')->hcpy(0);
         $x = rfits('foo.fits')->hcpy(1);

       "hcpy" sets or clears the hdrcpy flag of a PDL, and returns the PDL itself.  That makes it convenient for
       inline use in expressions.

   online_cpus
       Returns  the  number  of  available  processors  cores.  Used  to  set  the  number   of   threads   with
       "set_autopthread_targ" if $ENV{PDL_AUTOPTHREAD_TARG} is not set.

   set_autopthread_targ
       Set the target number of processor threads (pthreads) for multi-threaded processing.

        set_autopthread_targ($num_pthreads);

       $num_pthreads is the target number of pthreads the auto-pthread process will try to achieve.

       See PDL::ParallelCPU for an overview of the auto-pthread process.

         # Example turning on auto-pthreading for a target of 2 pthreads and for functions involving
         #   PDLs with greater than 1M elements
         set_autopthread_targ(2);
         set_autopthread_size(1);

         # Execute a pdl function, processing will split into two pthreads
         $x = minimum($y);

         # Get the actual number of pthreads that were run.
         $actual_pthread = get_autopthread_actual();

   get_autopthread_targ
       Get the current target number of processor threads (pthreads) for multi-threaded processing.

        $num_pthreads = get_autopthread_targ();

       $num_pthreads is the target number of pthreads the auto-pthread process will try to achieve.

       See PDL::ParallelCPU for an overview of the auto-pthread process.

   get_autopthread_actual
       Get the actual number of pthreads executed for the last pdl processing function.

        $autopthread_actual = get_autopthread_actual();

       $autopthread_actual is the actual number of pthreads executed for the last pdl processing function.

       See PDL::ParallelCPU for an overview of the auto-pthread process.

   get_autopthread_dim
       Get the actual dimension on which pthreads were used for the last pdl processing function.

        $autopthread_dim = get_autopthread_dim();

       $autopthread_dim  is  the  actual  dimension  on  which  pthreads  were  used for the last pdl processing
       function.

       See PDL::ParallelCPU for an overview of the auto-pthread process.

   set_autopthread_size
       Set the minimum size (in M-elements or 2^20 elements) of the largest PDL involved  in  a  function  where
       auto-pthreading will be performed. For small PDLs, it probably isn't worth starting multiple pthreads, so
       this function is used to define a minimum threshold where auto-pthreading won't be attempted.

        set_autopthread_size($size);

       $size  is  the  mimumum  size,  in  M-elements or 2^20 elements (approx 1e6 elements) for the largest PDL
       involved in a function.

       See PDL::ParallelCPU for an overview of the auto-pthread process.

         # Example turning on auto-pthreading for a target of 2 pthreads and for functions involving
         #   PDLs with greater than 1M elements
         set_autopthread_targ(2);
         set_autopthread_size(1);

         # Execute a pdl function, processing will split into two pthreads as long as
         #  one of the pdl-threaded dimensions is at least 2.
         $x = minimum($y);

         # Get the actual number of pthreads that were run.
         $actual_pthread = get_autopthread_actual();

   get_autopthread_size
       Get the current autopthread_size setting.

        $autopthread_size = get_autopthread_size();

       $autopthread_size is the mimumum size limit for auto_pthreading to occur, in M-elements or 2^20  elements
       (approx 1e6 elements) for the largest PDL involved in a function

       See PDL::ParallelCPU for an overview of the auto-pthread process.

AUTHOR

       Copyright  (C)  Karl  Glazebrook  (kgb@aaoepp.aao.gov.au),  Tuomas J. Lukka, (lukka@husc.harvard.edu) and
       Christian Soeller (c.soeller@auckland.ac.nz) 1997.  Modified, Craig DeForest  (deforest@boulder.swri.edu)
       2002.   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 v5.38.2                                       2024-04-10                                          Core(3pm)