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REF ARRAYS                                          John Gibson Feb 1996

        COPYRIGHT University of Sussex 1996. All Rights Reserved.

<<<<<<<<<<<<<<<<<<<<<                             >>>>>>>>>>>>>>>>>>>>>>
<<<<<<<<<<<<<<<<<<<<<      ARRAY PROCEDURES       >>>>>>>>>>>>>>>>>>>>>>
<<<<<<<<<<<<<<<<<<<<<                             >>>>>>>>>>>>>>>>>>>>>>

This REF file  details the  procedures which  deal with  the array  data
structure. It introduces array structures  and how they are  implemented
in Poplog. There is also a section  on sparse arrays, which can be  used
for  storing   associations   between  arbitrary   objects   (see   also

         CONTENTS - (Use <ENTER> g to access required sections)

  1   Introduction

  2   Predicates On Arrays

  3   Obtaining Array Parameters

  4   Constructing New Arrays

  5   Generic Data Structure Procedures on Arrays

  6   Miscellaneous
      6.1   Storing Arrays on Disk

  7   Examples of Arrays

  8   Sparse Arrays
      8.1   Examples of Sparse Arrays

  9   Related Documentation

1  Introduction

Arrays are data  structures which  enable information to  be stored  and
accessed on  the  basis of  a  set  of integer  subscripts,  where  each
subscript corresponds to a  separate 'dimension' of  the array; thus  an
N-dimensional array requires N such subscripts to access or update  each
of its elements.

    A one dimensional array is analogous to a vector except that vectors
can be indexed  only from  1 to their  length, whereas  arrays can  have
bounds covering  arbitrary  ranges  of  integers.  (For  information  on
vectors  also  see  REF * VECTORS,  * INTVEC,  * STRINGS,  * DATA,   and

    Because  computer   memory   cannot  directly   represent   multiple
dimensions, the elements of  an array actually have  to be stored in  an
underlying 1-dimensional  structure (e.g.  a vector),  each position  in
which corresponds to a particular set of N subscript values. The task of
the array accessing  mechanism is therefore  to convert a  given set  of
N-dimensional subscripts  into the  appropriate 1-dimensional  subscript
for accessing this structure.

    In Poplog, arrays are implemented as special procedures  constructed
by newanyarray.  Such a  procedure for  an N-dimensional  array  takes N
arguments,  and  includes  within  it  the  arrayvector,  that  is,  the
underlying 1-dimensional structure  in which the  elements of the  array
are in reality stored (which, despite  its name, need not actually  be a
vector although it usually is). When called, e.g.

        array(sub1, sub2, ..., subN)

the array  procedure  performs  the  computation  of  the  1-dimensional
subscript from the N values given, and supplies this to the  appropriate
access procedure for  the arrayvector structure  (which then returns  or
updates the specified element).

    An array  may have  any number  of elements  in a  given  dimension,
subscripted by any suitable  range of integers. That  is, an array  with
say, 30 in a particular dimension is not restricted to using  subscripts
1 to 30,  but can  use 0 to  29, 5  to 34, -10  to 19,  etc. An  array's
dimensions are  specified to  newanyarray by  supplying its  boundslist,
i.e. a list of the minimum and maximum subscripts in each dimension  (of
length 2 * N for an N-dimensional array). When called, array  procedures
mishap if any  of their subscript  arguments is not  in the  appropriate

    When using an array in general, it is not necessary to know how  its
elements are arranged in the arrayvector; however, this does need to  be
known when the latter needs to  be processed separately from the  array.
While in principle  many different  schemes are  possible, Poplog  (like
most systems) provides just two: arraying 'by row' or 'by column'. Since
the terms 'row' and 'column'  only make sense for 2-dimensional  arrays,
we shall not attempt to define them, but simply say that 'by row'  means
the elements are stored with subscripts increasing in significance  from
left  to  right,   and  'by  column'   with  subscripts  increasing   in
significance  from  right   to  left.  That   is,  letting  array   be a
3-dimensional array with subscripts 1 -  3 in each dimension, the  order
of the 3 * 3 * 3 = 27 elements in its arrayvector with the two different
schemes would be as follows:

    Arrayvector Subscript          By Row             By Column
    ---------------------          ------             ---------
             1                  array(1, 1, 1)      array(1, 1, 1)
             2                  array(2, 1, 1)      array(1, 1, 2)
             3                  array(3, 1, 1)      array(1, 1, 3)
             4                  array(1, 2, 1)      array(1, 2, 1)
             5                  array(2, 2, 1)      array(1, 2, 2)
             6                  array(3, 2, 1)      array(1, 2, 3)
             7                  array(1, 3, 1)      array(1, 3, 1)
             8                  array(2, 3, 1)      array(1, 3, 2)
             9                  array(3, 3, 1)      array(1, 3, 3)
             10                 array(1, 1, 2)      array(2, 1, 1)
             ...                ...                 ...
             26                 array(2, 3, 3)      array(3, 3, 2)
             27                 array(3, 3, 3)      array(3, 3, 3)

Note that  (as mentioned  above), the  arrayvector of  an array  is  not
limited to  being an  actual vector-class  structure. The  arguments  to
newanyarray allow the specification of any 'virtual' vector, in terms of
an 'vector init'  procedure and a  'subscriptor' procedure;  newanyarray
then calls the 'init' procedure  with an appropriate length argument  to
construct the arrayvector initially, and  the array procedure then  uses
the 'subscriptor' to store and retrieve elements.

    Note also that  two or more  arrays can  be made to  share the  same
arrayvector structure,  either in  whole or  in part  (for example,  one
array can be a sub-array of another).

    While arrays are  limited to  storing associations  between sets  of
integers and  arbitrary  values,  Poplog also  provides  mechanisms  for
storing associations  between arbitrary  objects  -- see  Sparse  Arrays
below  and  REF * PROPS.   See  also   REF * PROCEDURE  for   procedures
applicable to arrays as procedures in general.

2  Predicates On Arrays

As mentioned above, arrays are procedures: thus isprocedure is true  for
any array, and the datakey of an  array will be the same as the  datakey
of any procedure. (See REF * KEYS.)

isarray(item) -> array                                       [procedure]
        Returns a  true result  if  item is  either an  array  procedure
        itself,  or  is  a  closure   of  one  through  any  number   of
        sub-closures (i.e. the  pdpart of item  is examined  recursively
        until a non-closure is found, and then this is tested for  being
        an array). If item is an array procedure, or one is found inside
        a nest of closures, then that is returned, otherwise false.

        (This enables closures  of arrays  to be  recognised as  arrays,
        e.g. if array  is 3-dimensional array  then isarray will  return
        array when applied to the 2-dimensional array array(%2%), etc.)

isarray_by_row(array) -> bool                                [procedure]
        Returns true if  the array  array is  arrayed by  row, false  if
        arrayed by column.

3  Obtaining Array Parameters

boundslist(array) -> bounds_list                             [procedure]
        Given an array array,  returns its list  of minimum and  maximum
        subscripts in each dimension.

arrayvector(array) -> arrayvec                               [procedure]
arrayvec -> arrayvector(array)
        Returns/updates the  1-dimensional structure  used to  hold  the
        elements of the  array array.  The updater checks  that the  new
        arrayvec is the same data type as the old.

arrayvector_bounds(array) -> min_sub -> max_sub              [procedure]
        Returns the minimum  and maximum  subscripts used  by the  array
        array on  its arrayvector.  (Generally, min_sub  will be  1  and
        max_sub will be the number of  elements in the array; this  will
        not be the case, however, when array is actually a sub-array  of
        the arrayvector.)

array_subscrp(array) -> subscr_p                             [procedure]
        Returns the subscriptor procedure used to access elements in the
        arrayvector of the array array.

4  Constructing New Arrays

newanyarray  is  the  basic  procedure  for  constructing  arrays.   For
historical and  other  reasons,  the arguments  to  this  procedure  are
somewhat complicated, in that it can take a number of optional arguments
in various combinations. Essentially  though, the pieces of  information
it requires to construct a new array are quite straightforward, viz

    # A 2 * N list of minimum  and maximum subscripts for each of  the N
      dimensions (the  boundslist).  This is  used  to derive  both  the
      number of dimensions, and the size in each dimension (and thus the
      total number of elements in the array).

    # A specification for the  arrayvector to hold  the elements of  the
      array, and a subscriptor procedure with which to access and update
      it. These two  can be  specified in  a number  of different  ways,
      either as separate arguments or by a single argument which implies
      values for both together.

Other optional pieces  of information can  specify whether the  elements
are to be arrayed by row or by column, an initialisation for each  array
element, and (when the  new array is  to be a  sub-array of an  existing
one),  the  starting  offset  of  the  new  array  within  the  existing

newanyarray(bounds_list, element_init, arrayvec_spec,        [procedure]
    subscr_p, arrayvec_offset, by_row) -> array
        This procedure constructs and returns a new N-dimensional  array
        procedure array (where N >= 0). Its arguments are as follows:

            A list of 2 * N integers whose elements are alternately  the
            minimum and maximum subscript in each dimension, i.e.

                [% min1, max1, min2, max2, ..., minN, maxN %]

            This  argument  is  always  required.  An  empty  boundslist
            specifies  a  0-dimensional  array  (an  object  which  when
            applied to zero subscripts returns its single value).

            This argument is optional,  and specifies an  initialisation
            for  each  array  element:  its  interpretation  depends  on
            whether it is a procedure or not.

            If a procedure, it is assumed to take N subscript  arguments
            and to return a (possibly different) initialising value  for
            each position in the array. newanyarray will then initialise
            the array  by  applying  the  procedure  in  turn  to  every
            combination of subscripts, i.e.

                 element_init(sub1, sub2, ..., subN)
                     -> array(sub1, sub2, ..., subN)

            (Note that the order in which the combinations of subscripts
            are generated is UNDEFINED).

            Otherwise, if element_init is not a procedure, every element
            of the array is simply initialised to that value.  (However,
            to distinguish it from  bounds_list, this argument must  not
            be a list -- if you wish to initialise the elements to  some
            list, you  must  use  a procedure  returning  the  list,  as

            This  argument  is  always   required,  and  specifies   the
            arrayvector structure to  be used to  store the elements  of
            the array. It must supply either an existing structure, or a
            procedure to construct a new  one: for the former the  value
            may be either

                (a) an actual vector-class structure (e.g. full  vector,
                    string, intvec, shortvec, etc);

                (b) an array procedure whose arrayvector is to be used;

            while for the latter it may be

                (c) a 'vector init' procedure p (which will be called as

                      p(size) -> arrayvec

                    where size is the number of elements in the array);

                (d) a vector-class key whose class_init procedure is  to
                    be used (see REF * DEFSTRUCT, * KEYS).

            All cases except  (c) also implicitly  supply a  subscriptor
            procedure  for  the  structure,  making  the  next  argument
            (subscr_p) optional; for case (c), subscr_p must be present.

            If an existing structure  is specified with  (a) or (b),  it
            must of course be large enough to accommodate the new  array

            Note that if element_init is omitted, the initial values  of
            the  array  elements  will  depend  upon  the  arrayvec_spec
            argument (i.e. for a new structure they will be whatever the
            init procedure  initialises them  to,  and for  an  existing
            structure they will have their current values).

            A subscriptor procedure for accessing and updating  elements
            of the arrayvector,  i.e. a  procedure with  updater of  the

                subscr_p(subscript, arrayvec) -> element
                element -> subscr_p(subscript, arrayvec)

            This argument may always be supplied, but is essential  only
            when arrayvec_spec specifies a  'vector init' procedure;  in
            all  other  cases,  i.e.  an  existing  array,  an  existing
            vector-class structure or vector-class key, the  subscriptor
            procedure derived from that is used if subscr_p is omitted.

            An optional integer argument specifying the starting  offset
            of the new array's elements within an existing array  vector
            got from arrayvec_spec (i.e. this argument is illegal in all
            cases where a new arrayvector  has to be constructed).  Note
            that this is an offset, not a subscript, i.e. 0 means  start
            at the first element (the default), 1 at the second, etc.

            The existing structure must  be large enough to  accommodate
            all the array elements starting at the given offset.

            An optional argument specifying  whether the array  elements
            are to be arrayed by row or by column: if supplied, it  must
            be a  boolean,  true meaning  by  row or  false  meaning  by
            column. If  omitted, the  value of  poparray_by_row is  used

poparray_by_row -> bool                                       [variable]
bool -> poparray_by_row
        This boolean variable controls the  order in which the  elements
        of an array produced by newanyarray are stored in its underlying
        vector, and supplies the default  value for the BY_ROW  argument

newarray(bounds_list, element_init) -> full_array            [procedure]
        This procedure provides a  simpler interface to newanyarray  for
        constructing arrays of full items, and is just

                newanyarray(% vector_key %)

        i.e. use standard full vectors to store the array elements  (see
        REF * VECTORS).

newsarray(bounds_list, element_init) -> char_array           [procedure]
        Same as newarray,  but using strings  rather than full  vectors,

                newanyarray(% string_key %)

        (see REF * STRINGS).

5  Generic Data Structure Procedures on Arrays

The  generic   data  structure   procedures  described   in   REF * DATA
(datalength, appdata,  explode, fill,  and others  defined in  terms  of
those) can all be applied to arrays:  they treat an array as the set  of
its arrayvector  elements between  the  minimum and  maximum  subscripts
given by the arrayvector_bounds. Thus, for example, if

        arrayvector_bounds(array) -> min_sub -> max_sub

then datalength(array) will be

        max_sub - min_sub + 1

Similarly, appdata(array, p) will apply the procedure p to the value  of
each arrayvector element from min_sub to max_sub inclusive, and so on.

    The procedure copy when  applied to an array  copies both the  array
procedure  and  its  arrayvector  (so   that  the  copy  is   completely
independent of the original).

6  Miscellaneous

in_array                                                        [syntax]
        This * FOR_FORM allows  iteration over data  in arrays, much  as
        other forms allow iteration over data in lists and vectors.
        Its format is:

            for var1, var2, ...
                with_index ivar
                in_array array1, array2, ...
                updating_last n
                in_region list
                of_dimension d

        See HELP * in_array for details.

arrayscan(boundslist, p)                                     [procedure]
        Given a boundlist  of array minimum  and maximum subscripts  (as
        supplied to newanyarray, etc), applies the procedure p to  every
        combination of subscripts  in that range  (ordered 'by  column',
        i.e.  with  the  last  subscript  varying  fastest).  For   each
        combination, p is given a list of subscripts of length N,  where
        boundslist is of length 2 * N. For example, the following

            arrayscan([3 5 1 3], spr);

        will produce

            [3 1] [3 2] [3 3] [4 1] [4 2] [4 3] [5 1] [5 2] [5 3]

        The for-forms * in_array and * in_region provide alternatives to

6.1  Storing Arrays on Disk
The libraries LIB * ARRAYFILE  and LIB * DATAFILE may  be used to  store
arrays on disk, and be subsequently read back into Poplog. arrayfile  is
the more efficient and space-economical procedure; however, it can  only
be  used  on  arrays  whose  arrayvector  is  a  'byte-accessible'  data
structure. datafile should be used to save arrays whose arrayvector is a
full vector.

arrayfile(filename) -> array                                 [procedure]
arrayfile(filename, array) -> array
array -> arrayfile(filename)
        Stores the array array in the disk file named by filename, using
        a special  (machine-specific) data  format. The  arrayvector  of
        array  must  be  a   byte-accesible  structure.  The   following
        information is recorded:

            # The number of dimensions, and bounds, of array
            # The dataword of the array's arrayvector
            # Whether array is ordered by row or column
            # The contents of the arrayvector of array

        In its non-updater form, arrayfile reads the information  stored
        in filename, and returns a new array constructed from it. If the
        optional second argument array is  specified, the data saved  in
        filename is  written  into it;  no  new array  is  created.  See
        HELP * ARRAYFILE for examples.

The procedure datafile is documented in REF * datafile.

7  Examples of Arrays

The following:

        constant procedure
            multab = newarray([1 12 1 12], nonop *);

will create and assign to multab a  12 x 12 2-dimensional array each  of
whose elements  can  be a  full  Poplog  item, and  where  each  element
subscripted by I, J is initialised to I * J (in other words, multab is a
multiplication table):

        multab(4, 3) =>
        ** 12

To turn an existing string of "noughts-and-crosses" into an array:

        constant procedure
            oxo = newanyarray([1 3 1 3], '0 X X00 X');

        cucharout(oxo(1, 3));

If, in the  previous example, we  make the  array by row  instead of  by
column, the mapping between  subscripts and positions  in the string  is

        constant procedure
            oxo2 = newanyarray([1 3 1 3], '0 X X00 X', false);

        cucharout(oxo2(1, 3));

8  Sparse Arrays

It is  sometimes necessary  to use  large arrays  in which  many of  the
elements will all have some default value, and only relatively few  will
have a 'significant' value, i.e. different from the default. Represented
as ordinary arrays,  such 'sparse'  arrays are very  wasteful of  space,
since  the  arrayvector  must  allow  storage  cells  for  each  element
corresponding to a given combination of subscripts, and yet many or most
of these will just repeat the default value.

    Rather than using  an vector-type  structure to  hold the  elements,
Poplog sparse  arrays  are therefore  implemented  as  multi-dimensional
properties, that is, they use a tree of properties to associate each set
of  subscripts  to  a  value  (see  REF * PROPS  for  a  description  of
properties). This means  that only  the 'significant'  elements take  up
space, and  moreover,  the  'subscripts' are  not  restricted  to  being
integers, but can  be any  Poplog items. (Although  this approach  saves
space, it  does however  mean that  accessing sparse  array elements  is
slower than for ordinary arrays.)

    A sparse array can also have an 'active default' -- i.e. a procedure
that is run to  decide what the  default value of  an element should  be
when  it  has  not  been  assigned  a  value  explicitly;  for   certain
applications this can save even more space.

newanysparse(dimensions, default_item)     -> sparse_array   [procedure]
newanysparse(dimensions, default_p, apply) -> sparse_array
        Constructs  and  returns  a   new  N-dimensional  sparse   array
        procedure (where N >= 1). This can be called as

            sparse_array(sub1, sub2, ..., subN) -> element
            element -> sparse_array(sub1, sub2, ..., subN)

        to access or update the element associated with a given set of N
        'subscripts' (which  can be  any  items at  all, but  note  that
        subscript equality is on the basis of ==, not =).

        The dimensions argument  specifies the number  of dimensions  N,
        either directly as an  integer or as an  N-element list. In  the
        latter case, the elements  of the list  are integers giving  the
        table sizes  to be  used for  the properties  employed for  each
        dimension; in  the former  case, when  dimensions is  simply  an
        integer, the table size in  each dimension defaults to 20.  (The
        table size for a property affects how fast items are accessed in
        it -- see REF * PROPS.  For maximum speed  it should be  roughly
        the 'size', i.e. number of  different subscript values, in  each
        dimension; also, subscripts are dealt  with from right to  left,
        so that putting  'larger' dimensions  to the  left of  'smaller'
        ones will increase efficiency.)

        The remaining argument(s) specify the default value for elements
        of  the  array:  in  the  first  form  of  the  call,  the  item
        default_item is the fixed default  value for every element.  The
        second form specifies an  'active default' procedure  default_p,
        and  to  distinguish  this  from   the  first  form  (in   which
        default_item could be  a procedure), the  last argument must  be
        the procedure apply.  default_p is  expected to  be a  procedure
        which takes N 'subscript' arguments and returns a default value,

                default_p(sub1, sub2, ..., subN) -> value

        (this is comparable to a procedure specified as the element_init
        argument to newanyarray).

newsparse(dimensions) -> sparse_array                        [procedure]
        This is a  simpler version  of newanysparse which  has the  word
        "undef" as a fixed default_item, i.e. same as


8.1  Examples of Sparse Arrays
The first example is an sparse  array representing points in 3-D  space,
where each element in the array is a list of points to which that  point
is connected  to; each  point is  defaults to  being connected  just  to

        define lconstant here(x, y, z);
            lvars x, y, z;
            [[^x ^y ^z]]

        constant procedure
            connected = newanysparse(3, here, apply);

In this array, each cell  contains a list of  the points it is  directly
connected to:

        connected(1, 2, 3) =>
        ** [[1 2 3]]
        connected(8, 9, 10) =>
        ** [[8 9 10]]

Some explicit connectivity can then be added:

        [8 9 10] :: connected(1, 2, 3) -> connected(1, 2, 3);

        connected(1,2,3) =>
        ** [[8 9 10] [1 2 3]]

The second example creates  a sparse array in  which the 3  'dimensions'
are English words,  foreign languages,  and modalities,  and where  each
element is the translation  of the English  word into the  corresponding
language  and  modality   (the  default   value  being   false  for   no

        constant procedure
            dictionary = newanysparse(3, false);

        "bonjour" -> dictionary("hello", "french", "polite");
        "ola" -> dictionary("hello", "spanish", "familiar");

        dictionary("hello", "french", "polite") =>
        ** bonjour
        dictionary("hello", "french", "vulgar") =>
        ** <false>

9  Related Documentation

    Information on Poplog data types and how they are represented.

    Describes the information  associated with each  data type and  some
    general procedures for  manipulating data and  creating fast  access

    Describes standard  full  vectors  (vectors  containing  any  Poplog

    Describes intvecs (vectors  containing 32 bit  signed integers)  and
    shortvecs (vectors containing 16 bit signed integers).

    Describes byte vectors.

    Information  on  properties   (hash-tables,  indexed  by   arbitrary

    Describes syntax for creating new vector or record classes.

    An introduction to arrays in Pop-11.

    Describes a particular type of  property for associating items  with
    structures on the basis of structure equality.

--- C.all/ref/arrays
--- Copyright University of Sussex 1996. All rights reserved.