A
SizeSequence
object
efficiently maintains an ordered list
of sizes and corresponding positions.
One situation for which
SizeSequence
might be appropriate is in a component
that displays multiple rows of unequal size.
In this case, a single
SizeSequence
object could be used to track the heights
and Y positions of all rows.
Another example would be a multi-column component,
such as a JTable
,
in which the column sizes are not all equal.
The JTable
might use a single
SizeSequence
object
to store the widths and X positions of all the columns.
The JTable
could then use the
SizeSequence
object
to find the column corresponding to a certain position.
The JTable
could update the
SizeSequence
object
whenever one or more column sizes changed.
The following figure shows the relationship between size and position data
for a multi-column component.
In the figure, the first index (0) corresponds to the first column,
the second index (1) to the second column, and so on.
The first column's position starts at 0,
and the column occupies size0 pixels,
where size0 is the value returned by
getSize(0)
.
Thus, the first column ends at size0 - 1.
The second column then begins at
the position size0
and occupies size1 (getSize(1)
) pixels.
Note that a SizeSequence
object simply represents intervals
along an axis.
In our examples, the intervals represent height or width in pixels.
However, any other unit of measure (for example, time in days)
could be just as valid.
Implementation Notes
Normally when storing the size and position of entries,
one would choose between
storing the sizes or storing their positions
instead. The two common operations that are needed during
rendering are:
getIndex(position)
and
setSize(index, size)
.
Whichever choice of internal format is made one of these
operations is costly when the number of entries becomes large.
If sizes are stored, finding the index of the entry
that encloses a particular position is linear in the
number of entries. If positions are stored instead, setting
the size of an entry at a particular index requires updating
the positions of the affected entries, which is also a linear
calculation.
Like the above techniques this class holds an array of N integers
internally but uses a hybrid encoding, which is halfway
between the size-based and positional-based approaches.
The result is a data structure that takes the same space to store
the information but can perform most operations in Log(N) time
instead of O(N), where N is the number of entries in the list.
Two operations that remain O(N) in the number of entries are
the insertEntries
and removeEntries
methods, both
of which are implemented by converting the internal array to
a set of integer sizes, copying it into the new array, and then
reforming the hybrid representation in place.