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This module implements a data type `cube`
for representing multidimensional cubes.

Table F-3 shows the
valid external representations for the `cube` type. `x`,
`y`, etc. denote floating-point
numbers.

Table F-3. Cube External Representations

x |
A one-dimensional point (or, zero-length one-dimensional interval) |

(x) |
Same as above |

x1,x2,...,xn |
A point in n-dimensional space, represented internally as a zero-volume cube |

(x1,x2,...,xn) |
Same as above |

(x),(y) |
A one-dimensional interval starting at x and ending at y or vice versa; the order does
not matter |

[(x),(y)] |
Same as above |

(x1,...,xn),(y1,...,yn) |
An n-dimensional cube represented by a pair of its diagonally opposite corners |

[(x1,...,xn),(y1,...,yn)] |
Same as above |

It does not matter which order the opposite corners of a
cube are entered in. The `cube` functions
automatically swap values if needed to create a uniform
"lower left — upper right" internal
representation.

White space is ignored, so `[( x),(y)]` is the same as

Values are stored internally as 64-bit floating point numbers. This means that numbers with more than about 16 significant digits will be truncated.

The `cube` module includes a GiST
index operator class for `cube` values. The
operators supported by the GiST operator class are shown in
Table F-4.

Table F-4. Cube GiST Operators

Operator | Description |
---|---|

a = b |
The cubes a and b are identical. |

a && b |
The cubes a and b overlap. |

a @> b |
The cube a contains the cube b. |

a <@ b |
The cube a is contained in the cube b. |

(Before PostgreSQL 8.2, the containment operators `@>` and `<@` were
respectively called `@` and `~`. These names are still available, but are
deprecated and will eventually be retired. Notice that the old
names are reversed from the convention formerly followed by the
core geometric data types!)

The standard B-tree operators are also provided, for example

These operators do not make a lot of sense for any practical purpose but sorting. These operators first compare (a) to (c), and if these are equal, compare (b) to (d). That results in reasonably good sorting in most cases, which is useful if you want to use ORDER BY with this type.Table F-5 shows the available functions.

Table F-5. Cube Functions

cube(float8) returns
cube |
Makes a one dimensional cube with both coordinates
the same. cube(1) ==
'(1)' |

cube(float8, float8) returns
cube |
Makes a one dimensional cube. cube(1,2) == '(1),(2)' |

cube(float8[]) returns
cube |
Makes a zero-volume cube using the coordinates
defined by the array. cube(ARRAY[1,2]) == '(1,2)' |

cube(float8[], float8[])
returns cube |
Makes a cube with upper right and lower left
coordinates as defined by the two arrays, which must be
of the same length. cube('{1,2}'::float[], '{3,4}'::float[]) ==
'(1,2),(3,4)' |

cube(cube, float8) returns
cube |
Makes a new cube by adding a dimension on to an
existing cube with the same values for both parts of
the new coordinate. This is useful for building cubes
piece by piece from calculated values. cube('(1)',2) == '(1,2),(1,2)' |

cube(cube, float8, float8)
returns cube |
Makes a new cube by adding a dimension on to an
existing cube. This is useful for building cubes piece
by piece from calculated values. cube('(1,2)',3,4) == '(1,3),(2,4)' |

cube_dim(cube) returns
int |
Returns the number of dimensions of the cube |

cube_ll_coord(cube, int)
returns double |
Returns the n'th coordinate value for the lower left corner of a cube |

cube_ur_coord(cube, int)
returns double |
Returns the n'th coordinate value for the upper right corner of a cube |

cube_is_point(cube) returns
bool |
Returns true if a cube is a point, that is, the two defining corners are the same. |

cube_distance(cube, cube)
returns double |
Returns the distance between two cubes. If both cubes are points, this is the normal distance function. |

cube_subset(cube, int[])
returns cube |
Makes a new cube from an existing cube, using a
list of dimension indexes from an array. Can be used to
find both the LL and UR coordinates of a single
dimension, e.g. cube_subset(cube('(1,3,5),(6,7,8)'),
ARRAY[2]) = '(3),(7)'. Or can be used to drop
dimensions, or reorder them as desired, e.g. cube_subset(cube('(1,3,5),(6,7,8)'),
ARRAY[3,2,1,1]) = '(5, 3, 1, 1),(8, 7, 6,
6)'. |

cube_union(cube, cube) returns
cube |
Produces the union of two cubes |

cube_inter(cube, cube) returns
cube |
Produces the intersection of two cubes |

cube_enlarge(cube c, double r,
int n) returns cube |
Increases the size of a cube by a specified radius in at least n dimensions. If the radius is negative the cube is shrunk instead. This is useful for creating bounding boxes around a point for searching for nearby points. All defined dimensions are changed by the radius r. LL coordinates are decreased by r and UR coordinates are increased by r. If a LL coordinate is increased to larger than the corresponding UR coordinate (this can only happen when r < 0) than both coordinates are set to their average. If n is greater than the number of defined dimensions and the cube is being increased (r >= 0) then 0 is used as the base for the extra coordinates. |

I believe this union:

select cube_union('(0,5,2),(2,3,1)', '0'); cube_union ------------------- (0, 0, 0),(2, 5, 2) (1 row)

does not contradict common sense, neither does the intersection

select cube_inter('(0,-1),(1,1)', '(-2),(2)'); cube_inter ------------- (0, 0),(1, 0) (1 row)

In all binary operations on differently-dimensioned cubes, I assume the lower-dimensional one to be a Cartesian projection, i. e., having zeroes in place of coordinates omitted in the string representation. The above examples are equivalent to:

cube_union('(0,5,2),(2,3,1)','(0,0,0),(0,0,0)'); cube_inter('(0,-1),(1,1)','(-2,0),(2,0)');

The following containment predicate uses the point syntax, while in fact the second argument is internally represented by a box. This syntax makes it unnecessary to define a separate point type and functions for (box,point) predicates.

select cube_contains('(0,0),(1,1)', '0.5,0.5'); cube_contains -------------- t (1 row)

For examples of usage, see the regression test `sql/cube.sql`.

To make it harder for people to break things, there is a
limit of 100 on the number of dimensions of cubes. This is set
in `cubedata.h` if you need something
bigger.

Original author: Gene Selkov, Jr. `<selkovjr@mcs.anl.gov>`

,
Mathematics and Computer Science Division, Argonne National
Laboratory.

My thanks are primarily to Prof. Joe Hellerstein (http://db.cs.berkeley.edu/jmh/) for elucidating the gist of the GiST (http://gist.cs.berkeley.edu/), and to his former student, Andy Dong (http://best.me.berkeley.edu/~adong/), for his example written for Illustra, http://best.berkeley.edu/~adong/rtree/index.html. I am also grateful to all Postgres developers, present and past, for enabling myself to create my own world and live undisturbed in it. And I would like to acknowledge my gratitude to Argonne Lab and to the U.S. Department of Energy for the years of faithful support of my database research.

Minor updates to this package were made by Bruno Wolff III
`<bruno@wolff.to>`

in
August/September of 2002. These include changing the precision
from single precision to double precision and adding some new
functions.

Additional updates were made by Joshua Reich `<josh@root.net>`

in July
2006. These include `cube(float8[],
float8[])` and cleaning up the code to use the V1 call
protocol instead of the deprecated V0 protocol.