[postgis-devel] [PostGIS] #935: [raster] ST_Quantile and ST_ApproxQuantile

[PostGIS]

#935: [raster] ST_Quantile and ST_ApproxQuantile
----------------------------+-----------------------------------------------
 Reporter:  dustymugs       |       Owner:  pracine              
     Type:  task            |      Status:  new                  
 Priority:  medium          |   Milestone:  PostGIS Raster Future
Component:  postgis raster  |     Version:  trunk                
 Keywords:                  |  
----------------------------+-----------------------------------------------
 In addition to determining the histogram of a raster, providing the
 ability to compute quantiles permits a user to reference a value in the
 context of the sample or population.  Thus, a value could be examined to
 be at the raster's 25%, 50%, 75% percentile.

 http://en.wikipedia.org/wiki/Quantile

 ST_Quantile variations:

 1. ST_Quantile(rast raster, nband int, hasnodata boolean, quantiles double
 precision[]) -> set of records

     nband: index of band to process on

     hasnodata: if FALSE, any pixel who's value is nodata is ignored.

     quantiles: array of percentages to compute values for

 {{{
 ST_Quantile(rast, 1, FALSE, ARRAY[0.1, 0.3, 0.7])

 ST_Quantile(rast, 1, TRUE, ARRAY[0.2])

 ST_Quantile(rast, 1, FALSE, ARRAY[0, 1])
 }}}

 2. ST_Quantile(rast raster, nband int, quantiles double precision[]) ->
 set of records

     "hasnodata" is assumed to be FALSE

 {{{
 ST_Quantile(rast, 1, ARRAY[0.1, 0.3, 0.7])
 }}}

 3. ST_Quantile(rast raster, nband int, hasnodata boolean) -> set of
 records

     "quantiles" assumed to be ARRAY[0, 0.25, 0.5, 0.75, 1]

 4. ST_Quantile(rast raster, nband int) -> set of records

     "hasnodata" is assumed to be FALSE and "quantiles" assumed to be
 ARRAY[0, 0.25, 0.5, 0.75, 1]

 5. ST_Quantile(rast raster, quantiles double precision[]) -> set of
 records

     "nband" is assumed to be 1 and "hasnodata" is FALSE

 6. ST_Quantile(rast raster, nband int, quantile double precision) ->
 record

     quantile: the single percentile to compute

 7. ST_Quantile(rast raster, quantile double precision) -> record

     "nband" is assumed to be 1

 8. ST_Quantile(rast raster) -> set of records

     "nband" is assumed to be 1 and "quantiles" assumed to be ARRAY[0,
 0.25, 0.5, 0.75, 1]

 ST_ApproxQuantile adds a "sample_percent" indicating the percentage of the
 raster to sample

 1. ST_ApproxQuantile(rast raster, nband int, hasnodata boolean,
 sample_percent double precision, quantiles double precision[]) -> set of
 records

     nband: index of band to process on

     hasnodata: if FALSE, any pixel who's value is nodata is ignored

     sample_percent: a value between 0 and 1 indicating the percentage of
 the raster band's pixels to consider when computing the quantiles

     quantiles: array of percentages to compute values for

 {{{
 ST_ApproxQuantile(rast, 1, FALSE, 0.1, ARRAY[0.1, 0.3, 0.7])

 ST_ApproxQuantile(rast, 1, TRUE, .2, ARRAY[0.2])

 ST_ApproxQuantile(rast, 1, FALSE, 0.3, ARRAY[0, 1])
 }}}

 2. ST_ApproxQuantile(rast raster, nband int, sample_percent double
 precision, quantiles double precision[]) -> set of records

     "hasnodata" is assumed to be FALSE

 {{{
 ST_ApproxQuantile(rast, 1, .05, ARRAY[0.1, 0.3, 0.7])
 }}}

 3. ST_ApproxQuantile(rast raster, nband int, sample_percent double
 precision) -> set of records

     "hasnodata" is assumed to be FALSE and "quantiles" assumed to be
 ARRAY[0, 0.25, 0.5, 0.75, 1]

 4. ST_ApproxQuantile(rast raster, sample_percent double precision,
 quantiles double precision[]) -> set of records

     "nband" is assumed to be 1

 5. ST_ApproxQuantile(rast raster, nband int, sample_percent double
 precision, quantile double precision) -> record

     quantile: the single percentile to compute

 6. ST_ApproxQuantile(rast raster, sample_percent double precision,
 quantile double precision) -> record

     "nband" is assumed to be 2

 7. ST_ApproxQuantile(rast raster, sample_percent double precision) -> set
 of records

     "nband" is assumed to be 1 and "quantiles" assumed to be ARRAY[0,
 0.25, 0.5, 0.75, 1]

 8. ST_ApproxQuantile(rast raster, nband int, quantile double precision) ->
 record

     "sample_percent" assumed to be 0.1

 9. ST_ApproxQuantile(rast raster, quantiles double precision[]) -> set of
 records

     "nband" is assumed to be 1 and "sample_percent" assumed to be 0.1

 10. ST_ApproxQuantile(rast raster, quantile double precision) -> record

     "nband" assumed to be 1 and "sample_percent" assumed to be 0.1

 11. ST_ApproxQuantile(rast raster, nband int) -> set of records

     "quantiles" assumed to be ARRAY[0, 0.25, 0.5, 0.75, 1] and
 "sample_percent" assumed to be 0.1

 12. ST_ApproxQuantile(rast raster) -> set of records

     "nband" is assumed to be 1, "quantiles" assumed to be ARRAY[0, 0.25,
 0.5, 0.75, 1] and "sample_percent" assumed to be 0.1

-- 
Ticket URL: <http://trac.osgeo.org/postgis/ticket/935>
PostGIS <http://trac.osgeo.org/postgis/>
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