filters.stats

The Stats Filter calculates the minimum, maximum and average (mean) values of dimensions. On request it will also provide an enumeration of values of a dimension and skewness and kurtosis.

The output of the stats filter is metadata that can be stored by writers or used through the PDAL API. Output from the stats filter can also be quickly obtained in JSON format by using the command “pdal info –stats”.

Note

The filter can compute both sample and population statistics. For kurtosis, the filter can also compute standard and excess kurtosis. However, only a single value is reported for each statistic type in metadata, and that is the sample statistic, rather than the population statistic. For kurtosis the sample excess kurtosis is reported. This seems to match the behavior of many other software packages.

Example

[
    "input.las",
    {
        "type":"filters.stats",
        "dimensions":"X,Y,Z,Classification",
        "enumerate":"Classification"
    },
    {
        "type":"writers.las",
        "filename":"output.las"
    }
]

Options

dimensions

A comma-separated list of dimensions whose statistics should be processed. If not provided, statistics for all dimensions are calculated.

enumerate

A comma-separated list of dimensions whose values should be enumerated. Note that this list does not add to the list of dimensions that may be provided in the dimensions option.

count

Identical to the enumerate option, but provides a count of the number of points in each enumerated category.

global

A comma-separated list of dimensions for which global statistics (median, mad, mode) should be calculated.

advanced

Calculate advanced statistics (skewness, kurtosis). [Default: false]

where

An expression that limits points passed to a filter. Points that don’t pass the expression skip the stage but are available to subsequent stages in a pipeline. [Default: no filtering]

where_merge

A strategy for merging points skipped by a ‘where’ option when running in standard mode. If true, the skipped points are added to the first point view returned by the skipped filter. If false, skipped points are placed in their own point view. If auto, skipped points are merged into the returned point view provided that only one point view is returned and it has the same point count as it did when the filter was run. [Default: auto]