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Uber Filter

PCGEx | Uber Filter

Combine multiple filters

The Uber Filter node combines multiple filters to refine points within a dataset. You can either split the dataset based on filters results or write the result to an attribute.


In
Points to be filtered
Filters
Filters to be evaluated
Inside
Points that passed the filters
Outside
Points that didn't pass the filters.

Table of content


The Uber Filter node leverages any and all the filters available as part of the ecosystem to filter out points inside individual datasets. Alternatively, you can choose to only write the combined filters result as a bool attribute.

details/filter-ecosystem/filter-uber-filter-lead.png

Properties


Property Description
Settings
Mode How to ouput data.
See below.
Result Attribute Name
bool
Name of the attribute the filter result will be written to.
Swap If enabled, inverts the combined result of the filters.
Mode
Partition Split input dataset in either Inside (filter passed) or Outside (filters failed) outputs.
Write Preserve input and write the result of the filter to an attribute.

Available Filters


🝖 AND / OR (Group)

Group multiple filters to set up complex AND/OR branches.

🝖 Compare Nearest (Numeric)

The Numeric Comparison Filter compares the arithmetic value of an attribute against the closest point from another dataset.

🝖 Compare (Numeric)

The Numeric Comparison Filter compares the arithmetic value of two attributes

🝖 Compare (String)

Compares two string-like attributes against each other.

🝖 Bool

Performs a simple boolean comparison, converting numeric values to true (> 0) or false (<= 0).

🝖 Within Range

Checks if an attribute value falls within a specified range.

🝖 Dot Product

Compares the dot product of two direction vectors against a third value.

🝖 Modulo Comparison

Compares the modulo of two attributes against a third operand, with configurable comparisons and tolerance.

🝖 Bounds

Checks if a point is inside or outside the provided bounds, with options for bounds types and an epsilon adjustment.

🝖 Bitmask

Checks specific flags in an int64 bitmask attribute with configurable mask types, comparisons, and an option to invert results.

🝖 Random

Random filter.

🝖 Mean Value

The Mean Value Filter compares per-point values of an attribute against the mean statistical value of that same attribute.

🝖 Self Compare (Numeric)

Compares the numeric value at one index against the same attribute at another index.

🝖 Self Compare (String)

Compares the string value at one index against the same attribute at another index.

🝖 Spline Inclusion

Checks against how a point is included in a spline.

🝖 Path Inclusion

Checks against how a point is included in a path.