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Attribute Context Menu

Commands available when right-clicking an Attribute in the Data Tree. Attributes are data channels attached to point clouds or meshes, containing scalar or vector values for each point or triangle (e.g., elevation, curvature, RGB colour, classifications).

Transforms​

Normalise​

Menu name: Normalize Tooltip Normalise attribute values to 0-1 range.

What it does Scales attribute values linearly to the range [0, 1]. The minimum value becomes 0, the maximum becomes 1, and all other values are scaled proportionally. The original attribute is preserved, and a new normalised attribute is created. This transform is useful for comparing attributes with different units or scales.

When to use it

  • Preparing attributes for machine learning or classification
  • Comparing attributes with different value ranges
  • Creating dimensionless versions of physical quantities
  • Before combining multiple attributes in calculations

Notes Creates new attribute with "_Normalised" suffix. Original attribute unchanged. For attributes with min=max (constant values), all values become 0. Filter limits are adjusted accordingly to the new range.

Z Score​

Menu name: Z Score Tooltip Transform to Z-scores (standard deviations from mean).

What it does Transforms attribute values to Z-scores by subtracting the mean and dividing by the standard deviation. Resulting values represent how many standard deviations each value is from the mean. Values near 0 are close to average, large positive/negative values are outliers. Creates a new Z-score attribute.

When to use it

  • Identifying statistical outliers
  • Comparing values across attributes with different scales
  • Standardising data for statistical analysis
  • Highlighting unusual values in datasets

Notes Z-scores typically range from -3 to +3, with ~99.7% of values within this range for normally distributed data. Values beyond ±3 are likely outliers. New attribute has "_ZScore" suffix.

Log Transform​

Menu name: Log Transform Tooltip Apply logarithmic transformation.

What it does Applies natural logarithm (ln) transformation to attribute values. This compresses large values more than small values, making highly skewed distributions more symmetric. Useful for attributes spanning multiple orders of magnitude. Creates new log-transformed attribute.

When to use it

  • Visualising attributes with very large ranges (e.g., permeability, concentration)
  • Normalising right-skewed distributions
  • Preparing data for statistical analysis assuming log-normality
  • Improving colour scale representation of wide-range data

Notes

Positive Values Only

Only works on positive values. Zero or negative values are set to NaN or a small positive value. Consider adding a constant to shift all values positive if needed.

Result is ln(x). For log base 10, use Calculator with log10() function.

Square Root​

Menu name: Square Root Tooltip Apply square root transformation.

What it does Applies square root transformation to attribute values. This moderately compresses large values, making moderately skewed distributions more symmetric. Less aggressive than log transform. Creates new square-root-transformed attribute.

When to use it

  • Reducing moderate positive skewness
  • Stabilising variance in count data
  • Improving visualisation of clustered data
  • Moderate compression of value ranges

Notes Only works on non-negative values. Negative values are set to NaN. Less dramatic than log transform. Result is √x. New attribute has "_Sqrt" suffix.

Exponential​

Menu name: Exponential Tooltip Apply exponential transformation.

What it does Applies exponential transformation (e^x) to attribute values. This is the inverse of log transform and expands value ranges, amplifying differences. Small input changes produce large output changes. Creates new exponential-transformed attribute.

When to use it

  • Reversing log transformations
  • Amplifying small differences
  • Creating exponentially weighted values
  • Transforming log-scale data back to original scale

Notes

Range Expansion

Exponential transformation can create very large values quickly. Input values >10 may produce overflow. Consider normalising input first if values are large.

Result is e^x. New attribute has "_Exp" suffix.

Cox-Box Transform​

Menu name: Cox-Box Transform Tooltip Apply Cox-Box power transformation.

What it does Opens dialogue to specify lambda parameter. Applies Box-Cox power transformation, a family of transformations that includes log (λ=0), square root (λ=0.5), inverse (λ=-1), and identity (λ=1) as special cases. The transformation is (x^λ - 1)/λ, designed to normalise distributions. Creates new transformed attribute.

When to use it

  • Finding optimal transformation to normalise skewed data
  • Preparing data for statistical analysis assuming normality
  • When simple log or square root transforms don't fully normalise data
  • Systematic transformation selection based on data distribution

Notes Requires positive values. Lambda parameter typically ranges -2 to +2. Lambda=0 is equivalent to log transform. Optimal lambda can be estimated from data histogram.

Clamp to Filter​

Menu name: Clamp to Filter Tooltip Clamp values to current filter limits.

What it does Sets all attribute values outside the current filter range to the filter limit values. Values below the minimum filter become the minimum, values above the maximum become the maximum. Values within range are unchanged. This "clamps" outliers to the filter boundaries. Modifies the attribute in place.

When to use it

  • Removing extreme outliers whilst preserving data structure
  • Constraining values to a valid range
  • Preparing attributes for operations that don't handle outliers well
  • Limiting value ranges for visualisation

Notes

In-Place Modification

Modifies the attribute directly - cannot be undone except by reloading original data. Ensure filter limits are set correctly before applying. Use "Duplicate" on parent object first if you might need original values.

Clip to Filter​

Menu name: Clip to Filter Tooltip Remove values outside filter limits.

What it does Sets all attribute values outside the current filter range to NaN (not a number / missing value). Points or triangles with clipped values are excluded from visualisations and analyses. Unlike "Clamp", values are not replaced with boundaries but are marked as missing. Modifies attribute in place.

When to use it

  • Removing outliers completely from analysis
  • Creating masks based on attribute ranges
  • Excluding invalid or erroneous values
  • Preparing filtered subsets for export

Notes Values are set to NaN, not deleted. Parent geometry (points/triangles) remains. Values can be restored by reloading original data. Filter settings determine what is clipped.

Clip​

Menu name: Clip Tooltip Clip attribute values to specified range.

What it does Opens dialogue to specify minimum and maximum values. Sets all values outside this range to NaN (missing value). Similar to "Clip to Filter" but uses manually specified range rather than current filter limits. Creates new clipped attribute.

When to use it

  • Removing outliers with specific thresholds
  • Creating value range masks
  • Excluding physically impossible values
  • Preparing data for specific analysis requirements

Notes Creates new attribute with "_Clipped" suffix. Original preserved. Clipped values shown as no-data in visualisations. Useful for excluding known error ranges.

Compress​

Menu name: Compress Tooltip Compress attribute value range.

What it does Opens dialogue to specify compression parameters. Applies a compression function that reduces the dynamic range of the attribute, bringing extreme values closer to the centre whilst minimally affecting central values. Useful for improving visualisation of attributes with occasional extreme outliers.

When to use it

  • Improving false colour visualisation of attributes with outliers
  • Reducing influence of extreme values on colour scales
  • Creating more visually informative attribute displays
  • Preparing attributes for classification with outliers

Notes Various compression functions available (sigmoid, arctan, etc.). Creates new compressed attribute. Original values preserved. Compression parameters control aggressiveness.

Replace Isolated​

Menu name: Replace Isolated Tooltip Replace isolated values with neighbourhood average.

What it does Identifies attribute values that differ significantly from their spatial neighbours (outliers in local context) and replaces them with the average of surrounding values. This spatial filtering removes isolated spikes or dips in the attribute field. Opens dialogue to specify neighbourhood size and difference threshold.

When to use it

  • Removing noise spikes from attribute fields
  • Smoothing attributes whilst preserving edges
  • Cleaning up artifacts in calculated attributes
  • Improving attribute field continuity

Notes Works spatially - considers geometric neighbours, not value neighbours. Threshold determines what counts as "isolated". Too aggressive settings can over-smooth important features. Creates new smoothed attribute.

Selection​

Filtered​

Menu name: Filtered Tooltip Select elements with filtered attribute values.

What it does Selects all points or triangles that have attribute values within the current filter range. Selected elements are highlighted in the 3D view. This creates a spatial selection based on attribute criteria, useful for isolating features of interest.

When to use it

  • Selecting features based on attribute characteristics
  • Creating spatial selections from attribute queries
  • Isolating specific value ranges for further operations
  • Before deletion or export of filtered subsets

Notes Selection is based on current filter settings in the attribute display. Adjust filter min/max before selecting. Multiple selections can be combined using shift+click.

Unfiltered​

Menu name: Unfiltered Tooltip Select elements with unfiltered attribute values.

What it does Selects all points or triangles that have attribute values outside the current filter range. This is the inverse of "Select Filtered" - it selects what is currently hidden or excluded by the filter.

When to use it

  • Selecting outliers or excluded values
  • Identifying elements that will be removed by filtering
  • Inverting attribute-based selections
  • Quality control for filter settings

Notes Useful for checking what will be excluded before deleting. Selection is based on current filter settings. Combine with "Delete Selected" to remove outliers.

Analysis​

K-Means Clustering​

Menu name: K-Means Clustering Tooltip Perform K-means clustering on attribute.

What it does Opens dialogue to specify number of clusters (K). Performs K-means clustering algorithm on the attribute values, grouping elements into K clusters based on value similarity. Each element is assigned a cluster ID (1 to K). Creates a new discrete attribute containing cluster assignments.

When to use it

  • Automatic classification of attribute values
  • Identifying natural groupings in data
  • Creating discrete classes from continuous attributes
  • Unsupervised feature identification

Notes K-means seeks to minimise within-cluster variance. Requires specifying K (number of clusters) in advance. Algorithm is iterative and may take time for large datasets. Results depend on random initialisation - multiple runs may give slightly different results.

Cross Plot​

Menu name: Cross Plot Tooltip Create cross plot of two attributes.

What it does Opens dialogue to select a second attribute. Creates a scatter plot (cross plot) showing the relationship between this attribute (X axis) and the selected attribute (Y axis). Each point or triangle appears as a point on the plot. Interactive plot allows selecting ranges that highlight corresponding elements in 3D.

When to use it

  • Exploring relationships between attributes
  • Identifying correlations or trends
  • Finding attribute-based clusters visually
  • Quality control for calculated attributes

Notes Both attributes must be from the same parent object (point cloud or mesh). Plot can be used for interactive selection. Correlation statistics are displayed. Useful for multivariate analysis.

Calculator​

Menu name: Calculator Tooltip Open attribute calculator for custom calculations.

What it does Opens the Attribute Calculator dialogue. Allows creating new attributes through mathematical expressions combining existing attributes, constants, and functions (sin, cos, log, sqrt, etc.). Supports conditional expressions and complex calculations. New attributes are calculated per-element (point or triangle).

When to use it

  • Creating derived attributes from existing ones
  • Implementing custom analysis algorithms
  • Combining multiple attributes mathematically
  • Creating computed classification criteria

Notes Expression syntax similar to C/Python. Available functions include: +, -, *, /, ^, sin(), cos(), tan(), log(), sqrt(), abs(), min(), max(), if(). Attribute names referenced by name. Results stored as new attribute.

Replace Filtered Values​

Menu name: Replace Filtered Values Tooltip Replace filtered values with specified constant.

What it does Opens dialogue to specify replacement value. All attribute values within the current filter range are replaced with the specified constant. Values outside the filter remain unchanged. This creates uniform regions where the filter is active.

When to use it

  • Setting specific regions to a constant value
  • Creating binary masks (0/1 attributes)
  • Filling filtered areas with default values
  • Preparing attributes for specific algorithms

Notes

In-Place Modification

Modifies attribute directly - cannot be undone. Filter range determines what is replaced. Useful for creating regions with known values.

Export & Display​

Export Histogram​

Menu name: Export Histogram Tooltip Export attribute histogram to file.

What it does Opens file save dialogue. Exports the attribute's histogram (value distribution) to a CSV file. The file contains bin centres and counts, suitable for plotting or statistical analysis in external tools.

When to use it

  • Documenting attribute distributions
  • Performing statistical analysis in external tools (R, Python, Excel)
  • Creating publication-quality histogram plots
  • Comparing attribute distributions across datasets

Notes Histogram bin count and range based on current display settings. Export includes bin centres, counts, and cumulative distribution. CSV format is compatible with most analysis software.

Export Attribute​

Menu name: Export Attribute Tooltip Export attribute values with coordinates.

What it does Opens file save dialogue. Exports attribute values along with spatial coordinates (X, Y, Z) to a text file (CSV or similar). Each row contains position and attribute value. Useful for external analysis or import into GIS/spreadsheet applications.

When to use it

  • Exporting attributes for analysis in external software
  • Creating GIS-compatible attribute data
  • Sharing attribute data without full point cloud/mesh
  • Performing statistical analysis in R, Python, or Excel

Notes Export format options include CSV, ASCII, XYZ with attribute. Large attributes may produce large files. Filter settings determine which elements are exported. Coordinate system information included if available.

Copy Colour Scale to Clipboard​

Menu name: Copy Color Scale to Clipboard Tooltip Copy colour scale to clipboard as image.

What it does Copies the current attribute's colour scale bar (legend) to the system clipboard as an image. The image can be pasted into documents, presentations, or image editors. Includes attribute name, min/max values, and colour ramp.

When to use it

  • Creating figure legends for reports or papers
  • Documenting colour scales for publications
  • Building presentation graphics
  • Creating consistent legends across multiple figures

Notes Colour scale reflects current display settings (colour map, min/max, orientation). PNG format with transparency. Can be pasted directly into Word, PowerPoint, or image editors.

Organisation​

Move Up in List​

Menu name: Move Up in List Tooltip Move attribute up in display list.

What it does Moves the attribute up one position in the project tree and attribute display order. This changes the order in which attributes appear in lists and dialogues. Purely organisational - does not affect data or calculations.

When to use it

  • Organising attributes by importance or workflow order
  • Placing frequently used attributes at the top of lists
  • Grouping related attributes together
  • Customising attribute display order

Notes Only affects display order, not data. Top attribute cannot be moved up further. Attribute order is saved with the project.

Move Down in List​

Menu name: Move Down in List Tooltip Move attribute down in display list.

What it does Moves the attribute down one position in the project tree and attribute display order. This changes the order in which attributes appear in lists and dialogues. Purely organisational - does not affect data or calculations.

When to use it

  • Organising attributes by importance or workflow order
  • Moving less important attributes to the bottom
  • Grouping related attributes together
  • Customising attribute display order

Notes Only affects display order, not data. Bottom attribute cannot be moved down further. Attribute order is saved with the project.

Remove Common Prefix​

Menu name: Remove Common Prefix Tooltip Remove common prefix from attribute names.

What it does Scans all attribute names in the parent object to find common prefixes (e.g., "Sensor1_", "Import_"). Removes these prefixes from all attribute names, shortening names for better display. Useful when importing data with automatic naming that adds unwanted prefixes.

When to use it

  • Cleaning up imported attribute names
  • Removing automatic prefixes added by processing software
  • Shortening long attribute names for better display
  • Standardising attribute naming across datasets

Notes Affects all attributes in the parent object, not just selected one. Cannot be undone - note original names if needed. Attributes must have common prefix for operation to work.

Delete​

Menu name: Delete Tooltip Delete selected attribute.

What it does Permanently removes the selected attribute from the parent object (point cloud or mesh). The attribute data is deleted and cannot be recovered. The parent object's geometry and other attributes are unaffected.

When to use it

  • Removing unwanted or obsolete attributes
  • Cleaning up intermediate calculation results
  • Reducing project file size
  • Removing failed or erroneous calculations

Notes

Cannot be undone

Attribute data is permanently deleted. Cannot be undone except by recalculating or reloading original data. Ensure you don't need the attribute before deleting.

Some attributes may be required by specific operations - deleting them may affect functionality.