ZScore Rendering (Spatial Statistics)
Applies a cold (blue) to hot (red) color rendering scheme for a field of z-scores.
The Z Renderer creates a new layer file (.lyr) with z-scores rendered in the following manner:
- Z-scores below –2 standard deviations are rendered dark blue.
- Z-scores between –2 and –1 standard deviations are light blue.
- Z-scores between –1 and +1 standard deviations are neutral.
- Z-scores between 1 and 2 standard deviations are pink.
- Z-scores above 2 standard deviations are bright red.
Map layers can be used to define the Input Feature Class. When using a layer with a selection, only the selected features are included in the analysis.
Beginning with the ArcGIS 10 release, this tool is a built-in tool (rather than a Visual Basic executable). While every effort was made not to break custom model and script tools developed prior to ArcGIS 10, there may be cases where older models that use this tool must be rebuilt in order for the model to run.
The feature class containing a field with standardized z-scores.
The name of the field containing the z-scores.
The new output layer file to store rendering information. You must include the .lyr extension as part of the file name.
The following Python Window script demonstrates how to use the ZScore Rendering tool.
import arcpy arcpy.env.workspace = r"C:\data" arcpy.ZRenderer_stats("hotspot_output.shp", "GiInvDst", "hotspot_output_rendered.lyr")
The following stand-alone Python script demonstrates how to use the ZScore Rendering tool.
# Perform Hot Spot Analysis for assault incidents # Import system modules import arcpy # Local variables... workspace = r"C:\data" input = "assaults.shp" collect_output = "collect_output.shp" collect_count_field = "Count" hotspot_output = "hotspot_output.shp" hotspot_output_rendered = "hotspot_output_rendered.lyr" z_score_field_name = "GiInvDst" try: # Set the current workspace (to avoid having to specify the full path to the feature classes each time) arcpy.env.workspace = workspace # Convert assault incidents into weighted point data # Process: Collect Events... arcpy.CollectEvents_stats(input, collect_output) # Calculate Getis-Ord Gi* statistic # Process: Hot Spot Analysis (Getis-Ord Gi*)... arcpy.HotSpots_stats(collect_output, collect_count_field, hotspot_output, "INVERSE_DISTANCE", "EUCLIDEAN_DISTANCE", "NONE", "#", "#", "#") # Render hot spot analysis # Process: ZScore Rendering... arcpy.ZRenderer_stats(hotspot_output, z_score_field_name, hotspot_output_rendered) except: # If an error occurred when running the tool, print out the error message. print arcpy.GetMessages(2)