Summary
Visualizes the variables stored in a netCDF cube created with the Space Time Pattern Mining tools. Output from this tool is a three-dimensional representation uniquely rendered based on the variable and theme chosen.
Illustration
Usage
This tool only accepts netCDF files created by the Create Space Time Cube By Aggregating Points or Create Space Time Cube From Defined Locations tool.
The Value theme allows you to see the raw numbers associated with aggregation or creation of the cube.
If you have run Emerging Hot Spot Analysis on a particular variable, the Hot and cold spot results theme is available. This theme shows the statistical significance of each bin based on the space time hot spot analysis run in Emerging Hot Spot Analysis .
If you have run Local Outlier Analysis on a particular variable, the Cluster and outlier results theme is available. This theme shows the result type assigned to each statistically significant bin based on the analysis run in Local Outlier Analysis.
If you have run a tool from the Time Series Forecasting toolset on a particular variable, the Forecast results theme is available. This theme shows the time series at each location along with forecasted time steps. The fitted values for each time step are saved as a separate field. For cubes created by the Forest-based Forecast or Exponential Smoothing Forecast tool, the upper and lower bounds of the confidence intervals are saved as separate fields. Additionally, cubes created by the Exponential Smoothing Forecast tool have their level, trend, and seasonal components saved as separate fields. These attributes can be displayed in a map with symbology.
If the Outlier Option parameter in the Time Series Forecasting tools was specified, you will also have the Time series outlier results theme available.
For cubes that were created with the Create Space Time Cube From Defined Locations tool and aggregated temporally, the Temporal aggregation count theme is available to visualize the count of records aggregated into each space-time bin.
Time-series charts are created as part of the output of this tool. If the Display Theme parameter is Hot and cold spot results, the z-scores are plotted over time for each location. For all other display themes, the value of the Cube Variable parameter is charted over time for each location. These charts will be added to the Contents pane under the output feature class.
Any Summary Fields or Variables that were aggregated will also give you the option of visualizing the Estimated bins so you can see which bins were estimated based on your specifications in Create Space Time Cube By Aggregating Points or Create Space Time Cube From Defined Locations.
Because time is used as the vertical axis in visualizing the space-time cube, it is important for accurate interpretation that all locations on the ground are at the same elevation. This way, all time-step intervals start at the same base. To do this, turn off the default elevation services by clicking off any Ground layers that appear in the Elevation Surfaces group in the Contents pane.
Note:
The next time a New Scene value is added, the default surfaces will populate again.If the data is not drawing, you may need to clear the visibility range limits, which you can do by selecting the new layer in the Contents pane, choosing the Appearance tab, and clicking the Clear Limits button.
The output of this tool is symbolized with cube-shaped point symbols representing each bin in the cube. If your cube was created from defined locations, it is best practice to add a 2D representation of your polygons to the Scene for perspective.
The space-time cube can also be visualized in 3D using the Space Time Cube Explorer Add-in.
To maintain temporal precision, shapefile output is not recommended as it cannot store both date and time in the same field. This is particularly important when visualizing the results in 3D and using the time slider to explore the results. Temporal precision can only be achieved when storing data in a geodatabase.
Syntax
arcpy.stpm.VisualizeSpaceTimeCube3D(in_cube, cube_variable, display_theme, output_features)
| Parameter | Explanation | Data Type |
in_cube | The netCDF cube that contains the variable to be displayed. This file must have an .nc extension and must have been created using either the Create Space Time Cube By Aggregating Points or Create Space Time Cube From Defined Locations tool. | File |
cube_variable | The numeric variable in the netCDF cube that you want to explore. The cube will always contain the COUNT variable if aggregation was used in cube creation. Any summary fields or variables will also be available if they were included in the cube creation process. | String |
display_theme | Specifies the characteristic of the Cube Variable parameter to be displayed. Available options will vary depending on how the cube was created and the analyses run.
Value is the numeric value of the Cube Variable parameter and is always available. Estimated bins are only available for the summary fields that were included in the cube creation process. Hot and cold spot results will only be available for the Cube Variable parameter value for which Emerging Hot Spot Analysis has been run. Cluster and outlier results will only be available for Cube Variables for which Local Outlier Analysis has been run. Temporal aggregation count will only be available for defined location cubes that have been aggregated temporally. Forecast results will only be available for the Cube Variable parameter value for which a tool in the Time Series Forecasting toolset has been run. Time series outlier results will only be available when the Outlier Option parameter has been set for the tools in the Time Series Forecasting toolset. | String |
output_features | The output feature class results. This feature class will be a three-dimensional map representation of the display variable that can be displayed in a 3D scene. | Feature Class |
Code sample
The following Python window script demonstrates how to use the VisualizeSpaceTimeCube3D tool.
import arcpy
arcpy.env.workspace = r"C:\STPM"
arcpy.VisualizeSpaceTimeCube3D_stpm("Homicides.nc", "COUNT",
"HOT_AND_COLD_SPOT_RESULTS",
"Homicides_Count_HS.shp")The following stand-alone Python script demonstrates how to use the VisualizeSpaceTimeCube3D tool.
# Display Space Time Cube of homicide incidents in a metropolitan area
# Import system modules
import arcpy
# Set geoprocessor object property to overwrite existing output, by default
arcpy.env.overwriteOutput = True
# Local variables...
workspace = r"C:\STPM"
arcpy.env.workspace = workspace
# Display Space Time Cube of homicide with the hot and cold spots with crime
# counts.
# Process: Visualize Space Time Cube in 3D
cube = arcpy.VisualizeSpaceTimeCube3D_stpm("Homicides.nc", "COUNT",
"HOT_AND_COLD_SPOT_RESULTS",
"Homicides_Count_HS.shp")Environments
Licensing information
- Basic: Yes
- Standard: Yes
- Advanced: Yes