# Analyze the spatial distribution of 911 calls in a metropolitan area
# using the Cluster-Outlier Analysis Tool (Anselin's Local Moran's I)
# Import system modules
import arcpy
# Set property to overwrite outputs if they already exist
arcpy.env.overwriteOutput = True
# Local variables...
workspace = r"C:\Data\911Calls"
try:
# Set the current workspace
# (to avoid having to specify the full path to the feature classes each time)
arcpy.env.workspace = workspace
# Copy the input feature class and integrate the points to snap
# together at 500 feet
# Process: Copy Features and Integrate
cf = arcpy.CopyFeatures_management("911Calls.shp", "911Copied.shp")
integrate = arcpy.Integrate_management("911Copied.shp #", "500 Feet")
# Use Collect Events to count the number of calls at each location
# Process: Collect Events
ce = arcpy.CollectEvents_stats("911Copied.shp", "911Count.shp", "Count", "#")
# Add a unique ID field to the count feature class
# Process: Add Field and Calculate Field
af = arcpy.AddField_management("911Count.shp", "MyID", "LONG", "#", "#", "#", "#",
"NON_NULLABLE", "NON_REQUIRED", "#",
"911Count.shp")
cf = arcpy.CalculateField_management("911Count.shp", "MyID", "!FID!", "PYTHON")
# Create Spatial Weights Matrix for Calculations
# Process: Generate Spatial Weights Matrix...
swm = arcpy.GenerateSpatialWeightsMatrix_stats("911Count.shp", "MYID",
"euclidean6Neighs.swm",
"K_NEAREST_NEIGHBORS",
"#", "#", "#", 6)
# Cluster/Outlier Analysis of 911 Calls
# Process: Local Moran's I
clusters = arcpy.ClustersOutliers_stats("911Count.shp", "ICOUNT",
"911ClusterOutlier.shp",
"GET_SPATIAL_WEIGHTS_FROM_FILE",
"EUCLIDEAN_DISTANCE", "NONE",
"#", "euclidean6Neighs.swm", "NO_FDR", "499")
except arcpy.ExecuteError:
# If an error occurred when running the tool, print out the error message.
print(arcpy.GetMessages())