class CrossKFunction(object):
###
# Initialize the tool.
###
def __init__(self):
self.label = "Cross K Function"
self.description = "Uses a Cross K Function to analyze clustering and dispersion trends in a set of origin and destination points (for example, bridges and crashes)."
self.canRunInBackground = False
env.overwriteOutput = True
self.kfHelper = KFunctionHelper()
###
# Get input from the users.
###
def getParameterInfo(self):
# Input origin points features.
srcPoints = arcpy.Parameter(
displayName="Input Origin Points Feature Dataset (e.g. bridges)",
name="srcPoints",
datatype="Feature Class",
parameterType="Required",
direction="Input")
srcPoints.filter.list = ["Point"]
# Input destination origin features.
destPoints = arcpy.Parameter(
displayName=
"Input Destination Points Feature Dataset (e.g. crashes)",
name="destPoints",
datatype="Feature Class",
parameterType="Required",
direction="Input")
destPoints.filter.list = ["Point"]
# Network dataset.
networkDataset = arcpy.Parameter(displayName="Input Network Dataset",
name="network_dataset",
datatype="Network Dataset Layer",
parameterType="Required",
direction="Input")
# Number of distance increments.
numBands = arcpy.Parameter(
displayName="Input Number of Distance Bands",
name="num_dist_bands",
datatype="Long",
parameterType="Optional",
direction="Input")
# Beginning distance.
begDist = arcpy.Parameter(displayName="Input Beginning Distance",
name="beginning_distance",
datatype="Double",
parameterType="Required",
direction="Input")
begDist.value = 0
# Distance increment.
distInc = arcpy.Parameter(displayName="Input Distance Increment",
name="distance_increment",
datatype="Double",
parameterType="Required",
direction="Input")
distInc.value = 1000
# Snap distance.
snapDist = arcpy.Parameter(displayName="Input Snap Distance",
name="snap_distance",
datatype="Double",
parameterType="Required",
direction="Input")
snapDist.value = 25
# Output location.
outNetKLoc = arcpy.Parameter(
displayName="Output Location (Database Path)",
name="out_location",
datatype="DEWorkspace",
parameterType="Required",
direction="Input")
outNetKLoc.value = arcpy.env.workspace
# The raw ODCM data.
outRawODCMFCName = arcpy.Parameter(
displayName="Raw ODCM Data Table",
name="output_raw_odcm_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outRawODCMFCName.value = "Cross_K_Raw_ODCM_Data"
# The raw data feature class (e.g. observed and random point computations).
outRawFCName = arcpy.Parameter(
displayName="Raw Network-K Data Table (Raw Analysis Data)",
name="output_raw_analysis_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outRawFCName.value = "Cross_K_Raw_Analysis_Data"
# The analysis feature class.
outAnlFCName = arcpy.Parameter(
displayName="Network-K Summary Data (Plottable Data)",
name="output_analysis_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outAnlFCName.value = "Cross_K_Summary_Data"
# Confidence envelope (number of permutations).
numPerms = arcpy.Parameter(
displayName="Number of Random Point Permutations",
name="num_permutations",
datatype="GPString",
parameterType="Required",
direction="Input")
permKeys = self.kfHelper.getPermutationSelection().keys()
numPerms.filter.list = permKeys
numPerms.value = permKeys[0]
# Projected coordinate system.
outCoordSys = arcpy.Parameter(
displayName=
"Output Network Dataset Length Projected Coordinate System",
name="coordinate_system",
datatype="GPSpatialReference",
parameterType="Optional",
direction="Input")
# Number of points field.
numPointsFieldName = arcpy.Parameter(
displayName="Number of Points Field",
name="num_points_field",
datatype="GPString",
parameterType="Optional",
direction="Input")
return [
srcPoints, destPoints, networkDataset, numBands, begDist, distInc,
snapDist, outNetKLoc, outRawODCMFCName, outRawFCName, outAnlFCName,
numPerms, outCoordSys, numPointsFieldName
]
###
# Check if the tool is available for use.
###
def isLicensed(self):
# Network Analyst tools must be available.
return arcpy.CheckExtension("Network") == "Available"
###
# Set parameter defaults.
###
def updateParameters(self, parameters):
networkDataset = parameters[2].value
outCoordSys = parameters[12].value
# Default the coordinate system.
if networkDataset is not None and outCoordSys is None:
ndDesc = arcpy.Describe(networkDataset)
# If the network dataset's coordinate system is a projected one,
# use its coordinate system as the defualt.
if (ndDesc.spatialReference.projectionName != ""
and ndDesc.spatialReference.linearUnitName == "Meter"
and ndDesc.spatialReference.factoryCode != 0):
parameters[12].value = ndDesc.spatialReference.factoryCode
# Set the source of the fields (the network dataset).
if networkDataset is not None:
parameters[13].filter.list = self.kfHelper.getEdgeSourceFieldNames(
networkDataset)
###
# If any fields are invalid, show an appropriate error message.
###
def updateMessages(self, parameters):
outCoordSys = parameters[12].value
if outCoordSys is not None:
if outCoordSys.projectionName == "":
parameters[12].setErrorMessage(
"Output coordinate system must be a projected coordinate system."
)
elif outCoordSys.linearUnitName != "Meter":
parameters[12].setErrorMessage(
"Output coordinate system must have a linear unit code of 'Meter.'"
)
else:
parameters[12].clearMessage()
###
# Execute the tool.
###
def execute(self, parameters, messages):
srcPoints = parameters[0].valueAsText
destPoints = parameters[1].valueAsText
networkDataset = parameters[2].valueAsText
numBands = parameters[3].value
begDist = parameters[4].value
distInc = parameters[5].value
snapDist = parameters[6].value
outNetKLoc = parameters[7].valueAsText
outRawODCMFCName = parameters[8].valueAsText
outRawFCName = parameters[9].valueAsText
outAnlFCName = parameters[10].valueAsText
numPerms = self.kfHelper.getPermutationSelection()[
parameters[11].valueAsText]
outCoordSys = parameters[12].value
numPointsFieldName = parameters[13].value
ndDesc = arcpy.Describe(networkDataset)
gkfSvc = GlobalKFunctionSvc()
# Refer to the note in the NetworkDatasetLength tool.
if outCoordSys is None:
outCoordSys = ndDesc.spatialReference
messages.addMessage("\nOrigin points: {0}".format(srcPoints))
messages.addMessage("Destination points: {0}".format(destPoints))
messages.addMessage("Network dataset: {0}".format(networkDataset))
messages.addMessage("Number of distance bands: {0}".format(numBands))
messages.addMessage("Beginning distance: {0}".format(begDist))
messages.addMessage("Distance increment: {0}".format(distInc))
messages.addMessage("Snap distance: {0}".format(snapDist))
messages.addMessage(
"Path to output cross-K feature class: {0}".format(outNetKLoc))
messages.addMessage(
"Raw ODCM data table: {0}".format(outRawODCMFCName))
messages.addMessage(
"Raw cross-K data table (raw analysis data): {0}".format(
outRawFCName))
messages.addMessage(
"Cross-K summary data (plottable data): {0}".format(outAnlFCName))
messages.addMessage(
"Number of random permutations: {0}".format(numPerms))
messages.addMessage(
"Network dataset length projected coordinate system: {0}".format(
outCoordSys.name))
messages.addMessage(
"Number of Points Field Name: {0}\n".format(numPointsFieldName))
# Calculate the length of the network.
networkLength = self.kfHelper.calculateLength(networkDataset,
outCoordSys)
messages.addMessage("Total network length: {0}".format(networkLength))
# Count the number of crashes.
numDests = self.kfHelper.countNumberOfFeatures(
os.path.join(outNetKLoc, destPoints))
# Set up a cutoff lenght for the ODCM data if possible. (Optimization.)
cutoff = gkfSvc.getCutoff(numBands, distInc, begDist)
# The results of all the calculations end up here.
netKCalculations = []
# Use a mutable container for the number of bands so that the below callback
# can write to it. The "nonlocal" keyword not available in Python 2.x.
numBandsCont = [numBands]
# Callback function that does the Network K calculation on an OD cost matrix.
def doNetKCalc(odDists, iteration):
# Do the actual network k-function calculation.
netKCalc = CrossKCalculation(networkLength, numDests, odDists,
begDist, distInc, numBandsCont[0])
netKCalculations.append(netKCalc.getDistanceBands())
# If the user did not specifiy a number of distance bands explicitly,
# store the number of bands. It's computed from the observed data.
if numBandsCont[0] is None:
numBandsCont[0] = netKCalc.getNumberOfDistanceBands()
# Generate the ODCM permutations, including the ODCM for the observed data.
# doNetKCalc is called on each iteration.
randODCMPermSvc = RandomODCMPermutationsSvc()
randODCMPermSvc.generateODCMPermutations(
"Cross Analysis", srcPoints, destPoints, networkDataset, snapDist,
cutoff, outNetKLoc, outRawODCMFCName, numPerms, outCoordSys,
numPointsFieldName, messages, doNetKCalc)
# Store the raw analysis data.
messages.addMessage("Writing raw analysis data.")
gkfSvc.writeRawAnalysisData(outNetKLoc, outRawFCName, netKCalculations)
# Analyze the data and store the results.
messages.addMessage("Analyzing data.")
gkfSvc.writeAnalysisSummaryData(numPerms, netKCalculations, outNetKLoc,
outAnlFCName)
class GlobalKFunction(object):
###
# Initialize the tool.
###
def __init__(self):
self.label = "Global K Function"
self.description = "Uses a Global Network K Function to analyze clustering and dispersion trends in a set of crash points."
self.canRunInBackground = False
env.overwriteOutput = True
self.kfHelper = KFunctionHelper()
###
# Get input from the users.
###
def getParameterInfo(self):
# Input origin features.
points = arcpy.Parameter(
displayName="Input Points Feature Dataset",
name="points",
datatype="Feature Class",
parameterType="Required",
direction="Input")
points.filter.list = ["Point"]
# Network dataset.
networkDataset = arcpy.Parameter(
displayName="Input Network Dataset",
name = "network_dataset",
datatype="Network Dataset Layer",
parameterType="Required",
direction="Input")
# Number of distance increments.
numBands = arcpy.Parameter(
displayName="Input Number of Distance Bands",
name="num_dist_bands",
datatype="Long",
parameterType="Optional",
direction="Input")
# Beginning distance.
begDist = arcpy.Parameter(
displayName="Input Beginning Distance",
name="beginning_distance",
datatype="Double",
parameterType="Required",
direction="Input")
begDist.value = 0
# Distance increment.
distInc = arcpy.Parameter(
displayName="Input Distance Increment",
name="distance_increment",
datatype="Double",
parameterType="Required",
direction="Input")
distInc.value = 1000
# Snap distance.
snapDist = arcpy.Parameter(
displayName="Input Snap Distance",
name="snap_distance",
datatype="Double",
parameterType="Required",
direction="Input")
snapDist.value = 25
# Output location.
outNetKLoc = arcpy.Parameter(
displayName="Output Location (Database Path)",
name="out_location",
datatype="DEWorkspace",
parameterType="Required",
direction="Input")
outNetKLoc.value = arcpy.env.workspace
# The raw ODCM data.
outRawODCMFCName = arcpy.Parameter(
displayName="Raw ODCM Data Table",
name = "output_raw_odcm_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outRawODCMFCName.value = "Global_K_Raw_ODCM_Data"
# The raw data feature class (e.g. observed and random point computations).
outRawFCName = arcpy.Parameter(
displayName="Raw Global-K Data Table (Raw Analysis Data)",
name = "output_raw_analysis_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outRawFCName.value = "Global_K_Raw_Analysis_Data"
# The analysis feature class.
outAnlFCName = arcpy.Parameter(
displayName="Global-K Summary Data (Plottable Data)",
name = "output_analysis_feature_class",
datatype="GPString",
parameterType="Required",
direction="Output")
outAnlFCName.value = "Global_K_Summary_Data"
# Confidence envelope (number of permutations).
numPerms = arcpy.Parameter(
displayName="Number of Random Point Permutations",
name = "num_permutations",
datatype="GPString",
parameterType="Required",
direction="Input")
permKeys = self.kfHelper.getPermutationSelection().keys()
numPerms.filter.list = permKeys
numPerms.value = permKeys[0]
# Projected coordinate system.
outCoordSys = arcpy.Parameter(
displayName="Output Network Dataset Length Projected Coordinate System",
name="coordinate_system",
datatype="GPSpatialReference",
parameterType="Optional",
direction="Input")
# Number of points field.
numPointsFieldName = arcpy.Parameter(
displayName="Number of Points Field",
name = "num_points_field",
datatype="GPString",
parameterType="Optional",
direction="Input")
return [points, networkDataset, numBands, begDist, distInc, snapDist,
outNetKLoc, outRawODCMFCName, outRawFCName, outAnlFCName, numPerms,
outCoordSys, numPointsFieldName]
###
# Check if the tool is available for use.
###
def isLicensed(self):
# Network Analyst tools must be available.
return arcpy.CheckExtension("Network") == "Available"
###
# Set parameter defaults.
###
def updateParameters(self, parameters):
networkDataset = parameters[1].value
outCoordSys = parameters[11].value
# Default the coordinate system.
if networkDataset is not None and outCoordSys is None:
ndDesc = arcpy.Describe(networkDataset)
# If the network dataset's coordinate system is a projected one,
# use its coordinate system as the defualt.
if (ndDesc.spatialReference.projectionName != "" and
ndDesc.spatialReference.linearUnitName == "Meter" and
ndDesc.spatialReference.factoryCode != 0):
parameters[11].value = ndDesc.spatialReference.factoryCode
# Set the source of the fields (the network dataset).
if networkDataset is not None:
parameters[12].filter.list = self.kfHelper.getEdgeSourceFieldNames(networkDataset)
###
# If any fields are invalid, show an appropriate error message.
###
def updateMessages(self, parameters):
outCoordSys = parameters[11].value
if outCoordSys is not None:
if outCoordSys.projectionName == "":
parameters[11].setErrorMessage("Output coordinate system must be a projected coordinate system.")
elif outCoordSys.linearUnitName != "Meter":
parameters[11].setErrorMessage("Output coordinate system must have a linear unit code of 'Meter.'")
else:
parameters[11].clearMessage()
###
# Execute the tool.
###
def execute(self, parameters, messages):
points = parameters[0].valueAsText
networkDataset = parameters[1].valueAsText
numBands = parameters[2].value
begDist = parameters[3].value
distInc = parameters[4].value
snapDist = parameters[5].value
outNetKLoc = parameters[6].valueAsText
outRawODCMFCName = parameters[7].valueAsText
outRawFCName = parameters[8].valueAsText
outAnlFCName = parameters[9].valueAsText
numPermsDesc = parameters[10].valueAsText
numPerms = self.kfHelper.getPermutationSelection()[numPermsDesc]
outCoordSys = parameters[11].value
numPointsFieldName = parameters[12].value
ndDesc = arcpy.Describe(networkDataset)
gkfSvc = GlobalKFunctionSvc()
# Refer to the note in the NetworkDatasetLength tool.
if outCoordSys is None:
outCoordSys = ndDesc.spatialReference
messages.addMessage("\nOrigin points: {0}".format(points))
messages.addMessage("Network dataset: {0}".format(networkDataset))
messages.addMessage("Number of distance bands: {0}".format(numBands))
messages.addMessage("Beginning distance: {0}".format(begDist))
messages.addMessage("Distance increment: {0}".format(distInc))
messages.addMessage("Snap distance: {0}".format(snapDist))
messages.addMessage("Output location (database path): {0}".format(outNetKLoc))
messages.addMessage("Raw ODCM data table: {0}".format(outRawODCMFCName))
messages.addMessage("Raw global-K data table (raw analysis data): {0}".format(outRawFCName))
messages.addMessage("Global-K summary data (plottable data): {0}".format(outAnlFCName))
messages.addMessage("Number of random permutations: {0}".format(numPerms))
messages.addMessage("Network dataset length projected coordinate system: {0}".format(outCoordSys.name))
messages.addMessage("Number of Points Field Name: {0}\n".format(numPointsFieldName))
# Calculate the length of the network.
networkLength = self.kfHelper.calculateLength(networkDataset, outCoordSys)
messages.addMessage("Total network length: {0}".format(networkLength))
# Count the number of crashes.
numPoints = self.kfHelper.countNumberOfFeatures(os.path.join(outNetKLoc, points))
# Set up a cutoff lenght for the ODCM data if possible. (Optimization.)
cutoff = gkfSvc.getCutoff(numBands, distInc, begDist)
# The results of all the calculations end up here.
netKCalculations = []
# Use a mutable container for the number of bands so that the below callback
# can write to it. The "nonlocal" keyword not available in Python 2.x.
numBandsCont = [numBands]
# Callback function that does the Network K calculation on an OD cost matrix.
def doNetKCalc(odDists, iteration):
# Do the actual network k-function calculation.
netKCalc = NetworkKCalculation(networkLength, numPoints, odDists, begDist, distInc, numBandsCont[0])
netKCalculations.append(netKCalc.getDistanceBands())
# If the user did not specifiy a number of distance bands explicitly,
# store the number of bands. It's computed from the observed data.
if numBandsCont[0] is None:
numBandsCont[0] = netKCalc.getNumberOfDistanceBands()
# Generate the ODCM permutations, including the ODCM for the observed data.
# doNetKCalc is called on each iteration.
randODCMPermSvc = RandomODCMPermutationsSvc()
randODCMPermSvc.generateODCMPermutations("Global Analysis",
points, points, networkDataset, snapDist, cutoff, outNetKLoc,
outRawODCMFCName, numPerms, outCoordSys, numPointsFieldName, messages, doNetKCalc)
# Store the raw analysis data.
messages.addMessage("Writing raw analysis data.")
gkfSvc.writeRawAnalysisData(outNetKLoc, outRawFCName, netKCalculations)
# Analyze the data and store the results.
messages.addMessage("Analyzing data.")
gkfSvc.writeAnalysisSummaryData(numPerms, netKCalculations, outNetKLoc, outAnlFCName)
class RandomODCMPermutationsSvc:
###
# Initialize the service (stateless).
###
def __init__(self):
self.kfHelper = KFunctionHelper()
###
# Generate the ODCM permutations.
# @param analysisType Either Global Analysis or Cross Analysis.
# @param srcPoints The source points.
# @param destPoints The destination points. Ignored if analysisType is GLOBAL.
# @param networkDataset The network dataset to use for the ODCMs.
# @param snapDist The snap distance for points that are not directly on the network.
# @param cutoff The cutoff distance. Ignored if None.
# @param outLoc The full path to a database. The ODCM data will be written here.
# @param outFC The name of the feature class in outLoc where the ODCM data will be written.
# @param numPerms The number of permutations (string representation).
# @param outCoordSys The coordinate system to project the points into (optional).
# @param numPointsFieldName The optional name of a field in the network dataset's edge source
# from which the number of random points should be derived.
# @param messages A messages instances with addMessage() implemented (for debug output).
# @param callback A callback function(odDists, iteration) called on each iteration
# with the current OD cost matrix.
###
def generateODCMPermutations(self, analysisType, srcPoints, destPoints,
networkDataset, snapDist, cutoff, outLoc, outFC, numPerms, outCoordSys,
numPointsFieldName, messages, callback = None):
# Default no-op for the callback.
if callback is None:
callback = lambda odDists, iteration: None
# For global analysis the destination points are the same as the source points
# (e.g. destPoints is ignored).
if analysisType == "GLOBAL" or destPoints is None:
destPoints = srcPoints
# Count the number of crashes (there may be fewer points in the ODCM, but it's the total
# number of crashes that is needed).
numDests = self.kfHelper.countNumberOfFeatures(os.path.join(outLoc, destPoints))
messages.addMessage("Number of crashes: {0}".format(numDests))
# Make the observed ODCM and calculate the distance between each set of
# points. If a cross analysis is selected, find the distance between the
# source and destination points. Otherwise there is only one set of points
odDists = self._calculateDistances(networkDataset, srcPoints, destPoints, snapDist, cutoff)
self._writeODCMData(odDists, outLoc, outFC, 0)
callback(odDists, 0)
messages.addMessage("Iteration 0 (observed) complete.")
# Generate the OD Cost matrix permutations.
kfTimer = KFunctionTimer(numPerms)
for i in range(1, numPerms + 1):
if numPointsFieldName:
randPoints = self.kfHelper.generateRandomPoints(networkDataset, outCoordSys, None, numPointsFieldName)
else:
randPoints = self.kfHelper.generateRandomPoints(networkDataset, outCoordSys, numDests, None)
# See the note above: Either find the distance from the source points to the random points,
# or the distance between the random points.
if analysisType == "CROSS":
odDists = self._calculateDistances(networkDataset, srcPoints, randPoints, snapDist, cutoff)
else:
odDists = self._calculateDistances(networkDataset, randPoints, randPoints, snapDist, cutoff)
self._writeODCMData(odDists, outLoc, outFC, i)
callback(odDists, i)
# Clean up the random points table.
arcpy.Delete_management(randPoints)
# Show the progress.
kfTimer.increment()
messages.addMessage("Iteration {0} complete. Elapsed time: {1}s. ETA: {2}s.".format(
i, kfTimer.getElapsedTime(), kfTimer.getETA()))
###
# Calculate the distances between each set of points using an OD Cost Matrix.
# @param networkDataset A network dataset which the points are on.
# @param srcPoints The source points to calculate distances from.
# @param destPoints The destination points to calculate distances to.
# @param snapDist If a point is not directly on the network, it will be
# snapped to the nearset line if it is within this threshold.
# @param cutoff The cutoff distance for the ODCM (optional).
###
def _calculateDistances(self, networkDataset, srcPoints, destPoints, snapDist, cutoff):
# This is the current map, which should be an OSM base map.
curMapDoc = arcpy.mapping.MapDocument("CURRENT")
# Get the data from from the map (see the DataFrame object of arcpy).
dataFrame = arcpy.mapping.ListDataFrames(curMapDoc, "Layers")[0]
# Create the cost matrix.
costMatResult = arcpy.na.MakeODCostMatrixLayer(networkDataset, "TEMP_ODCM_NETWORK_K", "Length", cutoff)
odcmLayer = costMatResult.getOutput(0)
# The OD Cost Matrix layer will have Origins and Destinations layers. Get
# a reference to each of these.
odcmSublayers = arcpy.na.GetNAClassNames(odcmLayer)
odcmOriginLayer = odcmSublayers["Origins"]
odcmDestLayer = odcmSublayers["Destinations"]
# Add the origins and destinations to the ODCM.
arcpy.na.AddLocations(odcmLayer, odcmOriginLayer, srcPoints, "", snapDist)
arcpy.na.AddLocations(odcmLayer, odcmDestLayer, destPoints, "", snapDist)
# Solve the matrix.
arcpy.na.Solve(odcmLayer)
# Show the ODCM layer (it must be showing to open th ODLines sub layer below).
#arcpy.mapping.AddLayer(dataFrame, odcmLayer, "TOP")
#arcpy.RefreshTOC()
# Get the "Lines" layer, which has the distance between each point.
odcmLines = arcpy.mapping.ListLayers(odcmLayer, odcmSublayers["ODLines"])[0]
# This array will hold all the OD distances.
odDists = []
if srcPoints == destPoints:
# If the source points and destination points are the same, exclude the
# distance from the point to itself.
where = """{0} <> {1}""".format(
arcpy.AddFieldDelimiters(odcmLines, "originID"),
arcpy.AddFieldDelimiters(odcmLines, "destinationID"))
else:
where = ""
with arcpy.da.SearchCursor(
in_table=odcmLines,
field_names=["Total_Length", "originID", "destinationID"],
where_clause=where) as cursor:
for row in cursor:
odDists.append({"Total_Length": row[0], "OriginID": row[1], "DestinationID": row[2]})
return odDists
###
# Write the ODCM data to a table.
# @param odDists An array of raw ODCM data.
# @param outLoc The location of a database.
# @param outFC The feature class name, in outLoc, to write the data to.
# @param iteration The iteration number (0 is observed).
###
def _writeODCMData(self, odDists, outLoc, outFC, iteration):
# This is the full path to the output feature class.
outFCFullPath = os.path.join(outLoc, outFC)
if iteration == 0:
# Create the output table.
arcpy.CreateTable_management(outLoc, outFC)
arcpy.AddField_management(outFCFullPath, "Iteration_Number", "LONG")
arcpy.AddField_management(outFCFullPath, "OriginID", "LONG")
arcpy.AddField_management(outFCFullPath, "DestinationID", "LONG")
arcpy.AddField_management(outFCFullPath, "Total_Length", "DOUBLE")
with arcpy.da.InsertCursor(outFCFullPath,
["Iteration_Number", "OriginID", "DestinationID", "Total_Length"]) as cursor:
for odDist in odDists:
cursor.insertRow([iteration, odDist["OriginID"], odDist["DestinationID"], odDist["Total_Length"]])