def writeAnalysisSummaryData(self, numPerms, netKCalculations, outNetKLoc,
outAnlFCName):
# Analyze the network k results (generate plottable output).
# No confidence intervals are computed if there are no random permutations.
if numPerms != 0:
netKAn_95 = NetworkKAnalysis(.95, netKCalculations)
netKAn_90 = NetworkKAnalysis(.90, netKCalculations)
# Write the analysis data to a table.
outAnlFCFullPath = os.path.join(outNetKLoc, outAnlFCName)
arcpy.CreateTable_management(outNetKLoc, outAnlFCName)
arcpy.AddField_management(outAnlFCFullPath, "Description", "TEXT")
arcpy.AddField_management(outAnlFCFullPath, "Distance_Band", "DOUBLE")
arcpy.AddField_management(outAnlFCFullPath, "Point_Count", "DOUBLE")
arcpy.AddField_management(outAnlFCFullPath, "K_Function", "DOUBLE")
with arcpy.da.InsertCursor(
outAnlFCFullPath,
["Description", "Distance_Band", "Point_Count", "K_Function"
]) as cursor:
self._writeAnalysis(cursor, netKCalculations[0], "Observed")
if numPerms != 0:
self._writeAnalysis(cursor,
netKAn_95.getLowerConfidenceEnvelope(),
"2.5% Lower Bound")
self._writeAnalysis(cursor,
netKAn_95.getUpperConfidenceEnvelope(),
"2.5% Upper Bound")
self._writeAnalysis(cursor,
netKAn_90.getLowerConfidenceEnvelope(),
"5% Lower Bound")
self._writeAnalysis(cursor,
netKAn_90.getUpperConfidenceEnvelope(),
"5% Upper Bound")
def test_confidence_envelope(self):
confInt = .95
netKCalculations = self.getRandNetK(1000)
# There should be 25 below the confidence interval, and 25 above.
# Envelope size = 999 * .95 = 949
# 25 below the envelope, so the index of lower envelope should be 25.
# 25 above the envelope, so the index of the upper envelope should be 973.
# e.g. [25 - 973] are in the envelope, inclusive.
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[0]["count"], 0)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 25)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[2]["count"], 50)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[0]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 973)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[2]["count"], 1946)
# 948 - 50 + 1 = 899 = 999 * .90
confInt = .90
netKCalculations = self.getRandNetK(1000)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 899)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 50)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 948)
# 95 - 2 + 1 = 94 = 99 * .95
# Note that the extra permuation is distributed above the envelope (2 below and 3 above).
confInt = .95
netKCalculations = self.getRandNetK(100)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 94)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 2)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 95)
confInt = .90
netKCalculations = self.getRandNetK(100)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 89)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 5)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 93)
confInt = .95
netKCalculations = self.getRandNetK(10)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 9)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 8)
confInt = .90
netKCalculations = self.getRandNetK(10)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 8)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 7)
def test_confidence_envelope(self):
confInt = .95
netKCalculations = self.getRandNetK(1000)
# There should be 25 below the confidence interval, and 25 above.
# Envelope size = 999 * .95 = 949
# 25 below the envelope, so the index of lower envelope should be 25.
# 25 above the envelope, so the index of the upper envelope should be 973.
# e.g. [25 - 973] are in the envelope, inclusive.
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[0]["count"], 0)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 25)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[2]["count"], 50)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[0]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 973)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[2]["count"], 1946)
# 948 - 50 + 1 = 899 = 999 * .90
confInt = .90
netKCalculations = self.getRandNetK(1000)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 899)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 50)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 948)
# 95 - 2 + 1 = 94 = 99 * .95
# Note that the extra permuation is distributed above the envelope (2 below and 3 above).
confInt = .95
netKCalculations = self.getRandNetK(100)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 94)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 2)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 95)
confInt = .90
netKCalculations = self.getRandNetK(100)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 89)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 5)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 93)
confInt = .95
netKCalculations = self.getRandNetK(10)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 9)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 8)
confInt = .90
netKCalculations = self.getRandNetK(10)
netKAn = NetworkKAnalysis(confInt, netKCalculations)
self.assertEqual(netKAn.getEnvelopeSize(), 8)
self.assertEqual(netKAn.getLowerConfidenceEnvelope()[1]["count"], 0)
self.assertEqual(netKAn.getUpperConfidenceEnvelope()[1]["count"], 7)
def writeAnalysisSummaryData(self, numPerms, netKCalculations, outNetKLoc, outAnlFCName):
# Analyze the network k results (generate plottable output).
# No confidence intervals are computed if there are no random permutations.
if numPerms != 0:
netKAn_95 = NetworkKAnalysis(.95, netKCalculations)
netKAn_90 = NetworkKAnalysis(.90, netKCalculations)
# Write the analysis data to a table.
outAnlFCFullPath = os.path.join(outNetKLoc, outAnlFCName)
arcpy.CreateTable_management(outNetKLoc, outAnlFCName)
arcpy.AddField_management(outAnlFCFullPath, "Description", "TEXT")
arcpy.AddField_management(outAnlFCFullPath, "Distance_Band", "DOUBLE")
arcpy.AddField_management(outAnlFCFullPath, "Point_Count", "DOUBLE")
arcpy.AddField_management(outAnlFCFullPath, "K_Function", "DOUBLE")
with arcpy.da.InsertCursor(outAnlFCFullPath,
["Description", "Distance_Band", "Point_Count", "K_Function"]) as cursor:
self._writeAnalysis(cursor, netKCalculations[0], "Observed")
if numPerms != 0:
self._writeAnalysis(cursor, netKAn_95.getLowerConfidenceEnvelope(), "2.5% Lower Bound")
self._writeAnalysis(cursor, netKAn_95.getUpperConfidenceEnvelope(), "2.5% Upper Bound")
self._writeAnalysis(cursor, netKAn_90.getLowerConfidenceEnvelope(), "5% Lower Bound")
self._writeAnalysis(cursor, netKAn_90.getUpperConfidenceEnvelope(), "5% Upper Bound")