def get_autocorrelation(csvfile, shpfile, year):
observations = Weights.extractObservations(csvfile, "ALL", [year])
w = Weights.generateWeightsUsingShapefile(shpfile, idVariable="STATE_NAME")
globalAutocorrelation = autocorrelation.globalAutocorrelation(
observations, w)
localAutocorrelation = autocorrelation.localAutocorrelation(
observations, w)
print(globalAutocorrelation, localAutocorrelation)
return str(globalAutocorrelation), str(localAutocorrelation)
def runGSA(case_num, autocorrelationRows, autocorrelationCols, sdRows, sdCols, idVariable):
fileDict = dao.getFileDict(case_num)
observations = weights.extractObservations(fileDict['GSA_Input_CSV'], autocorrelationRows, autocorrelationCols)
w = weights.generateWeightsUsingShapefile(fileDict['GSA_Input_SHP'], idVariable=idVariable)
globalAutoCorrelation = autocorrelation.globalAutocorrelation(observations, w)
localAutoCorrelation = autocorrelation.localAutocorrelation(observations, w)
observations = weights.extractObservations(fileDict['GSA_Input_CSV'], sdRows, sdCols)
spatialDynamics = spatial_dynamics.markov(observations, w, method="spatial")
return localAutoCorrelation, globalAutoCorrelation, spatialDynamics
def autocorrelation():
#replace variables here as above.
observations = Weights.extractObservations("usjoin.csv", "ALL", [2008])
w = Weights.generateWeightsUsingShapefile("us48.shp",
idVariable="STATE_NAME")
globalAutocorrelation = autocorrelation.globalAutocorrelation(
observations, w)
localAutocorrelation = autocorrelation.localAutocorrelation(
observations, w)
print(globalAutocorrelation, localAutocorrelation)
return str(globalAutocorrelation) + " " + str(localAutocorrelation)