GCMC_PythonScripts/parallel_pdal_buildingheights at main · WillhKessler/GCMC_PythonScripts · GitHub

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import multiprocessing
import threading
import json

from multiprocessing import Pool

def definegrid(projName):
    #Call the USGS
    #Get the list of projects
    ## Define Lidar Source
    #lidarsource="http://usgs-lidar-public.s3.amazonaws.com/MA_CentralEastern_1_2021/ept.json" # Boston
    lidarsource="http://usgs-lidar-public.s3.amazonaws.com/USGS_LPC_TX_Central_B1_2017_LAS_2019/ept.json" #Austin

def processProject():


def lidarPipe(lidarsource,bufferbounds):
    LAStiles = json.dumps([
                    {
                        "type":"readers.ept",
                        "filename":lidarsource,
                        "bounds":str(bufferbounds)
                        },
                    {
                        "type":"filters.hag_nn",
                        "allow_extrapolation":"true",
                    },
                    {
                         "type":"filters.expression",
                        "expression":"(!(Classification ==2 || Classification ==3 || Classification ==4 || Classification ==5 || Classification ==7 || Classification ==18) && HeightAboveGround>1)"
                    },
                    {
                        "type":"filters.crop",
                        "polygon":footprintWKT
                    },
                    {
                         "filename":outputdirectory+"\\"+name+"testlasAOI_{}.las".format("a"+str(count))
                    }

                    ])


    pipeline = pdal.Pipeline(LAStiles)
    pipeline.execute()
    arrays = pipeline.arrays
    return arrays


N = 5000000
def cube(x):
    return math.sqrt(x)


if __name__ == "__main__":
    with Pool() as pool:
      result = pool.map(cube, range(10,N))
    print("Program finished!")