Hello,
I am running a script where in the first step I create a xy-Event-Layer out of txt-files. I am loading like 2000 files one after another out of one folder.
Now the process works fine, only it gets slower and slower. After 8 hours it needs like 4 minutes for one file, while in the beginning it finished 6 files in one minute.
My Question is:
Could it be that ArcGIS is saving something like an image of the XY-Eventlayers in temp-files somewhere so that my RAM can't work anymore in the end?
The thing is, if I kill the script, turn the PC off and on again and start again, it works as fast as in the beginning. If I only delete the files in the "delete"folder, (which I created for the output of line 31-38 which appears during the process) and in the "normal" temp-folder, it doesn't get better.
Thanks in advance for any help!
The script looks like this:
import os, arcpy
Pfad="C:/Users/Lolaley/Desktop/DAC_MD/"
Pfad1="C:/Users/Lolaley/Desktop/DAC_MD/Delete/"
PfadTxt="C:/Users/Lolaley/Desktop/DAC_MD/01_MD_HH/"
# Festlegen ob das Ergebnis Hydr. Höhen oder Salzgehalt ist
Sz="HH"
arcpy.CheckOutExtension("Spatial")
TextDateienListe = os.listdir(PfadTxt)
import re
def k(s):
return [w.isdigit() and int(w) or w for w in re.split(r'(\d+)', s)]
TextDateienListe = sorted(TextDateienListe, key=k)
for Datei in TextDateienListe:
#Datei=TextDateienListe[1]
b = os.path.splitext(Datei)
# XY-Event Layer erstellen // Input: txt-Datei //Output: Layer mit Variable EventLayerName
EventLayerName= b[0] + "_Layer"
arcpy.MakeXYEventLayer_management(PfadTxt+Datei,"x","y",EventLayerName,"PROJCS['ETRS_1989_UTM_Zone_33N',GEOGCS['GCS_ETRS_1989',DATUM['D_ETRS_1989',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',15.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]];-5120900 -9998100 10000;-100000 10000;-100000 10000;0,001;0,001;0,001;IsHighPrecision",Sz)
# Kriging // Output: Raster rXXX
arcpy.gp.Kriging_sa(EventLayerName,Sz,Pfad1+"r" + b[0],"Spherical 15,717080","15,7170800000001","VARIABLE 12","#")
# Hydrotopdatei kopieren zum späteren Einlesen der gemittelten Werte
arcpy.CopyFeatures_management(Pfad+"HydrotMD.shp",Pfad1+"Hydrotop" + b[0]+".shp","#","0","0","0")
#Zonale Statistiken: Mittelwerte bilden für Hydrotop und Raster und in Tabelle ausspucken
arcpy.gp.ZonalStatisticsAsTable_sa(Pfad1+"Hydrotop" + b[0]+".shp","ID_COMTESS",Pfad1+"r" + b[0],Pfad1+ "t"+b[0],"DATA","MEAN")
# Tabellenfeld per ID_COMTESS-Feld in die hydrotop-Datei integrieren
arcpy.JoinField_management(Pfad1+"Hydrotop" + b[0]+".shp","ID_COMTESS",Pfad1+ "t"+b[0],"ID_COMTESS","MEAN")
#Exportieren der ID mit dem dazugehörigen Mittelwert in eine Textdatei
arcpy.ExportXYv_stats(Pfad1+"Hydrotop" + b[0]+".shp","ID_COMTESS;MEAN","SPACE",Pfad + "Results/01_MD_"+Sz+"_"+b[0]+".txt","#")
arcpy.CheckInExtension("Spatial")
