def arcResampleRasters (FileList=["file1.tif","file2.tif"],
inPath=None,
outPath=None,
scale="templateRaster.tif"):
import arcpy
import os
if inPath==None: inPath==os.getcwd()
if inPath==None: inPath==os.getcwd()
inFileList = for f in FileList: inPath + "scaled"+str(scale)+f)
inFileString = if len(inFileList>1): ';'.join(map(str, inFileList)) else str(inFileList)
outFileList = for f in FileList: outPath + "scaled"+str(scale)+f)
outFileString = ';'.join(map(str, outFileList)
#Rescale Function Call
arcpy.Rescale_management(inFileString, outFileString, resolution,"CUBIC")
print("completed rescale, output file location:", outPath)
return()
def shift_and_rescale(image, mask_arr):
basename = os.path.splitext(os.path.basename(image))[0]
image = arcpy.sa.Raster(image)
mask = arcpy.NumPyArrayToRaster(mask_arr.astype(np.uint8) * 255)
arcpy.env.outputCoordinateSystem = image
os.makedirs(resources.temp_shifted, exist_ok=True)
shifted = os.path.join(resources.temp_shifted,
"{}.tif".format(basename))
arcpy.Shift_management(mask,
shifted,
image.extent.XMin - mask.extent.XMin,
image.extent.YMin - mask.extent.YMin,
in_snap_raster=image)
# match LIDAR resolution
os.makedirs(resources.temp_rescaled, exist_ok=True)
rescaled = os.path.join(resources.temp_rescaled,
"{}.tif".format(basename))
arcpy.Rescale_management(shifted, rescaled, image.meanCellWidth,
image.meanCellHeight)
return rescaled
columnsAco = columnsAcoResult.getOutput(0)
print rowsAco
print type(columnsAco)
#Chooses appropriate raster to apply landsat cell size to, scales raster up while considering possible row/column number mismatch
#between acolite and original
cellSizeXFlt = float(cellSizeX)
cellSizeYFlt = float(cellSizeY)
rowsOriginalFlt = float(rowsOriginal)
columnsOriginalFlt = float(columnsOriginal)
rowsAcoFlt = float(rowsAco)
columnsAcoFlt = float(columnsAco)
if removeborderYN == 'true':
arcpy.Rescale_management(
"intermedClipped", "intermedScale",
cellSizeXFlt / (columnsAcoFlt / columnsOriginalFlt),
cellSizeYFlt / (rowsAcoFlt / rowsOriginalFlt))
else:
if flipYN == 'true':
arcpy.Rescale_management(
"intermedMir", "intermedScale",
cellSizeXFlt / (columnsAcoFlt / columnsOriginalFlt),
cellSizeYFlt / (rowsAcoFlt / rowsOriginalFlt))
else:
if rotateYN == 'true':
arcpy.Rescale_management(
"intermedRot", "intermedScale",
cellSizeXFlt / (columnsAcoFlt / columnsOriginalFlt),
cellSizeYFlt / (rowsAcoFlt / rowsOriginalFlt))
else:
arcpy.Rescale_management(
#flips acolite image if appropriate
if flipYN == 'true':
if rotateYN == 'true':
arcpy.Mirror_management("intermedRot", "intermedMir")
else:
arcpy.Mirror_management(acoRaster, "intermedMir")
#rescales acolite image
cellSizeXResult = arcpy.GetRasterProperties_management(pathLandsat, "CELLSIZEX")
cellSizeYResult = arcpy.GetRasterProperties_management(pathLandsat, "CELLSIZEY")
cellSizeX = cellSizeXResult.getOutput(0)
cellSizeY = cellSizeYResult.getOutput(0)
#Chooses appropriate raster to apply landsat cell size to
if flipYN == 'true':
arcpy.Rescale_management("intermedMir", "intermedScale", cellSizeX, cellSizeY)
else:
if rotateYN == 'true':
arcpy.Rescale_management("intermedRot", "intermedScale", cellSizeX, cellSizeY)
else:
arcpy.Rescale_management(acoRaster, "intermedScale", cellSizeX, cellSizeY)
#Reclassify and clip corrected acolite image to get rid of nodata border
myRemapRange = RemapRange([[-1,1,1]])
# Execute Reclassify
outReclassify = arcpy.sa.Reclassify("intermedScale", "VALUE",myRemapRange,'NODATA')
##====================================
## arcpy_RescaleRaster
##Rescale
##Usage: Usage: Rescale_management in_raster out_raster x_scale y_scale
import arcpy
arcpy.env.workspace = r"C:/Workspace"
##Rescale a TIFF image by a factor of 4 in both directions
arcpy.Rescale_management("image.tif", "rescale.tif", "4", "4")