def StudyAreaWatershed(output_workspace, dem_hydro, processes):
# Check out the ArcGIS Spatial Analyst extension license
arcpy.CheckOutExtension("Spatial")
# Set environment variables
arcpy.env.overwriteOutput = True
arcpy.env.workspace = output_workspace
arcpy.env.scratchWorkspace = output_workspace
arcpy.env.cellSize = dem_hydro
arcpy.env.parallelProcessingFactor = processes
# List parameter values
arcpy.AddMessage("Workspace: {}".format(arcpy.env.workspace))
arcpy.AddMessage("DEM hydro: "
"{}".format(arcpy.Describe(dem_hydro).baseName))
arcpy.AddMessage("processes: {}".format(processes))
# Fill sinks
arcpy.AddMessage("Beginning filling sinks...")
dem_fill = arcpy.sa.Fill(in_surface_raster=dem_hydro)
arcpy.AddMessage("Fill sinks complete.")
# Calculate D8 flow direction (suitable for input into the Watershed tool)
arcpy.AddMessage("Beginning flow direction...")
flow_dir_d8 = arcpy.sa.FlowDirection(in_surface_raster=dem_fill,
flow_direction_type="D8")
flow_direction_d8 = os.path.join(output_workspace, "flow_direction_d8")
flow_dir_d8.save(flow_direction_d8)
# Calculate raster statistics and build pyramids
arcpy.AddMessage(" Calculating statistics...")
arcpy.CalculateStatistics_management(flow_direction_d8)
arcpy.AddMessage(" Building pyraminds...")
arcpy.BuildPyramids_management(flow_direction_d8)
arcpy.AddMessage("Flow direction complete.")
# Calculate flow accumulation
arcpy.AddMessage("Beginning flow accumulation...")
flow_accum_d8 = arcpy.sa.FlowAccumulation(flow_dir_d8,
data_type="FLOAT",
flow_direction_type="D8")
flow_accumulation_d8 = os.path.join(output_workspace,
"flow_accumulation_d8")
flow_accum_d8.save(flow_accumulation_d8)
# Calculate raster statistics and build pyramids
arcpy.AddMessage(" Calculating statistics...")
arcpy.CalculateStatistics_management(flow_accumulation_d8)
arcpy.AddMessage(" Building pyraminds...")
arcpy.BuildPyramids_management(flow_accumulation_d8)
arcpy.AddMessage("Flow accumulation complete.")
# Return
arcpy.SetParameter(3, flow_accumulation_d8)
def multi_convert_to_raster(polygon_fc_list, output_workspace):
for polygon_fc in polygon_fc_list:
env.extent = polygon_fc
env.snapRaster = SNAP_RASTER
short_name = os.path.splitext(os.path.basename(polygon_fc))[0]
arcpy.AddMessage("Converting {}...".format(short_name))
output_raster = os.path.join(output_workspace, short_name + '_raster')
lagoslakeid_field = arcpy.ListFields(polygon_fc,
'*lagoslakeid')[0].name
zoneid_field = arcpy.ListFields(polygon_fc, '*zoneid')[0].name
if lagoslakeid_field:
zone_field = lagoslakeid_field
else:
zone_field = zoneid_field
output_raster = arcpy.PolygonToRaster_conversion(polygon_fc,
zone_field,
output_raster,
'CELL_CENTER',
cellsize=CELL_SIZE)
arcpy.BuildPyramids_management(output_raster, SKIP_FIRST=True)
if lagoslakeid_field:
arcpy.BuildRasterAttributeTable_management(output_raster, True)
arcpy.AddField_management(output_raster, 'lagoslakeid', 'LONG')
arcpy.CalculateField_management(output_raster, 'lagoslakeid',
'!Value!', 'PYTHON_9.3')
arcpy.AddMessage("Completed.")
def heatMapGen(radius, cellSize):
print "Setting database and workspace..." + str(time.ctime())
arcpy.env.workspace = "D:/GD/WGiSR/_Konferencje/Plener 2018/heatMap/data.gdb"
print " Database and workspace set! " + str(time.ctime())
print "Setting local variables..." + str(time.ctime())
mxd = arcpy.mapping.MapDocument(
"D:/GD/WGiSR/_Konferencje/Plener 2018/heatMap/HeatMap.mxd")
df = arcpy.mapping.ListDataFrames(mxd)[0]
template = "D:/GD/WGiSR/_Konferencje/Plener 2018/heatMap/kd_temp_hypso.lyr"
inData = "OSM_STOPS_2180"
print " Local variables set! " + str(time.ctime())
print " Generating Heat Map..." + str(time.ctime())
arcpy.Delete_management("kd")
arcpy.CheckOutExtension("Spatial")
kd = arcpy.sa.KernelDensity(inData, "NONE", cellSize, radius,
"SQUARE_KILOMETERS")
kd.save("kd")
arcpy.BuildPyramids_management("kd")
arcpy.MakeRasterLayer_management("kd")
layer = arcpy.mapping.Layer("kd")
tempLyr = arcpy.mapping.Layer(template)
arcpy.ApplySymbologyFromLayer_management(layer, tempLyr)
arcpy.mapping.AddLayer(df, layer)
mxd.save()
print " Heat Map generated! " + str(time.ctime())
print " Exporting map..." + str(time.ctime())
arcpy.mapping.ExportToJPEG(
mxd,
"D:/GD/WGiSR/_Konferencje/Plener 2018/heatMap/_genMaps/HeatMap_radius_"
+ str(radius) + ".jpg")
print " Map exported! " + str(time.ctime())
def build_stats(outfilename):
try:
# generate pyramids and statistics for final output
gprint('BUILDING OUTPUT STATISTICS & PYRAMIDS' + '\n')
arcpy.CalculateStatistics_management(outfilename, "1", "1", "#")
arcpy.BuildPyramids_management(outfilename)
except:
pass
def run_combine(in_directory_species_grids, raster_list_combine, folder,
out_folder, region):
# sets workspace to locations with input species rasters and generates list
arcpy.env.workspace = in_directory_species_grids + os.sep + folder
sp_list = arcpy.ListRasters()
# combine each species file with the habitat and elevation rasters
for spe_raster in sp_list: # loops over each species
c_raster_list = raster_list_combine # makes a copy of list with the use layers for combine
if spe_raster.split(
"_"
)[1] in skip_species: # bypasses species in the species skip list set by user
continue
else:
print('Start Generating species overlap files'
) # print for tracking
start_raster = datetime.datetime.now(
) # elapse clock for species combine
# path species file
in_spe = in_directory_species_grids + os.sep + folder + os.sep + spe_raster
c_raster_list.insert(0, in_spe)
try: # try except loop so an error won't cause the script to stop
if not arcpy.Exists(out_folder + os.sep + spe_raster
): # skips files that already exist
# inset the path to the species file to list of raster to combine in index position 0
print('Start Combine for {0} with {1}'.format(
spe_raster, c_raster_list)) # print for tracking
print("Out location will be {0}".format(
os.path.join(out_folder, spe_raster[:8])))
out_combine = Combine(
c_raster_list
) # runs combine tools from spatial analyst
# saves combine; set out name to 8 character to the limit for a ESRI grid
out_combine.save(os.path.join(out_folder, spe_raster[:8]))
# print for tracking
print 'Saved {0} \n Build raster attribute table'.format(
out_folder + os.sep + spe_raster[:8])
# Builds raster attribute table and pyramids
arcpy.BuildRasterAttributeTable_management(
os.path.join(out_folder, spe_raster[:8]))
print 'Build pyramids'
arcpy.BuildPyramids_management(out_folder + os.sep +
spe_raster[:8])
# generates output text files used as lookups to identify habitat, elevation and species
output_lookup_tables(spe_raster, c_raster_list, out_folder,
region)
print 'Completed {0} in {1}'.format(
out_folder + os.sep + spe_raster[:8],
datetime.datetime.now() - start_raster)
except Exception as error: # exceptions for if error trips; print error and deleted any temp file generated
print('Error was {0} elapse time was {1}'.format(
error.args[0],
datetime.datetime.now() - start_raster))
if arcpy.Exists(out_folder + os.sep + spe_raster[:8]):
arcpy.Delete_management(out_folder + os.sep +
spe_raster[:8])
c_raster_list.remove(in_spe)
def build_stats(raster):
"""Builds statistics and pyramids for output rasters"""
try:
arcpy.CalculateStatistics_management(raster, "1", "1", "#")
except Exception:
gprint('Statistics failed. They can still be calculated manually.')
try:
arcpy.BuildPyramids_management(raster)
except Exception:
gprint('Pyramids failed. They can still be built manually.')
return
def fill_sinks(workspace, in_raster, out_raster):
# after http://desktop.arcgis.com/en/arcmap/10.4/tools/spatial-analyst-toolbox/fill.htm
# Set environment settings
env.workspace = workspace
# Execute ExtractByMask
outFill = Fill(in_raster)
# Save the output
outFill.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def extract(workspace, in_raster, mask, out_raster):
# after http://desktop.arcgis.com/en/arcmap/10.4/tools/spatial-analyst-toolbox/extract-by-mask.htm
# Set environment settings
env.workspace = workspace
# Execute ExtractByMask
outExtractByMask = ExtractByMask(in_raster, mask)
# Save the output
outExtractByMask.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def idw(inPointFeatures, zField, out_raster, in_Mask):
if os.path.exists(out_raster):
return
cellSize = 0.02
power = 2
total_raster = os.path.join(os.path.dirname(out_raster),
os.path.basename(out_raster) + "IDW")
arcpy.CheckOutExtension("GeoStats")
arcpy.IDW_ga(inPointFeatures, zField, "", total_raster, cellSize, power)
outExtractByMask = ExtractByMask(total_raster, in_Mask)
outExtractByMask.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
arcpy.Delete_management(total_raster)
def Krig(inPointFeatures, zField, outRaster, in_Mask):
if os.path.exists(outRaster):
return
kModel = "CIRCULAR"
cellSize = 0.02
total_raster = os.path.join(os.path.dirname(outRaster),
os.path.basename(outRaster) + "Kr")
arcpy.CheckOutExtension("GeoStats")
arcpy.Kriging_3d(inPointFeatures, zField, total_raster, kModel, cellSize)
outExtractByMask = ExtractByMask(total_raster, in_Mask)
arcpy.Delete_management(total_raster)
outExtractByMask.save(outRaster)
arcpy.BuildPyramids_management(outRaster)
def get_soc0_999(workspace, in_raster, value_table, out_raster):
# Set environment settings
env.workspace = workspace
# Set local variables
field_name = 'mukey'
lookup_field = 'soc0_999'
arcpy.JoinField_management(in_raster, field_name, value_table, field_name,
lookup_field)
#arcpy.AddJoin_management(in_raster, field_name, value_table, field_name)
outraster = Lookup(in_raster, lookup_field)
arcpy.CalculateStatistics_management(outraster)
outraster.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def buildPyramids_new(inras, technique):
print 'running buildPyramids() function....'
#Build Pyramids for single Raster Dataset
#Define the type and compression of pyramids in the tool
#Skip if dataset already has pyramids
pyramid_level = "-1"
skipfirst = "NONE"
resample_technique = technique
compression_type = "JPEG"
compression_quality = "100"
skipexist = "OVERWRITE"
arcpy.BuildPyramids_management(inras, pyramid_level, skipfirst,
resample_technique, compression_type,
compression_quality, skipexist)
def execute(self, parameters, messages):
arcpy.env.overwriteOutput = True
for param in parameters:
arcpy.AddMessage("Parameter: %s = %s" %
(param.name, param.valueAsText))
input_bathymetry = parameters[0].valueAsText
output_directory = parameters[2].valueAsText
depths = parameters[1].valueAsText
if not os.path.exists(output_directory):
os.makedirs(output_directory)
arcpy.AddMessage("Extracting depths from " + str(input_bathymetry) +
".")
depth_list = load_depth_string(depths)
arcpy.AddMessage("Depths are: " + str(depth_list))
# Set environment variables for processing
env.mask = input_bathymetry
env.cellSize = input_bathymetry
extraster = arcpy.Raster(input_bathymetry)
extent1 = extraster.extent
env.extent = extent1
env.workspace = output_directory
# Conduct the extraction process
# Loop through each depth in the Depths list
for item in depth_list:
individual_depth = int(float(item))
null_value_clause = "VALUE > " + "-" + str(individual_depth)
arcpy.AddMessage("Processing depth: " + str(individual_depth))
output_set_null = SetNull(input_bathymetry, "1", null_value_clause)
output_set_null_2 = ApplyEnvironment(output_set_null)
output_set_null_2.save(
os.path.join(output_directory, "bath" + str(individual_depth)))
arcpy.env.pyramid = "PYRAMIDS 3 BILINEAR JPEG"
arcpy.BuildPyramids_management(
os.path.join(output_directory, "bath" + str(individual_depth)))
return
def flow_direction(workspace, in_raster, out_raster):
# after http://desktop.arcgis.com/en/arcmap/10.4/tools/spatial-analyst-toolbox/flow-direction.htm
# Description: Creates a raster of flow direction from each cell to its
# steepest downslope neighbor.
# Requirements: Spatial Analyst Extension
# Set environment settings
env.workspace = workspace
# Set local variables
inSurfaceRaster = in_raster
# Execute FlowDirection
outFlowDirection = FlowDirection(inSurfaceRaster, "NORMAL")
# Save the output
outFlowDirection.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def main(out_directory, in_directory_species_grids, skip_reg):
start_time = datetime.datetime.now() # elapse clock
print "Start Time: " + start_time.ctime()
arcpy.CheckOutExtension("Spatial") # Check out license
# create out directory if it does not exist
if not os.path.exists(out_directory):
os.mkdir(out_directory)
list_dir = os.listdir(
in_directory_species_grids
) # get list of folders with species files - starts with region
for folder in list_dir:
region = folder.split('_')[0] # extract region abb
print("\nWorking on {0}".format(region)) # print for tracking
if region in skip_reg: # bypass region is in skip region set by user
continue
else:
# Create out folder if it doesn't exist
out_folder = out_directory + os.sep + folder
if not os.path.exists(out_folder):
os.mkdir(out_folder)
set_extent(region, snap_dict) # set processing extent
print('Generating lists of rasters to combine'
) # print for tracking
if include_on_off: # user defined inputs - if on/off is should be included variable will be true
# NOTE in CONUS when including on/off the number of unique values is extremely high
hab_to_combine = get_hab_ele_rast_path(region,
raster_layer_libraries)
rast_to_combine = get_on_off_field(hab_to_combine, region,
raster_layer_libraries)
else:
rast_to_combine = get_hab_ele_rast_path(
region, raster_layer_libraries)
for r in rast_to_combine: # Build att table and pyramids for each raster in combine
print(
'Building attribute tables and pyramids for {0}'.format(r))
arcpy.BuildRasterAttributeTable_management(r)
arcpy.BuildPyramids_management(r)
# Run combine for each species get list of species raster for region
run_combine(in_directory_species_grids, rast_to_combine, folder,
out_folder, region)
end = datetime.datetime.now() # end elapse clock
print "End Time: " + end.ctime()
elapsed = end - start_time
print "Elapsed Time: " + str(elapsed)
def LayerTif(tifPath):
#检查文件是否存在
print "路径有效！正在检查文件夹是否存在TIF数据……"
if os.path.exists(tifPath) == False:
print "指定路径的tif数据不存在！"
return
# 创建.lyr文件
try:
print "构建影像金字塔"
arcpy.BuildPyramids_management(tifPath)
# print "我去年买了表"
# arcpy.env.cellSize = tifPath
# print arcpy.env.cellSize
name, ext = os.path.splitext(tifPath)
RDlyr = name + ".lyr"
arcpy.MakeRasterLayer_management(tifPath, name, "", "", "")
arcpy.SaveToLayerFile_management(name, RDlyr, "RELATIVE")
except Exception, e:
print "error: ", e
return
def flow_accumulation(workspace, in_raster, out_raster):
# after http://desktop.arcgis.com/en/arcmap/10.4/tools/spatial-analyst-toolbox/flow-accumulation.htm
# Description: Creates a raster of accumulated flow to each cell.
# Requirements: Spatial Analyst Extension
# Set environment settings
env.workspace = workspace
# Set local variables
inFlowDirRaster = in_raster
inWeightRaster = ''
dataType = 'INTEGER'
# Execute FlowDirection
outFlowAccumulation = FlowAccumulation(inFlowDirRaster, inWeightRaster,
dataType)
# Save the output
outFlowAccumulation.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def slope(workspace, in_raster, out_raster):
# after http://desktop.arcgis.com/en/arcmap/10.4/tools/spatial-analyst-toolbox/slope.htm
# Description: Identifies the rate of maximum change
# in z-value from each cell.
# Requirements: Spatial Analyst Extension
# Set environment settings
env.workspace = workspace
# Set local variables
inRaster = in_raster
outMeasurement = 'DEGREE'
# Execute Slope
slopeDeg = Slope(inRaster, outMeasurement)
slopeRad = Times(slopeDeg, math.pi / 180)
# Save the output
slopeRad.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def multi_convert_to_raster(polygon_fc_list, output_workspace):
for polygon_fc in polygon_fc_list:
if 'hu12' in polygon_fc or 'buff' in polygon_fc or ('ws' in polygon_fc and 'nws' not in polygon_fc):
cell_size = 30
else:
cell_size = CELL_SIZE
env.extent = polygon_fc
env.snapRaster = SNAP_RASTER
short_name = os.path.splitext(os.path.basename(polygon_fc))[0]
arcpy.AddMessage("Converting {}...".format(short_name))
output_raster = os.path.join(output_workspace, short_name + '_raster')
zoneid_field = arcpy.ListFields(polygon_fc, '*zoneid')[0].name
output_raster = arcpy.PolygonToRaster_conversion(polygon_fc,
zoneid_field,
output_raster,
'CELL_CENTER',
cellsize = cell_size)
arcpy.BuildPyramids_management(output_raster, SKIP_FIRST = True)
arcpy.AddMessage("Completed.")
def do_calc(_):
r = fct(_)
if r is not None and 'save' in dir(r):
# do this so we can also use functions that don't return a raster
r.save(_)
del r
if buildPyramids:
has_pyramids = False
#~ # HACK: really not working for some reason
#~ retry = 0
#~ while retry < retries and not has_pyramids:
try:
print "Building pyramids"
arcpy.BuildPyramids_management(_)
has_pyramids = True
except:
#~ retry += 1
#~ delay = math.pow(2, retry)
#~ print "Building pyramids failed. Retrying in {} seconds...".format(delay)
print "Building pyramids failed."
#~ time.sleep(delay)
return _
def build_pyramids():
f = 'E:\\FVC内蒙古植被覆盖数据\\fusion\\fusion_int\\2018.tif'
arcpy.env.workspace = "C:/Workspace"
inws = "folder"
includedir = "INCLUDE_SUBDIRECTORIES"
buildpy = "BUILD_PYRAMIDS"
calcstats = "CALCULATE_STATISTICS"
buildsource = "NONE"
blockfield = "#"
estimatemd = "#"
skipx = "4"
skipy = "6"
ignoreval = "0;255"
pylevel = "3"
skipfirst = "NONE"
resample = "BILINEAR"
compress = "JPEG"
quality = "80"
skipexist = "SKIP_EXISTING"
# arcpy.BuildPyramidsAndStatistics_management()
print('building '+f)
arcpy.BuildPyramids_management(f)
def topographic_wetness_index(workspace, flow_accumulation_raster,
slope_raster, out_raster):
# Description: Computes topographic wetness index using flow accumulation
# and slope after Quin et al. 1991 (note that we assume 30m
# cell size, so cell_size_squared = 30^2 = 900)
#
# Quinn, P. F. B. J., et al.
# "The prediction of hillslope flow paths for distributed hydrological
# modelling using digital terrain models."
# Hydrological processes 5.1 (1991): 59-79.
# DOI: 10.1002/hyp.3360050106
#
# Requirements: Spatial Analyst Extension
# Set environment settings
env.workspace = workspace
# Execute math processors
# Note that each one of these creates a raster file in the workspace,
# but we only save the last one.
cell_size_squared = 900
tan_slope_raster = Tan(slope_raster)
squared_flow_accumulation_raster = Times(flow_accumulation_raster,
cell_size_squared)
quotient = Divide(squared_flow_accumulation_raster, tan_slope_raster)
twi = Ln(quotient)
# We need to normalize the twi values: (twi - twi_min) / (twi_max - twi_min)
twi_min_result = arcpy.GetRasterProperties_management(twi, "MINIMUM")
twi_max_result = arcpy.GetRasterProperties_management(twi, "MAXIMUM")
twi_min = float(twi_min_result.getOutput(0))
twi_max = float(twi_max_result.getOutput(0))
twi_top = Minus(twi, twi_min)
twi_bottom = twi_max - twi_min
twi_norm = Divide(twi_top, twi_bottom)
# Save the output
twi_norm.save(out_raster)
arcpy.BuildPyramids_management(out_raster)
def PrjExtRaster(outTemp, theSR, cSize, fcBuf, Year, ACPFlkup):
# Project to Buf's projection, unless it's in Albers
if theSR != '43007':
prjTemp = "%s//PRJTemp.tif" % env.scratchFolder
arcpy.ProjectRaster_management(outTemp, prjTemp, fcBuf, "NEAREST", cSize)
else:
prjTemp = outTemp
# Majority filter to reduce S&P
env.snapRaster = prjTemp
arcpy.AddMessage(" Majority")
if cSize > 30:
RMaj1 = MajorityFilter(prjTemp, "EIGHT", "HALF")
RMaj2 = MajorityFilter(RMaj1, "EIGHT", "HALF")
RMaj3 = MajorityFilter(RMaj2, "FOUR", "HALF")
RMajF = MajorityFilter(RMaj3, "FOUR", "HALF")
else:
RMaj1 = MajorityFilter(prjTemp, "EIGHT", "HALF")
RMajF = MajorityFilter(RMaj1, "FOUR", "HALF")
# Extract
extNASS = ExtractByMask(RMajF, fcBuf)
extNASS.save("wsCDL%s" % Year)
# join
arcpy.JoinField_management(extNASS, "Value", ACPFlkup, "Value", ["CLASS_NAME", "ROTVAL"])
#fini
arcpy.BuildPyramids_management(extNASS)
# cleanup
arcpy.Delete_management(outTemp)
if arcpy.Exists(prjTemp):
arcpy.Delete_management(prjTemp)
import arcpy
from arcpy import env
from datetime import datetime
import logging
start_timestamp = datetime.now()
# path to folder with rasters
env.workspace = r"C:\temp"
# create logging file
logging.basicConfig(filename="BuildStatisticsScriptLog.txt", level=logging.DEBUG)
RasterList = arcpy.ListRasters("*") # list rasters
TotalRasterCount = len(RasterList)
Counter = 0 # set counter for print messages
for raster in RasterList:
Counter += 1
arcpy.BuildPyramids_management(raster, "-1", "NONE", "NEAREST", "DEFAULT", "75", "SKIP_EXISTING")
print "Done with " + raster + " (" + str(Counter) + " out of " + str(TotalRasterCount) + ")"
logging.info("done with " + raster + " (" + str(Counter) + " out of " + str(TotalRasterCount) + ")")
print "done in: " + str(datetime.now() - start_timestamp)
logging.info("done at " + str(datetime.now()))
try:
maps_dir = glob.glob(maps_dir)[0]
except:
logging.info('No such folder: %s' % (maps_dir))
continue
print('UTM zone: %s' % (UTMz_name))
env.workspace = maps_dir
dat_files_list = arcpy.ListFiles("*.dat")
logging.info('Nr map files for %s: %d' %
(UTMz_name, len(dat_files_list)))
## Build pyramids for all .dat files in folder
for layer in dat_files_list:
print(layer)
arcpy.BuildPyramids_management(
os.path.join(env.workspace, layer),
skip_existing="SKIP_EXISTING"
) ## do not create pyramids if they already exist
print(toc(start_time))
## Test with parallel approach (not exactly working!)
#pool = multiprocessing.Pool(24, None, None, 1)
#
#pool.map(arcpy.BuildPyramids_management, arcpy.ListFiles())
#
## closing pool and waiting for each task to be finished
#pool.close()
#pool.join()
df = arcpy.mapping.ListDataFrames(mxd, "Layers")[0]
sr = arcpy.SpatialReference(2193)
print df.name
#todo export jpegs
print 'export JPEG'
for pageNum in range(1, mxd.dataDrivenPages.pageCount + 1):
print 'export ' + str(pageNum) + '...'
mxd.dataDrivenPages.currentPageID = pageNum
#todo: HARDCODE BELOW r"D:\tmp\Output"
arcpy.mapping.ExportToJPEG(mxd,
r"D:\tmp\Output" + str(pageNum) + ".jpg",
df,
df_export_width=1200,
df_export_height=1600,
world_file=True,
resolution=300,
color_mode="24-BIT_TRUE_COLOR")
arcpy.DefineProjection_management(r"D:\tmp\Output" + str(pageNum) + ".jpg",
sr)
arcpy.BuildPyramids_management(r"D:\tmp\Output" + str(pageNum) + ".jpg")
#todo remove Object
del mxd
#todo my Cool Message
print "Susan is Very cool"
def build_pyramid(in_raster):
arcpy.BuildPyramids_management(in_raster)
def createpyramids(inraster):
"""although this is a one liner, it could maybe use some customization"""
arcpy.BuildPyramids_management(inraster)
return True
import arcpy
import os
from arcpy import env
from arcpy.sa import *
import csv
env.overwriteOutput = True
env.workspace = r'D:\1. Codes and Programs\1. river detection comparison methods\00_my_Matlab_codes_for_single_image\sentinel2_T22WEV'
rasters = arcpy.ListRasters("*", "tif")
for raster in rasters:
print(raster)
arcpy.CalculateStatistics_management(raster)
arcpy.BuildPyramids_management(raster)
]
# get list of on/off field layers for region
# on_off_field = raster_layer_libraries + os.sep + region + '_' + 'OnOffField.gdb'
# arcpy.env.workspace = on_off_field
# raster_list_on_off = arcpy.ListRasters()
# # add path to the raster name for combine because the workspace is changing
# # append the habitat and elevation raster to to lst of raster to be combine with the path to the gdb
# # because the workspace is changing
# for v in raster_list_on_off :
# raster_list_combine.append(on_off_field + os.sep + v)
# build att table and builds for all rasters in combine
for r in raster_list_combine:
arcpy.BuildRasterAttributeTable_management(r)
arcpy.BuildPyramids_management(r)
# get list of species raster for region
arcpy.env.workspace = in_directory_species_grids + os.sep + folder
sp_list = arcpy.ListRasters()
# combine each species file with the habitat and elevation rasters
for spe_raster in sp_list:
if spe_raster.split("_")[1] in skip_species:
continue
else:
start_raster = datetime.datetime.now()
if not arcpy.Exists(out_folder + os.sep + spe_raster):
in_spe = in_directory_species_grids + os.sep + folder + os.sep + spe_raster
# inset the path to the species file to list of raster to combine in index position 1
raster_list_combine.insert(0, in_spe)
