def export_maps(mxd, btn_layer, btn_export_pdf, btn_export_png):
map_name = str(btn_layer.objectName())[6:]
if btn_export_png.isChecked() == True:
#print btn_layer.text(), ' Print PNG'
map.ExportToPNG(mxd, map_name+".png", resolution=300, \
transparent_color='255, 255, 255')
if btn_export_pdf.isChecked() == True:
#print btn_layer.text(), ' Print PDF'
map.ExportToPDF(mxd, map_name+".pdf" )
def exportMap(parameter):
inMap = parameter[0]
outMap = parameter[1]
formatMap = parameter[2]
arcpy.env.overwriteOutput = True
mxd = mapping.MapDocument(inMap)
mxd.activeView = 'PAGE_LAYOUT'
if formatMap == 'JPEG':
mapping.ExportToJPEG(mxd, outMap)
if formatMap == 'PDF':
mapping.ExportToPDF(mxd, outMap)
if formatMap == 'BMP':
mapping.ExportToBMP(mxd, outMap)
if formatMap == 'PNG':
mapping.ExportToPNG(mxd, outMap)
if formatMap == 'TIFF':
mapping.ExportToTIFF(mxd, outMap)
if formatMap == 'GIF':
mapping.ExportToGIF(mxd, outMap)
else:
mapping.ExportToJPEG(mxd, outMap)
backup_mxd = os.path.join(backup_dir, mdoc_name + '.mxd')
print "Saving as %s" % backup_mxd
shutil.copy(mapdoc, backup_mxd)
# update position of legend element
#main_df = mp.ListDataFrames(mxd)[1]
#main_lyrs = mp.ListLayers(mxd, "", main_df)
leg_elm = mp.ListLayoutElements(mxd, "LEGEND_ELEMENT", "Legend")[0]
leg_elm.elementPositionX = 8.8
leg_elm.elementPositionY = 5.7 - leg_elm.elementHeight
#save mapdoc
mxd.save()
#export map
map_name = os.path.join(out_dir, mdoc_name)
print "Exporting %s" % mapdoc
mp.ExportToPNG(mxd, map_name, resolution=96)
print '\n'
del mxd
count += 1
mapping.AddLayer(df, addIdwLyr, "AUTO_ARRANGE")
legend1.autoAdd = False
legend2.autoAdd = True
mapping.AddLayer(df, addSoilPointLyr, "AUTO_ARRANGE")
legend1.autoAdd = False
legend2.autoAdd = False
mapping.AddLayer(df, addBoundaryLyr, "AUTO_ARRANGE")
arcpy.mapping.AddLayer(df, baseLayer, "BOTTOM")
# set name of legends
legend1.title = baseName.split("_")[-1] + " Corrosion Rate (mils/year)"
legend2.title = ""
styleItem = mapping.ListStyleItems("ESRI.style", "Legend Items", "Horizontal Single Symbol Label Only")[0]
# set layer style
for lyr in legend1.listLegendItemLayers():
legend1.updateItem(lyr, styleItem)
legend1.adjustColumnCount(3)
for lyr in legend2.listLegendItemLayers():
legend2.updateItem(lyr, styleItem)
# print map
outMapName = baseName.split("_")[0] + depth + baseName.split("_")[-1]
outMap = os.path.join(outMapDir, outMapName)
mapping.ExportToPNG(mxd,outMap,resolution=300)
# clear up layers that added to the mxd template so as to get prepared for mapping the next idw layer
for lyr in arcpy.mapping.ListLayers(mxd, "", df):
arcpy.mapping.RemoveLayer(df, lyr)
print "Mapping Done"
mxd.save()
del mxd
# Create the vector to loop through
lyrVec = mp.ListLayers(df)
# To be safe, start by hiding all of the layers
for lyr in lyrVec:
lyr.visible = False
mxd.save()
# Loop through all layers and export PNGs
for lyr in lyrVec:
lyr.visible = True
# Set the name for out PNG file
lyrName = ap.Describe(lyr).name
outPNG = outimgDir + lyrName[:-4] + ".png"
mp.ExportToPNG(mxd, outPNG, df, 640, 480, 96, True)
lyr.visible = False
mxd.save()
del mxd, df
try:
del env.workspace, mapDoc, fldext_srcLyr, wd_srcLyr, fv_srcLyr, cric_srcLyr, rasDir, outlyrDir, outimgDir, refLayer, dirList, rasList, ras, rasName, outLyr, tmpLyr, wrkLyr #Do your cleanup properly
except:
pass
finally:
def mappingProcess(datetime, province, target_area, density_class=None, day_class=10, out_path=None, out_type= "png"):
# todo.控制densityClass和dayClass最多为14
cwd = os.getcwd()
infeature = ''.join([cwd, u"/data/LightningBulletin.gdb/", target_area])
mxd_density_path = ''.join([cwd, u"/data/LightningBulletin.gdb/", target_area, u"闪电密度空间分布模板.mxd"])
mxd_day_path = ''.join([cwd, u"/data/LightningBulletin.gdb/", target_area, u"地闪雷暴日空间分布模板.mxd"])
workspace = ''.join([cwd, u"/temp/", province, '/', datetime, '/', target_area, '.gdb'])
arcpy.env.workspace = workspace
arcpy.env.overwriteOutput = True
# *****处理地闪密度地图文档*******
mxd = mapping.MapDocument(mxd_density_path)
mask_lyr = mapping.ListLayers(mxd)[2]
target_lyr = mapping.ListLayers(mxd)[3]
mask_lyr.replaceDataSource(workspace, "FILEGDB_WORKSPACE", "densityMask")
target_lyr.replaceDataSource(workspace, "FILEGDB_WORKSPACE", "lightningDensity")
# 修改图例
# 计算数据分割值和不显示值
extract = ExtractByMask("lightningDensity", infeature)
raster = Raster("lightningDensity")
class_break_values, density_class = densityLegendLabel(extract.minimum / 100, extract.maximum / 100, density_class)
excluded_values = ''.join([str(round(raster.minimum - 0.5, 2)), "-", str(round(extract.minimum - 0.5, 2)), ";",
str(round(extract.maximum + 0.5, 2)), "-", str(round(raster.maximum + 0.5, 2))])
sym = target_lyr.symbology
sym.excludedValues = excluded_values
sym.classBreakValues = [x * 100 for x in class_break_values]
# 更改标题和图例
layout_items = mapping.ListLayoutElements(mxd, "TEXT_ELEMENT")
layout_items[-1].text = ''.join([datetime, target_area, u"闪电密度空间分布"]) # title标题
layout_items[-2].text = ''.join([target_area, u"气象局制"]) # 底注
density_class = class_break_values.__len__() - 1
class_break_values = [str(x) for x in class_break_values]
# TODO 将position参数放到设置文件里，或者自动处理
position = {u"绍兴市": (1.0436, 1.6639, 0.9859272727272728), u"嵊州市": (1.1138, 1.2614, 0.9869090909090698),
u"上虞区": (1.1372, 1.1617, 0.9862375000000156), u"诸暨市": (1.1138, 1.2614, 0.9869090909090698),
u"柯桥区": (1.1372, 1.1617, 0.9862375000000156), u"新昌县": (1.1138, 1.2614, 0.9869090909090698),
u"新乡市": (1.0436, 1.6639, 0.9859272727272728)}
Y, Xstart, gap = position[target_area]
for i in xrange(density_class + 1):
layout_items[i].text = class_break_values[i]
layout_items[i].elementPositionY = Y
layout_items[i].elementPositionX = Xstart + gap * i
for i in xrange(density_class + 1, 15): # 最多14类,15个标签
layout_items[i].elementPositionX = -20
mxd.save()
if not out_path:
out_path = workspace
out_name = os.path.join(out_path, ''.join([datetime, target_area, u"闪电密度空间分布"]))
out_type = out_type.lower()
if out_type in ["jpg", 'gpeg']:
mapping.ExportToJPEG(mxd, out_name, resolution=200)
elif out_type == "png":
mapping.ExportToPNG(mxd, out_name, resolution=200)
elif out_type == "pdf":
mapping.ExportToPDF(mxd, out_name)
elif out_type == "bmp":
mapping.ExportToBMP(mxd, out_name, resolution=200)
else:
mapping.ExportToTIFF(mxd, out_name, resolution=200)
# *****处理雷暴日地图文档*******
mxd = mapping.MapDocument(mxd_day_path)
mask_lyr = mapping.ListLayers(mxd)[2]
target_lyr = mapping.ListLayers(mxd)[3]
mask_lyr.replaceDataSource(workspace, "FILEGDB_WORKSPACE", "dayMask")
target_lyr.replaceDataSource(workspace, "FILEGDB_WORKSPACE", "lightningDay")
# 修改图例
# 计算数据分割值和不显示值
extract = ExtractByMask("lightningDay", infeature)
raster = Raster("lightningDay")
start = floor(extract.minimum)
end = ceil(extract.maximum)
class_break_values, day_class = dayLegendLabel(start, end, day_class)
excluded_values = ''.join([str(round(raster.minimum - 0.5, 2)), "-", str(round(extract.minimum - 0.5, 2)), ";",
str(round(extract.maximum + 0.5, 2)), "-", str(round(raster.maximum + 0.5, 2))])
sym = target_lyr.symbology
sym.excludedValues = excluded_values
sym.classBreakValues = class_break_values
# 更改标题和图例
layout_items = mapping.ListLayoutElements(mxd, "TEXT_ELEMENT")
layout_items[-1].text = ''.join([datetime, target_area, u"地闪雷暴日空间分布"])
layout_items[-2].text = ''.join([target_area, u"气象局制"]) # 底注
Y, Xstart, gap = position[target_area]
for i in xrange(day_class + 1):
layout_items[i].text = class_break_values[i]
layout_items[i].elementPositionY = Y
layout_items[i].elementPositionX = Xstart + gap * i
for i in xrange(day_class + 1, 15): # 最多14类,15个标签
layout_items[i].elementPositionX = -20
mxd.save()
out_name = os.path.join(out_path, ''.join([datetime, target_area, u"地闪雷暴日空间分布"]))
out_type = out_type.lower()
if out_type in ["jpg", 'gpeg']:
mapping.ExportToJPEG(mxd, out_name, resolution=200)
elif out_type == "png":
mapping.ExportToPNG(mxd, out_name, resolution=200)
elif out_type == "pdf":
mapping.ExportToPDF(mxd, out_name)
elif out_type == "bmp":
mapping.ExportToBMP(mxd, out_name, resolution=200)
else:
mapping.ExportToTIFF(mxd, out_name, resolution=200)
import arcpy.mapping as mp
#walk through directory and sub-dir
dir_root = "D:\LUIGI\OML\GIS Project Files"
out_dir = "D:\LUIGI\OML\JPEGS WORKING DRAFTS"
count = 1
for root, dirs, files in os.walk(dir_root):
#ignore .mxd files with keywords
if 'GROUND TRUTH' in root:
pass
elif 'BACKUP' in root:
pass
elif 'SCALE' in root:
pass
#perform desired operation on .mxd
else:
for mapdoc in glob.glob(root+'\*.mxd'):
if ", Davao" in mapdoc:
pass
elif "Davao" in mapdoc or "Iloilo" in mapdoc:
print '%d. %s' % (count, mapdoc)
mxd = mp.MapDocument(mapdoc)
mp.ExportToPNG(mxd, out_dir +
'\\' + os.path.basename(mapdoc),resolution=96)
del mxd
count += 1
lyr_a = mp.ListLayers(mxd, data_frame=df0)
lyr_b = mp.ListLayers(mxd, data_frame=df1)
i = 0
for FID_value in FIDs:
i = i + 1
# LAYER A ----------------------------------------------------------------
lyr_a[2].definitionQuery = '"FID" = ' + str(FID_value)
# print lyr_a[2].definitionQuery
extentOfLayer = lyr_a[2].getExtent(True) # visible extent of layer
df0.extent = extentOfLayer
arcpy.RefreshActiveView() # redraw the map
df0.scale = 35000
arcpy.RefreshActiveView() # redraw the map
# LAYER B ----------------------------------------------------------------
lyr_b[2].definitionQuery = '"FID" = ' + str(FID_value)
# print lyr_b[2].definitionQuery
outFile = outDir + "/LC_CortaderiaMap_S2Class_Tile_" + str(FID_value).zfill(3) + "_v2.png"
mp.ExportToPNG(mxd, outFile, 'PAGE_LAYOUT', width, height, dpi)
print "Finished map tile: " + str(FID_value) + " | " + str(round((float(i) / float(len(FIDs))) * 100, 1)) + "%\n"
del mxd