# Name: arcpy_SplitByAttributes.py # Description: Use the SplitByAttributes tool to split a feature class by unique values. # Import required modules import arcpy # Set local variables in_feature_class = 'c:/data/base.gdb/ecology' target_workspace = 'c:/data/output.gdb' fields = ['REGION', 'ECO_CODE'] arcpy.SplitByAttributes_analysis(in_feature_class, target_workspace, fields)
Est_Join, Per_a_proc,
'Estacao_Vazia_Features.DthInicioPeriodo IS NULL AND StageDW.SFG.StgEstacaoCurvaPermanencia_Features.MdaLatitude IS NOT NULL'
)
#Make XY Layer de período a processar
arcpy.MakeXYEventLayer_management(
Per_a_proc, "StageDW_SFG_StgEstacaoCurvaPermanencia_Features_MdaLongitude",
"StageDW_SFG_StgEstacaoCurvaPermanencia_Features_MdaLatitude", Per_fc,
"GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]];-400 -400 1000000000;-100000 10000;-100000 10000;8,98315284119521E-09;0,001;0,001;IsHighPrecision",
"")
#Split by attributes
arcpy.SplitByAttributes_analysis(
Per_fc, WsPeriodo,
"StageDW_SFG_StgEstacaoCurvaPermanencia_Features_DthInicioPeriodo;StageDW_SFG_StgEstacaoCurvaPermanencia_Features_DthFimPeriodo"
)
#Lista de FeatureClass de Pontos a processar
FcPontos = arcpy.ListFeatureClasses('', 'Point')
#Iteracao do IDW com extent do Brasil
for fc in FcPontos:
OutIDW = arcpy.Describe(fc).baseName + "_IDW"
#arcpy.IDW_ga(in_features=fc, z_field="Estacao_BI_Features_MdaiDRE_LT", out_ga_layer="", out_raster=OutIDW,
# cell_size="0,156020628", power="2",
# search_neighborhood="NBRTYPE=Smooth S_MAJOR=11,7367757908039 S_MINOR=11,7367757908039 ANGLE=0 SMOOTH_FACTOR=0,4",
# weight_field="")
tempEnvironment0 = arcpy.env.newPrecision
arcpy.env.newPrecision = "SINGLE"
tempEnvironment1 = arcpy.env.autoCommit
# Add XY Coordinates to feature class in the NAD_1983_Alaska_Albers projection
arcpy.AddXY_management(outShapefile)
# Delete intermediate files
arcpy.Delete_management(tempRaster)
elif noData == 1:
arcpy.AddMessage("All values for this watershed are nodata...")
# Delete intermediate files
arcpy.Delete_management(tempRaster)
# Set the snap raster and cell size environments
arcpy.env.snapRaster = area_of_interest
arcpy.env.cellSize = area_of_interest
# Split watersheds by attribute and store as independent feature classes in an empty geodatabase
arcpy.AddMessage("Splitting unique watersheds into independent feature classes...")
arcpy.SplitByAttributes_analysis(watersheds, watershed_geodatabase, ['HUC10'])
# List all watershed feature classes in the watershed geodatabase
arcpy.env.workspace = watershed_geodatabase
featureClasses = arcpy.ListFeatureClasses()
featureClasses_length = len(featureClasses)
# Loop through feature classes and convert them to point grids with the same cell size and grid as the area of interest
cell_size = arcpy.GetRasterProperties_management(area_of_interest, "CELLSIZEX")
grid_raster = os.path.join(workspace_folder, "grid_raster.tif")
count = 1
for feature in featureClasses:
arcpy.AddMessage("Converting watershed to point grid for watershed " + str(count) + " of " + str(featureClasses_length) + "...")
input_feature = os.path.join(watershed_geodatabase, feature)
output_shapefile = os.path.join(output_folder, feature + ".shp")
buildPointGrids(input_feature, grid_raster, cell_size, output_shapefile)
# Create a temp feature for Mexico
mexico = select_by_attribute(Nation, "\"ADM0_ID\" = '484'")
select_by_location(mergeFile, mexico, "2 Kilometers", output)
print "Step 10 completed at", datetime.datetime.now().strftime("%A, %B %d %Y %I:%M:%S%p")
## ---------------------------------------------------------------------------
## 11. Split By Attributes and Rename dataset
## Description: Split the dataset by state.
print "\nStep 11 Split by attribute starts at", datetime.datetime.now().strftime("%A, %B %d %Y %I:%M:%S%p")
fields = [ABV]
arcpy.SplitByAttributes_analysis(output, finalFolder, fields)
arcpy.env.workspace = "C:\\GIS_RGB\\Geodatabase\\Hydrau_WaterUse\\3_waterRights\\final_output\\"
list_fc = ["COA.shp", "CHI.shp", "DUR.shp", "NVL.shp", "TAM.shp"]
arcpy.Delete_management("T.shp")
for fc in list_fc:
name = os.path.splitext(fc)[0]
arcpy.Rename_management(fc, name + "_WaterRights")
print "Step 11 completed at", datetime.datetime.now().strftime("%A, %B %d %Y %I:%M:%S%p")
arcpy.env.cellSize = 0.5
src = r'D:\test\test.gdb\MAMMALS_COL_SMALL'
dst = r'D:\test\mammal_richness.tif'
# add a ones column and populate it with ones
arcpy.AddField_management(src, 'ONES', 'SHORT')
arcpy.CalculateField_management(src, 'ONES', '1')
# add a column with the feature ID in order to get unique values for each feat
arcpy.AddField_management(src, 'FEAT', 'TEXT')
arcpy.CalculateField_management(src, 'FEAT', "'feat_{}'.format(!FID!)",
'PYTHON')
# split features into single shapefiles
arcpy.SplitByAttributes_analysis(src, arcpy.env.workspace, 'FEAT')
# polygon to raster (using ones column)
for feat in arcpy.ListFeatureClasses():
fn = os.path.splitext(feat)[0]
ras_fn = '{}.tif'.format(fn)
arcpy.PolygonToRaster_conversion(feat, 'ONES', ras_fn)
# sum rasters
rasters = arcpy.ListRasters()
arcpy.CheckOutExtension('Spatial')
out_ras = arcpy.sa.CellStatistics(rasters, 'SUM')
out_ras.save(dst)
# remove folder with polygons and rasters
# shutil.rmtree(arcpy.env.workspace)
def hru2(path0, path, outMerge):
print(
'add latitude,longitude, HRU ID, and Elevation information to the HRU feature class'
)
import arcpy, os, re
# from arcpy.sa import *
from arcpy import env
arcpy.env.workspace = path
# arcpy.env.scratchWorkspace = path
# outMerge = os.path.join(path, "HRU5" + "." + "shp")
# outMerge = os.path.join(path, "output.gdb", "HRU5")
# arcpy.CopyFeatures_management("HRU4.shp", outMerge)
arcpy.DeleteField_management(outMerge, "ident")
# add latitude, longitude, elevation, area (km2), to the HRU feature class
arcpy.DeleteField_management(outMerge, ["POLY_AREA"])
arcpy.AddGeometryAttributes_management(outMerge, "AREA", "METERS",
"SQUARE_KILOMETERS") # area in km2
# add longitude, latitude fields
arcpy.AddField_management(outMerge, "latitude", "DOUBLE", "", "", 16)
arcpy.AddField_management(outMerge, "longitude", "DOUBLE", "", "", 16)
# gcs = arcpy.Describe("HRU.shp").spatialReference # HRU.shp is a projected coordinate system. for latitude, longitude we need geographic coordinate system.
sr = arcpy.SpatialReference(4269) # EPSG oce of NAD83=4269
with arcpy.da.UpdateCursor(outMerge,
['SHAPE@', 'latitude', 'longitude']) as rows:
for row in rows:
pnt_sr = row[0].projectAs(sr)
row[1:] = [pnt_sr.centroid.Y,
pnt_sr.centroid.X] # will be in decimal degrees
rows.updateRow(row)
del rows
# Replace none values in attribute table
with arcpy.da.UpdateCursor(outMerge,
['soil_type', 'LU_type', 'slope']) as rows:
for row in rows:
if row[0] == None:
row[0] = "1"
if row[1] == None:
row[1] = "1"
if row[2] == None:
row[2] = "1"
rows.updateRow(row)
del rows
# add mean elevation to the field
#altitude = os.path.join(path, "HRU2" + "." + "shp")
altitude = os.path.join(path0, "altitude" + "." + "tif")
elev_point = os.path.join(path, "elev_point")
arcpy.RasterToPoint_conversion(altitude, elev_point, "Value")
# Split feature class into multiple polygons based on landuse ID and then run the spatial join to add mean elevation to the attribute table, and finaly merge all polygons
arcpy.SplitByAttributes_analysis(outMerge, path, ['LU_type'])
fci = [
"T0_0", "T1_0", "T2_0", "T3_0", "T4_0", "T5_0", "T6_0", "T7_0", "T8_0",
"T9_0"
] #these are splitted shapefiles
fco = [
"T0_0_sj", "T1_0_sj", "T2_0_sj", "T3_0_sj", "T4_0_sj", "T5_0_sj",
"T6_0_sj", "T7_0_sj", "T8_0_sj", "T9_0_sj"
] #these are splitted shapefiles
for i in range(len(fci)):
fnp = os.path.join(path, fci[i]) # the input shapefile
fieldmappings = arcpy.FieldMappings()
# fieldmappings.addInputField("HRU.shp","Mean_elev")
fieldmappings.addTable(
fnp) # add attribute table of HRU feature class to the fieldmap
fieldmappings.addTable(
elev_point
) # add attribute table of elev_point feature class to the fieldmap
elevpntFieldIndex = fieldmappings.findFieldMapIndex("grid_code")
fieldmap = fieldmappings.getFieldMap(elevpntFieldIndex)
# Get the output field's properties as a field object
field = fieldmap.outputField
# Rename the field and pass the updated field object back into the field map
field.name = "Mean_Elev"
field.aliasName = "Mean_Elev"
fieldmap.outputField = field
# Set the merge rule to mean and then replace the old fieldmap in the mappings object
# with the updated one
fieldmap.mergeRule = "mean"
fieldmappings.replaceFieldMap(elevpntFieldIndex, fieldmap)
# Run the Spatial Join tool, using the defaults for the join operation and join type
# HRU6 = os.path.join(path, "output.gdb", "HRU6")
# HRU6 = os.path.join(path, "HRU6" + "." + "shp")
arcpy.SpatialJoin_analysis(fci[i], elev_point, fco[i], "#", "#",
fieldmappings)
HRU6 = os.path.join(path, "HRU6")
arcpy.Merge_management(fco, HRU6)
arcpy.DeleteField_management(HRU6, ["ident", "Join_Count", "TARGET_FID"])
arcpy.Delete_management(fci[0])
arcpy.Delete_management(fci[1])
arcpy.Delete_management(fci[2])
arcpy.Delete_management(fci[3])
arcpy.Delete_management(fci[4])
arcpy.Delete_management(fci[5])
arcpy.Delete_management(fci[6])
arcpy.Delete_management(fci[7])
arcpy.Delete_management(fci[8])
arcpy.Delete_management(fci[9])
arcpy.Delete_management(fco[0])
arcpy.Delete_management(fco[1])
arcpy.Delete_management(fco[2])
arcpy.Delete_management(fco[3])
arcpy.Delete_management(fco[4])
arcpy.Delete_management(fco[5])
arcpy.Delete_management(fco[6])
arcpy.Delete_management(fco[7])
arcpy.Delete_management(fco[8])
arcpy.Delete_management(fco[9])
# delete intermediate feature classes
# Numbering the HRU feature class
arcpy.AddField_management(HRU6, "HRU_ID", "LONG", "", "", 16)
HRU_ID = 1
with arcpy.da.UpdateCursor(HRU6, "HRU_ID") as cursor:
for row in cursor:
row[0] = HRU_ID
HRU_ID = HRU_ID + 1
cursor.updateRow(row)
print('done!')
# Start procedure to split input shapefiles
fgdb = root + os.sep + "fGDB.gdb"
fcname = os.path.split(pgshp)[1]
fcname = fcname.replace('.shp', '')
infc = fgdb + os.sep + fcname
# Create File GDB
if not arcpy.Exists(fgdb):
arcpy.CreateFileGDB_management(root, "fGDB.gdb")
# Convert input polygon shp to feature class
arcpy.FeatureClassToGeodatabase_conversion(pgshp, fgdb)
# Split shapefile by unique field into layers
arcpy.AddMessage("Splitting polygon shapefile")
arcpy.SplitByAttributes_analysis(infc, root, pgsf)
# Delete file Geodatabase
if arcpy.Exists(fgdb):
arcpy.Delete_management(fgdb)
# Set Workspace to input folder
arcpy.env.workspace = root
# Enable overwriting
arcpy.env.overwriteOutput = True
# Define variables related to tiff files in the input folder
pattern = "prate_*.tif" # Pattern that will be used to find & prepare a list of raster files
lTIFs = [
] # Create a blank list that would be populated by input geotiff files later
elif str == "NB":
return 1
elif str == "SB":
return 0
elif str == "CL":
return 1
elif str == "CC":
return 0
else:
return -1'''
arcpy.CalculateField_management(
routes_dir, 'NewDir', "direction(!DirName!)", "PYTHON3",
dirRouteBlock) # use code block above to cal the field
split_gdb = arcpy.SplitByAttributes_analysis(
routes_dir, os.path.join(root_dir, f'routes_split_{year}.gdb'),
["RouteAbbr", "NewDir"
])[0] # ! I can't tell whether this give me two files, or what happens
replaceGDB(root_dir, f'stops_split_{year}.gdb')
# the same as above, for stops
# ! can stops be defined with multiple directions depending on the route?
if 'NewDir' in arcpy.Describe(os.path.join(
gdb, "MetroBusStopsByLine__200120")).fields:
arcpy.DeleteField_management(
os.path.join(gdb, "MetroBusStopsByLine__200120"), 'NewDir')
dirBlock = '''def dirCalc(str):
if "EAST" in str :
return "0"
elif "WEST" in str:
def split_by_attributes(input_fc, workspace, split_fields):
arcpy.SplitByAttributes_analysis(
Input_Table=input_fc,
Target_Workspace=workspace,
Split_Fields=split_fields,
)
arcpy.RepairGeometry_management("all_wdpa_polybuffpnt_transboundary_novelarea_intersect","DELETE_NULL","OGC")
# recalculate ISO3 based on the geo iso3
arcpy.CalculateField_management("all_wdpa_polybuffpnt_transboundary_novelarea_intersect","WDPA_ISO3","!GEO_ISO3!","PYTHON_9.3")
# rename the nontransboundary sites
#arcpy.Rename_management(r"in_memory\all_wdpa_polybuffpnt_nontransboundary",r"in_memory\all_wdpa_polybuffpnt_national")
# append back the erased and intersected transboundary sites back into the nontransboundary sites
arcpy.Append_management(r"in_memory\all_wdpa_polybuffpnt_nontransboundary","all_wdpa_polybuffpnt_transboundary_novelarea_intersect","NO_TEST")
# repair it
arcpy.RepairGeometry_management(r"in_memory\all_wdpa_polybuffpnt_nontransboundary","DELETE_NULL","OGC")
# split by attribute (wdpa_iso3) to create an individual fc for each iso3
arcpy.SplitByAttributes_analysis(r"in_memory\all_wdpa_polybuffpnt_nontransboundary",sbafolder, "WDPA_ISO3")
# change the location of the workspace to represent the location of the sba output
arcpy.env.workspace = str(sbafolder)
arcpy.env.overwriteOutput = True
out_sba = arcpy.ListFeatureClasses()
# split the input into country specific subsets and do the analysis iso3 by iso3
for fc in out_sba:
desc = arcpy.Describe(fc)
# run a union, add in an xyco for each segment
arcpy.Union_analysis(fc,r"in_memory\Union")
arcpy.RepairGeometry_management(r"in_memory\union","DELETE_NULL","OGC")