def genericFilter(self,**kwargs):
try:
x = kwargs['name']
x = x.split(',')
if len(x[0])== 0:
pass
for p in [self.path]:
uc = UpdateCursor(p)
for row in uc:
fn = row.getValue('FULL_NAME')
for j in x:
if j in fn:
fn = fn.replace(j,'')
row.setValue('FULL_NAME', fn)
uc.updateRow(row)
del uc
except:
print "Error in %s." % sys._getframe().f_code.co_name
e = sys.exc_info()
log_file = open("H:/Programming/PyErrorLog.txt", 'a')
log_file.write(str(datetime.datetime.now().time()) + "\n")
log_file.write(str(e[0]) + "\n")
log_file.write(str(e[1]) + "\n")
traceback.print_tb(e[2],None,log_file)
log_file.write('\n')
log_file.close()
def fc_cleanup(self):
import arcpy
num=1
sort_fc = '/'.join([x.path,x.name+'_sort'+num])
while arcpy.Exists(sort_fc) == True:
num += 1
sort_fc = sort_fc.replace(sort_fc[-1],num)
arcpy.Sort_management(x.path+'/'+x.name,x.path+'/'+x.name+'_sort',[["UFI","ASCENDING"]])
uc = UpdateCursor(sort_fc)
ufi = -1
row = uc.next()
feat_dict = {}
lst_unis = []
for row in uc:
last_ufi,ufi = ufi,row.getValue('UFI')
nt = row.getValue('NT')
if ufi == last_ufi and nt in ('V',u'V'):
uni = row.getValue('UNI')
lst_unis.append(row.getValue('UNI'))
else:
feat_dict[ufi] = lst_unis
lst_unis = []
uc.updateRow(row)
row = uc.next()
del uc
num += 1
uc2 = UpdateCursor(sort_fc)
row = uc.next()
for row in uc2:
ufi = row.getValue('UFI')
uni = row.getValue('UNI')
if ufi in feat_dict:
lst_unis = feat_dict[ufi]
if uni in lst_unis:
uc2.deleteRow(row)
def all_values_in_column(table, column):
"""
Returns a set of all the values in the some column of a table
|table|: a dbf
|column|: the name of a column in the table, the column must be in the table
"""
values = set()
rows = UpdateCursor(table)
for row in rows:
values.add(row.getValue(column))
return values
def compute_adjacency_list(input_points, input_network, id_attribute,
impedance_attribute, accumulator_attributes,
search_radius, output_location, adj_dbf_name):
"""
|input_points|: point shape file marking entity (e.g. building) locations
|input_network|: street network in which |input_points| is located
|id_attribute|: the name of attribute that distinguishes between input points
|impedance_attribute|: distance between neighboring nodes will be based on
this attribute
|accumulator_attributes|: distance between neighboring nodes will also be
recorded for these attributes
|search_radius|: the maximum extent for centrality computation
|output_location|: adjacency list dbf will be saved here
|adj_dbf_name|: the name of the adjacency list dbf
"""
# Number of points in |input_points|
input_point_count = int(GetCount_management(input_points).getOutput(0))
# Make a directory to store all auxiliary files
auxiliary_dir = join(output_location, AUXILIARY_DIR_NAME)
if not Exists(auxiliary_dir):
mkdir(auxiliary_dir)
# Record the edge and junction source names of |input_network|
junction_feature, edge_feature = network_features(input_network)
# Calculate network locations if not already calculated
test_input_point = UpdateCursor(input_points).next()
locations_calculated = all(
row_has_field(test_input_point, field)
for field in NETWORK_LOCATION_FIELDS)
if not locations_calculated:
calculate_network_locations(input_points, input_network)
# Calculate barrier cost per input point if not already calculated
barrier_costs_calculated = row_has_field(test_input_point,
trim(BARRIER_COST_FIELD))
if not barrier_costs_calculated:
AddMessage(BARRIER_COST_COMPUTATION_STARTED)
# Add |BARRIER_COST_FIELD| column in |input_points|
AddField_management(in_table=input_points,
field_name=trim(BARRIER_COST_FIELD),
field_type="DOUBLE",
field_is_nullable="NON_NULLABLE")
# Initialize a dictionary to store the frequencies of (SnapX, SnapY) values
xy_count = {}
# A method to retrieve a (SnapX, SnapY) pair for a row in |input_points|
get_xy = lambda row: (row.getValue(trim("SnapX")),
row.getValue(trim("SnapY")))
barrier_pre_progress = Progress_Bar(input_point_count, 1,
BARRIER_COST_PRE_PROCESSING)
rows = UpdateCursor(input_points)
for row in rows:
snap_xy = get_xy(row)
if snap_xy in xy_count:
xy_count[snap_xy] += 1
else:
xy_count[snap_xy] = 1
barrier_pre_progress.step()
# Populate |BARRIER_COST_FIELD|, this will be used in OD matrix computation
barrier_progress = Progress_Bar(input_point_count, 1,
BARRIER_COST_COMPUTATION)
rows = UpdateCursor(input_points)
for row in rows:
barrier_cost = BARRIER_COST / xy_count[get_xy(row)]
row.setValue(trim(BARRIER_COST_FIELD), barrier_cost)
rows.updateRow(row)
barrier_progress.step()
AddMessage(BARRIER_COST_COMPUTATION_FINISHED)
# Necessary files
od_cost_matrix_layer = join(auxiliary_dir, OD_COST_MATRIX_LAYER_NAME)
od_cost_matrix_lines = join(od_cost_matrix_layer, OD_COST_MATRIX_LINES)
temp_adj_dbf_name = TEMP_ADJACENCY_DBF_NAME(adj_dbf_name)
temp_adj_dbf = join(output_location, temp_adj_dbf_name)
adj_dbf = join(output_location, adj_dbf_name)
partial_adj_dbf = join(auxiliary_dir, PARTIAL_ADJACENCY_LIST_NAME)
polygons = join(auxiliary_dir, POLYGONS_SHAPEFILE_NAME)
raster = join(auxiliary_dir, RASTER_NAME)
polygons_layer = join(auxiliary_dir, POLYGONS_LAYER_NAME)
input_points_layer = join(auxiliary_dir, INPUT_POINTS_LAYER_NAME)
# Make sure none of these files already exists
for path in [
od_cost_matrix_layer, temp_adj_dbf, adj_dbf, partial_adj_dbf,
polygons, raster, polygons_layer, input_points_layer,
od_cost_matrix_lines
]:
delete(path)
# Cutoff radius for OD matrix computation
cutoff_radius = 2 * BARRIER_COST + min(search_radius, BARRIER_COST / 2)
# Compute OD matrix
MakeODCostMatrixLayer_na(in_network_dataset=input_network,
out_network_analysis_layer=od_cost_matrix_layer,
impedance_attribute=impedance_attribute,
default_cutoff=str(cutoff_radius),
accumulate_attribute_name=accumulator_attributes,
UTurn_policy="ALLOW_UTURNS",
hierarchy="NO_HIERARCHY",
output_path_shape="NO_LINES")
# Determine raster cell size
points_per_raster_cell = OD_MATRIX_ENTRIES / input_point_count
raster_cell_count = max(1, input_point_count / points_per_raster_cell)
input_points_extent = Describe(input_points).Extent
raster_cell_area = (input_points_extent.width *
input_points_extent.height / raster_cell_count)
raster_cell_size = int(sqrt(raster_cell_area))
# Construct |raster| from |input_points|
PointToRaster_conversion(in_features=input_points,
value_field=id_attribute,
out_rasterdataset=raster,
cell_assignment="MOST_FREQUENT",
priority_field="NONE",
cellsize=str(raster_cell_size))
# Construct |polygons| from |raster|
RasterToPolygon_conversion(in_raster=raster,
out_polygon_features=polygons,
simplify="NO_SIMPLIFY",
raster_field="VALUE")
# Export empty |od_cost_matrix_lines| to |temp_dbf| to start adjacency list
TableToTable_conversion(in_rows=od_cost_matrix_lines,
out_path=output_location,
out_name=temp_adj_dbf_name)
# Construct |polygons_layer| and |input_points_layer|
for (feature, layer) in [(polygons, polygons_layer),
(input_points, input_points_layer)]:
MakeFeatureLayer_management(in_features=feature, out_layer=layer)
def add_locations(sub_layer, field_mappings=""):
"""
|sub_layer|: one of "Origins", "Destinations", "Barrier Points"
|field_mappings|: field mappings in addition to those for "Name" and
"CurbApproach"
"""
AddLocations_na(in_network_analysis_layer=od_cost_matrix_layer,
sub_layer=sub_layer,
in_table=input_points_layer,
field_mappings=("Name %s #; CurbApproach # 0; %s" %
(id_attribute, field_mappings)),
search_tolerance=SEARCH_TOLERANCE,
search_criteria=("%s SHAPE; %s SHAPE;" %
(junction_feature, edge_feature)),
append="CLEAR",
snap_to_position_along_network="SNAP",
snap_offset=SNAP_OFFSET)
# OD cost matrix destinations
AddMessage(ADDING_DESTINATIONS_STARTED)
SelectLayerByLocation_management(in_layer=input_points_layer)
add_locations("Destinations")
AddMessage(ADDING_DESTINATIONS_FINISHED)
# OD cost matrix point barriers
AddMessage(ADDING_BARRIERS_STARTED)
add_locations("Point Barriers",
("FullEdge # 0; BarrierType # 2;"
"Attr_%s %s #;" %
(impedance_attribute, trim(BARRIER_COST_FIELD))))
AddMessage(ADDING_BARRIERS_FINISHED)
# Compute adjacency list, one raster cell at a time
progress = Progress_Bar(raster_cell_count, 1, STEP_1)
rows = UpdateCursor(polygons)
for row in rows:
# Select the current polygon
SelectLayerByAttribute_management(in_layer_or_view=polygons_layer,
selection_type="NEW_SELECTION",
where_clause="FID = %s" %
str(row.FID))
# Origins
SelectLayerByLocation_management(in_layer=input_points_layer,
select_features=polygons_layer)
add_locations("Origins")
# Solve OD Cost matrix
Solve_na(in_network_analysis_layer=od_cost_matrix_layer,
ignore_invalids="SKIP")
# Add origin and destination fields to the adjacency list dbf
for (index, field) in [(0, ORIGIN_ID_FIELD_NAME),
(1, DESTINATION_ID_FIELD_NAME)]:
CalculateField_management(in_table=od_cost_matrix_lines,
field=field,
expression="!Name!.split(' - ')[%d]" %
index,
expression_type="PYTHON")
# Record actual distance between neighboring nodes
distance_field = "Total_%s" % impedance_attribute
CalculateField_management(in_table=od_cost_matrix_lines,
field=distance_field,
expression="!%s! - 2 * %d" %
(distance_field, BARRIER_COST),
expression_type="PYTHON")
# Append result to |temp_adj_dbf|
TableToTable_conversion(in_rows=od_cost_matrix_lines,
out_path=auxiliary_dir,
out_name=PARTIAL_ADJACENCY_LIST_NAME)
Append_management(inputs=partial_adj_dbf,
target=temp_adj_dbf,
schema_type="TEST")
progress.step()
# Copy data from |temp_adj_dbf| to |adj_dbf|
Rename_management(in_data=temp_adj_dbf, out_data=adj_dbf)
# Clean up
for path in [
od_cost_matrix_layer, partial_adj_dbf, polygons, raster,
polygons_layer, input_points_layer, auxiliary_dir
]:
delete(path)
def updateFC(self):
'''
Updates the feature class based on the distances found in the other
two functions
input:
lstNames - 'b' from the LevDist function
'''
try:
d0 = time.clock()
z = self.LevDist(self.namePairs)
dupeCount = 0
modCount = 0
ctr = 0
self.insGNDB = []
while z:
# n = varFlag,gUFI,gName,xUFI,xName,gUNI
n = z.next()
# cursor must apply to external names feature class; else will throw exception
# as fields such as "MF" do not exist
uc = UpdateCursor(self.path+'/'+self.name)
gUFI = n[1]
gN = n[2]
xUFI = n[3]
xN = n[4]
gUNI = n[5]
# initialize an empty list to put GNDB row objects for records to be demoted
# from N to V NT
for row in uc:
try:
uni = 1
# print row.getValue('FULL_NAME'), xN
uc_name = row.getValue('FULL_NAME')
uc_ufi = row.getValue('UFI')
if uc_name == xN and uc_ufi == xUFI:
if n[0] == 'DUPLICATE':
dupeCount += 1
row.setValue('GEONAME_NOTE',n[0])
# set MF column to M to capture coordinates
# or other feature mods
row.setValue('MF','M')
##################
#
# need to change this with new sources
row.setValue('USID1','TU-GAZETTEER-09')
#
##################
row.setValue('SOURCE_MOD_TYPE1','F')
row.setValue('UFI', gUFI)
row.setValue('UNI', gUNI)
uc.updateRow(row)
ctr += 1
# if exName is duplicate of GNDB Variant, find and
# demote GNDB N name
if n[6] == 'V':
rr = self.demote_gndb_rec(n[1],gUNI)
elif n[0] == 'VARIANT':
# Turkey Gazetteer is considered authoritative
# so discrepancies favor the gazetteer
# handles the external record
vRow = self.handle_variants(n,row)
uc.updateRow(vRow)
# demote the GNDB NT to 'V'
rr = self.demote_gndb_rec(n[1], gUNI) # = gndb row
self.insGNDB.append(rr)
modCount +=1
ctr +=1
print n[1]
except StopIteration:
print 'uc done'
except StopIteration:
print "ctr = %d" % ctr
print "Feature class modified:\n\t%d duplicate features found \
\n\t%d variant names added" % (dupeCount,modCount)
d1 = time.clock()
delta = d1-d0
print "%s took %f to complete." % (sys._getframe().f_code.co_name,\
delta)
ins_cur = InsertCursor(self.path+'/'+self.name)
ins_num = 0
for rec in self.insGNDB:
if rec == None:
continue
pt = Point()
row = ins_cur.newRow()
for k,d in rec.iteritems():
row.setValue(k,d)
row.setValue('MF','M')
row.setValue('NT','V')
if k == 'LON':
pt.X = d
elif k == 'LAT':
pt.Y = d
row.setNull('NAME_RANK')
row.setValue('SOURCE_MOD_TYPE1','N')
pt_geo = PointGeometry(pt)
row.setValue('Shape',pt_geo)
ins_cur.insertRow(row)
ins_num += 1
print "%d GNDB name records demoted and added to feature class." % \
ins_num
del ins_cur
except Exception, e:
e = sys.exc_info()
log_file = open("H:/Programming/PyErrorLog.txt", 'a')
log_file.write(str(datetime.datetime.now().time()) + "\n")
log_file.write(str(e[0]) + "\n")
log_file.write(str(e[1]) + "\n")
traceback.print_tb(e[2],None,log_file)
log_file.write('\n')
log_file.close()
test_node = nodes[selected_features.pop()]
measures = set([measure for measure in dir(test_node) if (measure in
FINAL_ATTRIBUTES or is_accumulator_field(measure))])
# Add a field in the output layer for each computed metric
for measure in measures:
AddField_management(in_table=output_layer, field_name=trim(measure),
field_type="DOUBLE", field_is_nullable="NON_NULLABLE")
# Figure out the id field to use based on the type of the input buildings
if (buildings_description.shapeType == "Polygon" and
inputs[ID_ATTRIBUTE] == ORIGINAL_FID):
id_field = "FID"
else:
id_field = inputs[ID_ATTRIBUTE]
# Fill the layer with the metric values
write_progress = Progress_Bar(N, 1, STEP_5)
layer_rows = UpdateCursor(output_layer)
for row in layer_rows:
id = row.getValue(id_field)
for measure in measures:
# If no value was computed for this node id, set value to 0
value = 0
if id in nodes and hasattr(nodes[id], measure):
value = getattr(nodes[id], measure)
row.setValue(trim(measure), value)
layer_rows.updateRow(row)
write_progress.step()
AddMessage(STEP_5_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_5_FAILED)
success = False
def compute_adjacency_list(input_points, input_network, id_attribute,
impedance_attribute, accumulator_attributes, search_radius, output_location,
adj_dbf_name):
"""
|input_points|: point shape file marking entity (e.g. building) locations
|input_network|: street network in which |input_points| is located
|id_attribute|: the name of attribute that distinguishes between input points
|impedance_attribute|: distance between neighboring nodes will be based on
this attribute
|accumulator_attributes|: distance between neighboring nodes will also be
recorded for these attributes
|search_radius|: the maximum extent for centrality computation
|output_location|: adjacency list dbf will be saved here
|adj_dbf_name|: the name of the adjacency list dbf
"""
# Number of points in |input_points|
input_point_count = int(GetCount_management(input_points).getOutput(0))
# Make a directory to store all auxiliary files
auxiliary_dir = join(output_location, AUXILIARY_DIR_NAME)
if not Exists(auxiliary_dir):
mkdir(auxiliary_dir)
# Record the edge and junction source names of |input_network|
edge_feature = None
junction_feature = None
for source in Describe(input_network).sources:
if source.sourceType == EDGE_FEATURE:
edge_feature = source.name
elif source.sourceType in JUNCTION_FEATURE:
junction_feature = source.name
if edge_feature == None:
AddWarning(WARNING_NO_EDGE_FEATURE(input_network))
raise Invalid_Input_Exception("Input Network")
if junction_feature == None:
AddWarning(WARNING_NO_JUNCTION_FEATURE(input_network))
raise Invalid_Input_Exception("Input Network")
# Calculate network locations if not already calculated
test_input_point = UpdateCursor(input_points).next()
locations_calculated = all(row_has_field(test_input_point, field)
for field in NETWORK_LOCATION_FIELDS)
if not locations_calculated:
AddMessage(CALCULATE_LOCATIONS_STARTED)
CalculateLocations_na(in_point_features=input_points,
in_network_dataset=input_network,
search_tolerance=SEARCH_TOLERANCE,
search_criteria=("%s SHAPE; %s SHAPE;" %
(junction_feature, edge_feature)),
exclude_restricted_elements="INCLUDE")
AddMessage(CALCULATE_LOCATIONS_FINISHED)
# Calculate barrier cost per input point if not already calculated
barrier_costs_calculated = row_has_field(test_input_point,
trim(BARRIER_COST_FIELD))
if not barrier_costs_calculated:
AddMessage(BARRIER_COST_COMPUTATION_STARTED)
# Add |BARRIER_COST_FIELD| column in |input_points|
AddField_management(in_table=input_points,
field_name=trim(BARRIER_COST_FIELD), field_type="DOUBLE",
field_is_nullable="NON_NULLABLE")
# Initialize a dictionary to store the frequencies of (SnapX, SnapY) values
xy_count = {}
# A method to retrieve a (SnapX, SnapY) pair for a row in |input_points|
get_xy = lambda row: (row.getValue(trim("SnapX")),
row.getValue(trim("SnapY")))
barrier_pre_progress = Progress_Bar(input_point_count, 1,
BARRIER_COST_PRE_PROCESSING)
rows = UpdateCursor(input_points)
for row in rows:
snap_xy = get_xy(row)
if snap_xy in xy_count:
xy_count[snap_xy] += 1
else:
xy_count[snap_xy] = 1
barrier_pre_progress.step()
# Populate |BARRIER_COST_FIELD|, this will be used in OD matrix computation
barrier_progress = Progress_Bar(input_point_count, 1,
BARRIER_COST_COMPUTATION)
rows = UpdateCursor(input_points)
for row in rows:
barrier_cost = BARRIER_COST / xy_count[get_xy(row)]
row.setValue(trim(BARRIER_COST_FIELD), barrier_cost)
rows.updateRow(row)
barrier_progress.step()
AddMessage(BARRIER_COST_COMPUTATION_FINISHED)
# Necessary files
od_cost_matrix_layer = join(auxiliary_dir, OD_COST_MATRIX_LAYER_NAME)
od_cost_matrix_lines = join(od_cost_matrix_layer, OD_COST_MATRIX_LINES)
temp_adj_dbf_name = "%s~.dbf" % adj_dbf_name[:-4]
temp_adj_dbf = join(output_location, temp_adj_dbf_name)
adj_dbf = join(output_location, adj_dbf_name)
partial_adj_dbf = join(auxiliary_dir, PARTIAL_ADJACENCY_LIST_NAME)
polygons = join(auxiliary_dir, POLYGONS_SHAPEFILE_NAME)
raster = join(auxiliary_dir, RASTER_NAME)
polygons_layer = join(auxiliary_dir, POLYGONS_LAYER_NAME)
input_points_layer = join(auxiliary_dir, INPUT_POINTS_LAYER_NAME)
# Make sure none of these files already exists
for path in [od_cost_matrix_layer, temp_adj_dbf, adj_dbf, partial_adj_dbf,
polygons, raster, polygons_layer, input_points_layer,
od_cost_matrix_lines]:
delete(path)
# Cutoff radius for OD matrix computation
cutoff_radius = 2 * BARRIER_COST + min(search_radius, BARRIER_COST / 2)
# Compute OD matrix
MakeODCostMatrixLayer_na(in_network_dataset=input_network,
out_network_analysis_layer=od_cost_matrix_layer,
impedance_attribute=impedance_attribute,
default_cutoff=str(cutoff_radius),
accumulate_attribute_name=accumulator_attributes,
UTurn_policy="ALLOW_UTURNS", hierarchy="NO_HIERARCHY",
output_path_shape="NO_LINES")
# Determine raster cell size
points_per_raster_cell = OD_MATRIX_ENTRIES / input_point_count
raster_cell_count = max(1, input_point_count / points_per_raster_cell)
input_points_extent = Describe(input_points).Extent
raster_cell_area = (input_points_extent.width * input_points_extent.height /
raster_cell_count)
raster_cell_size = int(sqrt(raster_cell_area))
# Construct |raster| from |input_points|
PointToRaster_conversion(in_features=input_points,
value_field=id_attribute, out_rasterdataset=raster,
cell_assignment="MOST_FREQUENT", priority_field="NONE",
cellsize=str(raster_cell_size))
# Construct |polygons| from |raster|
RasterToPolygon_conversion(in_raster=raster,
out_polygon_features=polygons, simplify="NO_SIMPLIFY",
raster_field="VALUE")
# Export empty |od_cost_matrix_lines| to |temp_dbf| to start adjacency list
TableToTable_conversion(in_rows=od_cost_matrix_lines,
out_path=output_location, out_name=temp_adj_dbf_name)
# Construct |polygons_layer| and |input_points_layer|
for (feature, layer) in [(polygons, polygons_layer),
(input_points, input_points_layer)]:
MakeFeatureLayer_management(in_features=feature, out_layer=layer)
def add_locations(sub_layer, field_mappings=""):
"""
|sub_layer|: one of "Origins", "Destinations", "Barrier Points"
|field_mappings|: field mappings in addition to those for "Name" and
"CurbApproach"
"""
AddLocations_na(in_network_analysis_layer=od_cost_matrix_layer,
sub_layer=sub_layer, in_table=input_points_layer,
field_mappings=("Name %s #; CurbApproach # 0; %s" %
(id_attribute, field_mappings)),
search_tolerance=SEARCH_TOLERANCE,
search_criteria=("%s SHAPE; %s SHAPE;" %
(junction_feature, edge_feature)),
append="CLEAR", snap_to_position_along_network="SNAP",
snap_offset=SNAP_OFFSET)
# OD cost matrix destinations
AddMessage(ADDING_DESTINATIONS_STARTED)
SelectLayerByLocation_management(in_layer=input_points_layer)
add_locations("Destinations")
AddMessage(ADDING_DESTINATIONS_FINISHED)
# OD cost matrix point barriers
AddMessage(ADDING_BARRIERS_STARTED)
add_locations("Point Barriers", ("FullEdge # 0; BarrierType # 2;"
"Attr_%s %s #;" % (impedance_attribute, trim(BARRIER_COST_FIELD))))
AddMessage(ADDING_BARRIERS_FINISHED)
# Compute adjacency list, one raster cell at a time
progress = Progress_Bar(raster_cell_count, 1, STEP_1)
rows = UpdateCursor(polygons)
for row in rows:
# Select the current polygon
SelectLayerByAttribute_management(in_layer_or_view=polygons_layer,
selection_type="NEW_SELECTION", where_clause="FID = %s" % str(row.FID))
# Origins
SelectLayerByLocation_management(in_layer=input_points_layer,
select_features=polygons_layer)
add_locations("Origins")
# Solve OD Cost matrix
Solve_na(in_network_analysis_layer=od_cost_matrix_layer,
ignore_invalids="SKIP")
# Add origin and destination fields to the adjacency list dbf
for (index, field) in [(0, ORIGIN_ID_FIELD_NAME),
(1, DESTINATION_ID_FIELD_NAME)]:
CalculateField_management(in_table=od_cost_matrix_lines,
field=field, expression="!Name!.split(' - ')[%d]" % index,
expression_type="PYTHON")
# Record actual distance between neighboring nodes
distance_field = "Total_%s" % impedance_attribute
CalculateField_management(in_table=od_cost_matrix_lines,
field=distance_field,
expression="!%s! - 2 * %d" % (distance_field, BARRIER_COST),
expression_type="PYTHON")
# Append result to |temp_adj_dbf|
TableToTable_conversion(in_rows=od_cost_matrix_lines,
out_path=auxiliary_dir, out_name=PARTIAL_ADJACENCY_LIST_NAME)
Append_management(inputs=partial_adj_dbf, target=temp_adj_dbf,
schema_type="TEST")
progress.step()
# Copy data from |temp_adj_dbf| to |adj_dbf|
Rename_management(in_data=temp_adj_dbf, out_data=adj_dbf)
# Clean up
for path in [od_cost_matrix_layer, partial_adj_dbf, polygons, raster,
polygons_layer, input_points_layer, auxiliary_dir]:
delete(path)
# Mame a feature layer of type amenities
MakeFeatureLayer_management(osmPoints, nameAmenitiesLayer,
queryStringAmenities)
# Select only amanities into the country El Salvador
SelectLayerByLocation_management(nameAmenitiesLayer, "CONTAINED_BY",
nameCountryLayer)
# Makes a separate shapefile for each types of amenities
CopyFeatures_management(nameAmenitiesLayer, typeAmenities)
# Get the new separete shapefile
amenitiesTable = typeAmenities + '.dbf'
# Name of new field for amenities
newField = "source"
# Add new field called 'source'
AddField_management(amenitiesTable, newField, "TEXT", 100)
with UpdateCursor(typeAmenities + ".shp", newField) as amenitiesRows:
for row in amenitiesRows:
# Update the value for each row in typeAmenities
row[0] = "OpenStreetMap"
amenitiesRows.updateRow(row)
except:
print 'It was not possible makes a separete shapefile for amenities'
success = False
# Step 2
if success:
AddMessage(STEP_2_STARTED)
try:
distance_field = trim("Total_%s" % inputs[IMPEDANCE_ATTRIBUTE])
accumulator_fields = set([trim("Total_%s" % accumulator_attribute)
for accumulator_attribute in inputs[ACCUMULATOR_ATTRIBUTES].split(";")
if accumulator_attribute != "#"])
# Graph representation: dictionary mapping node id's to Node objects
nodes = {}
# The number of rows in |adj_dbf|
directed_edge_count = int(GetCount_management(adj_dbf).getOutput(0))
graph_progress = Progress_Bar(directed_edge_count, 1, STEP_2)
rows = UpdateCursor(adj_dbf)
for row in rows:
# Get neighboring nodes, and the distance between them
origin_id = row.getValue(trim(ORIGIN_ID_FIELD_NAME))
destination_id = row.getValue(trim(DESTINATION_ID_FIELD_NAME))
distance = float(row.getValue(distance_field))
# Make sure the nodes are recorded in the graph
for id in [origin_id, destination_id]:
if not id in nodes:
nodes[id] = Node()
# Make sure that the nodes are neighbors in the graph
if origin_id != destination_id and distance >= 0:
accumulations = {}
for field in accumulator_fields:
accumulations[field] = float(row.getValue(field))
nodes[origin_id].add_neighbor(destination_id, distance, accumulations)
def main():
"""
Runs the centrality tool.
"""
env.overwriteOutput = True # Enable overwritting
CheckOutExtension("Network")
# Success of the program through the six steps
success = True
# Inputs to the tool
if len(argv) != INPUT_COUNT + 1:
raise Exception("Invalid number of inputs")
input_number = index()
input_number.next() # Skip over sys.argv[0]
inputs = {}
inputs[INPUT_BUILDINGS] = argv[input_number.next()]
inputs[POINT_LOCATION] = ("INSIDE" if argv[input_number.next()] == "true" else
"CENTROID")
inputs[INPUT_NETWORK] = argv[input_number.next()]
inputs[COMPUTE_REACH] = argv[input_number.next()] == "true"
inputs[COMPUTE_GRAVITY] = argv[input_number.next()] == "true"
inputs[COMPUTE_BETWEENNESS] = argv[input_number.next()] == "true"
inputs[COMPUTE_CLOSENESS] = argv[input_number.next()] == "true"
inputs[COMPUTE_STRAIGHTNESS] = argv[input_number.next()] == "true"
inputs[ID_ATTRIBUTE] = argv[input_number.next()]
inputs[NODE_WEIGHT_ATTRIBUTE] = argv[input_number.next()]
inputs[IMPEDANCE_ATTRIBUTE] = argv[input_number.next()]
try: inputs[SEARCH_RADIUS] = float(argv[input_number.next()])
except: inputs[SEARCH_RADIUS] = INFINITE_RADIUS
inputs[USE_NETWORK_RADIUS] = (argv[input_number.next()] ==
ON_THE_NETWORK_OPTION)
try: inputs[BETA] = float(argv[input_number.next()])
except: raise Invalid_Input_Exception("Beta")
inputs[NORMALIZE_RESULTS] = [measure for measure in
argv[input_number.next()].split(";") if measure != "#"]
inputs[OUTPUT_LOCATION] = argv[input_number.next()]
inputs[OUTPUT_FILE_NAME] = argv[input_number.next()]
inputs[ACCUMULATOR_ATTRIBUTES] = argv[input_number.next()]
# Record the origin nodes for centrality measurements
# This is important if the user selects a subset of the features to be origins
selected_features = all_values_in_column(inputs[INPUT_BUILDINGS],
inputs[ID_ATTRIBUTE])
# Clear selection if we got a layer file
try:
SelectLayerByAttribute_management(inputs[INPUT_BUILDINGS],
"CLEAR_SELECTION")
except:
pass
# Adjacency List table name
node_locations_needed = (inputs[COMPUTE_STRAIGHTNESS] or
not inputs[USE_NETWORK_RADIUS])
adj_dbf_name = ("%s_%s_%s_%s_%s_%s.dbf" % (ADJACENCY_LIST_NAME,
basename(inputs[INPUT_BUILDINGS]), basename(inputs[INPUT_NETWORK]),
inputs[ID_ATTRIBUTE], inputs[IMPEDANCE_ATTRIBUTE],
inputs[ACCUMULATOR_ATTRIBUTES])).replace("#", "None")
if len(adj_dbf_name) > MAX_FILE_NAME_LENGTH:
AddWarning(WARNING_LARGE_ADJ_FILE_NAME)
adj_dbf = join(inputs[OUTPUT_LOCATION], adj_dbf_name)
# Output file names
output_feature_class_name = feature_class_name(inputs[OUTPUT_FILE_NAME])
output_feature_class = "%s.shp" % join(inputs[OUTPUT_LOCATION],
output_feature_class_name)
# Create a feature class that is a copy of the input buildings
try:
AddMessage(INPUT_BUILDINGS_COPY_STARTED)
CreateFeatureclass_management(out_path=inputs[OUTPUT_LOCATION],
out_name=output_feature_class_name)
CopyFeatures_management(in_features=inputs[INPUT_BUILDINGS],
out_feature_class=output_feature_class)
AddMessage(INPUT_BUILDINGS_COPY_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(INPUT_BUILDINGS_COPY_FAILED)
success = False
output_layer_name = layer_name(inputs[OUTPUT_FILE_NAME])
output_layer = "%s.lyr" % join(inputs[OUTPUT_LOCATION], output_layer_name)
# If output has already been created, don't carry on
if Exists(output_layer):
AddWarning(WARNING_OUTPUT_ALREADY_EXISTS)
success = False
# We will convert polygon input buildings to point feature class
buildings_description = Describe(output_feature_class)
if buildings_description.shapeType == "Point":
# Input buildings are already a point shape file
inputs[INPUT_POINTS] = output_feature_class
elif buildings_description.shapeType == "Polygon":
# Input buildings need to be converted to point feature class
point_feature_class_name = POINT_FEATURE_CLASS_NAME(
basename(output_feature_class), inputs[POINT_LOCATION])
inputs[INPUT_POINTS] = "%s.shp" % join(inputs[OUTPUT_LOCATION],
point_feature_class_name)
# If FID is used as ID attribute, we need to change it since a point
# shapefile will be in use
if inputs[ID_ATTRIBUTE] == "FID":
inputs[ID_ATTRIBUTE] = ORIGINAL_FID
else:
# Input buildings need to be either points or polygons
raise Invalid_Input_Exception("Input Buildings")
# Find the appropriate symbology layer
for metric_index in range(len(METRICS)):
if inputs[COMPUTE_REACH + metric_index]:
first_metric = METRICS[metric_index]
break
symbology_layer_name = get_symbology_layer_name(
buildings_description.shapeType, first_metric)
symbology_layer = join(SYMBOLOGY_DIR, symbology_layer_name)
def clean_up():
"""
Removes all auxiliary files
"""
auxiliary_dir = join(inputs[OUTPUT_LOCATION], AUXILIARY_DIR_NAME)
od_cost_matrix_layer = join(auxiliary_dir, OD_COST_MATRIX_LAYER_NAME)
od_cost_matrix_lines = join(auxiliary_dir, OD_COST_MATRIX_LINES)
temp_adj_dbf_name = "%s~.dbf" % adj_dbf_name[-4]
temp_adj_dbf = join(inputs[OUTPUT_LOCATION], temp_adj_dbf_name)
partial_adj_dbf = join(auxiliary_dir, PARTIAL_ADJACENCY_LIST_NAME)
polygons = join(auxiliary_dir, POLYGONS_SHAPEFILE_NAME)
raster = join(auxiliary_dir, RASTER_NAME)
polygons_layer = join(auxiliary_dir, POLYGONS_LAYER_NAME)
input_points_layer = join(auxiliary_dir, INPUT_POINTS_LAYER_NAME)
for delete_path in [input_points_layer, polygons_layer, raster, polygons,
partial_adj_dbf, temp_adj_dbf, od_cost_matrix_lines,
od_cost_matrix_layer, auxiliary_dir]:
delete(delete_path)
try:
"""
Here we carry out the six steps of the tool
"""
# Step 1
if success:
AddMessage(STEP_1_STARTED)
# If necessary, convert input buildings to point feature class
if buildings_description.shapeType == "Polygon":
AddMessage(POINT_CONVERSION_STARTED)
to_point_feature_class(output_feature_class, inputs[INPUT_POINTS],
inputs[POINT_LOCATION])
AddMessage(POINT_CONVERSION_FINISHED)
if Exists(adj_dbf):
AddMessage(ADJACENCY_LIST_COMPUTED)
if node_locations_needed:
calculate_network_locations(inputs[INPUT_POINTS],
inputs[INPUT_NETWORK])
AddMessage(STEP_1_FINISHED)
else:
try:
compute_adjacency_list(inputs[INPUT_POINTS], inputs[INPUT_NETWORK],
inputs[ID_ATTRIBUTE], inputs[IMPEDANCE_ATTRIBUTE],
inputs[ACCUMULATOR_ATTRIBUTES], inputs[SEARCH_RADIUS],
inputs[OUTPUT_LOCATION], adj_dbf_name)
AddMessage(STEP_1_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_1_FAILED)
success = False
# Step 2
if success:
AddMessage(STEP_2_STARTED)
try:
distance_field = trim("Total_%s" % inputs[IMPEDANCE_ATTRIBUTE])
accumulator_fields = set([trim("Total_%s" % accumulator_attribute)
for accumulator_attribute in inputs[ACCUMULATOR_ATTRIBUTES].split(
";") if accumulator_attribute != "#"])
# Graph representation: dictionary mapping node id's to Node objects
nodes = {}
# The number of rows in |adj_dbf|
directed_edge_count = int(GetCount_management(adj_dbf).getOutput(0))
graph_progress = Progress_Bar(directed_edge_count, 1, STEP_2)
rows = UpdateCursor(adj_dbf)
for row in rows:
# Get neighboring nodes, and the distance between them
origin_id = row.getValue(trim(ORIGIN_ID_FIELD_NAME))
destination_id = row.getValue(trim(DESTINATION_ID_FIELD_NAME))
distance = float(row.getValue(distance_field))
# Make sure the nodes are recorded in the graph
for id in [origin_id, destination_id]:
if not id in nodes:
nodes[id] = Node()
# Make sure that the nodes are neighbors in the graph
if origin_id != destination_id and distance >= 0:
accumulations = {}
for field in accumulator_fields:
accumulations[field] = float(row.getValue(field))
nodes[origin_id].add_neighbor(destination_id, distance,
accumulations)
nodes[destination_id].add_neighbor(origin_id, distance,
accumulations)
graph_progress.step()
N = len(nodes) # The number of nodes in the graph
if N == 0:
AddWarning(WARNING_NO_NODES)
success = False
AddMessage(STEP_2_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_2_FAILED)
success = False
# Step 3
if success:
AddMessage(STEP_3_STARTED)
try:
get_weights = inputs[NODE_WEIGHT_ATTRIBUTE] != "#"
get_locations = node_locations_needed
# Keep track of number nodes in input points not present in the graph
point_not_in_graph_count = 0
input_point_count = int(
GetCount_management(inputs[INPUT_POINTS]).getOutput(0))
node_attribute_progress = Progress_Bar(input_point_count, 1, STEP_3)
rows = UpdateCursor(inputs[INPUT_POINTS])
for row in rows:
id = row.getValue(inputs[ID_ATTRIBUTE])
if not id in nodes:
point_not_in_graph_count += 1
continue
if get_weights:
setattr(nodes[id], WEIGHT,
row.getValue(trim(inputs[NODE_WEIGHT_ATTRIBUTE])))
if get_locations:
snap_x = row.getValue(trim("SnapX"))
snap_y = row.getValue(trim("SnapY"))
setattr(nodes[id], LOCATION, (snap_x, snap_y))
node_attribute_progress.step()
if point_not_in_graph_count:
AddWarning(WARNING_POINTS_NOT_IN_GRAPH(N,
point_not_in_graph_count))
AddMessage(STEP_3_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_3_FAILED)
success = False
# Step 4
if success:
AddMessage(STEP_4_STARTED)
try:
# Compute measures
compute_centrality(nodes, selected_features, inputs[COMPUTE_REACH],
inputs[COMPUTE_GRAVITY], inputs[COMPUTE_BETWEENNESS],
inputs[COMPUTE_CLOSENESS], inputs[COMPUTE_STRAIGHTNESS],
inputs[SEARCH_RADIUS], inputs[USE_NETWORK_RADIUS], inputs[BETA],
inputs[NORMALIZE_RESULTS], accumulator_fields)
AddMessage(STEP_4_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_4_FAILED)
success = False
# Step 5
if success:
AddMessage(STEP_5_STARTED)
try:
# Make output layer
MakeFeatureLayer_management(in_features=output_feature_class,
out_layer=output_layer_name)
# Save output layer
SaveToLayerFile_management(output_layer_name, output_layer,
"ABSOLUTE")
# Use a test node to figure out which metrics were computed
test_node_id = selected_features.pop()
# Make sure the test node is in the graph
while test_node_id not in nodes:
test_node_id = selected_features.pop()
test_node = nodes[test_node_id]
measures = set([measure for measure in dir(test_node) if (measure in
FINAL_ATTRIBUTES or is_accumulator_field(measure))])
# Add a field in the output layer for each computed metric
for measure in measures:
AddField_management(in_table=output_layer, field_name=trim(measure),
field_type="DOUBLE", field_is_nullable="NON_NULLABLE")
# Figure out the id field to use based on the type of input buildings
if (buildings_description.shapeType == "Polygon" and
inputs[ID_ATTRIBUTE] == ORIGINAL_FID):
id_field = "FID"
else:
id_field = inputs[ID_ATTRIBUTE]
# Fill the layer with the metric values
write_progress = Progress_Bar(N, 1, STEP_5)
layer_rows = UpdateCursor(output_layer)
for row in layer_rows:
id = row.getValue(id_field)
for measure in measures:
# If no value was computed for this node id, set value to 0
value = 0
if id in nodes and hasattr(nodes[id], measure):
value = getattr(nodes[id], measure)
row.setValue(trim(measure), value)
layer_rows.updateRow(row)
write_progress.step()
# Save to toolbox output
SetParameterAsText(OUTPUT_FEATURE_CLASS, output_feature_class)
AddMessage(STEP_5_FINISHED)
except:
AddWarning(GetMessages(2))
AddMessage(STEP_5_FAILED)
success = False
# Step 6
if success:
AddMessage(STEP_6_STARTED)
# Apply symbology
try:
ApplySymbologyFromLayer_management(in_layer=output_layer,
in_symbology_layer=symbology_layer)
except:
AddWarning(WARNING_APPLY_SYMBOLOGY_FAILED)
AddWarning(GetMessages(2))
AddMessage(STEP_6_FAILED)
# Display
try:
current_map_document = mapping.MapDocument("CURRENT")
data_frame = mapping.ListDataFrames(current_map_document,
"Layers")[0]
add_layer = mapping.Layer(output_layer)
mapping.AddLayer(data_frame, add_layer, "AUTO_ARRANGE")
AddMessage(STEP_6_FINISHED)
except:
AddWarning(WARNING_FAIL_TO_DISPLAY)
AddWarning(GetMessages(2))
AddMessage(STEP_6_FAILED)
# Clean up
clean_up()
AddMessage(SUCCESS if success else FAILURE)
except ExecuteAbort:
clean_up()