def test_Infinite_Reach(self):
"""
Test reach at infinite radius
"""
compute_centrality(self.graph, self.nodes, True, False, False, False,
False, INFINITE_RADIUS, True, 1, [], [])
assert eq_tol(getattr(self.graph["A"], REACH), 3)
assert eq_tol(getattr(self.graph["B"], REACH), 3)
assert eq_tol(getattr(self.graph["C"], REACH), 3)
assert eq_tol(getattr(self.graph["D"], REACH), 3)
def test_Closeness(self):
"""
Test closeness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, False, True,
False, INFINITE_RADIUS, True, 1, [], [])
assert eq_tol(getattr(self.graph["A"], CLOSENESS), 1.0 / 7)
assert eq_tol(getattr(self.graph["B"], CLOSENESS), 1.0 / 7)
assert eq_tol(getattr(self.graph["C"], CLOSENESS), 1.0 / 5)
assert eq_tol(getattr(self.graph["D"], CLOSENESS), 1.0 / 11)
def test_Gravity(self):
"""
Test gravity at infinite radius and a beta value of 1
"""
compute_centrality(self.graph, self.nodes, False, True, False, False,
False, INFINITE_RADIUS, True, 1, [], [])
assert eq_tol(getattr(self.graph["A"], GRAVITY), 1)
assert eq_tol(getattr(self.graph["B"], GRAVITY), 1)
assert eq_tol(getattr(self.graph["C"], GRAVITY), 4.0 / 3)
assert eq_tol(getattr(self.graph["D"], GRAVITY), 2.0 / 3)
def test_Betweenness(self):
"""
Test betweenness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, True, False,
False, INFINITE_RADIUS, True, 1, [], [])
assert eq_tol(getattr(self.graph["A"], BETWEENNESS), 0)
assert eq_tol(getattr(self.graph["B"], BETWEENNESS), 0)
assert eq_tol(getattr(self.graph["C"], BETWEENNESS), 6)
assert eq_tol(getattr(self.graph["D"], BETWEENNESS), 0)
def test_Degree_Reach(self):
"""
Test reach at radius 1 - the reach values are no the degrees of the nodes
"""
compute_centrality(self.graph, self.nodes, True, False, False, False, False,
1, 1, [], [])
assert eq_tol(getattr(self.graph["A"], REACH), 2)
assert eq_tol(getattr(self.graph["B"], REACH), 2)
assert eq_tol(getattr(self.graph["C"], REACH), 3)
assert eq_tol(getattr(self.graph["D"], REACH), 1)
def test_Gravity(self):
"""
Test gravity at infinite radius and a beta value of 1
"""
compute_centrality(self.graph, self.nodes, False, True, False, False, False,
INFINITE_RADIUS, 1, [], [])
assert eq_tol(getattr(self.graph["A"], GRAVITY), 1)
assert eq_tol(getattr(self.graph["B"], GRAVITY), 1)
assert eq_tol(getattr(self.graph["C"], GRAVITY), 4.0 / 3)
assert eq_tol(getattr(self.graph["D"], GRAVITY), 2.0 / 3)
def test_Closeness(self):
"""
Test closeness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, False, True, False,
INFINITE_RADIUS, 1, [], [])
assert eq_tol(getattr(self.graph["A"], CLOSENESS), 1.0 / 7)
assert eq_tol(getattr(self.graph["B"], CLOSENESS), 1.0 / 7)
assert eq_tol(getattr(self.graph["C"], CLOSENESS), 1.0 / 5)
assert eq_tol(getattr(self.graph["D"], CLOSENESS), 1.0 / 11)
def test_Infinite_Reach(self):
"""
Test reach at infinite radius
"""
compute_centrality(self.graph, self.nodes, True, False, False, False, False,
INFINITE_RADIUS, 1, [], [])
assert eq_tol(getattr(self.graph["A"], REACH), 3)
assert eq_tol(getattr(self.graph["B"], REACH), 3)
assert eq_tol(getattr(self.graph["C"], REACH), 3)
assert eq_tol(getattr(self.graph["D"], REACH), 3)
def test_Betweenness(self):
"""
Test betweenness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, True, False, False,
INFINITE_RADIUS, 1, [], [])
assert eq_tol(getattr(self.graph["A"], BETWEENNESS), 0)
assert eq_tol(getattr(self.graph["B"], BETWEENNESS), 0)
assert eq_tol(getattr(self.graph["C"], BETWEENNESS), 6)
assert eq_tol(getattr(self.graph["D"], BETWEENNESS), 0)
def test_Straightness(self):
"""
Test straightness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, False, False,
True, INFINITE_RADIUS, True, 1, [], [])
assert eq_tol(getattr(self.graph["A"], STRAIGHTNESS),
2 + sqrt(5) / (1 + sqrt(2)))
assert eq_tol(getattr(self.graph["B"], STRAIGHTNESS),
2 + sqrt(5) / (1 + sqrt(2)))
assert eq_tol(getattr(self.graph["C"], STRAIGHTNESS), 3)
assert eq_tol(getattr(self.graph["D"], STRAIGHTNESS),
1 + 2 * sqrt(5) / (1 + sqrt(2)))
def test_Straightness(self):
"""
Test straightness at infinite radius
"""
compute_centrality(self.graph, self.nodes, False, False, False, False, True,
INFINITE_RADIUS, 1, [], [])
assert eq_tol(getattr(self.graph["A"], STRAIGHTNESS),
2 + sqrt(5) / (1 + sqrt(2)))
assert eq_tol(getattr(self.graph["B"], STRAIGHTNESS),
2 + sqrt(5) / (1 + sqrt(2)))
assert eq_tol(getattr(self.graph["C"], STRAIGHTNESS), 3)
assert eq_tol(getattr(self.graph["D"], STRAIGHTNESS),
1 + 2 * sqrt(5) / (1 + sqrt(2)))
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[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)
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)
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()