Mapping

Criticality Maps

There are built in methods to create interactive maps from the results of completed criticality analyses. To create a criticality map, enter the wn and the criticality results file into the make_criticality_map() function:

# Fire criticality example
cm.make_criticality_map(wn, fire_criticality_summary.yml)
# Pipe criticality example
cm.make_criticality_map(wn, pipe_criticality_summary.yml)

See the api documentation on make_criticality_map() for all available function options.

Dataframe-based Maps

CriticalityMaps also has the ability to create more general network maps based on the wn_dataframe class. A wn_dataframe object is composed of the a wn object, a node_data pandas DataFrame indexed by the water network’s node ID’s, and a link_data pandas DataFrame indexed by the water network’s link ID’s.

Initializing a wn_dataframe object

The initialization of a wn_dataframe object requires a WNTR WaterNetworkModel (wn) object as input. The node_data and link_data DataFrames are automatically created and populated with a ‘coordinates’ column, containing the coordinates of those network components.:

# The most basic initialization of a wn_dataframe object
my_wn_dataframe = cm.wn_dataframe(wn)

Adding data to the wn_dataframe

To add data to the wn_dataframe, standard methods for adding columns to an existing pandas DataFrame can be used:

# collect some data indexed by node ID
elevations = {}
for name, node in wn.nodes:
    elevations[name] = node.elevations
# add the node data as a new column labeled "elevation"
my_wn_dataframe.node_data["elevation"] = elevations

# wn querys are another great way to collect data on the water network model
base_demands = wn.query_node_attribute("base_demand")
# add the node data as a new column labeled "base demand"
my_wn_dataframe.node_data["base demand"] = base_demands

# collect some other data indexed by link ID
diameters = wn.query_link_attribute("diameter")
# add the data as a new column labeled "diameter"
my_wn_dataframe.link_data["diameter"] = diameters

Optionally, initial node and link data indexed by component ID can also be added to the object at initialization:

my_wn_dataframe = cm.wn_dataframe(wn,
                                  node_data={"elevation": elevations,"base demand": base_demands},
                                  link_data={"diameter": diameters})

The data entered at initialization can be a DataFrame, a dict of dicts/Series, or any other object that can be converted to a dataframe by pandas.DataFrame(), so long as it is indexed by node/link ID.

Mapping the wn_dataframe

To map the data stored in the wn_dataframe on the water network, simply call the make_map() function of the wn_dataframe. Specify which fields will appear in tooltips and which fields are added as map overlays on the water network (Note: any fields added to map_columns will automatically be added to the tooltip when that layer is activated on the map).

my_wn_dataframe.make_map(map_columns=["base demand", "diameter"], tooltip_columns=["elevation"])

See the wn_dataframe class and its make_map() method in the api documentation for more details on implementation options.