def test_create_generic_coordinates_nx(net_plotting):
net = copy.deepcopy(net_plotting)
net.junction_geodata.drop(net.junction_geodata.index, inplace=True)
create_generic_coordinates(net, library="networkx")
assert len(net.junction_geodata) == len(net.junction)
def create_simple_collections(net, respect_valves=False, pipe_width=5.0, junction_size=1.0,
ext_grid_size=1.0, plot_sinks=False, plot_sources=False,
sink_size=1.0, source_size=1.0, valve_size=1.0, pump_size=1.0,
heat_exchanger_size=1.0, scale_size=True, junction_color="r",
pipe_color='silver', ext_grid_color='orange', valve_color='silver',
pump_color='silver', heat_exchanger_color='silver',
library="igraph", as_dict=True, **kwargs):
"""
Plots a pandapipes network as simple as possible. If no geodata is available, artificial
geodata is generated. For advanced plotting see the tutorial
:param net: The pandapipes format network.
:type net: pandapipesNet
:param respect_valves: Respect valves if artificial geodata is created. \
.. note:: This Flag is ignored if plot_line_switches is True
:type respect_valves: bool default False
:param pipe_width: width of pipes
:type pipe_width: float, default 5.0
:param junction_size: Relative size of junctions to plot. The value junction_size is multiplied\
with mean_distance_between_buses, which equals the distance between the max geoocord\
and the min divided by 200: \
mean_distance_between_buses = sum((net['bus_geodata'].max() \
- net['bus_geodata'].min()) / 200)
:type junction_size: float, default 1.0
:param ext_grid_size: Relative size of ext_grids to plot. See bus sizes for details. Note: \
ext_grids are plottet as rectangles
:type ext_grid_size: float, default 1.0
:param plot_sinks: Flag to decide whether sink symbols should be drawn.
:type plot_sinks: bool, default False
:param plot_sources: Flag to decide whether source symbols should be drawn.
:type plot_sources: bool, default False
:param sink_size: Relative size of sinks to plot.
:type sink_size: float, default 1.0
:param source_size: Relative size of sources to plot.
:type source_size: float, default 1.0
:param valve_size: Relative size of valves to plot.
:type valve_size: float, default 1.0
:param heat_exchanger_size:
:type heat_exchanger_size:
:param scale_size: Flag if junction_size, ext_grid_size, valve_size- and distance will be \
scaled with respect to grid mean distances
:type scale_size: bool, default True
:param junction_color: Junction Color. See also matplotlib or seaborn documentation on how to\
choose colors.
:type junction_color: str, tuple, default "r"
:param pipe_color: Pipe Color.
:type pipe_color: str, tuple, default "silver"
:param ext_grid_color: External Grid Color.
:type ext_grid_color: str, tuple, default "orange"
:param library: library name to create generic coordinates (case of missing geodata). Choose\
"igraph" to use igraph package or "networkx" to use networkx package. **NOTE**: \
Currently the networkx implementation is not working!
:type library: str, default "igraph"
:param as_dict: flag whether to return dictionary for network components or just a list
:type as_dict: bool, default True
:return: collections - list of simple collections for the given network
"""
# don't hide lines if switches are plotted
# create geocoord if none are available
if len(net.junction_geodata) == 0 and len(net.pipe_geodata) == 0:
logger.warning("No or insufficient geodata available --> Creating artificial coordinates." +
" This may take some time")
create_generic_coordinates(net, library=library)
if scale_size:
# if scale_size -> calc size from distance between min and max geocoord
sizes = get_collection_sizes(net, junction_size, ext_grid_size, sink_size, source_size,
valve_size, pump_size, heat_exchanger_size)
junction_size = sizes["junction"]
ext_grid_size = sizes["ext_grid"]
source_size = sizes["source"]
sink_size = sizes["sink"]
valve_size = sizes["valve"]
pump_size = sizes["pump"]
heat_exchanger_size = sizes["heat_exchanger"]
# create junction collections to plot
junction_coll = create_junction_collection(net, net.junction.index, size=junction_size,
color=junction_color, zorder=10)
# if bus geodata is available, but no line geodata
use_junction_geodata = len(net.pipe_geodata) == 0
plot_lines = net.pipe[net.pipe.in_service].index
# create line collections
pipe_coll = create_pipe_collection(net, plot_lines, color=pipe_color, linewidths=pipe_width,
use_junction_geodata=use_junction_geodata)
collections = {"junction": junction_coll, "pipe": pipe_coll}
# create ext_grid collections
eg_junctions_with_geo_coordinates = set(net.ext_grid.junction.values) \
& set(net.junction_geodata.index)
if len(eg_junctions_with_geo_coordinates) > 0:
eg_coll = create_junction_collection(
net, eg_junctions_with_geo_coordinates, patch_type="rect", size=ext_grid_size,
color=ext_grid_color, zorder=11)
collections["ext_grid"] = eg_coll
if 'source' in net and plot_sources and len(net.source) > 0:
source_colls = create_source_collection(net, size=source_size)
collections["source"] = source_colls
if 'sink' in net and plot_sinks and len(net.sink) > 0:
sink_colls = create_sink_collection(net, size=sink_size)
collections["sink"] = sink_colls
if 'valve' in net:
valve_colls = create_valve_collection(net, size=valve_size, linewidths=pipe_width,
color=valve_color, respect_valves=respect_valves)
collections["valve"] = valve_colls
if 'pump' in net:
pump_colls = create_pump_collection(net, size=pump_size, linewidths=pipe_width,
color=pump_color)
collections["pump"] = pump_colls
if 'circ_pump_mass' in net:
circ_pump_colls = create_pump_collection(net, table_name='circ_pump_mass',
size=pump_size, linewidths=pipe_width, color=pump_color)
collections["circ_pump_mass"] = circ_pump_colls
if 'circ_pump_pressure' in net:
circ_pump_colls = create_pump_collection(net, table_name='circ_pump_pressure',
size=pump_size, linewidths=pipe_width, color=pump_color)
collections["circ_pump_pressure"] = circ_pump_colls
if 'heat_exchanger' in net:
hxc = create_heat_exchanger_collection(net, size=heat_exchanger_size, linewidths=pipe_width,
color=heat_exchanger_color)
collections["heat_exchanger"] = hxc
if 'additional_collections' in kwargs:
collections["additional"] = list()
for collection in kwargs.pop('additional_collections'):
collections["additional"].extend(collection)
if as_dict:
return collections
return list(chain.from_iterable([list(c) if hasattr(c, "__iter__") else [c]
for c in collections.values()]))
