def create_valve_collection(net, valves=None, size=5., junction_geodata=None, color='k',
infofunc=None, picker=False, fill_closed=True,
respect_valves=False, **kwargs):
"""
Creates a matplotlib patch collection of pandapipes junction-junction valves. Valves are
plotted in the center between two junctions with a "helper" line (dashed and thin) being drawn
between the junctions as well.
:param net: The pandapipes network
:type net: pandapipesNet
:param valves: The valves for which the collections are created. If None, all valves which have\
entries in the respective junction geodata will be plotted.
:type valves: list, default None
:param size: Patch size
:type size: float, default 5.
:param junction_geodata: Coordinates to use for plotting. If None, net["junction_geodata"] is used.
:type junction_geodata: pandas.DataFrame, default None
:param colors: Color or list of colors for every valve
:type colors: iterable, float, default None
:param infofunc: infofunction for the patch element
:type infofunc: function, default None
:param picker: Picker argument passed to the patch collection
:type picker: bool, default False
:param fill_closed: If True, valves with parameter opened == False will be filled and those\
with opened == True will have a white facecolor. Vice versa if False.
:type fill_closed: bool, default True
:param kwargs: Keyword arguments are passed to the patch function
:return: lc - line collection, pc - patch collection
"""
valves = get_index_array(
valves, net.valve[net.valve.opened.values].index if respect_valves else net.valve.index)
valve_table = net.valve.loc[valves]
coords, valves_with_geo = coords_from_node_geodata(
valves, valve_table.from_junction.values, valve_table.to_junction.values,
junction_geodata if junction_geodata is not None else net["junction_geodata"], "valve",
"Junction")
if len(valves_with_geo) == 0:
return None
linewidths = kwargs.pop("linewidths", 2.)
linewidths = kwargs.pop("linewidth", linewidths)
linewidths = kwargs.pop("lw", linewidths)
infos = list(np.repeat([infofunc(i) for i in range(len(valves_with_geo))], 2)) \
if infofunc is not None else []
filled = valve_table["opened"].values
if fill_closed:
filled = ~filled
lc, pc = _create_complex_branch_collection(coords, valve_patches, size, infos,
picker=picker, linewidths=linewidths, filled=filled,
patch_facecolor=color, line_color=color,
**kwargs)
return lc, pc
def create_heat_exchanger_collection(net, heat_ex=None, size=5., junction_geodata=None,
infofunc=None, picker=False, **kwargs):
"""
Creates a matplotlib patch collection of pandapipes junction-junction heat_exchangers.
Heat_exchangers are plotted in the center between two junctions with a "helper" line
(dashed and thin) being drawn between the junctions as well.
:param net: The pandapipes network
:type net: pandapipesNet
:param size: Patch size
:type size: float, default 2.
:param helper_line_style: Line style of the "helper" line being plotted between two junctions
connected by a junction-junction heat_exchanger
:type helper_line_style: str, default ":"
:param helper_line_size: Line width of the "helper" line being plotted between two junctions
connected by a junction-junction heat_exchanger
:type helper_line_size: float, default 1.
:param helper_line_color: Line color of the "helper" line being plotted between two junctions
connected by a junction-junction valve
:type helper_line_color: str, default "gray"
:param orientation: Orientation of heat_exchanger collection. pi is directed downwards,
increasing values lead to clockwise direction changes.
:type orientation: float, default np.pi/2
:param kwargs: Keyword arguments are passed to the patch function
:return: heat_exchanger, helper_lines
:rtype: tuple of patch collections
"""
heat_ex = get_index_array(heat_ex, net.heat_exchanger.index)
hex_table = net.heat_exchanger.loc[heat_ex]
coords, hex_with_geo = coords_from_node_geodata(
heat_ex, hex_table.from_junction.values, hex_table.to_junction.values,
junction_geodata if junction_geodata is not None else net["junction_geodata"],
"heat_exchanger", "Junction")
if len(hex_with_geo) == 0:
return None
colors = kwargs.pop("color", "k")
linewidths = kwargs.pop("linewidths", 2.)
linewidths = kwargs.pop("linewidth", linewidths)
linewidths = kwargs.pop("lw", linewidths)
patch_edgecolor = kwargs.pop("patch_edgecolor", colors)
line_color = kwargs.pop("line_color", colors)
infos = list(np.repeat([infofunc(i) for i in range(len(hex_with_geo))], 2)) \
if infofunc is not None else []
lc, pc = _create_complex_branch_collection(
coords, heat_exchanger_patches, size, infos, picker=picker, linewidths=linewidths,
patch_edgecolor=patch_edgecolor, line_color=line_color, **kwargs)
return lc, pc
def create_pump_collection(net, pumps=None, table_name='pump', size=5., junction_geodata=None,
infofunc=None, picker=False, **kwargs):
"""
Creates a matplotlib patch collection of pandapipes junction-junction valves. Valves are
plotted in the center between two junctions with a "helper" line (dashed and thin) being drawn
between the junctions as well.
:param net: The pandapipes network
:type net: pandapipesNet
:param pumps: The pumps for which the collections are created. If None, all pumps which have\
entries in the respective junction geodata will be plotted.
:type pumps: list, default None
:param table_name: Name of the pump table from which to get the data.
:type table_name: str, default 'pump'
:param size: Patch size
:type size: float, default 5.
:param junction_geodata: Coordinates to use for plotting. If None, net["junction_geodata"] is used.
:type junction_geodata: pandas.DataFrame, default None
:param infofunc: infofunction for the patch element
:type infofunc: function, default None
:param picker: Picker argument passed to the patch collection
:type picker: bool, default False
:param kwargs: Keyword arguments are passed to the patch function
:return: lc - line collection, pc - patch collection
"""
pumps = get_index_array(pumps, net[table_name].index)
pump_table = net[table_name].loc[pumps]
coords, pumps_with_geo = coords_from_node_geodata(
pumps, pump_table.from_junction.values, pump_table.to_junction.values,
junction_geodata if junction_geodata is not None else net["junction_geodata"], "pump",
"Junction")
if len(pumps_with_geo) == 0:
return None
colors = kwargs.pop("color", "k")
linewidths = kwargs.pop("linewidths", 2.)
linewidths = kwargs.pop("linewidth", linewidths)
linewidths = kwargs.pop("lw", linewidths)
patch_edgecolor = kwargs.pop("patch_edgecolor", colors)
line_color = kwargs.pop("line_color", colors)
infos = list(np.repeat([infofunc(i) for i in range(len(pumps_with_geo))], 2)) \
if infofunc is not None else []
lc, pc = _create_complex_branch_collection(
coords, pump_patches, size, infos, picker=picker, linewidths=linewidths,
patch_edgecolor=patch_edgecolor, line_color=line_color, **kwargs)
return lc, pc
def create_pipe_collection(net, pipes=None, pipe_geodata=None, junction_geodata=None,
use_junction_geodata=False, infofunc=None, cmap=None, norm=None,
picker=False, z=None, cbar_title="Pipe Loading [%]", clim=None,
**kwargs):
"""
Creates a matplotlib pipe collection of pandapipes pipes.
:param net: The pandapipes network
:type net: pandapipesNet
:param pipes: The pipes for which the collections are created. If None, all pipes
in the network are considered.
:type pipes: list, default None
:param pipe_geodata: Coordinates to use for plotting. If None, net["pipe_geodata"] is used.
:type pipe_geodata: pandas.DataFrame, default None
:param junction_geodata: Coordinates to use for plotting in case of use_junction_geodata=True.\
If None, net["junction_geodata"] is used.
:type junction_geodata: pandas.DataFrame, default None
:param use_junction_geodata: Defines whether junction or pipe geodata are used.
:type use_junction_geodata: bool, default False
:param infofunc: infofunction for the line element
:type infofunc: function, default None
:param cmap: colormap for the line colors
:type cmap: matplotlib norm object, default None
:param norm: matplotlib norm object
:type norm: matplotlib norm object, default None
:param picker: Picker argument passed to the patch collection
:type picker: bool, default False
:param z: Array of pipe loading magnitudes for colormap. Used in case of given cmap. If None,\
net.res_pipe.loading_percent is used.
:type z: array, default None
:param cbar_title: colormap bar title in case of given cmap
:type cbar_title: str, default "Pipe Loading [%]"
:param clim: Setting the norm limits for image scaling
:type clim: tuple of floats, default None
:param kwargs: Keyword arguments are passed to the patch function and the patch maker
:return: lc (matplotlib line collection) - line collection for pipes
"""
if use_junction_geodata is False and net.pipe_geodata.empty:
# if bus geodata is available, but no line geodata
logger.warning("use_junction_geodata is automatically set to True, since net.pipe_geodata "
"is empty.")
use_junction_geodata = True
pipes = get_index_array(pipes, net.pipe.index)
if len(pipes) == 0:
return None
if use_junction_geodata:
coords, pipes_with_geo = coords_from_node_geodata(
pipes, net.pipe.from_junction.loc[pipes].values, net.pipe.to_junction.loc[pipes].values,
junction_geodata if junction_geodata is not None else net["junction_geodata"], "pipe",
"Junction")
else:
if pipe_geodata is None:
pipe_geodata = net.pipe_geodata
pipes_with_geo = pipes[np.isin(pipes, pipe_geodata.index.values)]
coords = list(pipe_geodata.loc[pipes_with_geo, "coords"])
pipes_without_geo = set(pipes) - set(pipes_with_geo)
if pipes_without_geo:
logger.warning("Could not plot pipes %s. Pipe geodata is missing for those pipes!"
% pipes_without_geo)
if len(pipes_with_geo) == 0:
return None
infos = [infofunc(pipe) for pipe in pipes_with_geo] if infofunc else []
lc = _create_line2d_collection(coords, pipes_with_geo, infos=infos, picker=picker, **kwargs)
if cmap is not None:
if z is None:
z = net.res_pipe.v_mean_m_per_s.loc[pipes_with_geo]
elif isinstance(z, pd.Series):
z = z.loc[pipes_with_geo]
add_cmap_to_collection(lc, cmap, norm, z, cbar_title, clim=clim)
return lc