respect_switches = True
# getting unique sets of buses for each voltage level
vlev_bus_dict = {}
for vl_buses in vlev_buses:
if net.bus.loc[vl_buses, 'vn_kv'].unique().shape[0] > 1:
logger.warning('buses from the same voltage level does not have the same vn_kv !?')
vn_kv = net.bus.loc[vl_buses, 'vn_kv'].unique()[0]
if vlev_bus_dict.get(vn_kv):
vlev_bus_dict[vn_kv].update(vl_buses)
else:
vlev_bus_dict[vn_kv] = vl_buses
# create a default colormap for voltage levels
nvlevs = len(vlev_bus_dict)
colors = get_plotly_color_palette(nvlevs)
colors_dict = dict(zip(vlev_bus_dict.keys(), colors))
# creating traces for buses and lines for each voltage level
bus_traces = []
line_traces = []
for vn_kv, buses_vl in vlev_bus_dict.items():
vlev_color = colors_dict[vn_kv]
bus_trace_vlev = create_bus_trace(net, buses=buses_vl, size=bus_size, legendgroup=str(vn_kv),
color=vlev_color, trace_name='buses {0} kV'.format(vn_kv))
if bus_trace_vlev is not None:
bus_traces += bus_trace_vlev
vlev_lines = net.line[net.line.from_bus.isin(buses_vl) & net.line.to_bus.isin(buses_vl)].index.tolist()
print(vlev_lines)
def vlevel_plotly(net, respect_switches=True, use_line_geodata=None, colors_dict=None, on_map=False,
projection=None, map_style='basic', figsize=1, aspectratio='auto', line_width=2,
bus_size=10):
"""
Plots a pandapower network in plotly
using lines/buses colors according to the voltage level they belong to.
If no geodata is available, artificial geodata is generated. For advanced plotting see the tutorial
INPUT:
**net** - The pandapower format network. If none is provided, mv_oberrhein() will be
plotted as an example
OPTIONAL:
**respect_switches** (bool, True) - Respect switches when artificial geodata is created
**use_line_geodata** (bool, True) - defines if lines patches are based on net.line_geodata of the lines (True)
or on net.bus_geodata of the connected buses (False)
*colors_dict** (dict, None) - dictionary for customization of colors for each voltage level in the form:
voltage_kv : color
**on_map** (bool, False) - enables using mapbox plot in plotly If provided geodata are not real
geo-coordinates in lon/lat form, on_map will be set to False.
**projection** (String, None) - defines a projection from which network geo-data will be transformed to
lat-long. For each projection a string can be found at http://spatialreference.org/ref/epsg/
**map_style** (str, 'basic') - enables using mapbox plot in plotly
- 'streets'
- 'bright'
- 'light'
- 'dark'
- 'satellite'
**figsize** (float, 1) - aspectratio is multiplied by it in order to get final image size
**aspectratio** (tuple, 'auto') - when 'auto' it preserves original aspect ratio of the network geodata
any custom aspectration can be given as a tuple, e.g. (1.2, 1)
**line_width** (float, 1.0) - width of lines
**bus_size** (float, 10.0) - size of buses to plot.
"""
version_check()
# create geocoord if none are available
if 'line_geodata' not in net:
net.line_geodata = pd.DataFrame(columns=['coords'])
if 'bus_geodata' not in net:
net.bus_geodata = pd.DataFrame(columns=["x", "y"])
if len(net.line_geodata) == 0 and len(net.bus_geodata) == 0:
logger.warning("No or insufficient geodata available --> Creating artificial coordinates." +
" This may take some time")
create_generic_coordinates(net, respect_switches=respect_switches)
if on_map:
logger.warning("Map plots not available with artificial coordinates and will be disabled!")
on_map = False
# check if geodata are real geographycal lat/lon coordinates using geopy
if on_map and projection is not None:
geo_data_to_latlong(net, projection=projection)
# if bus geodata is available, but no line geodata
if use_line_geodata is None:
use_line_geodata = False if len(net.line_geodata) == 0 else True
elif use_line_geodata and len(net.line_geodata) == 0:
logger.warning("No or insufficient line geodata available --> only bus geodata will be used.")
use_line_geodata = False
# getting connected componenets without consideration of trafos
graph = create_nxgraph(net, include_trafos=False)
vlev_buses = connected_components(graph)
# getting unique sets of buses for each voltage level
vlev_bus_dict = {}
for vl_buses in vlev_buses:
if net.bus.loc[vl_buses, 'vn_kv'].unique().shape[0] > 1:
logger.warning('buses from the same voltage level does not have the same vn_kv !?')
vn_kv = net.bus.loc[vl_buses, 'vn_kv'].unique()[0]
if vlev_bus_dict.get(vn_kv):
vlev_bus_dict[vn_kv].update(vl_buses)
else:
vlev_bus_dict[vn_kv] = vl_buses
# create a default colormap for voltage levels
nvlevs = len(vlev_bus_dict)
colors = get_plotly_color_palette(nvlevs)
colors_dict = dict(zip(vlev_bus_dict.keys(), colors))
# creating traces for buses and lines for each voltage level
bus_traces = []
line_traces = []
for vn_kv, buses_vl in vlev_bus_dict.items():
vlev_color = colors_dict[vn_kv]
bus_trace_vlev = create_bus_trace(net, buses=buses_vl, size=bus_size, legendgroup=str(vn_kv),
color=vlev_color, trace_name='buses {0} kV'.format(vn_kv))
if bus_trace_vlev is not None:
bus_traces += bus_trace_vlev
vlev_lines = net.line[net.line.from_bus.isin(buses_vl) & net.line.to_bus.isin(buses_vl)].index.tolist()
line_trace_vlev = create_line_trace(net, lines=vlev_lines, use_line_geodata=use_line_geodata,
respect_switches=respect_switches, legendgroup=str(vn_kv),
color=vlev_color, width=line_width, trace_name='lines {0} kV'.format(vn_kv))
if line_trace_vlev is not None:
line_traces += line_trace_vlev
trafo_traces = create_trafo_trace(net, color='gray', width=line_width * 2)
draw_traces(line_traces + trafo_traces + bus_traces, showlegend=True,
aspectratio=aspectratio, on_map=on_map, map_style=map_style, figsize=figsize)
def vlevel_plotly(net, respect_switches=True, use_line_geodata=None, colors_dict=None, on_map=False,
projection=None, map_style='basic', figsize=1, aspectratio='auto', line_width=2,
bus_size=10, filename="temp-plot.html", auto_open=True):
"""
Plots a pandapower network in plotly
using lines/buses colors according to the voltage level they belong to.
If no geodata is available, artificial geodata is generated. For advanced plotting see the
tutorial
INPUT:
**net** - The pandapower format network. If none is provided, mv_oberrhein() will be
plotted as an example
OPTIONAL:
**respect_switches** (bool, True) - Respect switches when artificial geodata is created
**use_line_geodata** (bool, True) - defines if lines patches are based on net.line_geodata
of the lines (True) or on net.bus_geodata of the connected buses (False)
*colors_dict** (dict, None) - dictionary for customization of colors for each voltage level
in the form: voltage : color
**on_map** (bool, False) - enables using mapbox plot in plotly If provided geodata are not
real geo-coordinates in lon/lat form, on_map will be set to False.
**projection** (String, None) - defines a projection from which network geo-data will be
transformed to lat-long. For each projection a string can be found at
http://spatialreference.org/ref/epsg/
**map_style** (str, 'basic') - enables using mapbox plot in plotly
- 'streets'
- 'bright'
- 'light'
- 'dark'
- 'satellite'
**figsize** (float, 1) - aspectratio is multiplied by it in order to get final image size
**aspectratio** (tuple, 'auto') - when 'auto' it preserves original aspect ratio of the
network geodata any custom aspectration can be given as a tuple, e.g. (1.2, 1)
**line_width** (float, 1.0) - width of lines
**bus_size** (float, 10.0) - size of buses to plot.
**filename** (str, "temp-plot.html") - filename / path to plot to. Should end on `*.html`
**auto_open** (bool, True) - automatically open plot in browser
OUTPUT:
**figure** (graph_objs._figure.Figure) figure object
"""
# getting connected componenets without consideration of trafos
graph = create_nxgraph(net, include_trafos=False)
vlev_buses = connected_components(graph)
# getting unique sets of buses for each voltage level
vlev_bus_dict = {}
for vl_buses in vlev_buses:
if net.bus.loc[vl_buses, 'vn_kv'].unique().shape[0] > 1:
logger.warning('buses from the same voltage level does not have the same vn_kv !?')
vn_kv = net.bus.loc[vl_buses, 'vn_kv'].unique()[0]
if vlev_bus_dict.get(vn_kv):
vlev_bus_dict[vn_kv].update(vl_buses)
else:
vlev_bus_dict[vn_kv] = vl_buses
# create a default colormap for voltage levels
nvlevs = len(vlev_bus_dict)
colors = get_plotly_color_palette(nvlevs)
colors_dict = colors_dict or dict(zip(vlev_bus_dict.keys(), colors))
bus_groups = [(buses, colors_dict[vlev], f"{vlev} kV") for vlev, buses in vlev_bus_dict.items()]
return _draw_colored_bus_groups_plotly(
net, bus_groups, respect_switches=respect_switches,
use_line_geodata=use_line_geodata, on_map=on_map, projection=projection,
map_style=map_style, figsize=figsize, aspectratio=aspectratio, line_width=line_width,
bus_size=bus_size, filename=filename, auto_open=auto_open)
