def test_create_generic_coordinates_igraph_custom_table_index():
net = nw.simple_four_bus_system()
for buses in [[0, 1], [0, 2], [0, 1, 2]]:
create_generic_coordinates(net,
buses=buses,
geodata_table="test",
overwrite=True)
assert np.all(net.test.index == buses)
def pf_res_plotly(net, cmap="Jet", use_line_geodata=None, on_map=False, projection=None,
map_style='basic', figsize=1, aspectratio='auto', line_width=2, bus_size=10,
climits_volt=(0.9, 1.1), climits_load=(0, 100), cpos_volt=1.0, cpos_load=1.1,
filename="temp-plot.html", auto_open=True):
"""
Plots a pandapower network in plotly
using colormap for coloring lines according to line loading and buses according to voltage in p.u.
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, False) - Respect switches when artificial geodata is created
**cmap** (str, True) - name of the colormap
**colors_dict** (dict, None) - by default 6 basic colors from default collor palette is used.
Otherwise, user can define a dictionary 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.
**climits_volt** (tuple, (0.9, 1.0)) - limits of the colorbar for voltage
**climits_load** (tuple, (0, 100)) - limits of the colorbar for line_loading
**cpos_volt** (float, 1.0) - position of the bus voltage colorbar
**cpos_load** (float, 1.1) - position of the loading percent colorbar
**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
"""
version_check()
if 'res_bus' not in net or net.get('res_bus').shape[0] == 0:
logger.warning('There are no Power Flow results. A Newton-Raphson power flow will be executed.')
runpp(net)
# 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=True)
if on_map:
logger.warning("Map plots not available with artificial coordinates and will be disabled!")
on_map = False
for geo_type in ["bus_geodata", "line_geodata"]:
dupl_geo_idx = pd.Series(net[geo_type].index)[pd.Series(
net[geo_type].index).duplicated()]
if len(dupl_geo_idx):
if len(dupl_geo_idx) > 20:
logger.warning("In net.%s are %i duplicated " % (geo_type, len(dupl_geo_idx)) +
"indices. That can cause troubles for draw_traces()")
else:
logger.warning("In net.%s are the following duplicated " % geo_type +
"indices. That can cause troubles for draw_traces(): " + str(
dupl_geo_idx))
# 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)
# ----- Buses ------
# initializating bus trace
# hoverinfo which contains name and pf results
precision = 3
hoverinfo = (
net.bus.name.astype(str) + '<br />' +
'V_m = ' + net.res_bus.vm_pu.round(precision).astype(str) + ' pu' + '<br />' +
'V_m = ' + (net.res_bus.vm_pu * net.bus.vn_kv.round(2)).round(precision).astype(str) + ' kV' + '<br />' +
'V_a = ' + net.res_bus.va_degree.round(precision).astype(str) + ' deg').tolist()
hoverinfo = pd.Series(index=net.bus.index, data=hoverinfo)
bus_trace = create_bus_trace(net, net.bus.index, size=bus_size, infofunc=hoverinfo, cmap=cmap,
cbar_title='Bus Voltage [pu]', cmin=climits_volt[0], cmax=climits_volt[1],
cpos=cpos_volt)
# ----- Lines ------
# if bus geodata is available, but no line geodata
# if bus geodata is available, but no line geodata
cmap_lines = 'jet' if cmap == 'Jet' else cmap
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
# hoverinfo which contains name and pf results
hoverinfo = (
net.line.name.astype(str) + '<br />' +
'I = ' + net.res_line.loading_percent.round(precision).astype(str) + ' %' + '<br />' +
'I_from = ' + net.res_line.i_from_ka.round(precision).astype(str) + ' kA' + '<br />' +
'I_to = ' + net.res_line.i_to_ka.round(precision).astype(str) + ' kA' + '<br />').tolist()
hoverinfo = pd.Series(index=net.line.index, data=hoverinfo)
line_traces = create_line_trace(net, use_line_geodata=use_line_geodata, respect_switches=True,
width=line_width,
infofunc=hoverinfo,
cmap=cmap_lines,
cmap_vals=net.res_line['loading_percent'].values,
cmin=climits_load[0],
cmax=climits_load[1],
cbar_title='Line Loading [%]',
cpos=cpos_load)
# ----- Trafos ------
# hoverinfo which contains name and pf results
hoverinfo = (
net.trafo.name.astype(str) + '<br />' +
'I = ' + net.res_trafo.loading_percent.round(precision).astype(str) + ' %' + '<br />' +
'I_hv = ' + net.res_trafo.i_hv_ka.round(precision).astype(str) + ' kA' + '<br />' +
'I_lv = ' + net.res_trafo.i_lv_ka.round(precision).astype(str) + ' kA' + '<br />').tolist()
hoverinfo = pd.Series(index=net.trafo.index, data=hoverinfo)
trafo_traces = create_trafo_trace(net, width=line_width * 1.5, infofunc=hoverinfo,
cmap=cmap_lines, cmin=0, cmax=100)
# ----- Ext grid ------
# get external grid from create_bus_trace
marker_type = 'circle' if on_map else 'square'
ext_grid_trace = create_bus_trace(net, buses=net.ext_grid.bus,
color='grey', size=bus_size * 2, trace_name='external_grid',
patch_type=marker_type)
return draw_traces(line_traces + trafo_traces + ext_grid_trace + bus_trace,
showlegend=False, aspectratio=aspectratio, on_map=on_map,
map_style=map_style, figsize=figsize, filename=filename, auto_open=auto_open)
def simple_plot(net,
respect_switches=False,
line_width=1.0,
bus_size=1.0,
ext_grid_size=1.0,
scale_size=True,
bus_color="b",
line_color='grey',
trafo_color='k',
ext_grid_color='y',
library="igraph"):
"""
Plots a pandapower network as simple as possible. If no geodata is available, artificial
geodata is generated. For advanced plotting see the tutorial
INPUT:
**net** - The pandapower format network.
OPTIONAL:
**respect_switches** (bool, False) - Respect switches if artificial geodata is created
**line_width** (float, 1.0) - width of lines
**bus_size** (float, 1.0) - Relative size of buses to plot.
The value bus_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)
**ext_grid_size** (float, 1.0) - Relative size of ext_grids to plot.
See bus sizes for details. Note: ext_grids are plottet as rectangles
**scale_size** (bool, True) - Flag if bus_size and ext_grid_size will be scaled with
respect to grid mean distances
**bus_color** (String, colors[0]) - Bus Color. Init as first value of color palette.
Usually colors[0] = "b".
**line_color** (String, 'grey') - Line Color. Init is grey
**trafo_color** (String, 'k') - Trafo Color. Init is black
**ext_grid_color** (String, 'y') - External Grid Color. Init is yellow
"""
# create geocoord if none are available
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,
library=library)
if scale_size:
# if scale_size -> calc size from distance between min and max geocoord
mean_distance_between_buses = sum(
(net['bus_geodata'].max() - net['bus_geodata'].min()) / 200)
# set the bus / ext_grid sizes accordingly
# Comment: This is implemented because if you would choose a fixed values
# (e.g. bus_size = 0.2), the size
# could be to small for large networks and vice versa
bus_size *= mean_distance_between_buses
ext_grid_size *= mean_distance_between_buses * 1.5
# create bus collections ti plot
bc = create_bus_collection(net,
net.bus.index,
size=bus_size,
color=bus_color,
zorder=10)
# if bus geodata is available, but no line geodata
use_bus_geodata = len(net.line_geodata) == 0
in_service_lines = net.line[net.line.in_service].index
nogolines = set(net.switch.element[(net.switch.et == "l") & (net.switch.closed == 0)]) \
if respect_switches else set()
plot_lines = in_service_lines.difference(nogolines)
lc = create_line_collection(net,
plot_lines,
color=line_color,
linewidths=line_width,
use_bus_geodata=use_bus_geodata)
collections = [bc, lc]
eg_buses_with_geo_coordinates = set(net.ext_grid.bus.values) & set(
net.bus_geodata.index)
if len(eg_buses_with_geo_coordinates) > 0:
sc = create_bus_collection(net,
eg_buses_with_geo_coordinates,
patch_type="rect",
size=ext_grid_size,
color=ext_grid_color,
zorder=11)
collections.append(sc)
# create trafo collection if trafo is available
trafo_buses_with_geo_coordinates = [
t for t, trafo in net.trafo.iterrows()
if trafo.hv_bus in net.bus_geodata.index
and trafo.lv_bus in net.bus_geodata.index
]
if len(trafo_buses_with_geo_coordinates) > 0:
tc = create_trafo_symbol_collection(net,
trafo_buses_with_geo_coordinates,
color=trafo_color)
collections.append(tc[0])
collections.append(tc[1])
draw_collections(collections)
plt.show()
def simple_plot(net, respect_switches=False, line_width=1.0, bus_size=1.0, ext_grid_size=1.0,
trafo_size=1.0, plot_loads=False, plot_sgens=False, load_size=1.0, sgen_size=1.0,
switch_size=2.0, switch_distance=1.0, plot_line_switches=False, scale_size=True,
bus_color="b", line_color='grey', trafo_color='k', ext_grid_color='y',
switch_color='k', library="igraph", show_plot=True, ax=None):
"""
Plots a pandapower network as simple as possible. If no geodata is available, artificial
geodata is generated. For advanced plotting see the tutorial
INPUT:
**net** - The pandapower format network.
OPTIONAL:
**respect_switches** (bool, False) - Respect switches if artificial geodata is created.
.. note::
This Flag is ignored if plot_line_switches is True
**line_width** (float, 1.0) - width of lines
**bus_size** (float, 1.0) - Relative size of buses to plot.
The value bus_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)
**ext_grid_size** (float, 1.0) - Relative size of ext_grids to plot.
See bus sizes for details. Note: ext_grids are plottet as rectangles
**trafo_size** (float, 1.0) - Relative size of trafos to plot.
**plot_loads** (bool, False) - Flag to decide whether load symbols should be drawn.
**plot_sgens** (bool, False) - Flag to decide whether sgen symbols should be drawn.
**load_size** (float, 1.0) - Relative size of loads to plot.
**sgen_size** (float, 1.0) - Relative size of sgens to plot.
**switch_size** (float, 2.0) - Relative size of switches to plot. See bus size for details
**switch_distance** (float, 1.0) - Relative distance of the switch to its corresponding \
bus. See bus size for details
**plot_line_switches** (bool, False) - Flag if line switches are plotted
**scale_size** (bool, True) - Flag if bus_size, ext_grid_size, bus_size- and distance \
will be scaled with respect to grid mean distances
**bus_color** (String, colors[0]) - Bus Color. Init as first value of color palette.
Usually colors[0] = "b".
**line_color** (String, 'grey') - Line Color. Init is grey
**trafo_color** (String, 'k') - Trafo Color. Init is black
**ext_grid_color** (String, 'y') - External Grid Color. Init is yellow
**switch_color** (String, 'k') - Switch Color. Init is black
**library** (String, "igraph") - library name to create generic coordinates (case of
missing geodata). "igraph" to use igraph package or "networkx" to use networkx package.
**show_plot** (bool, True) - Shows plot at the end of plotting
**ax** (object, None) - matplotlib axis to plot to
OUTPUT:
**ax** - axes of figure
"""
# don't hide lines if switches are plotted
if plot_line_switches:
respect_switches = False
# create geocoord if none are available
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, library=library)
if scale_size:
# if scale_size -> calc size from distance between min and max geocoord
sizes = get_collection_sizes(net, bus_size, ext_grid_size, switch_size,
switch_distance, load_size, sgen_size, trafo_size)
bus_size = sizes["bus"]
ext_grid_size = sizes["ext_grid"]
trafo_size = sizes["trafo"]
sgen_size = sizes["sgen"]
load_size = sizes["load"]
switch_size = sizes["switch"]
switch_distance = sizes["switch_distance"]
# create bus collections to plot
bc = create_bus_collection(net, net.bus.index, size=bus_size, color=bus_color, zorder=10)
# if bus geodata is available, but no line geodata
use_bus_geodata = len(net.line_geodata) == 0
in_service_lines = net.line[net.line.in_service].index
nogolines = set(net.switch.element[(net.switch.et == "l") & (net.switch.closed == 0)]) \
if respect_switches else set()
plot_lines = in_service_lines.difference(nogolines)
# create line collections
lc = create_line_collection(net, plot_lines, color=line_color, linewidths=line_width,
use_bus_geodata=use_bus_geodata)
collections = [bc, lc]
# create ext_grid collections
eg_buses_with_geo_coordinates = set(net.ext_grid.bus.values) & set(net.bus_geodata.index)
if len(eg_buses_with_geo_coordinates) > 0:
sc = create_bus_collection(net, eg_buses_with_geo_coordinates, patch_type="rect",
size=ext_grid_size, color=ext_grid_color, zorder=11)
collections.append(sc)
# create trafo collection if trafo is available
trafo_buses_with_geo_coordinates = [t for t, trafo in net.trafo.iterrows()
if trafo.hv_bus in net.bus_geodata.index and
trafo.lv_bus in net.bus_geodata.index]
if len(trafo_buses_with_geo_coordinates) > 0:
tc = create_trafo_collection(net, trafo_buses_with_geo_coordinates,
color=trafo_color, size=trafo_size)
collections.append(tc)
# create trafo3w collection if trafo3w is available
trafo3w_buses_with_geo_coordinates = [
t for t, trafo3w in net.trafo3w.iterrows() if trafo3w.hv_bus in net.bus_geodata.index and
trafo3w.mv_bus in net.bus_geodata.index and trafo3w.lv_bus in net.bus_geodata.index]
if len(trafo3w_buses_with_geo_coordinates) > 0:
tc = create_trafo3w_collection(net, trafo3w_buses_with_geo_coordinates,
color=trafo_color)
collections.append(tc)
if plot_line_switches and len(net.switch):
sc = create_line_switch_collection(
net, size=switch_size, distance_to_bus=switch_distance,
use_line_geodata=not use_bus_geodata, zorder=12, color=switch_color)
collections.append(sc)
if plot_sgens and len(net.sgen):
sgc = create_sgen_collection(net, size=sgen_size)
collections.append(sgc)
if plot_loads and len(net.load):
lc = create_load_collection(net, size=load_size)
collections.append(lc)
if len(net.switch):
bsc = create_bus_bus_switch_collection(net, size=switch_size)
collections.append(bsc)
ax = draw_collections(collections, ax=ax)
if show_plot:
plt.show()
return ax
def pf_res_plotly(net, cmap='Jet', use_line_geodata = 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 colormap for coloring lines according to line loading and buses according to voltage in p.u.
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, False) - Respect switches when artificial geodata is created
*cmap** (str, True) - name of the colormap
*colors_dict** (dict, None) - by default 6 basic colors from default collor palette is used.
Otherwise, user can define a dictionary 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.
"""
if 'res_bus' not in net or net.get('res_bus').shape[0] == 0:
logger.warning('There are no Power Flow results. A Newton-Raphson power flow will be executed.')
runpp(net)
# 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=True)
if on_map == True:
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)
# ----- Buses ------
# initializating bus trace
idx = net.line.index
# hoverinfo which contains name and pf results
hoverinfo = (net.bus['name'] + '<br>' +
'U = ' + net.res_bus.loc[idx, 'vm_pu'].astype(str) + ' pu' + '<br>' +
'U = ' + (net.res_bus.loc[idx, 'vm_pu'] * net.bus.vn_kv).astype(str) + ' kV' + '<br>' +
'ang = ' + net.res_bus.loc[idx, 'va_degree'].astype(str) + ' deg'
).tolist()
bus_trace = create_bus_trace(net, net.bus.index, size=bus_size, infofunc=hoverinfo, cmap=cmap,
cbar_title='Bus Voltage [pu]', cmin=0.9, cmax=1.1)
# ----- Lines ------
# if bus geodata is available, but no line geodata
# if bus geodata is available, but no line geodata
cmap_lines = 'jet' if cmap is 'Jet' else cmap
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
idx = net.line.index
# hoverinfo which contains name and pf results
hoverinfo = (net.line['name'] + '<br>' +
'I = ' + net.res_line.loc[idx, 'loading_percent'].astype(str) + ' %' + '<br>' +
'I_from = ' + net.res_line.loc[idx, 'i_from_ka'].astype(str) + ' kA' + '<br>' +
'I_to = ' + net.res_line.loc[idx, 'i_to_ka'].astype(str) + ' kA' + '<br>'
).tolist()
line_traces = []
line_traces = create_line_trace(net, use_line_geodata=use_line_geodata, respect_switches=True,
width=line_width,
infofunc=hoverinfo,
cmap=cmap_lines,
cmap_vals=net.res_line.loc[:, 'loading_percent'].values,
cmin=0,
cmax=100,
cbar_title='Line Loading [%]')
# ----- Trafos ------
idx = net.trafo.index
# hoverinfo which contains name and pf results
hoverinfo = (net.trafo['name'] + '<br>' +
'I = ' + net.res_trafo.loc[idx, 'loading_percent'].astype(str) + ' %' + '<br>' +
'I_hv = ' + net.res_trafo.loc[idx, 'i_hv_ka'].astype(str) + ' kA' + '<br>' +
'I_lv = ' + net.res_trafo.loc[idx, 'i_lv_ka'].astype(str) + ' kA' + '<br>'
).tolist()
trafo_traces = create_trafo_trace(net, width=line_width * 1.5, infofunc=hoverinfo,
cmap=cmap_lines, cmin=0, cmax=100)
# ----- Ext grid ------
# get external grid from create_bus_trace
marker_type = 'circle' if on_map else 'square'
ext_grid_trace = create_bus_trace(net, buses=net.ext_grid.bus,
color='grey', size=bus_size * 2, trace_name='external_grid',
patch_type=marker_type)
draw_traces(line_traces + trafo_traces + ext_grid_trace + bus_trace,
showlegend=False, aspectratio=aspectratio, on_map=on_map, map_style=map_style, figsize=figsize)
def simple_plotly(net,
respect_switches=True,
use_line_geodata=None,
on_map=False,
projection=None,
map_style='basic',
figsize=1,
aspectratio='auto',
line_width=1,
bus_size=10,
ext_grid_size=20.0,
bus_color="blue",
line_color='grey',
trafo_color='green',
ext_grid_color="yellow"):
"""
Plots a pandapower network as simple as possible in plotly.
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)
**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.
**ext_grid_size** (float, 20.0) - size of ext_grids to plot.
See bus sizes for details. Note: ext_grids are plotted as rectangles
**bus_color** (String, "blue") - Bus Color. Init as first value of color palette.
**line_color** (String, 'grey') - Line Color. Init is grey
**trafo_color** (String, 'green') - Trafo Color. Init is green
**ext_grid_color** (String, 'yellow') - External Grid Color. Init is yellow
OUTPUT:
**figure** (graph_objs._figure.Figure) figure object
"""
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.bus_geodata) == 0:
logger.warning(
"No or insufficient geodata available --> Creating artificial coordinates."
+ " This may take some time...")
create_generic_coordinates(net,
respect_separation_points=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)
# ----- Buses ------
# initializating bus trace
hoverinfo = get_hoverinfo(net, element="bus")
bus_trace = create_bus_trace(net,
net.bus.index,
size=bus_size,
color=bus_color,
infofunc=hoverinfo)
# ----- Lines ------
# 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
hoverinfo = get_hoverinfo(net, element="line")
line_traces = create_line_trace(net,
net.line.index,
respect_switches=respect_switches,
color=line_color,
width=line_width,
use_line_geodata=use_line_geodata,
infofunc=hoverinfo)
# ----- Trafos ------
hoverinfo = get_hoverinfo(net, element="trafo")
trafo_trace = create_trafo_trace(net,
color=trafo_color,
width=line_width * 5,
infofunc=hoverinfo,
use_line_geodata=use_line_geodata)
# ----- Ext grid ------
# get external grid from create_bus_trace
marker_type = 'circle' if on_map else 'square' # workaround because doesn't appear on mapbox if square
hoverinfo = get_hoverinfo(net, element="ext_grid")
ext_grid_trace = create_bus_trace(net,
buses=net.ext_grid.bus,
color=ext_grid_color,
size=ext_grid_size,
patch_type=marker_type,
trace_name='external_grid',
infofunc=hoverinfo)
return draw_traces(line_traces + trafo_trace + ext_grid_trace + bus_trace,
aspectratio=aspectratio,
figsize=figsize,
on_map=on_map,
map_style=map_style)
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 _simple_plotly_generic(net,
respect_separators,
use_branch_geodata,
on_map,
projection,
map_style,
figsize,
aspectratio,
branch_width,
node_size,
ext_grid_size,
node_color,
branch_color,
trafo_color,
trafo3w_color,
ext_grid_color,
node_element,
branch_element,
trans_element,
trans3w_element,
separator_element,
branch_trace_func,
node_trace_func,
hoverinfo_func,
filename='temp-plot.html',
auto_open=True):
version_check()
# create geocoord if none are available
branch_geodata = branch_element + "_geodata"
node_geodata = node_element + "_geodata"
if branch_geodata not in net:
net[branch_geodata] = pd.DataFrame(columns=['coords'])
if node_geodata not in net:
net[node_geodata] = pd.DataFrame(columns=["x", "y"])
if len(net[node_geodata]) == 0:
logger.warning(
"No or insufficient geodata available --> Creating artificial coordinates."
+ " This may take some time...")
create_generic_coordinates(net, respect_switches=respect_separators)
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)
# ----- Nodes (Buses) ------
# initializating node trace
hoverinfo = hoverinfo_func(net, element=node_element)
node_trace = node_trace_func(net,
net[node_element].index,
size=node_size,
color=node_color,
infofunc=hoverinfo)
# ----- branches (Lines) ------
# if node geodata is available, but no branch geodata
if use_branch_geodata is None:
use_branch_geodata = False if len(net[branch_geodata]) == 0 else True
elif use_branch_geodata and len(net[branch_geodata]) == 0:
logger.warning(
"No or insufficient line geodata available --> only bus geodata will be used."
)
use_branch_geodata = False
hoverinfo = hoverinfo_func(net, element=branch_element)
branch_traces = branch_trace_func(net,
net[branch_element].index,
use_branch_geodata,
respect_separators,
color=branch_color,
width=branch_width,
infofunc=hoverinfo)
trans_trace = []
# ----- Trafos ------
if 'trafo' in net:
hoverinfo = hoverinfo_func(net, element=trans_element)
trans_trace += create_trafo_trace(net,
color=trafo_color,
width=branch_width * 5,
infofunc=hoverinfo,
use_line_geodata=use_branch_geodata)
# ----- 3W Trafos ------
if 'trafo3w' in net:
hoverinfo = hoverinfo_func(net, element=trans3w_element)
trans_trace += create_trafo_trace(net,
color=trafo3w_color,
trafotype='3W',
width=branch_width * 5,
trace_name='3w_trafos',
infofunc=hoverinfo,
use_line_geodata=use_branch_geodata)
# ----- Ext grid ------
# get external grid from _create_node_trace
marker_type = 'circle' if on_map else 'square' # workaround because doesn't appear on mapbox if square
hoverinfo = hoverinfo_func(net, element="ext_grid")
ext_grid_trace = _create_node_trace(net,
nodes=net.ext_grid[node_element],
size=ext_grid_size,
patch_type=marker_type,
color=ext_grid_color,
infofunc=hoverinfo,
trace_name='external_grid',
node_element=node_element,
branch_element=branch_element)
return draw_traces(branch_traces + trans_trace + ext_grid_trace +
node_trace,
aspectratio=aspectratio,
figsize=figsize,
on_map=on_map,
map_style=map_style,
filename=filename,
auto_open=auto_open)
def test_create_generic_coordinates_nx():
net = create_test_network()
net.bus_geodata.drop(net.bus_geodata.index, inplace=True)
create_generic_coordinates(net, library="networkx")
assert len(net.bus_geodata) == len(net.bus)
def test_create_generic_coordinates_igraph(net_in):
net = copy.deepcopy(net_in)
net.bus_geodata.drop(net.bus_geodata.index, inplace=True)
create_generic_coordinates(net, library="igraph")
assert len(net.bus_geodata) == len(net.bus)
def _draw_colored_bus_groups_plotly(
net, bus_groups, respect_switches=True, use_line_geodata=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):
"""
Internal function of vlevel_plotly()
**bus_groups** - list of tuples consisting of set of bus indices, color, legendgroup
"""
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
# creating traces for buses and lines for each voltage level
bus_traces = []
line_traces = []
traced_lines = set()
for bus_group_legend in bus_groups:
buses_vl, vlev_color, legend_group = bus_group_legend
bus_trace_vlev = create_bus_trace(
net, buses=buses_vl, size=bus_size, legendgroup=legend_group, color=vlev_color,
trace_name=f'buses {legend_group}')
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()
traced_lines |= set(vlev_lines)
line_trace_vlev = create_line_trace(
net, lines=vlev_lines, use_line_geodata=use_line_geodata,
respect_switches=respect_switches, legendgroup=legend_group, color=vlev_color,
width=line_width, trace_name=f'lines {legend_group}')
if line_trace_vlev is not None:
line_traces += line_trace_vlev
# creating traces for other lines
line_trace_other = create_line_trace(
net, lines=net.line.index.difference(traced_lines).tolist(),
use_line_geodata=use_line_geodata, respect_switches=respect_switches,
color="grey", width=line_width)
if line_trace_vlev is not None:
line_traces += line_trace_other
trafo_traces = create_trafo_trace(net, color='gray', width=line_width * 2)
return draw_traces(line_traces + trafo_traces + bus_traces, showlegend=True,
aspectratio=aspectratio, on_map=on_map, map_style=map_style, figsize=figsize,
filename=filename, auto_open=auto_open)
def simple_plot(net=None,
respect_switches=False,
line_width=1.0,
bus_size=1.0,
ext_grid_size=1.0,
bus_color=colors[0],
line_color='grey',
trafo_color='g',
ext_grid_color='y'):
"""
Plots a pandapower network as simple as possible. 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, False) - Respect switches when artificial geodata is created
**line_width** (float, 1.0) - width of lines
**bus_size** (float, 1.0) - Relative size of buses to plot.
The value bus_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)
**ext_grid_size** (float, 1.0) - Relative size of ext_grids to plot.
See bus sizes for details. Note: ext_grids are plottet as rectangles
**bus_color** (String, colors[0]) - Bus Color. Init as first value of color palette. Usually colors[0] = "b".
**line_color** (String, 'grey') - Line Color. Init is grey
**trafo_color** (String, 'g') - Trafo Color. Init is green
**ext_grid_color** (String, 'y') - External Grid Color. Init is yellow
"""
if net is None:
import pandapower.networks as nw
logger.warning(
"No pandapower network provided -> Plotting mv_oberrhein")
net = nw.mv_oberrhein()
# create geocoord if none are available
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 bus_size or ext_grid_size is None:
# if either bus_size or ext_grid size is None -> calc size from distance between min and
# max geocoord
mean_distance_between_buses = sum(
(net['bus_geodata'].max() - net['bus_geodata'].min()) / 200)
# set the bus / ext_grid sizes accordingly
# Comment: This is implemented because if you would choose a fixed values
# (e.g. bus_size = 0.2), the size
# could be to small for large networks and vice versa
bus_size *= mean_distance_between_buses
ext_grid_size *= mean_distance_between_buses * 1.5
# if bus geodata is available, but no line geodata
use_line_geodata = False if len(net.line_geodata) == 0 else True
# create bus collections ti plot
bc = create_bus_collection(net,
net.bus.index,
size=bus_size,
color=bus_color,
zorder=10)
lc = create_line_collection(net,
net.line.index,
color=line_color,
linewidths=line_width,
use_line_geodata=use_line_geodata)
collections = [bc, lc]
eg_buses_with_geocoordinates = set(net.ext_grid.bus.values) & set(
net.bus_geodata.index)
if len(eg_buses_with_geocoordinates) > 0:
sc = create_bus_collection(net,
eg_buses_with_geocoordinates,
patch_type="rect",
size=ext_grid_size,
color=ext_grid_color,
zorder=11)
collections.append(sc)
# create trafo collection if trafo is available
trafo_buses_with_geocoordinates = [t for t, trafo in net.trafo.iterrows() \
if trafo.hv_bus in net.bus_geodata.index \
and trafo.lv_bus in net.bus_geodata.index]
if len(trafo_buses_with_geocoordinates) > 0:
tc = create_trafo_collection(net,
trafo_buses_with_geocoordinates,
color=trafo_color)
collections.append(tc)
draw_collections(collections)
plt.show()