Example #1
0
def create_bus_trace(net,
                     buses=None,
                     size=5,
                     patch_type="circle",
                     color="blue",
                     infofunc=None,
                     trace_name='buses',
                     legendgroup=None,
                     cmap=None,
                     cmap_vals=None,
                     cbar_title=None,
                     cmin=None,
                     cmax=None,
                     cpos=1.0,
                     colormap_column="vm_pu"):
    """
    Creates a plotly trace of pandapower buses.

    INPUT:
        **net** (pandapowerNet) - The pandapower network

    OPTIONAL:
        **buses** (list, None) - The buses for which the collections are created.
        If None, all buses in the network are considered.

        **size** (int, 5) - patch size

        **patch_type** (str, "circle") - patch type, can be

                - "circle" for a circle
                - "square" for a rectangle
                - "diamond" for a diamond
                - much more pathc types at https://plot.ly/python/reference/#scatter-marker

        **infofunc** (pd.Series, None) - hoverinfo for bus elements. Indices should correspond to
            the pandapower element indices

        **trace_name** (String, "buses") - name of the trace which will appear in the legend

        **color** (String, "blue") - color of buses in the trace

        **cmap** (String, None) - name of a colormap which exists within plotly
            (Greys, YlGnBu, Greens, YlOrRd, Bluered, RdBu, Reds, Blues, Picnic, Rainbow,
            Portland, Jet, Hot, Blackbody, Earth, Electric, Viridis) alternatively a custom
            discrete colormap can be used

        **cmap_vals** (list, None) - values used for coloring using colormap

        **cbar_title** (String, None) - title for the colorbar

        **cmin** (float, None) - colorbar range minimum

        **cmax** (float, None) - colorbar range maximum

        **cpos** (float, 1.1) - position of the colorbar

        **colormap_column** (str, "vm_pu") - set color of bus according to this variable

    """
    color = get_plotly_color(color)

    bus_trace = dict(type='scatter',
                     text=[],
                     mode='markers',
                     hoverinfo='text',
                     name=trace_name,
                     marker=dict(color=color, size=size, symbol=patch_type))

    buses = net.bus.index.tolist() if buses is None else list(buses)
    bus_plot_index = [
        b for b in buses if b in list(set(buses) & set(net.bus_geodata.index))
    ]

    bus_trace['x'], bus_trace['y'] = (net.bus_geodata.loc[bus_plot_index,
                                                          'x'].tolist(),
                                      net.bus_geodata.loc[bus_plot_index,
                                                          'y'].tolist())

    if not isinstance(infofunc, pd.Series) and isinstance(infofunc, Iterable) and \
            len(infofunc) == len(buses):
        infofunc = pd.Series(index=buses, data=infofunc)

    bus_trace['text'] = net.bus.loc[bus_plot_index, 'name'] if infofunc is None else \
        infofunc.loc[buses]

    if legendgroup:
        bus_trace['legendgroup'] = legendgroup

    # if color map is set
    if cmap is not None:
        # TODO introduce discrete colormaps (see contour plots in plotly)
        # if cmap_vals are not given

        cmap = 'Jet' if cmap is True else cmap

        if cmap_vals is not None:
            cmap_vals = cmap_vals
        else:
            if net.res_line.shape[0] == 0:
                logger.error(
                    "There are no power flow results for buses voltage magnitudes which are default for bus "
                    "colormap coloring..."
                    "set cmap_vals input argument if you want colormap according to some specific values..."
                )
            cmap_vals = net.res_bus.loc[bus_plot_index, colormap_column].values

        cmap_vals = net.res_bus.loc[
            bus_plot_index,
            colormap_column] if cmap_vals is None else cmap_vals

        cmin = cmap_vals.min() if cmin is None else cmin
        cmax = cmap_vals.max() if cmax is None else cmax

        bus_trace['marker'] = Marker(size=size,
                                     color=cmap_vals,
                                     cmin=cmin,
                                     cmax=cmax,
                                     colorscale=cmap,
                                     colorbar=ColorBar(thickness=10, x=cpos),
                                     symbol=patch_type)

        if cbar_title:
            bus_trace['marker']['colorbar']['title'] = cbar_title

        bus_trace['marker']['colorbar']['title']['side'] = 'right'

    return [bus_trace]
Example #2
0
def create_line_trace(net,
                      lines=None,
                      use_line_geodata=True,
                      respect_switches=False,
                      width=1.0,
                      color='grey',
                      infofunc=None,
                      trace_name='lines',
                      legendgroup=None,
                      cmap=None,
                      cbar_title=None,
                      show_colorbar=True,
                      cmap_vals=None,
                      cmin=None,
                      cmax=None,
                      cpos=1.1):
    """
    Creates a plotly trace of pandapower lines.

    INPUT:
        **net** (pandapowerNet) - The pandapower network

    OPTIONAL:
        **lines** (list, None) - The lines for which the collections are created.
        If None, all lines in the network are considered.

        **width** (int, 1) - line width

        **respect_switches** (bool, False) - flag for consideration of disconnected lines

        **infofunc** (pd.Series, None) - hoverinfo for line elements. Indices should correspond to
            the pandapower element indices

        **trace_name** (String, "lines") - name of the trace which will appear in the legend

        **color** (String, "grey") - color of lines in the trace

        **legendgroup** (String, None) - defines groups of layers that will be displayed in a legend
        e.g. groups according to voltage level (as used in `vlevel_plotly`)

        **cmap** (String, None) - name of a colormap which exists within plotly if set to True default `Jet`
        colormap is used, alternative colormaps : Greys, YlGnBu, Greens, YlOrRd,
        Bluered, RdBu, Reds, Blues, Picnic, Rainbow, Portland, Jet, Hot, Blackbody, Earth, Electric, Viridis

        **cmap_vals** (list, None) - values used for coloring using colormap

        **show_colorbar** (bool, False) - flag for showing or not corresponding colorbar

        **cbar_title** (String, None) - title for the colorbar

        **cmin** (float, None) - colorbar range minimum

        **cmax** (float, None) - colorbar range maximum

        **cpos** (float, 1.1) - position of the colorbar

        """

    color = get_plotly_color(color)

    # defining lines to be plot
    lines = net.line.index.tolist() if lines is None else list(lines)
    if len(lines) == 0:
        return []

    if infofunc is not None:
        if not isinstance(infofunc, pd.Series) and isinstance(infofunc, Iterable) and \
                len(infofunc) == len(lines):
            infofunc = pd.Series(index=lines, data=infofunc)
        if len(infofunc) != len(lines) and len(infofunc) != len(net.line):
            raise UserWarning(
                "Different amount of hover info than lines to plot")
        assert isinstance(infofunc, pd.Series), \
            "infofunc should be a pandas series with the net.line.index to the infofunc contents"

    no_go_lines = set()
    if respect_switches:
        no_go_lines = set(lines) & set(net.switch.element[
            (net.switch.et == "l") & (net.switch.closed == 0)])

    lines_to_plot = net.line.loc[set(net.line.index)
                                 & (set(lines) - no_go_lines)]
    no_go_lines_to_plot = None
    use_line_geodata = use_line_geodata if net.line_geodata.shape[
        0] > 0 else False

    if use_line_geodata:
        lines_to_plot = lines_to_plot.loc[set(lines_to_plot.index)
                                          & set(net.line_geodata.index)]
    else:
        lines_with_geodata = lines_to_plot.from_bus.isin(net.bus_geodata.index) & \
                             lines_to_plot.to_bus.isin(net.bus_geodata.index)
        lines_to_plot = lines_to_plot.loc[lines_with_geodata]

    cmap_lines = None
    if cmap is not None:
        # workaround: if colormap plot is used, each line need to be separate scatter object because
        # plotly still doesn't support appropriately colormap for line objects
        # TODO correct this when plotly solves existing github issue about Line colorbar

        cmap = 'jet' if cmap is True else cmap

        if cmap_vals is not None:
            if not isinstance(cmap_vals, np.ndarray):
                cmap_vals = np.asarray(cmap_vals)
        else:
            if net.res_line.shape[0] == 0:
                logger.error(
                    "There are no power flow results for lines which are default for line colormap coloring..."
                    "set cmap_vals input argument if you want colormap according to some specific values..."
                )
            cmap_vals = net.res_line.loc[lines_to_plot.index,
                                         'loading_percent'].values

        cmap_lines = get_plotly_cmap(cmap_vals,
                                     cmap_name=cmap,
                                     cmin=cmin,
                                     cmax=cmax)
        if len(cmap_lines) == len(net.line):
            # some lines are not plotted although cmap_value were provided for all lines
            line_idx_map = dict(
                zip(net.line.loc[lines].index.tolist(), range(len(lines))))
            cmap_lines = [
                cmap_lines[line_idx_map[idx]] for idx in lines_to_plot.index
            ]
        else:
            assert len(cmap_lines) == len(lines_to_plot), \
                "Different amounts of cmap values and lines to plot were supplied"

    line_traces = []
    for col_i, (idx, line) in enumerate(lines_to_plot.iterrows()):
        line_color = color
        line_info = line['name']
        if cmap is not None:
            try:
                line_color = cmap_lines[col_i]
                line_info = line['name'] if infofunc is None else infofunc.loc[
                    idx]
            except IndexError:
                logger.warning(
                    "No color and info for line {:d} (name: {}) available".
                    format(idx, line['name']))

        line_trace = dict(type='scatter',
                          text=[],
                          hoverinfo='text',
                          mode='lines',
                          name=trace_name,
                          line=Line(width=width, color=color))

        line_trace['x'], line_trace['y'] = _get_line_geodata_plotly(
            net, lines_to_plot.loc[idx:idx], use_line_geodata)

        line_trace['line']['color'] = line_color

        line_trace['text'] = line_info

        line_traces.append(line_trace)

    if show_colorbar and cmap is not None:

        cmin = cmap_vals.min() if cmin is None else cmin
        cmax = cmap_vals.max() if cmax is None else cmax
        try:
            # TODO for custom colormaps
            cbar_cmap_name = 'Jet' if cmap == 'jet' else cmap
            # workaround to get colorbar for lines (an unvisible node is added)
            # get x and y of first line.from_bus:
            x = [net.bus_geodata.x[net.line.from_bus[net.line.index[0]]]]
            y = [net.bus_geodata.y[net.line.from_bus[net.line.index[0]]]]
            lines_cbar = dict(type='scatter',
                              x=x,
                              y=y,
                              mode='markers',
                              marker=Marker(
                                  size=0,
                                  cmin=cmin,
                                  cmax=cmax,
                                  color='rgb(255,255,255)',
                                  opacity=0,
                                  colorscale=cbar_cmap_name,
                                  colorbar=ColorBar(thickness=10, x=cpos),
                              ))
            if cbar_title:
                lines_cbar['marker']['colorbar']['title'] = cbar_title

            lines_cbar['marker']['colorbar']['title']['side'] = 'right'

            line_traces.append(lines_cbar)
        except:
            pass

    if len(no_go_lines) > 0:
        no_go_lines_to_plot = net.line.loc[no_go_lines]
        for idx, line in no_go_lines_to_plot.iterrows():
            line_color = color
            line_trace = dict(type='scatter',
                              text=[],
                              hoverinfo='text',
                              mode='lines',
                              name='disconnected lines',
                              line=Line(width=width / 2,
                                        color='grey',
                                        dash='dot'))

            line_trace['x'], line_trace['y'] = _get_line_geodata_plotly(
                net, no_go_lines_to_plot.loc[idx:idx], use_line_geodata)

            line_trace['line']['color'] = line_color
            try:
                line_trace['text'] = infofunc.loc[idx]
            except (KeyError, IndexError, AttributeError):
                line_trace["text"] = line['name']

            line_traces.append(line_trace)

            if legendgroup:
                line_trace['legendgroup'] = legendgroup

    # sort infofunc so that it is the correct order lines_to_plot + no_go_lines_to_plot
    if infofunc is not None:
        if not isinstance(infofunc, pd.Series) and isinstance(infofunc, Iterable) and \
                len(infofunc) == len(net.line):
            infofunc = pd.Series(index=net.line.index, data=infofunc)
        assert isinstance(infofunc, pd.Series), \
            "infofunc should be a pandas series with the net.line.index to the infofunc contents"
        sorted_idx = lines_to_plot.index.tolist()
        if no_go_lines_to_plot is not None:
            sorted_idx += no_go_lines_to_plot.index.tolist()
        infofunc = infofunc.loc[sorted_idx]

    center_trace = create_edge_center_trace(line_traces,
                                            color=color,
                                            infofunc=infofunc,
                                            use_line_geodata=use_line_geodata)
    line_traces.append(center_trace)
    return line_traces
Example #3
0
def _create_branch_trace(net,
                         branches=None,
                         use_branch_geodata=True,
                         respect_separators=False,
                         width=1.0,
                         color='grey',
                         infofunc=None,
                         trace_name='lines',
                         legendgroup=None,
                         cmap=None,
                         cbar_title=None,
                         show_colorbar=True,
                         cmap_vals=None,
                         cmin=None,
                         cmax=None,
                         cpos=1.1,
                         branch_element='line',
                         separator_element='switch',
                         node_element='bus',
                         cmap_vals_category='loading_percent'):
    """
   Creates a plotly trace of branch elements. The rather generic, non-power net specific names
   were introduced to make it usable in other packages, e.g. for pipe networks.

   INPUT:
       **net** (pandapowerNet) - The  network

   OPTIONAL:
       **branches** (list, None) - The branches for which the collections are created.
                                   If None, all branches in the network are considered.

       **use_branch_geodata** (bool, True) - whether the geodata of the branch tables should be used

       **respect_separators** (bool, True) - whether separating elements like switches should be
                                             considered

       **width** (int, 1) - branch width

       **color** (String, "grey") - color of lines in the trace

       **infofunc** (pd.Series, None) - hoverinfo for line elements. Indices should correspond to
           the pandapower element indices

       **trace_name** (String, "lines") - name of the trace which will appear in the legend

       **legendgroup** (String, None) - defines groups of layers that will be displayed in a legend
       e.g. groups according to voltage level (as used in `vlevel_plotly`)

       **cmap** (String, None) - name of a colormap which exists within plotly if set to True default `Jet`
       colormap is used, alternative colormaps : Greys, YlGnBu, Greens, YlOrRd,
       Bluered, RdBu, Reds, Blues, Picnic, Rainbow, Portland, Jet, Hot, Blackbody, Earth, Electric, Viridis

       **cmap_vals** (list, None) - values used for coloring using colormap

       **show_colorbar** (bool, False) - flag for showing or not corresponding colorbar

       **cbar_title** (String, None) - title for the colorbar

       **cmin** (float, None) - colorbar range minimum

       **cmax** (float, None) - colorbar range maximum

       **cpos** (float, 1.1) - position of the colorbar

       **branch_element** (str, "line") - name of the branch element in the net. In a pandapower
                                          net, this is alwas "line"

       **separator_element** (str, "switch") - name of the separator element in the net. In a
                                               pandapower net, this is alwas "switch"

      **node_element** (str, "bus") - name of the node element in the net. In a pandapower net,
                                      this is alwas "bus" (net.bus)

       """

    color = get_plotly_color(color)

    # defining branches (lines) to be plot
    branches = net[branch_element].index.tolist(
    ) if branches is None else list(branches)
    if len(branches) == 0:
        return []

    if infofunc is not None:
        if not isinstance(infofunc, pd.Series) and isinstance(infofunc, Iterable) and \
                len(infofunc) == len(branches):
            infofunc = pd.Series(index=branches, data=infofunc)
        if len(infofunc) != len(branches) and len(infofunc) != len(
                net[branch_element]):
            raise UserWarning("Different amount of hover info than {}s to "
                              "plot".format(branch_element))
        assert isinstance(infofunc, pd.Series), \
            "infofunc should be a pandas series with the net.{}.index to the infofunc " \
            "contents".format(branch_element)
    no_go_branches = set()
    if respect_separators:
        if separator_element == "switch":
            no_go_branches = set(branches) & \
                             set(net[separator_element].element[(net[separator_element].et == "l") &
                                                             (net[separator_element].closed == 0)])
        elif separator_element == "valve":
            no_go_branches = set(branches) & \
                             set(net[separator_element][(~net[separator_element].in_service) |
                                                        (net[separator_element].opened)])
        else:
            raise NotImplementedError(
                "respect separtors is only implements for switches, "
                "not for {}s.".format(separator_element))
    branches_to_plot = net[branch_element].loc[set(net[branch_element].index)
                                               & (set(branches) -
                                                  no_go_branches)]
    no_go_branches_to_plot = None
    branch_geodata = branch_element + "_geodata"
    node_geodata = node_element + "_geodata"
    use_branch_geodata = use_branch_geodata if net[branch_geodata].shape[
        0] > 0 else False
    if use_branch_geodata:
        branches_to_plot = branches_to_plot.loc[
            set(branches_to_plot.index) & set(net[branch_geodata].index)]
    else:
        branches_with_geodata = branches_to_plot['from_'+node_element].isin(
                                                    net[node_geodata].index) & \
                                branches_to_plot['to_'+node_element].isin(net[node_geodata].index)
        branches_to_plot = branches_to_plot.loc[branches_with_geodata]
    cmap_branches = None
    if cmap is not None:
        # workaround: if colormap plot is used, each line need to be separate scatter object because
        # plotly still doesn't support appropriately colormap for line objects
        # TODO correct this when plotly solves existing github issue about Line colorbar

        cmap = 'jet' if cmap is True else cmap

        if cmap_vals is not None:
            if not isinstance(cmap_vals, np.ndarray):
                cmap_vals = np.asarray(cmap_vals)
        else:
            if net['res_' + branch_element].shape[0] == 0:
                logger.error(
                    "There are no simulation results for branches which are default for {}"
                    "colormap coloring..."
                    "set cmap_vals input argument if you want colormap according to some specific "
                    "values...".format(branch_element))
            cmap_vals = net['res_' +
                            branch_element].loc[branches_to_plot.index,
                                                cmap_vals_category].values

        cmap_branches = get_plotly_cmap(cmap_vals,
                                        cmap_name=cmap,
                                        cmin=cmin,
                                        cmax=cmax)
        if len(cmap_branches) == len(net[branch_element]):
            # some branches are not plotted although cmap_value were provided for all branches
            branch_idx_map = dict(
                zip(net[branch_element].loc[branches].index.tolist(),
                    range(len(branches))))
            cmap_branches = [
                cmap_branches[branch_idx_map[idx]]
                for idx in branches_to_plot.index
            ]
        else:
            assert len(cmap_branches) == len(branches_to_plot), \
                "Different amounts of cmap values and branches to plot were supplied"
    branch_traces = []
    for col_i, (idx, branch) in enumerate(branches_to_plot.iterrows()):
        line_color = color
        line_info = branch['name']
        if cmap is not None:
            try:
                line_color = cmap_branches[col_i]
                line_info = branch[
                    'name'] if infofunc is None else infofunc.loc[idx]
            except IndexError:
                logger.warning(
                    "No color and info for {} {:d} (name: {}) available".
                    format(branch_element, idx, branch['name']))

        line_trace = dict(type='scatter',
                          text=[],
                          hoverinfo='text',
                          mode='lines',
                          name=trace_name,
                          line=Line(width=width, color=color))

        line_trace['x'], line_trace['y'] = _get_branch_geodata_plotly(
            net, branches_to_plot.loc[idx:idx], use_branch_geodata,
            branch_element, node_element)

        line_trace['line']['color'] = line_color

        line_trace['text'] = line_info

        branch_traces.append(line_trace)
    if show_colorbar and cmap is not None:

        cmin = cmap_vals.min() if cmin is None else cmin
        cmax = cmap_vals.max() if cmax is None else cmax
        try:
            # TODO for custom colormaps
            cbar_cmap_name = 'Jet' if cmap == 'jet' else cmap
            # workaround to get colorbar for branches (an unvisible node is added)
            # get x and y of first line.from_bus:
            x = [
                net[node_geodata].x[net[branch_element]["from_" + node_element]
                                    [net[branch_element].index[0]]]
            ]
            y = [
                net[node_geodata].y[net[branch_element]["from_" + node_element]
                                    [net[branch_element].index[0]]]
            ]
            branches_cbar = dict(type='scatter',
                                 x=x,
                                 y=y,
                                 mode='markers',
                                 marker=Marker(
                                     size=0,
                                     cmin=cmin,
                                     cmax=cmax,
                                     color='rgb(255,255,255)',
                                     opacity=0,
                                     colorscale=cbar_cmap_name,
                                     colorbar=ColorBar(thickness=10, x=cpos),
                                 ))
            if cbar_title:
                branches_cbar['marker']['colorbar']['title'] = cbar_title

            branches_cbar['marker']['colorbar']['title']['side'] = 'right'

            branch_traces.append(branches_cbar)
        except:
            pass
    if len(no_go_branches) > 0:
        no_go_branches_to_plot = net[branch_element].loc[no_go_branches]
        for idx, branch in no_go_branches_to_plot.iterrows():
            line_color = color
            line_trace = dict(type='scatter',
                              text=[],
                              hoverinfo='text',
                              mode='lines',
                              name='disconnected branches',
                              line=Line(width=width / 2,
                                        color='grey',
                                        dash='dot'))

            line_trace['x'], line_trace['y'] = _get_branch_geodata_plotly(
                net, no_go_branches_to_plot.loc[idx:idx], use_branch_geodata,
                branch_element, node_element)

            line_trace['line']['color'] = line_color
            try:
                line_trace['text'] = infofunc.loc[idx]
            except (KeyError, IndexError, AttributeError):
                line_trace["text"] = branch['name']

            branch_traces.append(line_trace)

            if legendgroup:
                line_trace['legendgroup'] = legendgroup
    # sort infofunc so that it is the correct order lines_to_plot + no_go_lines_to_plot
    if infofunc is not None:
        if not isinstance(infofunc, pd.Series) and isinstance(infofunc, Iterable) and \
                len(infofunc) == len(net[branch_element]):
            infofunc = pd.Series(index=net[branch_element].index,
                                 data=infofunc)
        assert isinstance(infofunc, pd.Series), \
            "infofunc should be a pandas series with the net.{}.index to the infofunc contents" \
            .format(branch_element)
        sorted_idx = branches_to_plot.index.tolist()
        if no_go_branches_to_plot is not None:
            sorted_idx += no_go_branches_to_plot.index.tolist()
        infofunc = infofunc.loc[sorted_idx]
    center_trace = create_edge_center_trace(
        branch_traces,
        color=color,
        infofunc=infofunc,
        use_line_geodata=use_branch_geodata)
    branch_traces.append(center_trace)
    return branch_traces