@@ -106,7 +106,8 @@ if plotly_available:

         "x": 4,

         "*": 17,

         "d": 2,

-        "h": 14

+        "h": 14,

+        "no symbol": -1

     }

     converter_map_3d = {

@@ -981,7 +981,7 @@ def _plot_plotly(sys, num_lead_cells, unit,

          lead_site_edgecolor, lead_site_lw,

          lead_hop_lw, pos_transform,

          cmap, colorbar, file,

-         show):

+         show, fig=None):

     if not _p.plotly_available:

         raise RuntimeError("plotly was not found, but is required "

@@ -1111,6 +1111,9 @@ def _plot_plotly(sys, num_lead_cells, unit,

     assert dim == 2 or dim == 3

     site_node_trace, site_edge_trace = [], []

     for symbol, slc in symbol_slcs:

+        site_symbol_plotly = _p.convert_symbol_mpl_plotly(symbol)

+        if site_symbol_plotly == -1:

+            continue

         size = site_size[slc] if _p.isarray(site_size) else site_size

         col = site_color[slc] if _p.isarray(site_color) else site_color

         if _p.isarray(site_edgecolor) or _p.isarray(site_lw):

@@ -1144,7 +1147,7 @@ def _plot_plotly(sys, num_lead_cells, unit,

                                                                         symbol)

         site_node_trace_elem.mode = 'markers'

-        site_node_trace_elem.hoverinfo = 'text'

+        site_node_trace_elem.hoverinfo = 'none'

         site_node_trace_elem.marker.showscale = False

         site_node_trace_elem.marker.colorscale = \

                                           _p.convert_cmap_list_mpl_plotly(cmap)

@@ -1158,6 +1161,7 @@ def _plot_plotly(sys, num_lead_cells, unit,

         site_node_trace_elem.line.width = lw

         site_node_trace_elem.line.color = edgecol

+        site_node_trace_elem.showlegend = False

         site_node_trace.append(site_node_trace_elem)

@@ -1189,6 +1193,7 @@ def _plot_plotly(sys, num_lead_cells, unit,

     site_edge_trace_elem.line.width = hop_lw

     site_edge_trace_elem.line.color = hop_color

     site_edge_trace_elem.hoverinfo = 'none'

+    site_edge_trace_elem.showlegend = False

     site_edge_trace_elem.mode = 'lines'

     site_edge_trace.append(site_edge_trace_elem)

@@ -1218,7 +1223,8 @@ def _plot_plotly(sys, num_lead_cells, unit,

                                  _p.convert_symbol_mpl_plotly(lead_site_symbol)

         lead_node_trace_elem.mode = 'markers'

-        lead_node_trace_elem.hoverinfo = 'text'

+        lead_node_trace_elem.hoverinfo = 'none'

+        lead_node_trace_elem.showlegend = False

         lead_node_trace_elem.marker.showscale = False

         lead_node_trace_elem.marker.reversescale = False

         lead_node_trace_elem.marker.color = lead_site_colors

@@ -1238,7 +1244,8 @@ def _plot_plotly(sys, num_lead_cells, unit,

         lead_node_trace_elem.line.width = lead_site_lw

         lead_node_trace_elem.line.color = lead_site_edgecolor

-        lead_node_trace.append(lead_node_trace_elem)

+        if lead_node_trace_elem:

+            lead_node_trace.append(lead_node_trace_elem)

         lead_hop_colors = np.array([i[2] for i in hops[hops_slc]], dtype=float)

@@ -1267,6 +1274,7 @@ def _plot_plotly(sys, num_lead_cells, unit,

                                                         lead_color)

         lead_edge_trace_elem.hoverinfo = 'none'

         lead_edge_trace_elem.mode = 'lines'

+        lead_edge_trace_elem.showlegend = False

         lead_edge_trace.append(lead_edge_trace_elem)

@@ -1277,11 +1285,17 @@ def _plot_plotly(sys, num_lead_cells, unit,

                                            showticklabels=True),

                                 yaxis=dict(showgrid=False, zeroline=False,

                                            showticklabels=True))

-    full_trace = list(itertools.chain.from_iterable([site_edge_trace,

-                                        site_node_trace, lead_edge_trace,

-                                        lead_node_trace]))

-    fig = _p.plotly_graph_objs.Figure(data=full_trace,

-                                      layout=layout)

+    if fig == None:

+        full_trace = list(itertools.chain.from_iterable([site_edge_trace,

+                                            site_node_trace, lead_edge_trace,

+                                            lead_node_trace]))

+        fig = _p.plotly_graph_objs.Figure(data=full_trace,

+                                          layout=layout)

+    else:

+        full_trace = list(itertools.chain.from_iterable([lead_edge_trace,

+                                            lead_node_trace]))

+        for trace in full_trace:

+            fig.add_trace(trace)

     return fig

@@ -1610,7 +1624,14 @@ def mask_interpolate(coords, values, a=None, method='nearest', oversampling=3):

     # * 0.4 (which is just below sqrt(2) - 1) makes tree.query() exact.

     mask = tree.query(mask, eps=0.4)[0] > 0.99 * a

-    return np.ma.masked_array(img, mask), cmin, cmax

+    masked_result_array = np.ma.masked_array(img, mask)

+

+    if get_backend() != _p.Backends.matplotlib:

+        result_array = masked_result_array.filled(np.NaN)

+    else:

+        result_array = masked_result_array

+

+    return result_array, img, cmin, cmax

 def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,

@@ -1689,7 +1710,7 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,

     kwant.plotter.density

     """

-    if not _p.mpl_available:

+    if not (_p.mpl_available or _p.plotly_available):

         raise RuntimeError("matplotlib was not found, but is required "

                            "for map()")

@@ -1711,18 +1732,8 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,

                              'for finalized systems.')

     value = np.array(value)

     with _common.reraise_warnings():

-        img, min, max = mask_interpolate(coords, value, a, method, oversampling)

-    border = 0.5 * (max - min) / (np.asarray(img.shape) - 1)

-    min -= border

-    max += border

-    if ax is None:

-        fig = _make_figure(dpi, fig_size, use_pyplot=(file is None))

-        ax = fig.add_subplot(1, 1, 1, aspect='equal')

-    else:

-        fig = None

-

-    if cmap is None:

-        cmap = _p.kwant_red_matplotlib

+        img, unmasked_data, _min, _max = mask_interpolate(coords, value,

+                                                       a, method, oversampling)

     # Calculate the min/max bounds for the colormap.

     # User-provided values take precedence.

@@ -1745,9 +1756,96 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,

         warnings.warn(''.join(msg), RuntimeWarning, stacklevel=2)

     vmin, vmax = new_vmin, new_vmax

+    if get_backend() == _p.Backends.matplotlib:

+        fig = _map_matplotlib(syst, img, colorbar, _max, _min,  vmin, vmax,

+                        overflow_pct, underflow_pct, cmap, num_lead_cells,

+                        background, dpi, fig_size, ax, file)

+    elif get_backend() == _p.Backends.plotly:

+        fig = _map_plotly(syst, img, colorbar, _max, _min,  vmin, vmax,

+                          overflow_pct, underflow_pct, cmap, num_lead_cells,

+                          background)

+    else:

+        raise RuntimeError('Backend not supported by map().')

+

+    _maybe_output_fig(fig, file=file, show=show)

+

+    return fig

+

+

+def _map_plotly(syst, img, colorbar, _max, _min,  vmin, vmax, overflow_pct,

+                underflow_pct, cmap, num_lead_cells, background):

+

+    border = 0.5 * (_max - _min) / (np.asarray(img.shape) - 1)

+    _min -= border

+    _max += border

+

+    if cmap is None:

+        cmap = _p._colormaps.kwant_red

+

+    # Note that we tell imshow to show the array created by mask_interpolate

+    # faithfully and not to interpolate by itself another time.

+    # image = ax.imshow(img.T, extent=(_min[0], _max[0], _min[1], _max[1]),

+    #                   origin='lower', interpolation='none', cmap=cmap,

+    #                   vmin=vmin, vmax=vmax)

+    if not _p.plotly_available:

+        raise RuntimeError("plotly was not found, but is required "

+                           "for _map_plotly()")

+

+    if cmap is None:

+        cmap = _p.kwant_red_plotly

+

+    img = img.T

+    contour_object = _p.plotly_graph_objs.Heatmap()

+    contour_object.z = img

+    contour_object.x = np.linspace(_min[0],_max[0],img.shape[0])

+    contour_object.y = np.linspace(_min[1],_max[1],img.shape[1])

+    contour_object.zsmooth = False

+    contour_object.connectgaps = False

+    contour_object.colorscale = _p.convert_cmap_list_mpl_plotly(cmap)

+    contour_object.zmax = vmax

+    contour_object.zmin = vmin

+    contour_object.showlegend = False

+    contour_object.hoverinfo = 'none'

+

+    contour_object.showscale = colorbar

+

+    fig = _p.plotly_graph_objs.Figure(data=[contour_object])

+    fig.layout.plot_bgcolor = background

+    # fig.layout.width = 720

+    # fig.layout.height = fig.layout.width

+

+    if num_lead_cells:

+        fig = _plot_plotly(syst, num_lead_cells, site_symbol='no symbol',

+                           hop_lw=0, lead_site_symbol='s',

+                           lead_site_size=0.501, lead_site_lw=0,lead_hop_lw=0,

+                           lead_color='black', colorbar=False, show=False,

+                           fig=fig, unit='pt', site_size=None, site_color=None,

+                           site_edgecolor=None, site_lw=0, hop_color=None,

+                           lead_site_edgecolor=None,pos_transform=None,

+                           cmap=None, file=None)

+

+    return fig

+

+

+def _map_matplotlib(syst, img, colorbar, _max, _min,  vmin, vmax,

+                    overflow_pct, underflow_pct, cmap, num_lead_cells,

+                    background, dpi, fig_size, ax, file):

+

+    border = 0.5 * (_max - _min) / (np.asarray(img.shape) - 1)

+    _min -= border

+    _max += border

+    if ax is None:

+        fig = _make_figure(dpi, fig_size, use_pyplot=(file is None))

+        ax = fig.add_subplot(1, 1, 1, aspect='equal')

+    else:

+        fig = None

+

+    if cmap is None:

+        cmap = _p._colormaps.kwant_red

+

     # Note that we tell imshow to show the array created by mask_interpolate

     # faithfully and not to interpolate by itself another time.

-    image = ax.imshow(img.T, extent=(min[0], max[0], min[1], max[1]),

+    image = ax.imshow(img.T, extent=(_min[0], _max[0], _min[1], _max[1]),

                       origin='lower', interpolation='none', cmap=cmap,

                       vmin=vmin, vmax=vmax)

     if num_lead_cells:

@@ -1768,8 +1866,6 @@ def map(sys, value, colorbar=True, cmap=None, vmin=None, vmax=None, a=None,

             extend = 'max'

         fig.colorbar(image, extend=extend)

-    _maybe_output_fig(fig, file=file, show=show)

-

     return fig