Add plotly plotting functionality

.travis.yml

@@ -5,6 +5,7 @@ python:
 install:
   - pip install coveralls pytest-cov==2.6 pytest==3.2.3 Biopython bcbio-gff
   - pip install bokeh pandas
+  - pip install plotly
   - pip install -e .
 # command to run tests
 script:

README.rst

@@ -46,6 +46,12 @@ If you intend to use the bokeh features, you need to also install Bokeh and Pand
 
     (sudo) pip install bokeh pandas
 
+If you intend to use the plotly features, you need to also install Plotly and Pandas:
+
+.. code:: python
+
+    (sudo) pip install plotly pandas
+
 To parse GFF files, install the ``bcbio-gff`` library:
 
 .. code::

dna_features_viewer/GraphicRecord/GraphicRecord.py

@@ -15,9 +15,10 @@
 
 from .MatplotlibPlottableMixin import MatplotlibPlottableMixin
 from .BokehPlottableMixin import BokehPlottableMixin
+from .PlotlyPlottableMixin import PlotlyPlottableMixin
 
 
-class GraphicRecord(MatplotlibPlottableMixin, BokehPlottableMixin):
+class GraphicRecord(MatplotlibPlottableMixin, BokehPlottableMixin, PlotlyPlottableMixin):
     """Set of Genetic Features of a same DNA sequence, to be plotted together.
 
     Parameters

dna_features_viewer/GraphicRecord/PlotlyPlottableMixin.py

@@ -0,0 +1,182 @@
+try:
+    import plotly.graph_objects as go
+
+    PLOTLY_AVAILABLE = True
+except ImportError:
+    PLOTLY_AVAILABLE = False
+
+try:
+    import pandas as pd
+
+    PANDAS_AVAILABLE = True
+except ImportError:
+    PANDAS_AVAILABLE = False
+
+import matplotlib.pyplot as plt
+
+
+class PlotlyPlottableMixin:
+    def plotly_feature_patch(
+            self,
+            start,
+            end,
+            strand,
+            figure_width=5,
+            width=0.4,
+            level=0,
+            arrow_width_inches=0.05,
+            **kwargs
+    ):
+        """Return a dict with points coordinates of a plotly shape. Same as bokeh feature arrow
+
+        Parameters
+        ----------
+
+        start, end, strand
+
+        """
+        hw = width / 2.0
+        x1, x2 = (start, end) if (strand >= 0) else (end, start)
+        bp_per_width = figure_width / self.sequence_length
+        delta = arrow_width_inches / bp_per_width
+        if strand >= 0:
+            head_base = max(x1, x2 - delta)
+        else:
+            head_base = min(x1, x2 + delta)
+        result = dict(
+            xs=[x1, x1, head_base, x2, head_base, x1],
+            ys=[e + level for e in [-hw, hw, hw, 0, -hw, -hw]],
+        )
+        result.update(kwargs)
+        return result
+
+    def plot_with_plotly(self, figure_width=5, figure_height="auto", tools="auto"):
+        """Plot the graphic record using Plotly.
+        The returned fig object can be used in a Dash dashboard.
+
+        Examples
+        --------
+
+        >>>
+
+
+        """
+        if not PLOTLY_AVAILABLE:
+            raise ImportError("``plot_with_plotly`` requires plotly installed.")
+        if not PANDAS_AVAILABLE:
+            raise ImportError("``plot_with_plotly`` requires plotly installed.")
+
+        # Set up default tools
+        # if tools == "auto":
+        #     tools = [HoverTool(tooltips="@hover_html"), "xpan,xwheel_zoom,reset,tap"]
+
+        # FIRST PLOT WITH MATPLOTLIB AND GATHER INFOS ON THE PLOT
+        ax, (features_levels, plot_data) = self.plot(figure_width=figure_width)
+        width, height = [int(100 * e) for e in ax.figure.get_size_inches()]
+        plt.close(ax.figure)
+        if figure_height == "auto":
+            height = int(0.5 * height)
+        else:
+            height = 100 * figure_height
+        height = max(height, 185) # Minimal height to see all icons
+
+        max_y = max(
+            [data["annotation_y"] for f, data in plot_data.items()]
+            + list(features_levels.values())
+        )
+
+        fig = go.Figure()
+
+        # Update plot width and height
+        fig.update_layout(
+            autosize=False,
+            width=width,
+            height=height,
+            margin=dict(l=0, r=20, t=0, b=20)
+        )
+
+        # Update axes properties
+        fig.update_xaxes(
+            range=[0, self.sequence_length],
+            zeroline=False,
+        )
+
+        fig.update_yaxes(
+            range=[-1, max_y + 1],
+            zeroline=False,
+            showline=False,
+            showgrid=False,
+            visible=False,
+        )
+
+        # Add patches
+        for feature, level in features_levels.items():
+            patch = self.plotly_feature_patch(
+                feature.start,
+                feature.end,
+                feature.strand,
+                figure_width=figure_width,
+                level=level,
+                color=feature.color,
+                label=feature.label,
+                hover_html=(
+                    feature.html
+                    if feature.html is not None
+                    else feature.label
+                ),
+            )
+            fig.add_trace(
+                go.Scatter(
+                    x=patch["xs"],
+                    y=patch["ys"],
+                    fill="toself",
+                    mode="lines",
+                    name="",
+                    text=patch["label"],
+                    line_color="#000000",
+                    fillcolor=patch["color"],
+                )
+            )
+
+        if plot_data != {}:
+
+            text_df = pd.DataFrame.from_records(
+                [
+                    dict(
+                        x=feature.x_center,
+                        y=pdata["annotation_y"],
+                        text=feature.label,
+                        color=feature.color,
+                    )
+                    for feature, pdata in plot_data.items()
+                ]
+            )
+
+            # Scatter trace of text labels
+            fig.add_trace(go.Scatter(
+                x=text_df["x"],
+                y=text_df["y"],
+                text=text_df["text"],
+                mode="text",
+                hoverinfo="skip",
+                textfont=dict(size=12, family="arial"),
+                textposition="middle center",
+            ))
+
+            # Add segments
+            for feature, pdata in plot_data.items():
+                fig.add_shape(
+                    type="line",
+                    x0=feature.x_center,
+                    y0=pdata["annotation_y"],
+                    x1=feature.x_center,
+                    y1=pdata["feature_y"],
+                    line=dict(color="#000000", width=0.5)
+                )
+
+        fig.update_layout(
+            template="simple_white",
+            showlegend=False,
+        )
+
+        return fig