Python graph_objs.FigureWidget方法代码示例

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def create(self):
        self.createContent()

        if self._data != None:
            self._layout = go.Layout()

            margin = 20
            self._layout["margin"] = dict(l=margin,r=margin,b=margin,t=margin)

            xRange = self.getOpt("xrange")
            if xRange != None:
                self._layout["xaxis"]["range"] = xRange
            yRange = self.getOpt("yrange")
            if yRange != None:
                self._layout["yaxis"]["range"] = yRange

            self._layout["xaxis"]["showticklabels"] = self.getOpt("showticks",True)
            self._layout["xaxis"]["showline"] = False

            self._figure = go.FigureWidget(data=self._data,layout=self._layout)

            children = [self._banner,self._figure]

            if self.getOpt("show_controls",False):
                if self._controls == None:
                    self._controls = ControlPanel(self._datasource) 
                children.append(self._controls)

            self.children = children

        self.draw(None,True) 

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def summary_fig(
    mapper_summary,
    width=600,
    height=500,
    top=60,
    left=20,
    bottom=60,
    right=20,
    bgcolor="rgb(240,240,240)",
):
    """Define a dummy figure that displays info on the algorithms and
       sklearn class instances or methods used

       Returns a FigureWidget object representing the figure
    """
    text = _text_mapper_summary(mapper_summary)

    data = [
        dict(
            type="scatter",
            x=[0, width],
            y=[height, 0],
            mode="text",
            text=[text, ""],
            textposition="bottom right",
            hoverinfo="none",
        )
    ]

    layout = dict(
        title="Algorithms and scikit-learn objects/methods",
        width=width,
        height=height,
        font=dict(size=12),
        xaxis=dict(visible=False),
        yaxis=dict(visible=False, range=[0, height + 5]),
        margin=dict(t=top, b=bottom, l=left, r=right),
        plot_bgcolor=bgcolor,
    )

    return go.FigureWidget(data=data, layout=layout) 

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def createContent(self):
        if self.hasOpt("center"):
            self._map.center = self.getOpt("center")
        if self.hasOpt("zoom"):
            self._map.zoom = self.getOpt("zoom")

        self._lat = self.getOpt("lat")
        if self._lat == None:
            raise Exception("you must specify the lat property")

        self._lon = self.getOpt("lon")
        if self._lon == None:
            raise Exception("you must specify the lon property")

        #if len(self._circles) > 0:
            #for o in self._circles:
                #self._map.add_layer(o["layers"])

        #if len(self._polygons) > 0:
            #for o in self._polygons:
                #self._map.add_layer(o["layers"])

        self._colors = None

        if self.hasOpt("colormap"):
            self._colors = tools.Colors(colormap=self.getOpt("colormap"))
        elif self.hasOpt("colors"):
            self._colors = tools.Colors(colors=self.getOpt("colors"))
        else:
            self._colors = self._visuals._colors

        if self._colors != None:
            if self.hasOpt("color_range"):
                range = self.getOpt("color_range")
                self._colorRange = tools.ColorRange(self._colors,range[0],range[1])

        components = []

        components.append(self._banner)

        colorbar = None

        if self.hasOpt("color"):
            #data = go.Scatter(x=[None],y=[None],marker=dict(colorscale=self._visuals._colors.colorscale,showscale=True,cmin=-5,cmax=5,colorbar=dict(xpad=0,ypad=0,ticks="")))
            data = go.Scatter(x=[None],y=[None],marker=dict(colorscale=self._visuals._colors.colorscale,showscale=True,colorbar=dict(thickness=30)))
            layout = dict(xaxis=dict(visible=False),yaxis=dict(visible=False),showlegend=False)
            #self._colorbar = go.FigureWidget(data=data,layout=layout)
            #colorbar = widgets.Box([self._colorbar],layout=widgets.Layout(width="150px",margin="0px",padding="0px"))

        if colorbar != None:
            components.append(widgets.HBox([self._map,colorbar]))
        else:
            components.append(self._map)

        self.children = components 

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def node_hist_fig(
    node_color_distribution,
    title="Graph Node Distribution",
    width=400,
    height=300,
    top=60,
    left=25,
    bottom=60,
    right=25,
    bgcolor="rgb(240,240,240)",
    y_gridcolor="white",
):
    """Define the plotly plot representing the node histogram
    
    Parameters
    ----------
    node_color_distribution: list of dicts describing the build_histogram
    width, height: integers -  width and height of the histogram FigureWidget
    left, top, right, bottom: ints; number of pixels around the FigureWidget
    bgcolor: rgb of hex color code for the figure background color
    y_gridcolor: rgb of hex color code for the yaxis y_gridcolor

    Returns
    -------
    FigureWidget object representing the histogram of the graph nodes
    """

    text = [
        "{perc}%".format(**locals())
        for perc in [d["perc"] for d in node_color_distribution]
    ]

    pl_hist = go.Bar(
        y=[d["height"] for d in node_color_distribution],
        marker=dict(color=[d["color"] for d in node_color_distribution]),
        text=text,
        hoverinfo="y+text",
    )

    hist_layout = dict(
        title=title,
        width=width,
        height=height,
        font=dict(size=12),
        xaxis=dict(showline=True, zeroline=False, showgrid=False, showticklabels=False),
        yaxis=dict(showline=False, gridcolor=y_gridcolor, tickfont=dict(size=10)),
        bargap=0.01,
        margin=dict(l=left, r=right, b=bottom, t=top),
        hovermode="x",
        plot_bgcolor=bgcolor,
    )

    return go.FigureWidget(data=[pl_hist], layout=hist_layout) 

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def ipy_plot_interactive_annotate(df, ind, opacity=.3):
    import plotly.graph_objs as go
    from ipywidgets import interactive
    if 'labels' in df.columns:
        text = [f'Class {k}: index {i}' for i,k in zip(df.index, df.labels)] # hovertext
    else:
        text = [f'index {i}' for i in df.index] # hovertext
    xaxis, yaxis = df.columns[0], df.columns[1]
    scatter = go.Scattergl(x=df[xaxis], 
                           y=df[yaxis], 
                           mode='markers',
                           text=text,
                           marker=dict(size=2,
                                       opacity=opacity,
                                       ))
    sub = df.loc[ind]
    text = [f'{k}){i}' for i,k in zip(sub.index, sub.labels)]
    scatter2 = go.Scatter(x=sub[xaxis],
                            y=sub[yaxis],
                            mode='markers+text',
                            text=text,
                            textposition="top center",
                            textfont=dict(size=9,color='black'),
                            marker=dict(size=5,color='black'))
    f = go.FigureWidget([scatter,scatter2])
    f.update_layout(xaxis_title=xaxis, yaxis_title=yaxis)
    
    def update_axes(xaxis, yaxis, color_by, colorscale):
        scatter = f.data[0]
        scatter.x = df[xaxis]
        scatter.y = df[yaxis]
        
        scatter.marker.colorscale = colorscale
        if colorscale is None:
            scatter.marker.color = None
        else:
            scatter.marker.color = df[color_by] if color_by != 'index' else df.index
    
        scatter2 = f.data[1]
        scatter2.x = sub[xaxis]
        scatter2.y = sub[yaxis]
        with f.batch_update(): # what is this for??
            f.layout.xaxis.title = xaxis
            f.layout.yaxis.title = yaxis
        
    widget = interactive(update_axes, 
                    yaxis = df.select_dtypes('number').columns, 
                    xaxis = df.select_dtypes('number').columns,
                    color_by = df.columns,
                    colorscale = [None,'hsv','plotly3','deep','portland','picnic','armyrose'])
    return widget, f 

# 需要导入模块: from plotly import graph_objs [as 别名]
# 或者: from plotly.graph_objs import FigureWidget [as 别名]
def ipy_plot_interactive(df, opacity=.3):
    import plotly.graph_objs as go
    from ipywidgets import interactive
    if 'labels' in df.columns:
        text = [f'Class {k}: index {i}' for i,k in zip(df.index, df.labels)] # hovertext
    else:
        text = [f'index {i}' for i in df.index] # hovertext
    
    xaxis, yaxis = df.columns[0], df.columns[1]
    f = go.FigureWidget([go.Scattergl(x=df[xaxis],
                                  y=df[yaxis],
                                  mode='markers',
                                  text=text,
                                  marker=dict(size=2,
                                              opacity=opacity,
                                              color=np.arange(len(df)),
                                              colorscale='hsv'
                                             ))])
    scatter = f.data[0]
    N = len(df)
    f.update_layout(xaxis_title=xaxis, yaxis_title=yaxis)
    f.layout.dragmode = 'lasso'

    def update_axes(xaxis, yaxis, color_by, colorscale):
        scatter = f.data[0]
        scatter.x = df[xaxis]
        scatter.y = df[yaxis]
        
        scatter.marker.colorscale = colorscale
        if colorscale is None:
            scatter.marker.color = None
        else:
            scatter.marker.color = df[color_by] if color_by != 'index' else df.index
        with f.batch_update(): # what is this for??
            f.layout.xaxis.title = xaxis
            f.layout.yaxis.title = yaxis
 
    widget = interactive(update_axes, 
                         yaxis=df.select_dtypes('number').columns, 
                         xaxis=df.select_dtypes('number').columns,
                         color_by = df.columns,
                         colorscale = [None,'hsv','plotly3','deep','portland','picnic','armyrose'])

    t = go.FigureWidget([go.Table(
                        header=dict(values=['index']),
                        cells=dict(values=[df.index]),
                        )])

    def selection_fn(trace, points, selector):
        t.data[0].cells.values = [df.loc[points.point_inds].index]

    scatter.on_selection(selection_fn)
    return widget, f, t