Python plotly.graph_objs.FigureWidget() Examples
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code examples of plotly.graph_objs.FigureWidget().
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Example #1
Source File: visuals.py From python-esppy with Apache License 2.0 | 5 votes |
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)
Example #2
Source File: plotlyviz.py From kepler-mapper with MIT License | 5 votes |
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)
Example #3
Source File: visuals.py From python-esppy with Apache License 2.0 | 4 votes |
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
Example #4
Source File: visuals.py From python-esppy with Apache License 2.0 | 4 votes |
def create(self): size = self._gauge.getOpt("size",300) self._layout = go.Layout(width=size,height=size) self._data = [] self._tics = go.Pie(values=self._gauge._ticValues,labels=self._gauge._ticLabels, marker=dict(colors=["rgba(0,0,0,0)"] * (self._gauge._segments + 10),line_width = 0), direction="clockwise", rotation=int((((self._gauge._shape + 10) / 100) * 360) / 2), hole=self._gauge.getOpt("center_size",.40), sort=False, showlegend=False, hoverinfo="none", textposition="outside", textinfo="label") self._data.append(self._tics) self._intervals = go.Pie(values=self._gauge._intervalValues, labels=self._gauge._intervalLabels, text=self._gauge._segmentLabels, marker=dict(line_width=self._gauge.getOpt("line_width",4)), marker_colors=self._gauge._intervalColors, hole=self._gauge.getOpt("center_size",.40), sort=False, direction="clockwise", rotation=int(((self._gauge._shape / 100) * 360) / 2), showlegend=False, hoverinfo="none", textposition="inside", textinfo="text") self._data.append(self._intervals) margin = self._gauge.getOpt("margin",30) self._layout["margin"] = dict(l=margin,r=margin,b=margin,t=margin) #self._layout["paper_bgcolor"] = "#e8e8e8" #self._layout["plot_bgcolor"] = "blue" #self._layout["paper_bgcolor"] = "rgba(0,0,0,0)" self._layout["plot_bgcolor"] = "rgba(0,0,0,0)" self._figure = go.FigureWidget(data=self._data,layout=self._layout) height = size height += 30 #self.children = [self._title,self._figure],layout=widgets.Layout(border="1px solid #d8d8d8",width=str(size) + "px",height=str(height) + "px") self.children = [self._title,self._figure]
Example #5
Source File: plotlyviz.py From kepler-mapper with MIT License | 4 votes |
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)
Example #6
Source File: analysis.py From cryodrgn with GNU General Public License v3.0 | 4 votes |
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
Example #7
Source File: analysis.py From cryodrgn with GNU General Public License v3.0 | 4 votes |
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