How to use the plotly.offline.plot function in plotly

layout = go.Layout(title='Spectrogram Extraction Example using pyAudioAnalysis',
                   xaxis=dict(title='time (sec)',),
                   yaxis=dict(title='Freqs (Hz)',))

def normalize_signal(signal):
    signal = np.double(signal)
    signal = signal / (2.0 ** 15)
    signal = (signal - signal.mean())
    return  signal / ((np.abs(signal)).max() + 0.0000000001)

if __name__ == '__main__':
    [Fs, s] = wavfile.read("../data/sample_music.wav")
    s = normalize_signal(s)
    [S, t, f] = aF.spectrogram(s, Fs, int(Fs * 0.020), int(Fs * 0.020))
    heatmap = go.Heatmap(z=S.T, y=f, x=t)
    plotly.offline.plot(go.Figure(data=[heatmap], layout=layout),
                        filename="temp.html", auto_open=True)

fig = go.Figure(data=[edge_trace, node_trace],
                    layout=go.Layout(
                        title='<br>' + title,
                        titlefont=dict(size=16),
                        showlegend=False,
                        hovermode='closest',
                        margin=dict(b=20, l=5, r=5, t=40),
                        # annotations=[dict(
                        #     text="Python code: <a href="https://plot.ly/ipython-notebooks/network-graphs/"> https://plot.ly/ipython-notebooks/network-graphs/</a>",
                        #     showarrow=False,
                        #     xref="paper", yref="paper",
                        #     x=0.005, y=-0.002)],
                        xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
                        yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))

    plotly.offline.plot(fig, filename='{}.html'.format(output_path), auto_open=False, image_width=1600,
                        image_height=900, image='png')

),
            yaxis2=dict(
                title='Number of genomes',
                # ~ titlefont=dict(
                # ~ color='rgb(148, 103, 189)'
                # ~ ),
                # ~ tickfont=dict(
                # ~ color='rgb(148, 103, 189)'
                # ~ ),
                overlaying='y',
                side='right'
            )
        )

        fig = go.Figure({"data": listtraces, "layout": layout})
        plot_url = plotly.offline.plot(fig, filename=os.path.join(out_folder,'GenomeQualityPlot.html'))

        i += 1

    i = 0
    for stableiter in listStableIter:
        verboseprint( "At threshold " + str(thresholdlist[i]) + " it stabilized at the iteration number " + str(stableiter) )
        i += 1

    print (starttime)
    print ("Finished Script at : " + time.strftime("%H:%M:%S-%d/%m/%Y"))

from plotly import tools as tools
    fig = tools.make_subplots(rows=1, cols=3,
            subplot_titles=(
                "expected occupancies, beta={}".format(beta1),
                "expected occupancies, beta={}".format(beta2),
                "abs difference in ex. occupancies"))
    fig['layout'].update(title=title)

    for t in data1:
        fig.append_trace(t, 1, 1)
    for t in data2:
        fig.append_trace(t, 1, 2)
    for t in data3:
        fig.append_trace(t, 1, 3)
    # py.plot(fig, filename="output/beta_versus.html")
    py.plot(fig, filename="output/beta_versus_{}.html".format(100+uid),
            image='png', image_filename="output/beta_versus_{}.png".format(100+uid),
            image_width=1400, image_height=750)

ticks[0] = start.strftime('%I:%M %p')
    for i in range(30, 60*24, 30):
        ticks[i] = (start + timezone.timedelta(minutes=i)).strftime('%I:%M %p')

    layout_args['yaxis']['title'] = _('Time of day')
    layout_args['yaxis']['rangemode'] = 'tozero'
    layout_args['yaxis']['tickmode'] = 'array'
    layout_args['yaxis']['tickvals'] = list(ticks.keys())
    layout_args['yaxis']['ticktext'] = list(ticks.values())
    layout_args['yaxis']['tickfont'] = {'size': 10}

    fig = go.Figure({
        'data': traces,
        'layout': go.Layout(**layout_args)
    })
    output = plotly.plot(fig, output_type='div', include_plotlyjs=False)
    return utils.split_graph_output(output)

layout_args = utils.default_graph_layout_options()
    layout_args['title'] = _('<b>Average Feeding Durations</b>')
    layout_args['xaxis']['title'] = _('Date')
    layout_args['xaxis']['rangeselector'] = utils.rangeselector_date()
    layout_args['yaxis']['title'] = _('Average duration (minutes)')
    layout_args['yaxis2'] = dict(layout_args['yaxis'])
    layout_args['yaxis2']['title'] = _('Number of feedings')
    layout_args['yaxis2']['overlaying'] = 'y'
    layout_args['yaxis2']['side'] = 'right'

    fig = go.Figure({
        'data': [trace_avg, trace_count],
        'layout': go.Layout(**layout_args)
    })
    output = plotly.plot(fig, output_type='div', include_plotlyjs=False)
    return utils.split_graph_output(output)

def save_graph(data, layout):
        """Quick binder to dump plotly data and layout."""
        fig = go.Figure(data=data, layout=layout)

        return py.plot(fig, output_type='div', auto_open=False,
                       show_link=False, include_plotlyjs=False)

def show(self, filename=None, offline=True):
        if offline:
            from plotly.offline import plot
        else:
            from plotly.plotly import plot
        plot(self.figure, filename=filename, config=self._config)

def plot_changes(df_plot, group):
    created_line = go.Scatter(
        name='Created',
        x=df_plot.index,
        y=df_plot['created'])
    submitted_line = go.Scatter(
        name='Merged',
        x=df_plot.index,
        y=df_plot['merged'])
    updated_line = go.Scatter(
        name='Updated',
        x=df_plot.index,
        y=df_plot['updated'])
    plot_title = "Changes/PRs (%s projects)" % group
    changes_plot = plotly.offline.plot(
        {
            "data": [created_line, submitted_line, updated_line],
            "layout": go.Layout(title=plot_title)
        },
        show_link=False,
        output_type='div',
        include_plotlyjs='False')
    return changes_plot

tasks)]['task_status_name'] == 'running'),
                         name=app)
              for app, tasks in apps_dict.items()] +
        [go.Scatter(x=df_status['timestamp'],
                    y=y_axis_setup(
            df_status['task_status_name'] == 'running'),
            name='all')],
        layout=go.Layout(xaxis=dict(tickformat='%m-%d\n%H:%M:%S',
                                    autorange=True,
                                    title='Time'),
                         yaxis=dict(tickformat=',d',
                                    title='Tasks'),
                         hovermode='closest',
                         title='Tasks per app'))

    return plot(fig, show_link=False, output_type="div", include_plotlyjs=False)