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I am trying to re-work some jupyter notebooks using plotly instead of matplotlib. My original function is

def plot_power_spectrum(y):
    ps = np.abs(np.fft.fft(y - np.mean(y)))**2

    time_step = 1.0/6 # hours

    freqs = np.fft.fftfreq(y.size, time_step)
    idx = np.argsort(freqs)

    plt.plot(freqs[idx], ps[idx])
    plt.axvline(2*np.pi/168.0, color="magenta", alpha=0.4, lw=5)
    plt.axvline(-2*np.pi/168.0, color="magenta", alpha=0.4, lw=5)

I can't see a simple way to add such vertical lines (or other markup) in plotly.

I found this on using the cufflinks pandas integration. Although the function name is the same (iplot) it doesn't seem to be any relation.

I also saw this similar question. All I could think was "surely there's a simpler way"... Is there?

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sfjac
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1 Answers1

4

No problems doing it in plotly. Here is my notebook cell:

from plotly.graph_objs import *
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)

y=np.random.randint(30,size=100)

ps = np.abs(np.fft.fft(y - np.mean(y)))**2

time_step = 1.0/6 # hours

freqs = np.fft.fftfreq(y.size, time_step)
idx = np.argsort(freqs)


data = Scatter(x=freqs[idx], y=ps[idx])
layout = Layout(shapes=[dict({
            'type': 'line',
            'x0': 2*np.pi/168.0,
            'y0': 0,
            'x1': 2*np.pi/168.0,
            'y1': 35000,
            'line': {
                'color': '#FF00FF',
                'width': 5
            }})])
iplot({'data':[data], 'layout':layout})

For more examples check the shapes section here: https://plot.ly/python/shapes/

AlonG
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