plots 1D vectors and smoothes them using plotly

plot_1D_vector_and_smooth.py

import numpy as np
import plotly
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import plotly.graph_objs as go
init_notebook_mode(connected=True)
from plotly import tools
import scipy.signal as signal
from scipy.interpolate import interp1d

# myX - x axis values
# myY - y axis values
# smooth - smoothing value
def getSmooth(myX,myY,smooth):
    # BUTTER
    # GET THE WINDOW
    b, a = signal.butter(3, smooth, analog=False, btype = 'lowpass' , output='ba')
    fitData = signal.filtfilt(b,a,myY)
    # EXTRA STEP NEEDED TO SMOOTH - interpolate (this gives a function)
    f2 = interp1d(myX, fitData, kind='cubic')
    # MAKE A NEW X DOMAIN
    newX = np.linspace(0,len(myX)-1,len(myX))
    return newX, f2(newX)

# metricList - list of values to plot on Y
# mul - multiplier to move the values up and down along Y
# smooth - smooth value
# color1 - color of non smoothed line
# color2 - color of smoothed line
def getTwoLines(metricList,mul,smooth,color1,color2):
    scatter1 = go.Scatter( x=np.arange(len(metricList)), y=[k-mul for k in metricList], 
                          showlegend=False ,line=dict(color=color1,width=1) )
    newX,newY = getSmooth(np.arange(len(metricList)),[k-mul for k in metricList],smooth)
    scatter2 = go.Scatter( x=np.arange(len(newX)-1), y=[k for k in newY],
                         line=dict(color=color2,width=2))
    return [scatter1,scatter2]
  
dummy = np.random.normal(size=50)
data = getTwoLines(dummy,0,0.05,'rgb(31,120,180)','rgb(166,206,227)')

layout = go.Layout(
    title = "test title",
    xaxis=dict(
        showgrid=True,
        title="x axis"
    ),
    yaxis=dict(
        showgrid=True,
        title="y axis"
    )
)

fig = go.Figure(data=data, layout=layout)
iplot(fig)
plot(fig,
  show_link=False,
  image_filename="name", 
  image="svg")