Holoviewsとはmatplotlib plotly bokehなどのwrapperである。
公式: http://holoviews.org/
基本的な使い方: https://qiita.com/driller/items/53be86cea3c3201e7e0f

file出力

形式を選ぶ
renderer = hv.renderer('bokeh').instance(fig='html')
renderer = hv.renderer('matplotlib').instance(fig='png')

出力のpathを指定
renderer.save(gridspace, 'fname', style=dict(Image={'cmap':'jet'}))

grid上に並べる

dict = {(x,y): holoviewsのplotオブジェクト}
hv.GridSpace(dict, kdims=['x_name','y_name'])

sample code

import numpy as np
import holoviews as hv

def sine_curve(phase, freq):
    xvals = [0.1* i for i in range(100)]
    return hv.Curve((xvals, [np.sin(phase+freq*x) for x in xvals]))

phases      = [0, np.pi/2, np.pi, 3*np.pi/2]
frequencies = [0.5, 0.75, 1.0, 1.25]
curve_dict_2D = {(p,f):sine_curve(p,f) for p in phases for f in frequencies}
gridspace = hv.GridSpace(curve_dict_2D, kdims=['x', 'y'])
#renderer = hv.renderer('bokeh').instance(fig='html')
renderer = hv.renderer('matplotlib').instance(fig='png')
renderer.save(gridspace, 'fname', style=dict(Image={'cmap':'jet'}))