Matrix plots in Lightning

Setup



In [1]:

    
from lightning import Lightning

from numpy import random, arange, asarray, corrcoef, argsort, array
import networkx as nx
from sklearn import datasets

Connect to server



In [2]:

    
lgn = Lightning(ipython=True, host='http://public.lightning-viz.org')









    




Lightning initialized






    



Connected to server at http://public.lightning-viz.org

Simple matrix

Matrices are useful ways to visualize dense tables and correlation matrices data.
First we show a random matrix with default styles.
You can us the arrow keys to change the contrast (up/down) or the colormap (left/right).



In [3]:

    
mat = random.randn(10,10)
lgn.matrix(mat)









    Out[3]:

Different shapes

Rectanglular matrices will automatically size appropriately.



In [4]:

    
mat = random.randn(10,20)
lgn.matrix(mat)









    Out[4]:



In [5]:

    
mat = random.randn(20,10)
lgn.matrix(mat)









    Out[5]:

Colors

Matrices can be rendered using any colorbrewer colormaps.



In [6]:

    
mat = random.rand(10,10)
lgn.matrix(mat, colormap='Reds')









    Out[6]:



In [7]:

    
mat = random.rand(10,10)
lgn.matrix(mat, colormap='Spectral')









    Out[7]:

Labels

You can label the rows and columns of a matrix. Clicking on the text labels will highlight those rows and columns -- try it!



In [8]:

    
n, m = (8, 16)
mat = arange(n*m).reshape(n,m)
rows = ['row ' + str(i) for i in range(n)]
columns = ['col ' + str(i) for i in range(m)]

lgn.matrix(mat, row_labels=rows, column_labels=columns)









    Out[8]:

You can also turn on labeling of cells by their value.



In [9]:

    
mat = arange(n*m).reshape(n,m)

lgn.matrix(mat, numbers=True)









    Out[9]: