from clustergrammer_widget import *
import process_CCLE
net = Network()
ds_df = process_CCLE.quick_downsample(num_clusts=100)
found categories
ds_df.shape
(18874, 100)
net.load_file('../proc_data/inst_ds.txt')
ccle = net.export_df()
net.dat['mat'].shape
(18874, 100)
net.filter_N_top('row', 2000, rank_type='var')
net.normalize(axis='row', norm_type='zscore', keep_orig=True)
net.dat['mat'].shape
(2000, 100)
net.make_clust()
clustergrammer_widget(network=net.widget())
(18874, 100)