def l1000cds2_upload():
import requests
import json
from clustergrammer import Network
from pymongo import MongoClient
from bson.objectid import ObjectId
# get the json
l1000cds2 = json.loads( request.form.get('signatures') )
# initialize network
net = Network()
# load l1000cds2 to .dat
net.load_l1000cds2(l1000cds2)
# cluster
cutoff_comp = 0
min_num_comp = 2
net.cluster_row_and_col(dist_type='cosine', dendro=True)
# redefine initial ordering - rank by gene signature values and pert scores
net.dat['node_info']['row']['ini'] = net.sort_rank_node_values('row')
net.dat['node_info']['col']['ini'] = net.sort_rank_node_values('col')
net.viz = {}
net.viz['row_nodes'] = []
net.viz['col_nodes'] = []
net.viz['links'] = []
# remake visualization
net.viz_json()
# generate export dictionary
###############################
export_dict = {}
export_dict['name'] = 'l1000cds2'
export_dict['dat'] = net.export_net_json('dat')
export_dict['viz'] = net.viz
export_dict['_id'] = ObjectId(l1000cds2['_id'])
# set up connection
client = MongoClient(mongo_address)
db = client.clustergrammer
# save to database
##################################
tmp = db.networks.find_one({'_id': ObjectId(l1000cds2['_id']) })
if tmp is None:
tmp_id = db.networks.insert( export_dict )
# close client
client.close()
return redirect('/clustergrammer/l1000cds2/'+l1000cds2['_id'])
# import network class from Network.py
from clustergrammer import Network
# get instance of Network
net = Network()
print(net.__doc__)
print('make tsv clustergram')
# load network from tsv file
##############################
net.load_tsv_to_net('txt/example_tsv_network.txt')
inst_filt = 0.001
inst_meet = 1
net.filter_network_thresh(inst_filt,inst_meet)
# cluster
#############
net.cluster_row_and_col('cos')
# export data visualization to file
######################################
net.write_json_to_file('viz', 'json/default_example.json', 'indent')
