X.ix[X.ix[:,'Inhib_GSK690693_GSK1120212']>0,'Inhib_GSK690693_GSK1120212'] = 1
X.ix[X.ix[:,'Inhib_GSK690693']<0,'Inhib_GSK690693'] = 0
X.ix[X.ix[:,'Inhib_GSK690693_GSK1120212']<0,'Inhib_GSK690693_GSK1120212'] = 0
n_estimators = 100
max_depth = 3
regGBR[stim] = do_gbr(X, Y, n_estimators=n_estimators, max_depth=max_depth)
adj = build_adj_matrix(regGBR, node_list, stims)
A_true_bt20 = prior
for stim in adj:
path = 'results/sakev-BT20-{0}-Network'.format(stim)
for row in A_true_bt20.index:
for col in A_true_bt20.columns:
if A_true_bt20.ix[row,col] == 1:
adj[stim].ix[row,col] = 1
utilities.write_SIF_EDA(adj[stim], path)
## BT549
##############################################
print '----------- ' + 'BT549' + ' ------------'
inhibs = set(bt549['Inhibitor'])
stims = set(bt549['Stimulus'])
node_list = bt549.columns[4:]
inhib_targets = {'GSK690693' : ['AKT_pT308','AKT_pS473'],
'GSK690693_GSK1120212' : ['AKT_pT308','AKT_pS473','MEK1_pS217_S221']}
regGBR= {}
scalar = {}
td_bt549 = utilities.prepare_markov_data(utilities.introduce_inhibs(bt549, inhib_targets=inhib_targets, perfect=True), 'level', group_stimuli=False)
for stim in td_bt549:
X, Y = td_bt549[stim]
scalar[stim] = preprocessing.StandardScaler()
# load in the insilico data
insilico_data = pd.read_csv('data/insilico.csv', header=0)
inhibs = set(insilico_data['Inhibitor'])
stims = set(insilico_data['Stimulus'])
node_list = ['AB{0}'.format(i) for i in range(1, 21)]
inhib_targets = {'INH1' : 'AB12', 'INH2' : 'AB5', 'INH3' : 'AB8'}
regGBR= {}
scalar = {}
td = utilities.prepare_markov_data(utilities.introduce_inhibs(insilico_data, inhib_targets=inhib_targets, perfect=True), 'level', group_stimuli=True)
X, Y = td['all_stimuli']
scalar['all_stimuli'] = preprocessing.StandardScaler()
scalar['all_stimuli'].fit_transform(X)
X.ix[X.ix[:,'Inhib_INH1']>0,'Inhib_INH1'] = 1
X.ix[X.ix[:,'Inhib_INH2']>0,'Inhib_INH2'] = 1
X.ix[X.ix[:,'Inhib_INH3']>0,'Inhib_INH3'] = 1
X.ix[X.ix[:,'Inhib_INH1']<0,'Inhib_INH1'] = 0
X.ix[X.ix[:,'Inhib_INH2']<0,'Inhib_INH2'] = 0
X.ix[X.ix[:,'Inhib_INH3']<0,'Inhib_INH3'] = 0
# Step 2 : Fit
n_estimators = 100
max_depth = 3
regGBR['all_stimuli'] = do_gbr(X, Y, n_estimators=n_estimators, max_depth=max_depth)
# Step 3 : build and write adjacency matrix
adj = build_adj_matrix(regGBR, node_list, ['all_stimuli'])
utilities.write_SIF_EDA(adj['all_stimuli'], 'results/sakev-Network-Insilico')
