data_tes_path  = '/home/chengtao/june/data/svm_pos/tes'

plot_roc.beg_plt()

best = 0.00
best_hype = ''
for sco in sorted(os.listdir(lstm_path)):
    if 'info' in sco: continue
    H = X_obj.SCO_obj(lstm_path+'/'+sco+'/score')
    auc,fpr,tpr = H.read_report()
    if auc > best:
        best = auc
        best_hype  = sco
    #plot_roc.get_plt(auc,fpr,tpr,'lstm'+sco)
    

H = X_obj.SCO_obj(logr_path+'/0.001/score')
auc,fpr,tpr = H.read_report()
plot_roc.get_plt(auc,fpr,tpr,'logr 0.001')

H = X_obj.SCO_obj(lstm_path+'/'+best_hype+'/score')
auc,fpr,tpr = H.read_report()
plot_roc.get_plt(auc,fpr,tpr,'lstm 16_3_0.001')
print best_hype

plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_hmm.pkl','hmm: 1st stage')
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_svm.pkl','svm: 2nd stage')
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_cld.pkl','cloud operating point',True)

plot_roc.end_plt('2015-1027-1145.png')
Example #2
0
data_dev_path  = '/home/chengtao/june/data/svm_pos/dev'
data_tes_path  = '/home/chengtao/june/data/svm_pos/tes'

plot_roc.beg_plt()

best = 0.00
best_hype = ''
for sco in sorted(os.listdir(lstm_path)):
    if 'info' in sco: continue
    H = X_obj.SCO_obj(lstm_path+'/'+sco+'/score')
    auc,fpr,tpr = H.read_report()
    if auc > best:
        best = auc
        best_hype  = sco
    #plot_roc.get_plt(auc,fpr,tpr,'lstm'+sco)
    

H = X_obj.SCO_obj(logr_path+'/0.001/score')
auc,fpr,tpr = H.read_report()
plot_roc.get_plt(auc,fpr,tpr,'logr')

H = X_obj.SCO_obj(lstm_path+'/'+best_hype+'/score')
auc,fpr,tpr = H.read_report()
plot_roc.get_plt(auc,fpr,tpr,'lstm')
print best_hype
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_svm.pkl','svm')
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_hmm.pkl','hmm')
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_cld.pkl','cld',True)

plot_roc.end_plt('scores.png')
score_tra_path = "/home/chengtao/june/simple_exp/score/tra"
score_tes_path = "/home/chengtao/june/simple_exp/score/tra"
model_path = "/home/chengtao/june/simple_exp/model"
data_tra_path = "/home/chengtao/june/data/beta/tra"
data_tes_path = "/home/chengtao/june/data/beta/tes"

plot_roc.beg_plt()

best = 0.00
best_hype = ""
for sco in sorted(os.listdir(lstm_path)):
    if "info" in sco:
        continue
    H = X_obj.SCO_obj(lstm_path + "/" + sco + "/score")
    auc, fpr, tpr = H.read_report()
    if auc > best:
        best = auc
        best_hype = sco
    # plot_roc.get_plt(auc,fpr,tpr,'lstm'+sco)


H = X_obj.SCO_obj(logr_path + "/0.001/score")
auc, fpr, tpr = H.read_report()
plot_roc.get_plt(auc, fpr, tpr, "logr")

H = X_obj.SCO_obj(lstm_path + "/" + best_hype + "/score")
auc, fpr, tpr = H.read_report()
plot_roc.get_plt(auc, fpr, tpr, "single layer lstm")

plot_roc.end_plt("2015-1026-1811.png")
plot_roc.beg_plt()

best = 0.00
best_hype = ''
for sco in sorted(os.listdir(lstm_path)):
    if 'info' in sco: continue
    if  sys.argv[1] not in sco: continue
    H = X_obj.SCO_obj(lstm_path+'/'+sco+'/score')
    auc,fpr,tpr = H.read_report()
    if auc > best:
        best = auc
        best_hype  = sco
    plot_roc.get_plt(auc,fpr,tpr,'lstm '+sco)
    

#H = X_obj.SCO_obj(logr_path+'/0.001/score')
#auc,fpr,tpr = H.read_report()
#plot_roc.get_plt(auc,fpr,tpr,'logr 0.001')

#H = X_obj.SCO_obj(lstm_path+'/'+best_hype+'/score')
#auc,fpr,tpr = H.read_report()
#plot_roc.get_plt(auc,fpr,tpr,'lstm 16_3_0.001')
print best_hype

#plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_hmm.pkl','hmm: 1st stage')
#plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_svm.pkl','svm: 2nd stage')
plot_roc.sco_plt(data_dev_path+'/targets_utt.ark',data_dev_path+'/results_cld.pkl','cloud operating point',True)

plot_roc.end_plt('2015-1027-1207_{}.png'.format(sys.argv[1]))
import X_obj
import plot_roc
import os
import sys
lstm_path     = '/home/chengtao/june/hyper/lstm_negs'
lstm2_path     = '/home/chengtao/june/hyper/lstm'
data_tra_path  = '/home/chengtao/june/data/beta/tra'
data_tes_path  = '/home/chengtao/june/data/beta/tes'

plot_roc.beg_plt()

best_hype = '16_3_0.001'

H = X_obj.SCO_obj(lstm_path+'/'+best_hype+'/score')
auc,fpr,tpr = H.read_report()
plot_roc.get_plt(auc,fpr,tpr,'lstm trained on negative, tested on positive')

G = X_obj.SCO_obj(lstm_path+'/'+best_hype+'/score_dev')
auc,fpr,tpr = G.read_report()
plot_roc.get_plt(auc,fpr,tpr,'lstm trained on negative, tested on negative')

I = X_obj.SCO_obj(lstm2_path+'/'+best_hype+'/score')
auc,fpr,tpr = I.read_report()
plot_roc.get_plt(auc,fpr,tpr,'lstm trained on positive, tested on positive')

plot_roc.end_plt(sys.argv[0][:-3]+'.png')
Example #6
0
#prob = plot_roc.get_prob(post_path)
#answ = plot_roc.get_answ(data_path)

plot_roc.beg_plt()
#for x in ['lstm/16_1_0.001','lstm/16_2_0.001']:
for x in sorted(os.listdir('hyper/lstm')):
    if 'info' in x: continue
    print x.split('_')
    def func():
        data_path = 'data/svm_pos/dev/targets_seq.ark'
        post_path = 'hyper/lstm/{}/score/posteri_seq.ark'.format(x)
        #answ = plot_roc.get_answ(data_path)
        #prob = plot_roc.get_prob(post_path)
        #auc,fpr,tpr = plot_roc.get_auc(answ,prob)
        #print post_path,auc
        #plot_roc.roc_plt(fpr,tpr,x)
        plot_roc.roc_plt(data_path,post_path,x)
    if x.split('_')[2]=='0.001':# and x.split()[0]=='16':
        try: func()
        except:pass

'''
for x in ['dnn','svm']:
    data_path = '../lstm/ark/targets_{}_tes.ark'.format(x)
    post_path = '../lstm/ark/posteri_{}_tes.ark'.format(x)
    print post_path
    plot_roc.roc_plt(data_path,post_path,x)
'''

plot_roc.end_plt('xx.png')