def est_main():
numid2volume = {}
click_items = load_click_items(numid2volume)
pay_items = load_pay_items()
click_sig2prob = stats_items(click_items, lambda x:x.item_volume, 'Click')
#import pdb; pdb.set_trace()
pay_sig2prob = stats_items(pay_items, lambda x:numid2volume.get(long(x.num_id), -1), 'Pay')
header = ['num%s'%x for x in range(21)] + ["num%s-%s"%(x-9, x) for x in range(30,110,10)] + ["num%s-%s"%(x-49,x) for x in range(150,350,50)] + ['num%s-num%s'%(x-199,x) for x in range(400,1200,200)]
sig2header = dict(zip(range(1,len(header)+1), header))
scales = []
scale_f = open(FLAGS.scale_output, "w")
xindex = range(21) + range(30, 110, 10) + range(150,350,50) + range(400,1200,200)
for i in range(1, 38):
name = sig2header[i]
if pay_sig2prob.get(i, -1) != -1 and click_sig2prob.get(i, -1) != -1:
v = pay_sig2prob.get(i, -1) / click_sig2prob.get(i, -1)
else:
v = 0
#scales.append((i, v))
scales.append((xindex[i-1], v))
scale_f.write("%s : %s : %s : %s\n" % (name, click_sig2prob.get(i, -1), pay_sig2prob.get(i, -1), v))
g = gnuplot(FLAGS.plot_output)
g.xlabel = 'signal'
g.ylabel = 'scale'
dataset = {0:{'xy_arr':scales}}
g.plotline(dataset)
def stats_dist_diff(click_items, pay_items, splitter, key, numid2volumeprice):
def_item = {'volume':-1, 'price':-1}
fn_conv = lambda x:numid2volumeprice.get(long(x.num_id), def_item)[key]
click_sig2prob = stats_items_dist(click_items, fn_conv, 'Click', splitter)
pay_sig2prob = stats_items_dist(pay_items, fn_conv, 'Pay', splitter)
#import pdb; pdb.set_trace()
header = splitter.headers
sig2header = dict(zip(range(1,len(header)+1), header))
scales = []
scale_f = open("%s_%s" % (key, FLAGS.scale_output), "w")
#xindex = range(21) + range(30, 110, 10) + range(150,350,50) + range(400,1200,200)
xindex = splitter.range_sum
for i in range(1, len(splitter.headers)+1):
name = sig2header[i]
if pay_sig2prob.get(i, -1) != -1 and click_sig2prob.get(i, -1) != -1:
v = pay_sig2prob.get(i, -1) / click_sig2prob.get(i, -1)
else:
v = 0
#scales.append((i, v))
scales.append((xindex[i-1], v))
scale_f.write("%s : %s : %s : %s\n" % (name, click_sig2prob.get(i, -1), pay_sig2prob.get(i, -1), v))
g = gnuplot("%s_%s" % (key, FLAGS.plot_output))
g.xlabel = 'signal'
g.ylabel = 'scale'
dataset = {0:{'xy_arr':scales}}
g.plotline(dataset)
def stats_dist_diff(click_items, pay_items, splitter, key, numid2volumeprice):
def_item = {'volume': -1, 'price': -1}
fn_conv = lambda x: numid2volumeprice.get(long(x.num_id), def_item)[key]
click_sig2prob = stats_items_dist(click_items, fn_conv, 'Click', splitter)
pay_sig2prob = stats_items_dist(pay_items, fn_conv, 'Pay', splitter)
#import pdb; pdb.set_trace()
header = splitter.headers
sig2header = dict(zip(range(1, len(header) + 1), header))
scales = []
scale_f = open("%s_%s" % (key, FLAGS.scale_output), "w")
#xindex = range(21) + range(30, 110, 10) + range(150,350,50) + range(400,1200,200)
xindex = splitter.range_sum
for i in range(1, len(splitter.headers) + 1):
name = sig2header[i]
if pay_sig2prob.get(i, -1) != -1 and click_sig2prob.get(i, -1) != -1:
v = pay_sig2prob.get(i, -1) / click_sig2prob.get(i, -1)
else:
v = 0
#scales.append((i, v))
scales.append((xindex[i - 1], v))
scale_f.write(
"%s : %s : %s : %s\n" %
(name, click_sig2prob.get(i, -1), pay_sig2prob.get(i, -1), v))
g = gnuplot("%s_%s" % (key, FLAGS.plot_output))
g.xlabel = 'signal'
g.ylabel = 'scale'
dataset = {0: {'xy_arr': scales}}
g.plotline(dataset)
def est_main():
numid2volume = {}
click_items = load_click_items(numid2volume)
pay_items = load_pay_items()
click_sig2prob = stats_items(click_items, lambda x: x.item_volume, 'Click')
#import pdb; pdb.set_trace()
pay_sig2prob = stats_items(pay_items,
lambda x: numid2volume.get(long(x.num_id), -1),
'Pay')
header = ['num%s' % x for x in range(21)] + [
"num%s-%s" % (x - 9, x) for x in range(30, 110, 10)
] + ["num%s-%s" % (x - 49, x) for x in range(150, 350, 50)
] + ['num%s-num%s' % (x - 199, x) for x in range(400, 1200, 200)]
sig2header = dict(zip(range(1, len(header) + 1), header))
scales = []
scale_f = open(FLAGS.scale_output, "w")
xindex = range(21) + range(30, 110, 10) + range(150, 350, 50) + range(
400, 1200, 200)
for i in range(1, 38):
name = sig2header[i]
if pay_sig2prob.get(i, -1) != -1 and click_sig2prob.get(i, -1) != -1:
v = pay_sig2prob.get(i, -1) / click_sig2prob.get(i, -1)
else:
v = 0
#scales.append((i, v))
scales.append((xindex[i - 1], v))
scale_f.write(
"%s : %s : %s : %s\n" %
(name, click_sig2prob.get(i, -1), pay_sig2prob.get(i, -1), v))
g = gnuplot(FLAGS.plot_output)
g.xlabel = 'signal'
g.ylabel = 'scale'
dataset = {0: {'xy_arr': scales}}
g.plotline(dataset)
