def check_lambda_by_profit(cam_data, cam_data_length, cam_r, cam_base_ctr, dsp_budget, volume, dsp_l, cam_v, para, algo):
# init
cost = 0
profit = 0
budget_run_out = False
cam_data_index = arbitrage_rtb_test.init_cam_data_index(cam_data)
cam_vc = cam_v.copy() # we will change cam_vc when one campaign runs out of data
data_run_out = arbitrage_rtb_test.check_data_ran_out(cam_data_index, cam_data_length, cam_vc, volume)
# start simulation
while (not data_run_out) and (not budget_run_out):
cam = arbitrage_rtb_test.sample_cam(cam_vc)
yzp = arbitrage_rtb_test.next_cam_data(cam_data, cam_data_index, cam_data_length, cam)
if yzp == -1:
print cam_data_length
print cam_data_index
clk = yzp[0]
mp = yzp[1]
pctr = yzp[2]
r = cam_r[cam]
bid = arbitrage_rtb_test.bidding(r / config.cpc_payoff_ratio, cam_base_ctr[cam], r, dsp_l, pctr, algo, para)
if bid > mp: # win auction
cost += mp
if algo == "lin" or algo == "ortb":
profit += clk # these two algorithms care about clicks
else:
profit += clk * r - mp * 1.0E-3 # not cpm counting
budget_run_out = (cost >= dsp_budget)
data_run_out = arbitrage_rtb_test.check_data_ran_out(cam_data_index, cam_data_length, cam_vc, volume)
return -profit
def estimate_mu_sigma(cam_data, cam_data_length, cam_r, cam_base_ctr, dsp_budget, volume, dsp_l, cam_v,
algo_one_para, algo):
cam_mu = {}
cam_sigma = {} # standard deviation
para = algo_one_para[algo]
for cam in cam_data:
data = cam_data[cam]
length = cam_data_length[cam]
profit_margins = []
index = 0
for process in range(config.e_step_mu_process_num):
cost = 0
profit = 0
for i in range(min(volume, len(data))):
yzp = data[index]
index = (index + 1) % length # rotation
clk = yzp[0]
mp = yzp[1]
pctr = yzp[2]
r = cam_r[cam]
# bid = 0
# if algo == "sam":
# bid = arbitrage_rtb_test.bidding_sam(pctr, r, dsp_l, para)
# elif algo == "lin":
# bid = arbitrage_rtb_test.bidding_lin(pctr, cam_base_ctr[cam], para)
# elif algo == "ortb":
# bid = arbitrage_rtb_test.bidding_ortb(pctr, cam_base_ctr[cam], r, dsp_l, para)
# else:
# print "e-step portfolio algorithm name error"
bid = arbitrage_rtb_test.bidding(r / config.cpc_payoff_ratio, cam_base_ctr[cam], r, dsp_l, pctr, algo, para)
if bid > mp: # win auction
cost += mp * 1.0E-3 # should have the same unit
profit += clk * r - mp * 1.0E-3 # not cpm counting
if cost >= dsp_budget:
break
profit_margin = profit / max(cost, 0.1) # avoid zero division
profit_margins.append(profit_margin)
cam_mu[cam] = numpy.mean(profit_margins)
cam_sigma[cam] = numpy.std(profit_margins)
return cam_mu, cam_sigma
def get_market_price_up_value(cam_data, cam_r, cam_original_ecpc, cam_original_ctr,
dsp_l, algo, para):
up_value = 0.
num = 0
for cam in cam_data:
data = cam_data[cam]
original_ecpc = cam_original_ecpc[cam]
original_ctr = cam_original_ctr[cam]
r = cam_r[cam]
for yzp in data:
clk = yzp[0]
mp = yzp[1]
pctr = yzp[2]
bid = arbitrage_rtb_test.bidding(original_ecpc, original_ctr, r, dsp_l, pctr, algo, para)
if bid > mp:
up_value += (bid - mp) * 0.5
num += 1
up_value /= num
return up_value
def get_market_price_up_value(cam_data, cam_r, cam_original_ecpc,
cam_original_ctr, dsp_l, algo, para):
up_value = 0.
num = 0
for cam in cam_data:
data = cam_data[cam]
original_ecpc = cam_original_ecpc[cam]
original_ctr = cam_original_ctr[cam]
r = cam_r[cam]
for yzp in data:
clk = yzp[0]
mp = yzp[1]
pctr = yzp[2]
bid = arbitrage_rtb_test.bidding(original_ecpc, original_ctr, r,
dsp_l, pctr, algo, para)
if bid > mp:
up_value += (bid - mp) * 0.5
num += 1
up_value /= num
return up_value
def check_lambda_by_profit(cam_data, cam_data_length, cam_r, cam_base_ctr,
dsp_budget, volume, dsp_l, cam_v, para, algo):
# init
cost = 0
profit = 0
budget_run_out = False
cam_data_index = arbitrage_rtb_test.init_cam_data_index(cam_data)
cam_vc = cam_v.copy(
) # we will change cam_vc when one campaign runs out of data
data_run_out = arbitrage_rtb_test.check_data_ran_out(
cam_data_index, cam_data_length, cam_vc, volume)
# start simulation
while (not data_run_out) and (not budget_run_out):
cam = arbitrage_rtb_test.sample_cam(cam_vc)
yzp = arbitrage_rtb_test.next_cam_data(cam_data, cam_data_index,
cam_data_length, cam)
if yzp == -1:
print cam_data_length
print cam_data_index
clk = yzp[0]
mp = yzp[1]
pctr = yzp[2]
r = cam_r[cam]
bid = arbitrage_rtb_test.bidding(r / config.cpc_payoff_ratio,
cam_base_ctr[cam], r, dsp_l, pctr,
algo, para)
if bid > mp: # win auction
cost += mp
if algo == "lin" or algo == "ortb":
profit += clk # these two algorithms care about clicks
else:
profit += clk * r - mp * 1.0E-3 # not cpm counting
budget_run_out = (cost >= dsp_budget)
data_run_out = arbitrage_rtb_test.check_data_ran_out(
cam_data_index, cam_data_length, cam_vc, volume)
return -profit
