def main():
begin_time = time.clock()
print("#################### Setup ####################")
# ======================== Additional Parameters ============================ #
start_date = "20160620"
end_date = "20160620"
use_freq_stk = True
# ======================== Path ============================= #
tick_data_path = Util.get_path_tickdata()
output_path = Util.get_path_output()
# ======================== Data ============================= #
print("#################### Data ####################")
data_framework = DataFramework(start_date_str=start_date,end_date_str=end_date,path_tickdata=tick_data_path)
# ======================== Strategy ============================= #
print("#################### Strategy:Wave ####################")
define_wave = WaveByTick(Util.set_global_paras())
# ======================== Analysis ============================= #
print("#################### Analysis ####################")
analysis_all = AnalysisAll(data_framework,define_wave)
analysis_all.loop_date_stk_plot(use_freq_stk=use_freq_stk,output_path=output_path)
# ======================== End ============================= #
print("Complete! Total Time Used:",time.clock()-begin_time)
def one_day_update(wave_record_file_name):
start_date = "20160501"
end_date = "20160601"
wave_record_path = Util.get_wave_record_path() + 'wave_ret_record\\'
output_path = Util.get_path_output()
tick_data_path = Util.get_path_tickdata()
transaction_data_path = Util.get_path_transaction_data()
data_framework = DataFramework(start_date_str=start_date, end_date_str=end_date, path_tickdata=tick_data_path, path_transaction_data=transaction_data_path)
output = []
date_str = wave_record_file_name.split('.')[0].split('_')[-1]
wave_record_one_day_all_stock = pd.read_csv(wave_record_path + wave_record_file_name)
total_num = len(wave_record_one_day_all_stock)
num = 0
stock_str = ''
for k, one_wave_row in wave_record_one_day_all_stock.iterrows():
num += 1
if one_wave_row['wave_tot'] == 0:
one_wave_new = one_wave_row
else:
stock_str_new = str(one_wave_row['stock']).zfill(6)
if stock_str == stock_str_new:
pass
else:
stock_str = stock_str_new
tick_data_one_day_one_stock = TickdataOneDayOneStk(date_str, stock_str, data_framework)
one_wave_new = update_one_wave(one_wave_row, tick_data_one_day_one_stock)
output.append(one_wave_new)
print(date_str, one_wave_row['stock'], 'done', num/total_num, datetime.datetime.now())
output_df = pd.DataFrame(output)
output_df.to_csv(output_path + wave_record_file_name, index=False)
print(output_path+wave_record_file_name, 'done')
def main(start_date, end_date):
logger = logging.getLogger()
file_log = logging.FileHandler(Util.get_log_path())
logger.addHandler(file_log)
formatter = logging.Formatter("%(asctime)s %(levelname)s %(message)s")
file_log.setFormatter(formatter)
logger.setLevel(logging.INFO)
begin_time = time.clock()
# ======================== Additional Parameters ============================ #
# start_date = "20160516"
# end_date = "20160601"
use_freq_stk = False
# ======================== Path ============================= #
tick_data_path = Util.get_path_tickdata()
transaction_data_path = Util.get_path_transaction_data()
output_path = Util.get_path_output()
# ======================== Data ============================= #
data_framework = DataFramework(
start_date_str=start_date,
end_date_str=end_date,
path_tickdata=tick_data_path,
path_transaction_data=transaction_data_path,
use_specific_stk=True,
)
# ======================== Strategy ============================= #
define_wave = WaveByTick(Util.set_global_paras())
# ======================== Analysis ============================= #
analysis_all = AnalysisAll(data_framework, define_wave)
# analysis_all.loop_date_stk_calret(use_freq_stk=use_freq_stk, output_path=output_path, logger=logger)
analysis_all.loop_date_stk_plot(use_freq_stk=use_freq_stk,
output_path=output_path,
logger=logger)
# ======================== End ============================= #
print("Complete! Total Time Used:", time.clock() - begin_time)
wave_record = self.define_wave.tick_rolling(data_date_stk)
assert isinstance(wave_record,WaveRecord)
analysis_wave = AnalysisOneDayOneStk(data_date_stk.date_str,data_date_stk.stk_str,use_freq_stk,output_path)
analysis_wave.analyze_ret(data_date_stk, wave_record, self.define_wave.paras, logger=logger)
except Exception as e:
print('============================Error:', one_date, one_stk, e, '=========================')
logger.error('Error:' + str(one_date) + str(one_stk) + str(e))
# print(time.clock()-begin)
if __name__ == "__main__":
# begin=time.clock()
# Step 1:
test_data = DataFramework("20160620","20160620",Util.get_path_tickdata())
wave_calculation = WaveByTick(Util.set_global_paras())
record = test_data.get_intraday_record_from_csv_this_day("20160620","zx600564358")
# Step 2:
analysis = AnalysisAll(test_data,wave_calculation)
analysis.loop_date_stk_plot(True,Util.get_path_output())
# print(time.clock()-begin)
close_prc,ret,vol_capacity)
to_csv = open(self.output_path + "wave_ret_record\\" + "wave_ret_" + self.date_str + ".csv",'a')
to_csv.write(to_append)
to_csv.close()
wave_num += 1
if __name__ == "__main__":
begin=time.clock()
tmp_date="20160603"
tmp_code="002477"
# Step 1:
test_data = DataFramework(tmp_date,tmp_date,Util.get_path_tickdata())
wave_calculation = WaveByTick(Util.set_global_paras())
# Step 2:
test_tickdata = TickdataOneDayOneStk(tmp_date,tmp_code,test_data)
wave_record = wave_calculation.tick_rolling(test_tickdata)
analysis_wave = AnalysisOneDayOneStk(tmp_date,tmp_code,False,Util.get_path_output())
analysis_wave.analyze_plot(test_tickdata,wave_record,Util.set_global_paras(),test_data.get_intraday_record_from_csv_this_day(tmp_date,"zx600564358"))
plt.show()
# analysis_wave.analyze_ret(test_tickdata,wave_record,Util.set_global_paras())
print(time.clock()-begin)
'asize3', 'asize2', 'asize1',
'bsize1', 'bsize2', 'bsize3']] # 20160622, MK
px_mid_this_day_this_stk['ask1'] = px_mid_this_day_this_stk['ask1']/Util.px_multiplier
px_mid_this_day_this_stk['bid1'] = px_mid_this_day_this_stk['bid1']/Util.px_multiplier
px_mid_this_day_this_stk['mid_prc'] = (px_mid_this_day_this_stk['bid1'] + px_mid_this_day_this_stk['ask1'])/2
transaction_data_set_index = self.transaction_data_from_csv_filter_time
volume_buy = transaction_data_set_index[transaction_data_set_index['bs_flag'] == 66][['trade_volume']] # 66 is ascii code for 'B'
volume_sell = transaction_data_set_index[transaction_data_set_index['bs_flag'] == 83][['trade_volume']] # 83 is ascii code for 'S
self.px_mid_this_day_this_stk = px_mid_this_day_this_stk.loc[px_mid_this_day_this_stk['mid_prc'] > 0]
self.volume_buy = volume_buy
self.volume_sell = volume_sell
# px_mid_this_day_this_stk = (self.data_from_csv_filter_time['bid1'] +
# self.data_from_csv_filter_time['ask1'])/2/10000
# self.px_mid_this_day_this_stk = px_mid_this_day_this_stk[px_mid_this_day_this_stk>0]
except Exception as e:
print('data_error, {}, {}, {}'.format(self.date_str, self.stk_str, e))
self.px_mid_this_day_this_stk = pd.DataFrame({"mid_prc": [], "ask1": [], "bid1": [],
"asize3": [], "asize2": [], "asize1": [],
"bsize1": [], "bsize2": [], "bsize3": [],
'volume_buy': [], 'volume_sell': []})
self.volume_buy = pd.Series()
self.volume_sell = pd.Series()
if __name__ == "__main__":
test_data = DataFramework("20160401", "20160401", Util.get_path_tickdata())
test_tickdata = TickdataOneDayOneStk("20160401", "000005", test_data)
if __name__ == "__main__":
multiprocessing_num = 5
pool = multiprocessing.Pool(processes=multiprocessing_num)
start_date = '20160101'
end_date = '20161101'
tick_data_path = Util.get_path_tickdata()
transaction_data_path = Util.get_path_transaction_data()
output_path = Util.get_path_output()
data_framework = DataFramework(
start_date_str=start_date,
end_date_str=end_date,
path_tickdata=tick_data_path,
path_transaction_data=transaction_data_path,
use_specific_stk=True,
)
data_framework.update_date_list()
for date_str in data_framework.date_list:
print(date_str)
# main(date_str, date_str)
pool.apply_async(main, args=(
date_str,
date_str,
))
pool.close()
pool.join()
def main():
start_date = "20160501"
# end_date = "20160505"
# start_date = "20160506"
# end_date = "20160510"
# start_date = "20160511"
# end_date = "20160515"
# start_date = "20160516"
# end_date = "20160520"
# start_date = "20160521"
# end_date = "20160525"
# start_date = "20160526"
# end_date = "20160530"
# start_date = "20160531"
end_date = "20160601"
# start_date = "20160509"
# end_date = "20160609"
tick_data_path = Util.get_path_tickdata()
transaction_data_path = Util.get_path_transaction_data()
data_framework = DataFramework(start_date_str=start_date, end_date_str=end_date, path_tickdata=tick_data_path, path_transaction_data=transaction_data_path)
wave_record_path = Util.get_wave_record_path() + 'wave_ret_record\\'
output_path = Util.get_path_output()
file_exist = os.listdir(output_path)
file_list = [file_name_ for file_name_ in os.listdir(wave_record_path) if start_date<=file_name_.split('.')[0].split('_')[-1]<=end_date]
# file_list = [file_name_ for file_name_ in os.listdir(wave_record_path) if start_date<=file_name_.split('.')[0].split('_')[-1]<=end_date and file_name_ not in file_exist]
pool = multiprocessing.Pool(processes=7)
for wave_record_file_name in file_list:
print(wave_record_file_name, 'start', datetime.datetime.now())
output = []
date_str = wave_record_file_name.split('.')[0].split('_')[-1]
wave_record_one_day_all_stock = pd.read_csv(wave_record_path + wave_record_file_name)
total_num = len(wave_record_one_day_all_stock)
num = 0
stock_str = ''
for k, one_wave_row in wave_record_one_day_all_stock.iterrows():
# if one_wave_row['stock'] != 570: # todo
# continue
num += 1
if one_wave_row['wave_tot'] == 0:
one_wave_new = one_wave_row
else:
stock_str_new = str(one_wave_row['stock']).zfill(6)
if stock_str == stock_str_new:
pass
else:
stock_str = stock_str_new
tick_data_one_day_one_stock = TickdataOneDayOneStk(date_str, stock_str, data_framework)
one_wave_new = update_one_wave(one_wave_row, tick_data_one_day_one_stock)
output.append(one_wave_new)
print(date_str, one_wave_row['stock'], 'done', num/total_num, datetime.datetime.now())
output_df = pd.DataFrame(output)
output_df.to_csv(output_path + wave_record_file_name, index=False)
print(output_path+wave_record_file_name, 'done')