def get_latest_temp_datas(write_file_name=fc.ALL_TEMP_FILE,
data_dir=fc.ALL_TEMP_DIR,
files=[]):
"""
获取所有回测最后一个K线的数据：特定目录下
"""
#columns = ['date', 'close', 'id', 'trade', 'p_change', 'position', 'operation', 's_price', 'b_price', 'profit', 'cum_prf', 'fuli_prf', 'hold_count']
columns = pds.get_data_columns(dest_dir=data_dir)
#df = combine_file(tail_num=1,dest_dir=data_dir,keyword='bs_',prefile_slip_num=3,columns=columns)
df = combine_file(tail_num=1,
dest_dir=data_dir,
keyword='',
prefile_slip_num=0,
columns=columns,
file_list=files)
if df.empty:
return df
df['counts'] = df.index
df = df[columns + ['counts', 'code']]
df['code'] = df['code'].apply(lambda x: pds.format_code(x))
df['name'] = df['code'].apply(
lambda x: pds.format_name_by_code(x, CHINESE_DICT))
df = df.set_index('code')
if write_file_name:
df.to_csv(write_file_name, encoding='utf-8')
return df
def get_latest_yh_k_stocks(write_file_name=fc.ALL_YH_KDATA_FILE,
data_dir=fc.YH_SOURCE_DATA_DIR):
"""
获取所有银河最后一个K线的数据：特定目录下
"""
columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'amount']
columns = pds.get_data_columns(dest_dir=data_dir)
df = combine_file(tail_num=1,
dest_dir=data_dir,
keyword='',
prefile_slip_num=0,
columns=columns)
if df.empty:
return df
df['counts'] = df.index
df = df[['date', 'open', 'high', 'low', 'close', 'volume', 'amount'] +
['counts', 'code']]
df['code'] = df['code'].apply(lambda x: pds.format_code(x))
df['name'] = df['code'].apply(
lambda x: pds.format_name_by_code(x, CHINESE_DICT))
df = df.set_index('code')
"""
if CHINESE_DICT:#添加中文代码
try:
tail_df['name'] = CHINESE_DICT[prefile_name]
except:
tail_df['name'] = '某指数'
"""
if write_file_name:
try:
df.to_csv(write_file_name, encoding='utf-8')
except Exception as e:
print('get_latest_yh_k_stocks： ', e)
return df
def get_latest_yh_k_stocks_from_csv(file_name=fc.ALL_YH_KDATA_FILE):
"""
获取股票K线数据，数据来源银河证券
"""
#file_name = 'C:/work/result/all_yh_stocks.csv'
#columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'amount']+['counts','code']
columns = pds.get_data_columns(
dest_dir=fc.YH_SOURCE_DATA_DIR) + ['counts', 'code']
#try:
if True:
df = pd.read_csv(file_name) #,usecols=columns)
#print(df)
#print(type(df['code']))
df['code'] = df['name'].apply(lambda x: pds.format_code(x))
df['name'] = df['code'].apply(
lambda x: pds.format_name_by_code(x, CHINESE_DICT))
df = df.set_index('code')
return df
def get_all_regress_summary(given_stocks=[],
confirm=0.01,
dest_file=fc.ALL_SUMMARY_FILE):
all_result_df = tds.pd.DataFrame({})
"""
latest_temp_df = tds.pd.read_csv( fc.ALL_TEMP_FILE)
latest_temp_df['code'] = latest_temp_df['code'].apply(lambda x: pds.format_code(x))
stock_codes = latest_temp_df['code'].values.tolist()
latest_temp_df = latest_temp_df.set_index('code')
#print(latest_temp_df.ix['000014'].date)
"""
#given_stocks = ['000001','000002']
for stock_symbol in given_stocks:
s_stock = tds.Stockhistory(stock_symbol,
'D',
test_num=0,
source='yh',
rate_to_confirm=confirm)
result_series = s_stock.get_regression_result(
rate_to_confirm=confirm,
refresh_regression=False,
from_csv=True,
bs_csv_dir=fc.ALL_BACKTEST_DIR,
temp_csv_dir=fc.ALL_TEMP_DIR)
if not result_series.empty:
test_result_df = tds.pd.DataFrame({stock_symbol: result_series}).T
all_result_df = all_result_df.append(test_result_df,
ignore_index=False)
if dest_file:
try:
all_result_df['code'] = all_result_df.index
all_result_df['name'] = all_result_df['code'].apply(
lambda x: pds.format_name_by_code(x, CHINESE_DICT))
del all_result_df['code']
#dest_file = 'D:/work/result/all_summary1.csv'
all_result_df.to_csv(dest_file, encoding='utf-8')
except:
pass
return all_result_df