def get_trading_time(target_list: 'list',
frequency: 'str',
fre_num: 'int',
begin_date,
end_date=''):
if isinstance(target_list, str):
target_list = [target_list]
new_targets = todictmc(target_list)
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
new_end_date = to_int_now_date('%Y%m%d')
else:
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if frequency in ('day', 'week', 'month') and fre_num != 1:
raise ValueError(text.ERROR_INPUT_FREQUENCY_FREQNUM)
if 0 < new_end_date < new_begin_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
t, d = _history.get_trading_time(new_targets, frequency, new_begin_date,
new_end_date, fre_num)
if gv.freuency_to_int(frequency) >= gv.KFreq_Day:
d = np.arange(0, t.size, 1, dtype=np.int)
else:
d -= 1
return history_cvt.convert_trading_time_to_df(t, d)
def get_code_list(block: 'str', date=''):
blocks = block.strip().split(',')
if isinstance(date, str) and date.strip() == '':
new_date = to_int_now_date('%Y%m%d')
else:
new_date = convert_str_or_datetime_to_int_date(date)
ls = _history.get_code_list(blocks, new_date)
return history_cvt.convert_code_list_to_df(ls)
def _gen_run_factor_code_template(strategy_name, file_path=None):
_code_template = """
# -*- coding: utf-8 -*-
from atrader.calcfactor import *
import numpy as np
import random
def init(context: 'ContextFactor'):
reg_kdata('day', 1)
def calc_factor(context: 'ContextFactor'):
return np.array([random.gauss(0, 1) for _ in range(len(context.target_list))]).T
if __name__ == '__main__':
run_factor(factor_name='{STRATEGY_NAME}',
file_path='.',
targets='SZ50',
begin_date='{BEGIN_DATE}',
end_date='{END_DATE}',
fq=enums.FQ_FORWARD)
"""
ls = _code_template.format(
STRATEGY_NAME=strategy_name,
BEGIN_DATE=int_date_predate(to_int_now_date(), 10, out_fmt='%Y-%m-%d'),
END_DATE=to_int_now_date(fmt='%Y-%m-%d')).splitlines(
keepends=False)[1:]
context = '\n'.join([line[4:] for line in ls])
if file_path is not None:
with open(file_path, 'w', encoding='utf-8') as fp:
fp.write(context)
return context
def get_code_list_set(block, begin_date, end_date):
blocks = block.strip().split(',')
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
new_end_date = to_int_now_date('%Y%m%d')
else:
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if 0 < new_end_date < new_begin_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
ls = _history.get_code_list_set(blocks, new_begin_date, new_end_date)
return history_cvt.convert_code_list_set_to_df(ls)
def get_trading_days(market: 'str', begin_date, end_date=''):
# TODO market: 支持数字货币
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
new_end_date = to_int_now_date('%Y%m%d')
else:
new_end_date = convert_str_or_datetime_to_int_date(end_date)
if new_begin_date > new_end_date:
return None
result = _history.get_trading_days_condition(market, new_begin_date,
new_end_date)
if result.size < 1:
return None
return history_cvt.convert_trading_days_to_np_datetime(result)
def get_kdata_n(target_list: 'list',
frequency: 'str',
fre_num: 'int',
n: 'int',
end_date: 'str',
fq=0,
fill_up=False,
df=False,
sort_by_date=False):
if isinstance(target_list, str):
target_list = [target_list]
if len(target_list) < 1:
raise ValueError(
text.ERROR_INPUT_EMPTY_PARAM.format(PARAMNAME='target_list'))
if isinstance(end_date, str) and end_date.strip() == '':
end_date = to_int_now_date('%Y%m%d')
else:
end_date = convert_str_or_datetime_to_int_date(end_date)
new_targets = todictmc(target_list)
fq = convert_internal_fq_to_atcore(fq)
if frequency in ('day', 'week', 'month') and fre_num != 1:
raise ValueError(text.ERROR_INPUT_FREQUENCY_FREQNUM)
results = [None] * len(new_targets)
for idx, target in enumerate(new_targets):
kdata = _history.get_k_data_n([target], frequency, fre_num, n,
end_date, fill_up, fq)
results[idx] = history_cvt.convert_k_data_to_df(
kdata[0], target_list[idx],
cnt.env.get_target_type(todotmc(target)))
if df:
data_df = pd.concat(results, ignore_index=True) # type: pd.DataFrame
if sort_by_date:
data_df = data_df.sort_values(
'time', ascending=True,
na_position='first') # type: pd.DataFrame
data_df.index = range(data_df.shape[0])
return data_df
else:
return {target: results[idx] for idx, target in enumerate(target_list)}
def get_factor_by_day(factor_list: 'list', target_list: 'list', date=''):
if isinstance(factor_list, str):
factor_list = [factor_list]
if isinstance(target_list, str):
target_list = [target_list]
targets = check_target(todictmc(target_list))
if date == '':
new_date = to_int_now_date()
else:
new_date = convert_str_or_datetime_to_int_date(date)
check_begin_end_date(new_date, new_date)
factor_dict = _factors.get_factor_by_day(factor_list, targets, new_date)
factor_df = factor_cvt.convert_factor_by_day_to_df(
factor_dict) if factor_dict is not None else None
return factor_df
def get_main_contract(main_code: 'str', begin_date, end_date):
begin_date = convert_str_or_datetime_to_int_date(begin_date)
if isinstance(end_date, str) and end_date.strip() == '':
end_date = to_int_now_date('%Y%m%d')
else:
end_date = convert_str_or_datetime_to_int_date(end_date)
new_targets = todictmc(main_code)
if begin_date > end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
ls = _history.get_main_contract(new_targets['Market'], new_targets['Code'],
begin_date, end_date)
ls = [
t for t in ls
if str.lower(t['TargetIns']) != str.lower(new_targets['Code'])
]
return history_cvt.convert_main_contract_to_df(ls, new_targets['Market'])
def get_history_instruments(target_list: 'list',
begin_date,
end_date='',
df=False,
sort_by_date=True):
if isinstance(target_list, str):
target_list = [target_list]
targets = check_target(todictmc(target_list))
new_begin_date = convert_str_or_datetime_to_int_date(begin_date)
new_end_date = to_int_now_date(
) if end_date == '' else convert_str_or_datetime_to_int_date(end_date)
if begin_date != 0 and new_begin_date > new_end_date:
raise ValueError(text.ERROR_INPUT_BEGIN_GT_ENDDATE)
data_matrix = _history.get_history_instruments(targets, new_begin_date,
new_end_date)
return history_cvt.convert_history_instrument_matrix_to_output(
target_list, data_matrix, df, sort_by_date)
def _gen_run_back_test_code_template(strategy_name, file_path=None):
_code_template = """
# -*- coding: utf-8 -*-
from atrader import *
def double_mean(context: 'Context'):
len1 = context.len1
len2 = context.len2
max_len = max(len1, len2)
target_num = len(context.target_list)
value = np.full((target_num, 1), np.nan)
df_data = get_reg_kdata(target_num, target_indices=list(range(target_num)),
length=max_len, fill_up=True, df=True) # type: pd.DataFrame
close_s = df_data['close'] # type: pd.Series
for i in range(target_num):
close_item = close_s.iloc[(i * max_len):(i + 1) * max_len]
if close_item.shape[0] >= max(len1, len2):
mean1 = np.nanmean(close_item.iloc[-len1:], dtype=np.float64)
mean2 = np.nanmean(close_item.iloc[-len2:], dtype=np.float64)
if mean1 - mean2 > 0.000001:
value[i] = 1
if mean2 - mean1 > 0.000001:
value[i] = 2
return value
def init(context: 'Context'):
context.len1 = 5
context.len2 = 20
reg_kdata('min', 1)
reg_userindi(double_mean)
def on_data(context: 'Context'):
positions = context.account(0).positions
volume_sub = positions['volume_long'] - positions['volume_short'] # type: pd.Series
value = get_reg_userindi(context.reg_userindi[0], 1) # type: pd.DataFrame
for idx, _ in enumerate(context.target_list):
if volume_sub[idx] <= 0 and value.loc[0, 'value'][idx] == 1:
order_volume(0, idx, 100, enums.ORDERSIDE_BUY, enums.ORDERPOSITIONEFFECT_OPEN, enums.ORDERTYPE_MARKET, 0)
elif volume_sub[idx] >= 0 and value.loc[0, 'value'][idx] == 2:
order_volume(0, idx, 100, enums.ORDERSIDE_SELL, enums.ORDERPOSITIONEFFECT_CLOSE, enums.ORDERTYPE_MARKET, 0)
if __name__ == '__main__':
targets = ['szse.000001', 'sse.600000', 'dce.a0000', 'shfe.RB0000', 'cffex.if0000']
run_backtest(strategy_name='{STRATEGY_NAME}',
file_path='.',
target_list=targets,
frequency='min',
fre_num=1,
begin_date='{BEGIN_DATE}',
end_date='{END_DATE}',
fq=enums.FQ_NA)
"""
ls = _code_template.format(
STRATEGY_NAME=strategy_name,
BEGIN_DATE=int_date_predate(to_int_now_date(), 10, out_fmt='%Y-%m-%d'),
END_DATE=to_int_now_date(fmt='%Y-%m-%d')).splitlines(
keepends=False)[1:]
context = '\n'.join([line[4:] for line in ls])
if file_path is not None:
with open(file_path, 'w', encoding='utf-8') as fp:
fp.write(context)
return context