def test_align():
# -------------------------------------------------------------------------------------
# input and pre-process demo data
ds = RemoteDataService()
ds.init_from_config(data_config)
raw, msg = ds.query_lb_fin_stat('income', '600000.SH', 20151225, 20170501,
'oper_rev')
assert msg == '0,'
# print(raw)
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
print(raw_idx)
df_ann = raw_idx.loc[pd.IndexSlice[:, :], 'ann_date']
df_ann = df_ann.unstack(level=1)
df_value = raw_idx.loc[pd.IndexSlice[:, :], 'oper_rev']
df_value = df_value.unstack(level=1)
date_arr = ds.query_trade_dates(20160101, 20170501)
df_close = pd.DataFrame(index=date_arr, columns=df_value.columns, data=1e3)
# -------------------------------------------------------------------------------------
# demo usage of parser
parser = Parser()
parser.register_function(
'Myfunc',
lambda x: x * 0 + 1) # simultaneously test register function and align
expr_formula = 'signal / Myfunc(close)'
expression = parser.parse(expr_formula)
for i in range(100):
df_res = parser.evaluate({
'signal': df_value,
'close': df_close
}, df_ann, date_arr)
# -------------------------------------------------------------------------------------
sec = '600000.SH'
"""
# print to validate results
print "\n======Expression Formula:\n{:s}".format(expr_formula)
print "\n======Report date, ann_date and evaluation value:"
tmp = pd.concat([df_ann.loc[:, sec], df_value.loc[:, sec]], axis=1)
tmp.columns = ['df_ann', 'df_value']
print tmp
print "\n======Selection of result of expansion:"
print "20161028 {:.4f}".format(df_res.loc[20161028, sec])
print "20161031 {:.4f}".format(df_res.loc[20161031, sec])
print "20170427 {:.4f}".format(df_res.loc[20170427, sec])
"""
assert abs(df_res.loc[20161028, sec] - 82172000000) < 1
assert abs(df_res.loc[20161031, sec] - 120928000000) < 1
assert abs(df_res.loc[20170427, sec] - 42360000000) < 1
def test_calendar():
ds = RemoteDataService()
ds.init_from_config(data_config)
res1 = ds.query_trade_dates(20121224, 20130201)
assert len(res1) == 27
day_zero = 20170102
res2 = ds.query_next_trade_date(day_zero)
assert res2 == 20170103
res2_last = ds.query_last_trade_date(res2)
assert res2_last == 20161230
res3 = ds.query_next_trade_date(20170104)
assert res3 == 20170105
res4 = ds.query_last_trade_date(res3)
assert res4 == 20170104
res11 = ds.query_trade_dates(20161224, 20170201)
assert len(res11) == 23
assert not ds.is_trade_date(20150101)
assert not ds.is_trade_date(20130501)
def test_calendar():
ds = RemoteDataService()
ds.init_from_config(data_config)
res1 = ds.query_trade_dates(20121224, 20130201)
assert len(res1) == 27
day_zero = 20170102
res2 = ds.query_next_trade_date(day_zero)
assert res2 == 20170103
res2_last = ds.query_last_trade_date(res2)
assert res2_last == 20161230
res3 = ds.query_next_trade_date(20170104)
assert res3 == 20170105
res4 = ds.query_last_trade_date(res3)
assert res4 == 20170104
res11 = ds.query_trade_dates(20161224, 20170201)
assert len(res11) == 23
assert not ds.is_trade_date(20150101)
assert not ds.is_trade_date(20130501)
def test_align():
# -------------------------------------------------------------------------------------
# input and pre-process demo data
ds = RemoteDataService()
ds.init_from_config(data_config)
raw, msg = ds.query_lb_fin_stat('income', '600000.SH', 20151225, 20170501, 'oper_rev')
assert msg == '0,'
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
df_ann = raw_idx.loc[pd.IndexSlice[:, :], 'ann_date']
df_ann = df_ann.unstack(level=1)
df_value = raw_idx.loc[pd.IndexSlice[:, :], 'oper_rev']
df_value = df_value.unstack(level=1)
date_arr = ds.query_trade_dates(20160101, 20170501)
df_close = pd.DataFrame(index=date_arr, columns=df_value.columns, data=1e3)
# -------------------------------------------------------------------------------------
# demo usage of parser
parser = Parser()
parser.register_function('Myfunc', lambda x: x * 0 + 1) # simultaneously test register function and align
expr_formula = 'signal / Myfunc(close)'
expression = parser.parse(expr_formula)
for i in range(100):
df_res = parser.evaluate({'signal': df_value, 'close': df_close}, df_ann, date_arr)
# -------------------------------------------------------------------------------------
sec = '600000.SH'
"""
# print to validate results
print "\n======Expression Formula:\n{:s}".format(expr_formula)
print "\n======Report date, ann_date and evaluation value:"
tmp = pd.concat([df_ann.loc[:, sec], df_value.loc[:, sec]], axis=1)
tmp.columns = ['df_ann', 'df_value']
print tmp
print "\n======Selection of result of expansion:"
print "20161028 {:.4f}".format(df_res.loc[20161028, sec])
print "20161031 {:.4f}".format(df_res.loc[20161031, sec])
print "20170427 {:.4f}".format(df_res.loc[20170427, sec])
"""
assert abs(df_res.loc[20161028, sec] - 82172000000) < 1
assert abs(df_res.loc[20161031, sec] - 120928000000) < 1
assert abs(df_res.loc[20170427, sec] - 42360000000) < 1
