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_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
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', '000001.SZ,600000.SH,601328.SH,601988.SH',
20160505, 20170505, fields='oper_rev,oper_cost')
#fp = '../output/test_align.csv'
#raw = pd.read_csv(fp)
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
# -------------------------------------------------------------------------------------
# get DataFrames
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)
# -------------------------------------------------------------------------------------
# get data array and align
# date_arr = ds.get_trade_date(20160325, 20170625)
date_arr = np.array([20160325, 20160328, 20160329, 20160330, 20160331, 20160401, 20160405, 20160406,
20160407, 20160408, 20160411, 20160412, 20160413, 20160414, 20160415, 20160418,
20160419, 20160420, 20160421, 20160422, 20160425, 20160426, 20160427, 20160428,
20160429, 20160503, 20160504, 20160505, 20160506, 20160509, 20160510, 20160511,
20160512, 20160513, 20160516, 20160517, 20160518, 20160519, 20160520, 20160523,
20160524, 20160525, 20160526, 20160527, 20160530, 20160531, 20160601, 20160602,
20160603, 20160606, 20160607, 20160608, 20160613, 20160614, 20160615, 20160616,
20160617, 20160620, 20160621, 20160622, 20160623, 20160624, 20160627, 20160628,
20160629, 20160630, 20160701, 20160704, 20160705, 20160706, 20160707, 20160708,
20160711, 20160712, 20160713, 20160714, 20160715, 20160718, 20160719, 20160720,
20160721, 20160722, 20160725, 20160726, 20160727, 20160728, 20160729, 20160801,
20160802, 20160803, 20160804, 20160805, 20160808, 20160809, 20160810, 20160811,
20160812, 20160815, 20160816, 20160817, 20160818, 20160819, 20160822, 20160823,
20160824, 20160825, 20160826, 20160829, 20160830, 20160831, 20160901, 20160902,
20160905, 20160906, 20160907, 20160908, 20160909, 20160912, 20160913, 20160914,
20160919, 20160920, 20160921, 20160922, 20160923, 20160926, 20160927, 20160928,
20160929, 20160930, 20161010, 20161011, 20161012, 20161013, 20161014, 20161017,
20161018, 20161019, 20161020, 20161021, 20161024, 20161025, 20161026, 20161027,
20161028, 20161031, 20161101, 20161102, 20161103, 20161104, 20161107, 20161108,
20161109, 20161110, 20161111, 20161114, 20161115, 20161116, 20161117, 20161118,
20161121, 20161122, 20161123, 20161124, 20161125, 20161128, 20161129, 20161130,
20161201, 20161202, 20161205, 20161206, 20161207, 20161208, 20161209, 20161212,
20161213, 20161214, 20161215, 20161216, 20161219, 20161220, 20161221, 20161222,
20161223, 20161226, 20161227, 20161228, 20161229, 20161230, 20170103, 20170104,
20170105, 20170106, 20170109, 20170110, 20170111, 20170112, 20170113, 20170116,
20170117, 20170118, 20170119, 20170120, 20170123, 20170124, 20170125, 20170126,
20170203, 20170206, 20170207, 20170208, 20170209, 20170210, 20170213, 20170214,
20170215, 20170216, 20170217, 20170220, 20170221, 20170222, 20170223, 20170224,
20170227, 20170228, 20170301, 20170302, 20170303, 20170306, 20170307, 20170308,
20170309, 20170310, 20170313, 20170314, 20170315, 20170316, 20170317, 20170320,
20170321, 20170322, 20170323, 20170324, 20170327, 20170328, 20170329, 20170330,
20170331, 20170405, 20170406, 20170407, 20170410, 20170411, 20170412, 20170413,
20170414, 20170417, 20170418, 20170419, 20170420, 20170421, 20170424, 20170425,
20170426, 20170427, 20170428, 20170502, 20170503, 20170504, 20170505, 20170508,
20170509, 20170510, 20170511, 20170512, 20170515, 20170516, 20170517, 20170518,
20170519, 20170522, 20170523, 20170524, 20170525, 20170526, 20170531, 20170601,
20170602, 20170605, 20170606, 20170607, 20170608, 20170609, 20170612, 20170613,
20170614, 20170615, 20170616, 20170619, 20170620, 20170621, 20170622, 20170623])
# df_res = align(df_ann, df_evaluate, date_arr)
res_align = align(df_value, df_ann, date_arr)
for symbol, ser_value in df_value.iteritems():
ser_ann = df_ann[symbol]
ann_date_last = 0
assert res_align.loc[: ser_ann.iat[0]-1, symbol].isnull().all()
for i in range(len(ser_value)):
value = ser_value.iat[i]
ann_date = ser_ann.iat[i]
if i+1 >= len(ser_value):
ann_date_next = 99999999
else:
ann_date_next = ser_ann.iat[i+1]
assert (res_align.loc[ann_date: ann_date_next-1, symbol] == value).all()
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',
'000001.SZ,600000.SH,601328.SH,601988.SH',
20160505,
20170505,
fields='oper_rev,oper_cost')
#fp = '../output/test_align.csv'
#raw = pd.read_csv(fp)
idx_list = ['report_date', 'symbol']
raw_idx = raw.set_index(idx_list)
raw_idx.sort_index(axis=0, level=idx_list, inplace=True)
# -------------------------------------------------------------------------------------
# get DataFrames
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)
# -------------------------------------------------------------------------------------
# get data array and align
# date_arr = ds.get_trade_date(20160325, 20170625)
date_arr = np.array([
20160325, 20160328, 20160329, 20160330, 20160331, 20160401, 20160405,
20160406, 20160407, 20160408, 20160411, 20160412, 20160413, 20160414,
20160415, 20160418, 20160419, 20160420, 20160421, 20160422, 20160425,
20160426, 20160427, 20160428, 20160429, 20160503, 20160504, 20160505,
20160506, 20160509, 20160510, 20160511, 20160512, 20160513, 20160516,
20160517, 20160518, 20160519, 20160520, 20160523, 20160524, 20160525,
20160526, 20160527, 20160530, 20160531, 20160601, 20160602, 20160603,
20160606, 20160607, 20160608, 20160613, 20160614, 20160615, 20160616,
20160617, 20160620, 20160621, 20160622, 20160623, 20160624, 20160627,
20160628, 20160629, 20160630, 20160701, 20160704, 20160705, 20160706,
20160707, 20160708, 20160711, 20160712, 20160713, 20160714, 20160715,
20160718, 20160719, 20160720, 20160721, 20160722, 20160725, 20160726,
20160727, 20160728, 20160729, 20160801, 20160802, 20160803, 20160804,
20160805, 20160808, 20160809, 20160810, 20160811, 20160812, 20160815,
20160816, 20160817, 20160818, 20160819, 20160822, 20160823, 20160824,
20160825, 20160826, 20160829, 20160830, 20160831, 20160901, 20160902,
20160905, 20160906, 20160907, 20160908, 20160909, 20160912, 20160913,
20160914, 20160919, 20160920, 20160921, 20160922, 20160923, 20160926,
20160927, 20160928, 20160929, 20160930, 20161010, 20161011, 20161012,
20161013, 20161014, 20161017, 20161018, 20161019, 20161020, 20161021,
20161024, 20161025, 20161026, 20161027, 20161028, 20161031, 20161101,
20161102, 20161103, 20161104, 20161107, 20161108, 20161109, 20161110,
20161111, 20161114, 20161115, 20161116, 20161117, 20161118, 20161121,
20161122, 20161123, 20161124, 20161125, 20161128, 20161129, 20161130,
20161201, 20161202, 20161205, 20161206, 20161207, 20161208, 20161209,
20161212, 20161213, 20161214, 20161215, 20161216, 20161219, 20161220,
20161221, 20161222, 20161223, 20161226, 20161227, 20161228, 20161229,
20161230, 20170103, 20170104, 20170105, 20170106, 20170109, 20170110,
20170111, 20170112, 20170113, 20170116, 20170117, 20170118, 20170119,
20170120, 20170123, 20170124, 20170125, 20170126, 20170203, 20170206,
20170207, 20170208, 20170209, 20170210, 20170213, 20170214, 20170215,
20170216, 20170217, 20170220, 20170221, 20170222, 20170223, 20170224,
20170227, 20170228, 20170301, 20170302, 20170303, 20170306, 20170307,
20170308, 20170309, 20170310, 20170313, 20170314, 20170315, 20170316,
20170317, 20170320, 20170321, 20170322, 20170323, 20170324, 20170327,
20170328, 20170329, 20170330, 20170331, 20170405, 20170406, 20170407,
20170410, 20170411, 20170412, 20170413, 20170414, 20170417, 20170418,
20170419, 20170420, 20170421, 20170424, 20170425, 20170426, 20170427,
20170428, 20170502, 20170503, 20170504, 20170505, 20170508, 20170509,
20170510, 20170511, 20170512, 20170515, 20170516, 20170517, 20170518,
20170519, 20170522, 20170523, 20170524, 20170525, 20170526, 20170531,
20170601, 20170602, 20170605, 20170606, 20170607, 20170608, 20170609,
20170612, 20170613, 20170614, 20170615, 20170616, 20170619, 20170620,
20170621, 20170622, 20170623
])
# df_res = align(df_ann, df_evaluate, date_arr)
res_align = align(df_value, df_ann, date_arr)
for symbol, ser_value in df_value.iteritems():
ser_ann = df_ann[symbol]
ann_date_last = 0
assert res_align.loc[:ser_ann.iat[0] - 1, symbol].isnull().all()
for i in range(len(ser_value)):
value = ser_value.iat[i]
ann_date = ser_ann.iat[i]
if i + 1 >= len(ser_value):
ann_date_next = 99999999
else:
ann_date_next = ser_ann.iat[i + 1]
assert (res_align.loc[ann_date:ann_date_next - 1,
symbol] == value).all()
