def test_calc_wave_ratio(self):
cases=[
{"pre_price":10, "open":10.5, "high":11, "low":9},
{"pre_price":10, "open":7, "high":11, "low":9},
{"pre_price":10, "open":12, "high":11, "low":9},
{"pre_price":0, "open":10.5, "high":11, "low":9},
]
for case in cases:
try:
dict = wv.calc_wave_ratio(case["pre_price"], case["open"], case["high"], case["low"])
self.assertEqual(dict["min_ratio"], -0.15)
self.assertEqual(dict["max_ratio"], 0.05)
except ValueError as ve:
print(ve.message, "Test ValueError OK!")
except ZeroDivisionError as zde:
print(zde.message, "Test ZeroDivisionError OK!")
def export_ratio_table(code, start, end, thread_id):
# queue_lock.acquire()
ts.set_token(cfg.get_datayes_key())
mkt = ts.Market()
# print("exporting " + code + " from " + start + " to " + end)
st = time.time()
df = mkt.MktEqud(ticker=code, beginDate=start, endDate=end,
field='ticker,tradeDate,preClosePrice,openPrice,highestPrice,lowestPrice,closePrice')
print(" Thread {0} fetch online: {1}".format(thread_id, time.time()-st))
# queue_lock.release()
# df = ts.get_h_data(code, start, end)
# print(df)
wave_ratio_df = pd.DataFrame(columns=["max_ratio", "min_ratio"])
for i, row in df.iterrows():
dict = wv.calc_wave_ratio(row["preClosePrice"], row["openPrice"],
row["highestPrice"], row["lowestPrice"])
wave_ratio_df.loc[row["tradeDate"]] = dict
st = time.time()
idx_col = wv.calc_ratio_table_index_and_columns(max_ratio=0.03, min_ratio=-0.03)
index, columns = idx_col["index"], idx_col["columns"]
ratio_table = wv.calc_ratio_table(wave_ratio_df, index, columns)
print(" Thread {0} calc ratio table: {1}".format(thread_id, time.time()-st))
st = time.time()
length_ratio_df = wv.calc_length_ratio(ratio_table, len(wave_ratio_df.index))
print(" Thread {0} calc length ratio: {1}".format(thread_id, time.time()-st))
# write csv
st = time.time()
ratio_table.to_csv(cfg.get_ratio_table_path(code, start, end))
length_ratio_df.to_csv(cfg.get_length_ratio_path(code, start, end))
# print(" save csv: {0}".format(time.time()-st))
return length_ratio_df
