def test_calc_ratio_table_index_and_columns(self):
dict = wv.calc_ratio_table_index_and_columns(max_ratio=0.02, min_ratio=-0.018)
index, columns = dict["index"], dict["columns"]
self.assertEqual(len(index), 180)
self.assertEqual(len(columns), 200)
self.assertEqual(index[1], "0.0001")
self.assertEqual(columns[151], "0.0151")
df = wv.calc_ratio_table(self.wave_ratio_df, index, columns)
self.assertEqual(df["0.0000"]["0.0000"], 4)
self.assertEqual(df["0.0001"]["0.0001"], 4)
self.assertEqual(df["0.0002"]["0.0002"], 3)
self.assertEqual(df["0.0002"]["0.0003"], 2)
self.assertEqual(df["0.0140"]["0.0140"], 1)
self.assertEqual(df["0.0190"]["0.0160"], 0)
# print(df)
df.to_csv("/home/chengang/Data/df.csv")
table = wv.calc_length_ratio(df, 4)
def test_calc_ratio_table_index_and_columns(self):
dict = wv.calc_ratio_table_index_and_columns(max_ratio=0.02,
min_ratio=-0.018)
index, columns = dict["index"], dict["columns"]
self.assertEqual(len(index), 180)
self.assertEqual(len(columns), 200)
self.assertEqual(index[1], "0.0001")
self.assertEqual(columns[151], "0.0151")
df = wv.calc_ratio_table(self.wave_ratio_df, index, columns)
self.assertEqual(df["0.0000"]["0.0000"], 4)
self.assertEqual(df["0.0001"]["0.0001"], 4)
self.assertEqual(df["0.0002"]["0.0002"], 3)
self.assertEqual(df["0.0002"]["0.0003"], 2)
self.assertEqual(df["0.0140"]["0.0140"], 1)
self.assertEqual(df["0.0190"]["0.0160"], 0)
# print(df)
df.to_csv("/home/chengang/Data/df.csv")
table = wv.calc_length_ratio(df, 4)
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
