[GH-76] Add StochRSI and wave trend

Add StochRSI.  The default window is set to 14.
Use `StockDataFrame.RSI` to change it.

Add wave trand that includes two lines.  The default window of the ema
is set to `10` and `21`.
Use `StockDataFrame.WAVE_TREND_1` and `StockDataFrame.WAVE_TREND_2` to
change them.

stockstats.py

@@ -85,8 +85,13 @@ class StockDataFrame(pd.DataFrame):
 
     CCI = 14
 
+    RSI = 14
+
     VR = 26
 
+    WAVE_TREND_1 = 10
+    WAVE_TREND_2 = 21
+
     KAMA_SLOW = 34
     KAMA_FAST = 5
 
@@ -337,7 +342,7 @@ def _get_rsv(cls, df, window):
 
     # noinspection PyUnresolvedReferences
     @classmethod
-    def _get_rsi(cls, df, window):
+    def _get_rsi(cls, df, window=None):
         """ Calculate the RSI (Relative Strength Index) within N periods
 
         calculated based on the formula at:
@@ -347,6 +352,11 @@ def _get_rsi(cls, df, window):
         :param window: number of periods
         :return: None
         """
+        if window is None:
+            window = cls.RSI
+            column_name = 'rsi'
+        else:
+            column_name = 'rsi_{}'.format(window)
         window = cls.get_int_positive(window)
 
         change = cls._delta(df['close'], -1)
@@ -356,9 +366,56 @@ def _get_rsi(cls, df, window):
         n_ema = cls._smma(close_nm, window)
 
         rs_column_name = 'rs_{}'.format(window)
-        rsi_column_name = 'rsi_{}'.format(window)
         df[rs_column_name] = rs = p_ema / n_ema
-        df[rsi_column_name] = 100 - 100 / (1.0 + rs)
+        df[column_name] = 100 - 100 / (1.0 + rs)
+
+    @classmethod
+    def _get_stochrsi(cls, df, window=None):
+        """ Calculate the Stochastic RSI
+
+        calculated based on the formula at:
+        https://www.investopedia.com/terms/s/stochrsi.asp
+
+        :param df: data
+        :param window: number of periods
+        :return: None
+        """
+        if window is None:
+            window = cls.RSI
+            column_name = 'stochrsi'
+        else:
+            column_name = 'stochrsi_{}'.format(window)
+        window = cls.get_int_positive(window)
+
+        rsi = df['rsi_{}'.format(window)]
+        rsi_min = cls._mov_min(rsi, window)
+        rsi_max = cls._mov_max(rsi, window)
+
+        cv = (rsi - rsi_min) / (rsi_max - rsi_min)
+        df[column_name] = cv * 100
+
+    @classmethod
+    def _get_wave_trend(cls, df):
+        """ Calculate LazyBear's Wavetrend
+        Check the algorithm described below:
+        https://medium.com/@samuel.mcculloch/lets-take-a-look-at-wavetrend-with-crosses-lazybear-s-indicator-2ece1737f72f
+
+        n1: period of EMA on typical price
+        n2: period of EMA
+
+        :param df: data frame
+        :return: None
+        """
+        n1 = cls.WAVE_TREND_1
+        n2 = cls.WAVE_TREND_2
+
+        tp = cls._middle(df)
+        esa = cls._ema(tp, n1)
+        d = cls._ema((tp - esa).abs(), n1)
+        ci = (tp - esa) / (0.015 * d)
+        tci = cls._ema(ci, n2)
+        df["wt1"] = tci
+        df["wt2"] = cls._sma(tci, 4)
 
     @classmethod
     def _smma(cls, series, window):
@@ -1108,6 +1165,8 @@ def _get_cross(df, key):
     def __init_not_exist_column(cls, df, key):
         handlers = {
             ('change',): cls._get_change,
+            ('rsi',): cls._get_rsi,
+            ('stochrsi',): cls._get_stochrsi,
             ('rate',): cls._get_rate,
             ('middle',): cls._get_middle,
             ('boll', 'boll_ub', 'boll_lb'): cls._get_boll,
@@ -1128,6 +1187,7 @@ def __init_not_exist_column(cls, df, key):
             ('chop',): cls._get_chop,
             ('log-ret',): cls._get_log_ret,
             ('mfi',): cls._get_mfi,
+            ('wt1', 'wt2'): cls._get_wave_trend,
         }
         for names, handler in handlers.items():
             if key in names:

test.py

@@ -165,7 +165,6 @@ def test_column_min(self):
     def test_column_shift_positive(self):
         stock = self.get_stock_20day()
         close_s = stock['close_2_s']
-        print(close_s)
         assert_that(close_s.loc[20110118], equal_to(12.48))
         assert_that(close_s.loc[20110119], equal_to(12.48))
         assert_that(close_s.loc[20110120], equal_to(12.48))
@@ -413,13 +412,26 @@ def test_rsv_nan_value(self):
         assert_that(df['rsv_9'][0], equal_to(0.0))
 
     def test_get_rsi(self):
-        self._supor.get('rsi_6')
-        self._supor.get('rsi_12')
-        self._supor.get('rsi_24')
+        rsi = self._supor.get('rsi')
+        rsi_6 = self._supor.get('rsi_6')
+        rsi_12 = self._supor.get('rsi_12')
+        rsi_14 = self._supor.get('rsi_14')
+        rsi_24 = self._supor.get('rsi_24')
         idx = 20160817
-        assert_that(self._supor.loc[idx, 'rsi_6'], near_to(71.3114))
-        assert_that(self._supor.loc[idx, 'rsi_12'], near_to(63.1125))
-        assert_that(self._supor.loc[idx, 'rsi_24'], near_to(61.3064))
+        assert_that(rsi_6.loc[idx], near_to(71.3114))
+        assert_that(rsi_12.loc[idx], near_to(63.1125))
+        assert_that(rsi_24.loc[idx], near_to(61.3064))
+        assert_that(rsi.loc[idx], near_to(rsi_14.loc[idx]))
+
+    def test_get_stoch_rsi(self):
+        stock = self.get_stock_90day()
+        stoch_rsi = stock['stochrsi']
+        stoch_rsi_6 = stock['stochrsi_6']
+        stoch_rsi_14 = stock['stochrsi_14']
+        idx = 20110331
+        assert_that(stoch_rsi.loc[idx], near_to(67.0955))
+        assert_that(stoch_rsi_6.loc[idx], near_to(27.5693))
+        assert_that(stoch_rsi_14.loc[idx], near_to(stoch_rsi.loc[idx]))
 
     def test_get_wr(self):
         self._supor.get('wr_10')
@@ -576,3 +588,10 @@ def test_column_conflict(self):
         idx = 20110331
         assert_that(res['close_26_ema'].loc[idx], near_to(13.2488))
         assert_that(res['macd'].loc[idx], near_to(0.1482))
+
+    def test_wave_trend(self):
+        stock = self.get_stock_90day()
+        wt1, wt2 = stock['wt1'], stock['wt2']
+        idx = 20110331
+        assert_that(wt1.loc[idx], near_to(38.9610))
+        assert_that(wt2.loc[idx], near_to(31.6997))