Update doc strings for functions

README.md

@@ -17,6 +17,7 @@ Bollinger Bands
   -Lower Bollinger Band
   -Bandwidth
   -Percent Bandwidth
+  -Range
 Chaikin Money Flow
 Chande Momentum Oscillator
 Commodity Channel Index

py_ti/accumulation_distribution.py

@@ -4,7 +4,9 @@
 
 def accumulation_distribution(close_data, high_data, low_data, volume):
     """
-    Accumulation/Distribution
+    Accumulation/Distribution.
+
+    Formula:
     A/D = (Ct - Lt) - (Ht - Ct) / (Ht - Lt) * Vt + A/Dt-1
     """
     catch_errors.check_for_input_len_diff(

py_ti/aroon.py

@@ -6,6 +6,8 @@
 def aroon_up(data, period):
     """
     Aroon Up.
+
+    Formula:
     AROONUP = (((PERIOD) - (PERIODS since PERIOD high)) / (PERIOD)) * 100
     """
     catch_errors.check_for_period_error(data, period)
@@ -25,6 +27,8 @@ def aroon_up(data, period):
 def aroon_down(data, period):
     """
     Aroon Down.
+
+    Formula:
     AROONDWN = (((PERIOD) - (PERIODS SINCE PERIOD LOW)) / (PERIOD)) * 100
     """
     catch_errors.check_for_period_error(data, period)

py_ti/average_true_range.py

@@ -5,6 +5,8 @@
 def average_true_range(close_data, period):
     """
     Average True Range.
+
+    Formula:
     ATRt = ATRt-1 * (n - 1) + TRt / n
     """
     tr = true_range(close_data, period)

py_ti/average_true_range_percent.py

@@ -8,6 +8,8 @@
 def average_true_range_percent(close_data, period):
     """
     Average True Range Percent.
+
+    Formula:
     ATRP = (ATR / CLOSE) * 100
     """
     catch_errors.check_for_period_error(close_data, period)

py_ti/bollinger_bands.py

@@ -6,7 +6,13 @@
     )
 
 
-def upper_bollinger_band(data, period, std=2.0):
+def upper_bollinger_band(data, period, std_mult=2.0):
+    """
+    Upper Bollinger Band.
+
+    Formula:
+    u_bb = SMA(t) + STD(SMA(t-n:t)) * std_mult
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)
@@ -15,27 +21,34 @@ def upper_bollinger_band(data, period, std=2.0):
     upper_bb = []
     for idx in range(len(data) - period + 1):
         std_dev = np.std(data[idx:idx + period])
-        upper_bb.append(simple_ma[idx] + std_dev * std)
+        upper_bb.append(simple_ma[idx] + std_dev * std_mult)
     upper_bb = fill_for_noncomputable_vals(data, upper_bb)
 
     return np.array(upper_bb)
 
 
 def middle_bollinger_band(data, period, std=2.0):
+    """
+    Middle Bollinger Band.
+
+    Formula:
+    m_bb = sma()
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)
-    simple_ma = sma(data, period)[period-1:]
-
-    middle_bb = []
-    for idx in range(len(data) - period + 1):
-        middle_bb.append(simple_ma[idx])
-    middle_bb = fill_for_noncomputable_vals(data, middle_bb)
+    mid_bb = sma(data, period)
 
-    return np.array(middle_bb)
+    return mid_bb
 
 
 def lower_bollinger_band(data, period, std=2.0):
+    """
+    Lower Bollinger Band.
+
+    Formula:
+    u_bb = SMA(t) - STD(SMA(t-n:t)) * std_mult
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)
@@ -51,6 +64,12 @@ def lower_bollinger_band(data, period, std=2.0):
 
 
 def bandwidth(data, period, std=2.0):
+    """
+    Bandwidth.
+
+    Formula:
+    bw = u_bb - l_bb / m_bb
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)
@@ -63,6 +82,12 @@ def bandwidth(data, period, std=2.0):
 
 
 def bb_range(data, period, std=2.0):
+    """
+    Range.
+
+    Formula:
+    bb_range = u_bb - l_bb
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)
@@ -73,6 +98,12 @@ def bb_range(data, period, std=2.0):
 
 
 def percent_bandwidth(data, period, std=2.0):
+    """
+    Percent Bandwidth.
+
+    Formula:
+    %_bw = data() - l_bb() / bb_range()
+    """
     catch_errors.check_for_period_error(data, period)
 
     period = int(period)

py_ti/catch_errors.py

@@ -1,12 +1,28 @@
 
 def check_for_period_error(data, period):
+    """
+    Check for Period Error.
+
+    This method checks if the developer is trying to enter a period that is
+    larger than the data set being entered. If that is the case an exception is
+    raised with a custom message that informs the developer that their period
+    is greater than the data set.
+    """
     period = int(period)
     data_len = len(data)
     if data_len < period:
         raise Exception("Error: data_len < period")
 
 
 def check_for_input_len_diff(*args):
+    """
+    Check for Input Length Difference.
+
+    This method checks if multiple data sets that are inputted are all the same
+    size. If they are not the same length an error is raised with a custom
+    message that informs the developer that the data set's lengths are not the
+    same.
+    """
     arrays_len = map(lambda arr: len(arr), args)
     if not all(a == arrays_len[0] for a in arrays_len):
         err_msg = ("Error: mismatched data lengths, check to ensure that all "

py_ti/chaikin_money_flow.py

@@ -6,6 +6,8 @@
 def chaikin_money_flow(close_data, high_data, low_data, volume, period):
     """
     Chaikin Money Flow.
+
+    Formula:
     CMF = SUM[(((Cn - Ln) - (Hn - Cn)) / (Hn - Ln)) * V] / SUM(Vn)
     """
     catch_errors.check_for_input_len_diff(

py_ti/chande_momentum_oscillator.py

@@ -6,6 +6,9 @@
 def chande_momentum_oscillator(close_data, period):
     """
     Chande Momentum Oscillator.
+
+    Formula:
+    cmo = 100 * ((sum_up - sum_down) / (sum_up + sum_down))
     """
     catch_errors.check_for_period_error(close_data, period)
 

py_ti/commodity_channel_index.py

@@ -9,6 +9,8 @@
 def commodity_channel_index(close_data, high_data, low_data, period):
     """
     Commodity Channel Index.
+
+    Formula:
     CCI = (TP - SMA(TP)) / (0.015 * Mean Deviation)
     """
     catch_errors.check_for_input_len_diff(close_data, high_data, low_data)

py_ti/detrended_price_oscillator.py

@@ -6,6 +6,8 @@
 def detrended_price_oscillator(data, period):
     """
     Detrended Price Oscillator.
+
+    Formula:
     DPO = DATA[i] - Avg(DATA[period/2 + 1])
     """
     catch_errors.check_for_period_error(data, period)

py_ti/directional_indicators.py

@@ -11,6 +11,8 @@
 def calculate_up_moves(high_data):
     """
     Up Move.
+
+    Formula:
     UPMOVE = Ht - Ht-1
     """
     up_moves = map(
@@ -23,6 +25,8 @@ def calculate_up_moves(high_data):
 def calculate_down_moves(low_data):
     """
     Down Move.
+
+    Formula:
     DWNMOVE = Lt-1 - Lt
     """
     down_moves = map(
@@ -34,7 +38,9 @@ def calculate_down_moves(low_data):
 
 def positive_directional_movement(high_data, low_data):
     """
-    Positive Directional Movement (+DM)
+    Positive Directional Movement (+DM).
+
+    Formula:
     +DM: if UPMOVE > DWNMOVE and UPMOVE > 0 then +DM = UPMOVE else +DM = 0
     """
     catch_errors.check_for_input_len_diff(high_data, low_data)
@@ -53,7 +59,9 @@ def positive_directional_movement(high_data, low_data):
 
 def negative_directional_movement(high_data, low_data):
     """
-    Negative Directional Movement (-DM)
+    Negative Directional Movement (-DM).
+
+
     -DM: if DWNMOVE > UPMOVE and DWNMOVE > 0 then -DM = DWNMOVE else -Dm = 0
     """
     catch_errors.check_for_input_len_diff(high_data, low_data)
@@ -72,7 +80,9 @@ def negative_directional_movement(high_data, low_data):
 
 def positive_directional_index(close_data, high_data, low_data, period):
     """
-    Positive Directional Index (+DI)
+    Positive Directional Index (+DI).
+
+    Formula:
     +DI = 100 * SMMA(+DM) / ATR
     """
     catch_errors.check_for_input_len_diff(close_data, high_data, low_data)
@@ -85,7 +95,9 @@ def positive_directional_index(close_data, high_data, low_data, period):
 
 def negative_directional_index(close_data, high_data, low_data, period):
     """
-    Negative Directional Index (-DI)
+    Negative Directional Index (-DI).
+
+    Formula:
     -DI = 100 * SMMA(-DM) / ATR
     """
     catch_errors.check_for_input_len_diff(close_data, high_data, low_data)
@@ -99,6 +111,8 @@ def negative_directional_index(close_data, high_data, low_data, period):
 def average_directional_index(close_data, high_data, low_data, period):
     """
     Average Directional Index.
+
+    Formula:
     ADX = 100 * SMMA(abs((+DI - -DI) / (+DI + -DI)))
     """
     avg_di = (abs(

py_ti/double_exponential_moving_average.py

@@ -8,6 +8,7 @@ def double_exponential_moving_average(data, period):
     """
     Double Exponential Moving Average.
 
+    Formula:
     DEMA = 2*EMA - EMA(EMA)
     """
     catch_errors.check_for_period_error(data, period)

py_ti/double_smoothed_stochastic.py

@@ -8,7 +8,10 @@
 
 def double_smoothed_stochastic(data, period):
     """
-    Double Smoothed Stochastic
+    Double Smoothed Stochastic.
+
+    Formula:
+    dss = 100 *  EMA(Close - Lowest Low) / EMA(Highest High - Lowest Low)
     """
     catch_errors.check_for_period_error(data, period)
     lows = map(

py_ti/exponential_moving_average.py

@@ -6,10 +6,11 @@ def exponential_moving_average(data, period):
     """
     Exponential Moving Average.
 
-    Formula: p0 + (1 - w) * p1 + (1 - w)^2 * p2 + (1 + w)^3 * p3 +...
+    Formula:
+    p0 + (1 - w) * p1 + (1 - w)^2 * p2 + (1 + w)^3 * p3 +...
                 /   1 + (1 - w) + (1 - w)^2 + (1 - w)^3 +...
 
-            where: w = 2 / (N + 1)
+    where: w = 2 / (N + 1)
     """
     catch_errors.check_for_period_error(data, period)
     emas = map(

py_ti/hull_moving_average.py

@@ -8,6 +8,8 @@
 def hull_moving_average(data, period):
     """
     Hull Moving Average.
+
+    Formula:
     HMA = WMA(2*WMA(n/2) - WMA(n)), sqrt(n)
     """
     catch_errors.check_for_period_error(data, period)

py_ti/ichimoku_cloud.py

@@ -22,6 +22,8 @@ def conversion_base_line_helper(data, period):
 def tenkansen(data, period=9):
     """
     TenkanSen (Conversion Line)
+
+    Formula:
     (H + L) / 2  :: default period=9
     """
     ts = conversion_base_line_helper(data, period)
@@ -31,6 +33,8 @@ def tenkansen(data, period=9):
 def kijunsen(data, period=26):
     """
     KijunSen (Base Line)
+
+    Formula:
     (H + L) / 2  :: default period=26
     """
     ks = conversion_base_line_helper(data, period)
@@ -40,6 +44,8 @@ def kijunsen(data, period=26):
 def chiku_span(data):
     """
     Chiku Span (Lagging Span)
+
+    Formula:
     Close shifted back 26 bars
     """
     cs = data[25::]
@@ -49,6 +55,8 @@ def chiku_span(data):
 def senkou_a(data):
     """
     Senkou A (Leading Span A)
+
+    Formula:
     (TenkanSen + KijunSen) / 2 :: Shift Forward 26 bars
     """
     sa = (tenkansen(data) + kijunsen(data)) / 2
@@ -61,6 +69,8 @@ def senkou_a(data):
 def senkou_b(data, period=52):
     """
     Senkou B (Leading Span B)
+
+    Formula:
     (H + L) / 2  :: default period=52 :: shifted forward 26 bars
     """
     sb = conversion_base_line_helper(data, period)