new version

Author: philippe-ostiguy

indicator.py

@@ -1,4 +1,4 @@
-"""Return the values of the indicator of our choice through the desired timeframe and lenght"""
+"""Return the values of the indicator of our choice through the desired timeframe and interval"""
 
 import indicators.regression.linear_regression as lr
 import indicators.regression.mann_kendall as mk
@@ -11,19 +11,22 @@ class Indicator(InitOp):
     def __init__(self):
         super().__init__()
 
-
     def __call__(self):
         super().__call__()
 
     def calcul_indicator(self):
-
         """Function that return the value of an indicator through desired period and the calculation lenght of the
         indicator
 
-        The indicator always take into account the value of price for the same row. Ex: We are at row 99, the indicator
-        will take into account the data for row 99 then write the value on row 99. Basically, we have to enter or
-        exit the market (or exit) on the next row (value)
+        The indicator always take into account the value of the price for the same row.
+        Ex: We are at row 99, the indicator will take into account the data for row 99 then write the value on row 99.
+        Basically, we have to enter or exit the market (or exit) on the next row (value)
+
+        The function iterate through the indicators in `self.indicator` and through the range of `self.series`,defined
+        in `init_operations.py` and function `init_series()`. Then it calculates the value of the indicator using
+        the subseries `self.sous_series`.
         """
+
         super().__call__()
         rg = lr.RegressionSlopeStrenght(self.series,self)
         mk_ = mk.MannKendall(self.series,self)

init_operations.py

@@ -1,4 +1,4 @@
-"""Class with functions that initialize the program"""
+"""Module to easily reinitiliaze values when needed """
 
 from initialize import Initialize
 from manip_data import ManipData as md
@@ -15,18 +15,18 @@ def __call__(self):
 
 
     def reset_value(self):
-        """Value that must be reseted if we run walk-foward analysis"""
+        """Function to reset the dictionary that contains the trading journal (entry, exit, return).
+
+         We need to do that when we optimize, ie when `self.is_walkfoward` is `True` """
         self.trades_track = pd.DataFrame(columns=[self.entry_row, self.entry_level, self.exit_row, self.exit_level, \
                                                   self.trade_return])
 
     def init_series(self):
-        """Function to get the data as Dataframe"""
+        """Function that extract data from csv to a pandas Dataframe"""
 
-        self.series = md.csv_to_pandas(self.date_name, self.date_debut, self.date_fin, self.name,self.directory,
+        self.series = md.csv_to_pandas(self.date_name, self.start_date, self.end_date, self.name, self.directory,
                             self.asset, ordinal_name=self.date_ordinal_name, is_fx=self.is_fx, dup_col = self.dup_col)
 
-        t = 5
-
         """
         if self.is_detrend:
             self.series_test = md.de_trend(self.series,self.period, self.p_value,self.date_name,