edate = dt.datetime.strptime(edate_str, "%d-%m-%Y")
# %%
if (load_data):
######## CREATE THE OBJECT AND LOAD THE DATA ##########
# Tell which company and which period we want
timeData = CTD.CTimeData(symbols[0], periods[0])
timeData.set_csv(storage_folder, file_name) # Load the data into the model
if (preprocessing_data):
timeData = tut.preprocess_data(timeData, sdate, edate)
## Get the valid trading days sorted
days_keys, day_dict = timeData.get_indexDictByDay()
Ndays = len(days_keys)
timeData_daily = tut.get_daily_timedata(timeData, symbols[0])
H, L, O, C, V = np.array(
timeData_daily.TD[["High", "Low", "Open", "Close", "Volume"]][:]).T
if (extract_features):
"""
Create the target for the regressing and classifier systems
"""
Target = bMl.diff(C).flatten() # Continuous target .Target[0] = NaN
Target_bin = np.zeros(Target.shape) # Binarized target
Target_bin[np.where(Target >= 0)] = 1
data_df = None
## Create Pandas Data Frame for the information of the ML problem
data_df = pd.DataFrame({
'Time': days_keys,
edate = dt.datetime.strptime(edate_str, "%d-%m-%Y")
if (load_data):
######## CREATE THE OBJECT AND LOAD THE DATA ##########
# Tell which company and which period we want
timeData = CTD.CTimeData(symbols[0],periods[0])
timeData.set_csv(storage_folder,file_name) # Load the data into the model
if (preprocessing_data):
timeData = tut.preprocess_data(timeData, sdate,edate)
## Get the valid trading days sorted
days_keys, day_dict = timeData.get_indexDictByDay()
Ndays = len(days_keys)
timeData_daily = tut.get_daily_timedata(timeData, symbols[0])
H,L,O,C,V = np.array(timeData_daily.TD[["High","Low","Open","Close","Volume"]][:]).T
"""
Create the target for the classifier:
"""
Target = bMl.diff(C).flatten() # Continuous target Target[0] = NaN
Target_bin = np.zeros(Target.shape) # Binarized
Target_bin[np.where(Target >=0)] = 1
## Create Pandas Data Frame for the information of the ML problem
data_df = pd.DataFrame({'Time': days_keys, 'Target_clas': Target_bin, 'Target_reg': Target}) # 'Current_diff': Target}
data_df.set_index('Time',inplace = True)