Minor updates to comment out unused code.

Author: rsesha

auto_ts/__init__.py

@@ -17,7 +17,7 @@ def warn(*args, **kwargs):
 import seaborn as sns  # type: ignore
 import matplotlib.pyplot as plt  # type: ignore
 
-# This gives an error when running from a python script. 
+# This gives an error when running from a python script.
 # Maybe, this should be set in the jupyter notebook directly.
 #get_ipython().magic('matplotlib inline')
 sns.set(style="white", color_codes=True)
@@ -107,12 +107,6 @@ def Auto_Timeseries(traindata, ts_column, target, sep=',', score_type='rmse',
         d_max = 1
         q_max = 3
     ################################
-    # Check: seasonal_order is not used anywhere in the code, hence commented for now.
-    # if type(seasonal_PDQ) == tuple:
-    #     seasonal_order = copy.deepcopy(seasonal_PDQ)
-    # else:
-    #     seasonal_order = (3, 1, 3)
-
     ########## This is where we start the loading of the data file ######################
     if isinstance(traindata, str):
         if traindata != '':
@@ -434,7 +428,7 @@ def Auto_Timeseries(traindata, ts_column, target, sep=',', score_type='rmse',
 #Defining AUTO_TIMESERIES here
 ##########################################################
 module_type = 'Running' if  __name__ == "__main__" else 'Imported'
-version_number = '0.0.20'
+version_number = '0.0.21'
 print("""Running Auto Timeseries version: %s...Call by using:
         auto_ts.Auto_Timeseries(traindata, ts_column,
                             target, sep,  score_type='rmse', forecast_period=5,

auto_ts/models/build_prophet.py

@@ -58,7 +58,7 @@ def build_prophet_model(ts_df, time_col, target, forecast_period, time_interval,
         time_int = 'D'
     elif time_interval in ['weeks', 'weekly', 'w']:
         time_int = 'W'
-        seasonal_period = 52
+        #seasonal_period = 52
     elif time_interval in ['qtr', 'quarter', 'q']:
         time_int = 'Q'
     elif time_interval in ['years', 'year', 'annual', 'y', 'a']:
@@ -68,7 +68,7 @@ def build_prophet_model(ts_df, time_col, target, forecast_period, time_interval,
     elif time_interval in ['minutes', 'minute', 'min', 'n']:
         time_int = 'M'
     elif time_interval in ['seconds', 'second', 'sec', 's']:
-        time_interval = 'S'
+        time_int = 'S'
     else:
         time_int = 'W'
     future = model.make_future_dataframe(periods=forecast_period, freq=time_int)

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="auto_ts",
-    version="0.0.20",
+    version="0.0.21",
     author="Ram Seshadri",
     # author_email="author@example.com",
     description="Automatically Build Multiple Time Series models fast - now with Facebook Prophet!",