Added the boilerplate code for the deseasonalization of data.

toarstats/trends/interface.py

@@ -6,6 +6,7 @@ calculate_trend - calculate the trend using the requested method
 
 from toarstats.trends.ols import ols
 from toarstats.trends.quant_reg import quant_reg
+from toarstats.trends.utils import deseasonalize
 
 
 def calculate_trend(method, data, formula="value ~ datetime", quantiles=None):
@@ -30,14 +31,15 @@ def calculate_trend(method, data, formula="value ~ datetime", quantiles=None):
     :return: The result of the fit or a list of fit results if
              ``method="quant"`` and multiple quantiles are given
     """
+    deseasonalized_data = deseasonalize(data)
     if method == "OLS":
-        fit = ols(data, formula)
+        fit = ols(deseasonalized_data, formula)
     elif method == "quant":
         try:
-            fit = [quant_reg(data, formula, quantile)
+            fit = [quant_reg(deseasonalized_data, formula, quantile)
                    for quantile in quantiles]
         except TypeError:
-            fit = quant_reg(data, formula, quantiles)
+            fit = quant_reg(deseasonalized_data, formula, quantiles)
     else:
         raise ValueError(f"{method} is not recognized, must be 'OLS' or"
                          " 'quant'")

toarstats/trends/utils.py

+"""This module contains helper functions for the trends subpackage.
+
+This module contains the following function:
+deseasonalize - calculate the trend using the requested method
+"""
+
+
+def deseasonalize(data):
+    """Deseasonalize the data.
+
+    :param data: data containing a list of date time values and
+                 associated parameter values
+
+    :return: The deseasonalized data
+    """
+    return data