Added OLS and quantile regression.

toarstats/trends/interface.py

@@ -4,7 +4,8 @@ This module contains the following function:
 calculate_trend - calculate the trend using the requested method
 """
 
-import statsmodels.formula.api as smf
+from toarstats.trends.ols import ols
+from toarstats.trends.quant_reg import quant_reg
 
 
 def calculate_trend(method, data, formula="value ~ datetime", quantiles=None):
@@ -22,4 +23,22 @@ def calculate_trend(method, data, formula="value ~ datetime", quantiles=None):
     :param quantiles: a single quantile or a list of quantiles to
                       calculate, these must be between 0 and 1; only
                       needed when ``method="quant"``
+
+    :raises ValueError: raised if the ``method`` parameter is not
+                        recognized
+
+    :return: The result of the fit or a list of fit results if
+             ``method="quant"`` and multiple quantiles are given
     """
+    if method == "OLS":
+        fit = ols(data, formula)
+    elif method == "quant":
+        try:
+            fit = [quant_reg(data, formula, quantile)
+                   for quantile in quantiles]
+        except TypeError:
+            fit = quant_reg(data, formula, quantiles)
+    else:
+        raise ValueError(f"{method} is not recognized, must be 'OLS' or"
+                         " 'quant'")
+    return fit

toarstats/trends/ols.py

+"""Ordinary least squares (OLS) linear regression calculation.
+
+This module contains the following function:
+ols - calculate the OLS linear regression
+"""
+
+import statsmodels.formula.api as smf
+
+
+def ols(data, formula):
+    """Calculate the OLS linear regression.
+
+    :param data: data containing a list of date time values and
+                 associated parameter values on which to calculate the
+                 trend
+    :param formula: the formula specifying the model
+
+    :return: The result of the fit
+    """
+    model = smf.ols(formula, data)
+    fit = model.fit()
+    return fit

toarstats/trends/quant_reg.py

+"""Quantile regression calculation.
+
+This module contains the following function:
+quant_reg - calculate the OLS linear regression
+"""
+
+import statsmodels.formula.api as smf
+
+
+def quant_reg(data, formula, quantile):
+    """Calculate the quantile regression.
+
+    :param data: data containing a list of date time values and
+                 associated parameter values on which to calculate the
+                 trend
+    :param formula: the formula specifying the model
+    :param quantile: a single quantile, must be between 0 and 1
+
+    :return: The result of the fit
+    """
+    model = smf.quantreg(formula, data)
+    fit = model.fit(q=quantile)
+    return fit