Add function for linear inter- and/or extrapolation

Author: SabineHaas

windpowerlib/tools.py

@@ -4,6 +4,9 @@
 
 """
 
+import numpy as np
+
+
 __copyright__ = "Copyright oemof developer group"
 __license__ = "GPLv3"
 
@@ -54,3 +57,64 @@ def smallest_difference(value_1, value_2, comp_value, corresp_1, corresp_2):
     else:
         corresp_value = corresp_2
     return (closest_value, corresp_value)
+
+
+def linear_extra_interpolation(data_frame, requested_height, column_name):
+    r"""
+    Inter- or extrapolates between the values of a data frame.
+
+    This function can for example be used for the interpolation of a wind
+    speed, density or temperature.
+
+    Parameters
+    ----------
+    data_frame : DataFrame
+        Indices are the values between which will be interpolated or from which
+        will be extrapolated, the corresponding values are in the column
+        specified by `column_name` and they can be floats, pd.Series or
+        np.arrays.
+    requested_height : float
+        Height for which the interpolation takes place (e.g. hub height of wind
+        turbine).
+    column_name : string
+        Name of the column in the DataFrame `data_frame` that contains the
+        correponding values.
+
+    Returns
+    -------
+    interpolant : pandas.Series, numpy.array or float
+        Result of the interpolation (e.g. density at hub height).
+
+    Notes
+    -----
+
+    For the interpolation np.interp() is used and the following equation is
+    used for extrapolation:
+
+    .. math:: interpolant = (value_2 - value_1) / (height_2 - height_1) *
+              (requested_height - height_1) + value_1
+
+    with:
+        height_2: largest/smallest value in data frame, height_1: second
+        largest/smallest value in data frame, value_2: corresponding value to
+        height_2, value_1: correponding value to height_1
+
+    """
+    if requested_height > max(data_frame.index):
+        height_2 = max(data_frame.index)
+        value_2 = data_frame[column_name][height_2]
+        height_1 = sorted(data_frame.index)[-2]  # Second largest number
+        value_1 = data_frame[column_name][height_1]
+        interpolant = ((value_2 - value_1) / (height_2 - height_1) *
+                       (requested_height - height_1) + value_1)
+    elif requested_height < min(data_frame.index):
+        height_2 = min(data_frame.index)
+        value_2 = data_frame[column_name][height_2]
+        height_1 = sorted(data_frame.index)[1]  # Second smallest number
+        value_1 = data_frame[column_name][height_1]
+        interpolant = ((value_2 - value_1) / (height_2 - height_1) *
+                       (requested_height - height_1) + value_1)
+    else:
+        interpolant = np.interp(requested_height, data_frame.index,
+                                data_frame[column_name])
+    return interpolant