Added Benchmarking functions for scaling.py module

benchmarks/benchmarks/scaling.py

@@ -0,0 +1,37 @@
+"""
+ASV benchmarks for scaling.py
+"""
+
+import pandas as pd
+from pvlib import scaling
+import numpy as np
+
+
+class Scaling:
+
+    def setup(self):
+        self.n = 1000
+        lat = np.array((9.99, 10, 10.01))
+        lon = np.array((4.99, 5, 5.01))
+        self.coordinates = np.array([(lati, loni) for
+                                     (lati, loni) in zip(lat, lon)])
+        self.times = pd.date_range('2019-01-01', freq='1T', periods=self.n)
+        self.positions = np.array([[0, 0], [100, 0], [100, 100], [0, 100]])
+        self.clearsky_index = pd.Series(np.random.rand(self.n),
+                                        index=self.times)
+        self.cloud_speed = 5
+        self.tmscales = np.array((1, 2, 4, 8, 16, 32, 64,
+                                 128, 256, 512, 1024, 2048, 4096))
+
+    def time_latlon_to_xy(self):
+        scaling.latlon_to_xy(self.coordinates)
+
+    def time__compute_wavelet(self):
+        scaling._compute_wavelet(self.clearsky_index, dt=1)
+
+    def time__compute_vr(self):
+        scaling._compute_vr(self.positions, self.cloud_speed, self.tmscales)
+
+    def time_wvm(self):
+        scaling.wvm(self.clearsky_index, self.positions,
+                    self.cloud_speed, dt=1)

docs/sphinx/source/whatsnew/v0.9.2.rst

@@ -29,6 +29,7 @@ Documentation
 Benchmarking
 ~~~~~~~~~~~~~
 * Updated version of numba in asv.conf from 0.36.1 to 0.40.0 to solve numba/numpy conflict. (:issue:`1439`, :pull:`1440`)
+* Added benchmarks for the `pvlib.scaling` module (:pull:`1445`)
 * Added a basic CI asv check (:issue:`1446`, :pull:`1454`)
 
 Requirements