Merge branch 'master' of gitlab.windenergy.dtu.dk:toolbox/WindEnergyToolbox

wetb/signal/tests/test_nan_replace.py

+'''
+Created on 02/11/2015
+
+@author: MMPE
+'''
+import unittest
+import numpy as np
+from wetb.signal.nan_replace import replace_by_mean, replace_by_line, \
+    replace_by_polynomial, max_no_nan
+from matplotlib.pyplot import plot, show
+class TestNan_replace(unittest.TestCase):
+
+
+    def test_nan_replace_by_mean(self):
+        a = np.array([1, 5, 6, 4, 5, np.nan, 3, 1, 5, 6, 4.])
+        np.testing.assert_array_equal(replace_by_mean(a), [1, 5, 6, 4, 5, 4, 3, 1, 5, 6, 4.])
+        a = np.array([1, 5, 6, 4, 5, np.nan, np.nan, 1, 5, 6, 4.])
+        np.testing.assert_array_equal(replace_by_mean(a), [1, 5, 6, 4, 5, 3, 3, 1, 5, 6, 4.])
+        a = np.array([np.nan, 5, 6, 4, 5, np.nan, 3, 1, 5, 6, np.nan])
+        np.testing.assert_array_equal(replace_by_mean(a), [5, 5, 6, 4, 5, 4, 3, 1, 5, 6, 6])
+
+
+    def test_nan_replace_by_line(self):
+        a = np.array([1, 5, 6, 4, 5, np.nan, 3, 1, 5, 6, 4.])
+        np.testing.assert_array_equal(replace_by_line(a), [1, 5, 6, 4, 5, 4, 3, 1, 5, 6, 4.])
+        a = np.array([1, 5, 6, 4, 5, np.nan, np.nan, 2, 5, 6, 4.])
+        np.testing.assert_array_equal(replace_by_line(a), [1, 5, 6, 4, 5, 4, 3, 2, 5, 6, 4.])
+        a = np.array([np.nan, 5, 6, 4, 5, np.nan, 3, 1, 5, 6, np.nan])
+        np.testing.assert_array_equal(replace_by_line(a), [5, 5, 6, 4, 5, 4, 3, 1, 5, 6, 6])
+
+
+    def test_nan_replace_by_polynomial(self):
+        a = np.array([np.nan, 5, 6, 4, 5, np.nan, 3, 1, 5, 6, np.nan])
+        np.testing.assert_array_equal(replace_by_polynomial(a), [5, 5, 6, 4, 5, 4, 3, 1, 5, 6, 6])
+        a = np.array([1, 5, 6, 4, 5, np.nan, np.nan, 1, 5, 6, 4.])
+        np.testing.assert_array_almost_equal(replace_by_polynomial(a, 3, 2), [1, 5, 6, 4, 5, 3.3, 1.2, 1, 5, 6, 4.])
+
+        if 0:
+            plot(a)
+            plot(replace_by_polynomial(a, 3, 2))
+            show()
+
+
+    def test_nan_replace_by_polynomial2(self):
+        a = np.r_[np.arange(10), np.repeat(np.nan, 100), 10 - np.arange(10)]
+        self.assertLessEqual(replace_by_polynomial(a, 3, 9).max(), np.nanmax(a))
+
+        if 0:
+            plot(a, '.r')
+            plot(replace_by_polynomial(a, 3, 9), 'g-')
+            show()
+
+
+    def test_max_no_nan(self):
+        a = np.array([1, 5, 6, 4, 5, np.nan, 3, 1, 5, np.nan, 4.])
+        self.assertEqual(max_no_nan(a), 1)
+        a = np.array([1, 5, 6, 4, 5, np.nan, np.nan, 1, 5, np.nan, 4.])
+        self.assertEqual(max_no_nan(a), 2)
+        a = np.array([np.nan, np.nan, np.nan, 4, 5, np.nan, np.nan, 1, 5, np.nan, 4.])
+        self.assertEqual(max_no_nan(a), 3)
+        a = np.array([1, 5, 6, 4, 5, np.nan, 4, 1, 5, np.nan, np.nan])
+        self.assertEqual(max_no_nan(a), 2)
+
+if __name__ == "__main__":
+    #import sys;sys.argv = ['', 'Test.test_nanreplace']
+    unittest.main()

wetb/signal/tests/test_subset_mean.py

@@ -9,7 +9,7 @@ import unittest
 import numpy as np
 from wetb import gtsdf
 from wetb.signal.subset_mean import time_trigger, subset_mean, \
-    non_nan_index_trigger, revolution_trigger
+    non_nan_index_trigger, revolution_trigger_old, revolution_trigger
 from wetb.utils.geometry import rpm2rads
 
 
@@ -68,10 +68,10 @@ class TestSubsetMean(unittest.TestCase):
         ds = gtsdf.Dataset(tfp+'azi.hdf5')
         azi, rpm, time = [ds(x)[8403:8803] for x in ['azi','Rot_cor','Time']]
         
-        trigger = revolution_trigger(azi)
+        trigger = revolution_trigger_old(azi)
         np.testing.assert_array_equal(trigger, [ 17, 128, 241, 354])
         azi[64] = 358
-        trigger = revolution_trigger(azi, (ds('Rot_cor'), np.diff(time).mean()))
+        trigger = revolution_trigger_old(azi, (ds('Rot_cor'), np.diff(time).mean()))
         
 #         import matplotlib.pyplot as plt
 #         t = np.arange(len(azi))
@@ -82,5 +82,31 @@ class TestSubsetMean(unittest.TestCase):
         np.testing.assert_array_equal(trigger, [ (128,241),(241,354)])
 
 
+    def test_revolution_trigger(self):
+        rotor_position = np.arange(0.,360*10,4)
+        rotor_position += np.random.random(len(rotor_position))
+        rotor_position = rotor_position % 360
+        if 0:
+            x1 = np.random.randint(0, len(rotor_position),10)
+            print (list(x1))
+            x2 = np.random.randint(0, len(rotor_position),10)
+            print (list(x2))
+        else:
+            x1 = [447, 854, 595, 804, 847, 488, 412, 199, 675, 766]
+            x2 = [92, 647, 821, 422, 33, 159, 369, 99, 157, 464]
+            
+        rotor_position[x1] += 360
+        rotor_position[x2] -= 360
+        rotor_position[90] = 180
+        
+        indexes = revolution_trigger(rotor_position, 20,1/(90/20/60))
+        np.testing.assert_array_equal(indexes, [ 91, 180, 270, 360, 450, 540, 630, 720, 810])
+        if 0:
+            import matplotlib.pyplot as plt
+            plt.plot(rotor_position)
+            plt.plot(indexes, np.zeros_like(indexes),'.')
+            plt.show()
+        
+
 if __name__ == "__main__":
     unittest.main()

wetb/wind/shear.py

@@ -99,7 +99,7 @@ def fit_power_shear_ref(z_u_lst, z_ref, plt=None):
     """
     def shear_error(x, z_u_lst, z_ref):
         alpha, u_ref = x
-        return np.sum([(u - u_ref * (z / z_ref) ** alpha) ** 2 for z, u in z_u_lst])
+        return np.nansum([(u - u_ref * (z / z_ref) ** alpha) ** 2 for z, u in z_u_lst])
     z_u_lst = [(z, np.mean(u)) for z, u in z_u_lst]
     alpha, u_ref = fmin(shear_error, (.1, 10), (z_u_lst, z_ref), disp=False)
     if plt:
@@ -107,6 +107,9 @@ def fit_power_shear_ref(z_u_lst, z_ref, plt=None):
         plt.plot(u, z, '.')
         z = np.linspace(min(z), max(z), 100)
         plt.plot(power_shear(alpha, z_ref, u_ref)(z), z)
+        plt.margins(.1)
+    if alpha==.1 and u_ref==10: # Initial conditions
+        return np.nan, np.nan
     return alpha, u_ref
 
 

wetb/wind/tests/test_Shear.py

@@ -49,6 +49,24 @@ class TestShear(unittest.TestCase):
         14: WSP gl. coo.,Vz 21
         """
 
+    def test_power_shear_fit(self):
+        z = [30,50,70]
+        a,u_ref = .3,10
+        u = power_shear(a,50,u_ref)(z)
+        np.testing.assert_array_almost_equal(fit_power_shear_ref(zip(z,u), 50), [a,u_ref],3)
+        if 0:
+            import matplotlib.pyplot as plt
+            fit_power_shear_ref(zip(z,u), 50, plt)
+            plt.show()
+        
+    def test_power_shear_fit_nan(self):
+        z = [30,50,70]
+        a,u_ref = .3,10
+        u = power_shear(a,50,u_ref)(z)
+        u[2] = np.nan
+        np.testing.assert_array_almost_equal(fit_power_shear_ref(zip(z,u), 50), [a,u_ref],3)
+        u[:] = np.nan
+        np.testing.assert_array_almost_equal(fit_power_shear_ref(zip(z,u), 50), [np.nan, np.nan],3)
 
     def test_power_shear(self):
         if all: