Return diffuse components from Perez transposition model (#259)

* Saving diffuse components into dict to be returned

* dictionary returned depending on optional boolean input argument for
 backward compatibility

* Wrote test for diffuse components

* all tests are passing

* Updated docstring and fixed test for Python3

* Now testing each calculated component

* and not just the sum of them

* Updated whatsnew file with changes

* Cleaning changes

* Defining components as ordered dict
* Treating case where inputs can be scalar

* Check that component col order is correct in test

Author: anomam

docs/sphinx/source/whatsnew/v0.4.2.txt

@@ -46,6 +46,7 @@ Enhancements
   separate pages for each function, class, or method. (:issue:`258`)
 * Improved Linke turbidity factor time interpolation with Python `calendar`
   month days and leap years (:issue:`265`)
+* Added option to return diffuse components from Perez transposition model.
 
 
 Other
@@ -61,3 +62,4 @@ Code Contributors
 * Will Holmgren
 * Volker Beutner
 * Mark Mikofski
+* Marc Anoma

pvlib/irradiance.py

@@ -886,7 +886,7 @@ def king(surface_tilt, dhi, ghi, solar_zenith):
 
 def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
           solar_zenith, solar_azimuth, airmass,
-          model='allsitescomposite1990'):
+          model='allsitescomposite1990', return_components=False):
     '''
     Determine diffuse irradiance from the sky on a tilted surface using
     one of the Perez models.
@@ -953,6 +953,10 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
         * 'capecanaveral1988'
         * 'albany1988'
 
+    return_components: bool (optional, default=False)
+        Flag used to decide whether to return the calculated diffuse components
+        or not.
+
     Returns
     --------
     sky_diffuse : numeric
@@ -1043,7 +1047,26 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,
     else:
         sky_diffuse = np.where(np.isnan(airmass), 0, sky_diffuse)
 
-    return sky_diffuse
+    if return_components:
+        diffuse_components = OrderedDict()
+
+        # Calculate the different components
+        diffuse_components['isotropic'] = dhi * term1
+        diffuse_components['circumsolar'] = dhi * term2
+        diffuse_components['horizon'] = dhi * term3
+
+        # Set values of components to 0 when sky_diffuse is 0
+        mask = sky_diffuse == 0
+        if isinstance(sky_diffuse, pd.Series):
+            diffuse_components = pd.DataFrame(diffuse_components)
+            diffuse_components.ix[mask] = 0
+        else:
+            diffuse_components = {k: np.where(mask, 0, v) for k, v in diffuse_components.items()}
+
+        return sky_diffuse, diffuse_components
+
+    else:
+        return sky_diffuse
 
 
 def disc(ghi, zenith, datetime_or_doy, pressure=101325):

pvlib/test/test_irradiance.py

@@ -158,6 +158,29 @@ def test_perez():
     assert_series_equal(out, expected, check_less_precise=2)
 
 
+def test_perez_components():
+    am = atmosphere.relativeairmass(ephem_data['apparent_zenith'])
+    dni = irrad_data['dni'].copy()
+    dni.iloc[2] = np.nan
+    out, df_components = irradiance.perez(40, 180, irrad_data['dhi'], dni,
+                     dni_et, ephem_data['apparent_zenith'],
+                     ephem_data['azimuth'], am, return_components=True)
+    expected = pd.Series(np.array(
+        [   0.        ,   31.46046871,  np.nan,   45.45539877]),
+        index=times)
+    expected_components = pd.DataFrame(
+        np.array([[  0.        ,  26.84138589,          np.nan,  31.72696071],
+                 [ 0.        ,  0.        ,         np.nan,  4.47966439],
+                 [ 0.        ,  4.62212181,         np.nan,  9.25316454]]).T,
+        columns=['isotropic', 'circumsolar', 'horizon'],
+        index=times
+    )
+    sum_components = df_components.sum(axis=1)
+
+    assert_series_equal(out, expected, check_less_precise=2)
+    assert_frame_equal(df_components, expected_components)
+    assert_series_equal(sum_components, expected, check_less_precise=2)
+
 @needs_numpy_1_10
 def test_perez_arrays():
     am = atmosphere.relativeairmass(ephem_data['apparent_zenith'])