Repository: pvlib/pvanalytics (language: python)

Issue:
Adding component sum function calculations to the irradiance module
Hey all, Josh Peterson from the University of Oregon approached me at PVPMC, interested in getting some of his functions based on published works integrated into PVAnalytics. One of the first functions he shared with me is based on the irradiance component sum equations (incredibly similar to what we have for our QCRad checks, but this directly calculates a field based on the other fields, with potential fields being GHI, DNI, or DHI). I'm sharing this function on his behalf to encourage further discussion. From what he's shared, I'd envision it as a way to calculate data fields if they aren't currently present in a data set for future analysis, as I think a lot of the validation of existing irradiance fields (say, comparing ground-based GHI measurements to component sum-calculated GHI using a GHI ratio) is already sitting up there in our QCRad checks. Let me know what you guys think about potentially adding this. I was going to flag an issue for each of the functions he'd like to add to encourage further discussion by the entire team. I can work with Josh to add the algorithms to the package, if we decide as a group to incorporate them.

Here is outline of the functionality, which is being used to estimate GHI using DNI and DHI values:

```
import numpy as np

def subroutineGHIcalc(dni, dhi, sza, szalimit, fillvalue, fillnightoption):
    '''
    Computes GHI from component sum equation
    ghi = dni * Cos(sza) + dhi

    Inputs: 
    dni is an array of floats
    dhi is an array of floats (Must be same units as DNI)
    sza is an array of floats (degrees)
    
    szalimit: float (degrees) SZA boundary between night and day. SZA values greater than the limit are filled with a constant
        default: 90
        
    fillvalue: float. The value that is used to fill in nighttime values.
        default: NA
    
    fillnightoption: 
        1: fill the nighttime value with the fill value (NA, 0, -99 etc)
        2: fill the nighttime value with the DHI value such that at night (GHI == DHI)
        Other: do nothing to the nighttimie values. compute them as they are. 

    Returns: GHI: array of floats, (same units as DNI)
    '''               
    # Not sure if we want to do a test to make sure the DNI, DHI, SZA are valid values.
    # Specifically are they floats. I don't think we would want to test if they are reasonable..
    # Compute the GHI value from the component sum equation
    ghi = dni * np.cos(sza * np.pi / 180) + dhi
    # Decide what you are going to do with the nighttime values
    if (fillnightoption == 1) |(fillnightoption == 2):
        # Find the locations where the sun is below the sza limit. 
        mask = (szalimit <= sza) 
    if (fillnightoption == 1):    
        # Replace the nighttime values with a fill value
        ghi[mask] = fillvalue
    elif fillnightoption == 2:
        # Replace the nighttime values with the DHI values. 
        # This will put 
        ghi[mask] =dhi[mask]
    return ghi

# A simple test
dni = np.array([1000,900,800])
dhi = np.array([50, 100, 200])
sza = np.array([100, 30, 30 ])

ghi = subroutineGHIcalc(dni, dhi, sza, 90, fillvalue=33, fillnightoption=1)

print(ghi)
```






Discussion / hints:
I don't think there's a function like this in `pvlib.irradiance` and if not, that's where I would add it.
[pvlib.irradiance.dni](https://github.com/pvlib/pvlib-python/blob/master/pvlib/irradiance.py#L2849) and [ModelChain._complete_irradiance](https://github.com/pvlib/pvlib-python/blob/master/pvlib/modelchain.py#L1301) are relevant
This is my first time on GitHub as an editor, so I don't quite know the protocols that I should follow. Specifically I don't know if I am getting into the weeds too quickly. 

1. I think that the function needs to have the default values defined. Something along the lines of 
def subroutineGHIcalc(dni, dhi, sza, szalimit=90, fillvalue=np.nan, fillnightoption=1):

2. There are two ways that the nighttime values can remain unchanged. If the fillnightoption is not 1 or 2. or if the szalimit is set to 180 or greater. In the second way the mask will remain empty and there will not be any values replaced. When I wrote the function, I didn't have a great way to get around this. Any suggestions. 
If I'm following:
- szalimit defines the separation between day and night,
- fillnightoption indicates if night values are to be filled with fillvalue.
Is that correct?

Fix patch:
diff --git a/docs/api.rst b/docs/api.rst
index 629370e78..94e149b1d 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -65,6 +65,17 @@ clearsky insolation for the same day.
 
    quality.irradiance.daily_insolation_limits
 
+There is function for calculating the component sum for GHI, DHI,
+and DNI, and correcting for nighttime periods. Using this function, we can
+estimate one irradiance field using the two other irradiance fields.
+This can be useful for comparison, as well as to
+calculate missing data fields. 
+
+.. autosummary::
+   :toctree: generated/
+
+   quality.irradiance.calculate_component_sum_series
+
 Gaps
 ----
 
diff --git a/docs/examples/irradiance-quality/component-sum-irradiance.py b/docs/examples/irradiance-quality/component-sum-irradiance.py
new file mode 100644
index 000000000..1915961ba
--- /dev/null
+++ b/docs/examples/irradiance-quality/component-sum-irradiance.py
@@ -0,0 +1,119 @@
+"""
+Component Sum Equations for Irradiance Data
+===========================================
+
+Estimate GHI, DHI, and DNI using the component sum equations, with
+nighttime corrections.
+"""
+
+# %%
+# Estimating GHI, DHI, and DNI using the component sum equations is useful
+# if the associated field is missing, or as a comparison to an existing
+# physical data stream.
+
+import pvanalytics
+from pvanalytics.quality.irradiance import calculate_component_sum_series
+import pvlib
+import matplotlib.pyplot as plt
+import pandas as pd
+import pathlib
+
+# %%
+# First, read in data from the RMIS NREL system. This data set contains
+# 5-minute right-aligned data. It includes POA, GHI,
+# DNI, DHI, and GNI measurements.
+
+pvanalytics_dir = pathlib.Path(pvanalytics.__file__).parent
+rmis_file = pvanalytics_dir / 'data' / 'irradiance_RMIS_NREL.csv'
+data = pd.read_csv(rmis_file, index_col=0, parse_dates=True)
+
+# %%
+# Now generate solar zenith estimates for the location,
+# based on the data's time zone and site latitude-longitude
+# coordinates. This is done using the
+# :py:func:`pvlib.solarposition.get_solarposition` function.
+latitude = 39.742
+longitude = -105.18
+time_zone = "Etc/GMT+7"
+data = data.tz_localize(time_zone)
+solar_position = pvlib.solarposition.get_solarposition(data.index,
+                                                       latitude,
+                                                       longitude)
+
+
+# %%
+# Get the clearsky DNI values associated with the current location, using
+# the :py:func:`pvlib.solarposition.get_solarposition` function. These clearsky
+# values are used to calculate DNI data.
+site = pvlib.location.Location(latitude, longitude, tz=time_zone)
+clearsky = site.get_clearsky(data.index)
+
+# %%
+# Use :py:func:`pvanalytics.quality.irradiance.calcuate_ghi_component`
+# to estimate GHI measurements using DHI and DNI measurements
+
+component_sum_ghi = calculate_component_sum_series(
+    solar_zenith=solar_position['zenith'],
+    dhi=data['irradiance_dhi__7983'],
+    dni=data['irradiance_dni__7982'],
+    zenith_limit=90,
+    fill_night_value='equation')
+
+# %%
+# Plot the 'irradiance_ghi__7981' data stream against the estimated component
+# sum GHI, for comparison
+data['irradiance_ghi__7981'].plot()
+component_sum_ghi.plot()
+plt.legend(labels=["RMIS GHI", "Component Sum GHI"],
+           loc="upper left")
+plt.xlabel("Date")
+plt.ylabel("GHI (W/m^2)")
+plt.tight_layout()
+plt.show()
+
+# %%
+# Use :py:func:`pvanalytics.quality.irradiance.calcuate_dhi_component`
+# to estimate DHI measurements using GHI and DNI measurements
+
+component_sum_dhi = calculate_component_sum_series(
+    solar_zenith=solar_position['zenith'],
+    dni=data['irradiance_dni__7982'],
+    ghi=data['irradiance_ghi__7981'],
+    zenith_limit=90,
+    fill_night_value='equation')
+
+# %%
+# Plot the 'irradiance_dhi__7983' data stream against the estimated component
+# sum GHI, for comparison
+data['irradiance_dhi__7983'].plot()
+component_sum_dhi.plot()
+plt.legend(labels=["RMIS DHI", "Component Sum DHI"],
+           loc="upper left")
+plt.xlabel("Date")
+plt.ylabel("GHI (W/m^2)")
+plt.tight_layout()
+plt.show()
+
+# %%
+# Use :py:func:`pvanalytics.quality.irradiance.calcuate_dni_component`
+# to estimate DNI measurements using GHI and DHI measurements
+
+component_sum_dni = calculate_component_sum_series(
+    solar_zenith=solar_position['zenith'],
+    dhi=data['irradiance_dhi__7983'],
+    ghi=data['irradiance_ghi__7981'],
+    dni_clear=clearsky['dni'],
+    zenith_limit=90,
+    fill_night_value='equation')
+
+# %%
+# Plot the 'irradiance_dni__7982' data stream against the estimated component
+# sum GHI, for comparison
+data['irradiance_dni__7982'].plot()
+component_sum_dni.plot()
+plt.legend(labels=["RMIS DNI", "Component Sum DNI"],
+           loc="upper left")
+plt.xlabel("Date")
+plt.ylabel("DNI (W/m^2)")
+plt.tight_layout()
+plt.show()
diff --git a/docs/whatsnew/0.1.3.rst b/docs/whatsnew/0.1.3.rst
index e22b85b2c..cce81fb6b 100644
--- a/docs/whatsnew/0.1.3.rst
+++ b/docs/whatsnew/0.1.3.rst
@@ -5,9 +5,9 @@
 
 Enhancements
 ~~~~~~~~~~~~
+* Added function ``pvanalytics.quality.irradiance.calculate_component_sum_series`` for calculating the component sum values of GHI, DHI, and DNI, and performing nighttime corrections (:issue:`157`, :pull:`163`)
 * Updated the :py:func:`~pvanalytics.gaps.stale_values_round` function with pandas functionality, leading to the same results with a 300X speedup. (:issue:`156`, :pull:`158`)
 
-
 Bug Fixes
 ~~~~~~~~~
 
@@ -19,7 +19,7 @@ Requirements
 Documentation
 ~~~~~~~~~~~~~
 
-Added 4 new gallery example pages:
+Added new gallery example pages:
 
 * ``pvanalytics.metrics`` (:issue:`133`, :pull:`153`):
 
@@ -33,6 +33,8 @@ Added 4 new gallery example pages:
   * :py:func:`~pvanalytics.quality.weather.wind_limits`
   * :py:func:`~pvanalytics.quality.weather.module_temperature_check`
 
+* ``pvanalytics.quality.irradiance.calculate_component_sum_series``(:issue:`157`, :pull:`163`)
+
 Restructured the example gallery by separating the examples into categories
 and adding README's (:issue:`154`, :pull:`155`).  
 
diff --git a/pvanalytics/data/irradiance_RMIS_NREL.csv b/pvanalytics/data/irradiance_RMIS_NREL.csv
index 3ac4301a9..f6bf643c9 100644
--- a/pvanalytics/data/irradiance_RMIS_NREL.csv
+++ b/pvanalytics/data/irradiance_RMIS_NREL.csv
@@ -1,1441 +1,1441 @@
-measured_on,irradiance_dhi__7983,irradiance_dni__7982,irradiance_ghi__7981,irradiance_gni__7994,irradiance_poa__7984
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diff --git a/pvanalytics/quality/irradiance.py b/pvanalytics/quality/irradiance.py
index e19b30ef5..290569e7d 100644
--- a/pvanalytics/quality/irradiance.py
+++ b/pvanalytics/quality/irradiance.py
@@ -471,3 +471,192 @@ def daily_insolation_limits(irrad, clearsky, daily_min=0.4, daily_max=1.25):
         lower_bound=daily_min
     )
     return good_days.reindex(irrad.index, method='pad', fill_value=False)
+
+
+def _fill_nighttime(component, component_sum_df, fill_night_value,
+                    solar_zenith, zenith_limit):
+    # This function is used to fill in nighttime values for the computed
+    # irradiance time series (GHI, DHI, DNI).
+    # Set the series based on the component.
+    if component == 'GHI':
+        series = component_sum_df['ghi']
+    elif component == 'DHI':
+        series = component_sum_df['dhi']
+    else:
+        series = component_sum_df['dni']
+    # Logic for filling in nighttime values for a
+    # component sum series.
+    # Find the locations where the sun is below the sza limit.
+    mask = (zenith_limit <= solar_zenith)
+    if isinstance(fill_night_value, float) | isinstance(fill_night_value, int):
+        # Replace the nighttime values with a fill value--this can be np.nan,
+        # which is a float
+        series[mask] = fill_night_value
+    elif fill_night_value == 'equation':
+        # Use the nighttime equation GHI = 0 + DHI, which translates as:
+        # GHI_Calc (at night) = DHI_measured
+        # DHI_Calc (at night) = GHI_measured
+        # DNI_Calc (at night) = 0
+        if component == 'GHI':
+            series[mask] = component_sum_df['dhi'][mask]
+        elif component == 'DHI':
+            series[mask] = component_sum_df['ghi'][mask]
+        else:
+            series[mask] = 0
+    elif fill_night_value is None:
+        pass
+    else:
+        raise ValueError("The fill_night_value variable must be None,"
+                         " float or int, or 'equation'. Please change "
+                         "the variable fill_night_value value.")
+    return series
+
+
+def _complete_irradiance(solar_zenith,
+                         ghi=None,
+                         dhi=None,
+                         dni=None,
+                         dni_clear=None):
+    """
+    TODO: This method exists in the pvlib-python library. Once a new PVLib
+    release or pre-release is cut, this private function can be deleted and
+    the associated PVLib function can be directly leveraged.
+
+    Use the component sum equations to calculate the missing series, using
+    the other available time series. One of the three parameters (ghi, dhi,
+    dni) is passed as None, and the other associated series passed are used to
+    calculate the missing series value.
+    The "component sum" or "closure" equation relates the three
+    primary irradiance components as follows:
+
+    .. math::
+
+          GHI = DHI + DNI * \cos(\theta_z)
+
+    Parameters
+    ----------
+    solar_zenith : Series
+        Zenith angles in decimal degrees, with datetime index.
+        Angles must be >=0 and <=180. Must have the same datetime index
+        as ghi, dhi, and dni series, when available.
+    ghi : Series, optional
+        Pandas series of dni data, with datetime index. Must have the same
+        datetime index as dni, dhi, and zenith series, when available.
+    dhi : Series, optional
+        Pandas series of dni data, with datetime index. Must have the same
+        datetime index as ghi, dni, and zenith series, when available.
+    dni : Series, optional
+        Pandas series of dni data, with datetime index. Must have the same
+        datetime index as ghi, dhi, and zenith series, when available.
+    dni_clear : Series, optional
+        Pandas series of clearsky dni data. Must have the same datetime index
+        as `ghi`, `dhi`, `dni`, and `solar_zenith` series, when available. See pvlib-python's 
+        [dni](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.irradiance.dni.html#pvlib.irradiance.dni) for details.
+
+    Returns
+    -------
+    component_sum_df : Dataframe
+        Pandas series of 'ghi', 'dhi', and 'dni' columns with datetime index
+    """
+    if ghi is not None and dhi is not None and dni is None:
+        dni = pvlib.irradiance.dni(ghi, dhi, solar_zenith,
+                                   clearsky_dni=dni_clear,
+                                   clearsky_tolerance=1.1)
+    elif dni is not None and dhi is not None and ghi is None:
+        ghi = (dhi + dni * cosd(solar_zenith))
+    elif dni is not None and ghi is not None and dhi is None:
+        dhi = (ghi - dni * cosd(solar_zenith))
+    else:
+        raise ValueError(
+            "Please check that exactly one of ghi, dhi and dni parameters "
+            "is set to None"
+        )
+    # Merge the outputs into a master dataframe containing 'ghi', 'dhi',
+    # and 'dni' columns
+    component_sum_df = pd.DataFrame({'ghi': ghi,
+                                     'dhi': dhi,
+                                     'dni': dni})
+    return component_sum_df
+
+
+def calculate_component_sum_series(solar_zenith,
+                                   ghi=None,
+                                   dhi=None,
+                                   dni=None,
+                                   dni_clear=None,
+                                   zenith_limit=90,
+                                   fill_night_value=None):
+    r'''
+    Use the component sum equations to calculate the missing series, using
+    the other available time series. One of the three parameters (ghi, dhi,
+    dni) is passed as None, and the two series are used to
+    calculate the missing series. After calculation, the series is
+    run through a nighttime routine, where nighttime values are set based on
+    the fill_night_value parameter.
+
+    The "component sum" or "closure" equation relates the three
+    primary irradiance components as follows:
+
+    .. math::
+
+       GHI = DHI + DNI * \cos(\theta_z)
+
+
+    Parameters
+    ----------
+    solar_zenith : Series
+        Zenith angles in decimal degrees, with datetime index.
+        Angles must be >=0 and <=180. Must have the same datetime index
+        as `dni`, `dhi`, and `dni`, when available.
+    ghi : Series, optional
+        Pandas series of GHI data, with datetime index. Must have the same
+        datetime index as `dni`, `dhi`, and `solar_zenith`, when available.
+    dhi : Series, optional
+        Pandas series of DNI data, with datetime index. Must have the same
+        datetime index as ghi, dni, and zenith series, when available.
+    dni : Series, optional
+        Pandas series of dni data, with datetime index. Must have the same
+        datetime index as `ghi`, `dhi`, and `solar_zenith`, when available.
+    dni_clear : Series, optional
+        Pandas series of clearsky dni data. Must have the same datetime index
+        as `ghi`, `dhi`, `dni`, and `solar_zenith`, when available. See
+        pvlib-python's 
+        `dni <https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.irradiance.dni.html#pvlib.irradiance.dni>`_ for details.
+    zenith_limit: Float
+        Solar zenith boundary between night and day, in degrees.
+        For calculation of the component sum, `solar_zenith` is set to 90 where
+        `solar_zenith > zenith_limit`.
+    fill_night_value: String or float or int, default None
+        Options include 'equation', float or int values (np.nan, 0, etc.), or
+        None.
+        This is the fill value for nighttime periods.
+        If a float or int value is passed (np.nan, 0 , -.5, etc.), then
+        nighttime values are filled using the fill_night_value parameter.
+        If 'equation' is used, nighttime periods are filled using the
+        component sum equation with DNI=0:
+            GHI = 0 + DHI
+        If None, then the nighttime values are based on the component sum
+        equation.
+
+    Returns
+    -------
+    Series
+        Pandas series of the calculated values, based on the component sum
+        equation and corrected for nighttime periods.
+    '''
+    component_sum_df = _complete_irradiance(solar_zenith, ghi,
+                                            dhi, dni, dni_clear)
+    if ghi is None:
+        component = 'GHI'
+    elif dhi is None:
+        component = 'DHI'
+    elif dni is None:
+        component = 'DNI'
+    else:
+        raise ValueError(
+            "Please check that exactly one of ghi, dhi and dni parameters "
+            "is set to None"
+        )
+    return _fill_nighttime(component, component_sum_df,
+                           fill_night_value,
+                           solar_zenith, zenith_limit)


Test patch:
diff --git a/pvanalytics/tests/quality/test_irradiance.py b/pvanalytics/tests/quality/test_irradiance.py
index 0b7af6262..8990f2d8a 100644
--- a/pvanalytics/tests/quality/test_irradiance.py
+++ b/pvanalytics/tests/quality/test_irradiance.py
@@ -3,11 +3,27 @@
 import pytz
 import pandas as pd
 import numpy as np
-
 import pytest
 from pandas.util.testing import assert_series_equal
-
 from pvanalytics.quality import irradiance
+from ..conftest import DATA_DIR
+
+
+test_file_1 = DATA_DIR / "irradiance_RMIS_NREL.csv"
+
+
+@pytest.fixture
+def generate_RMIS_irradiance_series():
+    # Pull down the saved PVLib dataframe and process it
+    df = pd.read_csv(test_file_1, index_col=0, parse_dates=True)
+    df = df.tz_localize("Etc/GMT+7")
+    # Get the GHI, DHI, and DNI series
+    dni_series = df['irradiance_dni__7982']
+    dhi_series = df['irradiance_dhi__7983']
+    ghi_series = df['irradiance_ghi__7981']
+    dni_clear_series = df['pvlib_clearsky_dni']
+    sza = df['pvlib_zenith']
+    return (dhi_series, dni_series, ghi_series, dni_clear_series, sza)
 
 
 @pytest.fixture
@@ -314,3 +330,84 @@ def test_daily_insolation_limits_uneven(albuquerque):
         pd.Series(True, index=ghi.index),
         check_names=False
     )
+
+
+def test_calculate_ghi_component(generate_RMIS_irradiance_series):
+    """
+    Test calculate_component_sum_series() function on GHI calculation.
+    """
+    # Pull down RMIS data to test on
+    dhi_series, dni_series, ghi_series, dni_clear_series, sza_series = \
+        generate_RMIS_irradiance_series
+    # Run with fill_night_value as np.nan
+    ghi_series_fill_value = irradiance.calculate_component_sum_series(
+        solar_zenith=sza_series,
+        dhi=dhi_series,
+        dni=dni_series,
+        zenith_limit=90,
+        fill_night_value=np.nan)
+    # Make sure that periods where sza>90 are marked as NaN
+    assert all(ghi_series_fill_value[sza_series > 90].isna())
+    # Run with fill_night_value = 'equation'
+    ghi_series_equation = irradiance.calculate_component_sum_series(
+        solar_zenith=sza_series,
+        dhi=dhi_series,
+        dni=dni_series,
+        fill_night_value='equation')
+    # Make sure that periods where sza>90 are equal equal to GHI values
+    assert all(ghi_series_equation[sza_series > 90].dropna() ==
+               dhi_series[sza_series > 90].dropna())
+    # Run with fill_night_value = None
+    ghi_series_none = irradiance.calculate_component_sum_series(
+        solar_zenith=sza_series,
+        dhi=dhi_series,
+        dni=dni_series,
+        zenith_limit=90,
+        fill_night_value=None)
+    ghi_test = dni_series * np.cos(sza_series * np.pi / 180) + dhi_series
+    assert all(ghi_test.round(5).dropna() == ghi_series_none.round(5).dropna())
+    # Throw an error if int/float, None, or 'equation' aren't passed in
+    # fill_night_value parameter
+    with pytest.raises(ValueError):
+        irradiance.calculate_component_sum_series(solar_zenith=sza_series,
+                                                  dhi=dhi_series,
+                                                  dni=dni_series,
+                                                  zenith_limit=90,
+                                                  fill_night_value='random')
+
+
+def test_calculate_dhi_component(generate_RMIS_irradiance_series):
+    """
+    Test calculate_component_sum_series() function on DHI calculation.
+    """
+    # Pull down RMIS data to test on
+    dhi_series, dni_series, ghi_series, dni_clear_series, sza_series = \
+        generate_RMIS_irradiance_series
+    # Test with equation used
+    dhi_series_equation = irradiance.calculate_component_sum_series(
+        solar_zenith=sza_series,
+        ghi=ghi_series,
+        dni=dni_series,
+        zenith_limit=90,
+        fill_night_value='equation')
+    # Make sure that periods where sza>90 are equal equal to GHI values
+    assert all(dhi_series_equation[sza_series > 90].dropna() ==
+               ghi_series[sza_series > 90].dropna())
+
+
+def test_calculate_dni_component(generate_RMIS_irradiance_series):
+    """
+    Test calculate_component_sum_series() function on DNI calculation.
+    """
+    # Pull down RMIS data to test on
+    dhi_series, dni_series, ghi_series, dni_clear_series, sza_series = \
+        generate_RMIS_irradiance_series
+    dni_series_equation = irradiance.calculate_component_sum_series(
+        solar_zenith=sza_series,
+        ghi=ghi_series,
+        dhi=dhi_series,
+        dni_clear=dni_clear_series,
+        zenith_limit=90,
+        fill_night_value='equation')
+    # Make sure that periods where sza>90 are equal equal to GHI values
+    assert all(dni_series_equation[sza_series > 90].dropna() == 0)