Apply suggestions from code review

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>

Author: kandersolar

docs/sphinx/source/reference/solarposition.rst

@@ -43,7 +43,7 @@ Functions for calculating sunrise, sunset and transit times.
    solarposition.sun_rise_set_transit_geometric
 
 
-The spa module contains the implementation of the built-in NLR SPA
+The spa module contains the implementation of the built-in NREL SPA
 algorithm.
 
 .. autosummary::

docs/sphinx/source/user_guide/getting_started/installation.rst

@@ -235,19 +235,19 @@ Alternatively, users may install all optional dependencies using
 
 .. _nrelspa:
 
-NLR SPA algorithm
+NREL SPA algorithm
 ------------------
 
 pvlib-python is distributed with several validated, high-precision, and
 high-performance solar position calculators. We strongly recommend using
 the built-in solar position calculators.
 
 pvlib-python also includes unsupported wrappers for the official NLR
-SPA algorithm. NLR's license does not allow redistribution of the
+implementation of NREL SPA. NLR's license does not allow redistribution of the
 source code, so you must jump through some hoops to use it with pvlib.
 You will need a C compiler to use this code.
 
-To install the NLR SPA algorithm for use with pvlib:
+To install the NREL SPA algorithm for use with pvlib:
 
 #. Download the pvlib repository (as described in :ref:`obtainsource`)
 #. Download the `SPA files from NLR <http://www.nlr.gov/midc/spa/>`_

pvlib/iotools/tmy.py

@@ -161,7 +161,7 @@ def read_tmy3(filename, coerce_year=None, map_variables=True, encoding=None):
 
     .. admonition:: Midnight representation
 
-       The function is able to handle midnight represented as 24:00 (NLR TMY3
+       The function is able to handle midnight represented as 24:00 (NREL TMY3
        format, see [1]_) and as 00:00 (SolarAnywhere TMY3 format, see [3]_).
 
     .. warning:: TMY3 irradiance data corresponds to the *previous* hour, so

pvlib/snow.py

@@ -320,7 +320,7 @@ def loss_townsend(snow_total, snow_events, surface_tilt, relative_humidity,
         Uses of the Townsend Snow Model. In "Photovoltaic Reliability
         Workshop (PVRW) 2023 Proceedings: Posters.", ed. Silverman,
         T. J. Dec. 2023. NREL/CP-5900-87918.
-        :doi:`10.2172/1429291`
+        Available at: https://www.osti.gov/biblio/2229734
     .. [3] Townsend, T. (2013). Predicting PV Energy Loss Caused by Snow.
         Solar Power International, Chicago IL.
         :doi:`10.13140/RG.2.2.14299.68647`

pvlib/solarposition.py

@@ -56,10 +56,10 @@ def get_solarposition(time, latitude, longitude,
         if ``altitude`` is not supplied.
 
     method : string, default 'nrel_numpy'
-        'nrel_numpy' uses an implementation of the NLR SPA algorithm
+        'nrel_numpy' uses an implementation of the NREL SPA algorithm
         described in [1] (default, recommended): :py:func:`spa_python`
 
-        'nrel_numba' uses an implementation of the NLR SPA algorithm
+        'nrel_numba' uses an implementation of the NREL SPA algorithm
         described in [1], but also compiles the code first:
         :py:func:`spa_python`
 
@@ -129,8 +129,8 @@ def spa_c(time, latitude, longitude, pressure=101325., altitude=0.,
           temperature=12., delta_t=67.0,
           raw_spa_output=False):
     r"""
-    Calculate the solar position using the C implementation of the NLR
-    SPA code.
+    Calculate the solar position using the NLR C implementation of the
+    NREL SPA.
 
     The source files for this code are located in './spa_c_files/', along with
     a README file which describes how the C code is wrapped in Python.
@@ -283,9 +283,9 @@ def spa_python(time, latitude, longitude,
                atmos_refract=None, how='numpy', numthreads=4):
     """
     Calculate the solar position using a python implementation of the
-    NLR SPA algorithm.
+    NREL SPA algorithm.
 
-    The details of the NLR SPA algorithm are described in [1]_, [2]_.
+    The details of the NREL SPA algorithm are described in [1]_, [2]_.
 
     If numba is installed, the functions can be compiled to
     machine code and the function can be multithreaded.
@@ -394,9 +394,9 @@ def sun_rise_set_transit_spa(times, latitude, longitude, how='numpy',
                              delta_t=67.0, numthreads=4):
     """
     Calculate the sunrise, sunset, and sun transit times using the
-    NLR SPA algorithm.
+    NREL SPA algorithm.
 
-    The details of the NLR SPA algorithm are described in [1]_.
+    The details of the NREL SPA algorithm are described in [1]_.
 
     If numba is installed, the functions can be compiled to
     machine code and the function can be multithreaded.
@@ -956,9 +956,9 @@ def pyephem_earthsun_distance(time):
 def nrel_earthsun_distance(time, how='numpy', delta_t=67.0, numthreads=4):
     """
     Calculates the distance from the earth to the sun using the
-    NLR SPA algorithm.
+    NREL SPA algorithm.
 
-    The details of the NLR SPA algorithm are described in [1]_.
+    The details of the NREL SPA algorithm are described in [1]_.
 
     Parameters
     ----------

pvlib/spa.py

@@ -1,5 +1,5 @@
 """
-Calculate the solar position using the NLR SPA algorithm either using
+Calculate the solar position using the NREL SPA algorithm either using
 numpy arrays or compiling the code to machine language with numba.
 """
 
@@ -402,7 +402,7 @@ def nocompile(*args, **kwargs):
 @jcompile('float64(int64, int64, int64, int64, int64, int64, int64)',
           nopython=True)
 def julian_day_dt(year, month, day, hour, minute, second, microsecond):
-    """This is the original way to calculate the julian day from the NLR paper.
+    """This is the original way to calculate the julian day from the NREL paper.
     However, it is much faster to convert to unix/epoch time and then convert
     to julian day. Note that the date must be UTC."""
     if month <= 2:
@@ -1031,7 +1031,7 @@ def solar_position(unixtime, lat, lon, elev, pressure, temp, delta_t,
 
     """
     Calculate the solar position using the
-    NLR SPA algorithm described in [1].
+    NREL SPA algorithm described in [1].
 
     If numba is installed, the functions can be compiled
     and the code runs quickly. If not, the functions
@@ -1214,7 +1214,7 @@ def transit_sunrise_sunset(dates, lat, lon, delta_t, numthreads):
 def earthsun_distance(unixtime, delta_t, numthreads):
     """
     Calculates the distance from the earth to the sun using the
-    NLR SPA algorithm described in [1].
+    NREL SPA algorithm described in [1].
 
     Parameters
     ----------

pvlib/spectrum/spectrl2.py

@@ -203,7 +203,7 @@ def spectrl2(apparent_zenith, aoi, surface_tilt, ground_albedo,
         Surface pressure. [Pa]
     relative_airmass : numeric
         Relative airmass. The airmass model used in [1]_ is the `'kasten1966'`
-        model, while a later implementation by NLR uses the
+        model, while a later implementation by NREL used the
         `'kastenyoung1989'` model. [unitless]
     precipitable_water : numeric
         Atmospheric water vapor content. [cm]

tests/iotools/test_tmy.py

@@ -107,7 +107,7 @@ def solaranywhere_index():
 
 def test_solaranywhere_tmy3(solaranywhere_index):
     # The SolarAnywhere TMY3 format specifies midnight as 00:00 whereas the
-    # NLR TMY3 format utilizes 24:00. The SolarAnywhere file is therefore
+    # NREL TMY3 format utilizes 24:00. The SolarAnywhere file is therefore
     # included to test files with  00:00 timestamps are parsed correctly
     data, meta = tmy.read_tmy3(TMY3_SOLARANYWHERE, encoding='iso-8859-1',
                                map_variables=False)

tests/test_shading.py

@@ -170,7 +170,7 @@ def test_projected_solar_zenith_angle_numeric(
 ):
     psza_func = shading.projected_solar_zenith_angle
     axis_tilt, axis_azimuth, timedata = true_tracking_angle_and_inputs_NREL
-    # test against data provided by NLR
+    # test against data provided by NREL
     psz = psza_func(
         timedata["Apparent Zenith"],
         timedata["Solar Azimuth"],