From c9b860cd2e164f75e8c9a4d83528dc67daeb1e3b Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 1 Jul 2024 21:26:42 +0100
Subject: [PATCH 01/37] Create spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 141 ++++++++++++++++++++++
 1 file changed, 141 insertions(+)
 create mode 100644 docs/examples/spectrum/spectral_factor.py

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
new file mode 100644
index 0000000000..f327ec8140
--- /dev/null
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -0,0 +1,141 @@
+"""
+Spectral Mismatch Estimation
+============================
+Comparison of spectral factor calculation methods used to estimate the spectral
+mismatch factor from atmopsheric variable inputs.
+"""
+
+# %%
+# Introduction
+# ------------
+# This example demonstrates how to use different `spectrum.spectral_factor`
+# models in pvlib to calculate the spectral mismatch factor, :math:`M`. While
+# :math:`M` for a photovoltaic (PV) module can be calculated exactly using
+# spectral irradiance and module spectral response data, these data are not
+# always available. pvlib provides several functions to estimate the spectral
+# mismatch factor, :math:`M`, using proxies of the prevaiing spectral
+# irradiance conditions, such as air mass and clearsky index, which are easily
+# derived from common ground-based measurements such as broadband irradiance.
+# More information on a range of spectral factor models, as wel as the
+# variables upon which they are based, can be found in [1]_.
+
+from matplotlib import pyplot as plt
+import pandas as pd
+import pvlib as pv
+from pvlib import location
+from pvlib.solarposition import get_solarposition
+from pvlib.atmosphere import get_relative_airmass
+
+# Let's import some data. This example uses a Typical Meteorological Year 3
+# (TMY3) file for the
+# location of Greensboro, North Carolina, from the pvlib data directory. This
+# TMY3 file is constructed using the median month from each year between 1980
+# and 2003, from which we extract the first week of August 2001 to analyse.
+meteo, metadata = pv.iotools.read_tmy3(
+    r'C:\Users\ezxrd3\Documents\GitHub\pvlib-python\pvlib\data\723170TYA.csv',
+    map_variables=True)
+meteo = meteo.sort_index()
+meteo = meteo.between_time('06:00', '20:00').loc['2001-08-01':'2001-08-07']
+
+# %%
+# pvlib Spectral Factor Functions
+# -----------------------------
+# This example demonstrates the application of three pvlib spectral factor
+# functions, namely `sapm`_, `pvspec`, and `firstsolar`_.
+
+# %%
+# SAPM
+# ----
+# The SAPM function for the spectral mismatch
+# factor calculates :math:`M` using absolute airmass, :math:`AM_a` as an input.
+
+# %%
+# PVSPEC
+# ------
+# The PVSPEC function for the spectral mismatch factor calculates :math:`M`
+# using :math:`AM_a` and the clearsky index, :math:`k_c` as inputs.
+
+# %%
+# First Solar
+# -----------
+# The First Solar function for the spectral mismatch factor calculates
+# :math:`M` using :math:`AM_a` and the atmospheric precipitable water content,
+# :math:`W`, as inputs.
+
+# %%
+# Calculation of inputs
+# ---------------------
+# Let's calculate the absolute air mass, which is required for all three
+# models. We use the Kasten and Young [2]_ model, which requires the apparent
+# sun zenith. Note: TMY3 files timestamps indicate the end of the hour, so we
+# shift the indices back 30-minutes to calculate solar position at the centre
+# of the interval.
+
+# Create a location object
+lat, lon = metadata['latitude'], metadata['longitude']
+alt = altitude = metadata['altitude']
+tz = 'Etc/GMT+5'
+loc = location.Location(lat, lon, tz=tz, name='Greensboro, NC')
+
+# Calculate solar position parameters
+solpos = get_solarposition(
+    meteo.index.shift(freq="-30min"), lat, lon, alt,
+    pressure=meteo.pressure*100,  # convert from millibar to Pa
+    temperature=meteo.temp_air)
+solpos.index = meteo.index  # reset index to end of the hour
+
+amr = get_relative_airmass(solpos.apparent_zenith).dropna()  # relative airmass
+ama = amr*(meteo.pressure/1013.25)  # absolute airmass
+
+# Now we calculate the clearsky index, :math:`kc`, by comparing the TMY3 GHI to
+# the modelled clearky GHI.
+
+cs = loc.get_clearsky(meteo.index)
+kc = cs.ghi/meteo.ghi
+
+# :math:`W` is provided in the TMY3 file but in other cases can be calculated
+# from temperature and relative humidity.
+
+w = meteo.precipitable_water
+
+# %%
+# Calculation of Spectral Mismatch
+
+# Let's calculate the spectral mismatch factor using the three pvlib functions.
+# First, we need to import some model coefficients for the SAPM spectral factor
+# function, which, unlike the other two functions, lacks built-in coefficients.
+
+# Import some for a mc-Si module from the SAPM module database.
+module = pv.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
+# Calculate :math:`M` using the three models for an mc-Si PV module.
+m_sapm = pv.spectrum.spectral_factor_sapm(ama, module)
+m_pvspec = pv.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
+m_fs = pv.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
+df_results = pd.concat([m_sapm, m_pvspec, m_fs], axis=1)
+df_results.columns = ['SAPM', 'PVSPEC', 'FS']
+# %%
+# Comparison Plots
+
+# We can plot the results to visualisee variability between the models. Note
+# that this is not an exact comparison since the exact same PV modules has
+# not been modelled in each case, only the same module technology.
+
+# Convert Dataframe Indexes to Month-Day our:Minute format
+df_results.index = df_results.index.strftime("%m-%d")
+
+# Plot :math:`M`
+fig1, ax1 = plt.subplots()
+df_results.plot(ax=ax1)
+
+ax1.set_xlabel('Date (m-d H:M)')
+ax1.set_ylabel('Mismatch (-)')
+ax1.legend()
+plt.show()
+
+# We can also zoom in one one day, for example August 1st.
+df_results.index = m_fs.index
+df_results = df_results.loc['2001-08-01':'2001-08-01']
+df_results.index = df_results.index.strftime("%H:%M")
+fig2, ax1 = plt.subplots()
+df_results.plot(ax=ax1)
+plt.show()

From d1156beb07734e7e327b3d42be03cc4262bb0a86 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 1 Jul 2024 22:43:12 +0100
Subject: [PATCH 02/37] Update spectral_factor.py

fix directory, add refs
---
 docs/examples/spectrum/spectral_factor.py | 21 +++++++++++++++++----
 1 file changed, 17 insertions(+), 4 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index f327ec8140..c24092cba5 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -16,9 +16,10 @@
 # mismatch factor, :math:`M`, using proxies of the prevaiing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
-# More information on a range of spectral factor models, as wel as the
+# More information on a range of spectral factor models, as well as the
 # variables upon which they are based, can be found in [1]_.
 
+import pathlib
 from matplotlib import pyplot as plt
 import pandas as pd
 import pvlib as pv
@@ -31,9 +32,9 @@
 # location of Greensboro, North Carolina, from the pvlib data directory. This
 # TMY3 file is constructed using the median month from each year between 1980
 # and 2003, from which we extract the first week of August 2001 to analyse.
-meteo, metadata = pv.iotools.read_tmy3(
-    r'C:\Users\ezxrd3\Documents\GitHub\pvlib-python\pvlib\data\723170TYA.csv',
-    map_variables=True)
+DATA_DIR = pathlib.Path(pv.__file__).parent / 'data'
+meteo, metadata = pv.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
+                                       map_variables=True)
 meteo = meteo.sort_index()
 meteo = meteo.between_time('06:00', '20:00').loc['2001-08-01':'2001-08-07']
 
@@ -139,3 +140,15 @@
 fig2, ax1 = plt.subplots()
 df_results.plot(ax=ax1)
 plt.show()
+
+"""
+References
+----------
+.. [1] Daxini, Rajiv, and Yupeng Wu (2023). "Review of methods to account for
+      the solar spectral influence on photovoltaic device performance." Energy
+      286
+      :doi:`10.1364/AO.28.004735`
+.. [2] Kasten, F. and Young, A.T., 1989. Revised optical air mass tables
+   and approximation formula. Applied Optics, 28(22), pp.4735-4738.
+   :doi:`10.1364/AO.28.004735`
+"""

From 8fefcf2f89bc98c711cca18ee6532b13551f469c Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 1 Jul 2024 23:13:27 +0100
Subject: [PATCH 03/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 53 ++++++++++++-----------
 1 file changed, 28 insertions(+), 25 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index c24092cba5..76bab9aa38 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -19,6 +19,12 @@
 # More information on a range of spectral factor models, as well as the
 # variables upon which they are based, can be found in [1]_.
 
+# Let's import some data. This example uses a Typical Meteorological Year 3
+# (TMY3) file for the
+# location of Greensboro, North Carolina, from the pvlib data directory. This
+# TMY3 file is constructed using the median month from each year between 1980
+# and 2003, from which we extract the first week of August 2001 to analyse.
+
 import pathlib
 from matplotlib import pyplot as plt
 import pandas as pd
@@ -27,11 +33,6 @@
 from pvlib.solarposition import get_solarposition
 from pvlib.atmosphere import get_relative_airmass
 
-# Let's import some data. This example uses a Typical Meteorological Year 3
-# (TMY3) file for the
-# location of Greensboro, North Carolina, from the pvlib data directory. This
-# TMY3 file is constructed using the median month from each year between 1980
-# and 2003, from which we extract the first week of August 2001 to analyse.
 DATA_DIR = pathlib.Path(pv.__file__).parent / 'data'
 meteo, metadata = pv.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
                                        map_variables=True)
@@ -42,26 +43,28 @@
 # pvlib Spectral Factor Functions
 # -----------------------------
 # This example demonstrates the application of three pvlib spectral factor
-# functions, namely `sapm`_, `pvspec`, and `firstsolar`_.
+# functions, namely `SAPM`_, `PVSPEC`_, and `firstsolar`_.
 
 # %%
 # SAPM
 # ----
-# The SAPM function for the spectral mismatch
-# factor calculates :math:`M` using absolute airmass, :math:`AM_a` as an input.
+# The SAPM function (:py:func:`pvlib.spectrum.spectral_factor_sapm`) for the
+# spectral mismatch factor calculates :math:`M` using absolute airmass,
+# :math:`AM_a` as an input.
 
 # %%
 # PVSPEC
 # ------
-# The PVSPEC function for the spectral mismatch factor calculates :math:`M`
-# using :math:`AM_a` and the clearsky index, :math:`k_c` as inputs.
+# The PVSPEC function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`) for
+# the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and the
+# clearsky index, :math:`k_c` as inputs.
 
 # %%
 # First Solar
 # -----------
-# The First Solar function for the spectral mismatch factor calculates
-# :math:`M` using :math:`AM_a` and the atmospheric precipitable water content,
-# :math:`W`, as inputs.
+# The First Solar function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`)
+# for the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and
+# the atmospheric precipitable water content, :math:`W`, as inputs.
 
 # %%
 # Calculation of inputs
@@ -101,6 +104,7 @@
 
 # %%
 # Calculation of Spectral Mismatch
+# --------------------------------
 
 # Let's calculate the spectral mismatch factor using the three pvlib functions.
 # First, we need to import some model coefficients for the SAPM spectral factor
@@ -116,7 +120,7 @@
 df_results.columns = ['SAPM', 'PVSPEC', 'FS']
 # %%
 # Comparison Plots
-
+# ----------------
 # We can plot the results to visualisee variability between the models. Note
 # that this is not an exact comparison since the exact same PV modules has
 # not been modelled in each case, only the same module technology.
@@ -141,14 +145,13 @@
 df_results.plot(ax=ax1)
 plt.show()
 
-"""
-References
-----------
-.. [1] Daxini, Rajiv, and Yupeng Wu (2023). "Review of methods to account for
-      the solar spectral influence on photovoltaic device performance." Energy
-      286
-      :doi:`10.1364/AO.28.004735`
-.. [2] Kasten, F. and Young, A.T., 1989. Revised optical air mass tables
-   and approximation formula. Applied Optics, 28(22), pp.4735-4738.
-   :doi:`10.1364/AO.28.004735`
-"""
+# %%
+# References
+# ----------
+# .. [1] Daxini, Rajiv, and Yupeng Wu (2023). "Review of methods to account for
+#        the solar spectral influence on photovoltaic device performance."
+#        Energy 286
+#        :doi:`10.1364/AO.28.004735`
+# .. [2] Kasten, F. and Young, A.T., 1989. Revised optical air mass tables
+#        and approximation formula. Applied Optics, 28(22), pp.4735-4738.
+#        :doi:`10.1364/AO.28.004735`

From c566795912ffe7c5e4d8337d6177be239ce5df56 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 1 Jul 2024 23:34:16 +0100
Subject: [PATCH 04/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 76bab9aa38..83e517207a 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -24,7 +24,7 @@
 # location of Greensboro, North Carolina, from the pvlib data directory. This
 # TMY3 file is constructed using the median month from each year between 1980
 # and 2003, from which we extract the first week of August 2001 to analyse.
-
+# %%
 import pathlib
 from matplotlib import pyplot as plt
 import pandas as pd
@@ -62,7 +62,8 @@
 # %%
 # First Solar
 # -----------
-# The First Solar function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`)
+# The First Solar function (:py:func:`pvlib.spectrum.spectral_factor_firstsolar
+# `)
 # for the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and
 # the atmospheric precipitable water content, :math:`W`, as inputs.
 

From e8b63ec0053040e14d3d3afa787a263b6f8ee539 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 1 Jul 2024 23:50:36 +0100
Subject: [PATCH 05/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 83e517207a..b9df47c9f1 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -20,10 +20,11 @@
 # variables upon which they are based, can be found in [1]_.
 
 # Let's import some data. This example uses a Typical Meteorological Year 3
-# (TMY3) file for the
-# location of Greensboro, North Carolina, from the pvlib data directory. This
-# TMY3 file is constructed using the median month from each year between 1980
-# and 2003, from which we extract the first week of August 2001 to analyse.
+# (TMY3) file for the location of Greensboro, North Carolina, from the pvlib
+# data directory. This TMY3 file is constructed using the median month from
+# each year between 1980 and 2003, from which we extract the first week of
+# August 2001 to analyse.
+
 # %%
 import pathlib
 from matplotlib import pyplot as plt
@@ -62,10 +63,10 @@
 # %%
 # First Solar
 # -----------
-# The First Solar function (:py:func:`pvlib.spectrum.spectral_factor_firstsolar
-# `)
-# for the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and
-# the atmospheric precipitable water content, :math:`W`, as inputs.
+# The First Solar function
+# (:py:func:`pvlib.spectrum.spectral_factor_firstsolar`) for the spectral
+# mismatch factor calculates :math:`M` using :math:`AM_a` and the atmospheric
+# precipitable water content, :math:`W`, as inputs.
 
 # %%
 # Calculation of inputs
@@ -106,7 +107,6 @@
 # %%
 # Calculation of Spectral Mismatch
 # --------------------------------
-
 # Let's calculate the spectral mismatch factor using the three pvlib functions.
 # First, we need to import some model coefficients for the SAPM spectral factor
 # function, which, unlike the other two functions, lacks built-in coefficients.

From 12c5d6cdcf578e622186c219987113d66dfc518a Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 11:18:31 +0100
Subject: [PATCH 06/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 42 +++++++++++------------
 1 file changed, 20 insertions(+), 22 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index b9df47c9f1..3c9f5770f1 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -9,16 +9,16 @@
 # Introduction
 # ------------
 # This example demonstrates how to use different `spectrum.spectral_factor`
-# models in pvlib to calculate the spectral mismatch factor, :math:`M`. While
-# :math:`M` for a photovoltaic (PV) module can be calculated exactly using
+# models in pvlib to calculate the spectral mismatch factor, M. While
+# M for a photovoltaic (PV) module can be calculated exactly using
 # spectral irradiance and module spectral response data, these data are not
 # always available. pvlib provides several functions to estimate the spectral
-# mismatch factor, :math:`M`, using proxies of the prevaiing spectral
+# mismatch factor, M, using proxies of the prevaiing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
 # More information on a range of spectral factor models, as well as the
 # variables upon which they are based, can be found in [1]_.
-
+#
 # Let's import some data. This example uses a Typical Meteorological Year 3
 # (TMY3) file for the location of Greensboro, North Carolina, from the pvlib
 # data directory. This TMY3 file is constructed using the median month from
@@ -38,7 +38,8 @@
 meteo, metadata = pv.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
                                        map_variables=True)
 meteo = meteo.sort_index()
-meteo = meteo.between_time('06:00', '20:00').loc['2001-08-01':'2001-08-07']
+# meteo = meteo.between_time('06:00', '20:00').loc['2001-08-01':'2001-08-07']
+meteo = meteo.loc['2001-08-01':'2001-08-07']
 
 # %%
 # pvlib Spectral Factor Functions
@@ -48,24 +49,25 @@
 
 # %%
 # SAPM
-# ----
+# ^^^^
 # The SAPM function (:py:func:`pvlib.spectrum.spectral_factor_sapm`) for the
-# spectral mismatch factor calculates :math:`M` using absolute airmass,
+# spectral mismatch factor calculates M using absolute airmass,
 # :math:`AM_a` as an input.
 
 # %%
 # PVSPEC
+# ^^^^^^
 # ------
 # The PVSPEC function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`) for
-# the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and the
+# the spectral mismatch factor calculates M using :math:`AM_a` and the
 # clearsky index, :math:`k_c` as inputs.
 
 # %%
 # First Solar
-# -----------
+# ^^^^^^^^^^^
 # The First Solar function
 # (:py:func:`pvlib.spectrum.spectral_factor_firstsolar`) for the spectral
-# mismatch factor calculates :math:`M` using :math:`AM_a` and the atmospheric
+# mismatch factor calculates M using :math:`AM_a` and the atmospheric
 # precipitable water content, :math:`W`, as inputs.
 
 # %%
@@ -113,7 +115,7 @@
 
 # Import some for a mc-Si module from the SAPM module database.
 module = pv.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
-# Calculate :math:`M` using the three models for an mc-Si PV module.
+# Calculate M using the three models for an mc-Si PV module.
 m_sapm = pv.spectrum.spectral_factor_sapm(ama, module)
 m_pvspec = pv.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
 m_fs = pv.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
@@ -126,33 +128,29 @@
 # that this is not an exact comparison since the exact same PV modules has
 # not been modelled in each case, only the same module technology.
 
-# Convert Dataframe Indexes to Month-Day our:Minute format
-df_results.index = df_results.index.strftime("%m-%d")
-
-# Plot :math:`M`
+# Plot M
 fig1, ax1 = plt.subplots()
 df_results.plot(ax=ax1)
 
 ax1.set_xlabel('Date (m-d H:M)')
 ax1.set_ylabel('Mismatch (-)')
 ax1.legend()
+ax1.set_ylim(0.8, 1.2)
 plt.show()
 
 # We can also zoom in one one day, for example August 1st.
-df_results.index = m_fs.index
-df_results = df_results.loc['2001-08-01':'2001-08-01']
-df_results.index = df_results.index.strftime("%H:%M")
 fig2, ax1 = plt.subplots()
-df_results.plot(ax=ax1)
+df_results.loc['2001-08-01'].plot(ax=ax1)
+ax1.set_ylim(0.8, 1.2)
 plt.show()
 
 # %%
 # References
 # ----------
-# .. [1] Daxini, Rajiv, and Yupeng Wu (2023). "Review of methods to account for
-#        the solar spectral influence on photovoltaic device performance."
+# .. [1] Daxini, Rajiv, and Wu, Yupeng (2023). "Review of methods to account
+#        for the solar spectral influence on photovoltaic device performance."
 #        Energy 286
-#        :doi:`10.1364/AO.28.004735`
+#        :doi:`10.1016/j.energy.2023.129461`
 # .. [2] Kasten, F. and Young, A.T., 1989. Revised optical air mass tables
 #        and approximation formula. Applied Optics, 28(22), pp.4735-4738.
 #        :doi:`10.1364/AO.28.004735`

From fedba9317db5464082cf8be07c1bfba66dbd1641 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 12:06:29 +0100
Subject: [PATCH 07/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 17 ++++++++---------
 1 file changed, 8 insertions(+), 9 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 3c9f5770f1..8780bf5244 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -2,15 +2,15 @@
 Spectral Mismatch Estimation
 ============================
 Comparison of spectral factor calculation methods used to estimate the spectral
-mismatch factor from atmopsheric variable inputs.
+mismatch factor,:math:`M`, from atmopsheric variable inputs.
 """
 
 # %%
 # Introduction
 # ------------
 # This example demonstrates how to use different `spectrum.spectral_factor`
-# models in pvlib to calculate the spectral mismatch factor, M. While
-# M for a photovoltaic (PV) module can be calculated exactly using
+# models in pvlib to calculate the spectral mismatch factor, :math:`M`. While
+# :math:`M` for a photovoltaic (PV) module can be calculated exactly using
 # spectral irradiance and module spectral response data, these data are not
 # always available. pvlib provides several functions to estimate the spectral
 # mismatch factor, M, using proxies of the prevaiing spectral
@@ -51,15 +51,14 @@
 # SAPM
 # ^^^^
 # The SAPM function (:py:func:`pvlib.spectrum.spectral_factor_sapm`) for the
-# spectral mismatch factor calculates M using absolute airmass,
+# spectral mismatch factor calculates :math:`M` using absolute airmass,
 # :math:`AM_a` as an input.
 
 # %%
 # PVSPEC
 # ^^^^^^
-# ------
 # The PVSPEC function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`) for
-# the spectral mismatch factor calculates M using :math:`AM_a` and the
+# the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and the
 # clearsky index, :math:`k_c` as inputs.
 
 # %%
@@ -67,7 +66,7 @@
 # ^^^^^^^^^^^
 # The First Solar function
 # (:py:func:`pvlib.spectrum.spectral_factor_firstsolar`) for the spectral
-# mismatch factor calculates M using :math:`AM_a` and the atmospheric
+# mismatch factor calculates :math:`M` using :math:`AM_a` and the atmospheric
 # precipitable water content, :math:`W`, as inputs.
 
 # %%
@@ -135,13 +134,13 @@
 ax1.set_xlabel('Date (m-d H:M)')
 ax1.set_ylabel('Mismatch (-)')
 ax1.legend()
-ax1.set_ylim(0.8, 1.2)
+ax1.set_ylim(0.85, 1.15)
 plt.show()
 
 # We can also zoom in one one day, for example August 1st.
 fig2, ax1 = plt.subplots()
 df_results.loc['2001-08-01'].plot(ax=ax1)
-ax1.set_ylim(0.8, 1.2)
+ax1.set_ylim(0.85, 1.15)
 plt.show()
 
 # %%

From eeea56b2dc10259c4dc2b43f6325e4c68ce5dfe7 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 15:13:38 +0100
Subject: [PATCH 08/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 8780bf5244..a1cdaadf51 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -2,7 +2,7 @@
 Spectral Mismatch Estimation
 ============================
 Comparison of spectral factor calculation methods used to estimate the spectral
-mismatch factor,:math:`M`, from atmopsheric variable inputs.
+mismatch factor, :math:`M`, from atmospheric variable inputs.
 """
 
 # %%

From bca1f937c238923f41b5ffdda9f8d56dad7a2b89 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 15:13:48 +0100
Subject: [PATCH 09/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index a1cdaadf51..7e69b24b8c 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -13,7 +13,7 @@
 # :math:`M` for a photovoltaic (PV) module can be calculated exactly using
 # spectral irradiance and module spectral response data, these data are not
 # always available. pvlib provides several functions to estimate the spectral
-# mismatch factor, M, using proxies of the prevaiing spectral
+# mismatch factor, M, using proxies of the prevailing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
 # More information on a range of spectral factor models, as well as the

From 4c7ca2d05492f8006f9072b22cdd05a36b084227 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 15:58:01 +0100
Subject: [PATCH 10/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 31 ++++++-----------------
 1 file changed, 8 insertions(+), 23 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 7e69b24b8c..60525f55ee 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -45,29 +45,14 @@
 # pvlib Spectral Factor Functions
 # -----------------------------
 # This example demonstrates the application of three pvlib spectral factor
-# functions, namely `SAPM`_, `PVSPEC`_, and `firstsolar`_.
-
-# %%
-# SAPM
-# ^^^^
-# The SAPM function (:py:func:`pvlib.spectrum.spectral_factor_sapm`) for the
-# spectral mismatch factor calculates :math:`M` using absolute airmass,
-# :math:`AM_a` as an input.
-
-# %%
-# PVSPEC
-# ^^^^^^
-# The PVSPEC function (:py:func:`pvlib.spectrum.spectral_factor_pvspec`) for
-# the spectral mismatch factor calculates :math:`M` using :math:`AM_a` and the
-# clearsky index, :math:`k_c` as inputs.
-
-# %%
-# First Solar
-# ^^^^^^^^^^^
-# The First Solar function
-# (:py:func:`pvlib.spectrum.spectral_factor_firstsolar`) for the spectral
-# mismatch factor calculates :math:`M` using :math:`AM_a` and the atmospheric
-# precipitable water content, :math:`W`, as inputs.
+# functions:
+#
+# - :py:func:`~pvlib.spectrum.spectral_factor_sapm`, which requires only
+#   the absolute airmass :math:`AM_a`
+# - :py:func:`~pvlib.spectrum.spectral_factor_pvspec`, which requires
+#   :math:`AM_a` and the clearsky index :math:`k_c`
+# - :py:func:`~pvlib.spectrum.spectral_factor_firstsolar`, which requires
+#   :math:`AM_a` and the atmospheric precipitable water content :math:`W`
 
 # %%
 # Calculation of inputs

From 134fc3002a98acbc93084baa3b7231455721c682 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 15:58:19 +0100
Subject: [PATCH 11/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 60525f55ee..c067a9e875 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -86,7 +86,8 @@
 kc = cs.ghi/meteo.ghi
 
 # :math:`W` is provided in the TMY3 file but in other cases can be calculated
-# from temperature and relative humidity.
+# from temperature and relative humidity
+# (see :py:func:`pvlib.atmosphere.gueymard94_pw`).
 
 w = meteo.precipitable_water
 

From 96c61447d5747e69988088e3bfafc8926def11fc Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 16:11:10 +0100
Subject: [PATCH 12/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index c067a9e875..019df9714d 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -36,9 +36,7 @@
 
 DATA_DIR = pathlib.Path(pv.__file__).parent / 'data'
 meteo, metadata = pv.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
-                                       map_variables=True)
-meteo = meteo.sort_index()
-# meteo = meteo.between_time('06:00', '20:00').loc['2001-08-01':'2001-08-07']
+                                       coerce_year=2001, map_variables=True)
 meteo = meteo.loc['2001-08-01':'2001-08-07']
 
 # %%

From dba0ce85a33dccface29730c2d28faae44b3b900 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 16:12:05 +0100
Subject: [PATCH 13/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 019df9714d..19c323f924 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -107,7 +107,7 @@
 # %%
 # Comparison Plots
 # ----------------
-# We can plot the results to visualisee variability between the models. Note
+# We can plot the results to visualise variability between the models. Note
 # that this is not an exact comparison since the exact same PV modules has
 # not been modelled in each case, only the same module technology.
 

From 2f1fa7a9c6c66b17f152349470d59ce5b3b561fe Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 16:16:35 +0100
Subject: [PATCH 14/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 19c323f924..519a0624a6 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -68,8 +68,8 @@
 loc = location.Location(lat, lon, tz=tz, name='Greensboro, NC')
 
 # Calculate solar position parameters
-solpos = get_solarposition(
-    meteo.index.shift(freq="-30min"), lat, lon, alt,
+solpos = loc.get_solarposition(
+    meteo.index.shift(freq="-30min"),
     pressure=meteo.pressure*100,  # convert from millibar to Pa
     temperature=meteo.temp_air)
 solpos.index = meteo.index  # reset index to end of the hour

From c3f9b05bcf7b8a64c6ec9e14038a624308a8aa9d Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 16:18:47 +0100
Subject: [PATCH 15/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 519a0624a6..4efe81a26c 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -31,7 +31,6 @@
 import pandas as pd
 import pvlib as pv
 from pvlib import location
-from pvlib.solarposition import get_solarposition
 from pvlib.atmosphere import get_relative_airmass
 
 DATA_DIR = pathlib.Path(pv.__file__).parent / 'data'

From 9837013d44d965d25751f75f84602a469c4fafa3 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Wed, 3 Jul 2024 16:27:25 +0100
Subject: [PATCH 16/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 4efe81a26c..8680202f9b 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -80,7 +80,7 @@
 # the modelled clearky GHI.
 
 cs = loc.get_clearsky(meteo.index)
-kc = cs.ghi/meteo.ghi
+kc = pv.irradiance.clearsky_index(meteo.ghi, cs.ghi)
 
 # :math:`W` is provided in the TMY3 file but in other cases can be calculated
 # from temperature and relative humidity

From 21043c9baddef4f4681645099472299aafcda152 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:22:19 +0100
Subject: [PATCH 17/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 24 +++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 8680202f9b..820d22b08f 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -29,13 +29,12 @@
 import pathlib
 from matplotlib import pyplot as plt
 import pandas as pd
-import pvlib as pv
+import pvlib
 from pvlib import location
-from pvlib.atmosphere import get_relative_airmass
 
-DATA_DIR = pathlib.Path(pv.__file__).parent / 'data'
-meteo, metadata = pv.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
-                                       coerce_year=2001, map_variables=True)
+DATA_DIR = pathlib.Path(pvlib.__file__).parent / 'data'
+meteo, metadata = pvlib.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV',
+                                          coerce_year=2001, map_variables=True)
 meteo = meteo.loc['2001-08-01':'2001-08-07']
 
 # %%
@@ -73,14 +72,15 @@
     temperature=meteo.temp_air)
 solpos.index = meteo.index  # reset index to end of the hour
 
-amr = get_relative_airmass(solpos.apparent_zenith).dropna()  # relative airmass
+amr = pvlib.atmosphere.get_relative_airmass(solpos.apparent_zenith).dropna()
+# relative airmass
 ama = amr*(meteo.pressure/1013.25)  # absolute airmass
 
 # Now we calculate the clearsky index, :math:`kc`, by comparing the TMY3 GHI to
 # the modelled clearky GHI.
 
 cs = loc.get_clearsky(meteo.index)
-kc = pv.irradiance.clearsky_index(meteo.ghi, cs.ghi)
+kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)
 
 # :math:`W` is provided in the TMY3 file but in other cases can be calculated
 # from temperature and relative humidity
@@ -96,11 +96,11 @@
 # function, which, unlike the other two functions, lacks built-in coefficients.
 
 # Import some for a mc-Si module from the SAPM module database.
-module = pv.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
+module = pvlib.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
 # Calculate M using the three models for an mc-Si PV module.
-m_sapm = pv.spectrum.spectral_factor_sapm(ama, module)
-m_pvspec = pv.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
-m_fs = pv.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
+m_sapm = pvlib.spectrum.spectral_factor_sapm(ama, module)
+m_pvspec = pvlib.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
+m_fs = pvlib.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
 df_results = pd.concat([m_sapm, m_pvspec, m_fs], axis=1)
 df_results.columns = ['SAPM', 'PVSPEC', 'FS']
 # %%
@@ -122,7 +122,7 @@
 
 # We can also zoom in one one day, for example August 1st.
 fig2, ax1 = plt.subplots()
-df_results.loc['2001-08-01'].plot(ax=ax1)
+df_results.loc['2001-08-02'].plot(ax=ax1)
 ax1.set_ylim(0.85, 1.15)
 plt.show()
 

From 4254c85a5245c2c63a69d270f3a1969bd422608b Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:26:14 +0100
Subject: [PATCH 18/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Ioannis Sifnaios <88548539+IoannisSifnaios@users.noreply.github.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 820d22b08f..eac79f3bf2 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -13,7 +13,7 @@
 # :math:`M` for a photovoltaic (PV) module can be calculated exactly using
 # spectral irradiance and module spectral response data, these data are not
 # always available. pvlib provides several functions to estimate the spectral
-# mismatch factor, M, using proxies of the prevailing spectral
+# mismatch factor, :math:`M`, using proxies of the prevailing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
 # More information on a range of spectral factor models, as well as the

From 18ceb371f63d998a200de78049781dc0fbbc46b8 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:26:27 +0100
Subject: [PATCH 19/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Ioannis Sifnaios <88548539+IoannisSifnaios@users.noreply.github.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index eac79f3bf2..44afd9057c 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -12,7 +12,7 @@
 # models in pvlib to calculate the spectral mismatch factor, :math:`M`. While
 # :math:`M` for a photovoltaic (PV) module can be calculated exactly using
 # spectral irradiance and module spectral response data, these data are not
-# always available. pvlib provides several functions to estimate the spectral
+# always available. Pvlib provides several functions to estimate the spectral
 # mismatch factor, :math:`M`, using proxies of the prevailing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.

From 1bf00b1d39fc8d2a99acc4bacf9d96e40beffd60 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:31:49 +0100
Subject: [PATCH 20/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 820d22b08f..c0bbfb3fc8 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -75,13 +75,13 @@
 amr = pvlib.atmosphere.get_relative_airmass(solpos.apparent_zenith).dropna()
 # relative airmass
 ama = amr*(meteo.pressure/1013.25)  # absolute airmass
-
+# %%
 # Now we calculate the clearsky index, :math:`kc`, by comparing the TMY3 GHI to
 # the modelled clearky GHI.
 
 cs = loc.get_clearsky(meteo.index)
 kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)
-
+# %%
 # :math:`W` is provided in the TMY3 file but in other cases can be calculated
 # from temperature and relative humidity
 # (see :py:func:`pvlib.atmosphere.gueymard94_pw`).

From 8c859a7a175ffe2057d5ca282451b230a5cfd3c3 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 15:39:15 +0100
Subject: [PATCH 21/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 4ada83150e..083ce028c9 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -76,8 +76,8 @@
 # relative airmass
 ama = amr*(meteo.pressure/1013.25)  # absolute airmass
 # %%
-# Now we calculate the clearsky index, :math:`kc`, by comparing the TMY3 GHI to
-# the modelled clearky GHI.
+# Now we calculate the clearsky index, :math:`k_c`, by comparing the TMY3 GHI
+# to the modelled clearky GHI.
 
 cs = loc.get_clearsky(meteo.index)
 kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)

From d935a7c933a607375d71f566d3858d16ddbdd0cb Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 16:15:05 +0100
Subject: [PATCH 22/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 083ce028c9..fe54e0d79c 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -111,7 +111,7 @@
 # not been modelled in each case, only the same module technology.
 
 # Plot M
-fig1, ax1 = plt.subplots()
+fig1, ax1 = plt.subplots(figsize=(9.6, 7.2))
 df_results.plot(ax=ax1)
 
 ax1.set_xlabel('Date (m-d H:M)')
@@ -121,7 +121,7 @@
 plt.show()
 
 # We can also zoom in one one day, for example August 1st.
-fig2, ax1 = plt.subplots()
+fig2, ax1 = plt.subplots(figsize=(9.6, 7.2))
 df_results.loc['2001-08-02'].plot(ax=ax1)
 ax1.set_ylim(0.85, 1.15)
 plt.show()

From 37bdee0fd6ee62afa897eedc8eab9e98c903b81b Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 16:38:47 +0100
Subject: [PATCH 23/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 37 ++++++++++++-----------
 1 file changed, 19 insertions(+), 18 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index fe54e0d79c..bbe3ba211d 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -9,21 +9,21 @@
 # Introduction
 # ------------
 # This example demonstrates how to use different `spectrum.spectral_factor`
-# models in pvlib to calculate the spectral mismatch factor, :math:`M`. While
-# :math:`M` for a photovoltaic (PV) module can be calculated exactly using
-# spectral irradiance and module spectral response data, these data are not
-# always available. Pvlib provides several functions to estimate the spectral
-# mismatch factor, :math:`M`, using proxies of the prevailing spectral
+# models in pvlib-python to calculate the spectral mismatch factor, :math:`M`.
+# While :math:`M` for a photovoltaic (PV) module can be calculated exactly
+# using spectral irradiance and module spectral response data, these data are
+# not always available. pvlib-python provides several functions to estimate the
+# spectral mismatch factor, :math:`M`, using proxies of the prevailing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
 # More information on a range of spectral factor models, as well as the
 # variables upon which they are based, can be found in [1]_.
 #
 # Let's import some data. This example uses a Typical Meteorological Year 3
-# (TMY3) file for the location of Greensboro, North Carolina, from the pvlib
-# data directory. This TMY3 file is constructed using the median month from
-# each year between 1980 and 2003, from which we extract the first week of
-# August 2001 to analyse.
+# (TMY3) file for the location of Greensboro, North Carolina, from the
+# pvlib-python data directory. This TMY3 file is constructed using the median
+# month from each year between 1980 and 2003, from which we extract the first
+# week of August 2001 to analyse.
 
 # %%
 import pathlib
@@ -38,10 +38,10 @@
 meteo = meteo.loc['2001-08-01':'2001-08-07']
 
 # %%
-# pvlib Spectral Factor Functions
-# -----------------------------
-# This example demonstrates the application of three pvlib spectral factor
-# functions:
+# Spectral Factor Functions
+# -------------------------
+# This example demonstrates the application of three pvlib-python
+# spectral factor functions:
 #
 # - :py:func:`~pvlib.spectrum.spectral_factor_sapm`, which requires only
 #   the absolute airmass :math:`AM_a`
@@ -91,9 +91,10 @@
 # %%
 # Calculation of Spectral Mismatch
 # --------------------------------
-# Let's calculate the spectral mismatch factor using the three pvlib functions.
-# First, we need to import some model coefficients for the SAPM spectral factor
-# function, which, unlike the other two functions, lacks built-in coefficients.
+# Let's calculate the spectral mismatch factor using the three spectral factor
+# functions. First, we need to import some model coefficients for the SAPM
+# spectral factor function, which, unlike the other two functions, lacks
+# built-in coefficients.
 
 # Import some for a mc-Si module from the SAPM module database.
 module = pvlib.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
@@ -111,7 +112,7 @@
 # not been modelled in each case, only the same module technology.
 
 # Plot M
-fig1, ax1 = plt.subplots(figsize=(9.6, 7.2))
+fig1, ax1 = plt.subplots()
 df_results.plot(ax=ax1)
 
 ax1.set_xlabel('Date (m-d H:M)')
@@ -121,7 +122,7 @@
 plt.show()
 
 # We can also zoom in one one day, for example August 1st.
-fig2, ax1 = plt.subplots(figsize=(9.6, 7.2))
+fig2, ax1 = plt.subplots()
 df_results.loc['2001-08-02'].plot(ax=ax1)
 ax1.set_ylim(0.85, 1.15)
 plt.show()

From 665f494059d747ea7fb6cce85fc79d56f083a9fc Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 16:42:47 +0100
Subject: [PATCH 24/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index bbe3ba211d..79dafa0a25 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -120,7 +120,7 @@
 ax1.legend()
 ax1.set_ylim(0.85, 1.15)
 plt.show()
-
+# %%
 # We can also zoom in one one day, for example August 1st.
 fig2, ax1 = plt.subplots()
 df_results.loc['2001-08-02'].plot(ax=ax1)

From ea486840f424f51112dfe7e02494b850faa9fbcb Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 16:46:45 +0100
Subject: [PATCH 25/37] Update v0.11.1.rst

---
 docs/sphinx/source/whatsnew/v0.11.1.rst | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/docs/sphinx/source/whatsnew/v0.11.1.rst b/docs/sphinx/source/whatsnew/v0.11.1.rst
index 1e839c596c..d29b62ef3f 100644
--- a/docs/sphinx/source/whatsnew/v0.11.1.rst
+++ b/docs/sphinx/source/whatsnew/v0.11.1.rst
@@ -25,6 +25,9 @@ Testing
 
 Documentation
 ~~~~~~~~~~~~~
+* Add new example to the example gallery to demonstrate the application of
+  several spectral mismatch factor models.
+  (:issue:`2107`, :pull:`2114`)
 
 
 Requirements
@@ -34,3 +37,4 @@ Requirements
 Contributors
 ~~~~~~~~~~~~
 * Echedey Luis (:ghuser:`echedey-ls`)
+* Rajiv Daxini (:ghuser:`RDaxini`)

From 3b0a79b125b91c04a84219466eeaa51c48fde59d Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 17:31:09 +0100
Subject: [PATCH 26/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 79dafa0a25..904cc8dd87 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -44,11 +44,11 @@
 # spectral factor functions:
 #
 # - :py:func:`~pvlib.spectrum.spectral_factor_sapm`, which requires only
-#   the absolute airmass :math:`AM_a`
+#   the absolute airmass, :math:`AM_a`
 # - :py:func:`~pvlib.spectrum.spectral_factor_pvspec`, which requires
-#   :math:`AM_a` and the clearsky index :math:`k_c`
+#   :math:`AM_a` and the clearsky index, :math:`k_c`
 # - :py:func:`~pvlib.spectrum.spectral_factor_firstsolar`, which requires
-#   :math:`AM_a` and the atmospheric precipitable water content :math:`W`
+#   :math:`AM_a` and the atmospheric precipitable water content, :math:`W`
 
 # %%
 # Calculation of inputs
@@ -120,11 +120,11 @@
 ax1.legend()
 ax1.set_ylim(0.85, 1.15)
 plt.show()
-# %%
-# We can also zoom in one one day, for example August 1st.
-fig2, ax1 = plt.subplots()
-df_results.loc['2001-08-02'].plot(ax=ax1)
-ax1.set_ylim(0.85, 1.15)
+
+# We can also zoom in one one day, for example August 2nd.
+fig2, ax2 = plt.subplots()
+df_results.loc['2001-08-02'].plot(ax=ax2)
+ax2.set_ylim(0.85, 1.15)
 plt.show()
 
 # %%

From d4c03cb03d6b0c879e6e34b837db8f9da49557ef Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 19:56:36 +0100
Subject: [PATCH 27/37] Update spectral_factor.py

trying new plots (goal to increase size)
---
 docs/examples/spectrum/spectral_factor.py | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 904cc8dd87..acfed3c531 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -112,19 +112,21 @@
 # not been modelled in each case, only the same module technology.
 
 # Plot M
-fig1, ax1 = plt.subplots()
-df_results.plot(ax=ax1)
-
-ax1.set_xlabel('Date (m-d H:M)')
+fig1, (ax1, ax2) = plt.subplots(2, 1)
+df_results.plot(ax=ax1, legend=False)
+ax1.set_xlabel('Day')
 ax1.set_ylabel('Mismatch (-)')
-ax1.legend()
 ax1.set_ylim(0.85, 1.15)
-plt.show()
 
 # We can also zoom in one one day, for example August 2nd.
-fig2, ax2 = plt.subplots()
+# fig2, ax2 = plt.subplots()
 df_results.loc['2001-08-02'].plot(ax=ax2)
+ax2.set_xlabel('Time')
+ax2.set_ylabel('Mismatch (-)')
 ax2.set_ylim(0.85, 1.15)
+
+plt.tight_layout()
+
 plt.show()
 
 # %%

From 0af9b2d9e81b998aa8ddb73c14afe78b20a750de Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Thu, 4 Jul 2024 20:28:17 +0100
Subject: [PATCH 28/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index acfed3c531..63504b2584 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -77,7 +77,7 @@
 ama = amr*(meteo.pressure/1013.25)  # absolute airmass
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, by comparing the TMY3 GHI
-# to the modelled clearky GHI.
+# to the modelled clearsky GHI.
 
 cs = loc.get_clearsky(meteo.index)
 kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)
@@ -119,7 +119,6 @@
 ax1.set_ylim(0.85, 1.15)
 
 # We can also zoom in one one day, for example August 2nd.
-# fig2, ax2 = plt.subplots()
 df_results.loc['2001-08-02'].plot(ax=ax2)
 ax2.set_xlabel('Time')
 ax2.set_ylabel('Mismatch (-)')

From e1398d3de4e8fd69a99b6a807cfde4a1c764c152 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Fri, 5 Jul 2024 22:01:05 +0100
Subject: [PATCH 29/37] Apply suggestions from code review

Co-authored-by: Echedey Luis <80125792+echedey-ls@users.noreply.github.com>
Co-authored-by: Adam R. Jensen <39184289+AdamRJensen@users.noreply.github.com>
---
 docs/examples/spectrum/spectral_factor.py | 17 ++++++++++-------
 docs/sphinx/source/whatsnew/v0.11.1.rst   |  2 +-
 2 files changed, 11 insertions(+), 8 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 63504b2584..81072ddfe4 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -1,6 +1,7 @@
 """
 Spectral Mismatch Estimation
 ============================
+
 Comparison of spectral factor calculation methods used to estimate the spectral
 mismatch factor, :math:`M`, from atmospheric variable inputs.
 """
@@ -8,11 +9,11 @@
 # %%
 # Introduction
 # ------------
-# This example demonstrates how to use different `spectrum.spectral_factor`
+# This example demonstrates how to use different ``spectrum.spectral_factor_*``
 # models in pvlib-python to calculate the spectral mismatch factor, :math:`M`.
 # While :math:`M` for a photovoltaic (PV) module can be calculated exactly
 # using spectral irradiance and module spectral response data, these data are
-# not always available. pvlib-python provides several functions to estimate the
+# often not available. pvlib-python provides several functions to estimate the
 # spectral mismatch factor, :math:`M`, using proxies of the prevailing spectral
 # irradiance conditions, such as air mass and clearsky index, which are easily
 # derived from common ground-based measurements such as broadband irradiance.
@@ -76,8 +77,8 @@
 # relative airmass
 ama = amr*(meteo.pressure/1013.25)  # absolute airmass
 # %%
-# Now we calculate the clearsky index, :math:`k_c`, by comparing the TMY3 GHI
-# to the modelled clearsky GHI.
+# Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
+# to clearsky GHI.
 
 cs = loc.get_clearsky(meteo.index)
 kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)
@@ -98,10 +99,12 @@
 
 # Import some for a mc-Si module from the SAPM module database.
 module = pvlib.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
+#
 # Calculate M using the three models for an mc-Si PV module.
 m_sapm = pvlib.spectrum.spectral_factor_sapm(ama, module)
 m_pvspec = pvlib.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
 m_fs = pvlib.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
+
 df_results = pd.concat([m_sapm, m_pvspec, m_fs], axis=1)
 df_results.columns = ['SAPM', 'PVSPEC', 'FS']
 # %%
@@ -115,13 +118,13 @@
 fig1, (ax1, ax2) = plt.subplots(2, 1)
 df_results.plot(ax=ax1, legend=False)
 ax1.set_xlabel('Day')
-ax1.set_ylabel('Mismatch (-)')
+ax1.set_ylabel('Spectral mismatch (-)')
 ax1.set_ylim(0.85, 1.15)
 
 # We can also zoom in one one day, for example August 2nd.
 df_results.loc['2001-08-02'].plot(ax=ax2)
 ax2.set_xlabel('Time')
-ax2.set_ylabel('Mismatch (-)')
+ax2.set_ylabel('Spectral mismatch (-)')
 ax2.set_ylim(0.85, 1.15)
 
 plt.tight_layout()
@@ -131,7 +134,7 @@
 # %%
 # References
 # ----------
-# .. [1] Daxini, Rajiv, and Wu, Yupeng (2023). "Review of methods to account
+# .. [1] Daxini, R., and Wu, Y., 2023. "Review of methods to account
 #        for the solar spectral influence on photovoltaic device performance."
 #        Energy 286
 #        :doi:`10.1016/j.energy.2023.129461`
diff --git a/docs/sphinx/source/whatsnew/v0.11.1.rst b/docs/sphinx/source/whatsnew/v0.11.1.rst
index d29b62ef3f..a44ab96e36 100644
--- a/docs/sphinx/source/whatsnew/v0.11.1.rst
+++ b/docs/sphinx/source/whatsnew/v0.11.1.rst
@@ -25,7 +25,7 @@ Testing
 
 Documentation
 ~~~~~~~~~~~~~
-* Add new example to the example gallery to demonstrate the application of
+* Added gallery example demonstrating the application of
   several spectral mismatch factor models.
   (:issue:`2107`, :pull:`2114`)
 

From 69d9567a5a99cae62779c9243af4ae164c488908 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Sat, 6 Jul 2024 14:47:51 +0100
Subject: [PATCH 30/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 81072ddfe4..dabd30303e 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -2,8 +2,8 @@
 Spectral Mismatch Estimation
 ============================
 
-Comparison of spectral factor calculation methods used to estimate the spectral
-mismatch factor, :math:`M`, from atmospheric variable inputs.
+Comparison of methods to estimate the spectral mismatch factor
+from atmospheric variable inputs.
 """
 
 # %%
@@ -120,9 +120,11 @@
 ax1.set_xlabel('Day')
 ax1.set_ylabel('Spectral mismatch (-)')
 ax1.set_ylim(0.85, 1.15)
+ax1.legend(loc='upper center', frameon=False, ncols=3,
+           bbox_to_anchor=(0.5, 1.3))
 
 # We can also zoom in one one day, for example August 2nd.
-df_results.loc['2001-08-02'].plot(ax=ax2)
+df_results.loc['2001-08-02'].plot(ax=ax2, legend=False)
 ax2.set_xlabel('Time')
 ax2.set_ylabel('Spectral mismatch (-)')
 ax2.set_ylim(0.85, 1.15)

From 68edc03be2678a5041ccad3be34d0ff5294ab6bc Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 10:44:40 +0100
Subject: [PATCH 31/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Adam R. Jensen <39184289+AdamRJensen@users.noreply.github.com>
---
 docs/examples/spectrum/spectral_factor.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index dabd30303e..2ecdae5112 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -20,7 +20,8 @@
 # More information on a range of spectral factor models, as well as the
 # variables upon which they are based, can be found in [1]_.
 #
-# Let's import some data. This example uses a Typical Meteorological Year 3
+# To demonstrate this functionality, first we need to import some data.
+# This example uses a Typical Meteorological Year 3
 # (TMY3) file for the location of Greensboro, North Carolina, from the
 # pvlib-python data directory. This TMY3 file is constructed using the median
 # month from each year between 1980 and 2003, from which we extract the first

From 094a744dfa6c6a3720f2339f4a658685e1f57185 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 10:51:08 +0100
Subject: [PATCH 32/37] expand ama/amr initialism

---
 docs/examples/spectrum/spectral_factor.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 2ecdae5112..026484a971 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -74,9 +74,9 @@
     temperature=meteo.temp_air)
 solpos.index = meteo.index  # reset index to end of the hour
 
-amr = pvlib.atmosphere.get_relative_airmass(solpos.apparent_zenith).dropna()
-# relative airmass
-ama = amr*(meteo.pressure/1013.25)  # absolute airmass
+airmass_relative = pvlib.atmosphere.get_relative_airmass(
+                                               solpos.apparent_zenith).dropna()
+airmass_absolute = airmass_relative*(meteo.pressure/1013.25)
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
 # to clearsky GHI.
@@ -102,9 +102,11 @@
 module = pvlib.pvsystem.retrieve_sam('SandiaMod')['LG_LG290N1C_G3__2013_']
 #
 # Calculate M using the three models for an mc-Si PV module.
-m_sapm = pvlib.spectrum.spectral_factor_sapm(ama, module)
-m_pvspec = pvlib.spectrum.spectral_factor_pvspec(ama, kc, 'multisi')
-m_fs = pvlib.spectrum.spectral_factor_firstsolar(w, ama, 'multisi')
+m_sapm = pvlib.spectrum.spectral_factor_sapm(airmass_absolute, module)
+m_pvspec = pvlib.spectrum.spectral_factor_pvspec(airmass_absolute, kc,
+                                                 'multisi')
+m_fs = pvlib.spectrum.spectral_factor_firstsolar(w, airmass_absolute,
+                                                 'multisi')
 
 df_results = pd.concat([m_sapm, m_pvspec, m_fs], axis=1)
 df_results.columns = ['SAPM', 'PVSPEC', 'FS']

From fa2e3533e9f4869351c78e22a3e78b9f59886a81 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 10:53:54 +0100
Subject: [PATCH 33/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 026484a971..89b43f8c03 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -75,7 +75,7 @@
 solpos.index = meteo.index  # reset index to end of the hour
 
 airmass_relative = pvlib.atmosphere.get_relative_airmass(
-                                               solpos.apparent_zenith).dropna()
+    solpos.apparent_zenith).dropna()
 airmass_absolute = airmass_relative*(meteo.pressure/1013.25)
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI

From 782e0762274cf0d3eff18368f09dab618cd829e1 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 11:11:06 +0100
Subject: [PATCH 34/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 89b43f8c03..f4266c6c6c 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -81,7 +81,8 @@
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
 # to clearsky GHI.
 
-cs = loc.get_clearsky(meteo.index)
+cs = loc.get_clearsky(meteo.index.shift(freq="-30min"))
+cs.index = meteo.index  # reset index to end of the hour
 kc = pvlib.irradiance.clearsky_index(meteo.ghi, cs.ghi)
 # %%
 # :math:`W` is provided in the TMY3 file but in other cases can be calculated

From 19d6ddbf4031683fb41682636bf1c62813b3bf02 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 18:48:26 +0100
Subject: [PATCH 35/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index f4266c6c6c..8e37eb9bba 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -76,7 +76,7 @@
 
 airmass_relative = pvlib.atmosphere.get_relative_airmass(
     solpos.apparent_zenith).dropna()
-airmass_absolute = airmass_relative*(meteo.pressure/1013.25)
+airmass_absolute = pvlib.atmosphere.get_absolute_airmass(airmass_relative)
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
 # to clearsky GHI.

From 2db4db071b024749a4ada40de64747e1adf1fdde Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 19:57:59 +0100
Subject: [PATCH 36/37] Update docs/examples/spectrum/spectral_factor.py

Co-authored-by: Kevin Anderson <kevin.anderso@gmail.com>
---
 docs/examples/spectrum/spectral_factor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 8e37eb9bba..f94df3a160 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -76,7 +76,7 @@
 
 airmass_relative = pvlib.atmosphere.get_relative_airmass(
     solpos.apparent_zenith).dropna()
-airmass_absolute = pvlib.atmosphere.get_absolute_airmass(airmass_relative)
+airmass_absolute = pvlib.atmosphere.get_absolute_airmass(airmass_relative, pressure=meteo.pressure*100)
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
 # to clearsky GHI.

From 63d52cb47352f04340dced84d1b5b3b3c01fc825 Mon Sep 17 00:00:00 2001
From: RDaxini <143435106+RDaxini@users.noreply.github.com>
Date: Mon, 8 Jul 2024 20:01:44 +0100
Subject: [PATCH 37/37] Update spectral_factor.py

---
 docs/examples/spectrum/spectral_factor.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index f94df3a160..83ee488fb4 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -76,7 +76,8 @@
 
 airmass_relative = pvlib.atmosphere.get_relative_airmass(
     solpos.apparent_zenith).dropna()
-airmass_absolute = pvlib.atmosphere.get_absolute_airmass(airmass_relative, pressure=meteo.pressure*100)
+airmass_absolute = pvlib.atmosphere.get_absolute_airmass(airmass_relative,
+                                                         meteo.pressure*100)
 # %%
 # Now we calculate the clearsky index, :math:`k_c`, which is the ratio of GHI
 # to clearsky GHI.