Skip to content

Add poa_ prefix to returned names when return_components=True in transposition functions #2627

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
kandersolar merged 5 commits into from
Jan 15, 2026
Merged

Add poa_ prefix to returned names when return_components=True in transposition functions #2627

Show file tree
Hide file tree
Changes from 3 commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
05c6ec0
add `poa_` prefix
kandersolar Dec 16, 2025
4cc1859
update infinite_sheds
kandersolar Dec 16, 2025
d287ce0
whatsnew
kandersolar Dec 16, 2025
0732fc5
lint
kandersolar Jan 13, 2026
b076a8c
Update docs/sphinx/source/whatsnew/v0.13.2.rst
kandersolar Jan 15, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 4 additions & 1 deletion docs/sphinx/source/whatsnew/v0.13.2.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -9,7 +9,10 @@ Breaking Changes
* Following the removal of the NSRDB PSM3 API, the :func:`!pvlib.iotools.get_psm3`,
:func:`!pvlib.iotools.read_psm3`, and :func:`!pvlib.iotools.parse_psm3`
functions are removed. (:issue:`2581`, :pull:`2582`)

* Rename column names to be prefixed with ``"poa_"`` when ``return_components=True``
Comment thread
kandersolar marked this conversation as resolved.
Outdated
in :py:func:`~pvlib.irradiance.haydavies`, :py:func:`~pvlib.irradiance.perez`,
and :py:func:`~pvlib.irradiance.perez_driesse`. (:issue:`2529`, :pull:`2627`)


Deprecations
~~~~~~~~~~~~
Expand Down
5 changes: 3 additions & 2 deletions pvlib/bifacial/infinite_sheds.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -301,15 +301,16 @@ def get_irradiance_poa(surface_tilt, surface_azimuth, solar_zenith,
sky_diffuse_comps_horizontal = haydavies(0, 180, dhi, dni, dni_extra,
solar_zenith, solar_azimuth,
return_components=True)
circumsolar_horizontal = sky_diffuse_comps_horizontal['circumsolar']
circumsolar_horizontal = \
sky_diffuse_comps_horizontal['poa_circumsolar']

# Call haydavies a second time where circumsolar_normal is facing
# directly towards sun, and can be added to DNI
sky_diffuse_comps_normal = haydavies(solar_zenith, solar_azimuth, dhi,
dni, dni_extra, solar_zenith,
solar_azimuth,
return_components=True)
circumsolar_normal = sky_diffuse_comps_normal['circumsolar']
circumsolar_normal = sky_diffuse_comps_normal['poa_circumsolar']

dhi = dhi - circumsolar_horizontal
dni = dni + circumsolar_normal
Expand Down
51 changes: 26 additions & 25 deletions pvlib/irradiance.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -793,10 +793,11 @@ def haydavies(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

diffuse_components : OrderedDict (array input) or DataFrame (Series input)
Keys/columns are:
* sky_diffuse: Total sky diffuse
* isotropic
* circumsolar
* horizon (always zero, not accounted for by the Hay-Davies model)
* poa_sky_diffuse: Total sky diffuse
* poa_isotropic
* poa_circumsolar
* poa_horizon (always zero, not accounted for by the
Hay-Davies model)

Notes
------
Expand Down Expand Up @@ -855,13 +856,13 @@ def haydavies(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

if return_components:
diffuse_components = OrderedDict()
diffuse_components['sky_diffuse'] = sky_diffuse
diffuse_components['poa_sky_diffuse'] = sky_diffuse

# Calculate the individual components
diffuse_components['isotropic'] = poa_isotropic
diffuse_components['circumsolar'] = poa_circumsolar
diffuse_components['horizon'] = np.where(
np.isnan(diffuse_components['isotropic']), np.nan, 0.)
diffuse_components['poa_isotropic'] = poa_isotropic
diffuse_components['poa_circumsolar'] = poa_circumsolar
diffuse_components['poa_horizon'] = np.where(
np.isnan(diffuse_components['poa_isotropic']), np.nan, 0.)

if isinstance(sky_diffuse, pd.Series):
diffuse_components = pd.DataFrame(diffuse_components)
Expand Down Expand Up @@ -1111,10 +1112,10 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

diffuse_components : OrderedDict (array input) or DataFrame (Series input)
Keys/columns are:
* sky_diffuse: Total sky diffuse
* isotropic
* circumsolar
* horizon
* poa_sky_diffuse: Total sky diffuse
* poa_isotropic
* poa_circumsolar
* poa_horizon


References
Expand Down Expand Up @@ -1197,12 +1198,12 @@ def perez(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

if return_components:
diffuse_components = OrderedDict()
diffuse_components['sky_diffuse'] = sky_diffuse
diffuse_components['poa_sky_diffuse'] = sky_diffuse

# Calculate the different components
diffuse_components['isotropic'] = dhi * term1
diffuse_components['circumsolar'] = dhi * term2
diffuse_components['horizon'] = dhi * term3
diffuse_components['poa_isotropic'] = dhi * term1
diffuse_components['poa_circumsolar'] = dhi * term2
diffuse_components['poa_horizon'] = dhi * term3

# Set values of components to 0 when sky_diffuse is 0
mask = sky_diffuse == 0
Expand Down Expand Up @@ -1353,10 +1354,10 @@ def perez_driesse(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

diffuse_components : OrderedDict (array input) or DataFrame (Series input)
Keys/columns are:
* sky_diffuse: Total sky diffuse
* isotropic
* circumsolar
* horizon
* poa_sky_diffuse: Total sky diffuse
* poa_isotropic
* poa_circumsolar
* poa_horizon

Notes
-----
Expand Down Expand Up @@ -1417,12 +1418,12 @@ def perez_driesse(surface_tilt, surface_azimuth, dhi, dni, dni_extra,

if return_components:
diffuse_components = OrderedDict()
diffuse_components['sky_diffuse'] = sky_diffuse
diffuse_components['poa_sky_diffuse'] = sky_diffuse

# Calculate the different components
diffuse_components['isotropic'] = dhi * term1
diffuse_components['circumsolar'] = dhi * term2
diffuse_components['horizon'] = dhi * term3
diffuse_components['poa_isotropic'] = dhi * term1
diffuse_components['poa_circumsolar'] = dhi * term2
diffuse_components['poa_horizon'] = dhi * term3

if isinstance(sky_diffuse, pd.Series):
diffuse_components = pd.DataFrame(diffuse_components)
Expand Down
40 changes: 19 additions & 21 deletions tests/test_irradiance.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -210,12 +210,14 @@


def test_haydavies_components(irrad_data, ephem_data, dni_et):
keys = ['poa_sky_diffuse', 'poa_isotropic', 'poa_circumsolar',
'poa_horizon']

Check failure on line 214 in tests/test_irradiance.py

View workflow job for this annotation

GitHub Actions / flake8-linter 

E127 continuation line over-indented for visual indent
Comment thread
kandersolar marked this conversation as resolved.
Outdated
expected = pd.DataFrame(np.array(
[[0, 27.1775, 102.9949, 33.1909],
[0, 27.1775, 30.1818, 27.9837],
[0, 0, 72.8130, 5.2071],
[0, 0, 0, 0]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
columns=keys,
index=irrad_data.index
)
# pandas
Expand All @@ -229,23 +231,16 @@
40, 180, irrad_data['dhi'].values, irrad_data['dni'].values, dni_et,
ephem_data['apparent_zenith'].values, ephem_data['azimuth'].values,
return_components=True)
assert_allclose(result['sky_diffuse'], expected['sky_diffuse'], atol=1e-4)
assert_allclose(result['isotropic'], expected['isotropic'], atol=1e-4)
assert_allclose(result['circumsolar'], expected['circumsolar'], atol=1e-4)
assert_allclose(result['horizon'], expected['horizon'], atol=1e-4)
for key in keys:
assert_allclose(result[key], expected[key], atol=1e-4)
assert isinstance(result, dict)
# scalar
result = irradiance.haydavies(
40, 180, irrad_data['dhi'].values[-1], irrad_data['dni'].values[-1],
dni_et[-1], ephem_data['apparent_zenith'].values[-1],
ephem_data['azimuth'].values[-1], return_components=True)
assert_allclose(result['sky_diffuse'], expected['sky_diffuse'].iloc[-1],
atol=1e-4)
assert_allclose(result['isotropic'], expected['isotropic'].iloc[-1],
atol=1e-4)
assert_allclose(result['circumsolar'], expected['circumsolar'].iloc[-1],
atol=1e-4)
assert_allclose(result['horizon'], expected['horizon'].iloc[-1], atol=1e-4)
for key in keys:
assert_allclose(result[key], expected[key].iloc[-1], atol=1e-4)
assert isinstance(result, dict)


Expand Down Expand Up @@ -312,13 +307,14 @@
[0., 26.84138589, np.nan, 31.72696071],
[0., 0., np.nan, 4.47966439],
[0., 4.62212181, np.nan, 9.25316454]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
columns=['poa_sky_diffuse', 'poa_isotropic', 'poa_circumsolar',
'poa_horizon'],
index=irrad_data.index
)
expected_for_sum = expected['sky_diffuse'].copy()
expected_for_sum = expected['poa_sky_diffuse'].copy()
expected_for_sum.iloc[2] = 0
sum_components = out.iloc[:, 1:].sum(axis=1)
sum_components.name = 'sky_diffuse'
sum_components.name = 'poa_sky_diffuse'

assert_frame_equal(out, expected, check_less_precise=2)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
Expand All @@ -338,13 +334,14 @@
[0., 25.806, np.nan, 33.181],
[0., 0.000, np.nan, 4.197],
[0., 4.184, np.nan, 10.018]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
columns=['poa_sky_diffuse', 'poa_isotropic', 'poa_circumsolar',
'poa_horizon'],
index=irrad_data.index
)
expected_for_sum = expected['sky_diffuse'].copy()
expected_for_sum = expected['poa_sky_diffuse'].copy()
expected_for_sum.iloc[2] = 0
sum_components = out.iloc[:, 1:].sum(axis=1)
sum_components.name = 'sky_diffuse'
sum_components.name = 'poa_sky_diffuse'

assert_frame_equal(out, expected, check_less_precise=2)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
Expand Down Expand Up @@ -384,13 +381,14 @@
[166.785419, 142.24475, 119.173875, 83.525150, 45.725931],
[113.548755, 16.09757, 9.956174, 3.142467, 0],
[1.076010, -6.13353, -5.262151, -3.831230, -2.208923]]).T,
columns=['sky_diffuse', 'isotropic', 'circumsolar', 'horizon'],
columns=['poa_sky_diffuse', 'poa_isotropic', 'poa_circumsolar',
'poa_horizon'],
index=times
)

expected_for_sum = expected['sky_diffuse'].copy()
expected_for_sum = expected['poa_sky_diffuse'].copy()
sum_components = out.iloc[:, 1:].sum(axis=1)
sum_components.name = 'sky_diffuse'
sum_components.name = 'poa_sky_diffuse'

assert_frame_equal(out, expected, check_less_precise=2)
assert_series_equal(sum_components, expected_for_sum, check_less_precise=2)
Expand Down
Loading