diff --git a/.github/workflows/flake8.yml b/.github/workflows/flake8.yml
index 8e054ecb08..09c022f51c 100644
--- a/.github/workflows/flake8.yml
+++ b/.github/workflows/flake8.yml
@@ -12,7 +12,7 @@ jobs:
with:
python-version: '3.11'
- name: Install Flake8 5.0.4 linter
- run: pip install flake8==5.0.4 # use this version for --diff option
+ run: pip install flake8==5.0.4 # use this version for --diff option, should match version in pyproject.toml
- name: Setup Flake8 output matcher for PR annotations
run: echo '::add-matcher::.github/workflows/flake8-linter-matcher.json'
- name: Fetch pull request target branch
diff --git a/docs/examples/spectrum/spectral_factor.py b/docs/examples/spectrum/spectral_factor.py
index 83ee488fb4..a1638340c4 100644
--- a/docs/examples/spectrum/spectral_factor.py
+++ b/docs/examples/spectrum/spectral_factor.py
@@ -46,7 +46,8 @@
# 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` and five SAPM coefficients :math:`A0` -
+# :math:`A4`
# - :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
@@ -104,7 +105,14 @@
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(airmass_absolute, module)
+m_sapm = pvlib.spectrum.spectral_factor_sapm(
+ airmass_absolute,
+ module["A0"],
+ module["A1"],
+ module["A2"],
+ module["A3"],
+ module["A4"],
+)
m_pvspec = pvlib.spectrum.spectral_factor_pvspec(airmass_absolute, kc,
'multisi')
m_fs = pvlib.spectrum.spectral_factor_firstsolar(w, airmass_absolute,
diff --git a/pvlib/iam.py b/pvlib/iam.py
index 161de84589..eb9326245b 100644
--- a/pvlib/iam.py
+++ b/pvlib/iam.py
@@ -7,22 +7,14 @@
IAM is typically a function of the angle of incidence (AOI) of the direct
irradiance to the module's surface.
"""
+import functools
import numpy as np
import pandas as pd
-import functools
+import scipy.interpolate
from scipy.optimize import minimize
-from pvlib.tools import cosd, sind, acosd
-# a dict of required parameter names for each IAM model
-# keys are the function names for the IAM models
-_IAM_MODEL_PARAMS = {
- 'ashrae': {'b'},
- 'physical': {'n', 'K', 'L'},
- 'martin_ruiz': {'a_r'},
- 'sapm': {'B0', 'B1', 'B2', 'B3', 'B4', 'B5'},
- 'interp': {'theta_ref', 'iam_ref'}
-}
+from pvlib.tools import cosd, sind, acosd
def ashrae(aoi, b=0.05):
@@ -75,9 +67,11 @@ def ashrae(aoi, b=0.05):
See Also
--------
- pvlib.iam.physical
- pvlib.iam.martin_ruiz
pvlib.iam.interp
+ pvlib.iam.martin_ruiz
+ pvlib.iam.physical
+ pvlib.iam.sapm
+ pvlib.iam.schlick
"""
iam = 1 - b * (1 / np.cos(np.radians(aoi)) - 1)
@@ -92,7 +86,7 @@ def ashrae(aoi, b=0.05):
return iam
-def physical(aoi, n=1.526, K=4.0, L=0.002, *, n_ar=None):
+def physical(aoi, n=1.526, K=4.0, L=0.002, n_ar=None):
r"""
Determine the incidence angle modifier using refractive index ``n``,
extinction coefficient ``K``, glazing thickness ``L`` and refractive
@@ -151,10 +145,11 @@ def physical(aoi, n=1.526, K=4.0, L=0.002, *, n_ar=None):
See Also
--------
- pvlib.iam.martin_ruiz
pvlib.iam.ashrae
pvlib.iam.interp
+ pvlib.iam.martin_ruiz
pvlib.iam.sapm
+ pvlib.iam.schlick
"""
n1, n3 = 1, n
if n_ar is None or np.allclose(n_ar, n1):
@@ -286,11 +281,12 @@ def martin_ruiz(aoi, a_r=0.16):
See Also
--------
- pvlib.iam.martin_ruiz_diffuse
- pvlib.iam.physical
pvlib.iam.ashrae
pvlib.iam.interp
+ pvlib.iam.physical
pvlib.iam.sapm
+ pvlib.iam.schlick
+ pvlib.iam.martin_ruiz_diffuse
'''
# Contributed by Anton Driesse (@adriesse), PV Performance Labs. July, 2019
@@ -314,7 +310,7 @@ def martin_ruiz(aoi, a_r=0.16):
def martin_ruiz_diffuse(surface_tilt, a_r=0.16, c1=0.4244, c2=None):
'''
- Determine the incidence angle modifiers (iam) for diffuse sky and
+ Determine the incidence angle modifiers (IAM) for diffuse sky and
ground-reflected irradiance using the Martin and Ruiz incident angle model.
Parameters
@@ -373,10 +369,8 @@ def martin_ruiz_diffuse(surface_tilt, a_r=0.16, c1=0.4244, c2=None):
See Also
--------
pvlib.iam.martin_ruiz
- pvlib.iam.physical
- pvlib.iam.ashrae
- pvlib.iam.interp
- pvlib.iam.sapm
+ pvlib.iam.marion_diffuse
+ pvlib.iam.schlick_diffuse
'''
# Contributed by Anton Driesse (@adriesse), PV Performance Labs. Oct. 2019
@@ -463,15 +457,14 @@ def interp(aoi, theta_ref, iam_ref, method='linear', normalize=True):
See Also
--------
- pvlib.iam.physical
pvlib.iam.ashrae
pvlib.iam.martin_ruiz
+ pvlib.iam.physical
pvlib.iam.sapm
+ pvlib.iam.schlick
'''
# Contributed by Anton Driesse (@adriesse), PV Performance Labs. July, 2019
- from scipy.interpolate import interp1d
-
# Scipy doesn't give the clearest feedback, so check number of points here.
MIN_REF_VALS = {'linear': 2, 'quadratic': 3, 'cubic': 4, 1: 2, 2: 3, 3: 4}
@@ -483,8 +476,9 @@ def interp(aoi, theta_ref, iam_ref, method='linear', normalize=True):
raise ValueError("Negative value(s) found in 'iam_ref'. "
"This is not physically possible.")
- interpolator = interp1d(theta_ref, iam_ref, kind=method,
- fill_value='extrapolate')
+ interpolator = scipy.interpolate.interp1d(
+ theta_ref, iam_ref, kind=method, fill_value='extrapolate'
+ )
aoi_input = aoi
aoi = np.asanyarray(aoi)
@@ -501,9 +495,19 @@ def interp(aoi, theta_ref, iam_ref, method='linear', normalize=True):
return iam
-def sapm(aoi, module, upper=None):
+def sapm(aoi, B0, B1, B2, B3, B4, B5, upper=None):
r"""
- Determine the incidence angle modifier (IAM) using the SAPM model.
+ Caclulate the incidence angle modifier (IAM), :math:`f_2`, using the
+ Sandia Array Performance Model (SAPM).
+
+ The SAPM incidence angle modifier is part of the broader Sandia Array
+ Performance Model, which defines five points on an IV curve using empirical
+ module-specific coefficients. Module coefficients for the SAPM are
+ available in the SAPM database and can be retrieved for use through
+ :py:func:`pvlib.pvsystem.retrieve_sam()`. More details on the SAPM can be
+ found in [1]_, while a full description of the procedure to determine the
+ empirical model coefficients, including those for the SAPM incidence angle
+ modifier, can be found in [2]_.
Parameters
----------
@@ -511,20 +515,46 @@ def sapm(aoi, module, upper=None):
Angle of incidence in degrees. Negative input angles will return
zeros.
- module : dict-like
- A dict or Series with the SAPM IAM model parameters.
- See the :py:func:`sapm` notes section for more details.
+ B0 : float
+ The coefficient of the degree-0 polynomial term.
+
+ B1 : float
+ The coefficient of the degree-1 polynomial term.
+
+ B2 : float
+ The coefficient of the degree-2 polynomial term.
+
+ B3 : float
+ The coefficient of the degree-3 polynomial term.
+
+ B4 : float
+ The coefficient of the degree-4 polynomial term.
+
+ B5 : float
+ The coefficient of the degree-5 polynomial term.
upper : float, optional
- Upper limit on the results.
+ Upper limit on the results. None means no upper limiting.
Returns
-------
iam : numeric
- The SAPM angle of incidence loss coefficient, termed F2 in [1]_.
+ The SAPM angle of incidence loss coefficient, :math:`f_2` in [1]_.
Notes
-----
+ The SAPM spectral correction functions parameterises :math:`f_2` as a
+ fifth-order polynomial function of angle of incidence:
+
+ .. math::
+
+ f_2 = b_0 + b_1 AOI + b_2 AOI^2 + b_3 AOI^3 + b_4 AOI^4 + b_5 AOI^5.
+
+ where :math:`f_2` is the spectral mismatch factor, :math:`b_{0-5}` are
+ the module-specific coefficients, and :math:`AOI` is the angle of
+ incidence. More detail on how this incidence angle modifier function was
+ developed can be found in [3]_. Its measurement is described in [4]_.
+
The SAPM [1]_ traditionally does not define an upper limit on the AOI
loss function and values slightly exceeding 1 may exist for moderate
angles of incidence (15-40 degrees). However, users may consider
@@ -532,30 +562,34 @@ def sapm(aoi, module, upper=None):
References
----------
- .. [1] King, D. et al, 2004, "Sandia Photovoltaic Array Performance
- Model", SAND Report 3535, Sandia National Laboratories, Albuquerque,
- NM.
-
- .. [2] B.H. King et al, "Procedure to Determine Coefficients for the
- Sandia Array Performance Model (SAPM)," SAND2016-5284, Sandia
- National Laboratories (2016).
-
- .. [3] B.H. King et al, "Recent Advancements in Outdoor Measurement
- Techniques for Angle of Incidence Effects," 42nd IEEE PVSC (2015).
- :doi:`10.1109/PVSC.2015.7355849`
+ .. [1] King, D., Kratochvil, J., and Boyson W. (2004), "Sandia
+ Photovoltaic Array Performance Model", (No. SAND2004-3535), Sandia
+ National Laboratories, Albuquerque, NM (United States).
+ :doi:`10.2172/919131`
+ .. [2] King, B., Hansen, C., Riley, D., Robinson, C., and Pratt, L.
+ (2016). Procedure to determine coefficients for the Sandia Array
+ Performance Model (SAPM) (No. SAND2016-5284). Sandia National
+ Laboratories, Albuquerque, NM (United States).
+ :doi:`10.2172/1256510`
+ .. [3] King, D., Kratochvil, J., and Boyson, W. "Measuring solar spectral
+ and angle-of-incidence effects on photovoltaic modules and solar
+ irradiance sensors." Conference Record of the 26th IEEE Potovoltaic
+ Specialists Conference (PVSC). IEEE, 1997.
+ :doi:`10.1109/PVSC.1997.654283`
+ .. [4] B.H. King et al, "Recent Advancements in Outdoor Measurement
+ Techniques for Angle of Incidence Effects," 42nd IEEE PVSC (2015).
+ :doi:`10.1109/PVSC.2015.7355849`
See Also
--------
- pvlib.iam.physical
pvlib.iam.ashrae
- pvlib.iam.martin_ruiz
pvlib.iam.interp
+ pvlib.iam.martin_ruiz
+ pvlib.iam.physical
+ pvlib.iam.schlick
"""
- aoi_coeff = [module['B5'], module['B4'], module['B3'], module['B2'],
- module['B1'], module['B0']]
-
- iam = np.polyval(aoi_coeff, aoi)
+ iam = np.polyval([B5, B4, B3, B2, B1, B0], aoi)
iam = np.clip(iam, 0, upper)
# nan tolerant masking
aoi_lt_0 = np.full_like(aoi, False, dtype='bool')
@@ -575,9 +609,11 @@ def marion_diffuse(model, surface_tilt, **kwargs):
Parameters
----------
- model : str
+ model : str or callable
The IAM function to evaluate across solid angle. Must be one of
- `'ashrae', 'physical', 'martin_ruiz', 'sapm', 'schlick'`.
+ `'ashrae', `interp`, 'martin_ruiz', 'physical', 'sapm', 'schlick'`
+ or be callable. If callable, then must take numeric AOI in degrees
+ as input and return the fractional IAM.
surface_tilt : numeric
Surface tilt angles in decimal degrees.
@@ -602,6 +638,14 @@ def marion_diffuse(model, surface_tilt, **kwargs):
See Also
--------
pvlib.iam.marion_integrate
+ pvlib.iam.ashrae
+ pvlib.iam.interp
+ pvlib.iam.martin_ruiz
+ pvlib.iam.physical
+ pvlib.iam.sapm
+ pvlib.iam.schlick
+ pvlib.iam.martin_ruiz_diffuse
+ pvlib.iam.schlick_diffuse
References
----------
@@ -613,7 +657,7 @@ def marion_diffuse(model, surface_tilt, **kwargs):
Examples
--------
>>> marion_diffuse('physical', surface_tilt=20)
- {'sky': 0.9539178294437575,
+ {'sky': 0.953917829443757
'horizon': 0.7652650139134007,
'ground': 0.6387140117795903}
@@ -622,26 +666,28 @@ def marion_diffuse(model, surface_tilt, **kwargs):
'horizon': array([0.86478428, 0.91825792]),
'ground': array([0.77004435, 0.8522436 ])}
"""
+ if callable(model):
+ # A callable IAM model function was specified.
+ func = model
+ else:
+ # Check that a builtin IAM function was specified.
+ builtin_models = _get_builtin_models()
- models = {
- 'physical': physical,
- 'ashrae': ashrae,
- 'sapm': sapm,
- 'martin_ruiz': martin_ruiz,
- 'schlick': schlick,
- }
+ try:
+ model = builtin_models[model]
+ except KeyError as exc:
+ raise ValueError(
+ f'model must be one of: {builtin_models.keys()}'
+ ) from exc
- try:
- iam_model = models[model]
- except KeyError:
- raise ValueError('model must be one of: ' + str(list(models.keys())))
+ func = model["func"]
- iam_function = functools.partial(iam_model, **kwargs)
- iam = {}
- for region in ['sky', 'horizon', 'ground']:
- iam[region] = marion_integrate(iam_function, surface_tilt, region)
+ iam_function = functools.partial(func, **kwargs)
- return iam
+ return {
+ region: marion_integrate(iam_function, surface_tilt, region)
+ for region in ['sky', 'horizon', 'ground']
+ }
def marion_integrate(function, surface_tilt, region, num=None):
@@ -814,10 +860,6 @@ def schlick(aoi):
iam : numeric
The incident angle modifier.
- See Also
- --------
- pvlib.iam.schlick_diffuse
-
References
----------
.. [1] Schlick, C. An inexpensive BRDF model for physically-based
@@ -827,6 +869,15 @@ def schlick(aoi):
for Diffuse radiation on Inclined photovoltaic Surfaces (FEDIS)",
Renewable and Sustainable Energy Reviews, vol. 161, 112362. June 2022.
:doi:`10.1016/j.rser.2022.112362`
+
+ See Also
+ --------
+ pvlib.iam.ashrae
+ pvlib.iam.interp
+ pvlib.iam.martin_ruiz
+ pvlib.iam.physical
+ pvlib.iam.sapm
+ pvlib.iam.schlick_diffuse
"""
iam = 1 - (1 - cosd(aoi)) ** 5
iam = np.where(np.abs(aoi) >= 90.0, 0.0, iam)
@@ -875,10 +926,6 @@ def schlick_diffuse(surface_tilt):
iam_ground : numeric
The incident angle modifier for ground-reflected diffuse.
- See Also
- --------
- pvlib.iam.schlick
-
Notes
-----
The analytical integration of the Schlick approximation was derived
@@ -913,6 +960,12 @@ def schlick_diffuse(surface_tilt):
for Diffuse radiation on Inclined photovoltaic Surfaces (FEDIS)",
Renewable and Sustainable Energy Reviews, vol. 161, 112362. June 2022.
:doi:`10.1016/j.rser.2022.112362`
+
+ See Also
+ --------
+ pvlib.iam.schlick
+ pvlib.iam.marion_diffuse
+ pvlib.iam.martin_ruiz_diffuse
"""
# these calculations are as in [2]_, but with the refractive index
# weighting coefficient w set to 1.0 (so it is omitted)
@@ -943,27 +996,96 @@ def schlick_diffuse(surface_tilt):
return cuk, cug
-def _get_model(model_name):
- # check that model is implemented
- model_dict = {'ashrae': ashrae, 'martin_ruiz': martin_ruiz,
- 'physical': physical}
+def _get_builtin_models():
+ """
+ Get builtin IAM models' usage information.
+
+ Returns
+ -------
+ info : dict
+ A dictionary of dictionaries keyed by builtin IAM model name, with
+ each model dictionary containing:
+
+ * 'func': callable
+ The callable model function
+ * 'params_required': set of str
+ The model function's required parameters
+ * 'params_optional': set of str
+ The model function's optional parameters
+
+ See Also
+ --------
+ pvlib.iam.ashrae
+ pvlib.iam.interp
+ pvlib.iam.martin_ruiz
+ pvlib.iam.physical
+ pvlib.iam.sapm
+ pvlib.iam.schlick
+ """
+ return {
+ 'ashrae': {
+ 'func': ashrae,
+ 'params_required': set(),
+ 'params_optional': {'b'},
+ },
+ 'interp': {
+ 'func': interp,
+ 'params_required': {'theta_ref', 'iam_ref'},
+ 'params_optional': {'method', 'normalize'},
+ },
+ 'martin_ruiz': {
+ 'func': martin_ruiz,
+ 'params_required': set(),
+ 'params_optional': {'a_r'},
+ },
+ 'physical': {
+ 'func': physical,
+ 'params_required': set(),
+ 'params_optional': {'n', 'K', 'L', 'n_ar'},
+ },
+ 'sapm': {
+ 'func': sapm,
+ 'params_required': {'B0', 'B1', 'B2', 'B3', 'B4', 'B5'},
+ 'params_optional': {'upper'},
+ },
+ 'schlick': {
+ 'func': schlick,
+ 'params_required': set(),
+ 'params_optional': set(),
+ },
+ }
+
+
+def _get_fittable_or_convertable_model(builtin_model_name):
+ # check that model is implemented and fittable or convertable
+ implemented_builtin_models = {
+ 'ashrae': ashrae, 'martin_ruiz': martin_ruiz, 'physical': physical,
+ }
+
try:
- model = model_dict[model_name]
- except KeyError:
- raise NotImplementedError(f"The {model_name} model has not been "
- "implemented")
+ return implemented_builtin_models[builtin_model_name]
+ except KeyError as exc:
+ raise NotImplementedError(
+ f"No implementation for model {builtin_model_name}"
+ ) from exc
+
- return model
+def _check_params(builtin_model_name, params):
+ # check that parameters passed in with IAM model belong to the model
+ handed_params = set(params.keys())
+ builtin_model = _get_builtin_models()[builtin_model_name]
+ expected_params = builtin_model["params_required"].union(
+ builtin_model["params_optional"]
+ )
+ if builtin_model_name == 'physical':
+ expected_params.remove('n_ar') # Not required.
-def _check_params(model_name, params):
- # check that the parameters passed in with the model
- # belong to the model
- exp_params = _IAM_MODEL_PARAMS[model_name]
- if set(params.keys()) != exp_params:
- raise ValueError(f"The {model_name} model was expecting to be passed "
- "{', '.join(list(exp_params))}, but "
- "was handed {', '.join(list(params.keys()))}")
+ if handed_params != expected_params:
+ raise ValueError(
+ f"The {builtin_model_name} model was expecting to be passed"
+ f"{expected_params}, but was handed {handed_params}"
+ )
def _sin_weight(aoi):
@@ -1179,8 +1301,8 @@ def convert(source_name, source_params, target_name, weight=_sin_weight,
pvlib.iam.martin_ruiz
pvlib.iam.physical
"""
- source = _get_model(source_name)
- target = _get_model(target_name)
+ source = _get_fittable_or_convertable_model(source_name)
+ target = _get_fittable_or_convertable_model(target_name)
aoi = np.linspace(0, 90, 91)
_check_params(source_name, source_params)
@@ -1277,7 +1399,7 @@ def fit(measured_aoi, measured_iam, model_name, weight=_sin_weight, xtol=None):
pvlib.iam.martin_ruiz
pvlib.iam.physical
"""
- target = _get_model(model_name)
+ target = _get_fittable_or_convertable_model(model_name)
if model_name == "physical":
bounds = [(0, 0.08), (1, 2)]
diff --git a/pvlib/modelchain.py b/pvlib/modelchain.py
index 8456aac114..365afd7b4f 100644
--- a/pvlib/modelchain.py
+++ b/pvlib/modelchain.py
@@ -6,14 +6,15 @@
the time to read the source code for the module.
"""
+from dataclasses import dataclass, field
from functools import partial
import itertools
+from typing import Optional, Tuple, TypeVar, Union
import warnings
+
import pandas as pd
-from dataclasses import dataclass, field
-from typing import Union, Tuple, Optional, TypeVar
-from pvlib import pvsystem, iam
+from pvlib import pvsystem
import pvlib.irradiance # avoid name conflict with full import
from pvlib.pvsystem import _DC_MODEL_PARAMS
from pvlib.tools import _build_kwargs
@@ -289,12 +290,12 @@ class ModelChain:
Parameters
----------
system : PVSystem
- A :py:class:`~pvlib.pvsystem.PVSystem` object that represents
- the connected set of modules, inverters, etc.
+ A :py:class:`~pvlib.pvsystem.PVSystem` object that represents the
+ connected set of modules, inverters, etc.
location : Location
- A :py:class:`~pvlib.location.Location` object that represents
- the physical location at which to evaluate the model.
+ A :py:class:`~pvlib.location.Location` object that represents the
+ physical location at which to evaluate the model.
clearsky_model : str, default 'ineichen'
Passed to location.get_clearsky. Only used when DNI is not found in
@@ -311,31 +312,29 @@ class ModelChain:
dc_model : str, or function, optional
If not specified, the model will be inferred from the parameters that
- are common to all of system.arrays[i].module_parameters.
- Valid strings are 'sapm', 'desoto', 'cec', 'pvsyst', 'pvwatts'.
- The ModelChain instance will be passed as the first argument
- to a user-defined function.
+ are common to all of system.arrays[i].module_parameters. Valid strings
+ are 'sapm', 'desoto', 'cec', 'pvsyst', 'pvwatts'. The ModelChain
+ instance will be passed as the first argument to a user-defined
+ function.
ac_model : str, or function, optional
If not specified, the model will be inferred from the parameters that
- are common to all of system.inverter_parameters.
- Valid strings are 'sandia', 'adr', 'pvwatts'. The
- ModelChain instance will be passed as the first argument to a
- user-defined function.
+ are common to all of system.inverter_parameters. Valid strings are
+ 'sandia', 'adr', 'pvwatts'. The ModelChain instance will be passed as
+ the first argument to a user-defined function.
aoi_model : str, or function, optional
If not specified, the model will be inferred from the parameters that
- are common to all of system.arrays[i].module_parameters.
- Valid strings are 'physical', 'ashrae', 'sapm', 'martin_ruiz',
- 'interp' and 'no_loss'. The ModelChain instance will be passed as the
- first argument to a user-defined function.
+ are common to all of system.arrays[i].module_parameters. Valid strings
+ are 'ashrae', 'interp', 'martin_ruiz', 'physical', 'sapm', 'schlick',
+ 'no_loss'. The ModelChain instance will be passed as the first
+ argument to a user-defined function.
spectral_model : str, or function, optional
If not specified, the model will be inferred from the parameters that
- are common to all of system.arrays[i].module_parameters.
- Valid strings are 'sapm', 'first_solar', 'no_loss'.
- The ModelChain instance will be passed as the first argument to
- a user-defined function.
+ are common to all of system.arrays[i].module_parameters. Valid strings
+ are 'sapm', 'first_solar', 'no_loss'. The ModelChain instance will be
+ passed as the first argument to a user-defined function.
temperature_model : str or function, optional
Valid strings are: 'sapm', 'pvsyst', 'faiman', 'fuentes', 'noct_sam'.
@@ -386,7 +385,6 @@ def __init__(self, system, location,
self.results = ModelChainResult()
-
@classmethod
def with_pvwatts(cls, system, location,
clearsky_model='ineichen',
@@ -770,62 +768,98 @@ def aoi_model(self, model):
model = model.lower()
if model == 'ashrae':
self._aoi_model = self.ashrae_aoi_loss
- elif model == 'physical':
- self._aoi_model = self.physical_aoi_loss
- elif model == 'sapm':
- self._aoi_model = self.sapm_aoi_loss
- elif model == 'martin_ruiz':
- self._aoi_model = self.martin_ruiz_aoi_loss
elif model == 'interp':
self._aoi_model = self.interp_aoi_loss
+ elif model == 'martin_ruiz':
+ self._aoi_model = self.martin_ruiz_aoi_loss
elif model == 'no_loss':
self._aoi_model = self.no_aoi_loss
+ elif model == 'physical':
+ self._aoi_model = self.physical_aoi_loss
+ elif model == 'sapm':
+ self._aoi_model = self.sapm_aoi_loss
+ elif model == 'schlick':
+ self._aoi_model = self.schlick_aoi_loss
else:
raise ValueError(model + ' is not a valid aoi loss model')
- else:
+ elif callable(model):
self._aoi_model = partial(model, self)
+ else:
+ raise ValueError(model + ' is not a valid aoi loss model')
def infer_aoi_model(self):
+ """
+ Infer AOI model by checking for all required model paramters or at
+ least one optional model parameter in module_parameter collected
+ across all arrays.
+ """
module_parameters = tuple(
- array.module_parameters for array in self.system.arrays)
+ array.module_parameters for array in self.system.arrays
+ )
params = _common_keys(module_parameters)
- if iam._IAM_MODEL_PARAMS['physical'] <= params:
- return self.physical_aoi_loss
- elif iam._IAM_MODEL_PARAMS['sapm'] <= params:
- return self.sapm_aoi_loss
- elif iam._IAM_MODEL_PARAMS['ashrae'] <= params:
+ builtin_models = pvlib.iam._get_builtin_models()
+
+ if (builtin_models['ashrae']["params_required"] and (
+ builtin_models['ashrae']["params_required"] <= params)) or (
+ not builtin_models['ashrae']["params_required"] and
+ (builtin_models['ashrae']["params_optional"] & params)
+ ):
return self.ashrae_aoi_loss
- elif iam._IAM_MODEL_PARAMS['martin_ruiz'] <= params:
- return self.martin_ruiz_aoi_loss
- elif iam._IAM_MODEL_PARAMS['interp'] <= params:
+
+ if (builtin_models['interp']["params_required"] and (
+ builtin_models['interp']["params_required"] <= params)) or (
+ not builtin_models['interp']["params_required"] and
+ (builtin_models['interp']["params_optional"] & params)
+ ):
return self.interp_aoi_loss
- else:
- raise ValueError('could not infer AOI model from '
- 'system.arrays[i].module_parameters. Check that '
- 'the module_parameters for all Arrays in '
- 'system.arrays contain parameters for the '
- 'physical, aoi, ashrae, martin_ruiz or interp '
- 'model; explicitly set the model with the '
- 'aoi_model kwarg; or set aoi_model="no_loss".')
+
+ if (builtin_models['martin_ruiz']["params_required"] and (
+ builtin_models['martin_ruiz']["params_required"] <= params)) or (
+ not builtin_models['martin_ruiz']["params_required"] and
+ (builtin_models['martin_ruiz']["params_optional"] & params)
+ ):
+ return self.martin_ruiz_aoi_loss
+
+ if (builtin_models['physical']["params_required"] and (
+ builtin_models['physical']["params_required"] <= params)) or (
+ not builtin_models['physical']["params_required"] and
+ (builtin_models['physical']["params_optional"] & params)
+ ):
+ return self.physical_aoi_loss
+
+ if (builtin_models['sapm']["params_required"] and (
+ builtin_models['sapm']["params_required"] <= params)) or (
+ not builtin_models['sapm']["params_required"] and
+ (builtin_models['sapm']["params_optional"] & params)
+ ):
+ return self.sapm_aoi_loss
+
+ # schlick model has no parameters to distinguish, esp. from no_loss.
+
+ raise ValueError(
+ 'could not infer AOI model from '
+ 'system.arrays[i].module_parameters. Check that the '
+ 'module_parameters for all Arrays in system.arrays contain '
+ 'parameters for the ashrae, interp, martin_ruiz, physical, or '
+ 'sapm model; explicitly set the model (esp. the parameter-free '
+ 'schlick) with the aoi_model kwarg or set aoi_model="no_loss".'
+ )
def ashrae_aoi_loss(self):
self.results.aoi_modifier = self.system.get_iam(
- self.results.aoi,
- iam_model='ashrae'
+ self.results.aoi, iam_model='ashrae'
)
return self
def physical_aoi_loss(self):
self.results.aoi_modifier = self.system.get_iam(
- self.results.aoi,
- iam_model='physical'
+ self.results.aoi, iam_model='physical'
)
return self
def sapm_aoi_loss(self):
self.results.aoi_modifier = self.system.get_iam(
- self.results.aoi,
- iam_model='sapm'
+ self.results.aoi, iam_model='sapm'
)
return self
@@ -837,8 +871,13 @@ def martin_ruiz_aoi_loss(self):
def interp_aoi_loss(self):
self.results.aoi_modifier = self.system.get_iam(
- self.results.aoi,
- iam_model='interp'
+ self.results.aoi, iam_model='interp'
+ )
+ return self
+
+ def schlick_aoi_loss(self):
+ self.results.aoi_modifier = self.system.get_iam(
+ self.results.aoi, iam_model='schlick'
)
return self
@@ -867,8 +906,10 @@ def spectral_model(self, model):
self._spectral_model = self.no_spectral_loss
else:
raise ValueError(model + ' is not a valid spectral loss model')
- else:
+ elif callable(model):
self._spectral_model = partial(model, self)
+ else:
+ raise ValueError(model + ' is not a valid spectral loss model')
def infer_spectral_model(self):
"""Infer spectral model from system attributes."""
diff --git a/pvlib/pvsystem.py b/pvlib/pvsystem.py
index f99f0275af..f4c76723fb 100644
--- a/pvlib/pvsystem.py
+++ b/pvlib/pvsystem.py
@@ -8,7 +8,6 @@
import io
import itertools
from pathlib import Path
-import inspect
from urllib.request import urlopen
import numpy as np
from scipy import constants
@@ -399,8 +398,8 @@ def get_iam(self, aoi, iam_model='physical'):
The angle of incidence in degrees.
aoi_model : string, default 'physical'
- The IAM model to be used. Valid strings are 'physical', 'ashrae',
- 'martin_ruiz', 'sapm' and 'interp'.
+ The IAM model to be used. Valid strings are 'ashrae', 'interp',
+ 'martin_ruiz', 'physical', 'sapm', and 'schlick'.
Returns
-------
iam : numeric or tuple of numeric
@@ -634,9 +633,14 @@ def sapm_spectral_loss(self, airmass_absolute):
The SAPM spectral loss coefficient.
"""
return tuple(
- spectrum.spectral_factor_sapm(airmass_absolute,
- array.module_parameters)
- for array in self.arrays
+ spectrum.spectral_factor_sapm(
+ airmass_absolute,
+ array.module_parameters["A0"],
+ array.module_parameters["A1"],
+ array.module_parameters["A2"],
+ array.module_parameters["A3"],
+ array.module_parameters["A4"],
+ ) for array in self.arrays
)
@_unwrap_single_value
@@ -1161,12 +1165,15 @@ def get_irradiance(self, solar_zenith, solar_azimuth, dni, ghi, dhi,
def get_iam(self, aoi, iam_model='physical'):
"""
- Determine the incidence angle modifier using the method specified by
+ Determine the incidence-angle modifier (IAM) for the given
+ angle of incidence (AOI) using the method specified by
``iam_model``.
Parameters for the selected IAM model are expected to be in
- ``Array.module_parameters``. Default parameters are available for
- the 'physical', 'ashrae' and 'martin_ruiz' models.
+ ``Array.module_parameters``. A minimal set of default parameters
+ are available for the 'ashrae', 'martin_ruiz', and 'physical'
+ models, but not for 'interp', 'sapm'. The 'schlick' model does not
+ take any parameters.
Parameters
----------
@@ -1174,13 +1181,13 @@ def get_iam(self, aoi, iam_model='physical'):
The angle of incidence in degrees.
aoi_model : string, default 'physical'
- The IAM model to be used. Valid strings are 'physical', 'ashrae',
- 'martin_ruiz', 'sapm' and 'interp'.
+ The IAM model to be used. Valid strings are 'ashrae', 'interp',
+ 'martin_ruiz', 'physical', 'sapm', and 'schlick'.
Returns
-------
iam : numeric
- The AOI modifier.
+ The IAM at the specified AOI.
Raises
------
@@ -1188,18 +1195,27 @@ def get_iam(self, aoi, iam_model='physical'):
if `iam_model` is not a valid model name.
"""
model = iam_model.lower()
- if model in ['ashrae', 'physical', 'martin_ruiz', 'interp']:
- func = getattr(iam, model) # get function at pvlib.iam
- # get all parameters from function signature to retrieve them from
- # module_parameters if present
- params = set(inspect.signature(func).parameters.keys())
- params.discard('aoi') # exclude aoi so it can't be repeated
- kwargs = _build_kwargs(params, self.module_parameters)
- return func(aoi, **kwargs)
- elif model == 'sapm':
- return iam.sapm(aoi, self.module_parameters)
- else:
- raise ValueError(model + ' is not a valid IAM model')
+
+ try:
+ model_info = iam._get_builtin_models()[model]
+ except KeyError as exc:
+ raise ValueError(f'{iam_model} is not a valid iam_model') from exc
+
+ for param in model_info["params_required"]:
+ if param not in self.module_parameters:
+ raise KeyError(f"{param} is missing in module_parameters")
+
+ params_required = _build_kwargs(
+ model_info["params_required"], self.module_parameters
+ )
+
+ params_optional = _build_kwargs(
+ model_info["params_optional"], self.module_parameters
+ )
+
+ return model_info["func"](
+ aoi, **params_required, **params_optional
+ )
def get_cell_temperature(self, poa_global, temp_air, wind_speed, model,
effective_irradiance=None):
@@ -2379,8 +2395,23 @@ def sapm_effective_irradiance(poa_direct, poa_diffuse, airmass_absolute, aoi,
pvlib.pvsystem.sapm
"""
- F1 = spectrum.spectral_factor_sapm(airmass_absolute, module)
- F2 = iam.sapm(aoi, module)
+ F1 = spectrum.spectral_factor_sapm(
+ airmass_absolute,
+ module["A0"],
+ module["A1"],
+ module["A2"],
+ module["A3"],
+ module["A4"],
+ )
+ F2 = iam.sapm(
+ aoi,
+ module["B0"],
+ module["B1"],
+ module["B2"],
+ module["B3"],
+ module["B4"],
+ module["B5"],
+ )
Ee = F1 * (poa_direct * F2 + module['FD'] * poa_diffuse)
diff --git a/pvlib/spectrum/mismatch.py b/pvlib/spectrum/mismatch.py
index 3afc210e73..dfde1a5a53 100644
--- a/pvlib/spectrum/mismatch.py
+++ b/pvlib/spectrum/mismatch.py
@@ -295,20 +295,19 @@ def spectral_factor_firstsolar(precipitable_water, airmass_absolute,
return modifier
-def spectral_factor_sapm(airmass_absolute, module):
+def spectral_factor_sapm(airmass_absolute, A0, A1, A2, A3, A4):
"""
- Calculates the spectral mismatch factor, :math:`f_1`,
- using the Sandia Array Performance Model approach.
+ Calculates the spectral mismatch factor, :math:`f_1`, using the Sandia
+ Array Performance Model (SAPM) approach.
- The SAPM spectral factor function is part of the broader Sandia Array
+ The SAPM incidence angle modifier is part of the broader Sandia Array
Performance Model, which defines five points on an IV curve using empirical
module-specific coefficients. Module coefficients for the SAPM are
- available in the SAPM database and can be retrieved for use in the
- ``module`` parameter through
- :py:func:`pvlib.pvsystem.retrieve_sam()`. More details on the
- SAPM can be found in [1]_, while a full description of the procedure to
- determine the empirical model coefficients, including those for the SAPM
- spectral correction, can be found in [2]_.
+ available in the SAPM database and can be retrieved for use through
+ :py:func:`pvlib.pvsystem.retrieve_sam()`. More details on the SAPM can be
+ found in [1]_, while a full description of the procedure to determine the
+ empirical model coefficients, including those for the SAPM spectral
+ correction, can be found in [2]_.
Parameters
----------
@@ -317,10 +316,20 @@ def spectral_factor_sapm(airmass_absolute, module):
Note: ``np.nan`` airmass values will result in 0 output.
- module : dict-like
- A dict, Series, or DataFrame defining the SAPM parameters.
- Must contain keys `'A0'` through `'A4'`.
- See the :py:func:`pvlib.pvsystem.sapm` notes section for more details.
+ A0 : float
+ The coefficient of the degree-0 polynomial term.
+
+ A1 : float
+ The coefficient of the degree-1 polynomial term.
+
+ A2 : float
+ The coefficient of the degree-2 polynomial term.
+
+ A3 : float
+ The coefficient of the degree-3 polynomial term.
+
+ A4 : float
+ The coefficient of the degree-4 polynomial term.
Returns
-------
@@ -330,7 +339,7 @@ def spectral_factor_sapm(airmass_absolute, module):
Notes
-----
The SAPM spectral correction functions parameterises :math:`f_1` as a
- fourth order polynomial function of absolute air mass:
+ fourth-order polynomial function of absolute air mass:
.. math::
@@ -361,10 +370,7 @@ def spectral_factor_sapm(airmass_absolute, module):
"""
- am_coeff = [module['A4'], module['A3'], module['A2'], module['A1'],
- module['A0']]
-
- spectral_loss = np.polyval(am_coeff, airmass_absolute)
+ spectral_loss = np.polyval([A4, A3, A2, A1, A0], airmass_absolute)
spectral_loss = np.where(np.isnan(spectral_loss), 0, spectral_loss)
diff --git a/pvlib/tests/spectrum/test_mismatch.py b/pvlib/tests/spectrum/test_mismatch.py
index 5397a81f46..992462b5c6 100644
--- a/pvlib/tests/spectrum/test_mismatch.py
+++ b/pvlib/tests/spectrum/test_mismatch.py
@@ -148,7 +148,14 @@ def test_spectral_factor_firstsolar_range():
])
def test_spectral_factor_sapm(sapm_module_params, airmass, expected):
- out = spectrum.spectral_factor_sapm(airmass, sapm_module_params)
+ out = spectrum.spectral_factor_sapm(
+ airmass,
+ sapm_module_params["A0"],
+ sapm_module_params["A1"],
+ sapm_module_params["A2"],
+ sapm_module_params["A3"],
+ sapm_module_params["A4"],
+ )
if isinstance(airmass, pd.Series):
assert_series_equal(out, expected, check_less_precise=4)
diff --git a/pvlib/tests/test_iam.py b/pvlib/tests/test_iam.py
index f5ca231bd4..eb76cf5984 100644
--- a/pvlib/tests/test_iam.py
+++ b/pvlib/tests/test_iam.py
@@ -3,15 +3,46 @@
@author: cwhanse
"""
+import inspect
import numpy as np
+from numpy.testing import assert_allclose
import pandas as pd
-
import pytest
-from .conftest import assert_series_equal
-from numpy.testing import assert_allclose
+import scipy.interpolate
from pvlib import iam as _iam
+from pvlib.tests.conftest import assert_series_equal
+
+
+def test_get_builtin_models():
+ builtin_models = _iam._get_builtin_models()
+
+ models = set(builtin_models.keys())
+ models_expected = {
+ "ashrae", "interp", "martin_ruiz", "physical", "sapm", "schlick"
+ }
+ assert set(models) == models_expected
+
+ for model in models:
+ builtin_model = builtin_models[model]
+
+ params_required_expected = set(
+ k for k, v in inspect.signature(
+ builtin_model["func"]
+ ).parameters.items() if v.default is inspect.Parameter.empty
+ )
+ assert builtin_model["params_required"].union(
+ {"aoi"}
+ ) == params_required_expected, model
+
+ params_optional_expected = set(
+ k for k, v in inspect.signature(
+ builtin_model["func"]
+ ).parameters.items() if v.default is not inspect.Parameter.empty
+ )
+ assert builtin_model["params_optional"] == \
+ params_optional_expected, model
def test_ashrae():
@@ -222,7 +253,15 @@ def test_iam_interp():
])
def test_sapm(sapm_module_params, aoi, expected):
- out = _iam.sapm(aoi, sapm_module_params)
+ out = _iam.sapm(
+ aoi,
+ sapm_module_params["B0"],
+ sapm_module_params["B1"],
+ sapm_module_params["B2"],
+ sapm_module_params["B3"],
+ sapm_module_params["B4"],
+ sapm_module_params["B5"],
+ )
if isinstance(aoi, pd.Series):
assert_series_equal(out, expected, check_less_precise=4)
@@ -232,13 +271,38 @@ def test_sapm(sapm_module_params, aoi, expected):
def test_sapm_limits():
module_parameters = {'B0': 5, 'B1': 0, 'B2': 0, 'B3': 0, 'B4': 0, 'B5': 0}
- assert _iam.sapm(1, module_parameters) == 5
+ assert _iam.sapm(
+ 1,
+ module_parameters["B0"],
+ module_parameters["B1"],
+ module_parameters["B2"],
+ module_parameters["B3"],
+ module_parameters["B4"],
+ module_parameters["B5"],
+ ) == 5
module_parameters = {'B0': 5, 'B1': 0, 'B2': 0, 'B3': 0, 'B4': 0, 'B5': 0}
- assert _iam.sapm(1, module_parameters, upper=1) == 1
+ assert _iam.sapm(
+ 1,
+ module_parameters["B0"],
+ module_parameters["B1"],
+ module_parameters["B2"],
+ module_parameters["B3"],
+ module_parameters["B4"],
+ module_parameters["B5"],
+ upper=1,
+ ) == 1
module_parameters = {'B0': -5, 'B1': 0, 'B2': 0, 'B3': 0, 'B4': 0, 'B5': 0}
- assert _iam.sapm(1, module_parameters) == 0
+ assert _iam.sapm(
+ 1,
+ module_parameters["B0"],
+ module_parameters["B1"],
+ module_parameters["B2"],
+ module_parameters["B3"],
+ module_parameters["B4"],
+ module_parameters["B5"],
+ ) == 0
def test_marion_diffuse_model(mocker):
@@ -265,10 +329,14 @@ def test_marion_diffuse_model(mocker):
assert physical_spy.call_count == 3
for k, v in ashrae_expected.items():
- assert_allclose(ashrae_actual[k], v)
+ assert_allclose(
+ ashrae_actual[k], v, err_msg=f"ashrae component {k}"
+ )
for k, v in physical_expected.items():
- assert_allclose(physical_actual[k], v)
+ assert_allclose(
+ physical_actual[k], v, err_msg=f"physical component {k}"
+ )
def test_marion_diffuse_kwargs():
@@ -281,11 +349,73 @@ def test_marion_diffuse_kwargs():
actual = _iam.marion_diffuse('ashrae', 20, b=0.04)
for k, v in expected.items():
- assert_allclose(actual[k], v)
+ assert_allclose(actual[k], v, err_msg=f"component {k}")
+
+
+# IEC 61853-2 measurement data for tests.
+AOI_DATA = np.array([
+ 0, 10, 20, 30, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90,
+])
+IAM_DATA = np.array([
+ 1.0000, 1.0000, 1.0014, 1.0002, 0.9984, 0.9941, 0.9911, 0.9815, 0.9631,
+ 0.9352, 0.8922, 0.8134, 0.6778, 0.4541, 0.0000,
+])
+
+
+def test_marion_diffuse_iam_function_without_kwargs():
+ """
+ Test PCHIP-interpolated custom IAM function from an IEC 61853-2 IAM
+ measurement, without any kwargs and with array input.
+ """
+ pchip = scipy.interpolate.PchipInterpolator(
+ AOI_DATA, IAM_DATA, extrapolate=False
+ )
+
+ # Custom IAM function without kwargs, using IEC 61853-2 measurement data.
+ def iam_pchip(aoi):
+ """
+ Compute unitless incident-angle modifier as a function of aoi, in
+ degrees.
+ """
+ iam_ = pchip(aoi)
+ iam_[90 < aoi] = 0.0
+
+ return iam_
+
+ expected = {
+ 'sky': np.array([0.95671526, 0.96967113, 0.95672627, 0.88137573]),
+ 'horizon': np.array([0.03718587, 0.94953826, 0.97722834, 0.94862772]),
+ 'ground': np.array([0., 0.88137573, 0.95672627, 0.96967113]),
+ }
+ actual = _iam.marion_diffuse(iam_pchip, np.array([0.0, 45, 90, 135]))
+
+ for k, v in expected.items():
+ assert_allclose(actual[k], v, rtol=2e-7, err_msg=f"component {k}")
+
+
+def test_marion_diffuse_iam_with_kwargs():
+ """
+ Test custom IAM function (using iam.interp) with kwargs and scalar input.
+ """
+ expected = {
+ 'sky': 0.9688222974371822,
+ 'horizon': 0.94824614710175,
+ 'ground': 0.878266931831978,
+ }
+ actual = _iam.marion_diffuse(
+ _iam.interp,
+ 45.0,
+ theta_ref=AOI_DATA,
+ iam_ref=IAM_DATA,
+ normalize=False,
+ )
+
+ for k, v in expected.items():
+ assert_allclose(actual[k], v, err_msg=f"component {k}")
def test_marion_diffuse_invalid():
- with pytest.raises(ValueError):
+ with pytest.raises(ValueError, match='model must be one of: '):
_iam.marion_diffuse('not_a_model', 20)
@@ -481,7 +611,9 @@ def scaled_weight(aoi):
def test_convert_model_not_implemented():
- with pytest.raises(NotImplementedError, match='model has not been'):
+ with pytest.raises(
+ NotImplementedError, match='No implementation for model foo'
+ ):
_iam.convert('ashrae', {'b': 0.1}, 'foo')
@@ -532,7 +664,9 @@ def scaled_weight(aoi):
def test_fit_model_not_implemented():
- with pytest.raises(NotImplementedError, match='model has not been'):
+ with pytest.raises(
+ NotImplementedError, match='No implementation for model foo'
+ ):
_iam.fit(np.array([0, 10]), np.array([1, 0.99]), 'foo')
diff --git a/pvlib/tests/test_modelchain.py b/pvlib/tests/test_modelchain.py
index dcbd820f16..e37aebfd99 100644
--- a/pvlib/tests/test_modelchain.py
+++ b/pvlib/tests/test_modelchain.py
@@ -2,17 +2,14 @@
import numpy as np
import pandas as pd
+import pytest
from pvlib import iam, modelchain, pvsystem, temperature, inverter
from pvlib.modelchain import ModelChain
from pvlib.pvsystem import PVSystem
from pvlib.location import Location
-from pvlib._deprecation import pvlibDeprecationWarning
from .conftest import assert_series_equal, assert_frame_equal
-import pytest
-
-from .conftest import fail_on_pvlib_version
@pytest.fixture(scope='function')
@@ -1428,7 +1425,7 @@ def constant_aoi_loss(mc):
@pytest.mark.parametrize('aoi_model', [
- 'sapm', 'ashrae', 'physical', 'martin_ruiz'
+ 'ashrae', 'martin_ruiz', 'physical', 'sapm', 'schlick' # not interp
])
def test_aoi_models(sapm_dc_snl_ac_system, location, aoi_model,
weather, mocker):
@@ -1444,7 +1441,7 @@ def test_aoi_models(sapm_dc_snl_ac_system, location, aoi_model,
@pytest.mark.parametrize('aoi_model', [
- 'sapm', 'ashrae', 'physical', 'martin_ruiz'
+ 'ashrae', 'martin_ruiz', 'physical', 'sapm', 'schlick' # not interp
])
def test_aoi_models_singleon_weather_single_array(
sapm_dc_snl_ac_system, location, aoi_model, weather):
@@ -1502,27 +1499,66 @@ def test_aoi_model_user_func(sapm_dc_snl_ac_system, location, weather, mocker):
assert mc.results.ac.iloc[1] < 1
-@pytest.mark.parametrize('aoi_model', [
- 'sapm', 'ashrae', 'physical', 'martin_ruiz', 'interp'
-])
+@pytest.mark.parametrize(
+ 'aoi_model',
+ # "schlick" omitted, cannot be distinguished from "no_loss" AOI model.
+ [
+ {'params': {'b': 0.025}},
+ {'params': {'iam_ref': (1., 0.85), 'theta_ref': (0., 80.)}},
+ {'params': {'a_r': 0.1}},
+ {'params': {'n': 1.5}},
+ {
+ 'params': {
+ 'B0': 1,
+ 'B1': -0.002438,
+ 'B2': 0.0003103,
+ 'B3': -0.00001246,
+ 'B4': 2.11E-07,
+ 'B5': -1.36E-09,
+ }
+ },
+ ],
+ ids=['ashrae', 'interp', 'martin_ruiz', 'physical', 'sapm'],
+)
def test_infer_aoi_model(location, system_no_aoi, aoi_model):
- for k in iam._IAM_MODEL_PARAMS[aoi_model]:
- system_no_aoi.arrays[0].module_parameters.update({k: 1.0})
+ system_no_aoi.arrays[0].module_parameters.update(aoi_model["params"])
mc = ModelChain(system_no_aoi, location, spectral_model='no_loss')
assert isinstance(mc, ModelChain)
-@pytest.mark.parametrize('aoi_model,model_kwargs', [
- # model_kwargs has both required and optional kwargs; test all
- ('physical',
- {'n': 1.526, 'K': 4.0, 'L': 0.002, # required
- 'n_ar': 1.8}), # extra
- ('interp',
- {'theta_ref': (0, 75, 85, 90), 'iam_ref': (1, 0.8, 0.42, 0), # required
- 'method': 'cubic', 'normalize': False})]) # extra
-def test_infer_aoi_model_with_extra_params(location, system_no_aoi, aoi_model,
- model_kwargs, weather, mocker):
- # test extra parameters not defined at iam._IAM_MODEL_PARAMS are passed
+@pytest.mark.parametrize(
+ 'aoi_model,model_kwargs',
+ [
+ (
+ 'sapm',
+ {
+ # required
+ 'B0': 1,
+ 'B1': -0.002438,
+ 'B2': 0.0003103,
+ 'B3': -0.00001246,
+ 'B4': 2.11E-07,
+ 'B5': -1.36E-09,
+ # optional
+ 'upper': 1.,
+ }
+ ),
+ (
+ 'interp',
+ {
+ # required
+ 'theta_ref': (0, 75, 85, 90),
+ 'iam_ref': (1, 0.8, 0.42, 0),
+ # optional
+ 'method': 'cubic',
+ 'normalize': False,
+ }
+ )
+ ]
+)
+def test_infer_aoi_model_with_required_and_optional_params(
+ location, system_no_aoi, aoi_model, model_kwargs, weather, mocker
+):
m = mocker.spy(iam, aoi_model)
system_no_aoi.arrays[0].module_parameters.update(**model_kwargs)
mc = ModelChain(system_no_aoi, location, spectral_model='no_loss')
@@ -1533,8 +1569,7 @@ def test_infer_aoi_model_with_extra_params(location, system_no_aoi, aoi_model,
def test_infer_aoi_model_invalid(location, system_no_aoi):
- exc_text = 'could not infer AOI model'
- with pytest.raises(ValueError, match=exc_text):
+ with pytest.raises(ValueError, match='could not infer AOI model'):
ModelChain(system_no_aoi, location, spectral_model='no_loss')
diff --git a/pvlib/tests/test_pvsystem.py b/pvlib/tests/test_pvsystem.py
index fd482c5127..9372234aff 100644
--- a/pvlib/tests/test_pvsystem.py
+++ b/pvlib/tests/test_pvsystem.py
@@ -25,16 +25,56 @@
@pytest.mark.parametrize('iam_model,model_params', [
('ashrae', {'b': 0.05}),
- ('physical', {'K': 4, 'L': 0.002, 'n': 1.526}),
+ ('interp', {'iam_ref': (1., 0.85), 'theta_ref': (0., 80.)}),
('martin_ruiz', {'a_r': 0.16}),
+ ('physical', {'K': 4, 'L': 0.002, 'n': 1.526}),
+ (
+ 'sapm',
+ {
+ k: v for k, v in pvsystem.retrieve_sam(
+ 'SandiaMod')['Canadian_Solar_CS5P_220M___2009_'].items()
+ if k in ('B0', 'B1', 'B2', 'B3', 'B4', 'B5')
+ }
+ ),
+ ('schlick', {}),
])
def test_PVSystem_get_iam(mocker, iam_model, model_params):
m = mocker.spy(_iam, iam_model)
system = pvsystem.PVSystem(module_parameters=model_params)
- thetas = 1
+ thetas = 45
iam = system.get_iam(thetas, iam_model=iam_model)
m.assert_called_with(thetas, **model_params)
- assert iam < 1.
+ assert 0 < iam < 1
+
+
+def test_PVSystem_get_iam_unsupported_model():
+ iam_model = 'foobar'
+ system = pvsystem.PVSystem()
+
+ with pytest.raises(
+ ValueError, match=f'{iam_model} is not a valid iam_model'
+ ):
+ system.get_iam(45, iam_model=iam_model)
+
+
+@pytest.mark.parametrize('iam_model,model_params', [
+ ('interp', {'iam_ref': (1., 0.85)}), # missing theta_ref
+ (
+ 'sapm',
+ {
+ k: v for k, v in pvsystem.retrieve_sam(
+ 'SandiaMod')['Canadian_Solar_CS5P_220M___2009_'].items()
+ if k in ('B0', 'B1', 'B2', 'B3', 'B4') # missing B5
+ }
+ ),
+])
+def test_PVSystem_get_iam_missing_required_param(iam_model, model_params):
+ system = pvsystem.PVSystem(module_parameters=model_params)
+
+ with pytest.raises(
+ KeyError, match="is missing in module_parameters"
+ ):
+ system.get_iam(45, iam_model=iam_model)
def test_PVSystem_multi_array_get_iam():
@@ -58,7 +98,15 @@ def test_PVSystem_get_iam_sapm(sapm_module_params, mocker):
mocker.spy(_iam, 'sapm')
aoi = 0
out = system.get_iam(aoi, 'sapm')
- _iam.sapm.assert_called_once_with(aoi, sapm_module_params)
+ _iam.sapm.assert_called_once_with(
+ aoi,
+ sapm_module_params["B0"],
+ sapm_module_params["B1"],
+ sapm_module_params["B2"],
+ sapm_module_params["B3"],
+ sapm_module_params["B4"],
+ sapm_module_params["B5"],
+ )
assert_allclose(out, 1.0, atol=0.01)
@@ -236,7 +284,14 @@ def test_PVSystem_multi_array_sapm(sapm_module_params):
def test_sapm_spectral_loss_deprecated(sapm_module_params):
with pytest.warns(pvlibDeprecationWarning,
match='Use pvlib.spectrum.spectral_factor_sapm'):
- pvsystem.sapm_spectral_loss(1, sapm_module_params)
+ pvsystem.sapm_spectral_loss(
+ 1,
+ sapm_module_params["A0"],
+ sapm_module_params["A1"],
+ sapm_module_params["A2"],
+ sapm_module_params["A3"],
+ sapm_module_params["A4"],
+ )
def test_PVSystem_sapm_spectral_loss(sapm_module_params, mocker):
@@ -244,8 +299,14 @@ def test_PVSystem_sapm_spectral_loss(sapm_module_params, mocker):
system = pvsystem.PVSystem(module_parameters=sapm_module_params)
airmass = 2
out = system.sapm_spectral_loss(airmass)
- spectrum.spectral_factor_sapm.assert_called_once_with(airmass,
- sapm_module_params)
+ spectrum.spectral_factor_sapm.assert_called_once_with(
+ airmass,
+ sapm_module_params["A0"],
+ sapm_module_params["A1"],
+ sapm_module_params["A2"],
+ sapm_module_params["A3"],
+ sapm_module_params["A4"],
+ )
assert_allclose(out, 1, atol=0.5)
diff --git a/pyproject.toml b/pyproject.toml
index 8464b7ce23..d1583421e1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,7 +9,7 @@ description = "A set of functions and classes for simulating the performance of
authors = [
{ name = "pvlib python Developers", email = "pvlib-admin@googlegroups.com" },
]
-requires-python = ">=3.9"
+requires-python = ">=3.9, <3.13"
dependencies = [
'numpy >= 1.19.3',
'pandas >= 1.3.0',
@@ -49,9 +49,9 @@ dynamic = ["version"]
optional = [
'cython',
'ephem',
- 'nrel-pysam',
- 'numba >= 0.17.0',
- 'solarfactors',
+ 'nrel-pysam; python_version < "3.13"',
+ 'numba >= 0.17.0; python_version < "3.13"',
+ 'solarfactors; python_version < "3.12"',
'statsmodels',
]
doc = [
@@ -65,10 +65,11 @@ doc = [
'pillow',
'sphinx-toggleprompt == 0.5.2',
'sphinx-favicon',
- 'solarfactors',
+ 'solarfactors; python_version < "3.12"',
'sphinx-hoverxref',
]
test = [
+ 'flake8==5.0.4', # Should match version in github workflow flake8.yml.
'pytest',
'pytest-cov',
'pytest-mock',