Replace interp1d #2394 (#2741)

* Replace interp1d #2394

* Replace CubicSpline by make_interp_spline k=3

* clean up/ simplify/move import to top

* remove list input

* Remove ifinstance check/Use np.interp

* linting

* Remove test to check for lists

* Update pvlib/iam.py

Co-authored-by: Cliff Hansen <cwhanse@sandia.gov>

* Update pvlib/iam.py with warn_deprecated

Co-authored-by: Cliff Hansen <cwhanse@sandia.gov>

* add imports for interp1d and warn_deprecate

* Add tests for invalid/deprecated interp methods

* Linting

* Update pvlib/iam.py

Co-authored-by: Cliff Hansen <cwhanse@sandia.gov>

* Add whatsnew for Deprecate scipy.interpolate

* Apply suggestion from @cwhanse

---------

Co-authored-by: Cliff Hansen <cwhanse@sandia.gov>

Author: jason-rpkt

docs/examples/shading/plot_partial_module_shading_simple.py

@@ -38,7 +38,6 @@
 from pvlib import pvsystem, singlediode
 import pandas as pd
 import numpy as np
-from scipy.interpolate import interp1d
 import matplotlib.pyplot as plt
 
 from scipy.constants import e as qe, k as kB
@@ -178,10 +177,8 @@ def plot_curves(dfs, labels, title):
 
 
 def interpolate(df, i):
-    """convenience wrapper around scipy.interpolate.interp1d"""
-    f_interp = interp1d(np.flipud(df['i']), np.flipud(df['v']), kind='linear',
-                        fill_value='extrapolate')
-    return f_interp(i)
+    """convenience wrapper around numpy.interp"""
+    return np.interp(i, np.flipud(df['i']), np.flipud(df['v']))
 
 
 def combine_series(dfs):

docs/sphinx/source/whatsnew/v0.15.3.rst

@@ -10,7 +10,7 @@ Breaking Changes
 
 Deprecations
 ~~~~~~~~~~~~
-
+* Deprecate non-polynomial interpolation options in :py:func:`pvlib.iam.interp` (:issue:`2394`, :pull:`2741`)
 
 Bug fixes
 ~~~~~~~~~
@@ -71,4 +71,5 @@ Contributors
 * Mathias Aschwanden (:ghuser:`maschwanden`)
 * Yonry Zhu (:ghuser:`yonryzhu`)
 * Darshan Gowda (:ghuser:`dgowdaan-cmyk`)
+* Jason Lun Leung (:ghuser:`jason-rpkt`)
 * Leonardo Scappatura (:ghuser:`Leonard013`)

pvlib/iam.py

@@ -13,6 +13,8 @@
 import functools
 from scipy.optimize import minimize
 from pvlib.tools import cosd, sind, acosd
+from pvlib._deprecation import warn_deprecated
+from scipy.interpolate import make_interp_spline, interp1d
 
 # a dict of required parameter names for each IAM model
 # keys are the function names for the IAM models
@@ -440,7 +442,6 @@ def interp(aoi, theta_ref, iam_ref, method='linear', normalize=True):
     method : str, default 'linear'
         Specifies the interpolation method.
         Useful options are: 'linear', 'quadratic', 'cubic'.
-        See scipy.interpolate.interp1d for more options.
 
     normalize : boolean, default True
         When true, the interpolated values are divided by the interpolated
@@ -469,9 +470,6 @@ def interp(aoi, theta_ref, iam_ref, method='linear', normalize=True):
     pvlib.iam.sapm
     '''
     # 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}
 
@@ -483,10 +481,25 @@ 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')
-    aoi_input = aoi
+    kvals = {'linear': 1, 'quadratic': 2, 'cubic': 3}
+    if method in kvals:
+        interpolator = make_interp_spline(
+            theta_ref, iam_ref, k=kvals[method])
+
+    elif method in {'nearest', 'nearest-up', 'zero',
+                    'slinear', 'previous', 'next'}:
+        msg = (
+            f"Interpolation method {method} is deprecated in pvlib"
+        )
+        warn_deprecated(since="0.15.3", removal="0.16.0", addendum=msg)
+        interpolator = interp1d(theta_ref, iam_ref, kind=method,
+                                fill_value='extrapolate')
+    else:
+        raise ValueError(
+            f"Interpolation method '{method}' is not supported"
+            " in pvlib-python.")
 
+    aoi_input = aoi
     aoi = np.asanyarray(aoi)
     aoi = np.abs(aoi)
     iam = interpolator(aoi)

pvlib/spectrum/response.py

@@ -6,7 +6,7 @@
 import numpy as np
 import pandas as pd
 import scipy.constants
-from scipy.interpolate import interp1d
+from scipy.interpolate import make_interp_spline
 
 
 _PLANCK_BY_LIGHT_SPEED_OVER_ELEMENTAL_CHARGE_BY_BILLION = (
@@ -66,16 +66,14 @@ def get_example_spectral_response(wavelength=None):
     if wavelength is None:
         resolution = 5.0
         wavelength = np.arange(280, 1200 + resolution, resolution)
+    x = SR_DATA[0]
+    y = SR_DATA[1]
+    spline = make_interp_spline(x, y, k=3)
 
-    interpolator = interp1d(SR_DATA[0], SR_DATA[1],
-                            kind='cubic',
-                            bounds_error=False,
-                            fill_value=0.0,
-                            copy=False,
-                            assume_sorted=True)
-
-    sr = pd.Series(data=interpolator(wavelength), index=wavelength)
+    values = spline(wavelength)
+    values[(wavelength < x[0]) | (wavelength > x[-1])] = 0.0
 
+    sr = pd.Series(data=values, index=wavelength)
     sr.index.name = 'wavelength'
     sr.name = 'spectral_response'
 

tests/test_iam.py

@@ -12,6 +12,7 @@
 from numpy.testing import assert_allclose
 
 from pvlib import iam as _iam
+from pvlib._deprecation import pvlibDeprecationWarning
 
 
 def test_ashrae():
@@ -171,8 +172,8 @@ def test_martin_ruiz_diffuse():
 
 def test_iam_interp():
 
-    aoi_meas = [0.0, 45.0, 65.0, 75.0]
-    iam_meas = [1.0,  0.9,  0.8,  0.6]
+    aoi_meas = np.array([0.0, 45.0, 65.0, 75.0])
+    iam_meas = np.array([1.0,  0.9,  0.8,  0.6])
 
     # simple default linear method
     aoi = 55.0
@@ -200,18 +201,80 @@ def test_iam_interp():
     assert_series_equal(iam, expected)
 
     # check beyond reference values
-    aoi = [-45, 0, 45, 85, 90, 95, 100, 105, 110]
-    expected = [0.9, 1.0, 0.9, 0.4, 0.3, 0.2, 0.1, 0.0, 0.0]
+    aoi = np.array([-45, 0, 45, 85, 90, 95, 100, 105, 110])
+    expected = np.array([0.9, 1.0, 0.9, 0.4, 0.3, 0.2, 0.1, 0.0, 0.0])
     iam = _iam.interp(aoi, aoi_meas, iam_meas)
     assert_allclose(iam, expected)
 
     # check exception clause
     with pytest.raises(ValueError):
-        _iam.interp(0.0, [0], [1])
+        _iam.interp(0.0, np.array([0]), np.array([1]))
 
     # check exception clause
     with pytest.raises(ValueError):
-        _iam.interp(0.0, [0, 90], [1, -1])
+        _iam.interp(0.0, np.array([0, 90]), np.array([1, -1]))
+
+    # check linear after updating interp1d
+    theta_ref = np.array([0, 60, 90])
+    iam_ref = np.array([1.0, 0.8, 0.0])
+
+    aoi = np.array([0, 30, 60])
+    iam = _iam.interp(
+        aoi, theta_ref, iam_ref,
+        method="linear", normalize=False)
+    expected = np.array([1.0, 0.9, 0.8])
+    np.testing.assert_allclose(iam, expected)
+
+    # check quadratic
+    theta_ref = np.array([0, 30, 60, 90])
+    iam_ref = 1.0 - 1e-4 * theta_ref**2
+    aoi = np.array([15, 45, 75])
+    iam = _iam.interp(
+        aoi,
+        theta_ref,
+        iam_ref,
+        method="quadratic",
+        normalize=False
+    )
+
+    expected = 1.0 - 1e-4 * aoi**2
+    np.testing.assert_allclose(iam, expected, rtol=1e-12)
+
+
+@pytest.mark.parametrize(
+    "method",
+    ["nearest", "nearest-up", "zero", "slinear", "previous", "next"]
+)
+def test_iam_interp_deprecated_methods(method):
+    theta_ref = np.array([0, 60, 90])
+    iam_ref = np.array([1.0, 0.8, 0.0])
+
+    with pytest.warns(
+        pvlibDeprecationWarning,
+        match=f"Interpolation method {method} is deprecated in pvlib"
+    ):
+        _iam.interp(
+            30,
+            theta_ref,
+            iam_ref,
+            method=method
+        )
+
+
+def test_iam_interp_invalid_method():
+    theta_ref = np.array([0, 60, 90])
+    iam_ref = np.array([1.0, 0.8, 0.0])
+
+    with pytest.raises(
+        ValueError,
+        match="is not supported"
+    ):
+        _iam.interp(
+            30,
+            theta_ref,
+            iam_ref,
+            method="unsupported"
+        )
 
 
 @pytest.mark.parametrize('aoi,expected', [