TEST: Added tests for psalsa and derpsalsa weightings

pybaselines/_weighting.py

@@ -448,7 +448,7 @@ def _derpsalsa(y, baseline, p, k, shape_y, partial_weights):
     # since it's faster than performing the square and exp on the full residual
     weights = np.full(shape_y, 1 - p, dtype=float)
     mask = residual > 0
-    weights[mask] = p * np.exp(-((residual[mask] / k)**2) / 2)
+    weights[mask] = p * np.exp(-0.5 * ((residual[mask] / k)**2))
     weights *= partial_weights
     return weights
 

pybaselines/spline.py

@@ -1080,7 +1080,8 @@ def pspline_psalsa(self, data, lam=1e3, p=0.5, k=None, num_knots=100, spline_deg
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         See Also
         --------
@@ -1104,6 +1105,8 @@ def pspline_psalsa(self, data, lam=1e3, p=0.5, k=None, num_knots=100, spline_deg
         )
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
         tol_history = np.empty(max_iter + 1)
         for i in range(max_iter + 1):
             baseline = self.pspline.solve_pspline(y, weight_array)
@@ -1185,7 +1188,8 @@ def pspline_derpsalsa(self, data, lam=1e2, p=1e-2, k=None, num_knots=100, spline
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         See Also
         --------
@@ -1208,6 +1212,8 @@ def pspline_derpsalsa(self, data, lam=1e2, p=1e-2, k=None, num_knots=100, spline
         )
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
 
         if smooth_half_window is None:
             smooth_half_window = self._size // 200
@@ -2248,7 +2254,8 @@ def pspline_psalsa(data, lam=1e3, p=0.5, k=None, num_knots=100, spline_degree=3,
     Raises
     ------
     ValueError
-        Raised if `p` is not between 0 and 1.
+        Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+        than 0.
 
     See Also
     --------
@@ -2336,7 +2343,8 @@ def pspline_derpsalsa(data, lam=1e2, p=1e-2, k=None, num_knots=100, spline_degre
     Raises
     ------
     ValueError
-        Raised if `p` is not between 0 and 1.
+        Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+        than 0.
 
     See Also
     --------

pybaselines/two_d/spline.py

@@ -11,6 +11,7 @@
 import numpy as np
 
 from .. import _weighting
+from .._validation import _check_scalar_variable
 from ..utils import ParameterWarning, gaussian, relative_difference
 from ._algorithm_setup import _Algorithm2D
 from ._whittaker_utils import PenalizedSystem2D
@@ -765,7 +766,8 @@ def pspline_psalsa(self, data, lam=1e3, p=0.5, k=None, num_knots=25, spline_degr
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         See Also
         --------
@@ -789,6 +791,8 @@ def pspline_psalsa(self, data, lam=1e3, p=0.5, k=None, num_knots=25, spline_degr
         )
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
         tol_history = np.empty(max_iter + 1)
         for i in range(max_iter + 1):
             baseline = self.pspline.solve(y, weight_array)

pybaselines/two_d/whittaker.py

@@ -763,7 +763,8 @@ def psalsa(self, data, lam=1e5, p=0.5, k=None, diff_order=2, max_iter=50, tol=1e
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         Notes
         -----
@@ -789,6 +790,8 @@ def psalsa(self, data, lam=1e5, p=0.5, k=None, diff_order=2, max_iter=50, tol=1e
         )
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
 
         shape = self._shape if self.whittaker_system._using_svd else self._size
         tol_history = np.empty(max_iter + 1)

pybaselines/whittaker.py

@@ -658,7 +658,8 @@ def psalsa(self, data, lam=1e5, p=0.5, k=None, diff_order=2, max_iter=50, tol=1e
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         Notes
         -----
@@ -679,6 +680,8 @@ def psalsa(self, data, lam=1e5, p=0.5, k=None, diff_order=2, max_iter=50, tol=1e
         y, weight_array = self._setup_whittaker(data, lam, diff_order, weights)
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
         tol_history = np.empty(max_iter + 1)
         for i in range(max_iter + 1):
             baseline = self.whittaker_system.solve(
@@ -758,7 +761,8 @@ def derpsalsa(self, data, lam=1e6, p=0.01, k=None, diff_order=2, max_iter=50, to
         Raises
         ------
         ValueError
-            Raised if `p` is not between 0 and 1.
+            Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+            than 0.
 
         References
         ----------
@@ -772,6 +776,8 @@ def derpsalsa(self, data, lam=1e6, p=0.01, k=None, diff_order=2, max_iter=50, to
         y, weight_array = self._setup_whittaker(data, lam, diff_order, weights)
         if k is None:
             k = np.std(y) / 10
+        else:
+            k = _check_scalar_variable(k, variable_name='k')
         if smooth_half_window is None:
             smooth_half_window = self._size // 200
         # could pad the data every iteration, but it is ~2-3 times slower and only affects
@@ -1283,7 +1289,8 @@ def psalsa(data, lam=1e5, p=0.5, k=None, diff_order=2, max_iter=50, tol=1e-3,
     Raises
     ------
     ValueError
-        Raised if `p` is not between 0 and 1.
+        Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+        than 0.
 
     Notes
     -----
@@ -1366,7 +1373,8 @@ def derpsalsa(data, lam=1e6, p=0.01, k=None, diff_order=2, max_iter=50, tol=1e-3
     Raises
     ------
     ValueError
-        Raised if `p` is not between 0 and 1.
+        Raised if `p` is not between 0 and 1. Also raised if `k` is not greater
+        than 0.
 
     References
     ----------

tests/test_spline.py

@@ -470,6 +470,12 @@ def test_whittaker_comparison(self, lam, p, diff_order):
             self, whittaker.psalsa, self.y, lam=lam, p=p, diff_order=diff_order
         )
 
+    @pytest.mark.parametrize('k', (0, -1))
+    def test_outside_k_fails(self, k):
+        """Ensures k values not greater than 0 raise an exception."""
+        with pytest.raises(ValueError):
+            self.class_func(self.y, k=k)
+
 
 class TestPsplineDerpsalsa(IterativeSplineTester):
     """Class for testing pspline_derpsalsa baseline."""
@@ -497,6 +503,12 @@ def test_whittaker_comparison(self, lam, p, diff_order):
             self, whittaker.derpsalsa, self.y, lam=lam, p=p, diff_order=diff_order
         )
 
+    @pytest.mark.parametrize('k', (0, -1))
+    def test_outside_k_fails(self, k):
+        """Ensures k values not greater than 0 raise an exception."""
+        with pytest.raises(ValueError):
+            self.class_func(self.y, k=k)
+
 
 class TestPsplineMPLS(SplineTester, InputWeightsMixin):
     """Class for testing pspline_mpls baseline."""