Increase test coverage

csaps/_base.py

@@ -87,7 +87,7 @@ def evaluate(self, xi: TData) -> np.ndarray:
             Interpolated/smoothed data
         """
 
-    def __repr__(self):
+    def __repr__(self):  # pragma: no cover
         return (
             f'{type(self).__name__}\n'
             f'  breaks: {self.breaks}\n'

csaps/_reshape.py

@@ -64,7 +64,7 @@ def to_2d(arr: np.ndarray, axis: int) -> np.ndarray:
     arr = np.asarray(arr)
     axis = arr.ndim + axis if axis < 0 else axis
 
-    if axis >= arr.ndim:
+    if axis >= arr.ndim:  # pragma: no cover
         raise ValueError(f'axis {axis} is out of array axes {arr.ndim}')
 
     tr_axes = list(range(arr.ndim))
@@ -135,7 +135,7 @@ def from_2d(arr: np.ndarray, shape: ty.Sequence[int], axis: int) -> np.ndarray:
     ndim = len(shape)
     axis = ndim + axis if axis < 0 else axis
 
-    if axis >= ndim:
+    if axis >= ndim:  # pragma: no cover
         raise ValueError(f'axis {axis} is out of N-D array axes {ndim}')
 
     new_shape = list(shape)

csaps/_sspndg.py

@@ -203,7 +203,7 @@ def __call__(self, xi: NdGridDataType) -> np.ndarray:
         """
         xi = ndgrid_prepare_data_sites(xi, 'xi')
 
-        if len(xi) != self._ndim:
+        if len(xi) != self._ndim:  # pragma: no cover
             raise ValueError(f'xi ({len(xi)}) and xdata ({self._ndim}) dimensions mismatch')
 
         return self._spline.evaluate(xi)

csaps/_sspumv.py

@@ -331,14 +331,14 @@ def __init__(self,
             xdata, ydata, weights=weights, smooth=smooth, axis=axis)
 
     @property
-    def smooth(self) -> TSmooth:
+    def smooth(self) -> float:
         return self._cssp.smooth
 
     @property
-    def spline(self) -> TSpline:
+    def spline(self) -> SplinePPForm:
         return self._cssp.spline
 
-    def __call__(self, xi: TXi) -> np.ndarray:
+    def __call__(self, xi: UnivariateDataType) -> np.ndarray:
         return self._cssp(xi)
 
 

tests/test_multivariate.py

@@ -14,4 +14,8 @@ def test_auto_tdata():
     t = [0., 3.74165739, 8.10055633, 12.68313203]
 
     sp = csaps.MultivariateCubicSmoothingSpline(data)
+
+    assert isinstance(sp.spline, csaps.SplinePPForm)
+    assert 0 < sp.smooth < 1
+    assert sp(t).shape == (3, 4)
     np.testing.assert_allclose(sp.t, t)

tests/test_gridded.py → tests/test_ndgrid.py

@@ -14,7 +14,9 @@
     ([[1, 2, 3], [1, 2, 3]], np.ones((3, 3)), [1, 2, 3], None),
     ([[1, 2, 3], [1, 2, 3]], np.ones((3, 3)), [[1, 2, 3]], None),
     ([[1, 2, 3], [1, 2, 3]], np.ones((3, 3)), [[1, 2], [1, 2]], None),
-    ([[1, 2, 3], [1, 2, 3]], np.ones((3, 3)), None, [0.5, 0.4, 0.2])
+    ([[1, 2, 3], [1, 2, 3]], np.ones((3, 3)), None, [0.5, 0.4, 0.2]),
+    (np.array([[1, 2, 3], [4, 5, 6]]), np.ones((3, 3)), None, None),
+    ([np.arange(6).reshape(2, 3), np.arange(6).reshape(2, 3)], np.ones((6, 6)), None, None),
 ])
 def test_invalid_data(x, y, w, p):
     with pytest.raises((ValueError, TypeError)):
@@ -33,4 +35,9 @@ def test_surface():
     noisy = ydata + (np.random.randn(*ydata.shape) * 0.75)
 
     sp = csaps.NdGridCubicSmoothingSpline(xdata, noisy)
-    _ = sp(xdata)
+    noisy_s = sp(xdata)
+
+    assert isinstance(sp.smooth, tuple)
+    assert len(sp.smooth) == 2
+    assert isinstance(sp.spline, csaps.NdGridSplinePPForm)
+    assert noisy_s.shape == noisy.shape

tests/test_shortcut.py

@@ -3,7 +3,7 @@
 import pytest
 import numpy as np
 
-from csaps import csaps, AutoSmoothingResult, UnivariateCubicSmoothingSpline, NdGridCubicSmoothingSpline
+from csaps import csaps, AutoSmoothingResult, CubicSmoothingSpline, NdGridCubicSmoothingSpline
 
 
 @pytest.fixture(scope='module')
@@ -34,7 +34,7 @@ def data(curve, surface, request):
     if request.param == 'univariate':
         x, y = curve
         xi = np.linspace(x[0], x[-1], 150)
-        return x, y, xi, 0.85, UnivariateCubicSmoothingSpline
+        return x, y, xi, 0.85, CubicSmoothingSpline
 
     elif request.param == 'ndgrid':
         x, y = surface
@@ -46,9 +46,15 @@ def data(curve, surface, request):
     'univariate',
     'ndgrid',
 ], indirect=True)
-def test_shortcut_output(data):
+@pytest.mark.parametrize('tolist', [True, False])
+def test_shortcut_output(data, tolist):
     x, y, xi, smooth, sp_cls = data
 
+    if tolist and isinstance(x, np.ndarray):
+        x = x.tolist()
+        y = y.tolist()
+        xi = xi.tolist()
+
     yi = csaps(x, y, xi, smooth=smooth)
     assert isinstance(yi, np.ndarray)
 

tests/test_univariate.py

@@ -160,6 +160,7 @@ def test_auto_smooth():
     xi = np.linspace(x[0], x[-1], 120)
     yi = sp(xi)
 
+    assert isinstance(sp.spline, csaps.SplinePPForm)
     np.testing.assert_almost_equal(sp.smooth, 0.996566686)
 
     desired_yi = [