Document params attribute for each class

skimage/measure/fit.py

@@ -37,12 +37,13 @@ class LineModel(BaseModel):
 
         min{ sum((dist - x_i * cos(theta) + y_i * sin(theta))**2) }
 
-    The ``params`` attribute contains the parameters in the following order::
-
-        dist, theta
-
     A minimum number of 2 points is required to solve for the parameters.
 
+    Attributes
+    ----------
+    params : tuple
+        Line model parameters in the following order `dist`, `theta`.
+
     """
 
     def estimate(self, data):
@@ -161,12 +162,13 @@ class CircleModel(BaseModel):
 
         min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) }
 
-    The ``params`` attribute contains the parameters in the following order::
-
-        xc, yc, r
-
     A minimum number of 3 points is required to solve for the parameters.
 
+    Attributes
+    ----------
+    params : tuple
+        Circle model parameters in the following order `xc`, `yc`, `r`.
+
     """
 
     def estimate(self, data):
@@ -292,6 +294,12 @@ class EllipseModel(BaseModel):
 
     A minimum number of 5 points is required to solve for the parameters.
 
+    Attributes
+    ----------
+    params : tuple
+        Ellipse model parameters in the following order `xc`, `yc`, `a`,
+        `b`, `theta`.
+
     """
 
     def estimate(self, data):

skimage/transform/_geometric.py

@@ -104,6 +104,11 @@ class ProjectiveTransform(GeometricTransform):
     matrix : (3, 3) array, optional
         Homogeneous transformation matrix.
 
+    Attributes
+    ----------
+    params : (3, 3) array
+        Homogeneous transformation matrix.
+
     """
 
     _coeffs = range(8)
@@ -291,6 +296,11 @@ class AffineTransform(ProjectiveTransform):
     translation : (tx, ty) as array, list or tuple, optional
         Translation parameters.
 
+    Attributes
+    ----------
+    params : (3, 3) array
+        Homogeneous transformation matrix.
+
     """
 
     _coeffs = range(6)
@@ -356,25 +366,20 @@ class PiecewiseAffineTransform(GeometricTransform):
     a Delaunay triangulation of the points to form a mesh. Each triangle is
     used to find a local affine transform.
 
+    Attributes
+    ----------
+    affines : list of AffineTransform objects
+        Affine transformations for each triangle in the mesh.
+    inverse_affines : list of AffineTransform objects
+        Inverse affine transformations for each triangle in the mesh.
+
     """
 
     def __init__(self):
         self._tesselation = None
         self._inverse_tesselation = None
-        self.affines_ = None
-        self.inverse_affines_ = None
-
-    @property
-    def affines(self):
-        warnings.warn('`affines` attribute is deprecated, '
-                      'use `affines_` instead.')
-        return self.affines_
-
-    @property
-    def inverse_affines(self):
-        warnings.warn('`inverse_affines` attribute is deprecated, '
-                      'use `inverse_affines_` instead.')
-        return self.inverse_affines_
+        self.affines = None
+        self.inverse_affines = None
 
     def estimate(self, src, dst):
         """Set the control points with which to perform the piecewise mapping.
@@ -394,21 +399,21 @@ class PiecewiseAffineTransform(GeometricTransform):
         # triangulate input positions into mesh
         self._tesselation = spatial.Delaunay(src)
         # find affine mapping from source positions to destination
-        self.affines_ = []
+        self.affines = []
         for tri in self._tesselation.vertices:
             affine = AffineTransform()
             affine.estimate(src[tri, :], dst[tri, :])
-            self.affines_.append(affine)
+            self.affines.append(affine)
 
         # inverse piecewise affine
         # triangulate input positions into mesh
         self._inverse_tesselation = spatial.Delaunay(dst)
         # find affine mapping from source positions to destination
-        self.inverse_affines_ = []
+        self.inverse_affines = []
         for tri in self._inverse_tesselation.vertices:
             affine = AffineTransform()
             affine.estimate(dst[tri, :], src[tri, :])
-            self.inverse_affines_.append(affine)
+            self.inverse_affines.append(affine)
 
     def __call__(self, coords):
         """Apply forward transformation.
@@ -437,7 +442,7 @@ class PiecewiseAffineTransform(GeometricTransform):
 
         for index in range(len(self._tesselation.vertices)):
             # affine transform for triangle
-            affine = self.affines_[index]
+            affine = self.affines[index]
             # all coordinates within triangle
             index_mask = simplex == index
 
@@ -472,7 +477,7 @@ class PiecewiseAffineTransform(GeometricTransform):
 
         for index in range(len(self._inverse_tesselation.vertices)):
             # affine transform for triangle
-            affine = self.inverse_affines_[index]
+            affine = self.inverse_affines[index]
             # all coordinates within triangle
             index_mask = simplex == index
 
@@ -507,6 +512,11 @@ class SimilarityTransform(ProjectiveTransform):
     translation : (tx, ty) as array, list or tuple, optional
         x, y translation parameters.
 
+    Attributes
+    ----------
+    params : (3, 3) array
+        Homogeneous transformation matrix.
+
     """
 
     def __init__(self, matrix=None, scale=None, rotation=None,
@@ -638,6 +648,12 @@ class PolynomialTransform(GeometricTransform):
         Polynomial coefficients where `N * 2 = (order + 1) * (order + 2)`. So,
         a_ji is defined in `params[0, :]` and b_ji in `params[1, :]`.
 
+    Attributes
+    ----------
+    params : (2, N) array
+        Polynomial coefficients where `N * 2 = (order + 1) * (order + 2)`. So,
+        a_ji is defined in `params[0, :]` and b_ji in `params[1, :]`.
+
     """
 
     def __init__(self, params=None):

skimage/transform/tests/test_geometric.py

@@ -236,10 +236,6 @@ def test_deprecated_params_attributes():
     tform = estimate_transform('polynomial', SRC, DST, order=3)
     assert_equal(tform._params, tform.params)
 
-    tform = estimate_transform('piecewise-affine', SRC, DST)
-    assert_equal(tform.affines, tform.affines_)
-    assert_equal(tform.inverse_affines, tform.inverse_affines_)
-
 
 if __name__ == "__main__":
     from numpy.testing import run_module_suite