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Disable catch of all warnings, return nan params instead

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This commit is contained in:
Johannes Schönberger
2015-01-22 06:49:16 -05:00
parent acf68c6d7c
commit ad85dfabd5
4 changed files with 71 additions and 78 deletions
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skimage/measure/fit.py
+2 -13
View File
@@ -502,7 +502,7 @@ def _dynamic_max_trials(n_inliers, n_samples, min_samples, probability):
def ransac(data, model_class, min_samples, residual_threshold,
is_data_valid=None, is_model_valid=None,
max_trials=100, stop_sample_num=np.inf, stop_residuals_sum=0,
stop_probability=1, exceptions=Exception):
stop_probability=1):
"""Fit a model to data with the RANSAC (random sample consensus) algorithm.
RANSAC is an iterative algorithm for the robust estimation of parameters
@@ -573,10 +573,6 @@ def ransac(data, model_class, min_samples, residual_threshold,
where the probability (confidence) is typically set to a high value
such as 0.99, and e is the current fraction of inliers w.r.t. the
total number of samples.
exceptions : exception class or tuple of exception classes
A list of exceptions that are ignored when estimating the model from a
random subset. By default all exceptions derived from the built-in
exception class `Exception` are ignored.
Returns
-------
@@ -692,14 +688,7 @@ def ransac(data, model_class, min_samples, residual_threshold,
# estimate model for current random sample set
sample_model = model_class()
if exceptions:
try:
sample_model.estimate(*samples)
except exceptions:
continue
else:
sample_model.estimate(*samples)
sample_model.estimate(*samples)
# check if estimated model is valid
if is_model_valid is not None and not is_model_valid(sample_model,
skimage/measure/tests/test_fit.py
-20
View File
@@ -247,26 +247,6 @@ def test_ransac_invalid_input():
residual_threshold=0, stop_probability=1.01)
def test_ransac_exceptions():
class Estimator(object):
def estimate(self, x):
raise AttributeError
def residuals(self, x):
return x
assert_raises(AttributeError, ransac, (np.zeros((10,)),), Estimator,
min_samples=2, residual_threshold=0, exceptions=None)
assert_raises(AttributeError, ransac, (np.zeros((10,)),), Estimator,
min_samples=2, residual_threshold=0, exceptions=tuple())
ransac((np.zeros((10,)),), Estimator, min_samples=2, residual_threshold=0)
ransac((np.zeros((10,)),), Estimator, min_samples=2,
residual_threshold=0, exceptions=AttributeError)
ransac((np.zeros((10,)),), Estimator, min_samples=2,
residual_threshold=0, exceptions=(AttributeError,))
def test_deprecated_params_attribute():
model = LineModel()
model.params = (10, 1)
skimage/transform/_geometric.py
+12 -4
View File
@@ -265,8 +265,12 @@ class ProjectiveTransform(GeometricTransform):
"""
src_matrix, src = _center_and_normalize_points(src)
dst_matrix, dst = _center_and_normalize_points(dst)
try:
src_matrix, src = _center_and_normalize_points(src)
dst_matrix, dst = _center_and_normalize_points(dst)
except ZeroDivisionError:
self.params = np.nan * np.empty((3, 3))
return
xs = src[:, 0]
ys = src[:, 1]
@@ -652,8 +656,12 @@ class SimilarityTransform(ProjectiveTransform):
"""
src_matrix, src = _center_and_normalize_points(src)
dst_matrix, dst = _center_and_normalize_points(dst)
try:
src_matrix, src = _center_and_normalize_points(src)
dst_matrix, dst = _center_and_normalize_points(dst)
except ZeroDivisionError:
self.params = np.nan * np.empty((3, 3))
return
xs = src[:, 0]
ys = src[:, 1]
skimage/transform/tests/test_geometric.py
+57 -41
View File
@@ -1,5 +1,5 @@
import numpy as np
from numpy.testing import (assert_equal, assert_array_almost_equal,
from numpy.testing import (assert_equal, assert_almost_equal,
assert_raises)
from skimage.transform._geometric import _stackcopy
from skimage.transform._geometric import GeometricTransform
@@ -38,7 +38,7 @@ def test_stackcopy():
y = np.eye(3, 3)
_stackcopy(x, y)
for i in range(layers):
assert_array_almost_equal(x[..., i], y)
assert_almost_equal(x[..., i], y)
def test_estimate_transform():
@@ -56,20 +56,20 @@ def test_matrix_transform():
def test_similarity_estimation():
# exact solution
tform = estimate_transform('similarity', SRC[:2, :], DST[:2, :])
assert_array_almost_equal(tform(SRC[:2, :]), DST[:2, :])
assert_almost_equal(tform(SRC[:2, :]), DST[:2, :])
assert_equal(tform.params[0, 0], tform.params[1, 1])
assert_equal(tform.params[0, 1], - tform.params[1, 0])
# over-determined
tform2 = estimate_transform('similarity', SRC, DST)
assert_array_almost_equal(tform2.inverse(tform2(SRC)), SRC)
assert_almost_equal(tform2.inverse(tform2(SRC)), SRC)
assert_equal(tform2.params[0, 0], tform2.params[1, 1])
assert_equal(tform2.params[0, 1], - tform2.params[1, 0])
# via estimate method
tform3 = SimilarityTransform()
tform3.estimate(SRC, DST)
assert_array_almost_equal(tform3.params, tform2.params)
assert_almost_equal(tform3.params, tform2.params)
def test_similarity_init():
@@ -79,15 +79,15 @@ def test_similarity_init():
translation = (1, 1)
tform = SimilarityTransform(scale=scale, rotation=rotation,
translation=translation)
assert_array_almost_equal(tform.scale, scale)
assert_array_almost_equal(tform.rotation, rotation)
assert_array_almost_equal(tform.translation, translation)
assert_almost_equal(tform.scale, scale)
assert_almost_equal(tform.rotation, rotation)
assert_almost_equal(tform.translation, translation)
# init with transformation matrix
tform2 = SimilarityTransform(tform.params)
assert_array_almost_equal(tform2.scale, scale)
assert_array_almost_equal(tform2.rotation, rotation)
assert_array_almost_equal(tform2.translation, translation)
assert_almost_equal(tform2.scale, scale)
assert_almost_equal(tform2.rotation, rotation)
assert_almost_equal(tform2.translation, translation)
# test special case for scale if rotation=0
scale = 0.1
@@ -95,9 +95,9 @@ def test_similarity_init():
translation = (1, 1)
tform = SimilarityTransform(scale=scale, rotation=rotation,
translation=translation)
assert_array_almost_equal(tform.scale, scale)
assert_array_almost_equal(tform.rotation, rotation)
assert_array_almost_equal(tform.translation, translation)
assert_almost_equal(tform.scale, scale)
assert_almost_equal(tform.rotation, rotation)
assert_almost_equal(tform.translation, translation)
# test special case for scale if rotation=90deg
@@ -106,24 +106,24 @@ def test_similarity_init():
translation = (1, 1)
tform = SimilarityTransform(scale=scale, rotation=rotation,
translation=translation)
assert_array_almost_equal(tform.scale, scale)
assert_array_almost_equal(tform.rotation, rotation)
assert_array_almost_equal(tform.translation, translation)
assert_almost_equal(tform.scale, scale)
assert_almost_equal(tform.rotation, rotation)
assert_almost_equal(tform.translation, translation)
def test_affine_estimation():
# exact solution
tform = estimate_transform('affine', SRC[:3, :], DST[:3, :])
assert_array_almost_equal(tform(SRC[:3, :]), DST[:3, :])
assert_almost_equal(tform(SRC[:3, :]), DST[:3, :])
# over-determined
tform2 = estimate_transform('affine', SRC, DST)
assert_array_almost_equal(tform2.inverse(tform2(SRC)), SRC)
assert_almost_equal(tform2.inverse(tform2(SRC)), SRC)
# via estimate method
tform3 = AffineTransform()
tform3.estimate(SRC, DST)
assert_array_almost_equal(tform3.params, tform2.params)
assert_almost_equal(tform3.params, tform2.params)
def test_affine_init():
@@ -134,71 +134,71 @@ def test_affine_init():
translation = (1, 1)
tform = AffineTransform(scale=scale, rotation=rotation, shear=shear,
translation=translation)
assert_array_almost_equal(tform.scale, scale)
assert_array_almost_equal(tform.rotation, rotation)
assert_array_almost_equal(tform.shear, shear)
assert_array_almost_equal(tform.translation, translation)
assert_almost_equal(tform.scale, scale)
assert_almost_equal(tform.rotation, rotation)
assert_almost_equal(tform.shear, shear)
assert_almost_equal(tform.translation, translation)
# init with transformation matrix
tform2 = AffineTransform(tform.params)
assert_array_almost_equal(tform2.scale, scale)
assert_array_almost_equal(tform2.rotation, rotation)
assert_array_almost_equal(tform2.shear, shear)
assert_array_almost_equal(tform2.translation, translation)
assert_almost_equal(tform2.scale, scale)
assert_almost_equal(tform2.rotation, rotation)
assert_almost_equal(tform2.shear, shear)
assert_almost_equal(tform2.translation, translation)
def test_piecewise_affine():
tform = PiecewiseAffineTransform()
tform.estimate(SRC, DST)
# make sure each single affine transform is exactly estimated
assert_array_almost_equal(tform(SRC), DST)
assert_array_almost_equal(tform.inverse(DST), SRC)
assert_almost_equal(tform(SRC), DST)
assert_almost_equal(tform.inverse(DST), SRC)
def test_projective_estimation():
# exact solution
tform = estimate_transform('projective', SRC[:4, :], DST[:4, :])
assert_array_almost_equal(tform(SRC[:4, :]), DST[:4, :])
assert_almost_equal(tform(SRC[:4, :]), DST[:4, :])
# over-determined
tform2 = estimate_transform('projective', SRC, DST)
assert_array_almost_equal(tform2.inverse(tform2(SRC)), SRC)
assert_almost_equal(tform2.inverse(tform2(SRC)), SRC)
# via estimate method
tform3 = ProjectiveTransform()
tform3.estimate(SRC, DST)
assert_array_almost_equal(tform3.params, tform2.params)
assert_almost_equal(tform3.params, tform2.params)
def test_projective_init():
tform = estimate_transform('projective', SRC, DST)
# init with transformation matrix
tform2 = ProjectiveTransform(tform.params)
assert_array_almost_equal(tform2.params, tform.params)
assert_almost_equal(tform2.params, tform.params)
def test_polynomial_estimation():
# over-determined
tform = estimate_transform('polynomial', SRC, DST, order=10)
assert_array_almost_equal(tform(SRC), DST, 6)
assert_almost_equal(tform(SRC), DST, 6)
# via estimate method
tform2 = PolynomialTransform()
tform2.estimate(SRC, DST, order=10)
assert_array_almost_equal(tform2.params, tform.params)
assert_almost_equal(tform2.params, tform.params)
def test_polynomial_init():
tform = estimate_transform('polynomial', SRC, DST, order=10)
# init with transformation parameters
tform2 = PolynomialTransform(tform.params)
assert_array_almost_equal(tform2.params, tform.params)
assert_almost_equal(tform2.params, tform.params)
def test_polynomial_default_order():
tform = estimate_transform('polynomial', SRC, DST)
tform2 = estimate_transform('polynomial', SRC, DST, order=2)
assert_array_almost_equal(tform2.params, tform.params)
assert_almost_equal(tform2.params, tform.params)
def test_polynomial_inverse():
@@ -210,17 +210,17 @@ def test_union():
tform2 = SimilarityTransform(scale=0.1, rotation=0.9)
tform3 = SimilarityTransform(scale=0.1 ** 2, rotation=0.3 + 0.9)
tform = tform1 + tform2
assert_array_almost_equal(tform.params, tform3.params)
assert_almost_equal(tform.params, tform3.params)
tform1 = AffineTransform(scale=(0.1, 0.1), rotation=0.3)
tform2 = SimilarityTransform(scale=0.1, rotation=0.9)
tform3 = SimilarityTransform(scale=0.1 ** 2, rotation=0.3 + 0.9)
tform = tform1 + tform2
assert_array_almost_equal(tform.params, tform3.params)
assert_almost_equal(tform.params, tform3.params)
assert tform.__class__ == ProjectiveTransform
tform = AffineTransform(scale=(0.1, 0.1), rotation=0.3)
assert_array_almost_equal((tform + tform.inverse).params, np.eye(3))
assert_almost_equal((tform + tform.inverse).params, np.eye(3))
def test_union_differing_types():
@@ -260,6 +260,22 @@ def test_deprecated_params_attributes():
assert_equal(tform._params, tform.params)
def test_degenerate():
src = dst = np.zeros((10, 2))
tform = SimilarityTransform()
tform.estimate(src, dst)
assert np.all(np.isnan(tform.params))
tform = AffineTransform()
tform.estimate(src, dst)
assert np.all(np.isnan(tform.params))
tform = ProjectiveTransform()
tform.estimate(src, dst)
assert np.all(np.isnan(tform.params))
if __name__ == "__main__":
from numpy.testing import run_module_suite
run_module_suite()