Update dependencies

examples/examples_requirements.txt

@@ -1,5 +1,4 @@
 astra-toolbox
-bm4d>=4.0.0
 colour_demosaicing
 xdesign>=0.5.5
 ray[tune]>=2.0.0

requirements.txt

@@ -3,9 +3,10 @@ scipy>=1.6.0
 tifffile
 imageio>=2.17
 matplotlib
-jaxlib>=0.3.0,<=0.3.24
-jax>=0.3.0,<=0.3.24
+jaxlib>=0.3.0,<=0.3.25
+jax>=0.3.0,<=0.3.25
 flax>=0.4.0
-bm3d>=3.0.9
+bm3d>=4.0.0
+bm4d>=4.2.2
 svmbir>=0.3.0
 pyabel>=0.8.5

scico/denoiser.py

@@ -5,26 +5,8 @@
 # user license can be found in the 'LICENSE' file distributed with the
 # package.
 
-"""
-Interfaces to standard denoisers.
-
-**Warning**: The :func:`bm4d` function is implemented as an interface
-to the `bm4d <https://pypi.org/project/bm4d>`__ package. The current
-version of this package, 4.0.0, appears to be compiled with compiler
-options that `change the behavior of the floating point unit
-<https://moyix.blogspot.com/2022/09/someones-been-messing-with-my-subnormals.html>`__
-in a way that results in lower numerical accuracy, and that persist
-for the duration of the process that loads it. If this package is
-installed, simply loading this module (:mod:`scico.denoiser`), is
-sufficient to inflict this loss of numerical precision on all other
-calculations run within the same process, even if :func:`bm4d` is not
-actually used. Users who are not making use of :func:`bm4d` are
-advised not to install the corresponding package. For additional
-information, see `scico issue #342
-<https://github.com/lanl/scico/issues/342>`__.
-"""
-
-import warnings
+"""Interfaces to standard denoisers."""
+
 
 import numpy as np
 
@@ -43,19 +25,6 @@
     have_bm4d = False
 else:
     have_bm4d = True
-    finfo = np.finfo(np.float32)  # type: ignore
-    if hasattr(finfo, "smallest_subnormal"):  # can't test with older numpy versions
-        if finfo.smallest_subnormal == 0.0:
-            warnings.warn(
-                "Importing module bm4d has had an adverse affect on floating point "
-                "accuracy. See the documentation for module scico.denoiser, and "
-                "scico issue #342."
-            )
-            warnings.filterwarnings(
-                action="ignore",
-                message="^The value of the smallest subnormal",
-                category=UserWarning,
-            )
 
 import scico.numpy as snp
 from scico._flax import DnCNNNet, load_weights

scico/test/functional/test_denoiser_func.py

@@ -23,12 +23,12 @@ def setup_method(self):
     def test_gry(self):
         y0 = self.f_gry.prox(self.x_gry, 1.0)
         y1 = denoiser.bm3d(self.x_gry, 1.0)
-        np.testing.assert_allclose(y0, y1, rtol=1e-5)
+        assert np.linalg.norm(y1 - y0) < 1e-3
 
     def test_rgb(self):
         y0 = self.f_rgb.prox(self.x_rgb, 1.0)
         y1 = denoiser.bm3d(self.x_rgb, 1.0, is_rgb=True)
-        np.testing.assert_allclose(y0, y1, rtol=1e-5)
+        assert np.linalg.norm(y1 - y0) < 1e-3
 
 
 # bm4d is known to be broken on OSX 11.6.5. It may be broken on earlier versions too,
@@ -44,7 +44,7 @@ def setup_method(self):
     def test(self):
         y0 = self.f.prox(self.x, 1.0)
         y1 = denoiser.bm4d(self.x, 1.0)
-        np.testing.assert_allclose(y0, y1, rtol=1e-5)
+        assert np.linalg.norm(y1 - y0) < 1e-3
 
 
 class TestDnCNN:

scico/test/test_denoiser.py

@@ -26,14 +26,14 @@ def test_shape(self):
     def test_gry(self):
         no_jit = bm3d(self.x_gry, 1.0)
         jitted = jax.jit(bm3d)(self.x_gry, 1.0)
-        np.testing.assert_allclose(no_jit, jitted, rtol=1e-3)
+        assert np.linalg.norm(no_jit - jitted) < 1e-3
         assert no_jit.dtype == np.float32
         assert jitted.dtype == np.float32
 
     def test_rgb(self):
         no_jit = bm3d(self.x_rgb, 1.0)
         jitted = jax.jit(bm3d)(self.x_rgb, 1.0, is_rgb=True)
-        np.testing.assert_allclose(no_jit, jitted, rtol=1e-3)
+        assert np.linalg.norm(no_jit - jitted) < 1e-3
         assert no_jit.dtype == np.float32
         assert jitted.dtype == np.float32
 
@@ -74,13 +74,13 @@ def test_shape(self):
     def test_jit(self):
         no_jit = bm4d(self.x1, 1.0)
         jitted = jax.jit(bm4d)(self.x1, 1.0)
-        np.testing.assert_allclose(no_jit, jitted, rtol=1e-3)
+        assert np.linalg.norm(no_jit - jitted) < 1e-3
         assert no_jit.dtype == np.float32
         assert jitted.dtype == np.float32
 
         no_jit = bm4d(self.x2, 1.0)
         jitted = jax.jit(bm4d)(self.x2, 1.0)
-        np.testing.assert_allclose(no_jit, jitted, rtol=1e-3)
+        assert np.linalg.norm(no_jit - jitted) < 1e-3
         assert no_jit.dtype == np.float32
         assert jitted.dtype == np.float32