Merge pull request #585 from nipy/rel/2.2.1

2.2.1 bug fix release

.mailmap

@@ -40,3 +40,4 @@ Satrajit Ghosh <[email protected]> Satrajit Ghosh <[email protected]>
 Jasper J.F. van den Bosch <[email protected]> Jasper <[email protected]>
 Gregory R. Lee <[email protected]> Gregory R. Lee <[email protected]>
 Demian Wassermann <[email protected]> Demian Wassermann <[email protected]>
+Paul McCarthy <[email protected]> Paul McCarthy <[email protected]>

Changelog

@@ -24,6 +24,25 @@ Gerhard (SG) and Eric Larson (EL).
 
 References like "pr/298" refer to github pull request numbers.
 
+2.2.1 (Wednesday 22 November 2017)
+==================================
+
+Bug fixes
+---------
+
+* Set L/R labels in orthoview correctly (pr/564) (CM)
+* Defer use of ufunc / memmap test - allows "freezing" (pr/572) (MB, reviewed
+  by Satra Ghosh)
+* Fix doctest failures with pre-release numpy (pr/582) (MB, reviewed by CM)
+
+Maintenance
+-----------
+
+* Update documentation around NIfTI qform/sform codes (pr/576) (Paul McCarthy,
+  reviewed by MB, CM) + (pr/580) (Bennet Fauber, reviewed by Paul McCarthy)
+* Skip precision test on macOS, newer numpy (pr/583) (MB, reviewed by CM)
+* Simplify AppVeyor script, removing conda (pr/584) (MB, reviewed by CM)
+
 2.2 (Friday 13 October 2017)
 ============================
 

appveyor.yml

@@ -1,60 +1,34 @@
 # vim ft=yaml
 # CI on Windows via appveyor
-# This file was based on Olivier Grisel's python-appveyor-demo
 
 environment:
 
   matrix:
-    - PYTHON: "C:\\Python27-conda32"
-      PYTHON_VERSION: "2.7"
-      PYTHON_ARCH: "32"
-
-    - PYTHON: "C:\\Python34-conda32"
-      PYTHON_VERSION: "3.4"
-      PYTHON_ARCH: "32"
-
-    - PYTHON: "C:\\Python34-conda64"
-      PYTHON_VERSION: "3.4"
-      PYTHON_ARCH: "64"
-
-    - PYTHON: "C:\\Python35-conda64"
-      PYTHON_VERSION: "3.5"
-      PYTHON_ARCH: "64"
-
-    - PYTHON: "C:\\Python35-conda32"
-      PYTHON_VERSION: "3.5"
-      PYTHON_ARCH: "32"
+    - PYTHON: C:\Python27
+    - PYTHON: C:\Python27-x64
+    - PYTHON: C:\Python34
+    - PYTHON: C:\Python34-x64
+    - PYTHON: C:\Python35
+    - PYTHON: C:\Python35-x64
+    - PYTHON: C:\Python36
+    - PYTHON: C:\Python36-x64
 
 install:
-  # Install miniconda Python
-  - "powershell ./tools/install_python.ps1"
-
   # Prepend newly installed Python to the PATH of this build (this cannot be
   # done from inside the powershell script as it would require to restart
   # the parent CMD process).
-  - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%"
-
-  # Set up a conda environment:
-  - conda config --set always_yes yes
-  - conda update -q conda
-  - conda info -a
-  - conda create -q -n test-environment python=%PYTHON_VERSION%
-  - activate test-environment
-
-  # Check that we have the expected version and architecture for Python
-  - "python --version"
-  - "python -c \"import struct; print(struct.calcsize('P') * 8)\""
+  - SET PATH=%PYTHON%;%PYTHON%\Scripts;%PATH%
 
   # Install the dependencies of the project.
-  - "conda install --yes --quiet numpy scipy matplotlib nose h5py mock"
-  - "pip install pydicom"
-  - "python setup.py install"
-  - "SET NIBABEL_DATA_DIR=%CD%\\nibabel-data"
+  - pip install numpy scipy matplotlib nose h5py mock
+  - pip install pydicom
+  - pip install .
+  - SET NIBABEL_DATA_DIR=%CD%\nibabel-data
 
 build: false  # Not a C# project, build stuff at the test step instead.
 
 test_script:
   # Change into an innocuous directory and find tests from installation
-  - "mkdir for_testing"
-  - "cd for_testing"
-  - "nosetests --with-doctest nibabel"
+  - mkdir for_testing
+  - cd for_testing
+  - nosetests --with-doctest nibabel

doc/source/index.rst

@@ -79,6 +79,7 @@ contributed code and discussion (in rough order of appearance):
 * Venky Reddy
 * Mark Hymers
 * Jasper J.F. van den Bosch
+* Bennet Fauber
 
 License reprise
 ===============

doc/source/nifti_images.rst

@@ -239,7 +239,7 @@ You can get the affine and the code using the ``coded=True`` argument to
        [   0.  ,    0.32,    2.17,   -7.25],
        [   0.  ,    0.  ,    0.  ,    1.  ]]), array(1, dtype=int16))
 
-You can set the sform with with the ``get_sform()`` method of the header and
+You can set the sform with the ``set_sform()`` method of the header and
 the image.
 
 >>> n1_header.set_sform(np.diag([2, 3, 4, 1]))
@@ -314,6 +314,63 @@ The algorithm is defined in the ``get_best_affine()`` method.  It is:
 #. If ``qform_code`` != 0 ('unknown') use the qform affine; else
 #. Use the fall-back affine.
 
+.. _default-sform-qform-codes:
+
+Default sform and qform codes
+=============================
+
+If you create a new image, e.g.:
+
+>>> data = np.random.random((20, 20, 20))
+>>> xform = np.eye(4) * 2
+>>> img = nib.nifti1.Nifti1Image(data, xform)
+
+The sform and qform codes will be initialised to 2 (aligned) and 0 (unknown)
+respectively:
+
+>>> img.get_sform(coded=True) # doctest: +NORMALIZE_WHITESPACE
+(array([[ 2.,  0.,  0.,  0.],
+        [ 0.,  2.,  0.,  0.],
+        [ 0.,  0.,  2.,  0.],
+        [ 0.,  0.,  0.,  1.]]), array(2, dtype=int16))
+>>> img.get_qform(coded=True)
+(None, 0)
+
+This is based on the assumption that the affine you specify for a newly
+created image will align the image to some known coordinate system. According
+to the `NIfTI specification <nifti1>`_, the qform is intended to encode a
+transformation into scanner coordinates - for a programmatically created
+image, we have no way of knowing what the scanner coordinate system is;
+furthermore, the qform cannot be used to store an arbitrary affine transform,
+as it is unable to encode shears. So the provided affine will be stored in the
+sform, and the qform will be left uninitialised.
+
+If you create a new image and specify an existing header, e.g.:
+
+>>> example_ni1 = os.path.join(data_path, 'example4d.nii.gz')
+>>> n1_img = nib.load(example_ni1)
+>>> new_header = header=n1_img.header.copy()
+>>> new_data = np.random.random(n1_img.shape[:3])
+>>> new_img = nib.nifti1.Nifti1Image(data, None, header=new_header)
+
+then the newly created image will inherit the same sform and qform codes that
+are in the provided header. However, if you create a new image with both an
+affine and a header specified, e.g.:
+
+>>> xform = np.eye(4)
+>>> new_img = nib.nifti1.Nifti1Image(data, xform, header=new_header)
+
+then the sform and qform codes will *only* be preserved if the provided affine
+is the same as the affine in the provided header. If the affines do not match,
+the sform and qform codes will be set to their default values of 2 and 0
+respectively. This is done on the basis that, if you are changing the affine,
+you are likely to be changing the space to which the affine is pointing. So
+the original sform and qform codes can no longer be assumed to be valid.
+
+If you wish to set the sform and qform affines and/or codes to some other
+value, you can always set them after creation using the ``set_sform`` and
+``set_qform`` methods, as described above.
+
 ************
 Data scaling
 ************

nibabel/benchmarks/bench_arrayproxy_slicing.py

@@ -191,7 +191,7 @@ def testfunc():
     data[:, 1] = [r[4] for r in results]
     try:
         data[:, 2] = [r[3] / r[4] for r in results]
-    except:
+    except ZeroDivisionError:
         data[:, 2] = np.nan
     data[:, 3] = [r[5] - r[6] for r in results]
 

nibabel/ecat.py

@@ -468,13 +468,13 @@ def get_series_framenumbers(mlist):
     mlist_nframes = len(frames_order)
     trueframenumbers = np.arange(nframes - mlist_nframes, nframes)
     frame_dict = {}
-    try:
-        for frame_stored, (true_order, _) in frames_order.items():
-            # frame as stored in file -> true number in series
+    for frame_stored, (true_order, _) in frames_order.items():
+        # frame as stored in file -> true number in series
+        try:
             frame_dict[frame_stored] = trueframenumbers[true_order] + 1
-        return frame_dict
-    except:
-        raise IOError('Error in header or mlist order unknown')
+        except IndexError:
+            raise IOError('Error in header or mlist order unknown')
+    return frame_dict
 
 
 def read_subheaders(fileobj, mlist, endianness):

nibabel/info.py

@@ -19,8 +19,8 @@
 _version_major = 2
 _version_minor = 2
 _version_micro = 1
-_version_extra = 'dev'
-# _version_extra = ''
+# _version_extra = 'dev'
+_version_extra = ''
 
 # Format expected by setup.py and doc/source/conf.py: string of form "X.Y.Z"
 __version__ = "%s.%s.%s%s" % (_version_major,

nibabel/nicom/dwiparams.py

@@ -21,7 +21,7 @@
 '''
 import numpy as np
 import numpy.linalg as npl
-from ..testing import setup_test  # flake8: noqa F401
+from ..testing import setup_test as setup_module # flake8: noqa F401
 
 
 def B2q(B, tol=None):

nibabel/nifti1.py

@@ -1764,7 +1764,20 @@ def __init__(self, dataobj, affine, header=None,
         if header is None and affine is not None:
             self._affine2header()
     # Copy docstring
-    __init__.doc = analyze.AnalyzeImage.__init__.__doc__
+    __init__.__doc__ = analyze.AnalyzeImage.__init__.__doc__ + '''
+    Notes
+    -----
+
+    If both a `header` and an `affine` are specified, and the `affine` does
+    not match the affine that is in the `header`, the `affine` will be used,
+    but the ``sform_code`` and ``qform_code`` fields in the header will be
+    re-initialised to their default values. This is performed on the basis
+    that, if you are changing the affine, you are likely to be changing the
+    space to which the affine is pointing.  The :meth:`set_sform` and
+    :meth:`set_qform` methods can be used to update the codes after an image
+    has been created - see those methods, and the :ref:`manual
+    <default-sform-qform-codes>` for more details.  '''
+
 
     def update_header(self):
         ''' Harmonize header with image data and affine

nibabel/testing/__init__.py

@@ -32,7 +32,7 @@
 data_path = abspath(pjoin(dirname(__file__), '..', 'tests', 'data'))
 
 
-from .np_features import VIRAL_MEMMAP
+from .np_features import memmap_after_ufunc
 
 def assert_dt_equal(a, b):
     """ Assert two numpy dtype specifiers are equal
@@ -218,4 +218,4 @@ def setup_test():
     """
     from distutils.version import LooseVersion
     if LooseVersion(np.__version__) >= LooseVersion('1.14'):
-        np.set_printoptions(sign='legacy')
+        np.set_printoptions(legacy="1.13")

nibabel/testing/np_features.py

@@ -4,16 +4,20 @@
 import numpy as np
 
 
-def _memmap_after_ufunc():
+def memmap_after_ufunc():
     """ Return True if ufuncs on memmap arrays always return memmap arrays
 
     This should be True for numpy < 1.12, False otherwise.
+
+    Memoize after first call.  We do this to avoid having to call this when
+    importing nibabel.testing, because we cannot depend on the source file
+    being present - see gh-571.
     """
+    if memmap_after_ufunc.result is not None:
+        return memmap_after_ufunc.result
     with open(__file__, 'rb') as fobj:
         mm_arr = np.memmap(fobj, mode='r', shape=(10,), dtype=np.uint8)
-        mm_preserved = isinstance(mm_arr + 1, np.memmap)
-    return mm_preserved
-
+        memmap_after_ufunc.result = isinstance(mm_arr + 1, np.memmap)
+    return memmap_after_ufunc.result
 
-# True if ufunc on memmap always returns a memmap
-VIRAL_MEMMAP = _memmap_after_ufunc()
+memmap_after_ufunc.result = None

nibabel/tests/test_arrayproxy.py

@@ -30,7 +30,7 @@
 from numpy.testing import assert_array_equal, assert_array_almost_equal
 from nose.tools import (assert_true, assert_false, assert_equal,
                         assert_not_equal, assert_raises)
-from nibabel.testing import VIRAL_MEMMAP
+from nibabel.testing import memmap_after_ufunc
 
 from .test_fileslice import slicer_samples
 from .test_openers import patch_indexed_gzip
@@ -298,6 +298,8 @@ def check_mmap(hdr, offset, proxy_class,
     # Whether scaled array memory backed by memory map (regardless of what
     # numpy says).
     scaled_really_mmap = unscaled_really_mmap and not has_scaling
+    # Whether ufunc on memmap return memmap
+    viral_memmap = memmap_after_ufunc()
     with InTemporaryDirectory():
         with open(fname, 'wb') as fobj:
             fobj.write(b' ' * offset)
@@ -324,9 +326,9 @@ def check_mmap(hdr, offset, proxy_class,
                 assert_false(back_is_mmap)
             else:
                 assert_equal(unscaled_is_mmap,
-                             VIRAL_MEMMAP or unscaled_really_mmap)
+                             viral_memmap or unscaled_really_mmap)
                 assert_equal(back_is_mmap,
-                             VIRAL_MEMMAP or scaled_really_mmap)
+                             viral_memmap or scaled_really_mmap)
                 if scaled_really_mmap:
                     assert_equal(back_data.mode, expected_mode)
             del prox, back_data

nibabel/tests/test_floating.py

@@ -4,6 +4,8 @@
 
 PY2 = sys.version_info[0] < 3
 
+from distutils.version import LooseVersion
+
 import numpy as np
 
 from ..casting import (floor_exact, ceil_exact, as_int, FloatingError,
@@ -103,7 +105,12 @@ def test_check_nmant_nexp():
         ti = type_info(t)
         if ti['nmant'] != 106:  # This check does not work for PPC double pair
             assert_true(_check_nmant(t, ti['nmant']))
-        assert_true(_check_maxexp(t, ti['maxexp']))
+        # Test fails for longdouble after blacklisting of OSX powl as of numpy
+        # 1.12 - see https://github.com/numpy/numpy/issues/8307
+        if (t != np.longdouble or
+              sys.platform != 'darwin' or
+              LooseVersion(np.__version__) < LooseVersion('1.12')):
+            assert_true(_check_maxexp(t, ti['maxexp']))
 
 
 def test_as_int():

nibabel/tests/test_image_api.py

@@ -377,9 +377,9 @@ def validate_shape(self, imaker, params):
 
     def validate_shape_deprecated(self, imaker, params):
         # Check deprecated get_shape API
+        img = imaker()
         with clear_and_catch_warnings() as w:
             warnings.simplefilter('always', DeprecationWarning)
-            img = imaker()
             assert_equal(img.get_shape(), params['shape'])
             assert_equal(len(w), 1)
 

nibabel/tests/test_spatialimages.py

@@ -25,7 +25,7 @@
 
 from .test_helpers import bytesio_round_trip
 from ..testing import (clear_and_catch_warnings, suppress_warnings,
-                       VIRAL_MEMMAP)
+                       memmap_after_ufunc)
 from ..tmpdirs import InTemporaryDirectory
 from .. import load as top_load
 
@@ -464,6 +464,7 @@ def get_disk_image(self):
     def test_load_mmap(self):
         # Test memory mapping when loading images
         img_klass = self.image_class
+        viral_memmap = memmap_after_ufunc()
         with InTemporaryDirectory():
             img, fname, has_scaling = self.get_disk_image()
             file_map = img.file_map.copy()
@@ -485,7 +486,7 @@ def test_load_mmap(self):
                     # numpies returned a memmap object, even though the array
                     # has no mmap memory backing.  See:
                     # https://github.com/numpy/numpy/pull/7406
-                    if has_scaling and not VIRAL_MEMMAP:
+                    if has_scaling and not viral_memmap:
                         expected_mode = None
                     kwargs = {}
                     if mmap is not None: