Implement Appveyor builds
initial test
Updated appveyor.yml
New nosetest call
With conda update conda
with pillow
without pillow
TST: Change case sensitivive JPG extension
Revert "TST: Change case sensitivive JPG extension"
This reverts commit 2deed7cc63736f7c6f0387bd37df4c6643c32847.
Trying with Python 2.7
Trying with version env
Trying again with variables
Testing on all Python versions
don't allow failures
Allow failure
Do not actually use tests
Ignore failing tests
Removed Python 2.6 test
Testing only Python 2.6
Testing out more sklearn like AppVeyor CI
Added install to pip
Add artifacts
Enabled all permutations
Disable 2.6, add PIL
Python 2.6, 2.7 only with PIL
Testing with variable dependencies
Allow failure with IF ELSE
With Python 3.4
Scikit-learn like appveyor CI
Fixing paths
Undo path fix
path fix single line
path fix single line 2
Using Miniconda
More path fixes
New wheelhouse link
Added pillow to requirements.txt
Added networkx to requirements.txt
Add testing of 32/64-bit Python 2.7 and 3.4 to matrix
Debugging Cython compile
Retry with all 4 builds
Updated install.ps1 file
Updated based on latest python-appveyor-demo
Debugging pip install
Specify numpy 1.8.1 until whl is uploaded to rackspace
Use skimage-wide requirements.txt file
Minor comment change to trigger build
Install wheel and then install from WHEELHOUSE
Install six from pip
Install networkx from pip
Install pyparsing from pip
Install pytz from pip
Try using just find-links
Install the binary dependencies first, then the rest
Add pillow to the install list
Fix appveyor.yml syntax
Fix requirements.txt syntax
Fix requirements.txt syntax again
Fix appveyor call to initial install
Fix appveyor call to initial install again
Fix appveyor call to initial install yet again
Install wheel
Install wheel first
Install wheel and nose in the appveyor requirements.txt
Fix Python3 version to match python ftp site
Only use cleanup decorator if available
Add debug info to multiimage test
More debugging information
Fix handling of path separators on Windows
Add another warning guard
Fix warning handling for non-windows
Do not use TkAgg as it may be causing alloc error
Clean up echo command
Allow for unclosed file warning
Fix spacing in echo command
Fix handling of multiple warnings
Update all test __init__ files
Update segmentation pkg
Update the color pkg
Update the exposure pkg
Update the filters pkg
Update the io pkg
Update the measure pkg
Update morphology package
Restructure test setup function
Add expected_warnings to __all__
Update restoration pkg.
Remove explicit filter check since it is done elsewhere
Fix the image test helpers
Update the transform pkg
Fix util pkg
Update viewer pkg
Reset plugins prior to running collections test
Handle warnings in morphology pkg
Add __init__ for morpohology tests
Handle warnings for novice pkg
Handle warnings for restoration pkg
Handle warnings for segmentation pkg
Handle warnings for _shared pkg
Handle warnings for transform pkg
Handle warnings for util pkg
Handle warnings in viewer module
Also:
* New tests to cover these new checks
* Improvements to docstrings and user warnings
* Generalize handling of `sampling` in accordance with docstring
* Some extra whitespace to improve readability
This commit represents all recommended changes since the last
commit, notably:
* PEP8 compliance (in new sections; a few old ones still
noncompliant w/indentations)
* Moved `depth` kwarg to end of list and in docstring.
Clarified `depth` docstring, and added section in Notes
further explaining this parameter.
* Added section in Notes warning that for multichannel inputs,
all channels are combined during scaling. The user must
separately normalize each channel prior to calling
random_walker()
* New method for parsing data, allowing more elegant gradient
calculation code. Probably also more extensible. The 2D
multispectral case forced this change.
* New test: `test_multispectral_2d()`
In this new version, all instances of 'spectrum' have been replaced with 'channel'. The documentation also reflects this change, and the new multichannel kwarg used to indicate multichannel input is named appropriately.
New boolean multichannel kwarg added, which controls if the input has multiple channels or not. Input 'data' is now array_like for both gray-level and multichannel. This kwarg is needed mainly because a 3-D array could be either 3 spatial dimensions or a set of different 2-D channels.
New scaling kwarg added (may be removed in future), controlling if data scaling is applied to ALL channels or each channel individually, if multichannel=True. No effect for gray-level data.
Removed np.sqrt(gradients) in _compute_weights_3d(), which was a bug. Tests now pass consistently.
New method for maintaining shape from input to output, where dims = data.shape prior to np.atleast_3d(). A theoretical (70,100,1) array passed should now result in a (70,100,1) shaped output, for example.
Updated and fixed multispectral test script to work with new version. TODO: Additional test(s) likely needed to cover code branches from new kwargs.
Since the multispectral path is equivalent except for gradient calcs,
only one test case is needed. This test is modeled on the 3-D
non-multispectral version. If deemed necessary, adding a 2-D case
would be simple.
* returning the probability to belong to a label instead of only the most
likely label is now possible
* fixing some type issues
* handling non-consecutive label values
Jonathan Helmus