Remove old tifffile plugin in favor of using it in PIL plugin.

skimage/io/_plugins/tifffile_plugin.ini

@@ -1,3 +0,0 @@
-[tifffile]
-description = Load and save TIFF and TIFF-based images using tifffile.py
-provides = imread, imsave

skimage/io/_plugins/tifffile_plugin.py

@@ -1,6 +0,0 @@
-try:
-    from tifffile import imread, imsave
-except ImportError:
-    raise ImportError("The tifffile module could not be found.\n"
-        "It can be obtained at "
-        "<http://www.lfd.uci.edu/~gohlke/code/tifffile.py>\n")

skimage/io/tests/test_tifffile.py

@@ -1,62 +0,0 @@
-import os
-import skimage as si
-import skimage.io as sio
-import numpy as np
-
-from numpy.testing import *
-from numpy.testing.decorators import skipif
-from tempfile import NamedTemporaryFile
-
-try:
-    import skimage.io._plugins.tifffile_plugin as tf
-    _plugins = sio.plugin_order()
-    TF_available = True
-    sio.use_plugin('tifffile')
-except ImportError:
-    TF_available = False
-
-np.random.seed(0)
-
-
-def teardown():
-    sio.reset_plugins()
-
-
-@skipif(not TF_available)
-def test_imread_uint16():
-    expected = np.load(os.path.join(si.data_dir, 'chessboard_GRAY_U8.npy'))
-    img = sio.imread(os.path.join(si.data_dir, 'chessboard_GRAY_U16.tif'))
-    assert img.dtype == np.uint16
-    assert_array_almost_equal(img, expected)
-
-
-@skipif(not TF_available)
-def test_imread_uint16_big_endian():
-    expected = np.load(os.path.join(si.data_dir, 'chessboard_GRAY_U8.npy'))
-    img = sio.imread(os.path.join(si.data_dir, 'chessboard_GRAY_U16B.tif'))
-    assert img.dtype == np.uint16
-    assert_array_almost_equal(img, expected)
-
-
-class TestSave:
-    def roundtrip(self, dtype, x):
-        f = NamedTemporaryFile(suffix='.tif')
-        fname = f.name
-        f.close()
-        sio.imsave(fname, x)
-        y = sio.imread(fname)
-        assert_array_equal(x, y)
-
-    @skipif(not TF_available)
-    def test_imsave_roundtrip(self):
-        for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]:
-            for dtype in (np.uint8, np.uint16, np.float32, np.float64):
-                x = np.ones(shape, dtype=dtype) * np.random.rand(*shape)
-
-                if not np.issubdtype(dtype, float):
-                    x = (x * 255).astype(dtype)
-                yield self.roundtrip, dtype, x
-
-
-if __name__ == "__main__":
-    run_module_suite()