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Merge pull request #5718 from mdboom/image-interpolation
Rewrite of image infrastructure
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‎doc/api/api_changes/2015-12-30_draw_image.rst‎

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Change in the ``draw_image`` backend API
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----------------------------------------
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The ``draw_image`` method implemented by backends has changed its interface.
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This change is only relevant if the backend declares that it is able
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to transform images by returning ``True`` from ``option_scale_image``.
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See the ``draw_image`` docstring for more information.

‎doc/users/whats_new/2015-12-30_image-interpolation.rst‎

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Improved image support
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----------------------
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Prior to version 2.0, matplotlib resampled images by first applying
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the color map and then resizing the result. Since the resampling was
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performed on the colored image, this introduced colors in the output
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image that didn't actually exist in the color map. Now, images are
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resampled first (and entirely in floating-point, if the input image is
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floating-point), and then the color map is applied.
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In order to make this important change, the image handling code was
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almost entirely rewritten. As a side effect, image resampling uses
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less memory and fewer datatype conversions than before.
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The experimental private feature where one could "skew" an image by
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setting the private member ``_image_skew_coordinate`` has been
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removed. Instead, images will obey the transform of the axes on which
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they are drawn.

‎doc/users/whats_new/rcparams.rst‎

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@@ -19,10 +19,20 @@ Configuration (rcParams)
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|`svg.hashsalt` | see note |
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+----------------------------+--------------------------------------------------+
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``svg.hashsalt``
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````````````````
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Added ``svg.hashsalt`` key to rcParams
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```````````````````````````````````````
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If ``svg.hashsalt`` is ``None`` (which it is by default), the svg
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backend uses ``uuid4`` to generate the hash salt. If it is not
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``None``, it must be a string that is used as the hash salt instead of
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``uuid4``. This allows for deterministic SVG output.
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Removed the ``svg.image_noscale`` rcParam
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`````````````````````````````````````````
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As a result of the extensive changes to image handling, the
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``svg.image_noscale`` rcParam has been removed. The same
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functionality may be achieved by setting ``interpolation='none'`` on
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individual images or globally using the ``image.interpolation``
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rcParam.

‎examples/api/demo_affine_image.py‎

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#!/usr/bin/env python
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"""
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For the backends that supports draw_image with optional affine
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transform (e.g., agg, ps backend), the image of the output should
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return Z
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def imshow_affine(ax, z, *kl, **kwargs):
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im = ax.imshow(z, *kl, **kwargs)
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x1, x2, y1, y2 = im.get_extent()
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im._image_skew_coordinate = (x2, y1)
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return im
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if 1:
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# image rotation
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fig, (ax1, ax2) = plt.subplots(1, 2)
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fig, ax1 = plt.subplots(1, 1)
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Z = get_image()
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im1 = imshow_affine(ax1, Z, interpolation='none',
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origin='lower',
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extent=[-2, 4, -3, 2], clip_on=True)
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im1 = ax1.imshow(Z, interpolation='none',
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origin='lower',
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extent=[-2, 4, -3, 2], clip_on=True)
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trans_data2 = mtransforms.Affine2D().rotate_deg(30) + ax1.transData
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im1.set_transform(trans_data2)
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ax1.set_xlim(-3, 5)
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ax1.set_ylim(-4, 4)
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# image skew
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im2 = ax2.imshow(Z, interpolation='none',
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origin='lower',
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extent=[-2, 4, -3, 2], clip_on=True)
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im2._image_skew_coordinate = (3, -2)
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plt.show()
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#plt.savefig("demo_affine_image")

‎examples/images_contours_and_fields/interpolation_methods.py‎

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'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',
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'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos']
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np.random.seed(0)
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grid = np.random.rand(4, 4)
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fig, axes = plt.subplots(3, 6, figsize=(12, 6),
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fig.subplots_adjust(hspace=0.3, wspace=0.05)
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for ax, interp_method in zip(axes.flat, methods):
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ax.imshow(grid, interpolation=interp_method)
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ax.imshow(grid, interpolation=interp_method, cmap='viridis')
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ax.set_title(interp_method)
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plt.show()

‎examples/pylab_examples/demo_annotation_box.py‎

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arr = np.arange(100).reshape((10, 10))
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im = OffsetImage(arr, zoom=2)
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im.image.axes = ax
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ab = AnnotationBbox(im, xy,
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xybox=(-50., 50.),
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from matplotlib._png import read_png
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fn = get_sample_data("grace_hopper.png", asfileobj=False)
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arr_lena = read_png(fn)
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arr_img = read_png(fn)
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imagebox = OffsetImage(arr_lena, zoom=0.2)
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imagebox = OffsetImage(arr_img, zoom=0.2)
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imagebox.image.axes = ax
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ab = AnnotationBbox(imagebox, xy,
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xybox=(120., -80.),

‎extern/agg24-svn/include/agg_span_image_filter_gray.h‎

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fg_ptr = (const value_type*)base_type::source().next_y();
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}
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fg >>= image_filter_shift;
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fg = color_type::downshift(fg, image_filter_shift);
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if(fg < 0) fg = 0;
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if(fg > color_type::full_value()) fg = color_type::full_value();
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span->v = (value_type)fg;

‎lib/matplotlib/__init__.py‎

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'savefig.extension': ('savefig.format', lambda x: x, None),
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'axes.color_cycle': ('axes.prop_cycle', lambda x: cycler('color', x),
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lambda x: [c.get('color', None) for c in x]),
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'svg.image_noscale': ('image.interpolation', None, None),
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}
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_deprecated_ignore_map = {

‎lib/matplotlib/axes/_base.py‎

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artists.remove(self._left_title)
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artists.remove(self._right_title)
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# add images to dsu if the backend supports compositing.
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# otherwise, does the manual compositing without adding images to dsu.
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if len(self.images) <= 1 or renderer.option_image_nocomposite():
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_do_composite = False
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else:
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_do_composite = True
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for im in self.images:
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artists.remove(im)
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if self.figure.canvas.is_saving():
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dsu = [(a.zorder, a) for a in artists]
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else:
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if self.axison and self._frameon:
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self.patch.draw(renderer)
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if _do_composite:
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# make a composite image, blending alpha
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# list of (mimage.Image, ox, oy)
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zorder_images = [(im.zorder, im) for im in self.images
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if im.get_visible()]
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zorder_images.sort(key=lambda x: x[0])
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mag = renderer.get_image_magnification()
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ims = [(im.make_image(mag), 0, 0, im.get_alpha())
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for z, im in zorder_images]
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l, b, r, t = self.bbox.extents
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width = int(mag * ((np.round(r) + 0.5) - (np.round(l) - 0.5)))
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height = int(mag * ((np.round(t) + 0.5) - (np.round(b) - 0.5)))
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im = mimage.from_images(height,
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width,
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ims)
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im.is_grayscale = False
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l, b, w, h = self.bbox.bounds
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# composite images need special args so they will not
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# respect z-order for now
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gc = renderer.new_gc()
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gc.set_clip_rectangle(self.bbox)
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gc.set_clip_path(mtransforms.TransformedPath(
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self.patch.get_path(),
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self.patch.get_transform()))
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renderer.draw_image(gc, round(l), round(b), im)
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gc.restore()
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if dsu_rasterized:
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for zorder, a in dsu_rasterized:
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a.draw(renderer)
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renderer.stop_rasterizing()
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for zorder, a in dsu:
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a.draw(renderer)
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mimage._draw_list_compositing_images(renderer, self, dsu)
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renderer.close_group('axes')
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self._cachedRenderer = renderer

‎lib/matplotlib/backend_bases.py‎

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"""
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return 1.0
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def draw_image(self, gc, x, y, im):
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def draw_image(self, gc, x, y, im, trans=None):
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"""
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Draw the image instance into the current axes;
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is the distance from bottom
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*im*
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the :class:`matplotlib._image.Image` instance
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An NxMx4 array of RGBA pixels (of dtype uint8).
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*trans*
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If the concrete backend is written such that
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`option_scale_image` returns `True`, an affine
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transformation may also be passed to `draw_image`. The
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backend should apply the transformation to the image
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before applying the translation of `x` and `y`.
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"""
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raise NotImplementedError
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