image
matplotlib.image
The image module supports basic image loading, rescaling and display operations.
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class matplotlib.image.AxesImage(ax, cmap=None, norm=None, interpolation=None, origin=None, extent=None, filternorm=1, filterrad=4.0, resample=False, **kwargs)
[source] -
Bases:
matplotlib.image._ImageBase
interpolation and cmap default to their rc settings
cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1
extent is data axes (left, right, bottom, top) for making image plots registered with data plots. Default is to label the pixel centers with the zero-based row and column indices.
Additional kwargs are matplotlib.artist properties
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get_cursor_data(event)
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Get the cursor data for a given event
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get_extent()
[source] -
Get the image extent: left, right, bottom, top
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get_window_extent(renderer=None)
[source] -
Get the axes bounding box in display space. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0.
Be careful when using this function, the results will not update if the artist window extent of the artist changes. The extent can change due to any changes in the transform stack, such as changing the axes limits, the figure size, or the canvas used (as is done when saving a figure). This can lead to unexpected behavior where interactive figures will look fine on the screen, but will save incorrectly.
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make_image(renderer, magnification=1.0, unsampled=False)
[source]
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set_extent(extent)
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extent is data axes (left, right, bottom, top) for making image plots
This updates ax.dataLim, and, if autoscaling, sets viewLim to tightly fit the image, regardless of dataLim. Autoscaling state is not changed, so following this with ax.autoscale_view will redo the autoscaling in accord with dataLim.
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class matplotlib.image.BboxImage(bbox, cmap=None, norm=None, interpolation=None, origin=None, filternorm=1, filterrad=4.0, resample=False, interp_at_native=True, **kwargs)
[source] -
Bases:
matplotlib.image._ImageBase
The Image class whose size is determined by the given bbox.
cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1
interp_at_native is a flag that determines whether or not interpolation should still be applied when the image is displayed at its native resolution. A common use case for this is when displaying an image for annotational purposes; it is treated similarly to Photoshop (interpolation is only used when displaying the image at non-native resolutions).
kwargs are an optional list of Artist keyword args
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contains(mouseevent)
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Test whether the mouse event occurred within the image.
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get_window_extent(renderer=None)
[source] -
Get the axes bounding box in display space. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0.
Be careful when using this function, the results will not update if the artist window extent of the artist changes. The extent can change due to any changes in the transform stack, such as changing the axes limits, the figure size, or the canvas used (as is done when saving a figure). This can lead to unexpected behavior where interactive figures will look fine on the screen, but will save incorrectly.
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make_image(renderer, magnification=1.0, unsampled=False)
[source]
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class matplotlib.image.FigureImage(fig, cmap=None, norm=None, offsetx=0, offsety=0, origin=None, **kwargs)
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Bases:
matplotlib.image._ImageBase
cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1
kwargs are an optional list of Artist keyword args
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get_extent()
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Get the image extent: left, right, bottom, top
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make_image(renderer, magnification=1.0, unsampled=False)
[source]
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set_data(A)
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Set the image array.
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zorder = 0
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class matplotlib.image.NonUniformImage(ax, *, interpolation='nearest', **kwargs)
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Bases:
matplotlib.image.AxesImage
kwargs are identical to those for AxesImage, except that 'nearest' and 'bilinear' are the only supported 'interpolation' options.
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get_extent()
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Get the image extent: left, right, bottom, top
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make_image(renderer, magnification=1.0, unsampled=False)
[source]
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set_array(*args)
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Retained for backwards compatibility - use set_data instead.
Parameters: -
A : array-like
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set_cmap(cmap)
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set the colormap for luminance data
Parameters: -
cmap : colormap or registered colormap name
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set_data(x, y, A)
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Set the grid for the pixel centers, and the pixel values.
- x and y are monotonic 1-D ndarrays of lengths N and M,
- respectively, specifying pixel centers
- A is an (M,N) ndarray or masked array of values to be
- colormapped, or a (M,N,3) RGB array, or a (M,N,4) RGBA array.
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set_filternorm(s)
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Set whether the resize filter normalizes the weights.
See help for
imshow
.Parameters: -
filternorm : bool
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set_filterrad(s)
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Set the resize filter radius only applicable to some interpolation schemes -- see help for imshow
Parameters: -
filterrad : positive float
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set_interpolation(s)
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Parameters: -
s : str, None
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Either 'nearest', 'bilinear', or
None
.
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set_norm(norm)
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Set the normalization instance.
Parameters: -
norm : Normalize
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class matplotlib.image.PcolorImage(ax, x=None, y=None, A=None, cmap=None, norm=None, **kwargs)
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Bases:
matplotlib.image.AxesImage
Make a pcolor-style plot with an irregular rectangular grid.
This uses a variation of the original irregular image code, and it is used by pcolorfast for the corresponding grid type.
cmap defaults to its rc setting
cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1
Additional kwargs are matplotlib.artist properties
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get_cursor_data(event)
[source] -
Get the cursor data for a given event
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make_image(renderer, magnification=1.0, unsampled=False)
[source]
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set_array(*args)
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Retained for backwards compatibility - use set_data instead.
Parameters: -
A : array-like
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set_data(x, y, A)
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Set the grid for the rectangle boundaries, and the data values.
- x and y are monotonic 1-D ndarrays of lengths N+1 and M+1,
- respectively, specifying rectangle boundaries. If None, they will be created as uniform arrays from 0 through N and 0 through M, respectively.
- A is an (M,N) ndarray or masked array of values to be
- colormapped, or a (M,N,3) RGB array, or a (M,N,4) RGBA array.
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matplotlib.image.composite_images(images, renderer, magnification=1.0)
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Composite a number of RGBA images into one. The images are composited in the order in which they appear in the
images
list.Parameters: -
images : list of Images
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Each must have a
make_image
method. For each image,can_composite
should returnTrue
, though this is not enforced by this function. Each image must have a purely affine transformation with no shear. -
renderer : RendererBase instance
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magnification : float
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The additional magnification to apply for the renderer in use.
Returns: -
tuple : image, offset_x, offset_y
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Returns the tuple:
- image: A numpy array of the same type as the input images.
- offset_x, offset_y: The offset of the image (left, bottom) in the output figure.
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matplotlib.image.imread(fname, format=None)
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Read an image from a file into an array.
Parameters: -
fname : str or file-like
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The image file to read. This can be a filename, a URL or a Python file-like object opened in read-binary mode.
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format : str, optional
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The image file format assumed for reading the data. If not given, the format is deduced from the filename. If nothing can be deduced, PNG is tried.
Returns: -
imagedata : numpy.array
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The image data. The returned array has shape
- (M, N) for grayscale images.
- (M, N, 3) for RGB images.
- (M, N, 4) for RGBA images.
Notes
Matplotlib can only read PNGs natively. Further image formats are supported via the optional dependency on Pillow. Note, URL strings are not compatible with Pillow. Check the Pillow documentation for more information.
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matplotlib.image.imsave(fname, arr, vmin=None, vmax=None, cmap=None, format=None, origin=None, dpi=100)
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Save an array as in image file.
The output formats available depend on the backend being used.
Parameters: -
fname : str or file-like
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The filename or a Python file-like object to store the image in. The necessary output format is inferred from the filename extension but may be explicitly overwritten using format.
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arr : array-like
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The image data. The shape can be one of MxN (luminance), MxNx3 (RGB) or MxNx4 (RGBA).
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vmin, vmax : scalar, optional
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vmin and vmax set the color scaling for the image by fixing the values that map to the colormap color limits. If either vmin or vmax is None, that limit is determined from the arr min/max value.
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cmap : str or Colormap, optional
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A Colormap instance or registered colormap name. The colormap maps scalar data to colors. It is ignored for RGB(A) data. Defaults to
rcParams["image.cmap"]
('viridis'). -
format : str, optional
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The file format, e.g. 'png', 'pdf', 'svg', ... . If not given, the format is deduced form the filename extension in fname. See
Figure.savefig
for details. -
origin : {'upper', 'lower'}, optional
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Indicates whether the
(0, 0)
index of the array is in the upper left or lower left corner of the axes. Defaults torcParams["image.origin"]
('upper'). -
dpi : int
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The DPI to store in the metadata of the file. This does not affect the resolution of the output image.
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matplotlib.image.pil_to_array(pilImage)
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Load a PIL image and return it as a numpy array.
Returns: - numpy.array
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The array shape depends on the image type:
- (M, N) for grayscale images.
- (M, N, 3) for RGB images.
- (M, N, 4) for RGBA images.
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matplotlib.image.thumbnail(infile, thumbfile, scale=0.1, interpolation='bilinear', preview=False)
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Make a thumbnail of image in infile with output filename thumbfile.
See Image Thumbnail.
Parameters: -
infile : str or file-like
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The image file -- must be PNG, Pillow-readable if you have Pillow installed.
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thumbfile : str or file-like
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The thumbnail filename.
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scale : float, optional
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The scale factor for the thumbnail.
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interpolation : str, optional
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The interpolation scheme used in the resampling. See the interpolation parameter of
imshow
for possible values. -
preview : bool, optional
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If True, the default backend (presumably a user interface backend) will be used which will cause a figure to be raised if
show
is called. If it is False, the figure is created usingFigureCanvasBase
and the drawing backend is selected assavefig
would normally do.
Returns: -
figure : Figure
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The figure instance containing the thumbnail.
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© 2012–2018 Matplotlib Development Team. All rights reserved.
Licensed under the Matplotlib License Agreement.
https://matplotlib.org/3.0.0/api/image_api.html