matplotlib.axes.Axes.imshow

Axes.imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=None, filternorm=1, filterrad=4.0, imlim=None, resample=None, url=None, *, data=None, **kwargs)

Display an image on the axes.

Parameters:	X : array_like, shape (n, m) or (n, m, 3) or (n, m, 4) Display the image in X to current axes. X may be an array or a PIL image. If X is an array, it can have the following shapes and types: MxN – values to be mapped (float or int) MxNx3 – RGB (float or uint8) MxNx4 – RGBA (float or uint8) The value for each component of MxNx3 and MxNx4 float arrays should be in the range 0.0 to 1.0. MxN arrays are mapped to colors based on the norm (mapping scalar to scalar) and the cmap (mapping the normed scalar to a color). cmap : Colormap, optional, default: None If None, default to rc image.cmap value. cmap is ignored if X is 3-D, directly specifying RGB(A) values. aspect : [‘auto’ | ‘equal’ | scalar], optional, default: None If ‘auto’, changes the image aspect ratio to match that of the axes. If ‘equal’, and extent is None, changes the axes aspect ratio to match that of the image. If extent is not None, the axes aspect ratio is changed to match that of the extent. If None, default to rc image.aspect value. interpolation : string, optional, default: None Acceptable values are ‘none’, ‘nearest’, ‘bilinear’, ‘bicubic’, ‘spline16’, ‘spline36’, ‘hanning’, ‘hamming’, ‘hermite’, ‘kaiser’, ‘quadric’, ‘catrom’, ‘gaussian’, ‘bessel’, ‘mitchell’, ‘sinc’, ‘lanczos’ If interpolation is None, default to rc image.interpolation. See also the filternorm and filterrad parameters. If interpolation is ‘none’, then no interpolation is performed on the Agg, ps and pdf backends. Other backends will fall back to ‘nearest’. norm : Normalize, optional, default: None A Normalize instance is used to scale a 2-D float X input to the (0, 1) range for input to the cmap. If norm is None, use the default func:normalize. If norm is an instance of NoNorm, X must be an array of integers that index directly into the lookup table of the cmap. vmin, vmax : scalar, optional, default: None vmin and vmax are used in conjunction with norm to normalize luminance data. Note if you pass a norm instance, your settings for vmin and vmax will be ignored. alpha : scalar, optional, default: None The alpha blending value, between 0 (transparent) and 1 (opaque) origin : [‘upper’ | ‘lower’], optional, default: None Place the [0,0] index of the array in the upper left or lower left corner of the axes. If None, default to rc image.origin. extent : scalars (left, right, bottom, top), optional, default: None The location, in data-coordinates, of the lower-left and upper-right corners. If None, the image is positioned such that the pixel centers fall on zero-based (row, column) indices. shape : scalars (columns, rows), optional, default: None For raw buffer images filternorm : scalar, optional, default: 1 A parameter for the antigrain image resize filter. From the antigrain documentation, if filternorm = 1, the filter normalizes integer values and corrects the rounding errors. It doesn’t do anything with the source floating point values, it corrects only integers according to the rule of 1.0 which means that any sum of pixel weights must be equal to 1.0. So, the filter function must produce a graph of the proper shape. filterrad : scalar, optional, default: 4.0 The filter radius for filters that have a radius parameter, i.e. when interpolation is one of: ‘sinc’, ‘lanczos’ or ‘blackman’
Returns:	image : AxesImage
Other Parameters:
	**kwargs : Artist properties.

See also

matshow

Plot a matrix or an array as an image.

Notes

Unless extent is used, pixel centers will be located at integer coordinates. In other words: the origin will coincide with the center of pixel (0, 0).

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All positional and all keyword arguments.