healpy.projaxes.HpxCartesianAxes.imshow¶

HpxCartesianAxes.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, **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 a float array, a uint8 array or a PIL image. If X is an array, it can have the following shapes:

MxN – luminance (grayscale, float array only)

MxNx3 – RGB (float or uint8 array)

MxNx4 – RGBA (float or uint8 array)

The value for each component of MxNx3 and MxNx4 float arrays should be in the range 0.0 to 1.0; MxN float arrays may be normalised.

cmap : ~matplotlib.colors.Colormap, optional, default: None

If None, default to rc image.cmap value. cmap is ignored when X has RGB(A) information

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 : ~matplotlib.colors.Normalize, optional, default: None

A ~matplotlib.colors.Normalize instance is used to scale luminance data to 0, 1. If None, use the default func:normalize. norm is only used if X is an array of floats.

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

Data limits for the axes. The default assigns zero-based row, column indices to the x, y centers of the pixels.

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 : ~matplotlib.image.AxesImage

Other Parameters:

kwargs : ~matplotlib.artist.Artist properties.