Axes.spy(self, Z, precision=0, marker=None, markersize=None, aspect='equal', origin='upper', **kwargs)[source]

Plot the sparsity pattern of a 2D array.

This visualizes the non-zero values of the array.

Two plotting styles are available: image and marker. Both are available for full arrays, but only the marker style works for scipy.sparse.spmatrix instances.

Image style

If marker and markersize are None, imshow is used. Any extra remaining keyword arguments are passed to this method.

Marker style

If Z is a scipy.sparse.spmatrix or marker or markersize are None, a Line2D object will be returned with the value of marker determining the marker type, and any remaining keyword arguments passed to plot.

Z(M, N) array-like

The array to be plotted.

precisionfloat or 'present', default: 0

If precision is 0, any non-zero value will be plotted. Otherwise, values of \(|Z| > precision\) will be plotted.

For scipy.sparse.spmatrix instances, you can also pass 'present'. In this case any value present in the array will be plotted, even if it is identically zero.

aspect{'equal', 'auto', None} or float, default: 'equal'

The aspect ratio of the Axes. This parameter is particularly relevant for images since it determines whether data pixels are square.

This parameter is a shortcut for explicitly calling Axes.set_aspect. See there for further details.

  • 'equal': Ensures an aspect ratio of 1. Pixels will be square.
  • 'auto': The Axes is kept fixed and the aspect is adjusted so that the data fit in the Axes. In general, this will result in non-square pixels.
  • None: Use rcParams["image.aspect"] (default: 'equal').
origin{'upper', 'lower'}, default: rcParams["image.origin"] (default: 'upper')

Place the [0, 0] index of the array in the upper left or lower left corner of the Axes. The convention 'upper' is typically used for matrices and images.

AxesImage or Line2D

The return type depends on the plotting style (see above).

Other Parameters:

The supported additional parameters depend on the plotting style.

For the image style, you can pass the following additional parameters of imshow:

For the marker style, you can pass any Line2D property except for linestyle:

Property Description
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha scalar or None
animated bool
antialiased or aa bool
clip_box Bbox
clip_on bool
clip_path Patch or (Path, Transform) or None
color or c color
contains unknown
dash_capstyle CapStyle or {'butt', 'projecting', 'round'}
dash_joinstyle JoinStyle or {'miter', 'round', 'bevel'}
dashes sequence of floats (on/off ink in points) or (None, None)
data (2, N) array or two 1D arrays
drawstyle or ds {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default'
figure Figure
fillstyle {'full', 'left', 'right', 'bottom', 'top', 'none'}
gid str
in_layout bool
label object
linestyle or ls {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
linewidth or lw float
marker marker style string, Path or MarkerStyle
markeredgecolor or mec color
markeredgewidth or mew float
markerfacecolor or mfc color
markerfacecoloralt or mfcalt color
markersize or ms float
markevery None or int or (int, int) or slice or list[int] or float or (float, float) or list[bool]
path_effects AbstractPathEffect
picker float or callable[[Artist, Event], tuple[bool, dict]]
pickradius float
rasterized bool
sketch_params (scale: float, length: float, randomness: float)
snap bool or None
solid_capstyle CapStyle or {'butt', 'projecting', 'round'}
solid_joinstyle JoinStyle or {'miter', 'round', 'bevel'}
transform matplotlib.transforms.Transform
url str
visible bool
xdata 1D array
ydata 1D array
zorder float

Examples using matplotlib.axes.Axes.spy