PlotAxes.spy¶
- PlotAxes.spy(z, **kwargs)[source]¶
Plot a sparcity pattern.
- Parameters
z (array-like) – The data passed as a positional argument or keyword argument.
data (dict-like, optional) – A dict-like dataset container (e.g.,
DataFrame
orDataArray
). If passed, positional arguments can optionally be validdata
keys and the arrays used for plotting are retrieved withdata[key]
. This is a native matplotlib feature.autoformat (
bool
, optional) – Whether thex
axis labels,y
axis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when aSeries
,DataFrame
,DataArray
, orQuantity
is passed to the plotting command. Default isrc.autoformat
=True
.
- Other Parameters
cmap (
colormap spec
, optional) – The colormap specifer, passed to theColormap
constructor function.norm (
normalizer spec
, optional) – The continuous colormap normalizer, passed to theNorm
constructor function. Ifdiscrete
isTrue
this is also used to normalize values passed toDiscreteNorm
before colors is selected.discrete (
bool
, optional) – IfFalse
, thenDiscreteNorm
is not applied to the colormap. Instead, for non-contour plots, the number of levels will be roughly controlled byrc['cmap.lut']
. This has a similar effect to usinglevels=large_number
but it may improve rendering speed. Default isFalse
forimshow
,matshow
,spy
,hexbin
,hist2d
, andheatmap
plots, butTrue
otherwise.sequential (
bool
, optional) – Userc['cmap.sequential']
='fire'
as the default colormap.diverging (
bool
, optional) – Userc['cmap.diverging']
='negpos'
as the default colormap and useDivergingNorm
as the default continuous normalizer. This will also ensure auto-generated levels include a value at zero.cyclic (
bool
, optional) – Userc['cmap.cyclic']
='twilight'
as the default colormap and modify the default arguments passed toDiscreteNorm
so that colors on either end are distinct.sequential, diverging, cyclic, qualitative (
bool
, optional) – Boolean arguments used ifcmap
is not passed. Set these toTrue
to use the defaultrc['cmap.sequential']
,rc['cmap.diverging']
,rc['cmap.cyclic']
, andrc['cmap.qualitative']
colormaps. The latter three options also change level- and norm-generation behavior.extend (
{{'neither', 'min', 'max', 'both'}}
, optional) – Whether to assign unique colors to out-of-bounds data and draw colorbar “extensions” when a colorbar is drawn.N – Shorthand for
levels
.levels (
int
orlist
offloat
, optional) – The number of level edges or a list of level edges. If the former,locator
is used to generate this many level edges at “nice” intervals. If the latter, the levels should be monotonically increasing or decreasing (note that decreasing levels will only work withpcolor
plots, notcontour
plots). Default isrc['cmap.levels']
=11
.values (
int
orlist
offloat
, optional) – The number of level centers or a list of level centers. If the former,locator
is used to generate this many level centers at “nice” intervals. If the latter, levels are inferred usingedges
. This will override anylevels
input.vmin, vmax (
float
, optional) – Used to determine level locations iflevels
orvalues
is an integer. Actual levels may not fall exactly onvmin
andvmax
, but the minimum level will be no smaller thanvmin
and the maximum level will be no larger thanvmax
. Ifvmin
orvmax
are not provided, the minimum and maximum data values are used.robust (
bool
,float
, or2-tuple
, optional) – IfTrue
andvmin
orvmax
were not provided, they are determined from the 2nd and 98th data percentiles rather than the minimum and maximum. If float, this percentile range is used (for example,90
corresponds to the 5th to 95th percentiles). If 2-tuple of float, these specific percentiles should be used. This feature is useful when your data has large outliers. Default isrc['cmap.robust']
=False
.inbounds (
bool
, optional) – IfTrue
andvmin
orvmax
were not provided, when axis limits have been explicitly restricted withset_xlim
orset_ylim
, out-of-bounds data is ignored. Default isrc['cmap.inbounds']
=True
. See alsorc['axes.inbounds']
.locator (
locator-spec
, optional) – The locator used to determine level locations iflevels
orvalues
is an integer. Passed to theLocator
constructor. Default isMaxNLocator
withlevels
integer levels.symmetric (
bool
, optional) – IfTrue
, automatically generated levels are symmetric about zero. Default is alwaysFalse
.positive (
bool
, optional) – IfTrue
, automatically generated levels are positive with a minimum at zero. Default is alwaysFalse
.negative (
bool
, optional) – IfTrue
, automatically generated levels are negative with a maximum at zero. Default is alwaysFalse
.nozero (
bool
, optional) – IfTrue
,0
is removed from the level list. This is mainly useful for single-colorcontour
plots.colorbar (
bool
,int
, orstr
, optional) – If notNone
, this is a location specifying where to draw an inset or panel colorbar from the resulting object(s). IfTrue
, the default location is used. Valid locations are described incolorbar
.colorbar_kw (dict-like, optional) – Ignored if
colorbar
isNone
. Extra keyword args for the call tocolorbar
.legend (
bool
,int
, orstr
, optional) – If notNone
, this is a location specifying where to draw an inset or panel legend from the resulting object(s). IfTrue
, the default location is used. Valid locations are described inlegend
.legend_kw (dict-like, optional) – Ignored if
legend
isNone
. Extra keyword args for the call tolegend
.**kwargs – Passed to
matplotlib.axes.Axes.spy
.