PlotAxes.imshow

PlotAxes.imshow(z, **kwargs)[source]

Plot an image.

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 or DataArray). If passed, positional arguments can optionally be string data keys and the arrays used for plotting are retrieved with data[key]. This is a native matplotlib feature.

  • autoformat (bool, optional) – Whether the x axis labels, y axis labels, axis formatters, axes titles, legend titles, and colorbar labels are automatically configured when a Series, DataFrame, DataArray, or Quantity is passed to the plotting command. Default is rc.autoformat = True.

Other Parameters
  • cmap (colormap spec, optional) – The colormap specifer, passed to the Colormap constructor function.

  • cmap_kw (dict-like, optional) – Passed to Colormap.

  • norm (normalizer spec, optional) – The continuous colormap normalizer, passed to the Norm constructor function. If discrete is True this is also used to normalize values passed to DiscreteNorm before colors is selected.

  • norm_kw (dict-like, optional) – Passed to Norm.

  • discrete (bool, optional) – If False, then DiscreteNorm is not applied to the colormap. Instead, for non-contour plots, the number of levels will be roughly controlled by rc['cmap.lut']. This has a similar effect to using levels=large_number but it may improve rendering speed. Default is False for imshow, matshow, spy, hexbin, hist2d, and heatmap plots, but True otherwise.

  • sequential (bool, optional) – Use rc['cmap.sequential'] = 'fire' as the default colormap.

  • diverging (bool, optional) – Use rc['cmap.diverging'] = 'negpos' as the default colormap and use DivergingNorm as the default continuous normalizer. This will also ensure auto-generated levels include a value at zero.

  • cyclic (bool, optional) – Use rc['cmap.cyclic'] = 'twilight' as the default colormap and modify the default arguments passed to DiscreteNorm so that colors on either end are distinct.

  • sequential, diverging, cyclic, qualitative (bool, optional) – Boolean arguments used if cmap is not passed. Set these to True to use the default rc['cmap.sequential'], rc['cmap.diverging'], rc['cmap.cyclic'], and rc['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 or list of float, 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 with pcolor plots, not contour plots). Default is rc['cmap.levels'] = 11.

  • values (int or list of float, 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 using edges. This will override any levels input.

  • vmin, vmax (float, optional) – Used to determine level locations if levels or values is an integer. Actual levels may not fall exactly on vmin and vmax, but the minimum level will be no smaller than vmin and the maximum level will be no larger than vmax. If vmin or vmax are not provided, the minimum and maximum data values are used.

  • robust (bool, float, or 2-tuple, optional) – If True and vmin or vmax 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 is rc['cmap.robust'] = False.

  • inbounds (bool, optional) – If True and vmin or vmax were not provided, when axis limits have been explicitly restricted with set_xlim or set_ylim, out-of-bounds data is ignored. Default is rc['cmap.inbounds'] = True. See also rc['axes.inbounds'].

  • locator (locator-spec, optional) – The locator used to determine level locations if levels or values is an integer. Passed to the Locator constructor. Default is MaxNLocator with levels integer levels.

  • locator_kw (dict-like, optional) – Passed to Locator.

  • symmetric (bool, optional) – If True, automatically generated levels are symmetric about zero. Default is always False.

  • positive (bool, optional) – If True, automatically generated levels are positive with a minimum at zero. Default is always False.

  • negative (bool, optional) – If True, automatically generated levels are negative with a maximum at zero. Default is always False.

  • nozero (bool, optional) – If True, 0 is removed from the level list. This is mainly useful for single-color contour plots.

  • colorbar (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel colorbar from the resulting object(s). If True, the default rc['colorbar.loc'] = 'right' is used. Valid locations are described in colorbar.

  • colorbar_kw (dict-like, optional) – Extra keyword args for the call to colorbar.

  • legend (bool, int, or str, optional) – If not None, this is a location specifying where to draw an inset or panel legend from the resulting object(s). If True, the default rc['legend.loc'] = 'best' is used. Valid locations are described in legend.

  • legend_kw (dict-like, optional) – Extra keyword args for the call to legend.

  • **kwargs – Passed to matplotlib.axes.Axes.imshow.