Multivariate Pattern Analysis in Python

# mvpa2.misc.plot.scatter.plot_scatter

`mvpa2.misc.plot.scatter.``plot_scatter`(dataXd, mask=None, masked_opacity=0.0, labels=None, colors=True, dimcolor=1, title=None, limits='auto', thresholds=None, hint_opacity=0.9, x_jitter=None, y_jitter=None, fig=None, ax_scatter=None, ax_hist_x=None, ax_hist_y=None, bp_location='scatter', xlim=None, ylim=None, rasterized=None, uniq=False, include_stats=False)

  Parameters:

  dataXd: array

  > The volumetric (or not) data to plot where first dimension should only have 2 items

  mask: array, optional

  > Additional mask to specify which values do not consider to plot. By default values with 0s in both dimensions are not plotted.

  masked_opacity: float, optional

  > By default masked out values are not plotted at all. Value in (0,1] will make them visible with this specified opacity

  labels: list of str, optional

  > Labels to place for x and y axes

  colors: bool or string or colormap, optional

  > Either to use colors to associate with physical location and what colormap to use (jet by default if colors=True)

  dimcolor: int

  > If `colors`, then which dimension (within given 3D volume) to “track”

  limits: ‘auto’, ‘same’, ‘per-axis’ or (min, max)

  > Limits for axes: when ‘auto’ if data ranges overlap is more than 50% of the union range, ‘same’ is considered. When ‘same’ – the same limits on both axes as determined by data. If two-element tuple or list is provided, then that range is applied to both axes.

  hint_opacity: float, optional

  > If `colors` is True, to then a “slice” of the volumetric data is plotted in the specified opacity to hint about the location of points in the original Xd data in `dimcolor` dimension

  x_jitter: float, optional

  > Half-width of uniform noise added to x values. Might be useful if data is quantized so it is valuable to jitter points a bit.

  y_jitter: float, optional

  > Half-width of uniform noise added to y values. Might be useful if data is quantized so it is valuable to jitter points a bit

  fig : Figure, optional

  > Figure to plot on, otherwise new one created

  ax_*: axes, optional

  > Axes for the scatter plot and histograms. If none of them is specified (which is the default) then ‘classical’ plot is rendered with histograms above and to the right

  bp_location: (‘scatter’, ‘hist’, None), optional

  > Where to place boxplots depicting data range

  xlim: tuple, optional

  ylim: tuple, optional

  > To fix plotted range

  rasterized: bool, optional

  > Passed to scatter call, to allow rasterization of heavy scatter plots

  uniq: bool, optional

  > Plot uniq values (those present in one but not in the other) along each axis with crosses

  include_stats: bool, optional

  > Whether to report additional statistics on the data. Stats are also reported via verbose at level 2