Multivariate Pattern Analysis in Python

# mvpa2.misc.plot.scatter.plot_scatter_files

`mvpa2.misc.plot.scatter.``plot_scatter_files`(files, mask_file=None, masked_opacity=0.0, mask_thresholds=None, volume=None, scales=None, return_data=False, thresholds=None, style='auto', **kwargs)

  Plot scatter plots based on data from files.

  Should work with volumetric file formats supported by nibabel and also .hdf5 files from PyMVPA

  Parameters:

  files: iterable of strings

  > Files to load

  mask_file: string, optional

  > Mask file. 0-ed out elements considered to be masked out

  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

  mask_thresholds: int or list or tuple, optional

  > A single (min) or two (lower, upper) values to decide which values to mask out (exclude). If lower < upper, excludes range [lower, upper]. if upper < lower, plots only values within [lower, upper] range.

  volume: int, None

  > If multi-volume files provided, which volume to consider. Otherwise will plot for points from all volumes

  scales: iterable of floats, optional

  > Scaling factors for the volumes

  return_data: bool, optional

  > Flag to return loaded data as the output of this function call

  style: str, (‘auto’, ‘full’, ‘pair1’, ‘upper_triang’)

  > Style of plotting – full and upper_triang are the scatter matrix plots. With ‘auto’ chooses pair1 for 2 files, and full if more than 2 provided