# pybedtools.contrib.plotting.binary_heatmap

`pybedtools.contrib.plotting.``binary_heatmap`(bts, names, plot=True, cluster=True)

  Plots a “binary heatmap”, showing the results of a multi-intersection.

  Each row is a different genomic region found in at least one of the input BedTools; each column represents a different file. Black indicates whether a feature was found at that particular site. Rows with black all the way across indicates that all features were colocalized at those sites.

  `bts` is an iterable of BedTool objects or filenames; `names` is a list of labels to use in the plot and is exactly the same length as `bts`.

  If `plot=True`, then plot the sorted, labeled matrix with matplotlib.

  Returns (summary, m) where `summary` is a dictionary summarizing the results and `m` is the sorted NumPy array. See source for further details.