Commit 0372a1b8 authored by Blaise Li's avatar Blaise Li
Browse files

Skipping size factor graph for small data.

parent 49776bd1
......@@ -1617,7 +1617,8 @@ rule test_size_factor:
# The filter amounts to counts_data.mean(axis=1) > 4
#np.log10(counts_data[counts_data.sum(axis=1) > 4 * len(counts_data.columns)] + 1).plot.kde()
#np.log10(counts_data[counts_data.prod(axis=1) > 0]).plot.kde()
assert len(counts_data) > 1, "Counts data with only one row cannot have its distribution estimated using KDE."
# assert len(counts_data) > 1, "Counts data with only one row cannot have its distribution estimated using KDE."
if len(counts_data) > 1:
pp = PdfPages(output.norm_counts_distrib_plot)
for normalizer in params.size_factor_types:
if normalizer == "median_ratio_to_pseudo_ref":
......@@ -1677,6 +1678,9 @@ rule test_size_factor:
# "The data matrix has %d lines and %d columns.\n" % (len(data), len(data.columns))])
# warnings.warn(msg + "\nSkipping %s_%s" % (wildcards.orientation, wildcards.biotype))
pp.close()
else:
# Make the file empty
open(output.norm_counts_distrib_plot, "w").close()
# TODO: Deal with 0-counts cases:
......
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