def main():
args = docopt(__doc__)
args = BtPlot.check_input(args)
blobdb_f = args['--infile']
cov_f = args['--cov']
rank = args['--rank']
min_length = int(args['--length'])
max_group_plot = int(args['--plotgroups'])
hide_nohits = args['--nohit']
taxrule = args['--taxrule']
c_index = args['--cindex']
exclude_groups = args['--exclude']
labels = args['--label']
colour_f = args['--colours']
refcov_f = args['--refcov']
catcolour_f = args['--catcolour']
sort_order = args['--sort']
sort_first = args['--sort_first']
multiplot = args['--multiplot']
out_prefix = args['--out']
sort_order = args['--sort']
hist_type = args['--hist']
no_title = args['--notitle']
ignore_contig_length = args['--noscale']
format_plot = args['--format']
no_plot_blobs = args['--noblobs']
#no_plot_reads = args['--noreads']
legend_flag = args['--legend']
cumulative_flag = args['--cumulative']
cov_lib_selection = args['--lib']
xlabel = args['--xlabel']
ylabel = args['--ylabel']
axis_max = float(args['--max'])
exclude_groups = BtIO.parseCmdlist(exclude_groups)
refcov_dict = BtIO.parseReferenceCov(refcov_f)
user_labels = BtIO.parseCmdLabels(labels)
catcolour_dict = BtIO.parseCatColour(catcolour_f)
colour_dict = BtIO.parseColours(colour_f)
# Load BlobDb
print(BtLog.status_d['9'] % blobdb_f)
blobDb = Bt.BlobDb('blobplot')
blobDb.version = interface.__version__
blobDb.load(blobdb_f)
# Generate plot data
print(BtLog.status_d['1'] % ('cov_y_axis', cov_f))
cov_y_dict, reads_total, reads_mapped, reads_unmapped, read_cov_dict = BtIO.parseCov(
cov_f, set(blobDb.dict_of_blobs))
print(BtLog.status_d['18'])
data_dict, min_cov, max_cov, cov_lib_dict = blobDb.getPlotData(
rank, min_length, hide_nohits, taxrule, c_index, catcolour_dict)
plotObj = BtPlot.PlotObj(data_dict, cov_lib_dict, cov_lib_selection,
'covplot', sort_first)
# set lowest coverage to 0.01
for contig in cov_y_dict:
if cov_y_dict[contig] < 0.1:
cov_y_dict[contig] = 0.1
plotObj.cov_y_dict = cov_y_dict
plotObj.exclude_groups = exclude_groups
plotObj.version = blobDb.version
plotObj.format = format_plot
plotObj.max_cov = axis_max
plotObj.no_title = no_title
plotObj.multiplot = multiplot
plotObj.hist_type = hist_type
plotObj.ignore_contig_length = ignore_contig_length
plotObj.max_group_plot = max_group_plot
plotObj.legend_flag = legend_flag
plotObj.cumulative_flag = cumulative_flag
# order by which to plot (should know about user label)
plotObj.group_order = BtPlot.getSortedGroups(data_dict, sort_order)
# labels for each level of stats
plotObj.labels.update(plotObj.group_order)
# plotObj.group_labels is dict that contains labels for each group : all/other/user_label
if (user_labels):
for group, label in user_labels.items():
plotObj.labels.add(label)
plotObj.group_labels = {group: set() for group in plotObj.group_order}
plotObj.relabel_and_colour(colour_dict, user_labels)
plotObj.compute_stats()
plotObj.refcov_dict = refcov_dict
# Plotting
info_flag = 1
out_f = ''
for cov_lib in plotObj.cov_libs:
plotObj.xlabel = basename(cov_lib_dict[cov_lib]['f'])
plotObj.ylabel = cov_f
if (ylabel):
plotObj.ylabel = ylabel
if (xlabel):
plotObj.xlabel = xlabel
out_f = "%s.%s.%s.p%s.%s.%s" % (blobDb.title, taxrule, rank,
max_group_plot, hist_type, min_length)
if catcolour_dict:
out_f = "%s.%s" % (out_f, "catcolour")
if ignore_contig_length:
out_f = "%s.%s" % (out_f, "noscale")
if c_index:
out_f = "%s.%s" % (out_f, "c_index")
if exclude_groups:
out_f = "%s.%s" % (out_f, "exclude_" + "_".join(exclude_groups))
if labels:
out_f = "%s.%s" % (out_f, "userlabel_" + "_".join(
set([name for name in user_labels.values()])))
out_f = "%s.%s" % (out_f, "covplot")
if (plotObj.cumulative_flag):
out_f = "%s.%s" % (out_f, "cumulative")
if (plotObj.multiplot):
out_f = "%s.%s" % (out_f, "multiplot")
out_f = BtIO.getOutFile(out_f, out_prefix, None)
if not (no_plot_blobs):
plotObj.plotScatter(cov_lib, info_flag, out_f)
info_flag = 0
plotObj.write_stats(out_f)
def parseCoverage(self, **kwargs):
# arguments
covLibObjs = kwargs['covLibObjs']
no_base_cov = kwargs['no_base_cov']
for covLib in covLibObjs:
self.addCovLib(covLib)
print BtLog.status_d['1'] % (covLib.name, covLib.f)
if covLib.fmt == 'bam' or covLib.fmt == 'sam':
base_cov_dict = {}
if covLib.fmt == 'bam':
base_cov_dict, covLib.reads_total, covLib.reads_mapped, read_cov_dict = BtIO.parseBam(
covLib.f, set(self.dict_of_blobs), no_base_cov)
else:
base_cov_dict, covLib.reads_total, covLib.reads_mapped, read_cov_dict = BtIO.parseSam(
covLib.f, set(self.dict_of_blobs), no_base_cov)
if covLib.reads_total == 0:
print BtLog.warn_d['4'] % covLib.f
for name, base_cov in base_cov_dict.items():
cov = base_cov / self.dict_of_blobs[name].agct_count
covLib.cov_sum += cov
self.dict_of_blobs[name].addCov(covLib.name, cov)
self.dict_of_blobs[name].addReadCov(
covLib.name, read_cov_dict[name])
# Create COV file for future use
out_f = BtIO.getOutFile(covLib.f, kwargs.get('prefix', None),
None)
covView = ViewObj(name="covlib",
out_f=out_f,
suffix="cov",
header="",
body=[])
self.view(viewObjs=[covView],
ranks=None,
taxrule=None,
hits_flag=None,
seqs=None,
cov_libs=[covLib.name],
progressbar=False)
elif covLib.fmt == 'cas':
cov_dict, covLib.reads_total, covLib.reads_mapped, read_cov_dict = BtIO.parseCas(
covLib.f, self.order_of_blobs)
if covLib.reads_total == 0:
print BtLog.warn_d['4'] % covLib.f
for name, cov in cov_dict.items():
covLib.cov_sum += cov
self.dict_of_blobs[name].addCov(covLib.name, cov)
self.dict_of_blobs[name].addReadCov(
covLib.name, read_cov_dict[name])
out_f = BtIO.getOutFile(covLib.f, kwargs.get('prefix', None),
None)
covView = ViewObj(name="covlib",
out_f=out_f,
suffix="cov",
header="",
body=[])
self.view(viewObjs=[covView],
ranks=None,
taxrule=None,
hits_flag=None,
seqs=None,
cov_libs=[covLib.name],
progressbar=False)
elif covLib.fmt == 'cov':
base_cov_dict, covLib.reads_total, covLib.reads_mapped, covLib.reads_unmapped, read_cov_dict = BtIO.parseCov(
covLib.f, set(self.dict_of_blobs))
#cov_dict = BtIO.readCov(covLib.f, set(self.dict_of_blobs))
if not len(base_cov_dict) == self.seqs:
print BtLog.warn_d['4'] % covLib.f
for name, cov in base_cov_dict.items():
covLib.cov_sum += cov
self.dict_of_blobs[name].addCov(covLib.name, cov)
if name in read_cov_dict:
self.dict_of_blobs[name].addReadCov(
covLib.name, read_cov_dict[name])
else:
pass
covLib.mean_cov = covLib.cov_sum / self.seqs
if covLib.cov_sum == 0.0:
print BtLog.warn_d['6'] % (covLib.name)
self.covLibs[covLib.name] = covLib
