outfiles_list = []
for d in batch_parameters:
dirname = c.experiment_name + '_clustered_reads'
outfile = c.experiment_name + '_clustered_reads'
if 'c_thresh' in d:
dirname = dirname + '-c{}'.format(int(d['c_thresh']*100))
outfile = outfile + '-c{}'.format(int(d['c_thresh']*100))
if 'n_filter' in d:
dirname = dirname + '-n{}'.format(d['n_filter'])
outfile = outfile + '-n{}'.format(d['n_filter'])
if 'maskN' in d:
dirname = dirname + '-maskN'
outfile = outfile + '-maskN'
path = os.path.join(c.clusters_outpath, dirname)
outfiles_list.append(os.path.join(path, outfile))
for cluster_file in outfiles_list:
name = os.path.split(cluster_file)[1]
out6 = cluster_summary_plot(cluster_file, plot_hist = 0)
hist_counter(out6[1], bins=5000, range =(1,10000),label=name)
''' Created on 28 Feb 2013 @author: musselle ''' import os import sys import numpy as np from plot_utils import cluster_summary_plot, hist_counter infileL6 = '/space/musselle/datasets/gazelles-zebras/clusters/L6clustered_reads' infileL8 = '/space/musselle/datasets/gazelles-zebras/clusters/L8clustered_reads' outL6 = cluster_summary_plot(infileL6, plot_hist = 0) outL8 = cluster_summary_plot(infileL8, plot_hist = 0) hist_counter(outL6[1], bins=5000, range =(1,10000),label='Lane 6') hist_counter(outL8[1], bins=5000, range =(1,10000),label='Lane 8')
