import numpy

x = numpy.loadtxt('/mnt/saturate/ecoli_5m-report.txt')

plot(x[:,0], x[:,1])
xlabel('number of reads examined')
ylabel('number of reads retained')
title('Saturation of assembly graph/information in E. coli data set')

x = numpy.loadtxt('/mnt/cover1/reads.hist')

plot(x[:,0], x[:,1])
xlabel('read abundance')
ylabel('N reads with that abundance')
title('Coverage spectrum of artificial two-species metagenome')

x = numpy.loadtxt('/mnt/cover2/reads.hist')

plot(x[:,0], x[:,1])
axis(xmax=300)
xlabel('read abundance')
ylabel('N reads with that abundance')
title('Coverage spectrum of E. coli colony')

x = numpy.loadtxt('/mnt/error/ecoli_ref-5m.fastq.gz.errhist')

plot(x[:,0], x[:,2])
xlabel('position in read')
ylabel('number of errors at that position')
title('reference-free error profile for E. coli reads')

x = numpy.loadtxt('/mnt/kmercov/counts.out')

plot(x[:,0], x[:,1])
xlabel('k-mer abundance')
ylabel('number of k-mers with that abundance')
title('read-based abundance of k-mers that ended up in assembly')

x = numpy.loadtxt('/mnt/part/group0.hist')
y = numpy.loadtxt('/mnt/part/group1.hist')

plot(x[:, 0], x[:, 1], label='partition 0')
plot(y[:, 0], y[:, 1], label='partition 1')
axis(ymax=150)
legend()
xlabel('k-mer abundance')
ylabel('number of k-mers with that abundance')
title('partitions correlate with species abundance')