def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
mm9_methods = {
'0 pseudo-counts':'%s/Analysis/hifive_mm9_ESC_bin_correlations.txt' % basedir,
'1 pseudo-count':'%s/Analysis/hifive_mm9_ESC_binPC1_correlations.txt' % basedir,
'3 pseudo-counts':'%s/Analysis/hifive_mm9_ESC_binPC3_correlations.txt' % basedir,
'6 pseudo-counts':'%s/Analysis/hifive_mm9_ESC_binPC6_correlations.txt' % basedir,
'HiCPipe':'%s/Analysis/hicpipe_mm9_ESC_correlations.txt' % basedir,
}
mm9_data = load_data(mm9_methods)
width = 16.8
spacer = 0.4
overall_width = (width - spacer * 2) / 2.6
c = canvas.canvas()
prob_ranges_img, prob_ranges_height = plot_dataset_ranges(mm9_data, width)
prob_ranges_img.text(0, prob_ranges_height, 'a',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(prob_ranges_img)
overall_height = prob_ranges_height * 0.6
hifive_overall_img = plot_overall(mm9_data, overall_width, overall_height, 'cis')
hifive_overall_img.text(0, overall_height + 0.1, 'b',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(hifive_overall_img, [trafo.translate(0, -overall_height - spacer)])
hifive_overall_img = plot_overall(mm9_data, overall_width, overall_height, 'trans')
hifive_overall_img.text(0, overall_height + 0.1, 'c',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(hifive_overall_img,
[trafo.translate(width - overall_width, -overall_height - spacer)])
c.insert(plot_key(overall_width * 0.6 + 0.4, overall_height, mm9_data),
[trafo.translate(overall_width + spacer + 0.6, -overall_height - spacer)])
c.writePDFfile(out_fname)
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
mm9_methods = {
'HiFive-Probability':'%s/Analysis/hifive_mm9_ESC_prob_correlations.txt' % basedir,
'HiFive-Express':'%s/Analysis/hifive_mm9_ESC_exp_correlations.txt' % basedir,
'HiFive-Binning':'%s/Analysis/hifive_mm9_ESC_bin_correlations.txt' % basedir,
}
dist_methods = {
'HiFive-Probability':'%s/Analysis/hifive_mm9_ESC_probnodist_correlations.txt' % basedir,
'HiFive-Express':'%s/Analysis/hifive_mm9_ESC_expnodist_correlations.txt' % basedir,
'HiFive-Binning':'%s/Analysis/hifive_mm9_ESC_binnodist_correlations.txt' % basedir,
}
mm9_data = load_data(mm9_methods)
dist_data = load_data(dist_methods)
width = 16.8
spacer = 0.4
range_width = (width - spacer) / 3.0
c = canvas.canvas()
mm9_ranges_img = plot_dataset_ranges(mm9_data, dist_data, range_width)
c.insert(mm9_ranges_img)
mm9_overall_img = plot_overall(mm9_data, dist_data, range_width, range_width)
mm9_overall_img.text(0, range_width, 'b',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(mm9_overall_img, [trafo.translate(range_width * 2 + spacer, range_width)])
c.insert(plot_key(range_width / 2, range_width / 2),
[trafo.translate(range_width * 2.25 + spacer, range_width * 0.25)])
c.writePDFfile(out_fname)
def makebinaries(number, y0):
size = 0.4
dist = 0.1
for n in range(32):
c.stroke(path.rect(n*size+(n/8)*dist, y0, size, size))
c.text((n+0.5)*size+(n/8)*dist, y0+0.07,
r"\sffamily %i" % ((number >> 31-n) & 1),
[text.halign.center])
if number >> 31:
c.text(32.2*size+5*dist, y0+0.07,
r"\sffamily = -%i" % ((number ^ 0xffffffff)+1))
else:
c.text(32.2*size+5*dist, y0+0.07, r"\sffamily = %i" % number)
p = path.path(path.moveto(0.2*size, size+0.03),
path.lineto(0.2*size, size+0.07),
path.lineto(3.8*size, size+0.07),
path.lineto(3.8*size, size+0.03))
for n in range(4):
c.stroke(p, [trafo.translate(n*(8*size+dist), y0)])
c.text(n*(8*size+dist)+2*size, size+0.14+y0,
r"\sffamily %X" % ((number >> ((3-n)*8+4)) & 15),
[text.halign.center])
c.stroke(p, [trafo.translate(n*(8*size+dist)+4*size, y0)])
c.text(n*(8*size+dist)+6*size, size+0.14+y0,
r"\sffamily %X" % ((number >> ((3-n)*8)) & 15),
[text.halign.center])
def main():
width = 16.8
out_fname = sys.argv[1]
basedir = "%s/Analysis/Timing" % '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
data_fnames = {
"HiFive-Probability":{'0':"%s/hifive_data" % basedir, '1':"%s/hifive_project" % basedir,
'3':'%s/hifive_prob' % basedir, '4':"%s/hifive_prob_heatmap" % basedir},
"HiFive-Binning":{'0':"%s/hifive_data" % basedir, '1':"%s/hifive_project_nodist" % basedir,
'3':'%s/hifive_bin' % basedir, '4':"%s/hifive_bin_heatmap" % basedir},
"HiFive-Express":{'0':"%s/hifive_data" % basedir, '1':"%s/hifive_project" % basedir,
'3':'%s/hifive_exp' % basedir, '4':"%s/hifive_exp_heatmap" % basedir},
"HiFive-ExpressKR":{'0':"%s/hifive_data" % basedir, '1':"%s/hifive_project_nodist" % basedir,
'3':'%s/hifive_expKR' % basedir, '4':"%s/hifive_expKR_heatmap" % basedir},
"HiFive-ExpressKR w/distance":{'0':"%s/hifive_data" % basedir, '1':"%s/hifive_project" % basedir,
'3':'%s/hifive_expKRdist' % basedir, '4':"%s/hifive_expKRdist_heatmap" % basedir},
"HiCPipe":{'0':"%s/bam2raw" % basedir, '1':"%s/hicpipe_data" % basedir,
'2':'%s/hicpipe_binning' % basedir, '3':'%s/hicpipe_norm' % basedir,
'4':'%s/hicpipe_heatmap' % basedir},
"HiCLib":{'0':"%s/hiclib_mapping" % basedir, '1':'%s/hiclib_data' % basedir,
'3':"%s/hiclib_norm" % basedir, '4':'%s/hiclib_heatmap' % basedir},
"HiCNorm":{'0':"%s/bam2raw" % basedir, '1':"%s/hicpipe_data" % basedir,
"2":"%s/hicnorm_data" % basedir, '3':'%s/hicnorm_norm' % basedir},
}
data = load_data(data_fnames)
c = canvas.canvas()
c.insert(plot_bargraph(data, width, 4.0), [trafo.translate(4.0, 0)])
c.insert(plot_key(width * 0.3, 1.5), [trafo.translate(width * 0.75 - 1.0, 0.2)])
c.writePDFfile(out_fname)
def paint(self, canvas, data, axis, axispos):
if self.breaklinesattrs is not None:
breaklinesdist_pt = unit.topt(self.breaklinesdist)
breaklineslength_pt = unit.topt(self.breaklineslength)
breaklinesextent_pt = (0.5*breaklinesdist_pt*math.fabs(self.cos) +
0.5*breaklineslength_pt*math.fabs(self.sin))
if canvas.extent_pt < breaklinesextent_pt:
canvas.extent_pt = breaklinesextent_pt
for v in [data.subaxes[name].vminover for name in data.names[1:]]:
# use a tangent of the basepath (this is independent of the tickdirection)
p = axispos.vbasepath(v, None).normpath()
breakline = p.tangent(0, length=self.breaklineslength)
widthline = p.tangent(0, length=self.breaklinesdist).transformed(trafomodule.rotate(self.breaklinesangle+90, *breakline.atbegin()))
# XXX Uiiii
tocenter = map(lambda x: 0.5*(x[0]-x[1]), zip(breakline.atbegin(), breakline.atend()))
towidth = map(lambda x: 0.5*(x[0]-x[1]), zip(widthline.atbegin(), widthline.atend()))
breakline = breakline.transformed(trafomodule.translate(*tocenter).rotated(self.breaklinesangle, *breakline.atbegin()))
breakline1 = breakline.transformed(trafomodule.translate(*towidth))
breakline2 = breakline.transformed(trafomodule.translate(-towidth[0], -towidth[1]))
canvas.layer("baseline").fill(path.path(path.moveto_pt(*breakline1.atbegin_pt()),
path.lineto_pt(*breakline1.atend_pt()),
path.lineto_pt(*breakline2.atend_pt()),
path.lineto_pt(*breakline2.atbegin_pt()),
path.closepath()), [color.gray.white])
canvas.layer("baseline").stroke(breakline1, self.defaultbreaklinesattrs + self.breaklinesattrs)
canvas.layer("baseline").stroke(breakline2, self.defaultbreaklinesattrs + self.breaklinesattrs)
_title.paint(self, canvas, data, axis, axispos)
def timeslice(x, y, transparency=0.0, label="", W=3):
dopath(
[(-1.1, y0), (-0.1, y1), (W + 0.2, y1), (W - 0.8, y0)],
fill=[shade, color.transparency(0.3)],
extra=[trafo.translate(x, y)],
closepath=True,
)
if label:
c.text(W + 0.2, 0.0, label, west + [trafo.translate(x, y)])
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
hic_fname1 = "%s/Data/HiC/HiFive/mm9_ESC_NcoI_prob.hcp" % basedir
hic_fname2 = "%s/Data/HiC/HiFive/mm9_ESC_HindIII_prob.hcp" % basedir
fivec_fnames = {
"Prob_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_prob.fcp" % basedir,
"Prob_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_prob.fcp" % basedir,
"Bin_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_bin.fcp" % basedir,
"Bin_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_bin.fcp" % basedir,
"Exp_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_exp.fcp" % basedir,
"Exp_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_exp.fcp" % basedir,
"Exp-KR_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_expKR.fcp" % basedir,
"Exp-KR_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_expKR.fcp" % basedir,
}
hic1 = hifive.HiC(hic_fname1)
hic2 = hifive.HiC(hic_fname2)
hic_hm = { 'Phillips': {} }
fc = hifive.FiveC(fivec_fnames["Prob_Phillips"])
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
for i in range(fc.frags['regions'].shape[0]):
binbounds = numpy.hstack((
fragments['start'][regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1, 1),
fragments['stop'][regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1, 1)))
binbounds = binbounds[numpy.where(fc.filter[regions['start_frag'][i]:regions['stop_frag'][i]])[0], :]
hic_hm['Phillips'][i] = dynamically_bin(hic1, hic2, regions['chromosome'][i], binbounds)
fc = hifive.FiveC(fivec_fnames["Prob_Nora"])
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
binbounds = numpy.hstack((
fragments['start'][regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1),
fragments['stop'][regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1)))
binbounds = binbounds[numpy.where(fc.filter[regions['start_frag'][0]:regions['stop_frag'][0]])[0], :]
hic_hm['Nora'] = dynamically_bin(hic1, hic2, regions['chromosome'][0], binbounds)
dist_corr = find_correlations( hic_hm, fivec_fnames, out_fname, True )
nodist_corr = find_correlations( hic_hm, fivec_fnames, out_fname, False )
c = canvas.canvas()
width = 16.8
spacer = 0.4
plot_width = (width - spacer * 2) / 2.5
plot_height = plot_width
key_width = width - (plot_width + spacer) * 2
phillips_img = plot_correlation_diffs(dist_corr, nodist_corr, 'Phillips', plot_width, plot_height)
nora_img = plot_correlation_diffs(dist_corr, nodist_corr, 'Nora', plot_width, plot_height)
key_img = plot_key(key_width, plot_height)
c.insert(phillips_img)
c.insert(nora_img, [trafo.translate(plot_width + spacer, 0)])
c.insert(key_img, [trafo.translate((plot_width + spacer) * 2, 0)])
c.text(0, plot_height, "a",
[text.halign.left, text.valign.top, text.size(-1)])
c.text(plot_width + spacer, plot_height, "b",
[text.halign.left, text.valign.top, text.size(-1)])
c.writePDFfile(out_fname)
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
mm9_methods = {
'HiFive-Probability':'%s/Analysis/hifive_mm9_ESC_prob_correlations.txt' % basedir,
'HiFive-Express':'%s/Analysis/hifive_mm9_ESC_exp_correlations.txt' % basedir,
'HiFive-Binning':'%s/Analysis/hifive_mm9_ESC_bin_correlations.txt' % basedir,
'HiCNorm':'%s/Analysis/hicnorm_mm9_ESC_correlations.txt' % basedir,
'HiCPipe':'%s/Analysis/hicpipe_mm9_ESC_correlations.txt' % basedir,
'Matrix-Balancing':'%s/Analysis/mb_mm9_ESC_correlations.txt' % basedir,
}
hg19_methods = {
'HiFive-Probability':'%s/Analysis/hifive_hg19_GM12878_prob_correlations.txt' % basedir,
'HiFive-Express':'%s/Analysis/hifive_hg19_GM12878_exp_correlations.txt' % basedir,
'HiFive-Binning':'%s/Analysis/hifive_hg19_GM12878_bin_correlations.txt' % basedir,
'HiCNorm':'%s/Analysis/hicnorm_hg19_GM12878_correlations.txt' % basedir,
'HiCPipe':'%s/Analysis/hicpipe_hg19_GM12878_correlations.txt' % basedir,
'Matrix-Balancing':'%s/Analysis/mb_hg19_GM12878_correlations.txt' % basedir,
}
mm9_data = load_data(mm9_methods)
hg19_data = load_data(hg19_methods)
width = 16.8
spacer = 0.4
overall_width = (width - spacer * 2) / 2.6
c = canvas.canvas()
mm9_ranges_img, mm9_ranges_height = plot_dataset_ranges(mm9_data, width, "MM9 ESC")
mm9_ranges_img.text(0, mm9_ranges_height, 'a',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(mm9_ranges_img)
hg19_ranges_img, hg19_ranges_height = plot_dataset_ranges(hg19_data, width, "HG19 GM12878")
hg19_ranges_img.text(0, hg19_ranges_height, 'b',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(hg19_ranges_img, [trafo.translate(0, -hg19_ranges_height - spacer)])
overall_height = mm9_ranges_height * 0.6
mm9_overall_img = plot_overall(mm9_data, overall_width, overall_height, "MM9 ESC")
mm9_overall_img.text(0, overall_height + 0.1, 'c',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(mm9_overall_img, [trafo.translate(0, -hg19_ranges_height - overall_height - spacer * 2)])
hg19_overall_img = plot_overall(hg19_data, overall_width, overall_height, "HG19 GM12878")
hg19_overall_img.text(0, overall_height + 0.1, 'd',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(hg19_overall_img, [trafo.translate(overall_width * 1.6 + spacer * 2,
-hg19_ranges_height - overall_height - spacer * 2)])
c.insert(plot_key(overall_width * 0.6 + 0.4, overall_height),
[trafo.translate(overall_width + spacer + 0.6, -hg19_ranges_height - overall_height - spacer * 2)])
c.writePDFfile(out_fname)
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
mm9_methods = {
'distance-corrected':'%s/Analysis/hifive_mm9_ESC_exp_correlations.txt' % basedir,
'raw':'%s/Analysis/hifive_mm9_ESC_expdist_correlations.txt' % basedir,
}
mm9_data = load_data(mm9_methods)
width = 16.8
spacer = 0.4
plot_width = (width - spacer * 4) / 5
c = canvas.canvas()
mm9_ranges_img, mm9_ranges_height = plot_dataset_ranges(mm9_data, plot_width, spacer)
mm9_ranges_img.text(0, mm9_ranges_height, 'b',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(mm9_ranges_img, [trafo.translate(plot_width + spacer, 0)])
mm9_overall_img = plot_overall(mm9_data, plot_width - spacer, (mm9_ranges_height - spacer) - 0.3)
c.text(0, mm9_ranges_height, 'a',
[text.halign.left, text.valign.top, text.size(-1)])
c.insert(mm9_overall_img, [trafo.translate(0, 0.4)])
c.writePDFfile(out_fname)
def plot_overall(data, width, height, name):
vo = 0.55
ho = 0.7
plot_width = width - ho
plot_height = height - vo - 0.3
c = canvas.canvas()
methods = data.keys()
methods.sort()
bar_colors = []
cis_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(data[methods[0]]['interaction'] == 'cis')])
trans_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(data[methods[0]]['interaction'] == 'trans')])
Y = numpy.zeros((len(methods), cis_binsizes.shape[0] + trans_binsizes.shape[0]), dtype=numpy.float32)
for i, method in enumerate(methods):
for j, binsize in enumerate(cis_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'cis') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j] = data[method]['correlation'][where]
for j, binsize in enumerate(trans_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'trans') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j + cis_binsizes.shape[0]] = data[method]['correlation'][where]
bar_colors.append(method_colors[method])
Y = numpy.array(Y)
g = graph.graphxy(width=plot_width, height=plot_height,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for i in range(len(methods)):
g.plot(graph.data.points(zip(zip(range(Y.shape[1]), [i] * Y.shape[1]), Y[i, :]), xname=1, y=2),
[graph.style.changebar([method_colors[methods[i]]])])
c.insert(g, [trafo.translate(ho, vo)])
for i, label in enumerate(["10Kb", "50Kb", "250Kb", "1Mb", "250Kb", "1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 6.0, vo - 0.05, "%s" % label,
[text.halign.center, text.valign.top, text.size(-3)])
c.text(ho + plot_width * 2.0 / 6.0, 0.05, "cis",
[text.halign.center, text.valign.bottom, text.size(-3)])
c.stroke(path.line(ho + 0.2, vo * 0.5, ho - 0.2 + plot_width * 4.0 / 6.0, vo * 0.5), [style.linewidth.THin])
c.text(ho + plot_width * 5.0 / 6.0, 0.05, "trans",
[text.halign.center, text.valign.bottom, text.size(-3)])
c.stroke(path.line(ho + 0.2 + plot_width * 4.0 / 6.0, vo * 0.5, ho - 0.2 + plot_width, vo * 0.5), [style.linewidth.THin])
c.text(0, plot_height * 0.5 + vo, "Correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
c.text(plot_width * 0.5 + ho, height, name,
[text.halign.center, text.valign.top, text.size(-3)])
return c
def plot_overall(data, width, height, int_type):
methods = data.keys()
methods.sort()
vo = 0.3
ho = 0.8
plot_width = width - ho
plot_height = height - vo - 0.3
c = canvas.canvas()
bar_colors = []
binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(data[methods[0]]['interaction'] == int_type)])
Y = numpy.zeros((len(methods), binsizes.shape[0]), dtype=numpy.float32)
for i, method in enumerate(methods):
for j, binsize in enumerate(binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == int_type) *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j] = data[method]['correlation'][where]
bar_colors.append(method_colors[method])
Y = numpy.array(Y)
minY = numpy.amin(Y)
maxY = numpy.amax(Y)
spanY = maxY - minY
minY -= spanY * 0.05
maxY += spanY * 0.05
g = graph.graphxy(width=plot_width, height=plot_height,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter, min=minY, max=maxY),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for i in range(len(methods)):
g.plot(graph.data.points(zip(zip(range(Y.shape[1]), [i] * Y.shape[1]), Y[i, :]), xname=1, y=2),
[graph.style.changebar([method_colors[methods[i]]])])
c.insert(g, [trafo.translate(ho, vo)])
if int_type == 'cis':
for i, label in enumerate(["10Kb", "50Kb", "250Kb", "1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 4.0, vo - 0.05, "%s" % label,
[text.halign.center, text.valign.top, text.size(-3)])
c.text(ho + plot_width * 0.5, height, "Cis",
[text.halign.center, text.valign.top, text.size(-2)])
else:
for i, label in enumerate(["250Kb", "1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 2.0, vo - 0.05, "%s" % label,
[text.halign.center, text.valign.top, text.size(-3)])
c.text(ho + plot_width * 0.5, height, "Trans",
[text.halign.center, text.valign.top, text.size(-2)])
c.text(0, plot_height * 0.5 + vo, "Correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
return c
def braid_id(x0=0., y0=0., H=3.0, t0="", t1=""):
tr = [trafo.translate(x0, y0)]
timeslice(x0, y0, 0., t0)
for i in range(3):
x = i*w
c.stroke(path.line(x, 0., x, H), st_Thick+tr)
timeslice(x0, y0+H, 0.3, t1)
for i in range(3):
c.fill(path.circle(i*w, 0., 0.06), tr)
c.fill(path.circle(i*w, H, 0.06), tr)
def braid_1(x0=0., y0=0., H=3.0, t0="", t1="", inverse=False):
if inverse:
rev = lambda x : list(reversed(x))
rev1 = lambda ps : [(x, H-y) for (x, y) in reversed(ps)]
else:
rev = list
rev1 = list
tr = [trafo.translate(x0, y0)]
ps0 = []
ps1 = []
ps2 = []
for i in range(N+1):
r = 1.*i/N
y = r*H
r1 = bump(r)
x = 0.5*(w - w*cos(2*pi*r1))
ps0.append((x, y))
x = w + w*(sin(0.5*pi*r))
ps1.append((x, y))
x = 1*w + w*cos(1.5*pi*r1)
ps2.append((x, y))
ps0 = rev1(ps0)
ps1 = rev1(ps1)
ps2 = rev1(ps2)
if not inverse: # HACK
timeslice(x0, y0, 0., t0)
for ps in draw(ps0, [ps1, ps2], rev([True, False])):
dopath(ps, st_Thick+tr)
for ps in draw(ps1, [ps0, ps2], rev([False])):
dopath(ps, st_Thick+tr)
for ps in draw(ps2, [ps0, ps1], rev([True, False, True])):
dopath(ps, st_Thick+tr)
timeslice(x0, y0+H, 0.3, t1)
for i in range(3):
c.fill(path.circle(i*w, 0., 0.06), tr)
c.fill(path.circle(i*w, H, 0.06), tr)
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
bin_file = '%s/Analysis/hifive_mm9_ESC_prob_correlations.txt' % basedir
pois_file = '%s/Analysis/hifive_mm9_ESC_probpois_correlations.txt' % basedir
bin_data = load_data(bin_file)
pois_data = load_data(pois_file)
width = 16.8
spacer = 0.4
range_width = (width - spacer) / 5.0
range_height = range_width * 1.4
c = canvas.canvas()
ranges_img = plot_dataset_ranges(bin_data, pois_data, range_width * 4, range_height)
c.insert(ranges_img)
overall_img = plot_overall(bin_data, pois_data, range_width, range_height)
c.insert(overall_img, [trafo.translate(range_width * 4 + spacer, 0)])
c.writePDFfile(out_fname)
def plot_single_range(data, binsize, width, height):
plot_width = width - 0.4
plot_height = height - 0.8
c = canvas.canvas()
xmax = 0.0
methods = data.keys()
methods.sort()
for method in methods:
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'cis') *
(data[method]['range'] > 0))
if where[0].shape[0] > 0:
xmax = max(xmax, numpy.amax(data[method]['range'][where]))
X = data[method]['range'][where]
X = numpy.r_[0, X]
X[0] = X[1] ** 2.0 / X[2]
xmin = X[0]
g = graph.graphxy(width=plot_width, height=plot_height,
x=graph.axis.log(painter=painter, min=X[0], max=xmax),
y=graph.axis.lin(painter=painter),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for x in X[1:-1]:
pos = ((log(x) - log(xmin)) / (log(xmax) - log(xmin)) * plot_width)
g.stroke(path.line(pos, 0, pos, plot_height), [style.linestyle.dotted, style.linewidth.THin])
X = (X[1:] ** 0.5) * (X[:-1] ** 0.5)
for method in methods:
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'cis') *
(data[method]['range'] > 0))
if where[0].shape[0] > 0:
Y = data[method]['correlation'][where]
g.plot(graph.data.points(zip(X, Y), x=1, y=2),
[graph.style.line(lineattrs=[method_colors[method], style.linewidth.Thick])])
if binsize / 1000000 > 0:
binstring = "%iMb" % (binsize / 1000000)
elif binsize / 1000 > 0:
binstring = "%iKb" % (binsize / 1000)
else:
binstring = str(binsize)
g.text(plot_width / 2, plot_height + 0.05, "%s Binning" % (binstring),
[text.halign.center, text.valign.bottom, text.size(-2)])
c.insert(g, [trafo.translate(0.4, 0.4)])
return c
def plot_overall(data, width, height):
plot_width = width - 0.4
plot_height = height - 0.4
c = canvas.canvas()
methods = data.keys()
methods.sort()
bar_colors = []
cis_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(data[methods[0]]['interaction'] == 'cis')])
trans_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(data[methods[0]]['interaction'] == 'trans')])
Y = numpy.zeros((len(methods), cis_binsizes.shape[0] + trans_binsizes.shape[0]), dtype=numpy.float32)
for i, method in enumerate(methods):
for j, binsize in enumerate(cis_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'cis') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j] = data[method]['correlation'][where]
for j, binsize in enumerate(trans_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'trans') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j + cis_binsizes.shape[0]] = data[method]['correlation'][where]
bar_colors.append(method_colors[method])
Y = numpy.array(Y)
g = graph.graphxy(width=plot_width, height=plot_height,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for i in range(len(methods)):
g.plot(graph.data.points(zip(zip(range(Y.shape[1]), [i] * Y.shape[1]), Y[i, :]), xname=1, y=2),
[graph.style.changebar([method_colors[methods[i]]])])
step = plot_width / (cis_binsizes.shape[0] + trans_binsizes.shape[0])
for i, binsize in enumerate(cis_binsizes):
g.text(step * (0.5 + i), -0.05, "%s cis" % (str(binsize/1000) + 'Kb').replace('000Kb', 'Mb'),
[text.halign.right, text.valign.middle, text.size(-4), trafo.rotate(45)])
for i, binsize in enumerate(trans_binsizes):
g.text(step * (0.5 + i + cis_binsizes.shape[0]), -0.05, "%s trans" % (str(binsize/1000) + 'Kb').replace('000Kb', 'Mb'),
[text.halign.right, text.valign.middle, text.size(-4), trafo.rotate(45)])
c.insert(g, [trafo.translate(0.7, 0.4)])
c.text(0, plot_height / 2.0 + 0.4, "Dataset Correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
return c
def plot_dataset_ranges(data, width, spacer):
methods = data.keys()
binsizes = numpy.unique(data[methods[0]]['binsize'])
plot_width = width - 0.4
plot_height = plot_width + 0.2
c = canvas.canvas()
for i, binsize in enumerate(binsizes):
img = plot_single_range(data, binsize, plot_width, plot_height)
c.insert(img, [trafo.translate((plot_width + spacer) * i + 0.4, 0.4 + spacer * 0.5)])
c.text(0, plot_height * 0.5 + 0.2 + spacer * 0.75, "Dataset correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
c.text(plot_width * 2 + spacer * 1.5 + 0.4, 0.35, "Interaction range (bp)",
[text.halign.center, text.valign.bottom, text.size(-3)])
c.fill(path.rect(0.4, 0.025, 0.2, 0.2), [color.rgb.black])
c.text(0.7, 0.125, "HiFive-Express using raw reads", [text.halign.left, text.valign.middle, text.size(-2)])
c.fill(path.rect(plot_width * 2 + spacer * 1.5, 0.025, 0.2, 0.2), [color.rgb.red])
c.text(plot_width * 2 + spacer * 1.5 + 0.3, 0.125, "HiFive-Express using distance-corrected reads",
[text.halign.left, text.valign.middle, text.size(-2)])
return c, plot_height + 0.4 + spacer
def plot_dataset_ranges(data, width):
methods = data.keys()
methods.sort()
binsizes = numpy.unique(data[methods[0]]['binsize'])
ho = 0.4
ho2 = 0.4
vo = 0.6
spacer = 0.25
plot_width = (width - ho - (binsizes.shape[0] - 1) * spacer) / binsizes.shape[0] - ho2
plot_height = plot_width
c = canvas.canvas()
for i, binsize in enumerate(binsizes):
img = plot_single_range(data, binsize, plot_width, plot_width, methods)
c.insert(img, [trafo.translate((plot_width + spacer) * i + ho2 * (i + 1) + ho, vo)])
c.text(0, plot_height * 0.5 + vo, "Correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
c.text((plot_width + ho2) * 2 + spacer * 1.5 + ho, 0, "Interaction Range (bp)",
[text.halign.center, text.valign.bottom, text.size(-3)])
return c, plot_height + vo + 0.3
def plot_dataset_ranges(data0, data1, width, height):
binsizes = numpy.unique(data0['binsize'])
ho = 1.1
ho2 = 0.2
vo = 1.0
plot_width = (width - ho - ho2 * 3) / 4.0
plot_height = height - vo
c = canvas.canvas()
for i, binsize in enumerate(binsizes):
if i == 0:
ylabel = True
else:
ylabel = False
img = plot_single_range(data0, data1, binsize, plot_width, plot_height, ylabel)
c.insert(img, [trafo.translate(ho + i * (plot_width + ho2), vo - 0.3)])
c.text(0, plot_height * 0.5 + vo - 0.3, r"$r_{Poisson} - r_{binomial}$",
[text.halign.center, text.valign.top, text.size(-2), trafo.rotate(90)])
c.text(plot_width * 2 + ho + 1.5 * ho2, 0, "Interaction Range (bp)",
[text.halign.center, text.valign.bottom, text.size(-3)])
c.text(0, height, 'a', [text.halign.left, text.valign.top, text.size(-1)])
return c
def plot_correlation_diffs(corr1, corr2, name, width, height):
ho = 1.2
vo = 0.4
plot_width = width - ho
plot_height = height - vo
diffs = {}
ymin = numpy.inf
ymax = -numpy.inf
for n in ['Phillips', 'Nora']:
for meth in meth_names.keys():
cname = "%s_%s" % (meth, n)
diff = corr2[cname] - corr1[cname]
ymin = min(ymin, diff)
ymax = max(ymax, diff)
for meth in meth_names.keys():
cname = "%s_%s" % (meth, name)
diffs[meth] = corr2[cname] - corr1[cname]
yspan = ymax - ymin
ymin -= yspan * 0.05
ymax += yspan * 0.05
yspan = ymax - ymin
c = canvas.canvas()
g = graph.graphxy(width=plot_width, height=plot_height,
x=graph.axis.bar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter, min=ymin, max=ymax),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
w = plot_width / float(len(meth_names) + 1)
y0 = -ymin / yspan * plot_height
for i, meth in enumerate(methods):
col = method_colors[meth]
g.stroke( path.rect((i + 0.5) * w, y0, w, diffs[meth] / yspan * plot_height), [deco.filled([col])])
g.stroke( path.line(0, y0, plot_width, y0), [style.linestyle.dotted, style.linewidth.THin])
c.insert(g, [trafo.translate(ho, vo)])
c.text(0, plot_height * 0.5 + vo, r"$r_{0K} - r_{50K}$",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
c.text(plot_width * 0.5 + ho, vo * 0.5, name,
[text.halign.center, text.valign.middle, text.size(-3)])
return c
def checkall(): # <<<
c = None
for knots, refpoints in [curve1(), curve2(), curve3(),
curve4(-90), curve4(0), curve4(70), curve5(),
curve6a(), curve6b(), curve6c(), curve7(),
curve8a(), curve8b(), curve9(), curve10()]:
#print myprint(knots)
mp_make_choices(knots, epsilon)
#print myprint(knots)
cc = canvas.canvas()
cc.stroke(mypath(knots), [deco.shownormpath(), deco.earrow.normal])
if c is None:
c = canvas.canvas()
c.insert(cc)
else:
c.insert(cc, [trafo.translate(0, c.bbox().bottom() - cc.bbox().top()-0.5)])
check(knots, refpoints)
c.writePDFfile()
c.writeEPSfile()
c.writeSVGfile()
def plot_bar(data, ranges, height, scale, split):
c = canvas.canvas()
pos = 0.0
x1 = 0.0
for i in range(5):
if str(i) in data:
x2 = data[str(i)] / 60.0 + pos
pos2 = x2
for j in range(1, ranges.shape[0]):
if x2 > ranges[j, 0] and x2 < ranges[j, 1]:
for k in range(j):
x2 -= ranges[k + 1, 0] - ranges[k, 1]
break
c.fill(path.rect(x1 * scale, 0, (x2 - x1) * scale, height), [step_colors[i]])
split_pos = ranges[0, 1] * scale
for j in range(ranges.shape[0] - 1):
if pos2 > ranges[j, 1]:
c.insert(split, [trafo.translate(split_pos, height * 0.5)])
split_pos += (ranges[j + 1, 1] - ranges[j + 1, 0]) * scale
pos += data[str(i)] / 60.0
x1 = x2
return c
def plot_dataset_ranges(data0, data1, width):
methods = data0.keys()
binsizes = numpy.unique(data0[methods[0]]['binsize'])
ho = 0.8
ho2 = 0.25
vo = 0.7
vo2 = 0.4
spacer = 0.0
plot_width = (2 * width - ho * 2 - ho2 - spacer) / 2
plot_height = width - vo - vo2
c = canvas.canvas()
for i, binsize in enumerate(binsizes):
img = plot_single_range(data0, data1, binsize, plot_width, plot_width, vo, vo2)
c.insert(img, [trafo.translate((plot_width + spacer + ho) * (i % 2) + ho2 + ho,
(1 - i /
2) * (plot_height + spacer + vo + vo2) + vo)])
c.text(0, plot_height + 0.5 * spacer + vo + vo2, r"$r_{0K} - r_{500K}$",
[text.halign.center, text.valign.top, text.size(-2), trafo.rotate(90)])
c.text(plot_width + ho2 + spacer * 0.5 + ho, 0, "Interaction Range (bp)",
[text.halign.center, text.valign.bottom, text.size(-3)])
c.text(0, width * 2 + spacer, 'a',
[text.halign.left, text.valign.top, text.size(-1)])
return c
def interface(): # <<<
c = None
for p in [
# ordinary open path:
mppath.path([beginknot(0,0), curve(), knot(6,4), curve(), knot(4,9), curve(), knot(1,7), curve(), endknot(3,5)], epsilon),
# path containing two open subpaths:
mppath.path([beginknot(0,0), curve(), endknot(6,4), beginknot(4,9), curve(), knot(1,7), curve(), endknot(3,5)], epsilon),
# closed path:
mppath.path([knot(0,0), curve(), knot(6,4), curve(), knot(4,9), curve(), knot(1,7), curve(), knot(3,5), curve()], epsilon),
# open path, but with endpoints in the middle:
mppath.path([knot(0,0), curve(), knot(6,4), curve(), endknot(4,9), beginknot(1,7), curve(), knot(3,5), curve()], epsilon),
# the same path in the right order
mppath.path([beginknot(1,7), curve(), knot(3,5), curve(), knot(0,0), curve(), knot(6,4), curve(), endknot(4,9)], epsilon),
# include a line
mppath.path([knot(0,0), curve(), knot(6,4), curve(), roughknot(4,9), line(), roughknot(1,7), curve(), knot(3,5), curve()], epsilon),
# XXX the endpoints have "open" at their other sides, not "curl" as in the open example above
mppath.path([knot(0,0), curve(), knot(6,4), curve(), knot(4,9), line(), knot(1,7), curve(), knot(3,5), curve()], epsilon),
mppath.path([knot(0,0), curve(), knot(6,4), line(), knot(3,5), curve()], epsilon),
mppath.path([knot(0,0), curve(), knot(6,4), curve(), knot(3,5), curve()], epsilon),
# TODO the internal mp_make_choices treats this as closed, but the last curve is not plotted:
mppath.path([knot(0,0), curve(), knot(6,4), curve(), knot(4,9), line(), knot(1,7), curve(), knot(3,5)], epsilon),
# include a line with given angles
mppath.path([knot(0,0), curve(), knot(6,4), curve(), knot(4,9), line(keepangles=True), knot(1,7), curve(), knot(3,5), curve()], epsilon),
# include rough knots
mppath.path([beginknot(0,0), curve(), roughknot(6,4,langle=90), curve(), roughknot(4,9,langle=-90),
line(keepangles=True), roughknot(1,7,lcurl=3), curve(), endknot(3,5,angle=0)], epsilon),
]:
cc = canvas.canvas()
cc.stroke(p, [deco.shownormpath(), deco.earrow.normal])
if c is None:
c = cc
else:
c.insert(cc, [trafo.translate(c.bbox().right() - cc.bbox().left() + 0.5, 0)])
c.writePDFfile()
c.writeEPSfile()
c.writeSVGfile()
def main():
out_fname = sys.argv[1]
basedir = '/'.join(os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
hic_phillips_fname1 = "%s/Data/HiC/HiCPipe/HM/mm9_ESC_NcoI_Phillips.hch" % basedir
hic_phillips_fname2 = "%s/Data/HiC/HiCPipe/HM/mm9_ESC_HindIII_Phillips.hch" % basedir
hic_nora_fname1 = "%s/Data/HiC/HiCPipe/HM/mm9_ESC_NcoI_Nora.hch" % basedir
hic_nora_fname2 = "%s/Data/HiC/HiCPipe/HM/mm9_ESC_HindIII_Nora.hch" % basedir
hic_phillips1 = h5py.File(hic_phillips_fname1, 'r')
hic_phillips2 = h5py.File(hic_phillips_fname2, 'r')
hic_nora1 = h5py.File(hic_nora_fname1, 'r')
hic_nora2 = h5py.File(hic_nora_fname2, 'r')
hm_phillips = {}
hm_nora = {}
for key in hic_phillips1.keys():
if key.count('unbinned_counts') == 0:
continue
region = int(key.split('.')[0])
hm_phillips[region] = dynamically_bin(hic_phillips1, hic_phillips2, region)
for key in hic_nora1.keys():
if key.count('unbinned_counts') == 0:
continue
region = int(key.split('.')[0])
hm_nora[region] = dynamically_bin(hic_nora1, hic_nora2, region)
fivec_fnames = {
"Prob_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_probnodist.fcp" % basedir,
"Prob_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_probnodist.fcp" % basedir,
"Bin_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_binnodist.fcp" % basedir,
"Bin_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_binnodist.fcp" % basedir,
"Exp_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_expnodist.fcp" % basedir,
"Exp_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_expnodist.fcp" % basedir,
"Exp-KR_Phillips":"%s/Data/FiveC/HiFive/Phillips_ESC_expKRnodist.fcp" % basedir,
"Exp-KR_Nora":"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_expKRnodist.fcp" % basedir,
}
data = {}
imgs = {}
ratio1 = 0
ratio2 = 0
for meth in ['Prob', 'Bin', 'Exp', 'Exp-KR']:
fc = hifive.FiveC(fivec_fnames["%s_Phillips" % meth])
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
counts = numpy.zeros(0, dtype=numpy.float64)
expected = numpy.zeros(0, dtype=numpy.float64)
hic_counts = numpy.zeros(0, dtype=numpy.float64)
hic_expected = numpy.zeros(0, dtype=numpy.float64)
skipped = []
for i in range(fc.frags['regions'].shape[0]):
temp = fc.cis_heatmap(i, datatype='fragment', arraytype='compact', binsize=0, skipfiltered=True)
if temp is None:
skipped.append(i)
continue
counts = numpy.hstack((counts, temp[:, :, 0].ravel()))
expected = numpy.hstack((expected, temp[:, :, 1].ravel()))
if i == 6:
ratio1 = temp.shape[1] / float(temp.shape[0])
imgs["%s_Phillips" % meth] = hifive.plotting.plot_full_array(temp, symmetricscaling=False)
if meth == 'Prob':
temp1 = numpy.zeros((temp.shape[0], temp.shape[1]), dtype=numpy.float32)
temp1[numpy.where(temp[:, :, 0] > 0.0)] = 1
if i == 6:
imgs["Raw_Phillips"] = hifive.plotting.plot_full_array(
numpy.dstack((temp[:, :, 0], temp1)), symmetricscaling=False)
binbounds = numpy.hstack((
fragments['start'][regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1, 1),
fragments['stop'][regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1, 1)))
valid = numpy.where(fc.filter[regions['start_frag'][i]:regions['stop_frag'][i]])[0]
binbounds = binbounds[valid, :]
temp = hm_phillips[i]
strands = fragments['strand'][regions['start_frag'][i]:regions['stop_frag'][i]][valid]
temp = temp[numpy.where(strands == 0)[0], :, :][:, numpy.where(strands == 1)[0], :]
hic_counts = numpy.hstack((hic_counts, temp[:, :, 0].ravel()))
hic_expected = numpy.hstack((hic_expected, temp[:, :, 1].ravel()))
if i == 6:
imgs["HiC_Phillips"] = hifive.plotting.plot_full_array(temp, symmetricscaling=False)
if meth == 'Prob':
data["Raw_Phillips"] = numpy.copy(counts)
where = numpy.where(hic_expected > 0.0)[0]
hic_counts[where] /= hic_expected[where]
data["HiC_Phillips"] = numpy.copy(hic_counts)
where = numpy.where(expected > 0.0)[0]
counts[where] /= expected[where]
data["%s_Phillips" % meth] = numpy.copy(counts)
fc = hifive.FiveC(fivec_fnames["%s_Nora" % meth])
temp = fc.cis_heatmap(0, datatype='fragment', arraytype='compact', binsize=0, skipfiltered=True)
ratio2 = temp.shape[1] / float(temp.shape[0])
imgs["%s_Nora" % meth] = hifive.plotting.plot_full_array(temp, symmetricscaling=False)
counts = temp[:, :, 0].ravel()
expected = temp[:, :, 1].ravel()
if meth == 'Prob':
temp1 = numpy.zeros((temp.shape[0], temp.shape[1]), dtype=numpy.float32)
temp1[numpy.where(temp[:, :, 0] > 0.0)] = 1
imgs["Raw_Nora"] = hifive.plotting.plot_full_array(
numpy.dstack((temp[:, :, 0], temp1)), symmetricscaling=False)
data["Raw_Nora"] = numpy.copy(counts)
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
binbounds = numpy.hstack((
fragments['start'][regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1),
fragments['stop'][regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1)))
binbounds = binbounds[numpy.where(fc.filter[regions['start_frag'][0]:regions['stop_frag'][0]])[0], :]
temp = hm_nora[0]
strands = fragments['strand'][regions['start_frag'][0]:regions['stop_frag'][0]]
temp = temp[numpy.where(strands==0)[0], :, :][:, numpy.where(strands == 1)[0], :]
imgs["HiC_Nora"] = hifive.plotting.plot_full_array(temp, symmetricscaling=False)
hic_counts = temp[:, :, 0].ravel()
hic_expected = temp[:, :, 1].ravel()
where = numpy.where(hic_expected > 0.0)[0]
hic_counts[where] /= hic_expected[where]
data["HiC_Nora"] = numpy.copy(hic_counts)
where = numpy.where(expected > 0.0)[0]
counts[where] /= expected[where]
data["%s_Nora" % meth] = numpy.copy(counts)
correlations = {}
output = open(out_fname.replace('pdf', 'txt'), 'w')
print >> output, "Method\tPhillips\tNora"
for meth in methods:
temp = [meth]
for name in ["Phillips", "Nora"]:
valid = numpy.where((data["%s_%s" % (meth, name)] > 0.0) * (data["HiC_%s" % name] > 0.0))
correlations["%s_%s" % (meth, name)] = numpy.corrcoef(numpy.log(data["%s_%s" % (meth, name)][valid]),
numpy.log(data["HiC_%s" % name][valid]))[0, 1]
temp.append(str(correlations["%s_%s" % (meth, name)]))
print >> output, '\t'.join(temp)
output.close()
width = 16.8
spacer = 0.3
c = canvas.canvas()
plot_width = (width - spacer * 3.0 - 0.4) / 4.0
for i, meth in enumerate(["Raw", "Prob", "HiC"]):
meth_names = {"Raw":"Raw", "Prob":"HiFive", "HiC":"HiC"}
c.text(plot_width * (i + 1.5) + spacer * (i + 1), (ratio1 + ratio2) * plot_width + spacer + 0.1,
"%s" % meth_names[meth], [text.halign.center, text.valign.bottom, text.size(-2)])
c.insert(bitmap.bitmap(0, 0, imgs["%s_Phillips" % meth], width=plot_width),
[trafo.translate((i + 1) * (plot_width + spacer), plot_width * ratio2 + spacer)])
c.insert(bitmap.bitmap(0, 0, imgs["%s_Nora" % meth], width=plot_width),
[trafo.translate((i + 1) * (plot_width + spacer), 0)])
g = graph.graphxy(width=plot_width - 0.8, height=plot_width * ratio1,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for i, meth in enumerate(methods):
Y = numpy.zeros(2, dtype=numpy.float32)
col = method_colors[meth]
for j, name in enumerate(["Phillips", "Nora"]):
Y[j] = correlations["%s_%s" % (meth, name)]
g.plot(graph.data.points(zip(zip(range(Y.shape[0]), [i] * Y.shape[0]), Y), xname=1, y=2),
[graph.style.changebar([col])])
g.text(-0.8, plot_width * ratio1 * 0.5, "Correlation",
[text.halign.center, text.valign.top, text.size(-3), trafo.rotate(90)])
g.text((plot_width - 0.8) * 0.25, -0.1, "Phillips",
[text.halign.center, text.valign.top, text.size(-3)])
g.text((plot_width - 0.8) * 0.75, -0.1, "Nora",
[text.halign.center, text.valign.top, text.size(-3)])
c.insert(g, [trafo.translate(0.8, plot_width * ratio2 + spacer)])
c.text(width, (ratio1 + ratio2 * 0.5) * plot_width + spacer, "Phillips",
[text.halign.center, text.valign.top, trafo.rotate(-90), text.size(-2)])
c.text(width, ratio1 * 0.5 * plot_width, "Nora",
[text.halign.center, text.valign.top, trafo.rotate(-90), text.size(-2)])
meth_names = {"Raw":"Raw", "Prob":"HiFive-Probability", "Exp":"HiFive-Express", "Bin":"HiFive-Binning",
"Exp-KR":"HiFive-ExpressKR", "Exp-KR-dist":"HiFive-ExpressKR-dist"}
for i, meth in enumerate(methods):
c.fill(path.rect(1.0, plot_width * ratio1 - 1.0 - i * 0.5, 0.2, 0.2), [method_colors[meth]])
c.text(1.3, plot_width * ratio1 - 0.9 - i * 0.5, "%s" % meth_names[meth],
[text.halign.left, text.valign.middle, text.size(-3)])
c.writePDFfile(out_fname)
pyplot.show()
quit()
from pyx import canvas, graph, text, color, style, trafo, unit
from pyx.graph import axis, key
text.set(mode="latex")
text.preamble(r"\usepackage{txfonts}")
figwidth = 12
gkey = key.key(pos=None, hpos=0.05, vpos=0.8)
xaxis = axis.linear(title=r"Time, \(t\)")
yaxis = axis.linear(title="Signal", min=-5, max=17)
g = graph.graphxy(width=figwidth, x=xaxis, y=yaxis, key=gkey)
plotdata = [graph.data.values(x=t, y=signal+offset, title=label) for label, signal, offset in (r"\(A(t) = \mathrm{square}(2\pi t/T)\)", A, 2.5), (r"\(B(t) = \mathrm{sawtooth}(\phi + 2 \pi t/T)\)", B, -2.5)]
linestyles = [style.linestyle.solid, style.linejoin.round, style.linewidth.Thick, color.gradient.Rainbow, color.transparency(0.5)]
plotstyles = [graph.style.line(linestyles)]
g.plot(plotdata, plotstyles)
g.plot(graph.data.values(x=t, y=listX, title="Blah"), plotstyles)
g.text(10*unit.x_pt, 0.56*figwidth, r"\textbf{Cross correlation of noisy anharmonic signals}")
g.text(10*unit.x_pt, 0.33*figwidth, "Phase shift: input \(\phi = %.2f \,\pi\), recovered \(\phi = %.2f \,\pi\)" % (phase_shift/pi, recovered_phase_shift/pi))
xxaxis = axis.linear(title=r"Time Lag, \(\Delta t\)", min=-1.5, max=1.5)
yyaxis = axis.linear(title=r"\(A(t) \star B(t)\)")
gg = graph.graphxy(width=0.2*figwidth, x=xxaxis, y=yyaxis)
plotstyles = [graph.style.line(linestyles + [color.rgb(0.2,0.5,0.2)])]
#gg.plot(graph.data.values(x=dt, y=xcorr), plotstyles)
gg.plot(graph.data.values(x=dt, y=xcorr, title="Blah"), plotstyles)
gg.stroke(gg.xgridpath(recovered_time_shift), [style.linewidth.THIck, color.gray(0.5), color.transparency(0.7)])
ggtrafos = [trafo.translate(0.75*figwidth, 0.45*figwidth)]
g.insert(gg, ggtrafos)
g.writePDFfile("so-xcorr-pyx")
c.stroke(path.rect(x0 + 8 * size, y0, 4 * size, size),
[deco.filled([codecolor])])
c.stroke(path.rect(x0 + 12 * size, y0, 6 * size, size),
[deco.filled([codecolor])])
c.stroke(path.rect(x0 + 18 * size, y0, 6 * size, size),
[deco.filled([codecolor])])
for n in range(len(codepointbinary)):
c.text(x0 + (n + 0.5) * size, y0 + dy,
r"\sffamily %i" % codepointbinary[n], [text.halign.center])
p = path.path(path.moveto(0.2 * size, size + 0.03),
path.lineto(0.2 * size, size + 0.07),
path.lineto(3.8 * size, size + 0.07),
path.lineto(3.8 * size, size + 0.03))
for n in range(bits // 4):
c.stroke(p, [trafo.translate(4 * n * size, y0)])
c.text((4 * n + 2) * size, size + 0.14 + y0,
r"\sffamily %X" % (codepoint >> (bits // 4 - n - 1) * 4 & 0x0f),
[text.halign.center])
utf8code = 0xE08080 \
+ (((codepoint >> 12) & 0x0f) << 16) \
+ (((codepoint >> 6) & 0x3f) << 8) \
+ (codepoint & 0x3f)
utf8codebinary = [(utf8code & 2**n) / 2**n for n in range(bits)]
utf8codebinary.reverse()
y1 = 2
c.fill(path.rect(x0, y1, 4 * size, size),
[utf8markercolor, deco.stroked([utf8markercolor])])
c.fill(path.rect(x0 + 8 * size, y1, 2 * size, size),
text.preamble(r'\usepackage{color}')
text.preamble(r'\definecolor{axis0}{rgb}{%s, %s, %s}' %
(color0.r, color0.g, color0.b))
text.preamble(r'\definecolor{axis1}{rgb}{%s, %s, %s}' %
(color1.r, color1.g, color1.b))
unit.set(xscale=1.2, wscale=1.5)
c = canvas.canvas()
m1 = np.arange(4).reshape(2, 2)
c_m1 = matrix_22(m1)
m2 = np.arange(4, 8).reshape(2, 2)
c_m2 = matrix_22(m2)
m3 = np.dot(m1, m2)
c_m3 = matrix_22(m3, dx=0.7)
c.insert(c_m1)
c.insert(c_m2, [trafo.translate(c_m1.bbox().width() + 0.1, 0)])
end = c_m1.bbox().right() + c_m2.bbox().width() + 0.1
dist2 = 0.6
c.insert(c_m3, [trafo.translate(end + dist2 - c_m3.bbox().left(), 0)])
ycenter = 0.5 * (c_m1.bbox().top() + c_m1.bbox().bottom())
for dy in (-0.05, 0.05):
c.stroke(
path.line(end + 0.15, ycenter + dy, end + dist2 - 0.15, ycenter + dy))
c_tot = canvas.canvas()
for y in range(4):
c_tot.insert(c, [trafo.translate(0, 1.5 * y)])
dx = 0.2
colorprops = [color.rgb(0.8, 0.2, 0), color.transparency(0.2)]
arrowprops = [deco.earrow] + colorprops
def plot_bargraph(data, width, height):
methods = [
'HiCLib', 'HiCPipe', 'HiCNorm', 'HiFive-Probability', 'HiFive-Binning',
'HiFive-Express', 'HiFive-ExpressKR', 'HiFive-ExpressKR w/distance'
]
ho = 4.0
left_width = (width - ho) * 0.45
mid_width1 = (width - ho) * 0.3
mid_width2 = (width - ho) * 0.125
right_width = (width - ho) * 0.125
bar_height = height / len(methods) - 0.1
data_totals = {}
ranges = numpy.zeros((4, 2), dtype=numpy.float32)
for meth in data:
data_totals[meth] = find_total(data[meth])
if meth == 'HiCPipe':
ranges[1, 1] = data_totals[meth]
elif meth == 'HiCNorm':
ranges[2, 1] = data_totals[meth]
elif meth == 'HiFive-Probability':
ranges[3, 1] = data_totals[meth]
else:
ranges[0, 1] = max(ranges[0, 1], data_totals[meth])
ranges /= 60.0
ranges[0, 1] = 28.0
ranges[1, 0] = ranges[1, 1] - ranges[0, 1] / 0.45 * 0.3 * 0.9
ranges[1, 1] = ranges[1, 1] + ranges[0, 1] / 0.45 * 0.3 * 0.1
ranges[2, 0] = ranges[2, 1] - ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[2, 1] = ranges[2, 1] + ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[3, 0] = ranges[3, 1] - ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[3, 1] = ranges[3, 1] + ranges[0, 1] / 0.45 * 0.125 * 0.5
c = canvas.canvas()
g1 = graph.graphxy(width=left_width,
height=height,
x=graph.axis.lin(painter=painter,
min=0,
max=ranges[0, 1]),
x2=graph.axis.lin(parter=None, min=0, max=ranges[0, 1]),
y=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g1)
g2 = graph.graphxy(width=mid_width1,
height=height,
x=graph.axis.lin(painter=painter,
min=ranges[1, 0],
max=ranges[1, 1]),
x2=graph.axis.lin(parter=None,
min=ranges[1, 0],
max=ranges[1, 1]),
y2=graph.axis.lin(painter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g2, [trafo.translate(left_width, 0)])
g3 = graph.graphxy(width=mid_width2,
height=height,
x=graph.axis.lin(painter=painter,
min=ranges[2, 0],
max=ranges[2, 1]),
x2=graph.axis.lin(parter=None,
min=ranges[2, 0],
max=ranges[2, 1]),
y2=graph.axis.lin(painter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g3, [trafo.translate(left_width + mid_width1, 0)])
g4 = graph.graphxy(width=right_width,
height=height,
x=graph.axis.lin(painter=painter,
min=ranges[3, 0],
max=ranges[3, 1]),
x2=graph.axis.lin(parter=None,
min=ranges[3, 0],
max=ranges[3, 1]),
y2=graph.axis.lin(parter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g4, [trafo.translate(left_width + mid_width1 + mid_width2, 0)])
split = canvas.canvas()
split.fill(
path.path(path.moveto(-0.15, -0.2), path.lineto(0.05, 0.2),
path.lineto(.15, 0.2), path.lineto(-0.05, -0.2),
path.closepath()), [color.cmyk.White])
split.stroke(path.line(-0.15, -0.2, 0.05, 0.2))
split.stroke(path.line(-0.05, -0.2, 0.15, 0.2))
c.insert(split, [trafo.translate(left_width, 0)])
c.insert(split, [trafo.translate(left_width, height)])
c.insert(split, [trafo.translate(left_width + mid_width1, 0)])
c.insert(split, [trafo.translate(left_width + mid_width1, height)])
c.insert(split, [trafo.translate(left_width + mid_width1 + mid_width2, 0)])
c.insert(split,
[trafo.translate(left_width + mid_width1 + mid_width2, height)])
for i, meth in enumerate(methods):
c.insert(
plot_bar(data[meth], ranges, bar_height, left_width / ranges[0, 1],
split),
[
trafo.translate(0, height - 0.05 - bar_height *
(i + 1) - i * 0.1)
])
c.text(-0.1,
height * (len(methods) - i - 0.5) / len(methods), meth,
[text.halign.right, text.valign.middle,
text.size(-2)])
c.text((width - ho) / 2.0, -0.35, "Runtime (minutes)",
[text.halign.center, text.valign.top,
text.size(-2)])
return c
from pyx import canvas, color, deformer, path, text, trafo, unit
text.set(text.LatexRunner)
text.preamble(r'''\usepackage[scaled=0.85,lining]{FiraMono}
\usepackage[utf8]{inputenc}''')
unit.set(xscale=1.2)
c = canvas.canvas()
dx = 0.3
h = 4
w = 6.5
p = path.rect(-dx, -dx, w + 2 * dx, h + 2 * dx)
p = deformer.smoothed(0.5).deform(p)
c.fill(p, [color.grey(0.5), trafo.translate(0.05, -0.05)])
c.fill(p, [color.grey(0.9)])
c1 = canvas.canvas()
boxwd = 0.7
for n in range(-5, 6):
x = (n - 0.5) * boxwd
c1.stroke(path.line(x, -0.5 * h - dx, x, 0.5 * h + dx))
for n in range(-5, 6):
y = (n - 0.5) * boxwd
c1.stroke(path.line(-0.5 * w - dx, y, 0.5 * w + dx, y))
highlight = color.rgb(0.7, 0, 0)
template = r'\texttt{{\bfseries{}}}'
pos = [0, 0]
number = 1
c1.text(*pos, template.format(number),
[text.halign.center, text.valign.middle, highlight])
julia_c = -0.8 + 0.156j
schwelle = 50000
maxit = 600
julia_daten = []
for y in np.linspace(ymin, ymax, seitenlaenge):
for x in np.linspace(xmin, xmax, seitenlaenge):
iterationen = julia_iteration(x, y, julia_c, schwelle, maxit)
julia_daten.append((x, y, iterationen / maxit))
c = canvas.canvas()
dx = 0.3
h = 4
w = 6.5
p = path.rect(-dx, -dx, w + 2 * dx, h + 2 * dx)
p = deformer.smoothed(0.5).deform(p)
c.fill(p, [color.grey(0.5), trafo.translate(0.05, -0.05)])
c1 = canvas.canvas([canvas.clip(p)])
g = graph.graphxy(height=8,
width=8,
x=graph.axis.linear(min=xmin, max=xmax),
y=graph.axis.linear(min=ymin, max=ymax))
g.plot(graph.data.points(julia_daten, x=1, y=2, color=3, title="iterations"),
[graph.style.density(gradient=color.rgbgradient.Rainbow)])
c1.insert(g, [trafo.translate(-0.1 * w, -0.5 * h)])
c.insert(c1)
c.writeGSfile(device="png16m", resolution=300)
(2.5, -0.1, -0.5,
graph.graphxyz.central(5, 210, -30))):
for direction in range(3):
for coord11, coord12 in zip(coordinates[:-1], coordinates[1:]):
for coord21, coord22 in zip(coordinates[:-1], coordinates[1:]):
pt1[direction] = side
pt1[(direction + 1) % 3] = coord11
pt1[(direction + 2) % 3] = coord21
pt2[direction] = side
pt2[(direction + 1) % 3] = coord12
pt2[(direction + 2) % 3] = coord21
pt3[direction] = side
pt3[(direction + 1) % 3] = coord12
pt3[(direction + 2) % 3] = coord22
pt4[direction] = side
pt4[(direction + 1) % 3] = coord11
pt4[(direction + 2) % 3] = coord22
p = path.path(path.moveto(*projector.point(*pt1)),
path.lineto(*projector.point(*pt2)),
path.lineto(*projector.point(*pt3)),
path.lineto(*projector.point(*pt4)),
path.closepath())
rgbcolor = [0, 0, 0]
rgbcolor[direction] = side + 0.5
rgbcolor[(direction + 1) % 3] = (coord11 + coord12 + 1) / 2
rgbcolor[(direction + 2) % 3] = (coord21 + coord22 + 1) / 2
c.fill(p, [color.rgb(*rgbcolor), trafo.translate(x0, y0)])
filename = os.path.splitext(sys.argv[0])[0] + '.png'
c.writeGSfile(filename, resolution=200)
x = baseprime % 25
y = 2 - (baseprime // 25)
c.fill(path.rect(x, y, 1, -1), [primecolor])
c.text(x + 0.5, y - 0.5, r'\textbf{%s}' % baseprime,
[text.halign.center, text.valign.middle,
color.grey(1)])
for n in range(baseprime**2, 50, baseprime):
if not n in cancelled:
cancelled.add(n)
x = n % 25
y = 2 - (n // 25)
c.stroke(path.line(x, y - 1, x + 1, y), [primecolor])
c.stroke(path.line(x, y, x + 1, y - 1), [primecolor])
draw_grid()
cc = canvas.canvas()
cc.items = c.items[:]
cgesamt.insert(cc, [trafo.translate(0, -2.3 * (nr + 1))])
for n in range(50):
if not n in cancelled:
x = n % 25
y = 2 - (n // 25)
c.fill(path.rect(x, y, 1, -1), [color.hsb(0.15, 1, 0.8)])
c.text(x + 0.5, y - 0.5, r'\textbf{%s}' % n,
[text.halign.center, text.valign.middle,
color.grey(1)])
draw_grid()
cgesamt.insert(c, [trafo.translate(0, -2.3 * (nr + 2))])
cgesamt.writePDFfile()
cgesamt.writeGSfile(device="png16m", resolution=600)
pathsegments = [path.path(path.moveto(qi, 0),
path.lineto(qf, 0)),
path.path(path.moveto(qf, 0),
path.lineto(width-radius, 0),
path.arc(width-radius, radius, radius, -90, 90),
path.lineto(qf, 2*radius)),
path.path(path.moveto(qf, 0),
path.lineto(qi, 0)),
path.path(path.moveto(qi, 0),
path.lineto(radius, 0),
path.arcn(radius, radius, radius, 270, 90),
path.lineto(qi, 2*radius))]
anzahl_segmente = (1, 2, 2, 3)
ypos = 0.5*dy
for n in range(1, ntraj+1):
offset = 0
if n % 2 == 0:
offset = -1
nsegmente = anzahl_segmente[(n-1) % 4] + (n-1)//4*4
for nsegment in range(1, nsegmente+1):
yshift = (-offset+nsegment-1)//2*2*radius
c.stroke(pathsegments[(offset+nsegment-1) % 4],
[trafo.translate(0, ypos+yshift),
linecolor, style.linewidth.Thick])
c.stroke(path.circle(qi, ypos, 0.06),
[style.linewidth.thick, linecolor, deco.filled([color.grey(1)])])
c.stroke(path.circle(qf, ypos+n//2*2*radius, 0.06),
[style.linewidth.thick, linecolor, deco.filled([color.grey(1)])])
ypos = ypos + dy + (n//2)*2*radius
c.writePDFfile()
arange = None
drawgrid(c, 4, 3, 0, gridcolor, arange=arange)
if hlshape is not None:
c.stroke(path.rect(0, 3, hlshape[1], -hlshape[0]),
[deco.filled([color.rgb(1, 0.8, 0.4)])])
drawgrid(c, hlshape[1], hlshape[0], 3 - hlshape[0], arange=False)
if arange is None:
alertcolor = color.rgb(0.6, 0, 0)
c.stroke(path.line(0, 0, 4, 3), [alertcolor, style.linewidth.Thick])
c.stroke(path.line(0, 3, 4, 0), [alertcolor, style.linewidth.Thick])
return c
text.set(text.LatexRunner)
text.preamble(r'\usepackage{arev}\usepackage[T1]{fontenc}')
unit.set(xscale=1.2, wscale=1.5)
xcells = 4
ycells = 3
gridcolor = color.grey(0.5)
c = canvas.canvas()
c.insert(array34(True))
c.insert(array34(False, (1, )), [trafo.translate(5, 0)])
c.insert(array34(False, (4, )), [trafo.translate(10, 0)])
c.insert(array34(False, (3, )), [trafo.translate(5, -4.5)])
c.insert(array34(False, (3, 1)), [trafo.translate(10, -4.5)])
c.writePDFfile()
def main():
out_fname = sys.argv[1]
basedir = '/'.join(
os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
hic_fname1 = "%s/Data/HiC/HiFive/mm9_ESC_NcoI_prob.hcp" % basedir
hic_fname2 = "%s/Data/HiC/HiFive/mm9_ESC_HindIII_prob.hcp" % basedir
fivec_fnames = {
"Prob_Phillips":
"%s/Data/FiveC/HiFive/Phillips_ESC_prob.fcp" % basedir,
"Prob_Nora":
"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_prob.fcp" % basedir,
"Bin_Phillips":
"%s/Data/FiveC/HiFive/Phillips_ESC_bin.fcp" % basedir,
"Bin_Nora":
"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_bin.fcp" % basedir,
"Exp_Phillips":
"%s/Data/FiveC/HiFive/Phillips_ESC_exp.fcp" % basedir,
"Exp_Nora":
"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_exp.fcp" % basedir,
"Exp-KR_Phillips":
"%s/Data/FiveC/HiFive/Phillips_ESC_expKR.fcp" % basedir,
"Exp-KR_Nora":
"%s/Data/FiveC/HiFive/Nora_ESC_male_E14_expKR.fcp" % basedir,
}
hic1 = hifive.HiC(hic_fname1)
hic2 = hifive.HiC(hic_fname2)
hic_hm = {'Phillips': {}}
fc = hifive.FiveC(fivec_fnames["Prob_Phillips"])
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
for i in range(fc.frags['regions'].shape[0]):
binbounds = numpy.hstack(
(fragments['start']
[regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1, 1),
fragments['stop']
[regions['start_frag'][i]:regions['stop_frag'][i]].reshape(-1,
1)))
binbounds = binbounds[numpy.where(
fc.filter[regions['start_frag'][i]:regions['stop_frag'][i]])[0], :]
hic_hm['Phillips'][i] = dynamically_bin(hic1, hic2,
regions['chromosome'][i],
binbounds)
fc = hifive.FiveC(fivec_fnames["Prob_Nora"])
fragments = fc.frags['fragments'][...]
regions = fc.frags['regions'][...]
binbounds = numpy.hstack(
(fragments['start']
[regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1),
fragments['stop']
[regions['start_frag'][0]:regions['stop_frag'][0]].reshape(-1, 1)))
binbounds = binbounds[numpy.where(
fc.filter[regions['start_frag'][0]:regions['stop_frag'][0]])[0], :]
hic_hm['Nora'] = dynamically_bin(hic1, hic2, regions['chromosome'][0],
binbounds)
dist_corr = find_correlations(hic_hm, fivec_fnames, out_fname, True)
nodist_corr = find_correlations(hic_hm, fivec_fnames, out_fname, False)
c = canvas.canvas()
width = 16.8
spacer = 0.4
plot_width = (width - spacer * 2) / 2.5
plot_height = plot_width
key_width = width - (plot_width + spacer) * 2
phillips_img = plot_correlation_diffs(dist_corr, nodist_corr, 'Phillips',
plot_width, plot_height)
nora_img = plot_correlation_diffs(dist_corr, nodist_corr, 'Nora',
plot_width, plot_height)
key_img = plot_key(key_width, plot_height)
c.insert(phillips_img)
c.insert(nora_img, [trafo.translate(plot_width + spacer, 0)])
c.insert(key_img, [trafo.translate((plot_width + spacer) * 2, 0)])
c.text(0, plot_height, "a",
[text.halign.left, text.valign.top,
text.size(-1)])
c.text(plot_width + spacer, plot_height, "b",
[text.halign.left, text.valign.top,
text.size(-1)])
c.writePDFfile(out_fname)
c.fill(p, [clientcolor, trafo.translate(0, -1.3 * r)])
return c
arrowcolor = color.grey(0.5)
text.set(text.LatexRunner)
text.preamble(r'\usepackage{arev}\usepackage[T1]{fontenc}')
unit.set(xscale=1.3)
c = canvas.canvas()
pos = [(0, 1), (sin(2 * pi / 3), cos(2 * pi / 3)),
(-sin(2 * pi / 3), cos(2 * pi / 3))]
sfak = 1.5
for x, y in pos:
c.insert(server(0.3), [trafo.translate(sfak * x, sfak * y)])
c.insert(client(), [trafo.scale(0.5).translated(3 * x, 3 * y + 0.15)])
c.stroke(path.line(2.7 * x, 2.7 * y, 1.9 * x, 1.9 * y), [
arrowcolor, deco.earrow.large, deco.barrow.large, style.linewidth.THick
])
for phi in (0, 120, 240):
c.stroke(
path.curve(-sfak * sin(2 * pi / 3) + 0.4, -0.5 * sfak + 0.15,
-sfak * sin(2 * pi / 3) + 0.8, -0.5 * sfak + 0.35,
sfak * sin(2 * pi / 3) - 0.8, -0.5 * sfak + 0.35,
sfak * sin(2 * pi / 3) - 0.4, -0.5 * sfak + 0.15), [
arrowcolor, deco.earrow.large, deco.barrow.large,
style.linewidth.THick,
trafo.rotate(phi)
])
c.insert(server(0.5, color.hsb(0.5, 0.8, 0.5), 0.13))
from pyx import metapost
from pyx.metapost.path import beginknot, endknot, smoothknot, tensioncurve
x0, y0 = tx0, ty0 = x, y
dx, dy = 1.5, 1.5
# Grid
for i in range(3):
c.stroke(path.line(x0+0.5*dx, y0-(i+1.0)*dy, x0+3.5*dx, y0-(i+1.0)*dy))
c.stroke(path.line(x0+(i+1.0)*dx, y0-0.5*dy, x0+(i+1.0)*dx, y0-3.5*dy))
c.stroke(path.rect(1.*dx + pip, -2.*dy + pip, dx-2*pip, dy-2*pip),
[green, style.linewidth.Thick, style.linestyle.dashed,
trafo.translate(tx0, ty0)])
def pair((x0, y0), (x1, y1), clr=None):
extra = [clr or blue, style.linewidth.Thick, style.linecap.round, trafo.translate(tx0, ty0)]
c.stroke(path.line(x0, y0, x1, y1), extra)
c.stroke(path.circle(x0, y0, 1.3*pip), extra)
c.stroke(path.circle(x1, y1, 1.3*pip), extra)
points0 = [
(1.3*dx, -1.7*dy), (1.3*dx, -2.5*dy),
(2.6*dx, -1.4*dy), (3.4*dx, -1.4*dy),
(1.7*dx, -1.7*dy), (1.7*dx, -2.5*dy)]
points = list(points0)
for nr, (label, boxcolor, symbolcolor, status) in enumerate(
(('working directory', color.hsb(0.87, 1, 0.6), color.rgb(0.6, 0,
0), 'modified'),
('staging area', color.hsb(0.2, 1, 0.6), color.rgb(0, 0.5, 0), 'staged'),
('repository (.git)', color.hsb(0.53, 1,
0.6), color.grey(0.3), 'committed'))):
xmid = nr * (wd + hdist) + 0.5 * wd
c.stroke(path.rect(nr * (wd + hdist), 0, wd, ht),
[deformer.smoothed(0.3), boxcolor, style.linewidth.Thick])
c.fill(path.rect(nr * (wd + hdist), ht + vdist, wd, htlabel),
[deformer.smoothed(0.3), boxcolor])
c.text(xmid, ht + vdist + 0.5 * htlabel, label,
[text.halign.center, text.valign.middle,
color.grey(1)])
c.insert(filesymbol(size, symbolcolor),
[trafo.translate(xmid, 0.55 * (ht - htlabel))])
c.text(xmid, 0.2 * (ht - htlabel), status,
[text.halign.center, symbolcolor])
ht = ht - htlabel
for nr, operation in enumerate(('git add', 'git commit')):
xmid = nr * (wd + hdist) + 0.5 * wd
c.stroke(
path.line(xmid + 0.5 * size + 0.1, 0.55 * ht,
xmid + wd + hdist - 0.5 * size - 0.1, 0.55 * ht),
[deco.earrow.large, style.linewidth.Thick])
cop = canvas.canvas()
optext = text.text(0, 0, operation,
[text.halign.center, text.valign.middle])
tblarge = optext.bbox().enlarged(0.1)
cop.fill(tblarge.path(), [deco.stroked([color.grey(0)]), color.grey(0.9)])
r'$\phi_\text{f}$')):
c.text((tick_outer + 0.3) * cos(_angle),
(tick_outer + 0.3) * sin(_angle), label,
[text.halign.center, text.valign.middle, endpointcolor])
if windingnumber:
c.text(0, -radius - 0.3, '$n={}$'.format(n),
[text.halign.center, text.valign.top])
c.stroke(spiral(radius, angle, n), [pathcolor, style.linewidth.Thick])
return c
radius = 1.5
text.set(engine=text.LatexEngine)
text.preamble(r'''\usepackage[sfdefault,lining,scaled=.85]{FiraSans}
\usepackage{newtxsf}''')
unit.set(vscale=1.2, wscale=1.3, xscale=1.3)
basename = os.path.splitext(sys.argv[0])[0]
c = canvas.canvas()
dx = 3.5 * radius
for nr, n in enumerate((0, -1)):
c.insert(winding(n, radius), [trafo.translate(nr * dx, 0)])
c.writePDFfile('{}_1'.format(basename))
c = canvas.canvas()
for nr, n in enumerate((1, -2, 2)):
c.insert(winding(n, radius, windingnumber=True),
[trafo.translate(nr * dx, 0)])
c.writePDFfile('{}_2'.format(basename))
'pentadecathlon': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
}
text.set(text.LatexRunner)
unit.set(xscale=4, wscale=2)
c = canvas.canvas()
xpos = 0
for k in ('blinker', 'beacon', 'toad', 'glider',
'pentadecathlon', 'pulsar'):
c.insert(draw_config(k), [trafo.translate(xpos, 0)])
wd = len(configs[k][0])
c.text(xpos+0.5*wd,
-0.5, r'\sffamily {}'.format(k),
[text.halign.center, text.valign.top])
xpos = xpos+wd+1
filename = os.path.splitext(sys.argv[0])[0]+'.png'
c.writeGSfile(filename, resolution=200)
c.stroke(path.curve(x-dist/3, -0.5*dist,
x+0.5*wd, -5*dist,
x+(lowerstride-0.5)*wd+lowerstride*dist, -5*dist,
x+lowerstride*wd+(lowerstride-0.7)*dist, -0.5*dist),
[deco.earrow.large])
c.text(x+0.5*lowerstride*wd+dist,-5.2*dist, r'\Large %i' % (lowerstride*8),
[text.halign.center, text.valign.top, textcolor])
return c
text.set(text.LatexRunner)
text.preamble(r'\usepackage[sfdefault,scaled=.85,lining]{FiraSans}\usepackage{newtxsf}')
unit.set(xscale=1.6, wscale=1.5)
c = canvas.canvas()
for nr, stride in enumerate((2, 3, 0)):
c.insert(make_stride_figure(stride), [trafo.translate(0, 6*nr)])
s1 = 8*stride
if stride:
s = ', '.join([str(s1), '8'])
else:
s = '8,'
c.text(0, 6*nr+2.5, '\\Large ({})'.format(s))
xoff = -5
yoff = 1
for nr, matrix in enumerate((r'$\begin{{pmatrix}}{} & {}\\{} & {}\\{} & {}\end{{pmatrix}}$',
r'$\begin{{pmatrix}}{} & {} & {}\\{} & {} & {}\end{{pmatrix}}$',
r'$\begin{{pmatrix}}{} & {} & {} & {} & {} & {}\end{{pmatrix}}$')):
m = matrix.format(*map(lambda x: '\\text{}'.format(x), range(6)))
c.text(xoff, 6*nr+yoff, '\\Large '+m, [text.halign.center, text.valign.middle])
gitlabfgcolor = color.grey(0.4)
gitlabbgcolor = color.grey(0.97)
maintainercolor = color.hsb(0.7, 1, 0.5)
usercolor = color.hsb(0.05, 1, 0.5)
c.stroke(path.rect(0, 0, wd, ht), [
deformer.smoothed(0.1), gitlabfgcolor, style.linewidth.Thick,
deco.filled([gitlabbgcolor])
])
clabel = canvas.canvas()
labeltext = text.text(0, 0, r'\textsf{\bfseries Gitlab}', [color.grey(1)])
extrawd = 0.15
labelbox = labeltext.bbox().enlarged(extrawd)
clabel.fill(labelbox.path(), [gitlabfgcolor, deformer.smoothed(0.1)])
clabel.insert(labeltext)
c.insert(clabel, [trafo.translate(extrawd, ht + extrawd)])
c.text(wd + 0.4, ht - 0.5, r'\footnotesize\textsf{read/write permissions}')
c.insert(read(1, usercolor), [trafo.translate(wd + 0.7, ht - 0.9)])
c.insert(write(1, usercolor), [trafo.translate(wd + 1.05, ht - 0.9)])
c.text(wd + 1.5, ht - 1.0, r'\footnotesize\textsf{user}', [usercolor])
c.insert(write(1, maintainercolor), [trafo.translate(wd + 1.05, ht - 1.3)])
c.insert(read(1, maintainercolor), [trafo.translate(wd + 0.7, ht - 1.3)])
c.text(wd + 1.5, ht - 1.4, r'\footnotesize\textsf{maintainer}',
[maintainercolor])
c.insert(repo('upstream', color.hsb(0.55, 1, 0.6), color.hsb(0.55, 0.1, 1)),
[trafo.translate(0.5, 2.8)])
c.insert(read(1, maintainercolor), [trafo.translate(0.85, 2.3)])
c.insert(write(1, maintainercolor), [trafo.translate(1.2, 2.3)])
c.insert(read(1, usercolor), [trafo.translate(1.65, 2.3)])
[text.halign.center, text.valign.middle])
c.stroke(path.rect(0, baseshape[0], shape[1], -shape[0]))
for nx in range(1, shape[1]):
c.stroke(path.line(nx, baseshape[0], nx, baseshape[0] - shape[0]))
for ny in range(1, shape[0]):
c.stroke(path.line(0, ny, shape[1], ny))
if not (shape == baseshape):
for nx in range(shape[1]):
for ny in range(shape[0]):
c.text(nx + 0.5, baseshape[0] - ny - 0.5,
str(baseshape[1] * ny + nx + 1),
[text.halign.center, text.valign.middle])
return c
text.set(text.LatexRunner)
text.preamble(
r'\usepackage[sfdefault,scaled=.85,lining]{FiraSans}\usepackage{newtxsf}')
unit.set(xscale=1.6, wscale=1.5)
c = canvas.canvas()
c.insert(array((3, 4)))
c.insert(array((1, )), [trafo.translate(5, 0)])
c.insert(array((4, )), [trafo.translate(10, 0)])
c.insert(array((3, )), [trafo.translate(5, -4.5)])
c.insert(array((3, 1)), [trafo.translate(10, -4.5)])
c.writePDFfile()
c.writeGSfile(device="png16m", resolution=600)
def main():
out_fname = sys.argv[1]
basedir = '/'.join(
os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
mm9_methods = {
'HiFive-Probability':
'%s/Analysis/hifive_mm9_ESC_prob_correlations.txt' % basedir,
'HiFive-Express':
'%s/Analysis/hifive_mm9_ESC_exp_correlations.txt' % basedir,
'HiFive-Binning':
'%s/Analysis/hifive_mm9_ESC_bin_correlations.txt' % basedir,
'HiCNorm': '%s/Analysis/hicnorm_mm9_ESC_correlations.txt' % basedir,
'HiCPipe': '%s/Analysis/hicpipe_mm9_ESC_correlations.txt' % basedir,
'Matrix-Balancing':
'%s/Analysis/mb_mm9_ESC_correlations.txt' % basedir,
}
hg19_methods = {
'HiFive-Probability':
'%s/Analysis/hifive_hg19_GM12878_prob_correlations.txt' % basedir,
'HiFive-Express':
'%s/Analysis/hifive_hg19_GM12878_exp_correlations.txt' % basedir,
'HiFive-Binning':
'%s/Analysis/hifive_hg19_GM12878_bin_correlations.txt' % basedir,
'HiCNorm':
'%s/Analysis/hicnorm_hg19_GM12878_correlations.txt' % basedir,
'HiCPipe':
'%s/Analysis/hicpipe_hg19_GM12878_correlations.txt' % basedir,
'Matrix-Balancing':
'%s/Analysis/mb_hg19_GM12878_correlations.txt' % basedir,
}
mm9_data = load_data(mm9_methods)
hg19_data = load_data(hg19_methods)
width = 16.8
spacer = 0.4
overall_width = (width - spacer * 2) / 2.6
c = canvas.canvas()
mm9_ranges_img, mm9_ranges_height = plot_dataset_ranges(
mm9_data, width, "MM9 ESC")
mm9_ranges_img.text(0, mm9_ranges_height, 'a',
[text.halign.left, text.valign.top,
text.size(-1)])
c.insert(mm9_ranges_img)
hg19_ranges_img, hg19_ranges_height = plot_dataset_ranges(
hg19_data, width, "HG19 GM12878")
hg19_ranges_img.text(0, hg19_ranges_height, 'b',
[text.halign.left, text.valign.top,
text.size(-1)])
c.insert(hg19_ranges_img,
[trafo.translate(0, -hg19_ranges_height - spacer)])
overall_height = mm9_ranges_height * 0.6
mm9_overall_img = plot_overall(mm9_data, overall_width, overall_height,
"MM9 ESC")
mm9_overall_img.text(0, overall_height + 0.1, 'c',
[text.halign.left, text.valign.top,
text.size(-1)])
c.insert(mm9_overall_img, [
trafo.translate(0, -hg19_ranges_height - overall_height - spacer * 2)
])
hg19_overall_img = plot_overall(hg19_data, overall_width, overall_height,
"HG19 GM12878")
hg19_overall_img.text(0, overall_height + 0.1, 'd',
[text.halign.left, text.valign.top,
text.size(-1)])
c.insert(hg19_overall_img, [
trafo.translate(overall_width * 1.6 + spacer * 2,
-hg19_ranges_height - overall_height - spacer * 2)
])
c.insert(plot_key(overall_width * 0.6 + 0.4, overall_height), [
trafo.translate(overall_width + spacer + 0.6,
-hg19_ranges_height - overall_height - spacer * 2)
])
c.writePDFfile(out_fname)
def plot_bargraph(data, width, height):
methods = ['HiCLib', 'HiCPipe', 'HiCNorm', 'HiFive-Probability', 'HiFive-Binning', 'HiFive-Express',
'HiFive-ExpressKR', 'HiFive-ExpressKR w/distance']
ho = 4.0
left_width = (width - ho) * 0.45
mid_width1 = (width - ho) * 0.3
mid_width2 = (width - ho) * 0.125
right_width = (width - ho) * 0.125
bar_height = height / len(methods) - 0.1
data_totals = {}
ranges = numpy.zeros((4, 2), dtype=numpy.float32)
for meth in data:
data_totals[meth] = find_total(data[meth])
if meth == 'HiCPipe':
ranges[1, 1] = data_totals[meth]
elif meth == 'HiCNorm':
ranges[2, 1] = data_totals[meth]
elif meth == 'HiFive-Probability':
ranges[3, 1] = data_totals[meth]
else:
ranges[0, 1] = max(ranges[0, 1], data_totals[meth])
ranges /= 60.0
ranges[0, 1] = 28.0
ranges[1, 0] = ranges[1, 1] - ranges[0, 1] / 0.45 * 0.3 * 0.9
ranges[1, 1] = ranges[1, 1] + ranges[0, 1] / 0.45 * 0.3 * 0.1
ranges[2, 0] = ranges[2, 1] - ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[2, 1] = ranges[2, 1] + ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[3, 0] = ranges[3, 1] - ranges[0, 1] / 0.45 * 0.125 * 0.5
ranges[3, 1] = ranges[3, 1] + ranges[0, 1] / 0.45 * 0.125 * 0.5
c = canvas.canvas()
g1 = graph.graphxy(width=left_width, height=height,
x=graph.axis.lin(painter=painter, min=0, max=ranges[0, 1]),
x2=graph.axis.lin(parter=None, min=0, max=ranges[0, 1]),
y=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g1)
g2 = graph.graphxy(width=mid_width1, height=height,
x=graph.axis.lin(painter=painter, min=ranges[1, 0], max=ranges[1, 1]),
x2=graph.axis.lin(parter=None, min=ranges[1, 0], max=ranges[1, 1]),
y2=graph.axis.lin(painter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g2, [trafo.translate(left_width, 0)])
g3 = graph.graphxy(width=mid_width2, height=height,
x=graph.axis.lin(painter=painter, min=ranges[2, 0], max=ranges[2, 1]),
x2=graph.axis.lin(parter=None, min=ranges[2, 0], max=ranges[2, 1]),
y2=graph.axis.lin(painter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g3, [trafo.translate(left_width + mid_width1, 0)])
g4 = graph.graphxy(width=right_width, height=height,
x=graph.axis.lin(painter=painter, min=ranges[3, 0], max=ranges[3, 1]),
x2=graph.axis.lin(parter=None, min=ranges[3, 0], max=ranges[3, 1]),
y2=graph.axis.lin(parter=None, min=0, max=1),
y=graph.axis.lin(painter=None, min=0, max=1))
c.insert(g4, [trafo.translate(left_width + mid_width1 + mid_width2, 0)])
split = canvas.canvas()
split.fill(path.path(path.moveto(-0.15, -0.2), path.lineto(0.05, 0.2), path.lineto(.15, 0.2),
path.lineto(-0.05, -0.2), path.closepath()), [color.cmyk.White])
split.stroke(path.line(-0.15, -0.2, 0.05, 0.2))
split.stroke(path.line(-0.05, -0.2, 0.15, 0.2))
c.insert(split, [trafo.translate(left_width, 0)])
c.insert(split, [trafo.translate(left_width, height)])
c.insert(split, [trafo.translate(left_width + mid_width1, 0)])
c.insert(split, [trafo.translate(left_width + mid_width1, height)])
c.insert(split, [trafo.translate(left_width + mid_width1 + mid_width2, 0)])
c.insert(split, [trafo.translate(left_width + mid_width1 + mid_width2, height)])
for i, meth in enumerate(methods):
c.insert(plot_bar(data[meth], ranges, bar_height, left_width / ranges[0, 1], split),
[trafo.translate(0, height - 0.05 - bar_height * (i + 1) - i * 0.1)])
c.text(-0.1, height * (len(methods) - i - 0.5) / len(methods), meth,
[text.halign.right, text.valign.middle, text.size(-2)])
c.text((width - ho) / 2.0, -0.35, "Runtime (minutes)",
[text.halign.center, text.valign.top, text.size(-2)])
return c
def plot_overall(data, width, height, name):
vo = 0.55
ho = 0.7
plot_width = width - ho
plot_height = height - vo - 0.3
c = canvas.canvas()
methods = data.keys()
methods.sort()
bar_colors = []
cis_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(
data[methods[0]]['interaction'] == 'cis')])
trans_binsizes = numpy.unique(data[methods[0]]['binsize'][numpy.where(
data[methods[0]]['interaction'] == 'trans')])
Y = numpy.zeros(
(len(methods), cis_binsizes.shape[0] + trans_binsizes.shape[0]),
dtype=numpy.float32)
for i, method in enumerate(methods):
for j, binsize in enumerate(cis_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'cis') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j] = data[method]['correlation'][where]
for j, binsize in enumerate(trans_binsizes):
where = numpy.where((data[method]['binsize'] == binsize) *
(data[method]['interaction'] == 'trans') *
(data[method]['range'] == 0))
if where[0].shape[0] > 0:
Y[i, j +
cis_binsizes.shape[0]] = data[method]['correlation'][where]
bar_colors.append(method_colors[method])
Y = numpy.array(Y)
g = graph.graphxy(
width=plot_width,
height=plot_height,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
for i in range(len(methods)):
g.plot(
graph.data.points(zip(zip(range(Y.shape[1]), [i] * Y.shape[1]),
Y[i, :]),
xname=1,
y=2),
[graph.style.changebar([method_colors[methods[i]]])])
c.insert(g, [trafo.translate(ho, vo)])
for i, label in enumerate(["10Kb", "50Kb", "250Kb", "1Mb", "250Kb",
"1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 6.0, vo - 0.05, "%s" % label,
[text.halign.center, text.valign.top,
text.size(-3)])
c.text(ho + plot_width * 2.0 / 6.0, 0.05, "cis",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(
path.line(ho + 0.2, vo * 0.5, ho - 0.2 + plot_width * 4.0 / 6.0,
vo * 0.5), [style.linewidth.THin])
c.text(ho + plot_width * 5.0 / 6.0, 0.05, "trans",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(
path.line(ho + 0.2 + plot_width * 4.0 / 6.0, vo * 0.5,
ho - 0.2 + plot_width, vo * 0.5), [style.linewidth.THin])
c.text(
0, plot_height * 0.5 + vo, "Correlation",
[text.halign.center, text.valign.top,
text.size(-3),
trafo.rotate(90)])
c.text(plot_width * 0.5 + ho, height, name,
[text.halign.center, text.valign.top,
text.size(-3)])
return c
def main():
width = 16.8
out_fname = sys.argv[1]
basedir = "%s/Analysis/Timing" % '/'.join(
os.path.dirname(os.path.realpath(__file__)).split('/')[:-2])
data_fnames = {
"HiFive-Probability": {
'0': "%s/hifive_data" % basedir,
'1': "%s/hifive_project" % basedir,
'3': '%s/hifive_prob' % basedir,
'4': "%s/hifive_prob_heatmap" % basedir
},
"HiFive-Binning": {
'0': "%s/hifive_data" % basedir,
'1': "%s/hifive_project_nodist" % basedir,
'3': '%s/hifive_bin' % basedir,
'4': "%s/hifive_bin_heatmap" % basedir
},
"HiFive-Express": {
'0': "%s/hifive_data" % basedir,
'1': "%s/hifive_project" % basedir,
'3': '%s/hifive_exp' % basedir,
'4': "%s/hifive_exp_heatmap" % basedir
},
"HiFive-ExpressKR": {
'0': "%s/hifive_data" % basedir,
'1': "%s/hifive_project_nodist" % basedir,
'3': '%s/hifive_expKR' % basedir,
'4': "%s/hifive_expKR_heatmap" % basedir
},
"HiFive-ExpressKR w/distance": {
'0': "%s/hifive_data" % basedir,
'1': "%s/hifive_project" % basedir,
'3': '%s/hifive_expKRdist' % basedir,
'4': "%s/hifive_expKRdist_heatmap" % basedir
},
"HiCPipe": {
'0': "%s/bam2raw" % basedir,
'1': "%s/hicpipe_data" % basedir,
'2': '%s/hicpipe_binning' % basedir,
'3': '%s/hicpipe_norm' % basedir,
'4': '%s/hicpipe_heatmap' % basedir
},
"HiCLib": {
'0': "%s/hiclib_mapping" % basedir,
'1': '%s/hiclib_data' % basedir,
'3': "%s/hiclib_norm" % basedir,
'4': '%s/hiclib_heatmap' % basedir
},
"HiCNorm": {
'0': "%s/bam2raw" % basedir,
'1': "%s/hicpipe_data" % basedir,
"2": "%s/hicnorm_data" % basedir,
'3': '%s/hicnorm_norm' % basedir
},
}
data = load_data(data_fnames)
c = canvas.canvas()
c.insert(plot_bargraph(data, width, 4.0), [trafo.translate(4.0, 0)])
c.insert(plot_key(width * 0.3, 1.5),
[trafo.translate(width * 0.75 - 1.0, 0.2)])
c.writePDFfile(out_fname)
def plot_overall(data0, data1, width, height):
vo = 1.15
ho = 1.15
plot_width = width - ho
plot_height = height - vo
c = canvas.canvas()
cis_binsizes = numpy.unique(
data0['binsize'][numpy.where(data0['interaction'] == 'cis')])
trans_binsizes = numpy.unique(
data0['binsize'][numpy.where(data0['interaction'] == 'trans')])
ymin = numpy.inf
ymax = -numpy.inf
Y = numpy.zeros((cis_binsizes.shape[0] + trans_binsizes.shape[0]),
dtype=numpy.float32)
for j, binsize in enumerate(cis_binsizes):
where = numpy.where(
(data0['binsize'] == binsize) * (data0['interaction'] == 'cis') *
(data0['range'] < 0))
where1 = numpy.where(
(data1['binsize'] == binsize) * (data1['interaction'] == 'cis') *
(data1['range'] < 0))
if where[0].shape[0] > 0:
Y[j] = (data1['correlation'][where1] - data0['correlation'][where])
ymin = min(ymin, Y[j])
ymax = max(ymax, Y[j])
for j, binsize in enumerate(trans_binsizes):
where = numpy.where(
(data0['binsize'] == binsize) * (data0['interaction'] == 'trans') *
(data0['range'] < 0))
where1 = numpy.where(
(data1['binsize'] == binsize) * (data1['interaction'] == 'trans') *
(data1['range'] < 0))
if where[0].shape[0] > 0:
Y[j + cis_binsizes.shape[0]] = (data1['correlation'][where1] -
data0['correlation'][where])
ymin = min(ymin, Y[j + cis_binsizes.shape[0]])
ymax = max(ymax, Y[j + cis_binsizes.shape[0]])
yspan = ymax - ymin
ymin -= yspan * 0.05
ymax += yspan * 0.05
Y = numpy.array(Y)
g = graph.graphxy(
width=plot_width,
height=plot_height,
x=graph.axis.bar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter, min=ymin, max=ymax),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
y0 = plot_height * (-ymin) / (ymax - ymin)
g.stroke(
path.line(0,
plot_height * (-ymin) / (ymax - ymin), plot_width,
plot_height * (-ymin) / (ymax - ymin)),
[style.linestyle.dotted, style.linewidth.THin])
w0 = plot_width / Y.shape[0]
w1 = w0 / 1.5
for j in range(Y.shape[0]):
x = j * w0 + 0.25 * w1
y = plot_height * (Y[j] - ymin) / (ymax - ymin)
g.fill(path.rect(x, y0, w1, y - y0))
c.insert(g, [trafo.translate(ho, vo)])
for i, label in enumerate(["10Kb", "50Kb", "250Kb", "1Mb", "250Kb",
"1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 6.0, vo - 0.05, "%s" % label, [
text.halign.right, text.valign.middle,
text.size(-3),
trafo.rotate(90)
])
c.text(ho + plot_width * 2.0 / 6.0, 0, "cis",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(path.line(ho + 0.2, 0.3, ho - 0.2 + plot_width * 4.0 / 6.0, 0.3),
[style.linewidth.THin])
c.text(ho + plot_width * 5.0 / 6.0, 0, "trans",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(
path.line(ho + 0.2 + plot_width * 4.0 / 6.0, 0.3,
ho - 0.2 + plot_width, 0.3), [style.linewidth.THin])
c.text(
0, plot_height * 0.5 + vo, r"$r_{Poisson} - r_{binomial}$",
[text.halign.center, text.valign.top,
text.size(-2),
trafo.rotate(90)])
c.text(0, height, 'b', [text.halign.left, text.valign.top, text.size(-1)])
return c
y0 = 3
dy = 0.07
c.fill(path.rect(x0, y0, 5*size, size),
[color.grey(0.5), deco.stroked([color.grey(0.5)])])
c.stroke(path.rect(x0+5*size, y0, 5*size, size))
c.stroke(path.rect(x0+10*size, y0, 6*size, size))
for n in range(len(codepointbinary)):
c.text(x0+(n+0.5)*size, y0+dy, r"\sffamily %i" % codepointbinary[n],
[text.halign.center])
p = path.path(path.moveto(0.2*size, size+0.03),
path.lineto(0.2*size, size+0.07),
path.lineto(3.8*size, size+0.07),
path.lineto(3.8*size, size+0.03))
for n in range(bits//4):
c.stroke(p, [trafo.translate(4*n*size, y0)])
c.text((4*n+2)*size, size+0.14+y0, r"\sffamily %X" %
(codepoint >> (bits//4-n-1)*4 & 0x0f),
[text.halign.center])
utf8code = 0xC080 \
+ (((codepoint >> 6) & 0x1f) << 8) \
+ (codepoint & 0x3f)
utf8codebinary = [(utf8code & 2**n)/2**n for n in range(bits)]
utf8codebinary.reverse()
y1 = 2
c.fill(path.rect(x0, y1, 3*size, size),
[color.grey(0.8), deco.stroked([color.grey(0.8)])])
c.fill(path.rect(x0+8*size, y1, 2*size, size),
[color.grey(0.8), deco.stroked([color.grey(0.8)])])
def plot_overall(data0, data1, width, height):
vo = 0.55
ho = 1.1
plot_width = width - ho
plot_height = height - vo
c = canvas.canvas()
methods = data0.keys()
methods.sort()
bar_colors = []
cis_binsizes = numpy.unique(data0[methods[0]]['binsize'][numpy.where(
data0[methods[0]]['interaction'] == 'cis')])
trans_binsizes = numpy.unique(data0[methods[0]]['binsize'][numpy.where(
data0[methods[0]]['interaction'] == 'trans')])
ymin = numpy.inf
ymax = -numpy.inf
Y = numpy.zeros(
(len(methods), cis_binsizes.shape[0] + trans_binsizes.shape[0]),
dtype=numpy.float32)
for i, method in enumerate(methods):
for j, binsize in enumerate(cis_binsizes):
where = numpy.where((data0[method]['binsize'] == binsize) *
(data0[method]['interaction'] == 'cis') *
(data0[method]['range'] < 0))
where1 = numpy.where((data1[method]['binsize'] == binsize) *
(data1[method]['interaction'] == 'cis') *
(data1[method]['range'] < 0))
if where[0].shape[0] > 0:
Y[i, j] = (data1[method]['correlation'][where1] -
data0[method]['correlation'][where])
ymin = min(ymin, Y[i, j])
ymax = max(ymax, Y[i, j])
for j, binsize in enumerate(trans_binsizes):
where = numpy.where((data0[method]['binsize'] == binsize) *
(data0[method]['interaction'] == 'trans') *
(data0[method]['range'] < 0))
where1 = numpy.where((data1[method]['binsize'] == binsize) *
(data1[method]['interaction'] == 'trans') *
(data1[method]['range'] < 0))
if where[0].shape[0] > 0:
Y[i, j + cis_binsizes.shape[0]] = (
data1[method]['correlation'][where1] -
data0[method]['correlation'][where])
ymin = min(ymin, Y[i, j + cis_binsizes.shape[0]])
ymax = max(ymax, Y[i, j + cis_binsizes.shape[0]])
bar_colors.append(method_colors[method])
yspan = ymax - ymin
ymin -= yspan * 0.05
ymax += yspan * 0.05
Y = numpy.array(Y)
g = graph.graphxy(
width=plot_width,
height=plot_height,
x=graph.axis.nestedbar(painter=graph.axis.painter.bar(nameattrs=None)),
y=graph.axis.lin(painter=painter, min=ymin, max=ymax),
x2=graph.axis.lin(parter=None, min=0, max=1),
y2=graph.axis.lin(parter=None, min=0, max=1))
y0 = plot_height * (-ymin) / (ymax - ymin)
g.stroke(
path.line(0,
plot_height * (-ymin) / (ymax - ymin), plot_width,
plot_height * (-ymin) / (ymax - ymin)),
[style.linestyle.dotted, style.linewidth.THin])
w0 = plot_width / Y.shape[1]
w1 = w0 / (len(methods) + 0.5)
for i in range(len(methods)):
for j in range(Y.shape[1]):
x = j * w0 + (i + 0.25) * w1
y = plot_height * (Y[i, j] - ymin) / (ymax - ymin)
g.stroke(path.rect(x, y0, w1, y - y0),
[deco.filled([method_colors[methods[i]]])])
c.insert(g, [trafo.translate(ho, vo)])
for i, label in enumerate(["10Kb", "50Kb", "250Kb", "1Mb", "250Kb",
"1Mb"]):
c.text(ho + plot_width * (i + 0.5) / 6.0, vo - 0.05, "%s" % label,
[text.halign.center, text.valign.top,
text.size(-3)])
c.text(ho + plot_width * 2.0 / 6.0, 0.05, "cis",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(
path.line(ho + 0.2, vo * 0.5, ho - 0.2 + plot_width * 4.0 / 6.0,
vo * 0.5), [style.linewidth.THin])
c.text(ho + plot_width * 5.0 / 6.0, 0.05, "trans",
[text.halign.center, text.valign.bottom,
text.size(-3)])
c.stroke(
path.line(ho + 0.2 + plot_width * 4.0 / 6.0, vo * 0.5,
ho - 0.2 + plot_width, vo * 0.5), [style.linewidth.THin])
c.text(
0, plot_height * 0.5 + vo, r"$r_{0K} - r_{500K}$",
[text.halign.center, text.valign.top,
text.size(-2),
trafo.rotate(90)])
return c
def interface(): # <<<
c = None
for p in [
# ordinary open path:
mppath.path([
beginknot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(4, 9),
curve(),
knot(1, 7),
curve(),
endknot(3, 5)
], epsilon),
# path containing two open subpaths:
mppath.path([
beginknot(0, 0),
curve(),
endknot(6, 4),
beginknot(4, 9),
curve(),
knot(1, 7),
curve(),
endknot(3, 5)
], epsilon),
# closed path:
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(4, 9),
curve(),
knot(1, 7),
curve(),
knot(3, 5),
curve()
], epsilon),
# open path, but with endpoints in the middle:
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
endknot(4, 9),
beginknot(1, 7),
curve(),
knot(3, 5),
curve()
], epsilon),
# the same path in the right order
mppath.path([
beginknot(1, 7),
curve(),
knot(3, 5),
curve(),
knot(0, 0),
curve(),
knot(6, 4),
curve(),
endknot(4, 9)
], epsilon),
# include a line
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
roughknot(4, 9),
line(),
roughknot(1, 7),
curve(),
knot(3, 5),
curve()
], epsilon),
# XXX the endpoints have "open" at their other sides, not "curl" as in the open example above
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(4, 9),
line(),
knot(1, 7),
curve(),
knot(3, 5),
curve()
], epsilon),
mppath.path(
[knot(0, 0),
curve(),
knot(6, 4),
line(),
knot(3, 5),
curve()], epsilon),
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(3, 5),
curve()
], epsilon),
# TODO the internal mp_make_choices treats this as closed, but the last curve is not plotted:
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(4, 9),
line(),
knot(1, 7),
curve(),
knot(3, 5)
], epsilon),
# include a line with given angles
mppath.path([
knot(0, 0),
curve(),
knot(6, 4),
curve(),
knot(4, 9),
line(keepangles=True),
knot(1, 7),
curve(),
knot(3, 5),
curve()
], epsilon),
# include rough knots
mppath.path([
beginknot(0, 0),
curve(),
roughknot(6, 4, langle=90),
curve(),
roughknot(4, 9, langle=-90),
line(keepangles=True),
roughknot(1, 7, lcurl=3),
curve(),
endknot(3, 5, angle=0)
], epsilon),
]:
cc = canvas.canvas()
cc.stroke(p, [deco.shownormpath(), deco.earrow.normal])
if c is None:
c = cc
else:
c.insert(cc, [
trafo.translate(c.bbox().right() - cc.bbox().left() + 0.5, 0)
])
c.writePDFfile()
c.writeEPSfile()
c.writeSVGfile()
path.closepath())
c.fill(p, [clientcolor, trafo.translate(0, -1.3*r)])
return c
random.seed(812357)
arrowcolor = color.grey(0.5)
text.set(text.LatexRunner)
text.preamble(r'\usepackage{arev}\usepackage[T1]{fontenc}')
unit.set(xscale=1.3)
c = canvas.canvas()
pos = [(0, 1), (sin(2*pi/3), cos(2*pi/3)), (-sin(2*pi/3), cos(2*pi/3))]
for x, y in pos:
c.insert(server(0.3), [trafo.translate(1.5*x, 1.5*y)])
c.insert(client(), [trafo.scale(0.5).translated(3*x, 3*y+0.15)])
c.stroke(path.line(2.7*x, 2.7*y, 1.9*x, 1.9*y),
[arrowcolor, deco.earrow.large, deco.barrow.large, style.linewidth.THick])
pos.append(pos[0])
fak = 0.3
for (x1, y1), (x2,y2) in zip(pos[:-1], pos[1:]):
c.stroke(path.line(1.5*x1+fak*(x2-x1), 1.5*y1+fak*(y2-y1),
1.5*x2-fak*(x2-x1), 1.5*y2-fak*(y2-y1)),
[arrowcolor, deco.earrow.Large, deco.barrow.Large, style.linewidth.THIck])
dy = 0.8
dx = 1.5
versionoff = 1.5
cf = canvas.canvas()
hueoff = 0.17
def update(self, *args):
"""update the population in self.world
"""
n = signal.convolve2d(self.world, self.v, mode='same', boundary='wrap')
self.world = self.world & (n == 2)
self.world = self.world | (n == 3)
c = canvas.canvas()
dx = 0.3
h = 4
w = 6.5
p = path.rect(-dx, -dx, w + 2 * dx, h + 2 * dx)
p = deformer.smoothed(0.5).deform(p)
c.fill(p, [color.grey(0.5), trafo.translate(0.05, -0.05)])
c1 = canvas.canvas([canvas.clip(p)])
c1.fill(p, [color.grey(0.9)])
np.random.seed = 42
game = Conway(300)
for _ in range(15):
game.update()
world = game.world
xoff = -0.5 * w - dx
yoff = -0.5 * h - dx
delta = 0.1
for nx in range(game.size):
for ny in range(game.size):
if world[nx, ny]:
myblue = color.rgb(0, 0, 0.8)
for c, start in ((frontplane, 0), (backplane, xcells * ycells)):
c.stroke(
path.rect(0, 0, 4, 3),
[deco.filled([color.grey(1), color.transparency(0.2)])])
for x in range(1, xcells):
c.stroke(path.line(x, 0, x, ycells))
for y in range(1, ycells):
c.stroke(path.line(0, y, xcells, y))
for entry in range(xcells * ycells):
x = entry % 4
y = ycells - entry // 4
c.text(x + 0.5, y - 0.5, str(start + entry),
[text.halign.center, text.valign.middle])
c = canvas.canvas()
c.insert(backplane, [trafo.translate(xshift, yshift)])
for x, y in product((0, xcells), (0, ycells)):
c.stroke(path.line(x, y, x + xshift, y + yshift))
c.insert(frontplane)
dx = -dist * yshift / sqrt(xshift**2 + yshift**2)
dy = dist * xshift / sqrt(xshift**2 + yshift**2)
c.stroke(path.line(dx, ycells + dy, dx + xshift, ycells + dy + yshift),
[deco.earrow, myred])
c.text(0.5 * xshift + 2 * dx, ycells + 0.5 * yshift + 2 * dy, 'axis 0', [
text.halign.center, myred,
trafo.rotate(180 / pi * atan2(yshift, xshift))
])
c.stroke(path.line(-dist, ycells, -dist, 0), [deco.earrow, mygreen])
c.text(-2 * dist, 0.5 * ycells, 'axis 1',
[text.halign.center, mygreen,
trafo.rotate(90)])
from pyx import canvas, color, deco, deformer, graph, path, style, trafo
def ellipse(r, scaley, fillcolor):
ce = canvas.canvas()
ce.fill(path.circle(0, 0, r), [trafo.scale(1, scaley), fillcolor])
return ce
c = canvas.canvas()
dx = 0.3
h = 4
w = 6.5
p = path.rect(-dx, -dx, w + 2 * dx, h + 2 * dx)
p = deformer.smoothed(0.5).deform(p)
c.fill(p, [color.grey(0.5), trafo.translate(0.05, -0.05)])
c1 = canvas.canvas([canvas.clip(p)])
c1.fill(p, [color.grey(0.9)])
r = 1
brown1 = color.rgb(148 / 255, 77 / 255, 48 / 255)
brown2 = color.rgb(193 / 255, 91 / 255, 49 / 255)
red1 = color.rgb(200 / 255, 0, 0)
red2 = color.rgb(220 / 255, 0.5, 0.5)
flame = color.rgb(248 / 255, 212 / 255, 27 / 255)
c2 = canvas.canvas()
c2.insert(ellipse(r, 0.5, brown1))
c2.fill(path.rect(-r, 0, 2 * r, 0.5 * r), [brown1])
c2.insert(ellipse(r, 0.5, brown2), [trafo.translate(0, 0.5 * r)])
c2.insert(ellipse(0.2 * r, 0.5, red1), [trafo.translate(0, 0.5 * r)])
for nr, (label, boxcolor, symbolcolor, status) in enumerate(
(('working directory', color.hsb(0.87, 1, 0.6), color.rgb(0.6, 0,
0), 'modified'),
('staging area', color.hsb(0.2, 1, 0.6), color.rgb(0, 0.5, 0), 'staged'),
('repository (.git)', color.hsb(0.53, 1,
0.6), color.grey(0.3), 'committed'))):
xmid = nr * (wd + hdist) + 0.5 * wd
c.stroke(path.rect(nr * (wd + hdist), 0, wd, ht),
[deformer.smoothed(0.3), boxcolor, style.linewidth.Thick])
c.fill(path.rect(nr * (wd + hdist), ht + vdist, wd, htlabel),
[deformer.smoothed(0.3), boxcolor])
c.text(xmid, ht + vdist + 0.5 * htlabel, label,
[text.halign.center, text.valign.middle,
color.grey(1)])
c.insert(filesymbol(size, symbolcolor), [trafo.translate(xmid, 0.5 * ht)])
c.text(xmid, 0.2 * ht, status, [text.halign.center, symbolcolor])
for nr, operation in enumerate(('git add', 'git commit')):
xmid = nr * (wd + hdist) + 0.5 * wd
c.stroke(
path.line(xmid + 0.5 * size + 0.1, 0.5 * ht,
xmid + wd + hdist - 0.5 * size - 0.1, 0.5 * ht),
[deco.earrow.large, style.linewidth.Thick])
cop = canvas.canvas()
optext = text.text(0, 0, operation,
[text.halign.center, text.valign.middle])
tblarge = optext.bbox().enlarged(0.1)
cop.fill(tblarge.path(), [deco.stroked([color.grey(0)]), color.grey(0.9)])
cop.insert(optext)
c.insert(
cop,
def rect(i0, j0, di=1, dj=1, txt=None):
extra = [green, style.linewidth.Thick, style.linestyle.dashed, trafo.translate(x, y)]
c.stroke(path.rect((i0-0.5)*dx, (j0-0.5)*dy, di*dx, dj*dy), extra)
if txt:
c.text((i0+di-0.5)*dx, (j0+dj-0.5)*dy-pip, txt,
[trafo.translate(x, y), text.halign.boxright, text.valign.top])
c = canvas.canvas()
r = 1
c.insert(server(r))
c.text(0, 0.5 * r + 0.3, 'central server', [text.halign.center])
h = 1.7
l = 2
for phi in (-30, 0, 30):
c.stroke(path.line(0, -h, 0, -h - l), [
arrowcolor, style.linewidth.THICK, deco.barrow.LArge,
deco.earrow.LArge,
trafo.rotate(phi)
])
for dx, dy in ((-2, -3.7), (0, -4.2), (2, -3.7)):
c.insert(client(), [trafo.translate(dx, dy)])
c.text(0, -5.5, 'clients', [text.halign.center])
dy = 0.8
dx = 1.5
versionoff = 1.5
cf = canvas.canvas()
hueoff = 0.17
nr_revisions = 0
for nr, (name, versions) in enumerate(
(('file 1', (0, 2, 4, 5)), ('file 2', (0, 1, 2, 3, 5)), ('file 3', (1, 4,
5)))):
nr_revisions = max(nr_revisions, max(versions))
hue = hueoff + nr / 3
cf.text(0, -nr * dy, name, [color.hsb(hue, 1, 0.5), text.valign.middle])
for nver, (v1, v2) in enumerate(zip(versions[:-1], versions[1:])):
