def plot_dataset_ranges(data, width, label):
methods = data.keys()
binsizes = numpy.unique(data[methods[0]]['binsize'])
ho = 0.4
ho2 = 0.4
vo = 0.6
spacer = 0.25
plot_width = (width - ho * 2 -
(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)
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(width, plot_height * 0.5 + vo, label, [
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 draw(self):
"""draw the text!!"""
for layer in self.sectors:
radius = self.sectors[layer]['radius']
letter_radius = radius + 0.25 * self.sector_width
prev_radian = 0
for radian in self.sectors[layer]['letters']:
end = False
letter = self.sectors[layer]['letters'][radian][0]
if len(letter) > 1:
end = True
freq = self.sectors[layer]['letters'][radian][1]
offset = False
cur_radian = radian
if (radian - prev_radian) * letter_radius < 0.22:
cur_radian = prev_radian + 0.22 / letter_radius
prev_radian = cur_radian
offset = True
centroid_x = radius * cos(radian) + self.xo
centroid_y = radius * sin(radian) + self.yo
if end:
letter_x = radius * cos(cur_radian) + self.xo
letter_y = radius * sin(cur_radian) + self.yo
else:
letter_x = letter_radius * cos(cur_radian) + self.xo
letter_y = letter_radius * sin(cur_radian) + self.yo
# rotate the text accordingly
transform = trafo.rotate(radian * 180 / pi)
if cur_radian > pi / 2 and cur_radian < (3 * pi / 2):
transform = trafo.rotate(180 + radian * 180 / pi)
# if this condition is true then the letter is actually the
# whole word, it is an end sector, so display the frequency
if len(letter) > 1:
letter += ' '
letter += str(freq)
# the random floats are me tuning the color just right lol
text_color = color.rgb(0, 0.0784 * 1.4, 0.156 * 1.4)
self.canvas.text(
letter_x, letter_y, r"\texttt{" + letter + '}', [
text.halign.center, text.valign.middle, transform,
text.size.scriptsize, text_color
])
if offset:
self.canvas.stroke(
path.line(centroid_x, centroid_y, letter_x, letter_y),
[style.linewidth(0.0035), text_color])
self.canvas.fill(path.circle(centroid_x, centroid_y, 0.0065),
[text_color])
prev_radian = cur_radian
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(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 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 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.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.stroke(breakline1, self.defaultbreaklinesattrs + self.breaklinesattrs)
canvas.stroke(breakline2, self.defaultbreaklinesattrs + self.breaklinesattrs)
_title.paint(self, canvas, data, axis, axispos)
def signature(self, deg_max=6, padded=False, has_border=False):
""" For a visualization of glyphs, lay out in a 2D grid PNG file. """
self.scale()
sig = canvas.canvas([trafo.rotate(90), trafo.mirror(0)])
scale = 1.5
if padded or has_border:
sig_margin = 0.2
x = (deg_max + 1) * scale + (1.5 * sig_margin)
border_path = path.path(path.moveto(0, 0), path.lineto(0, x),
path.lineto(x, x), path.lineto(x, 0),
path.closepath())
if padded:
border_color = color.cmyk.White
if has_border:
border_color = color.cmyk.Gray
sig.stroke(border_path, [
border_color,
trafo.translate(-sig_margin * 2, -sig_margin * 2),
style.linewidth(.025)
])
for index in self.glist:
if len(index) > 2:
c = degree_glyph(index[0], index[1], index[2],
(self.mincount, self.maxcount))
else:
c = degree_glyph(index[0], index[1], 1,
(self.mincount, self.maxcount))
sig.insert(c,
[trafo.translate(index[0] * scale, (index[1]) * scale)
]) # text writing requires full latex
return sig
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 plate_circle_layer(plate, information, message, plate_radius=32.6):
outerclip = 39.6
box_xoffset = 1.
box_xsize = 4.
box_ysize = 16.
text_ybuffer = 0.5
text_xbuffer = 0.3
clippath = path.circle(0., 0., outerclip)
plate_clipobject = canvas.clip(clippath)
plate_circle = canvas.canvas([plate_clipobject])
plate_circle.stroke(path.circle(0., 0., plate_radius),
[style.linewidth.THICk])
plate_circle.stroke(
path.line(-plate_radius + box_xoffset, -box_ysize * 0.5,
-plate_radius + box_xoffset - box_xsize, -box_ysize * 0.5),
[style.linewidth.THICk])
plate_circle.stroke(
path.line(-plate_radius + box_xoffset - box_xsize, -box_ysize * 0.5,
-plate_radius + box_xoffset - box_xsize, box_ysize * 0.5),
[style.linewidth.THICk])
plate_circle.stroke(
path.line(-plate_radius + box_xoffset, box_ysize * 0.5,
-plate_radius + box_xoffset - box_xsize, box_ysize * 0.5),
[style.linewidth.THICk])
tab_path = path.line(-plate_radius - text_xbuffer,
-box_ysize * 0.5 + text_ybuffer,
-plate_radius - text_xbuffer,
box_ysize * 0.5 - text_ybuffer)
tab_text = r"\font\myfont=cmr10 at 100pt {\myfont " + str(plate) + "}"
plate_circle.draw(tab_path, [deco.curvedtext(tab_text)])
information_path = (path.circle(0., 0., plate_radius).transformed(
trafo.rotate(90.)))
plate_circle.draw(information_path, [
deco.curvedtext(information,
textattrs=[text.valign.top, text.vshift.topzero])
])
message_path = (path.circle(0., 0.,
plate_radius).transformed(trafo.rotate(-90.)))
plate_circle.draw(message_path, [
deco.curvedtext(message,
textattrs=[text.valign.top, text.vshift.topzero])
])
return plate_circle
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 trafo(self, dx, dy):
direction = self.direction + math.atan2(dy, dx) * 180 / math.pi
while (direction > 180 + self.epsilon):
direction -= 360
while (direction < -180 - self.epsilon):
direction += 360
while (direction > 90 + self.epsilon):
direction -= 180
while (direction < -90 - self.epsilon):
direction += 180
return trafomodule.rotate(direction)
def trafo(self, dx, dy):
direction = self.direction + math.atan2(dy, dx) * 180 / math.pi
while (direction > 180 + self.epsilon):
direction -= 360
while (direction < -180 - self.epsilon):
direction += 360
while (direction > 90 + self.epsilon):
direction -= 180
while (direction < -90 - self.epsilon):
direction += 180
return trafomodule.rotate(direction)
def plot_dataset_ranges(data, width, label):
methods = data.keys()
binsizes = numpy.unique(data[methods[0]]['binsize'])
ho = 0.4
ho2 = 0.4
vo = 0.6
spacer = 0.25
plot_width = (width - ho * 2 - (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)
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(width, plot_height * 0.5 + vo, label,
[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 tetra(x, y, count=None, subcount=None, rev=1, back=True, front=True, reflect=False):
if back:
circle(x, y, r, shade)
rr = 1.0*r
if subcount is not None:
ps = []
for i in range(3):
theta1 = rev*2*(i+subcount)*pi/3
if i==0:
# start of curve
x1, y1 = x+rr*sin(theta1), y+rr*cos(theta1)
ps.append((x1, y1))
if i==1:
x1, y1 = x+0.7*r*sin(theta1), y+0.7*r*cos(theta1)
ps.append((x1, y1))
else:
x1, y1 = x+0.4*r*sin(theta1), y+0.4*r*cos(theta1)
ps.append((x1, y1))
if i==2:
# end of curve
x1, y1 = x+1.0*rr*sin(theta1), y+1.0*rr*cos(theta1)
ps.append((x1, y1))
c.stroke(path.path(
path.moveto(*ps[0]),
path.lineto(*ps[1]),
path.lineto(*ps[2]),
path.lineto(*ps[3]),
path.lineto(*ps[4])),
st_curve+[deformer.smoothed(0.6)])
if front:
for theta1 in [0., 2*pi/3, 4*pi/3]:
x1, y1 = x+0.5*r*sin(theta1), y+0.5*r*cos(theta1)
circle(x1, y1, r0, white)
if count is not None:
assert 0<=count<=2
s = 0.86*r
r1 = 2.4*r0
extra = []
#c.text(x, y, count)
if reflect:
#count = [0, 1, 2][count]
extra.append(trafo.scale(x=x, y=y, sx=-1, sy=1))
extra += [trafo.rotate(-count*120, x=x, y=y)]
t = Turtle(x1, y1-r1, -pi/2).right(pi, r1).fwd(s).right(pi, r1).fwd(s)
t.stroke(extra)
t.stroke(extra+[deco.earrow()])
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 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 RectMid(canv,
pt,
w,
h,
fi=0,
linewidth=LINE_DEF_WIDTH,
linecolor=LINE_DEF_COLOR,
fillcolor=None,
mstyle=[]):
rect = path.rect(pt.x, pt.y - h / 2, w, h)
rto = trafo.rotate(fi, pt.x, pt.y)
if fillcolor is not None:
canv.fill(rect, [fillcolor, rto])
canv.stroke(rect, [style.linewidth(linewidth), linecolor, rto] + mstyle)
def jog(cls, paths, length=0.5, deg=10):
if not isinstance(paths, list):
paths = [paths]
x, y = [
coord / unit.length(1)
for coord in paths[-1].tangent(paths[-1].end()).atend()
]
d = degrees(atan2(y, x))
begin = P(*paths[-1].tangent(paths[-1].end()).atbegin())
end = P(*paths[-1].tangent(paths[-1].end()).atend())
tan = end - begin
d = degrees(atan2(*[coord / unit.length(1) for coord in tan][::-1]))
dp = trafo.rotate(d - deg if d <= -90 else d + deg).apply(-length, 0)
paths[-1].append(path.rlineto(*dp))
return paths
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(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 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 winding(n,
radius,
angle=60,
windingnumber=False,
endpointcolor=color.rgb(0.6, 0.2, 0),
pathcolor=color.rgb(0.4, 0.3, 0.8)):
c = canvas.canvas()
ticklen = 0.1
c.stroke(path.circle(0, 0, radius), [style.linewidth.Thin])
tick = path.line((1 - ticklen) * radius, 0, (1 + ticklen) * radius, 0)
c.stroke(tick, [endpointcolor, style.linewidth.Thick])
c.stroke(tick, [trafo.rotate(angle), endpointcolor, style.linewidth.Thick])
tick_outer = (1 + ticklen) * radius
for _angle, label in ((0, r'$\phi_\text{i}$'), (radians(angle),
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
c.stroke(path.line(x+1.4*r, y, x+2.6*r, y), [deco.earrow()])
c.text(x+2.0*r, y+0.4*r, "$f$", center)
x += 4*r
surface(x, y, r, shade, mark=True)
t = Turtle(x, y-r, -0.45*pi)
dr = 0.15
r0 = 0.90
dtheta = 0.53*pi
dtheta = 0.45*pi
st_cw = [trafo.rotate(-90, x=x, y=y)]
t.right(0.45*pi, 0.90)
#c.stroke(path.circle(t.x, t.y, 0.1), st_cw)
t.right(0.45*pi, 0.75)
#c.stroke(path.circle(t.x, t.y, 0.1), st_cw)
t.right(0.70*pi, 0.55)
#c.stroke(path.circle(t.x, t.y, 0.1), st_cw)
t.right(0.45*pi, 0.44)
t.stroke(st_curve + st_cw)
t.stroke(st_curve + [trafo.rotate(90, x=x, y=y), deco.earrow()], reverse=True)
surface(x, y, r1, white, mark=True)
c.text(x-r, y+r, "$\widehat{a}$", northwest)
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)])
c.stroke(path.line(0, -dist, xcells, -dist), [deco.earrow, myblue])
c.text(0.5 * xcells, -2 * dist, 'axis 2',
[text.halign.center, text.valign.top, myblue])
c.writePDFfile()
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))
c.text(0.8, 0.2, 'Gitlab / Github server',
[color.hsb(0.5, 0.8, 0.5), text.size.small])
c.writePDFfile()
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([canvas.clip(p)])
c2 = canvas.canvas()
textcolor = color.hsb(0.6, 0.3, 1)
t = """\Huge
$2x^4+10x^3$
p1 = \{4: 2, 3: 10\}
$5x^2-x+32$
p2 = \{2: 5, 1: -1, 0: 32\}
multiply(p1, p2)
"""
c2.text(0, 0, t, [text.parbox(2*w), textcolor])
c1.insert(c2, [trafo.rotate(20).translated(-0.2*w, 0.9*h)])
c.insert(c1)
t = r'\Large $(2x^4+10x^3)(5x^2-x+32)$'
c.text(w/2, h/2, t, [text.halign.center, text.valign.middle,
color.hsb(0.05, 0.9, 0.6)])
c.writeGSfile(device="png16m", resolution=300)
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
anyon(0., r)
anyon(0., 0.)
anyon(0., -r)
anyon(w, r)
anyon(w, 0.)
anyon(w, -r)
if count==0:
pop()
else:
pop([trafo.translate(0., 8*r)])
pop([trafo.rotate(-90)])
x = -3.0*r
y = 0.0*r
c.text(x, y, r"$\sigma_1^{2}\ket{\psi}$", center)
y -= 4.0*r
c.text(x, y, r"$\ket{\psi}$", center)
c.stroke(path.line(x, y+r, x, -r), [deco.earrow(size=0.2)])
c.stroke(path.line(x-0.1, y+r, x+0.1, y+r))
x = +5.0*r
y = 0.0*r
def text_pyx(g, x_coord, y_coord, text_input, text_size = -2, color = None, rotation = 0.):
"""
Function that draws text in a given plot
INPUTS:
g (Object) A graph-type object to which you want to add the text
x_coord (Double) x-coordinate (in plot units) at which you want to place
the text
y_coord (Double) y-coordinate (in plot units) at which you want to place
the text
text_input (String) Text that you want to add.
text_size (int, optional) Text size of the text added to the plot. Default is -2.
color (instance) Color instance that defines the color that you want the
text to have. Default is black.
"""
# First define the text attributes:
textattrs = [pyx_text.size(text_size),pyx_text.halign.center, pyx_text.vshift.middlezero, trafo.rotate(rotation)]
# Now convert plot positions to pyx's:
x0,y0 = g.pos(x_coord, y_coord)
# If no color is given, draw black text. If color is given, draw text with the input color:
if color is None:
g.text(x0,y0,text_input,textattrs)
else:
# First, check which was the input color palette:
color_dict = color.color
if len(color_dict.keys()) == 4:
color_string = str(color_dict['c'])+','+str(color_dict['m'])+','+str(color_dict['y'])+','+str(color_dict['k'])
color_palette = 'cmyk'
else:
color_string = str(color_dict['r'])+','+str(color_dict['g'])+','+str(color_dict['b'])
color_palette = 'rgb'
# Now draw the text:
g.text(x0, y0, r"\textcolor["+color_palette+"]{"+color_string+"}{"+text_input+"}",textattrs)
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
def apogee_layer(holes, numbers=False, renumber=False):
offset_amount = -0.03
hole_radius = 0.4
# Read in APOGEE blocks information
blocks = apogee_south_blocks()
# Set up colors
pyxcolor = dict()
pyxcolor['red'] = color.cmyk.Red
pyxcolor['black'] = color.cmyk.Black
pyxcolor['blue'] = color.cmyk.CornflowerBlue
# Get science fiber information
isci = np.nonzero(np.array(holes['holetype']) == b'APOGEE_SOUTH')[0]
xfocal = np.array(holes['xfocal'])[isci]
yfocal = np.array(holes['yfocal'])[isci]
fiberid = np.array(holes['fiberid'])[isci]
block = np.array(holes['block'])[isci]
if (renumber):
fiberid = np.array(blocks.fibers['fiberid'])[fiberid - 1]
block = np.array(blocks.fibers['blockid'])[fiberid - 1]
# Create Voronoi tessellation
xy = np.array([xfocal, yfocal]).transpose()
vor = Voronoi(xy)
nridges = vor.ridge_points.shape[0]
# Set up object to print
clippath = path.circle(0., 0., interior_radius)
clipobject = canvas.clip(clippath)
interior = canvas.canvas([clipobject])
# Print lines separating blocks
for indx in range(nridges):
iv0 = vor.ridge_vertices[indx][0]
iv1 = vor.ridge_vertices[indx][1]
ip0 = vor.ridge_points[indx][0]
ip1 = vor.ridge_points[indx][1]
point0 = vor.points[ip0, :] / 10.
point1 = vor.points[ip1, :] / 10.
ib0 = block[ip0]
ib1 = block[ip1]
if (iv0 > 0 and iv1 > 0 and ib0 != ib1):
if (ib0 <= 25):
side0 = 'Red'
else:
side0 = 'Blue'
if (ib1 <= 25):
side1 = 'Red'
else:
side1 = 'Blue'
if (side0 == side1):
if (side0 == 'Red'):
color0 = color.cmyk.Red
color1 = color.cmyk.Red
else:
color0 = color.cmyk.Blue
color1 = color.cmyk.Blue
else:
color0 = color.cmyk.Black
color1 = color.cmyk.Black
vertex_start = vor.vertices[iv0, :] / 10.
vertex_end = vor.vertices[iv1, :] / 10.
(start0, end0) = offset_line(offset_amount, vertex_start,
vertex_end, point0)
interior.stroke(path.line(start0[1], start0[0], end0[1], end0[0]),
[style.linewidth.THick, color0])
(start1, end1) = offset_line(offset_amount, vertex_start,
vertex_end, point1)
interior.stroke(path.line(start1[1], start1[0], end1[1], end1[0]),
[style.linewidth.THick, color1])
# Print circles around holes
for indx in range(len(xfocal)):
hole_color = pyxcolor[blocks.fcolor(fiberid[indx])]
interior.stroke(
path.circle(yfocal[indx] / 10., xfocal[indx] / 10., hole_radius),
[style.linewidth.THick, hole_color])
if (numbers is True):
# Print numbers near holes
for indx in range(len(xfocal)):
if (indx <= 150):
props = [text.halign.boxleft, text.valign.middle]
else:
props = [
text.halign.boxright, text.valign.middle,
trafo.rotate(180.)
]
interior.text(
(yfocal[indx] / 10.) + hole_radius * 1.2, (xfocal[indx] / 10.),
r"\font\myfont=cmr10 at 20pt {\myfont " + str(fiberid[indx]) +
"}", props)
return interior
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 draw_continent_circle(con,
name="",
draw_upper_landscape=True,
draw_lower_landscape=False,
draw_upper_green=True,
draw_lower_purple=False,
draw_train_tracks=False,
draw_foliation=True,
foliation_style_old=False,
foliation_style_split=False,
foliation_style_cusp_leaves=True,
foliation_style_boundary_leaves=True,
shade_triangles=False,
draw_fund_domain=False,
fund_dom_tets=None,
draw_fund_domain_edges=False,
draw_tetrahedron_rectangles=[]):
global_scale_up = 10.0
edge_thickness = 0.02
track_thickness = 0.02
leaf_thickness = 0.03
edge_colours = {
True: color.rgb(0.9, 0.3, 0),
False: color.rgb(0, 0.3, 0.9)
}
green = color.rgb(0.0, 0.5, 0.0)
purple = color.rgb(0.5, 0.0, 0.5)
scl = trafo.trafo(matrix=((global_scale_up, 0), (0, global_scale_up)),
vector=(0, 0))
canv = canvas.canvas()
canv.stroke(path.circle(0, 0, global_scale_up), [style.linewidth(0.02)])
n = len(con.coast)
for v in con.coast:
i = v.coastal_index
t = 2 * pi * float(i) / float(n)
v.circle_pos = complex(cos(t), sin(t))
vert_pos = v.circle_pos * 1.01 * global_scale_up
canv.text(vert_pos.real,
vert_pos.imag,
"$" + str(con.vertices.index(v)) + "$",
textattrs=[
text.size(-4), text.halign.left, text.valign.middle,
trafo.rotate(
(180 / pi) * atan2(vert_pos.imag, vert_pos.real))
])
# vert_pos2 = v.circle_pos * 1.2 * global_scale_up
# p = path.path(path.moveto(vert_pos.real, vert_pos.imag), path.lineto(vert_pos2.real, vert_pos2.imag))
# canv.stroke(p, [deco.curvedtext("$"+str(con.vertices.index(v))+"$")])
### highlight vertices of tetrahedra in a fundamental domain
if draw_fund_domain:
if fund_dom_tets == None:
fund_dom_tets = get_fund_domain_tetrahedra(con)
for con_tet in fund_dom_tets:
if type(
con_tet
) == continent_tetrahedron: ### could be an integer if we didnt find this tet
if draw_fund_domain_edges:
for e in con_tet.edges():
col = edge_colours[e.is_red]
u, v = e.vertices
p = make_arc(u.circle_pos, v.circle_pos)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(edge_thickness),
style.linecap.round, col
])
update_fund_dom_tet_nums(con, fund_dom_tets)
for v in [v for v in con.coast if v.fund_dom_tet_nums != []]:
vert_pos = v.circle_pos * 1.03 * global_scale_up
canv.text(vert_pos.real,
vert_pos.imag,
"$" + str(v.fund_dom_tet_nums) + "$",
textattrs=[
text.size(-4), text.halign.left, text.valign.middle,
trafo.rotate(
(180 / pi) * atan2(vert_pos.imag, vert_pos.real))
])
# lower_colours = {True: color.rgb(0.5,0.3,0), False: color.rgb(0,0.3,0.5)}
# upper_colours = {True: color.rgb(0.9,0.3,0), False: color.rgb(0,0.3,0.9)}
landscape_edges = [con.lower_landscape_edges, con.upper_landscape_edges]
# colours = [lower_colours, upper_colours]
upper_tris = con.upper_landscape_triangles
lower_tris = con.lower_landscape_triangles
boundary_tris = [lower_tris, upper_tris]
if shade_triangles:
u, v, w = con.triangle_path[0].vertices
p = make_arc(u.circle_pos, v.circle_pos)
q = make_arc(v.circle_pos, w.circle_pos)
r = make_arc(w.circle_pos, u.circle_pos)
p.append(q[1])
p.append(r[1]) ### remove extraneous moveto commands
p = p.transformed(scl)
canv.stroke(
p, [deco.filled([color.transparency(0.8)]),
style.linewidth(0)])
u, v, w = con.triangle_path[-1].vertices
p = make_arc(u.circle_pos, v.circle_pos)
q = make_arc(v.circle_pos, w.circle_pos)
r = make_arc(w.circle_pos, u.circle_pos)
p.append(q[1])
p.append(r[1]) ### remove extraneous moveto commands
p = p.transformed(scl)
canv.stroke(
p, [deco.filled([color.transparency(0.8)]),
style.linewidth(0)])
# for triangle in con.triangle_path:
# u,v,w = triangle.vertices
# p = make_arc(u.circle_pos, v.circle_pos)
# q = make_arc(v.circle_pos, w.circle_pos)
# r = make_arc(w.circle_pos, u.circle_pos)
# p.append(q[1])
# p.append(r[1]) ### remove extraneous moveto commands
# p = p.transformed(scl)
# canv.stroke(p, [deco.filled([color.transparency(0.8)]), style.linewidth(0)])
to_do = []
if draw_lower_landscape:
to_do.append(0)
if draw_upper_landscape:
to_do.append(1)
for i in to_do:
for e in landscape_edges[i]:
col = edge_colours[e.is_red]
transp = []
if i == 0:
transp = [color.transparency(0.75)]
u, v = e.vertices
p = make_arc(u.circle_pos, v.circle_pos)
p = p.transformed(scl)
canv.stroke(
p,
[style.linewidth(edge_thickness), style.linecap.round, col] +
transp)
for tri in boundary_tris[i]:
center = incenter(tri.vertices[0].circle_pos,
tri.vertices[1].circle_pos,
tri.vertices[2].circle_pos)
# canv.fill(path.circle(global_scale_up*center[0], global_scale_up*center[1], 0.1))
canv.text(global_scale_up * center[0],
global_scale_up * center[1],
"$" + str(tri.index) + "$",
textattrs=[
text.size(-2), text.halign.center, text.valign.middle
] + transp)
### train tracks...
purple_train_routes = [
] ### pairs of coastal edges corresponding to a train route
green_train_routes = []
if draw_lower_purple:
if draw_train_tracks:
for tri in lower_tris:
midpts = []
is_reds = []
for e in tri.edges:
is_reds.append(e.is_red)
u, v = e.vertices
p, midpt = make_arc(u.circle_pos,
v.circle_pos,
return_midpt=True)
midpts.append(midpt)
for i in range(3):
if (is_reds[i] == is_reds[(i + 1) % 3]) or (
not is_reds[i] and is_reds[(i + 1) % 3]):
p = make_arc(midpts[i], midpts[(i + 1) % 3])
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(track_thickness),
style.linecap.round, purple
])
if draw_foliation:
for edge in con.lower_landscape_edges:
leaf_end_edges = []
if edge.is_coastal():
if not edge.is_coastal_sink(upper=False):
leaf_end_edges.append(edge)
for tri in edge.boundary_triangles:
if not tri.is_upper:
last_tri = con.flow(tri)[0]
last_edge = last_tri.edges[
last_tri.downriver_index()]
leaf_end_edges.append(last_edge)
else:
if edge.is_watershed():
for tri in edge.boundary_triangles:
last_tri = con.flow(tri)[0]
last_edge = last_tri.edges[
last_tri.downriver_index()]
leaf_end_edges.append(last_edge)
if len(leaf_end_edges) == 2:
purple_train_routes.append(leaf_end_edges)
if foliation_style_old:
leaf_ends = []
for e in leaf_end_edges:
endpts = e.vertices
_, midpt = make_arc(endpts[0].circle_pos,
endpts[1].circle_pos,
return_midpt=True)
leaf_ends.append(midpt)
p = make_arc(leaf_ends[0], leaf_ends[1])
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, purple
])
if draw_upper_green:
if draw_train_tracks:
for tri in upper_tris:
midpts = []
is_reds = []
for e in tri.edges:
is_reds.append(e.is_red)
u, v = e.vertices
p, midpt = make_arc(u.circle_pos,
v.circle_pos,
return_midpt=True)
midpts.append(midpt)
for i in range(3):
if (is_reds[i] == is_reds[(i + 1) % 3]) or (
is_reds[i] and not is_reds[(i + 1) % 3]):
p = make_arc(midpts[i], midpts[(i + 1) % 3])
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(track_thickness),
style.linecap.round, green
])
if draw_foliation:
for edge in con.upper_landscape_edges:
leaf_end_edges = []
if edge.is_coastal():
if not edge.is_coastal_sink(upper=True):
leaf_end_edges.append(edge)
for tri in edge.boundary_triangles:
if tri.is_upper:
last_tri = con.flow(tri)[0]
last_edge = last_tri.edges[
last_tri.downriver_index()]
leaf_end_edges.append(last_edge)
else:
if edge.is_watershed():
for tri in edge.boundary_triangles:
last_tri = con.flow(tri)[0]
last_edge = last_tri.edges[
last_tri.downriver_index()]
leaf_end_edges.append(last_edge)
if len(leaf_end_edges) == 2:
green_train_routes.append(leaf_end_edges)
if foliation_style_old:
leaf_ends = []
for e in leaf_end_edges:
endpts = e.vertices
_, midpt = make_arc(endpts[0].circle_pos,
endpts[1].circle_pos,
return_midpt=True)
leaf_ends.append(midpt)
p = make_arc(leaf_ends[0], leaf_ends[1])
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, green
])
if draw_foliation and (foliation_style_split or foliation_style_cusp_leaves
or foliation_style_boundary_leaves):
for e in con.coastal_edges:
e.purple_ends = []
e.green_ends = []
for e1, e2 in purple_train_routes:
e1.purple_ends.append(e2)
e2.purple_ends.append(e1)
for e1, e2 in green_train_routes:
e1.green_ends.append(e2)
e2.green_ends.append(e1)
for i, e in enumerate(con.coastal_edges):
rotated_coastal_edges = con.coastal_edges[
i:] + con.coastal_edges[:i]
e.purple_ends.sort(
key=lambda e_other: rotated_coastal_edges.index(e_other),
reverse=True)
e.green_ends.sort(
key=lambda e_other: rotated_coastal_edges.index(e_other),
reverse=True)
if e.is_red:
e.ends = e.green_ends + e.purple_ends
else:
e.ends = e.purple_ends + e.green_ends
if foliation_style_split:
for e1, e2 in purple_train_routes:
p1 = end_pos(e2, e1)
p2 = end_pos(e1, e2)
p = make_arc(p1, p2)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness), style.linecap.round,
purple
])
for e1, e2 in green_train_routes:
p1 = end_pos(e2, e1)
p2 = end_pos(e1, e2)
p = make_arc(p1, p2)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness), style.linecap.round, green
])
if foliation_style_cusp_leaves or foliation_style_boundary_leaves:
for i, c in enumerate(con.coast):
c.purple_thorn_end_positions = [] ### complex numbers
c.purple_thorn_ends = [
] ### [coastal arc, position along that arc]
e = con.coastal_edges[i]
e1 = e.purple_ends[0]
while True:
index = e1.purple_ends.index(e)
if index == len(e1.purple_ends) - 1:
break
else:
c.purple_thorn_end_positions.append(
end_pos(e, e1, offset=0.5))
c.purple_thorn_ends.append((e1, e1.ends.index(e)))
e, e1 = e1, e1.purple_ends[index + 1]
if foliation_style_boundary_leaves:
e_before = con.coastal_edges[(i - 1) % len(con.coast)]
e_after = con.coastal_edges[i]
first_pos = end_pos(e_after.purple_ends[0],
e_after,
offset=-0.25)
last_pos = end_pos(e_before.purple_ends[-1],
e_before,
offset=0.25)
c.purple_thorn_end_positions = [
first_pos
] + c.purple_thorn_end_positions + [last_pos]
arcs = []
for i in range(len(c.purple_thorn_end_positions) - 1):
arcs.append(
make_arc(c.purple_thorn_end_positions[i],
c.purple_thorn_end_positions[i + 1]))
for p in arcs:
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, purple
])
if foliation_style_cusp_leaves:
for thorn_end in c.purple_thorn_ends:
thorn_end_pos = end_pos2(thorn_end)
p = make_arc(c.circle_pos, thorn_end_pos)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, purple
])
for i, c in enumerate(con.coast):
c.green_thorn_end_positions = [] ### complex numbers
c.green_thorn_ends = [
] ### [coastal arc, position along that arc]
e = con.coastal_edges[i]
e1 = e.green_ends[0]
while True:
index = e1.green_ends.index(e)
if index == len(e1.green_ends) - 1:
break
else:
c.green_thorn_end_positions.append(
end_pos(e, e1, offset=0.5))
c.green_thorn_ends.append((e1, e1.ends.index(e)))
e, e1 = e1, e1.green_ends[index + 1]
if foliation_style_boundary_leaves:
e_before = con.coastal_edges[(i - 1) % len(con.coast)]
e_after = con.coastal_edges[i]
first_pos = end_pos(e_after.green_ends[0],
e_after,
offset=-0.25)
last_pos = end_pos(e_before.green_ends[-1],
e_before,
offset=0.25)
c.green_thorn_end_positions = [
first_pos
] + green_thorn_end_positions + [last_pos]
arcs = []
for i in range(len(c.green_thorn_end_positions) - 1):
arcs.append(
make_arc(c.green_thorn_end_positions[i],
c.green_thorn_end_positions[i + 1]))
for p in arcs:
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, green
])
if foliation_style_cusp_leaves:
for thorn_end in c.green_thorn_ends:
thorn_end_pos = end_pos2(thorn_end)
p = make_arc(c.circle_pos, thorn_end_pos)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(leaf_thickness),
style.linecap.round, green
])
for tet in draw_tetrahedron_rectangles:
purple_sides = tet_purple_rectangle_sides(
tet, actually_do_green=False)
green_sides = tet_purple_rectangle_sides(
tet, actually_do_green=True)
for side in purple_sides:
for cusp_leaf in side:
if cusp_leaf != None:
v, thorn_end = cusp_leaf
thorn_end_pos = end_pos2(thorn_end)
p = make_arc(v.circle_pos, thorn_end_pos)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(2 * leaf_thickness),
style.linecap.round, purple
])
for side in green_sides:
for cusp_leaf in side:
if cusp_leaf != None:
v, thorn_end = cusp_leaf
thorn_end_pos = end_pos2(thorn_end)
p = make_arc(v.circle_pos, thorn_end_pos)
p = p.transformed(scl)
canv.stroke(p, [
style.linewidth(2 * leaf_thickness),
style.linecap.round, green
])
output_filename = 'Images/CircleContinent/' + name + '.pdf'
canv.writePDFfile(output_filename)
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
c.stroke(path.rect(x0, y0, w, h), dashed)
c.stroke(path.rect(x0+w+m, y0, w, h), dotted)
grarrow = [green, style.linewidth.THick, deco.earrow(size=0.2)]
y = y0+0.3*h
c.stroke(path.line(x0+0.5*w, y, x0+1.5*w+m, y), grarrow)
anyon(x0+0.8*w, y)
anyon(x0+m+1.2*w, y)
y = y0+0.7*h
c.stroke(path.line(x0+1.5*w+m, y, x0+0.5*w, y), grarrow)
anyon(x0+0.8*w, y)
anyon(x0+m+1.2*w, y)
pop([trafo.rotate(-90), trafo.translate(0.7, 2.5*h)])
c.text(0., 0.5*h, "(a)")
# --------------------------------------------------------------------
#x0, y0 = 0.6, 0.
#c.text(x0-0.8, y0, "(b)")
push()
c.stroke(path.rect(x0, y0, w, h), dashed)
c.stroke(path.rect(x0+w+m, y0, w, h), dotted)
p = path.path(
path.moveto(x0+0.5*w, y0-0.3*h),
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
g = pyx.graph.graphxy(width=figwidth, height=figheight,
x=pyx.graph.axis.linear(min=nmin, max=nmax, title=r'$\log n_\mathrm{gas}$'),
y=pyx.graph.axis.linear(min=tmin, max=tmax, title=r'$\log T$'),
)
from pyx.style import linestyle, linewidth
from pyx.color import transparency
from pyx.graph.style import line
from pyx.graph import data
from pyx.trafo import rotate, scale
line.defaultlineattrs += [linewidth.thick, transparency(0.2)]
# Free-fall time < 1.e5 years
g.plot(data.function("x(y) = 5.31"), [line([linestyle.dashed])])
xx, yy = g.pos(5.6, 3.8)
g.text(xx, yy, r"\(t_\mathrm{ff} = 10^5\,\mathrm{yr}\)", [scale(0.7), rotate(90)])
# Plot contours of Jeans instability
for MJeans in (0.0, 1.0):
g.plot(data.function("y(x) = 0.491 + 0.6667*MJeans + 0.333*(x-3.0)",
context=locals()),
[line([linestyle.solid, linewidth.Thick])])
ang = N.arctan2(0.3333*(nmax-nmin), (tmax-tmin))*180.0/N.pi
x, y = g.pos(1.6, 0.8)
g.text(x, y, r"\(M_J = 10~M_\odot\)", [scale(0.7), rotate(ang)])
x, y = g.pos(3.6, 0.8)
g.text(x, y, r"\(M_J = 1~M_\odot\)", [scale(0.7), rotate(ang)])
# Plot contours of equilibrium T
execdir = os.path.dirname(sys.argv[0])
for Av, D in [
[0.0, 0.3],
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)])
c.stroke(path.line(0, -dist, xcells, -dist),
[deco.earrow, myblue])
c.text(0.5*xcells, -2*dist, 'axis 2',
[text.halign.center, text.valign.top, myblue])
c.writePDFfile()
box = c.bbox()
pd = 0.1
xoff = box.left() - pd
pdx = 0.2
pdy = 0.5
c.stroke(
path.curve(xoff,
box.top() + pd, xoff - pdx,
box.top() - pdy, xoff - pdx,
box.bottom() + pdy, xoff,
box.bottom() - pd))
xoff = box.right() + pd
c.stroke(
path.curve(xoff,
box.top() + pd, xoff + pdx,
box.top() - pdy, xoff + pdx,
box.bottom() + pdy, xoff,
box.bottom() - pd))
x = box.left() - pdx - 0.4
c.stroke(path.line(x, box.top(), x, box.bottom()), [deco.earrow, color0])
c.text(
x - 0.1, 0.5 * (box.top() + box.bottom()), 'axis 0',
[text.halign.center, color0, trafo.rotate(90)])
y = box.top() + 0.4
c.stroke(path.line(box.left(), y, box.right(), y), [deco.earrow, color1])
c.text(0.5 * (box.left() + box.right()), y + 0.1, 'axis 1',
[text.halign.center, color1])
c.writePDFfile()
c.writeGSfile(device="png16m", resolution=600)
dx = 2
dy = 0.8
c = canvas.canvas()
for nx in range(3):
for ny in range(3):
c.text(nx*dx, -ny*dy,
r'a[\textcolor{axis0}{%s}, \textcolor{axis1}{%s}]' % (ny, nx),
[text.halign.center])
box = c.bbox()
pd = 0.1
xoff = box.left()-pd
pdx = 0.2
pdy = 0.5
c.stroke(path.curve(xoff, box.top()+pd,
xoff-pdx, box.top()-pdy,
xoff-pdx, box.bottom()+pdy,
xoff, box.bottom()-pd))
xoff = box.right()+pd
c.stroke(path.curve(xoff, box.top()+pd,
xoff+pdx, box.top()-pdy,
xoff+pdx, box.bottom()+pdy,
xoff, box.bottom()-pd))
x = box.left()-pdx-0.4
c.stroke(path.line(x, box.top(), x, box.bottom()), [deco.earrow, color0])
c.text(x-0.1, 0.5*(box.top()+box.bottom()), 'axis 0',
[text.halign.center, color0, trafo.rotate(90)])
y = box.top()+0.4
c.stroke(path.line(box.left(), y, box.right(), y), [deco.earrow, color1])
c.text(0.5*(box.left()+box.right()), y+0.1, 'axis 1', [text.halign.center, color1])
c.writePDFfile()
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)
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