def test_render_KGML_modify(self):
""" Rendering of KGML to PDF, with modification.
"""
# We test rendering of the original KGML for KO01100,
# modifying line width for the lipid pathway
p = self.data
with open(p[0].infilename) as f:
pathway = read(f)
mod_rs = [e for e in pathway.orthologs if
len(set(e.name.split()).intersection(self.ko_ids))]
for r in mod_rs:
for g in r.graphics:
g.width = 10
kgml_map = KGMLCanvas(pathway)
kgml_map.draw(p[0].output_stem + '_widths.pdf')
# We test rendering of the original KGML for KO3070,
# modifying the reaction colours for each ortholog entry
with open(p[1].infilename) as f:
pathway = read(f)
orthologs = [e for e in pathway.orthologs]
# Use Biopython's ColorSpiral to generate colours
cs = ColorSpiral(a=2, b=0.2, v_init=0.85, v_final=0.5,
jitter=0.03)
colors = cs.get_colors(len(orthologs))
for o, c in zip(orthologs, colors):
for g in o.graphics:
g.bgcolor = c
kgml_map = KGMLCanvas(pathway)
pathway.image = p[1].pathway_image
kgml_map.import_imagemap = p[1].show_pathway_image
kgml_map.draw(p[1].output_stem + '_colors.pdf')
def test_render_KGML_modify(self):
"""Rendering of KGML to PDF, with modification."""
# We test rendering of the original KGML for KO01100,
# modifying line width for the lipid pathway
p = self.data
with open(p[0].infilename) as f:
pathway = read(f)
mod_rs = [
e for e in pathway.orthologs
if len(set(e.name.split()).intersection(self.ko_ids))
]
for r in mod_rs:
for g in r.graphics:
g.width = 10
kgml_map = KGMLCanvas(pathway)
kgml_map.draw(p[0].output_stem + '_widths.pdf')
# We test rendering of the original KGML for KO3070,
# modifying the reaction colours for each ortholog entry
with open(p[1].infilename) as f:
pathway = read(f)
orthologs = [e for e in pathway.orthologs]
# Use Biopython's ColorSpiral to generate colours
cs = ColorSpiral(a=2, b=0.2, v_init=0.85, v_final=0.5, jitter=0.03)
colors = cs.get_colors(len(orthologs))
for o, c in zip(orthologs, colors):
for g in o.graphics:
g.bgcolor = c
kgml_map = KGMLCanvas(pathway)
pathway.image = p[1].pathway_image
kgml_map.import_imagemap = p[1].show_pathway_image
kgml_map.draw(p[1].output_stem + '_colors.pdf')
def test_render_KGML_transparency(self):
"""Rendering of KGML to PDF, with color alpha channel."""
# We test rendering of the original KGML for KO01100,
# modifying alpha channel for the lipid pathway
p = self.data
with open(p[0].infilename) as f:
pathway = read(f)
mod_rs = [e for e in pathway.orthologs if
len(set(e.name.split()).intersection(self.ko_ids))]
for r in mod_rs:
for g in r.graphics:
# Modify hex colour directly by appending alpha channel
# to hex string
g.fgcolor = g.fgcolor + "77"
g.width = 20
kgml_map = KGMLCanvas(pathway)
kgml_map.draw(p[0].output_stem + "_transparency.pdf")
# We test rendering of the original KGML for KO3070,
# modifying the alpha channel for each ortholog entry
with open(p[1].infilename) as f:
pathway = read(f)
orthologs = list(pathway.orthologs)
# Use Biopython's ColorSpiral to generate colours
cs = ColorSpiral(a=2, b=0.2, v_init=0.85, v_final=0.5,
jitter=0.03)
colors = cs.get_colors(len(orthologs))
for o, c in zip(orthologs, colors):
# Modify color tuples to add alpha channel
c = c + (0.5, )
for g in o.graphics:
g.bgcolor = c
kgml_map = KGMLCanvas(pathway)
pathway.image = p[1].pathway_image
kgml_map.import_imagemap = p[1].show_pathway_image
kgml_map.draw(p[1].output_stem + "_transparency.pdf")
def test_render_KGML_transparency(self):
"""Rendering of KGML to PDF, with color alpha channel."""
# We test rendering of the original KGML for KO01100,
# modifying alpha channel for the lipid pathway
p = self.data
with open(p[0].infilename) as f:
pathway = read(f)
mod_rs = [e for e in pathway.orthologs if
len(set(e.name.split()).intersection(self.ko_ids))]
for r in mod_rs:
for g in r.graphics:
# Modify hex colour directly by appending alpha channel
# to hex string
g.fgcolor = g.fgcolor + "77"
g.width = 20
kgml_map = KGMLCanvas(pathway)
kgml_map.draw(p[0].output_stem + '_transparency.pdf')
# We test rendering of the original KGML for KO3070,
# modifying the alpha channel for each ortholog entry
with open(p[1].infilename) as f:
pathway = read(f)
orthologs = [e for e in pathway.orthologs]
# Use Biopython's ColorSpiral to generate colours
cs = ColorSpiral(a=2, b=0.2, v_init=0.85, v_final=0.5,
jitter=0.03)
colors = cs.get_colors(len(orthologs))
for o, c in zip(orthologs, colors):
# Modify color tuples to add alpha channel
c = c + (0.5, )
for g in o.graphics:
g.bgcolor = c
kgml_map = KGMLCanvas(pathway)
pathway.image = p[1].pathway_image
kgml_map.import_imagemap = p[1].show_pathway_image
kgml_map.draw(p[1].output_stem + '_transparency.pdf')
def test_colorlist(self):
"""Get set of eight colours, no jitter, using ColorSpiral."""
cs = ColorSpiral(a=4, b=0.33, jitter=0)
colours = list(cs.get_colors(8))
cstr = ["(%.2f, %.2f, %.2f)" % (r, g, b) for r, g, b in colours]
expected = \
['(0.64, 0.74, 0.81)', '(0.68, 0.52, 0.76)', '(0.72, 0.41, 0.55)',
'(0.68, 0.39, 0.31)', '(0.63, 0.54, 0.22)', '(0.48, 0.59, 0.13)',
'(0.24, 0.54, 0.06)', '(0.01, 0.50, -0.00)']
self.assertEqual(cstr, expected)
def test_colorlist(self):
"""Get set of eight colours, no jitter, using ColorSpiral."""
cs = ColorSpiral(a=4, b=0.33, jitter=0)
colours = list(cs.get_colors(8))
cstr = ["(%.2f, %.2f, %.2f)" % (r, g, b)
for r, g, b in colours]
expected = \
['(0.64, 0.74, 0.81)', '(0.68, 0.52, 0.76)', '(0.72, 0.41, 0.55)',
'(0.68, 0.39, 0.31)', '(0.63, 0.54, 0.22)', '(0.48, 0.59, 0.13)',
'(0.24, 0.54, 0.06)', '(0.01, 0.50, -0.00)']
self.assertEqual(cstr, expected)
def test_colorspiral(self):
"""Get set of 16 colours, no jitter, using ColorSpiral."""
cs = ColorSpiral(a=4, b=0.33, jitter=0)
radius = A4[0] * 0.025
for r, g, b in cs.get_colors(16):
self.c.setFillColor((r, g, b))
# Convert HSV colour to rectangular coordinates on HSV disc
h, s, v = colorsys.rgb_to_hsv(r, g, b)
coords = rect(s * A4[0] * 0.45, h * 2 * pi)
x, y = self.x_0 + coords.real, self.y_0 + coords.imag
self.c.ellipse(x - radius, y - radius, x + radius, y + radius,
stroke=0, fill=1)
self.finish()
def test_colorspiral(self):
"""Get set of 16 colours, no jitter, using ColorSpiral."""
cs = ColorSpiral(a=4, b=0.33, jitter=0)
radius = A4[0] * 0.025
for r, g, b in cs.get_colors(16):
self.c.setFillColor((r, g, b))
# Convert HSV colour to rectangular coordinates on HSV disc
h, s, v = colorsys.rgb_to_hsv(r, g, b)
coords = rect(s * A4[0] * 0.45, h * 2 * pi)
x, y = self.x_0 + coords.real, self.y_0 + coords.imag
self.c.ellipse(x - radius, y - radius, x + radius, y + radius,
stroke=0, fill=1)
self.finish()
def test_colorlist(self):
"""Get set of eight colours, no jitter, using ColorSpiral."""
cs = ColorSpiral(a=4, b=0.33, jitter=0)
colours = list(cs.get_colors(8))
cstr = [f"({r:.2f}, {g:.2f}, {b:.2f})" for r, g, b in colours]
expected = [
"(0.64, 0.74, 0.81)",
"(0.68, 0.52, 0.76)",
"(0.72, 0.41, 0.55)",
"(0.68, 0.39, 0.31)",
"(0.63, 0.54, 0.22)",
"(0.48, 0.59, 0.13)",
"(0.24, 0.54, 0.06)",
"(0.01, 0.50, -0.00)",
]
self.assertEqual(cstr, expected)
def write_clusters(seqfname, tree, clusters, unclustered):
"""Write output files: clusters & unique as FASTA, tree as phyloXML."""
is_aln = seqfname.endswith('.aln')
seq_idx = SeqIO.to_dict(
SeqIO.parse(seqfname, 'clustal' if is_aln else 'fasta'))
def write_cluster(cluster, fname):
"""Write the sequences of cluster tips to a FASTA file."""
records = [seq_idx[seqid] for seqid in sorted(cluster)]
with open(fname, 'w+') as handle:
for rec in records:
write_fasta(rec, handle, do_ungap=is_aln)
logging.info("Wrote %s (%d sequences)", fname, len(records))
colors = [
BranchColor(*map(lambda x: int(x * 255), rgb))
for rgb in ColorSpiral().get_colors(len(clusters))
]
for i, item in enumerate(
sorted(clusters.iteritems(),
reverse=True,
key=lambda kv: len(kv[1]))):
clade, cluster = item
write_cluster(cluster, os.path.basename(seqfname) + '.' + str(i))
clade.color = colors[i]
clade.width = 2
if unclustered:
write_cluster(unclustered, os.path.basename(seqfname) + '.Unique')
treefname = os.path.basename(seqfname) + '.xml'
Phylo.write(tree, treefname, 'phyloxml')
logging.info("Wrote %s", treefname)
def map2highlighted_map(map_id,
ko_list,
ko2freq,
biodb,
outpath='test.pdf',
taxon_id=False,
n_species=60):
import re
from chlamdb.biosqldb import shell_command
from Bio.Graphics.KGML_vis import KGMLCanvas
from Bio.Graphics import KGML_vis
import urllib.request
from Bio.KEGG.KGML.KGML_pathway import Pathway, Reaction, Relation
import Bio.KEGG.KGML.KGML_pathway
from Bio.KEGG.KGML import KGML_parser
from Bio.Graphics.ColorSpiral import ColorSpiral
import matplotlib.cm as cm
from matplotlib.colors import rgb2hex
import matplotlib as mpl
values = [float(i) for i in ko2freq.values()]
norm = mpl.colors.Normalize(vmin=0, vmax=n_species)
cmap = cm.OrRd
cmap2 = cm.Greens
m = cm.ScalarMappable(norm=norm, cmap=cmap)
m2 = cm.ScalarMappable(norm=norm, cmap=cmap2)
url_template = 'http://rest.kegg.jp/get/%s/kgml' % re.sub(
'map', 'ko', map_id)
print(url_template)
f = urllib.request.urlopen(url_template)
from Bio.Graphics import KGML_vis
pathway = KGML_parser.read(f.read().decode('UTF-8'))
kgml_map = KGMLCanvas(pathway, show_maps=True)
# Let's use some arbitrary colours for the orthologs
cs = ColorSpiral(a=2, b=0.2, v_init=0.85, v_final=0.5, jitter=0.03)
# Loop over the orthologs in the pathway, and change the
# background colour
orthologs = [e for e in pathway.orthologs]
for o in orthologs:
match = False
if 'K00163' in o.name:
print('##################################')
ko_temp_list = set([i.rstrip() for i in o.name.split('ko:')])
if len(ko_temp_list.intersection(set(ko2freq.keys()))) > 0:
ko_keep = []
for ko in ko_temp_list:
if ko in ko2freq:
ko_keep.append(ko)
if ko in ko_list:
match = True
o.name = 'ko:' + ' ko:'.join(ko_keep)
total = sum([
int(ko2freq[i])
for i in ko_temp_list.intersection(set(ko2freq.keys()))
])
for g in o.graphics:
if match:
g.bgcolor = rgb2hex(m2.to_rgba(float(total)))
else:
#print 'no match!!!!'
#print ko_temp_list
#print ko2freq.keys()
#print 'TOTAL:', total
g.bgcolor = rgb2hex(m.to_rgba(float(total)))
o.name = "%s (%s)" % (o.name.split('ko:')[0], total)
#else:
# for g in o.graphics:
# g.bgcolor = '#FFFFFF'
# Default settings are for the KGML elements only
# We need to use the image map, and turn off the KGML elements, to see
# only the .png base map. We could have set these values on canvas
# instantiation
kgml_map.import_imagemap = True
kgml_map.show_maps = True
kgml_map.show_orthologs = True
kgml_map.draw_relations = False
kgml_map.show_compounds = False
kgml_map.show_genes = False
kgml_map.show_compounds = False
kgml_map.show_genes = False
kgml_map.draw(outpath)
'''
print 'DIRLISAT:', dir(pathway)
maps = [m for m in pathway.maps]
for map in maps:
for g in map.graphics:
print g.name
'''
#print re.sub('pdf', 'svg', outpath)
shell_command.shell_command(
'inkscape %s --export-plain-svg=%s' %
(outpath, re.sub('pdf', 'svg', outpath))) # 'pdf2svg %s %s all'
t = edit_svg_map("%s" % re.sub('pdf', 'svg', outpath),
ko2freq.keys(),
biodb,
map_id,
taxon_id=taxon_id)
#print "%s" % re.sub('pdf', 'svg', outpath)
t.write("%s" % re.sub('pdf', 'svg', outpath))
