def plot_concept_evolution(
scenarios,
tree,
fileformat='pdf',
degree=90,
**keywords
):
"""
Plot the evolution according to the MLN method of all words for a given concept.
Parameters
----------
tree : str
A tree representation in Newick format.
fileformat : str (default="pdf")
A valid fileformat according to Matplotlib.
degree : int (default=90)
The degree by which the tree is drawn. 360 yields a circular tree, 180
yields a tree filling half of the space of a circle.
"""
# make defaults
defaults = dict(
figsize=(15, 15),
left=0.05,
top=0.95,
bottom=0.05,
right=0.95,
colormap=mpl.cm.jet,
edgewidth=5,
radius=2.5,
outer_radius=0.5,
inner_radius=0.25,
cognates='',
usetex=False,
latex_preamble=False,
textsize=8,
change=lambda x: x ** 1.75,
xlim=0,
ylim=0,
xlimr=False,
xliml=False,
ylimt=False,
ylimb=False,
rootsize=10,
legend=True,
legendsize=5,
legendAloc='upper right',
legendBloc='lower right',
markeredgewidth=2.5,
wedgeedgewidth=2,
gain_linestyle='dotted',
loss_linestyle='solid',
ax_linewidth=0,
labels={},
_prefix='- ',
_suffix=' -',
colors={},
start=0,
filename=rcParams['filename'],
loss_alpha=0.1,
loss_background='0.75',
edges=[],
hedge_color="black",
hedge_width=5,
hedge_linestyle='dashed',
)
keywords.update(defaults)
# set filename as variable for convenience
filename = keywords['filename']
# XXX customize later XXX
colormap = keywords['colormap']
# switch backend, depending on whether tex is used or not
backend = mpl.get_backend()
if keywords['usetex'] and backend != 'pgf':
plt.switch_backend('pgf')
elif not keywords['usetex'] and backend != 'TkAgg':
plt.switch_backend('TkAgg')
# check for preamble settings
if keywords['latex_preamble']:
mpl.rcParams['pgf.preamble'] = keywords['latex_preamble']
# make a graph
graph = nx.Graph()
# get the tgraph
tgraph = radial_layout(
tree,
degree=degree,
change=keywords['change'],
start=keywords['start']
)
# get the taxa
taxa = [n[0] for n in tgraph.nodes(data=True) if n[1]['tip']]
# set the labels
labels = {}
for taxon in taxa:
if taxon in keywords['labels']:
labels[taxon] = keywords['labels'][taxon]
else:
labels[taxon] = taxon
# get the number of paps in order to get the right colors
cfunc = np.array(np.linspace(10, 256, len(scenarios)), dtype='int')
if not keywords['colors']:
colors = {scenarios[i][0]: mpl.colors.rgb2hex(colormap(cfunc[i]))
for i in range(len(scenarios))}
else:
colors = keywords['colors']
# get the wedges for the paps
wedges = {}
linsp = np.linspace(0, 360, len(scenarios) + 1)
for i, scenario in enumerate(scenarios):
pap = scenario[0]
theta1, theta2 = linsp[i], linsp[i + 1]
wedges[pap] = (theta1, theta2)
if keywords['legend']:
# set the linestyle for the legend
if keywords['gain_linestyle'] == 'dotted':
ls = ':'
elif keywords['gain_linestyle'] == 'dashed':
ls = '--'
legendEntriesA = []
legendTextA = []
# add stuff for the legend
for pap, gls in scenarios:
w = mpl.patches.Wedge(
(0, 0),
1,
wedges[pap][0],
wedges[pap][1],
facecolor=colors[pap],
zorder=1,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black'
)
legendEntriesA += [w]
legendTextA += [pap]
# second legend explains evolution
legendEntriesB = []
legendTextB = []
p = mpl.patches.Wedge(
(0, 0),
1,
0,
360,
facecolor='0.5',
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
)
legendEntriesB += [p]
legendTextB += ['Loss Event']
p, = plt.plot(
0, 0,
ls,
color='black',
linewidth=keywords['wedgeedgewidth']
)
legendEntriesB += [p]
legendTextB += ['Gain Event']
# overwrite stuff
plt.plot(0, 0, 'o', markersize=2, zorder=2, color='white')
# iterate over the paps and append states to the graph
for pap, gls in scenarios:
# get the graph with the model
g = gls2gml(
gls,
tgraph,
tree,
filename=''
)
# iterate over the graph
for n, d in g.nodes(data=True):
# add the node if necessary
if n not in graph:
graph.add_node(n)
# add a pap-dictionary if it's not already there
if 'pap' not in graph.node[n]:
graph.node[n]['pap'] = {}
# add data
graph.node[n]['pap'][pap] = d['state']
# create the figure
fig = plt.figure(figsize=keywords['figsize'])
figsp = fig.add_subplot(111)
figsp.axes.get_xaxis().set_visible(False)
figsp.axes.get_yaxis().set_visible(False)
for s in figsp.spines.values():
s.set_linewidth(keywords['ax_linewidth'])
plt.axis('equal')
xvals = []
yvals = []
# iterate over edges first
for nA, nB in g.edges():
gA = g.node[nA]['graphics']
gB = g.node[nB]['graphics']
xA, yA = gA['x'], gA['y']
xB, yB = gB['x'], gB['y']
plt.plot(
[xA, xB],
[yA, yB],
'-',
color='black',
linewidth=keywords['edgewidth']
)
# add horizontal edges if this option is chosen
if keywords['edges']:
# get the coordinates
for nA, nB in keywords['edges']:
gA = g.node[nA]['graphics']
gB = g.node[nB]['graphics']
xA, yA = gA['x'], gA['y']
xB, yB = gB['x'], gB['y']
plt.plot(
[xA, xB],
[yA, yB],
'-',
color=keywords['hedge_color'],
linewidth=keywords["hedge_width"],
linestyle=keywords['hedge_linestyle']
)
# now iterate over the nodes
for n, d in graph.nodes(data=True):
cpaps = d['pap']
x, y = g.node[n]['graphics']['x'], g.node[n]['graphics']['y']
# get z-value which serves as zorder attribute
try:
z = 6 * len(tree.getConnectingEdges('root', n))
except:
z = 0
xvals += [x]
yvals += [y]
# plot the default marker
plt.plot(
x,
y,
'o',
markersize=keywords['rootsize'],
color='black',
zorder=50
)
# check for origins in cpaps
if 'O' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor='white',
zorder=57 + z,
linewidth=keywords['markeredgewidth'],
linestyle=keywords['gain_linestyle'],
)
figsp.add_artist(w)
# check for retentions
elif 'o' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor='white',
zorder=56 + z,
linewidth=keywords['markeredgewidth'],
linestyle='solid',
)
figsp.add_artist(w)
if 'L' in cpaps.values() and 'O' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor=keywords['loss_background'],
zorder=58 + z,
linewidth=keywords['markeredgewidth'],
edgecolor='black',
linestyle=keywords['loss_linestyle']
)
figsp.add_artist(w)
elif "L" in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor=keywords['loss_background'],
zorder=59 + z,
linewidth=keywords['markeredgewidth'],
edgecolor='black',
)
figsp.add_artist(w)
# plot all wedges
for pap in cpaps:
theta1, theta2 = wedges[pap]
color = colors[pap]
# check for characteristics of this pap
# if it's a loss
if cpaps[pap] == 'L':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
alpha=keywords['loss_alpha'], # 0.25,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
linestyle=keywords['loss_linestyle']
)
figsp.add_artist(w)
elif cpaps[pap] == 'o':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black'
)
figsp.add_artist(w)
elif cpaps[pap] == 'O':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
linestyle=keywords['gain_linestyle']
)
figsp.add_artist(w)
# add the labels if this option is chosen
if keywords['labels']:
# if node is a tip
if tgraph.node[n]['tip']:
# get the values
gf = tgraph.node[n]['graphics']
r = gf['angle']
x, y = gf['x'], gf['y']
ha = gf['s']
# modify the text
if ha == 'left':
text = keywords['_prefix'] + labels[n]
else:
text = labels[n] + keywords['_suffix']
# plot the text
plt.text(
x,
y,
text,
size=keywords['textsize'],
va='center',
ha=ha,
fontweight='bold',
color='black',
rotation=r,
rotation_mode='anchor',
zorder=z
)
# set up the xlimits
if not keywords['xlimr'] and not keywords['xliml']:
xl, xr = 2 * [keywords['xlim']]
else:
xl, xr = keywords['xliml'], keywords['xlimr']
# set up the xlimits
if not keywords['ylimt'] and not keywords['ylimb']:
yb, yt = 2 * [keywords['ylim']]
else:
yb, yt = keywords['ylimb'], keywords['ylimt']
plt.xlim((min(xvals) - xl, max(xvals) + xr))
plt.ylim((min(yvals) - yb, max(yvals) + yt))
prop = mpl.font_manager.FontProperties(size=keywords['legendsize'])
if keywords['legend']:
legend1 = plt.legend(
legendEntriesA,
legendTextA,
loc=keywords['legendAloc'],
numpoints=1,
prop=prop
)
plt.legend(
legendEntriesB,
legendTextB,
loc=keywords['legendBloc'],
prop=prop
)
figsp.add_artist(legend1)
plt.subplots_adjust(
left=keywords['left'],
right=keywords['right'],
top=keywords['top'],
bottom=keywords['bottom']
)
plt.savefig(filename + '.' + fileformat)
plt.clf()
log.file_written(filename + '.' + fileformat)
def plot_concept_evolution(scenarios,
tree,
fileformat='pdf',
degree=90,
**keywords):
"""
Plot the evolution according to the MLN method of all words for a given concept.
Parameters
----------
tree : str
A tree representation in Newick format.
fileformat : str (default="pdf")
A valid fileformat according to Matplotlib.
degree : int (default=90)
The degree by which the tree is drawn. 360 yields a circular tree, 180
yields a tree filling half of the space of a circle.
"""
# make defaults
defaults = dict(
figsize=(15, 15),
left=0.05,
top=0.95,
bottom=0.05,
right=0.95,
colormap=mpl.cm.jet,
edgewidth=5,
radius=2.5,
outer_radius=0.5,
inner_radius=0.25,
cognates='',
usetex=False,
latex_preamble=False,
textsize=8,
change=lambda x: x**1.75,
xlim=0,
ylim=0,
xlimr=False,
xliml=False,
ylimt=False,
ylimb=False,
rootsize=10,
legend=True,
legendsize=5,
legendAloc='upper right',
legendBloc='lower right',
markeredgewidth=2.5,
wedgeedgewidth=2,
gain_linestyle='dotted',
loss_linestyle='solid',
ax_linewidth=0,
labels={},
_prefix='- ',
_suffix=' -',
colors={},
start=0,
filename=rcParams['filename'],
loss_alpha=0.1,
loss_background='0.75',
edges=[],
hedge_color="black",
hedge_width=5,
hedge_linestyle='dashed',
)
keywords.update(defaults)
# set filename as variable for convenience
filename = keywords['filename']
# XXX customize later XXX
colormap = keywords['colormap']
# switch backend, depending on whether tex is used or not
backend = mpl.get_backend()
if keywords['usetex'] and backend != 'pgf':
plt.switch_backend('pgf')
elif not keywords['usetex'] and backend != 'TkAgg':
plt.switch_backend('TkAgg')
# check for preamble settings
if keywords['latex_preamble']:
mpl.rcParams['pgf.preamble'] = keywords['latex_preamble']
# make a graph
graph = nx.Graph()
# get the tgraph
tgraph = radial_layout(tree,
degree=degree,
change=keywords['change'],
start=keywords['start'])
# get the taxa
taxa = [n[0] for n in tgraph.nodes(data=True) if n[1]['tip']]
# set the labels
labels = {}
for taxon in taxa:
if taxon in keywords['labels']:
labels[taxon] = keywords['labels'][taxon]
else:
labels[taxon] = taxon
# get the number of paps in order to get the right colors
cfunc = np.array(np.linspace(10, 256, len(scenarios)), dtype='int')
if not keywords['colors']:
colors = {
scenarios[i][0]: mpl.colors.rgb2hex(colormap(cfunc[i]))
for i in range(len(scenarios))
}
else:
colors = keywords['colors']
# get the wedges for the paps
wedges = {}
linsp = np.linspace(0, 360, len(scenarios) + 1)
for i, scenario in enumerate(scenarios):
pap = scenario[0]
theta1, theta2 = linsp[i], linsp[i + 1]
wedges[pap] = (theta1, theta2)
if keywords['legend']:
# set the linestyle for the legend
if keywords['gain_linestyle'] == 'dotted':
ls = ':'
elif keywords['gain_linestyle'] == 'dashed':
ls = '--'
legendEntriesA = []
legendTextA = []
# add stuff for the legend
for pap, gls in scenarios:
w = mpl.patches.Wedge((0, 0),
1,
wedges[pap][0],
wedges[pap][1],
facecolor=colors[pap],
zorder=1,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black')
legendEntriesA += [w]
legendTextA += [pap]
# second legend explains evolution
legendEntriesB = []
legendTextB = []
p = mpl.patches.Wedge(
(0, 0),
1,
0,
360,
facecolor='0.5',
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
)
legendEntriesB += [p]
legendTextB += ['Loss Event']
p, = plt.plot(0,
0,
ls,
color='black',
linewidth=keywords['wedgeedgewidth'])
legendEntriesB += [p]
legendTextB += ['Gain Event']
# overwrite stuff
plt.plot(0, 0, 'o', markersize=2, zorder=2, color='white')
# iterate over the paps and append states to the graph
for pap, gls in scenarios:
# get the graph with the model
g = gls2gml(gls, tgraph, tree, filename='')
# iterate over the graph
for n, d in g.nodes(data=True):
# add the node if necessary
if n not in graph:
graph.add_node(n)
# add a pap-dictionary if it's not already there
if 'pap' not in graph.node[n]:
graph.node[n]['pap'] = {}
# add data
graph.node[n]['pap'][pap] = d['state']
# create the figure
fig = plt.figure(figsize=keywords['figsize'])
figsp = fig.add_subplot(111)
figsp.axes.get_xaxis().set_visible(False)
figsp.axes.get_yaxis().set_visible(False)
for s in figsp.spines.values():
s.set_linewidth(keywords['ax_linewidth'])
plt.axis('equal')
xvals = []
yvals = []
# iterate over edges first
for nA, nB in g.edges():
gA = g.node[nA]['graphics']
gB = g.node[nB]['graphics']
xA, yA = gA['x'], gA['y']
xB, yB = gB['x'], gB['y']
plt.plot([xA, xB], [yA, yB],
'-',
color='black',
linewidth=keywords['edgewidth'])
# add horizontal edges if this option is chosen
if keywords['edges']:
# get the coordinates
for nA, nB in keywords['edges']:
gA = g.node[nA]['graphics']
gB = g.node[nB]['graphics']
xA, yA = gA['x'], gA['y']
xB, yB = gB['x'], gB['y']
plt.plot([xA, xB], [yA, yB],
'-',
color=keywords['hedge_color'],
linewidth=keywords["hedge_width"],
linestyle=keywords['hedge_linestyle'])
# now iterate over the nodes
for n, d in graph.nodes(data=True):
cpaps = d['pap']
x, y = g.node[n]['graphics']['x'], g.node[n]['graphics']['y']
# get z-value which serves as zorder attribute
try:
z = 6 * len(tree.getConnectingEdges('root', n))
except:
z = 0
xvals += [x]
yvals += [y]
# plot the default marker
plt.plot(x,
y,
'o',
markersize=keywords['rootsize'],
color='black',
zorder=50)
# check for origins in cpaps
if 'O' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor='white',
zorder=57 + z,
linewidth=keywords['markeredgewidth'],
linestyle=keywords['gain_linestyle'],
)
figsp.add_artist(w)
# check for retentions
elif 'o' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor='white',
zorder=56 + z,
linewidth=keywords['markeredgewidth'],
linestyle='solid',
)
figsp.add_artist(w)
if 'L' in cpaps.values() and 'O' in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor=keywords['loss_background'],
zorder=58 + z,
linewidth=keywords['markeredgewidth'],
edgecolor='black',
linestyle=keywords['loss_linestyle'])
figsp.add_artist(w)
elif "L" in cpaps.values():
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] + keywords['outer_radius'],
0,
360,
facecolor=keywords['loss_background'],
zorder=59 + z,
linewidth=keywords['markeredgewidth'],
edgecolor='black',
)
figsp.add_artist(w)
# plot all wedges
for pap in cpaps:
theta1, theta2 = wedges[pap]
color = colors[pap]
# check for characteristics of this pap
# if it's a loss
if cpaps[pap] == 'L':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
alpha=keywords['loss_alpha'], # 0.25,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
linestyle=keywords['loss_linestyle'])
figsp.add_artist(w)
elif cpaps[pap] == 'o':
w = mpl.patches.Wedge((x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black')
figsp.add_artist(w)
elif cpaps[pap] == 'O':
w = mpl.patches.Wedge((x, y),
keywords['radius'],
theta1,
theta2,
facecolor=color,
zorder=61 + z,
linewidth=keywords['wedgeedgewidth'],
edgecolor='black',
linestyle=keywords['gain_linestyle'])
figsp.add_artist(w)
# add the labels if this option is chosen
if keywords['labels']:
# if node is a tip
if tgraph.node[n]['tip']:
# get the values
gf = tgraph.node[n]['graphics']
r = gf['angle']
x, y = gf['x'], gf['y']
ha = gf['s']
# modify the text
if ha == 'left':
text = keywords['_prefix'] + labels[n]
else:
text = labels[n] + keywords['_suffix']
# plot the text
plt.text(x,
y,
text,
size=keywords['textsize'],
va='center',
ha=ha,
fontweight='bold',
color='black',
rotation=r,
rotation_mode='anchor',
zorder=z)
# set up the xlimits
if not keywords['xlimr'] and not keywords['xliml']:
xl, xr = 2 * [keywords['xlim']]
else:
xl, xr = keywords['xliml'], keywords['xlimr']
# set up the xlimits
if not keywords['ylimt'] and not keywords['ylimb']:
yb, yt = 2 * [keywords['ylim']]
else:
yb, yt = keywords['ylimb'], keywords['ylimt']
plt.xlim((min(xvals) - xl, max(xvals) + xr))
plt.ylim((min(yvals) - yb, max(yvals) + yt))
prop = mpl.font_manager.FontProperties(size=keywords['legendsize'])
if keywords['legend']:
legend1 = plt.legend(legendEntriesA,
legendTextA,
loc=keywords['legendAloc'],
numpoints=1,
prop=prop)
plt.legend(legendEntriesB,
legendTextB,
loc=keywords['legendBloc'],
prop=prop)
figsp.add_artist(legend1)
plt.subplots_adjust(left=keywords['left'],
right=keywords['right'],
top=keywords['top'],
bottom=keywords['bottom'])
plt.savefig(filename + '.' + fileformat)
plt.clf()
log.file_written(filename + '.' + fileformat)
def plot_gls(
gls,
treestring,
degree=90,
fileformat='pdf',
**keywords
):
"""
Plot a gain-loss scenario for a given reference tree.
"""
# get kewyords
defaults = dict(
figsize=(15, 15),
left=0.05,
top=0.95,
bottom=0.05,
right=0.95,
radius=0.5,
textsize=8,
edgewidth=5,
linewidth=2,
scale_radius=1.2,
ylim=1,
xlim=1,
text=True,
gain_color='white',
loss_color='black',
gain_linestyle='dotted',
loss_linestyle='solid',
ax_linewidth=0,
filename=rcParams['filename']
)
for k in defaults:
if k not in keywords:
keywords[k] = defaults[k]
# set filename as variabel for convenience
filename = keywords['filename']
try:
tree = cg.LoadTree(treestring=treestring)
except:
try:
tree = cg.LoadTree(treestring)
except:
tree = treestring
tgraph = radial_layout(treestring, degree=degree)
graph = gls2gml(
gls,
tgraph,
tree
)
nodes = []
# assign nodes and edges
for n, d in graph.nodes(data=True):
g = d['graphics']
x = g['x']
y = g['y']
s = d['state']
nodes += [(x, y, s)]
# now plot the stuff
fig = plt.figure(figsize=keywords['figsize'])
figsp = fig.add_subplot(111)
figsp.axes.get_xaxis().set_visible(False)
figsp.axes.get_yaxis().set_visible(False)
# set the axes linewidht
for s in figsp.spines.values():
s.set_linewidth(keywords['ax_linewidth'])
plt.axis('equal')
for nA, nB in graph.edges():
xA = graph.node[nA]['graphics']['x']
xB = graph.node[nB]['graphics']['x']
yA = graph.node[nA]['graphics']['y']
yB = graph.node[nB]['graphics']['y']
plt.plot(
[xA, xB],
[yA, yB],
'-',
color='black',
linewidth=keywords['edgewidth'],
zorder=1
)
# now, iterate over nodes
for x, y, s in nodes:
if s == 'O':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
0, 360,
facecolor=keywords['gain_color'],
linewidth=keywords['linewidth'],
linestyle=keywords['gain_linestyle']
)
elif s == 'o':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] / keywords['scale_radius'],
0, 360,
facecolor=keywords['gain_color'],
linewidth=keywords['linewidth']
)
elif s == 'L':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'],
0, 360,
facecolor=keywords['loss_color'],
linewidth=keywords['linewidth'],
linestyle=keywords['loss_linestyle']
)
else:
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] / keywords['scale_radius'],
0, 360,
facecolor=keywords['loss_color'],
linewidth=keywords['linewidth']
)
figsp.add_artist(w)
# if text is chosen as argument
if keywords['text']:
if s in 'Oo':
t = '1'
c = 'black'
else:
t = '0'
c = 'white'
plt.text(
x,
y,
t,
size=keywords['textsize'],
color=c,
va="center",
ha="center",
fontweight='bold'
)
# set x and y-values
xvals = [x[0] for x in nodes]
yvals = [x[1] for x in nodes]
plt.xlim(min(xvals) - keywords['xlim'], max(xvals) + keywords['xlim'])
plt.ylim(min(yvals) - keywords['ylim'], max(yvals) + keywords['ylim'])
plt.subplots_adjust(
left=keywords['left'],
right=keywords['right'],
top=keywords['top'],
bottom=keywords['bottom']
)
plt.savefig(
filename + '.' + fileformat
)
plt.clf()
log.file_written(filename + '.' + fileformat)
def plot_gls(gls, treestring, degree=90, fileformat='pdf', **keywords):
"""
Plot a gain-loss scenario for a given reference tree.
"""
# get kewyords
defaults = dict(figsize=(15, 15),
left=0.05,
top=0.95,
bottom=0.05,
right=0.95,
radius=0.5,
textsize=8,
edgewidth=5,
linewidth=2,
scale_radius=1.2,
ylim=1,
xlim=1,
text=True,
gain_color='white',
loss_color='black',
gain_linestyle='dotted',
loss_linestyle='solid',
ax_linewidth=0,
filename=rcParams['filename'])
for k in defaults:
if k not in keywords:
keywords[k] = defaults[k]
# set filename as variabel for convenience
filename = keywords['filename']
try:
tree = cg.LoadTree(treestring=treestring)
except:
try:
tree = cg.LoadTree(treestring)
except:
tree = treestring
tgraph = radial_layout(treestring, degree=degree)
graph = gls2gml(gls, tgraph, tree)
nodes = []
# assign nodes and edges
for n, d in graph.nodes(data=True):
g = d['graphics']
x = g['x']
y = g['y']
s = d['state']
nodes += [(x, y, s)]
# now plot the stuff
fig = plt.figure(figsize=keywords['figsize'])
figsp = fig.add_subplot(111)
figsp.axes.get_xaxis().set_visible(False)
figsp.axes.get_yaxis().set_visible(False)
# set the axes linewidht
for s in figsp.spines.values():
s.set_linewidth(keywords['ax_linewidth'])
plt.axis('equal')
for nA, nB in graph.edges():
xA = graph.node[nA]['graphics']['x']
xB = graph.node[nB]['graphics']['x']
yA = graph.node[nA]['graphics']['y']
yB = graph.node[nB]['graphics']['y']
plt.plot([xA, xB], [yA, yB],
'-',
color='black',
linewidth=keywords['edgewidth'],
zorder=1)
# now, iterate over nodes
for x, y, s in nodes:
if s == 'O':
w = mpl.patches.Wedge((x, y),
keywords['radius'],
0,
360,
facecolor=keywords['gain_color'],
linewidth=keywords['linewidth'],
linestyle=keywords['gain_linestyle'])
elif s == 'o':
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] / keywords['scale_radius'],
0,
360,
facecolor=keywords['gain_color'],
linewidth=keywords['linewidth'])
elif s == 'L':
w = mpl.patches.Wedge((x, y),
keywords['radius'],
0,
360,
facecolor=keywords['loss_color'],
linewidth=keywords['linewidth'],
linestyle=keywords['loss_linestyle'])
else:
w = mpl.patches.Wedge(
(x, y),
keywords['radius'] / keywords['scale_radius'],
0,
360,
facecolor=keywords['loss_color'],
linewidth=keywords['linewidth'])
figsp.add_artist(w)
# if text is chosen as argument
if keywords['text']:
if s in 'Oo':
t = '1'
c = 'black'
else:
t = '0'
c = 'white'
plt.text(x,
y,
t,
size=keywords['textsize'],
color=c,
va="center",
ha="center",
fontweight='bold')
# set x and y-values
xvals = [x[0] for x in nodes]
yvals = [x[1] for x in nodes]
plt.xlim(min(xvals) - keywords['xlim'], max(xvals) + keywords['xlim'])
plt.ylim(min(yvals) - keywords['ylim'], max(yvals) + keywords['ylim'])
plt.subplots_adjust(left=keywords['left'],
right=keywords['right'],
top=keywords['top'],
bottom=keywords['bottom'])
plt.savefig(filename + '.' + fileformat)
plt.clf()
log.file_written(filename + '.' + fileformat)