def init_figures(issplit, isvector, naxes, nplots):
"""
initialize figures and set up backends
issplit: true if we're making separate vector and raster figures
isvector: true if we're making vector lines
naxes: number of axes, used for sizing
nplots: number of subplots, used for sizing
"""
figsize = (3 + 0.6 * naxes, 2 + (4 / 3) * nplots)
# figsize = (3 + 0.6 * naxes, 2 + (10/3) * nplots)
if issplit:
raster = matplotlib.figure.Figure(figsize=figsize)
agg.FigureCanvasAgg(raster)
vector = matplotlib.figure.Figure(figsize=figsize)
svg.FigureCanvasSVG(vector)
elif isvector:
vector = matplotlib.figure.Figure(figsize=figsize)
svg.FigureCanvasSVG(vector)
raster = vector
else:
raster = matplotlib.figure.Figure(figsize=figsize)
agg.FigureCanvasAgg(raster)
vector = raster
return raster, vector
def cli():
args = get_args()
algos = args.algos.split(",")
print algos
problems = args.problems.split(",")
print problems
nalgos = len(algos)
nproblems = len(problems)
fig = matplotlib.figure.Figure(figsize=(nalgos * 3, nproblems * 2.2))
if args.svg:
svg.FigureCanvasSVG(fig)
else:
agg.FigureCanvasAgg(fig)
keywords = {}
keywords["stat"] = args.stat
keywords["metric"] = args.metric
keywords["dirname"] = args.stats_directory
if args.cbar_context_low is not None:
keywords["context_l"] = args.cbar_context_low
if args.cbar_context_high is not None:
keywords["context_h"] = args.cbar_context_high
if args.best is not None:
keywords["best"] = args.best
if args.worst is not None:
keywords["worst"] = args.worst
controlmaps(fig, algos, problems, args.params_dir, **keywords)
fig.subplots_adjust(right=0.88, wspace=0.03, hspace=0.3)
fig.savefig(args.output_file)
def make_image(func, data, fig_format='svg', **kwds):
content_type = {'png': 'image/png', 'svg': 'image/svg+xml'}[fig_format]
fig = __figs.get(tuple(kwds.items()), None)
if fig is None:
fig = mpl.figure.Figure(**kwds)
canvas = backend_svg.FigureCanvasSVG(fig)
__figs[tuple(kwds.items())] = fig
else:
fig.clear()
func(fig, data)
buff = io.BytesIO()
fig.savefig(buff, format=fig_format)
img = buff.getvalue()
height = int(fig.get_dpi() * fig.get_figheight())
width = int(fig.get_dpi() * fig.get_figwidth())
return img, width, height
def cli():
args = get_args()
table = pandas.read_table(args.table, sep=' ')
fig = matplotlib.figure.Figure()
if args.vector:
svg.FigureCanvasSVG(fig)
else:
agg.FigureCanvasAgg(fig)
algos = args.algos.split(",")
barchart_figure(fig,
table,
algos,
args.key,
barwidth=args.width,
barheight=args.height)
fig.savefig(args.output)
===========================================================
statusplot.py
"""
import pandas
import matplotlib
import matplotlib.backends.backend_svg as svg
from numpy import array
status = pandas.read_table("status.txt", index_col=0)
grouped = status.groupby(["alg", "dv", "obj", "eps"])
status["progress"] = status.apply(lambda row: float(row["sets"]) / row["needed"], axis = 1)
means = grouped["progress"].mean()
width, height = matplotlib.figure.figaspect(0.2)
print width, height
fig = matplotlib.figure.Figure(figsize = (width, height))
svg.FigureCanvasSVG(fig)
colors = means.apply(lambda progress: [[0.7, 0.7, 0.2],[0.2,0.8,0.2]][int(progress)])
subplots = ["Borg", "eMOEA", "eNSGAII", "NSGAII"]
for ii in range(len(subplots)):
alg = subplots[ii]
ax = fig.add_subplot(1,4,ii+1)
co = array(list(colors.ix[alg].values))
ax.barh(range(6), means.ix[alg].values, color=co)
ax.set_yticks([])
ax.set_yticks([0.4 + x for x in range(6)])
ax.set_yticklabels(["","","","","",""])
ax.set_xticks([0, 0.25, 0.5, 0.75, 1.0])
ax.set_xticklabels(["0", "", "0.5", "", "1"])
ax.set_title(alg)
labels = means.ix["Borg"].index.values
