import matplotlib
if matplotlib.__version__ < '0.65':
import matplotlib.matlab as MM
else:
import matplotlib.pylab as MM
except:
print ' If you had Matplotlib installed, you would be looking'
print ' at timing plots right now...'
sys.exit(0)
darkblue = '#2c11cf'
lightblue = '#8f84e0'
steelblue = '#5d82ef'
x = range(len(t_lst.keys()))
ax = []
ax.append(MM.axes([.05, .05, .40, .40])) # lower left
ax.append(MM.axes([.05, .55, .40, .40])) # upper left
ax.append(MM.axes([.55, .05, .40, .40])) # lower right
ax.append(MM.axes([.55, .55, .40, .40])) # upper right
for i in range(4):
ax[i].plot(x, [t_lst[k][i] for k in K],
color=darkblue,
linewidth=3)
ax[i].plot(x, [t_ref[k][i] for k in K],
color=lightblue,
linewidth=3)
ax[i].set_xticks([])
ax[i].set_title('Limited memory p = %-d' % plist[i],
fontsize='small')
ax[i].legend(['Python', 'Fortran'], 'upper left')
for i in [2, 3]:
def __init__(self, solvers, **kwargs):
self.solvers = solvers
# Obtain options class with all default values
self.opts = OptionClass()
# Assign non-default options
self.SetOptions(**kwargs)
self.bw = self.opts.bw
import matplotlib
matplotlib.use(self.opts.backend)
if matplotlib.__version__ < '0.65':
import matplotlib.matlab as MM
else:
import matplotlib.pylab as MM
self.linestyle = [ '-', '--', '-.', ':', '.', ',', 'o', '^', 'v', '<',
'>', 's', '+', 'x', 'D', 'd', '1', '2', '3', '4',
'h', 'H', 'p', '|', '_' ]
self.nlstyles = len(self.linestyle)
self.grays = [ '0.0', '0.5', '0.8', '0.2', '0.6', '0.9', '0.4', '0.95' ]
self.ngrays = len(self.grays)
self.color = [ 'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w' ]
self.ncolors = len(self.color)
self.metrics = MetricsClass(self.solvers, self.opts)
self.pprofs = RatioClass(self.metrics, self.opts)
self.nprobs = self.metrics.nprobs
self.nsolvs = self.metrics.nsolvs
self.ax = MM.axes()
# Generate the y-axis data
self.ydata = numpy.arange(self.nprobs) * (1.0 / self.nprobs)
# Set the x-axis ranges
self.xmax = self.pprofs.maxrat + 1.0e-3
if self.opts.logscale is not None:
self.xmax = max(self.opts.logscale, self.xmax)
else:
self.xmax = max(1, self.xmax)
self.epsilon = 0.0
plotargs = {}
if self.opts.logscale is not None:
self.mmplotcmd = self.ax.semilogx
plotargs['basex'] = self.opts.logscale
self.epsilon = 0.001
self.xmin = 1.0
else:
self.mmplotcmd = self.ax.plot
self.xmin = 0.0
# Generate arguments for the gplot command
self.profiles = []
lscount = 0
colcount = 0
for s in range(self.nsolvs):
if self.bw:
#curcolor = 'k'
curcolor = self.grays[(colcount % self.ngrays)]
else:
curcolor = self.color[(colcount % self.ncolors)]
lstyle = '' #self.linestyle[(lscount % self.nlstyles)]
sname = self.solvers[s]
srats = self.pprofs.solv_ratios(s)
if self.opts.logscale is not None:
srats += self.epsilon
self.profiles.append(self.mmplotcmd(srats,
self.ydata,
curcolor + lstyle,
linewidth=2.5,
drawstyle='steps-pre',
antialiased=True,
**plotargs))
#if self.bw: lscount += 1
#if (lscount % self.nlstyles) == 0 and not self.bw:
colcount += 1
if self.opts.logscale is not None:
self.ax.set_xscale('log', basex=self.opts.logscale)
# Set legend if required
if self.opts.legend:
self.ax.legend(self.solvers, 'lower right')
if self.opts.title:
self.ax.set_title(self.opts.title)
if self.opts.xlabel:
self.ax.set_xlabel(self.opts.xlabel)
if self.opts.ylabel:
self.ax.set_ylabel(self.opts.ylabel)
self.ax.set_xlim([self.xmin, self.xmax])
self.ax.set_ylim([self.opts.ymin, self.opts.ymax])
self.show = MM.show
self.savefig = MM.savefig
import matplotlib
if matplotlib.__version__ < '0.65':
import matplotlib.matlab as MM
else:
import matplotlib.pylab as MM
except:
print ' If you had Matplotlib installed, you would be looking'
print ' at timing plots right now...'
sys.exit(0)
darkblue = '#2c11cf'
lightblue = '#8f84e0'
steelblue = '#5d82ef'
x = range(len(t_lst.keys()))
ax = []
ax.append(MM.axes([ .05, .05, .40, .40 ])) # lower left
ax.append(MM.axes([ .05, .55, .40, .40 ])) # upper left
ax.append(MM.axes([ .55, .05, .40, .40 ])) # lower right
ax.append(MM.axes([ .55, .55, .40, .40 ])) # upper right
for i in range(4):
ax[i].plot(x, [ t_lst[k][i] for k in K ], color=darkblue, linewidth=3)
ax[i].plot(x, [ t_ref[k][i] for k in K ], color=lightblue, linewidth=3)
ax[i].set_xticks([])
ax[i].set_title('Limited memory p = %-d' % plist[i], fontsize='small')
ax[i].legend(['Python', 'Fortran'], 'upper left')
for i in [2,3]:
ax[i].set_ylabel('Time (s)', fontsize='small')
MM.show()
# For the number of iterations, use first value of p as reference
x = range(len(i_lst.keys()))