def main():
# Get the command line arguments
args = docopt(__doc__)
fileNames = args['<reduce-files>']
estimatorToPlot = args['--estimator']
NDIM = int(args['--ndim'])
plotType = args['--plot_type']
title = args['--title']
hval = args['--hline'] and float(args['--hline'])
if args['--hline']:
if args['--hlabel']:
hlabel = args['--hlabel']
else:
hlabel = '%s = %5.2f' % (estimatorToPlot[0], hval)
if args['--legend']:
varLabel = [l for l in args['--legend']]
else:
varLabel = [None]
xLim = args['--xlim'] and [float(x) for x in args['--xlim']]
yLim = args['--ylim'] and [float(y) for y in args['--ylim']]
# Analyze the imput files
reduce = pimchelp.ScalarReduce(fileNames, None)
# Get a color scheme and marker list
numColors = max(reduce.getNumVarParams(), 2)
markers, colors = plotoptions.markersColors(numColors)
# create a description object
descrip = pimchelp.Description(NDIM)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# Plot each estimator
for n, est in enumerate(estimatorToPlot):
plt.figure(n + 1)
ax = plt.subplot(111)
if title:
plt.title(title)
# Add a possible horizontal line indicating some value
if args['--hline']:
plt.axhline(y=hval, color='#4d4d4d', linewidth=2.0, label=hlabel)
for i in range(reduce.getNumVarParams()):
lab = reduce.getVarLabel(i)
if not lab or varLabel:
lab = varLabel[i]
pOptions['color'] = colors[i]
# fill between to represent error bars
if 'f' in plotType:
emin = reduce.estimator(est, i) - reduce.estimatorError(est, i)
emax = reduce.estimator(est, i) + reduce.estimatorError(est, i)
plt.fill_between(reduce.param(),
emax,
emin,
color=colors[i],
alpha=0.2)
# plot with points
if 'p' in plotType:
plt.plot(reduce.param(),
reduce.estimator(est, i),
markerfacecolor=colors[i],
label=lab,
**pOptions)
# plot lines only
if plotType == 'l':
plt.plot(reduce.param(),
reduce.estimator(est, i),
label=lab,
**pOptions)
# plot errorbars
elif 'e' in plotType:
print pOptions
eb = plt.errorbar(reduce.param(),
reduce.estimator(est, i),
yerr=reduce.estimatorError(est, i),
label=lab)
# Set the width of the cap lines
# for cap in eb[1]:
# cap.set_mew(2.0)
plt.xlabel(descrip.paramLongName[reduce.reduceLabel], labelpad=16)
plt.ylabel(descrip.estimatorLongName[est])
leg = plt.legend(frameon=False, loc='best', prop={'size': 18})
if xLim != []:
plt.xlim(xLim[0], xLim[1])
if yLim != []:
plt.ylim(yLim[0], yLim[1])
plt.show()
def main():
# parse the command line options
args = docopt(__doc__)
fileNames = args["<file>"]
estimatorToPlot = args["--estimator"]
NDIM = int(args["--ndim"])
plotType = args["--plot"]
varLabel = args["--label"]
xLim = args["--xLim"]
yLim = args["--yLim"]
# don't want any empty lists
# if varLabel == []:
# varLabel = None
if xLim == []:
xLim = None
if yLim == []:
yLim = None
if len(fileNames) < 1:
sys.exit("\nNeed to specify at least one scalar estimator file\n")
# Analyze the imput files
# reduce = pimchelp.ScalarReduce(fileNames,varLabel)
reduce = pimchelp.ScalarReduce(fileNames, None)
# Get a color scheme and marker list
numColors = max(reduce.getNumVarParams(), 2)
markers, colors = plotoptions.markersColors(numColors)
# create a description object
descrip = pimchelp.Description(NDIM)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# Plot each estimator
for n, est in enumerate(estimatorToPlot):
if args["--same"]:
pl.figure(1)
else:
pl.figure(n + 1)
ax = pl.subplot(111)
for i in range(reduce.getNumVarParams()):
if args["--same"]:
lab = varLabel[n]
else:
lab = reduce.getVarLabel(i)
pOptions["color"] = colors[i]
if "p" in plotType:
pl.plot(reduce.param(), reduce.estimator(est, i), markerfacecolor=colors[i], label=lab, **pOptions)
if plotType == "l":
pl.plot(reduce.param(), reduce.estimator(est, i), label=lab, **pOptions)
elif "e" in plotType:
if args["--same"]:
eb = pl.errorbar(
reduce.param(),
reduce.estimator(est, i),
yerr=reduce.estimatorError(est, i),
markerfacecolor=colors[i + n],
ecolor=colors[i + n],
label=lab,
**pOptions
)
else:
eb = pl.errorbar(
reduce.param(),
reduce.estimator(est, i),
yerr=reduce.estimatorError(est, i),
markerfacecolor=colors[i],
ecolor=colors[i],
label=lab,
**pOptions
)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(2.0)
# pl.tight_layout()
pl.xlabel(descrip.paramLongName[reduce.reduceLabel], fontsize=18)
pl.ylabel(descrip.estimatorLongName[est], fontsize=18)
leg = pl.legend(frameon=False, loc="best", prop={"size": 18})
if xLim != None:
pl.xlim(xLim[0], xLim[1])
if yLim != None:
pl.ylim(yLim[0], yLim[1])
pl.grid(True)
pl.show()
def main():
# Get the command line arguments
args = docopt(__doc__)
fileNames = args['<reduce-files>']
estimatorToPlot = args['--estimator']
NDIM = int(args['--ndim'])
plotType = args['--plot_type']
title = args['--title']
hval = args['--hline'] and float(args['--hline'])
if args['--hline']:
if args['--hlabel']:
hlabel = args['--hlabel']
else:
hlabel = '%s = %5.2f' % (estimatorToPlot[0],hval)
if args['--legend']:
varLabel = [l for l in args['--legend']]
else:
varLabel = [None]
xLim = args['--xlim'] and [float(x) for x in args['--xlim']]
yLim = args['--ylim'] and [float(y) for y in args['--ylim']]
# Analyze the imput files
reduce = pimchelp.ScalarReduce(fileNames,None)
# Get a color scheme and marker list
numColors = max(reduce.getNumVarParams(),2)
markers,colors = plotoptions.markersColors(numColors)
# create a description object
descrip = pimchelp.Description(NDIM)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# Plot each estimator
for n,est in enumerate(estimatorToPlot):
plt.figure(n+1)
ax = plt.subplot(111)
if title:
plt.title(title)
# Add a possible horizontal line indicating some value
if args['--hline']:
plt.axhline(y=hval,color='#4d4d4d',linewidth=2.0,label=hlabel)
for i in range(reduce.getNumVarParams()):
lab = reduce.getVarLabel(i)
if not lab or varLabel:
lab = varLabel[i]
pOptions['color'] = colors[i]
# fill between to represent error bars
if 'f' in plotType:
emin = reduce.estimator(est,i)-reduce.estimatorError(est,i)
emax = reduce.estimator(est,i)+reduce.estimatorError(est,i)
plt.fill_between(reduce.param(), emax,emin, color=colors[i],
alpha=0.2)
# plot with points
if 'p' in plotType:
plt.plot(reduce.param(), reduce.estimator(est,i),
markerfacecolor=colors[i],label=lab, **pOptions)
# plot lines only
if plotType == 'l':
plt.plot(reduce.param(), reduce.estimator(est,i),
label=lab,**pOptions)
# plot errorbars
elif 'e' in plotType:
eb = plt.errorbar(reduce.param(), reduce.estimator(est,i),
yerr=reduce.estimatorError(est,i),
markerfacecolor=colors[i], ecolor=colors[i],
label=lab, **pOptions)
# Set the width of the cap lines
# for cap in eb[1]:
# cap.set_mew(2.0)
plt.xlabel(descrip.paramLongName[reduce.reduceLabel],labelpad=16)
plt.ylabel(descrip.estimatorLongName[est])
leg = plt.legend(frameon=False, loc='best', prop={'size':18})
if xLim != []:
plt.xlim(xLim[0],xLim[1])
if yLim != []:
plt.ylim(yLim[0],yLim[1])
plt.show()
def main():
# setup the argument parser
parser = argparse.ArgumentParser(description='Plot a vector estimator.')
parser.add_argument('fileNames',
help='Reduced scalar estimator files',
nargs='+')
parser.add_argument('--ndim',
'-d',
help='Number of spatial dimensions.',
type=int,
default=3)
parser.add_argument('--plot',
'-p',
help='The plot type. l = lines, p = points, \
e = errorbars',
type=str,
choices=['l', 'e', 'p', 'lp', 'le'],
default='e')
parser.add_argument('--label',
'-l',
help='Parameter name for labels.',
type=str)
parser.add_argument('--subplot',
'-s',
help='Dimensions of a subplot matrix.',
type=int,
nargs='+')
parser.add_argument('--xlim',
'-x',
help='x-axis limits',
type=float,
nargs='+')
parser.add_argument('--ylim',
'-y',
help='y-axis limits',
type=float,
nargs='+')
parser.add_argument('--log',
help='Set y-axis log scale',
action='store_true')
args = parser.parse_args()
fileNames = args.fileNames
NDIM = args.ndim
varLabel = args.label
plotType = args.plot
subplot = args.subplot
xLim = args.xlim
yLim = args.ylim
log = args.log
if len(fileNames) < 1:
parser.error("Need to specify at least one vector estimator file")
# Analyze the imput files
estimatorName = pimchelp.getVectorEstimatorName(fileNames[0])
print estimatorName
reduce = pimchelp.VectorReduce(fileNames, estimatorName, varLabel)
# Get a color scheme and marker list
numColors = reduce.getNumReduceParams()
markers, colors = plotoptions.markersColors(numColors)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# create a description object
descrip = pimchelp.Description(NDIM)
# Plot each estimator
for varIndex in range(reduce.getNumVarParams()):
pl.figure(varIndex + 1)
#ax = pl.subplot(111)
for reduceIndex in range(reduce.getNumReduceParams()):
lab = reduce.getReduceLabel(reduceIndex)
pOptions['color'] = colors[reduceIndex]
if 'e' in plotType:
eb = pl.errorbar(reduce.x(varIndex, reduceIndex),
reduce.estimator(varIndex, reduceIndex),
yerr=reduce.estimatorError(
varIndex, reduceIndex),
markerfacecolor=colors[reduceIndex],
ecolor=colors[reduceIndex],
label=lab,
**pOptions)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(1.0)
else:
pl.plot(reduce.x(varIndex, reduceIndex),
reduce.estimator(varIndex, reduceIndex),
label=lab,
**pOptions)
pl.xlabel(descrip.estimatorXLongName[estimatorName])
pl.ylabel(descrip.estimatorLongName[estimatorName])
leg = pl.legend(frameon=False, loc='best', prop={'size': 18})
# # Add a colorbar
# cmap = loadgmt.getcmap('cb/div','Spectral_08')
# T = reduce.param()[::2]
# cb = pl.colorbar(loadgmt.getMap(cmap,T),ax=ax,ticks=T)
# cb.ax.set_ylabel('Temperature',rotation=-90)
if xLim != None:
pl.xlim(xLim[0], xLim[1])
if yLim != None:
pl.ylim(yLim[0], yLim[1])
# Set a log scale
if log:
ax = pl.subplot(111)
ax.set_yscale('log')
# Plot a possible subplot matrix
if subplot != None:
f, ax = pl.subplots(subplot[0],
subplot[1],
sharex=True,
squeeze=False,
sharey=True)
numReduce = reduce.getNumReduceParams()
for reduceIndex in range(reduce.getNumReduceParams()):
id = getIndex(reduceIndex, subplot, 2)
pOptions['color'] = colors[reduceIndex]
lab = reduce.getReduceLabel(reduceIndex)
for varIndex in range(reduce.getNumVarParams()):
pOptions['marker'] = markers[varIndex]
if 'e' in plotType:
eb = ax[id[0], id[1]].errorbar(
reduce.x(varIndex, reduceIndex),
reduce.estimator(varIndex, reduceIndex),
yerr=reduce.estimatorError(0, reduceIndex),
markerfacecolor=colors[reduceIndex],
ecolor=colors[reduceIndex],
label=lab,
**pOptions)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(1.0)
else:
ax[id[0],
id[1]].plot(reduce.x(varIndex, reduceIndex),
reduce.estimator(varIndex, reduceIndex),
label=lab,
**pOptions)
ax[id[0], id[1]].legend(frameon=False,
loc='upper left',
prop={'size': 18})
if xLim != None:
ax[id[0], id[1]].set_xlim(xLim[0], xLim[1])
if yLim != None:
ax[id[0], id[1]].set_ylim(yLim[0], yLim[1])
[
ax[-1, n].set_xlabel(descrip.estimatorXLongName[estimatorName])
for n in range(subplot[1])
]
[
ax[n, 0].set_ylabel(descrip.estimatorLongName[estimatorName])
for n in range(subplot[0])
]
f.subplots_adjust(hspace=0.10)
f.subplots_adjust(wspace=0.10)
pl.show()
def main():
# setup the argument parser
parser = argparse.ArgumentParser(description='Plot a vector estimator.')
parser.add_argument('fileNames', help='Reduced scalar estimator files', nargs='+')
parser.add_argument('--ndim', '-d', help='Number of spatial dimensions.',
type=int, default=3)
parser.add_argument('--plot','-p', help='The plot type. l = lines, p = points, \
e = errorbars', type=str, choices=['l','e','p','lp','le'],
default='e')
parser.add_argument('--label', '-l', help='Parameter name for labels.', type=str)
parser.add_argument('--subplot', '-s', help='Dimensions of a subplot matrix.',
type=int, nargs='+')
parser.add_argument('--xlim', '-x', help='x-axis limits', type=float,
nargs='+')
parser.add_argument('--ylim', '-y', help='y-axis limits', type=float,
nargs='+')
parser.add_argument('--log', help='Set y-axis log scale',
action='store_true')
args = parser.parse_args()
fileNames = args.fileNames
NDIM = args.ndim
varLabel = args.label
plotType = args.plot
subplot = args.subplot
xLim = args.xlim
yLim = args.ylim
log = args.log
if len(fileNames) < 1:
parser.error("Need to specify at least one vector estimator file")
# Analyze the imput files
estimatorName = pimchelp.getVectorEstimatorName(fileNames[0])
print estimatorName
reduce = pimchelp.VectorReduce(fileNames,estimatorName,varLabel)
# Get a color scheme and marker list
numColors = reduce.getNumReduceParams()
markers,colors = plotoptions.markersColors(numColors)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# create a description object
descrip = pimchelp.Description(NDIM)
# Plot each estimator
for varIndex in range(reduce.getNumVarParams()):
pl.figure(varIndex+1)
#ax = pl.subplot(111)
for reduceIndex in range(reduce.getNumReduceParams()):
lab = reduce.getReduceLabel(reduceIndex)
pOptions['color'] = colors[reduceIndex]
if 'e' in plotType:
eb = pl.errorbar(reduce.x(varIndex,reduceIndex),
reduce.estimator(varIndex,reduceIndex),
yerr=reduce.estimatorError(varIndex,reduceIndex),
markerfacecolor=colors[reduceIndex],
ecolor=colors[reduceIndex], label=lab,
**pOptions)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(1.0)
else:
pl.plot(reduce.x(varIndex,reduceIndex),
reduce.estimator(varIndex,reduceIndex),
label=lab, **pOptions)
pl.xlabel(descrip.estimatorXLongName[estimatorName])
pl.ylabel(descrip.estimatorLongName[estimatorName])
leg = pl.legend(frameon=False, loc='best', prop={'size':18})
# # Add a colorbar
# cmap = loadgmt.getcmap('cb/div','Spectral_08')
# T = reduce.param()[::2]
# cb = pl.colorbar(loadgmt.getMap(cmap,T),ax=ax,ticks=T)
# cb.ax.set_ylabel('Temperature',rotation=-90)
if xLim != None:
pl.xlim(xLim[0],xLim[1])
if yLim != None:
pl.ylim(yLim[0],yLim[1])
# Set a log scale
if log:
ax = pl.subplot(111)
ax.set_yscale('log')
# Plot a possible subplot matrix
if subplot != None:
f, ax = pl.subplots(subplot[0], subplot[1], sharex=True, squeeze=False, sharey=True)
numReduce = reduce.getNumReduceParams()
for reduceIndex in range(reduce.getNumReduceParams()):
id = getIndex(reduceIndex,subplot,2)
pOptions['color'] = colors[reduceIndex]
lab = reduce.getReduceLabel(reduceIndex)
for varIndex in range(reduce.getNumVarParams()):
pOptions['marker'] = markers[varIndex]
if 'e' in plotType:
eb = ax[id[0],id[1]].errorbar(reduce.x(varIndex,reduceIndex),
reduce.estimator(varIndex,reduceIndex),
yerr=reduce.estimatorError(0,reduceIndex),
markerfacecolor=colors[reduceIndex],
ecolor=colors[reduceIndex], label=lab,
**pOptions)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(1.0)
else:
ax[id[0],id[1]].plot(reduce.x(varIndex,reduceIndex),
reduce.estimator(varIndex,reduceIndex),
label=lab, **pOptions)
ax[id[0],id[1]].legend(frameon=False, loc='upper left', prop={'size':18})
if xLim != None:
ax[id[0],id[1]].set_xlim(xLim[0],xLim[1])
if yLim != None:
ax[id[0],id[1]].set_ylim(yLim[0],yLim[1])
[ax[-1,n].set_xlabel(descrip.estimatorXLongName[estimatorName]) for n in range(subplot[1])]
[ax[n,0].set_ylabel(descrip.estimatorLongName[estimatorName]) for n in range(subplot[0])]
f.subplots_adjust(hspace=0.10)
f.subplots_adjust(wspace=0.10)
pl.show()
def main():
# parse the command line options
args = docopt(__doc__)
fileNames = args['<file>']
estimatorToPlot = args['--estimator']
NDIM = int(args['--ndim'])
plotType = args['--plot']
varLabel = args['--label']
xLim = args['--xLim']
yLim = args['--yLim']
# don't want any empty lists
#if varLabel == []:
# varLabel = None
if xLim == []:
xLim = None
if yLim == []:
yLim = None
if len(fileNames) < 1:
sys.exit("\nNeed to specify at least one scalar estimator file\n")
# Analyze the imput files
#reduce = pimchelp.ScalarReduce(fileNames,varLabel)
reduce = pimchelp.ScalarReduce(fileNames, None)
# Get a color scheme and marker list
numColors = max(reduce.getNumVarParams(), 2)
markers, colors = plotoptions.markersColors(numColors)
# create a description object
descrip = pimchelp.Description(NDIM)
# get the plot options
pOptions = plotoptions.plotOptions(plotType)
# Plot each estimator
for n, est in enumerate(estimatorToPlot):
if args['--same']:
pl.figure(1)
else:
pl.figure(n + 1)
ax = pl.subplot(111)
for i in range(reduce.getNumVarParams()):
if args['--same']:
lab = varLabel[n]
else:
lab = reduce.getVarLabel(i)
pOptions['color'] = colors[i]
if 'p' in plotType:
pl.plot(reduce.param(),
reduce.estimator(est, i),
markerfacecolor=colors[i],
label=lab,
**pOptions)
if plotType == 'l':
pl.plot(reduce.param(),
reduce.estimator(est, i),
label=lab,
**pOptions)
elif 'e' in plotType:
if args['--same']:
eb = pl.errorbar(reduce.param(),
reduce.estimator(est, i),
yerr=reduce.estimatorError(est, i),
markerfacecolor=colors[i + n],
ecolor=colors[i + n],
label=lab,
**pOptions)
else:
eb = pl.errorbar(reduce.param(),
reduce.estimator(est, i),
yerr=reduce.estimatorError(est, i),
markerfacecolor=colors[i],
ecolor=colors[i],
label=lab,
**pOptions)
# Set the width of the cap lines
for cap in eb[1]:
cap.set_mew(2.0)
#pl.tight_layout()
pl.xlabel(descrip.paramLongName[reduce.reduceLabel], fontsize=18)
pl.ylabel(descrip.estimatorLongName[est], fontsize=18)
leg = pl.legend(frameon=False, loc='best', prop={'size': 18})
if xLim != None:
pl.xlim(xLim[0], xLim[1])
if yLim != None:
pl.ylim(yLim[0], yLim[1])
pl.grid(True)
pl.show()
