def plot(self, resp, zai=None, pert=None, mat=None, mevscale=False,
egrid=None, sigma=3, normalize=True, ax=None, labelFmt=None,
title=None, logx=True, logy=False, loglog=False, xlabel=None,
ylabel=None, legend=None, ncol=1):
"""
Plot sensitivities due to some or all perturbations.
.. note::
Without passing ``zai``, ``pert``, or ``mat``
arguments, this method will plot all permutations of
sensitivities for a given response.
Parameters
----------
resp: str
Name of the specific response to be examined. Must be a key
in ``sensitivities`` and ``energyIntegratedSens``
zai: None or str or int or iterable
Plot sensitivities due to these isotopes. Passing ``None``
will plot against all isotopes.
pert: None or str or list of strings
Plot sensitivities due to these perturbations. Passing ``None``
will plot against all perturbations.
mat: None or str or list of strings
Plot sensitivities due to these materials. Passing ``None``
will plot against all materials.
mevscale : bool, optional
Flag for plotting energy grid in MeV units. If ``True``, the energy
axis is expressed in MeV. Default is ``False``.
egrid : numpy.array, optional
User-defined energy grid boundaries displayed on the sensitivities
as vblack, dashed vertical lines. Default is ``None``.
{sigma}
normalize: True
Normalize plotted data per unit lethargy
{ax}
labelFmt: None or str
Formattable string to be applied to the labels.
The following entries will be formatted for each plot
permuation::
{m} - name of the material
{z} - isotope zai
{p} - specific perturbation
{r} - response being plotted
{logx}
{logy}
{loglog}
{xlabel}
{ylabel}
{legend}
{ncol}
Returns
-------
{rax}
Raises
------
KeyError
If response or any passed perturbation settings are not
present on the object
See Also
--------
* :py:meth:`str.format` - used for formatting labels
"""
for subDict in {'sensitivities', 'energyIntegratedSens'}:
if resp not in getattr(self, subDict):
raise KeyError("Response {} missing from {}"
.format(resp, subDict))
labelFmt = labelFmt or "mat: {m} zai: {z} pert: {p}"
if isinstance(zai, (str, int)):
zai = {zai, }
zais = self._getCleanedPertOpt('zais', zai)
perts = self._getCleanedPertOpt('perts', pert)
mats = self._getCleanedPertOpt('materials', mat)
ax = ax or gca()
sigma = max(int(sigma), 0)
resMat = self.sensitivities[resp]
values = resMat[..., 0]
if normalize:
values = values.copy() / self.lethargyWidths
errors = resMat[..., 1] * values * sigma
energies = self.energies if mevscale else self.energies * 1E6
for z, m, p in product(zais, mats, perts):
iZ = self.zais[z]
iM = self.materials[m]
iP = self.perts[p]
yVals = values[iM, iZ, iP]
yVals = hstack((yVals, yVals[-1]))
yErrs = errors[iM, iZ, iP]
yErrs = hstack((yErrs, yErrs[-1]))
label = labelFmt.format(r=resp, z=z, m=m, p=p)
ax.errorbar(energies, yVals, yErrs, label=label,
drawstyle='steps-post')
if egrid is not None:
for group in egrid:
ax.axvline(group, color='k', linestyle='dashed')
if xlabel is None:
xlabel = "Energy [MeV]" if mevscale else "Energy [eV]"
if ylabel is None:
parts = ["Sensitivity"]
if normalize:
parts.append("per unit lethargy")
if sigma:
parts.append(r"$\pm{}\sigma$".format(sigma))
ylabel = " ".join(parts)
ax = formatPlot(ax, loglog=loglog, logx=logx, logy=logy, legendcols=ncol,
legend=legend, xlabel=xlabel, ylabel=ylabel)
return ax
def plot(self,
resp,
zai=None,
pert=None,
mat=None,
sigma=3,
normalize=True,
ax=None,
labelFmt=None,
title=None,
logx=True,
logy=False,
loglog=False,
xlabel=None,
ylabel=None,
legend=None,
ncol=1):
"""
Plot sensitivities due to some or all perturbations.
.. note::
Without passing ``zai``, ``pert``, or ``mat``
arguments, this method will plot all permutations of
sensitivities for a given response.
Parameters
----------
resp: str
Name of the specific response to be examined. Must be a key
in ``sensitivities`` and ``energyIntegratedSens``
zai: None or str or int or iterable
Plot sensitivities due to these isotopes. Passing ``None``
will plot against all isotopes.
pert: None or str or list of strings
Plot sensitivities due to these perturbations. Passing ``None``
will plot against all perturbations.
mat: None or str or list of strings
Plot sensitivities due to these materials. Passing ``None``
will plot against all materials.
{sigma}
normalize: True
Normalize plotted data per unit lethargy
{ax}
labelFmt: None or str
Formattable string to be applied to the labels.
The following entries will be formatted for each plot
permuation::
{m} - name of the material
{z} - isotope zai
{p} - specific perturbation
{r} - response being plotted
{logx}
{logy}
{loglog}
{xlabel}
{ylabel}
{legend}
{ncol}
Returns
-------
{rax}
Raises
------
KeyError
If response or any passed perturbation settings are not
present on the object
See Also
--------
* :py:meth:`str.format` - used for formatting labels
"""
for subDict in {'sensitivities', 'energyIntegratedSens'}:
if resp not in getattr(self, subDict):
raise KeyError("Response {} missing from {}".format(
resp, subDict))
labelFmt = labelFmt or "mat: {m} zai: {z} pert: {p}"
if isinstance(zai, (str, int)):
zai = {
zai,
}
zais = self._getCleanedPertOpt('zais', zai)
perts = self._getCleanedPertOpt('perts', pert)
mats = self._getCleanedPertOpt('materials', mat)
ax = ax or gca()
sigma = max(int(sigma), 0)
resMat = self.sensitivities[resp]
values = resMat[..., 0]
if normalize:
values = values.copy() / self.lethargyWidths
errors = resMat[..., 1] * values * sigma
energies = self.energies * 1E6
for z, m, p in product(zais, mats, perts):
iZ = self.zais[z]
iM = self.materials[m]
iP = self.perts[p]
yVals = values[iM, iZ, iP]
yVals = hstack((yVals, yVals[-1]))
yErrs = errors[iM, iZ, iP]
yErrs = hstack((yErrs, yErrs[-1]))
label = labelFmt.format(r=resp, z=z, m=m, p=p)
ax.errorbar(energies,
yVals,
yErrs,
label=label,
drawstyle='steps-post')
xlabel = 'Energy [eV]' if xlabel is None else xlabel
ylabel = ylabel if ylabel is not None else ('Sensitivity {} {}'.format(
'per unit lethargy' if normalize else '',
r'$\pm{}\sigma$'.format(sigma) if sigma else ''))
ax = formatPlot(ax,
loglog=loglog,
logx=logx,
logy=logy,
ncol=ncol,
legend=legend,
xlabel=xlabel,
ylabel=ylabel.strip())
return ax
def plot(self,
mts='all',
ax=None,
loglog=False,
xlabel=None,
ylabel=None,
logx=True,
logy=False,
title=None,
legend=None,
ncol=1,
**kwargs):
"""
Return a matplotlib figure for plotting XS.
mts should be a list of the desired MT numbers to plot for this
XS. Units should automatically be fixed between micro and macro XS.
Parameters
----------
mts: int, string, or list of ints
If it's a string, it should be 'all'.
A single int indicates one MT reaction number.
A list should be a list of MT numbers to plot.
{ax}
{loglog}
{logx}
{logy}
{xlabel}
{ylabel}
{title}
{legend}
{ncol}
{kwargs} :py:func:`matplotlib.pyplot.plot`
Returns
-------
{rax}
Raises
------
TypeError
if MT numbers that don't make sense come up
"""
if mts == 'all':
mts = self.MT
elif isinstance(mts, int):
# convert to list if it's just one MT
mts = [mts]
elif isinstance(mts, list) and all([isinstance(ii, int)
for ii in mts]):
pass
else:
msg = ("mts argument must be a string saying 'all',"
"a list of integer MTs, or a single interger"
"instead, {} of type {} was passed.".format(mts, type(mts)))
raise TypeError(msg)
for mt in mts:
if mt not in self.MT:
error("{} not in collected MT numbers, {}".format(mt, self.MT))
ax = ax or pyplot.gca()
x = self.metadata['egrid']
for mt in mts:
for i, MT in enumerate(self.MT):
if mt == MT:
y = self.xsdata[:, i]
ax.plot(x, y, drawstyle='steps', label=self.MTdescrip[i])
title = title or '{} cross section{}'.format(
self.name, 's' if len(mts) > 1 else '')
xlabel = xlabel or "Energy [MeV]"
ylabel = ylabel or (
'Cross Section ({})'.format('b' if self.isIso else 'cm$^{-1}$'))
ax = formatPlot(ax,
loglog=loglog,
logx=logx,
logy=logy,
ncol=ncol,
legend=legend,
title=title,
xlabel=xlabel,
ylabel=ylabel)
return ax
def plot(self,
mts='all',
ax=None,
loglog=False,
xlabel=None,
ylabel=None,
logx=True,
logy=False,
title=None,
legend=None,
ncol=1,
labels=None,
**kwargs):
"""
Plot XS corresponding to their MTs.
Parameters
----------
mts : int, string, or list of ints
If it's a string, it should be 'all'.
A single int indicates one MT reaction number.
A list should be a list of MT numbers to plot.
{ax}
{loglog}
{logx}
{logy}
{xlabel}
{ylabel}
{title}
{legend}
{ncol}
labels : str or list of str or dict {int: str}
Labels to apply to the plot. Defaults to labeling by MT
description. If a string, then ``mts`` must be a single
integer. If a list of strings, each label will be applied
to each entry in ``mts``. If a dictionary, keys must be
mts and their labels as values. The number of keys do
not have to align with the number of MTs
{kwargs} :func:`matplotlib.pyplot.plot`
Returns
-------
{rax}
Raises
------
TypeError
If MT numbers that don't make sense come up
"""
mts = self._processPlotMts(mts)
userlabel = kwargs.pop("label", None)
if userlabel is not None:
# Allow label to be passed for single MT plots
# Little easier to remember and it makes more sense.
# Don't allow mixed label / labels arguments
if labels is not None:
raise ValueError(
"Passing label and labels is not allowed. Prefer labels")
if len(mts) == 1:
labels = [userlabel]
else:
raise ValueError("Use labels when plotting multiple MTs")
else:
labels = self._processPlotLabels(mts, labels)
ax = ax or pyplot.gca()
kwargs.setdefault("drawstyle", "steps")
for mt, label in zip(mts, labels):
y = self[mt]
ax.plot(self.energies, y, label=label, **kwargs)
title = title or '{} cross section{}'.format(
self.name, 's' if len(mts) > 1 else '')
xlabel = xlabel or "Energy [MeV]"
ylabel = ylabel or (
'Cross Section ({})'.format('b' if self.isIso else 'cm$^{-1}$'))
ax = formatPlot(ax,
loglog=loglog,
logx=logx,
logy=logy,
legendcols=ncol,
legend=legend,
title=title,
xlabel=xlabel,
ylabel=ylabel)
return ax
