本文整理汇总了Python中Analysis.normalization方法的典型用法代码示例。如果您正苦于以下问题：Python Analysis.normalization方法的具体用法？Python Analysis.normalization怎么用？Python Analysis.normalization使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Analysis的用法示例。
在下文中一共展示了Analysis.normalization方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _line_spectrum
# 需要导入模块: import Analysis [as 别名]
# 或者: from Analysis import normalization [as 别名]
def _line_spectrum(data, min, line, dE, width, width_error):
# Draw histogram
n, bins = Analysis.histogram(data, binsize=binsize)
if method in ("cs"):
gn, gbins = Analysis.group_bin(n, bins, min=min)
else:
# No grouping in mle and ls
gn, gbins = n, bins
ngn = gn/(np.diff(gbins))
ngn_sigma = np.sqrt(gn)/(np.diff(gbins))
cbins = (gbins[1:]+gbins[:-1])/2
if plotting:
figure()
if width_error is not None:
label = 'FWHM$=%.2f\pm %.2f$ eV' % (width, width_error)
else:
label = 'FWHM$=%.2f$ eV (Fixed)' % width
if method == "cs":
errorbar(cbins, ngn, yerr=ngn_sigma, xerr=np.diff(gbins)/2, capsize=0, ecolor='k', fmt=None, label=label)
else:
hist(data, bins=gbins, weights=np.ones(len(data))/binsize, histtype='step', ec='k', label=label)
E = np.linspace(bins.min(), bins.max(), 1000)
model = Analysis.normalization(ngn, gbins, dE, width, line=line, shift=shift) \
* Analysis.line_model(E, dE, width, line=line, shift=shift, full=True)
# Plot theoretical model
plot(E, model[0], 'r-')
# Plot fine structures
for m in model[1:]:
plot(E, m, 'b--')
xlabel('Energy$\quad$(eV)')
ylabel('Normalized Count$\quad$(count/eV)')
legend(frameon=False)
ymin, ymax = ylim()
ylim(ymin, ymax*1.1)
tight_layout()
savefig("%s-%s.pdf" % (session, line))
if savedat:
np.savetxt('%s-%s.dat' % (session, line), np.vstack((cbins, gn)).T,
header='Energy (keV), Count', delimiter='\t')