本文整理汇总了Python中matplotlib.backends.backend_pdf.PdfPages.clsoe方法的典型用法代码示例。如果您正苦于以下问题：Python PdfPages.clsoe方法的具体用法？Python PdfPages.clsoe怎么用？Python PdfPages.clsoe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matplotlib.backends.backend_pdf.PdfPages的用法示例。
在下文中一共展示了PdfPages.clsoe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: make_plot_conditional_nH_T
# 需要导入模块: from matplotlib.backends.backend_pdf import PdfPages [as 别名]
# 或者: from matplotlib.backends.backend_pdf.PdfPages import clsoe [as 别名]
def make_plot_conditional_nH_T(denArr, tempArr, m_GArr, m_JArr, fignamestr, bin_by_mgrp = True, nbins = 10, nptcl_each = 0, propArr=[], ncolor=5):
if fignamestr[0].find("max") != -1:
ylabel = r"$M_J^{max}$"
elif fignamestr[0].find("peak") != -1:
ylabel = r"$M_J^{peak}$"
else:
ylabel = r"$M_J(%s)$" % fignamestr[0][2:]
mrange_x = [0.9*N.min(m_GArr), 1.1*N.max(m_GArr)]
mrange_y = [0.9*N.min(m_JArr), 1.1*N.max(m_JArr)]
ii = N.where(m_yArr < m_xArr)[0]
print ii
## make seperate plot
if len(ii) > 0 and len(propArr) > 0:
## choose the color based on the density
id_clprop, clprop_bins, colorArr = color_by_prop(propArr[ii], ncolor)
fig = plt.figure(2)
figname = "n_H-T_%s_ov%d_vr%d_%sLTmG_eqN%s_%sclr.pdf" % (fignamestr[1], int(simI["over_density"]), simI["virial_radius"], fignamestr[0], int(bin_by_mass))
figpp = PdfPages(figname)
nrow = 2; ncol = 2; nplt = nrow*ncol
pltkwarg = dict(linestyle="--", marker="o", ms=5., mew=0., alpha=0.7, mec="none")
for icl, idx in enumerate(ii):
iplt = icl % nplt
if iplt == 0:
plt.clf()
ax = fig.add_subplot(2, 2, iplt + 1)
pltkwarg["color"] = colorArr[id_clprop[icl]]
ax.plot(xArr[idx, :], yArr[idx, :], **pltkwarg)
ax.plot(xArr[idx, -1], yArr[idx, -1], "k+", ms=6.)
ax.set_xscale("log"); ax.set_yscale("log")
#ax.set_xlim([1.e-5, 1.e-1]); ax.set_ylim([8.e3, 1.2e5])
ax.set_xlim(N.min(xArr[ii, :]), N.max(xArr[ii, :]))
ax.set_ylim(N.min(yArr[ii, :]), N.max(yArr[ii, :]))
ax.set_xlabel(r"$n_H$"); ax.set_ylabel(r"$T$")
if iplt == 3:
figpp.savefig()
figpp.clsoe()
## plot in one panel
elif len(ii) > 0 and len(ii) <= 30:
fig = plt.figure(2)
plt.clf()
ax = fig.add_subplot(111)
colorArr = []
for icl in xrange(len(ii)):
colorArr.append(plt.get_cmap("hsv")(float(icl)/(len(ii))))
pltkwarg = dict(linestyle="--", marker="o", ms=5., mew=0., alpha=0.7, mec="none")
for icl, idx in enumerate(ii):
pltkwarg["color"] = colorArr[icl]
ax.plot(xArr[idx, :], yArr[idx, :], **pltkwarg)
for icl, idx in enumerate(ii):
ax.plot(xArr[idx, -1], yArr[idx, -1], "k+", ms=6.)
ax.set_xscale("log")
ax.set_yscale("log")
#ax.set_xlim([1.e-5, 1.e-1]); ax.set_ylim([8.e3, 1.2e5])
ax.set_xlim(N.min(denArr[ii, :]), N.max(denArr[ii, :]))
ax.set_ylim(N.min(tempArr[ii, :]), N.max(tempArr[ii, :]))
ax.set_xlabel(r"$n_H$"); ax.set_ylabel(r"$T$")
figname = "n_H-T_%s_ov%d_vr%d_%sLTmG_eqN%s.%s" % (fignamestr[1], int(simI["over_density"]), simI["virial_radius"], fignamestr[0], int(bin_by_mass), figext)
plt.savefig(figname)