本文整理汇总了Python中torch.set_font_sizes函数的典型用法代码示例。如果您正苦于以下问题：Python set_font_sizes函数的具体用法？Python set_font_sizes怎么用？Python set_font_sizes使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了set_font_sizes函数的3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: load_src
def load_src(name, fpath):
import os, imp
return imp.load_source(name, os.path.join(os.path.dirname(__file__), fpath))
load_src("torch", "../torchpack/torch.py")
load_src("hgspy", "../torchpack/hgspy.py")
import torch
import hgspy
DPI = 300
figformat = 'png'
plot_size = 5
fontsize = 16
torch.set_font_sizes(fontsize=16)
inputfile1 = "data/galsim/starpop-hm-a.txt"
data1 = np.genfromtxt(inputfile1, skip_header=1)
def plot_scatter(ax, dat, colormap):
x = dat[:,12]
y = dat[:,13]
xy = np.vstack([x,y])
z = scipy.stats.gaussian_kde(xy)(xy)
idx = z.argsort()
x, y, z = x[idx], y[idx], z[idx]
示例2: load_src
def load_src(name, fpath):
import os, imp
return imp.load_source(name, os.path.join(os.path.dirname(__file__), fpath))
load_src("torch", "../torchpack/torch.py")
load_src("hgspy", "../torchpack/hgspy.py")
import torch
import hgspy
DPI = 300
figformat = 'png'
plot_size = 5
fontsize = 16
outputfile_qlyc = "mass-vs-qlyc.png"
torch.set_font_sizes(fontsize)
data = np.genfromtxt("refdata/zams.txt", skip_header=1)
### Data set up.
mass = data[:,0]
qlyc = data[:,6]
### Plotting.
plotter = torch.Plotter(1, 1, plot_size, figformat, DPI)
### Axes.
grid = plotter.axes1D((1,1), aspect_ratio=0.75)
grid[0].set_xlabel(plotter.format_label(torch.VarType('M_\star', units='M_{\odot}')))
grid[0].set_ylabel(plotter.format_label(torch.VarType('Q_\\mathrm{Lyc}', units='s^{-1}', isLog10=True)))示例3: plot
def plot():
import warnings
import sys
def load_src(name, fpath):
import os, imp
return imp.load_source(name, os.path.join(os.path.dirname(__file__), fpath))
load_src("torch", "../torchpack/torch.py")
load_src("hgspy", "../torchpack/hgspy.py")
import torch
import hgspy
DPI = 300
figformat = 'png'
plot_size = 5
fontsize = 16
plot_type = "ssw" # ["if", "hii", "ssw"]
outputfile_qlyc = "henney-" + plot_type + ".png"
torch.set_font_sizes(fontsize)
### Data
lmp = []
lmn = []
lhp = []
lhn = []
lcie = []
lpdr = []
ltot = []
if plot_type == "ssw":
nh = 1
elif plot_type == "hii":
nh = 1000
else:
nh = 10000
hii = 1.0
if plot_type == "if":
hii = 0.5
N = 1001
minlogT = 4.0
maxlogT = 8.0
if plot_type == "if" or plot_type == "hii":
minlogT = 3.8
maxlogT = 4.0
isLog = True
nhii = hii * nh
nhi = (1.0 - hii) * nh
if not isLog:
tem = np.linspace(10.0**minlogT, 10.0**maxlogT, N, endpoint=True)
else:
tem = np.linspace(minlogT, maxlogT, N, endpoint=True)
for i in range(len(tem)):
itemp = tem[i]
if isLog:
itemp = math.pow(10.0, itemp)
lmp.append(coolCollExcIonMetals(nhii, itemp))
lmn.append(coolCollExcNeuMetals(nhii, nhi, itemp))
lhp.append(coolFreeFree(nhii, itemp))
lhn.append(coolCollExcNeuHydrogen(nhii, nhi, itemp))
lcie.append(coolCIE(nhii, itemp))
lpdr.append(coolPDR(nhi, itemp))
ltot.append(lmp[i] + lmn[i] + lhp[i] + lhn[i] + lcie[i] + lpdr[i])
### Plotting.
plotter = torch.Plotter(1, 1, plot_size, figformat, DPI)
### Axes.
grid = plotter.axes1D((1,1), aspect_ratio=0.75)
grid[0].set_xlabel(plotter.format_label(torch.VarType('T', units='K', isLog10=True)))
grid[0].set_ylabel(plotter.format_label(torch.VarType('C', units='erg\\:s^{-1}\\:cm^{-3}', isLog10=False)))
### Plot.
if plot_type == "if":
grid[0].plot(tem, lmn, label=r"$C_\mathrm{M^0}$", color='m')
grid[0].plot(tem, lhn, label=r"$C_\mathrm{H^0}$", color='y')
grid[0].plot(tem, lmp, label=r"$C_\mathrm{M^+}$", color='g')
grid[0].plot(tem, lhp, label=r"$C_\mathrm{H^+}$", color='r')
grid[0].plot(tem, ltot, label=r"$C_\mathrm{tot}$", color='k')
elif plot_type == "hii":
grid[0].plot(tem, lmp, label=r"$C_\mathrm{M^+}$", color='g')
grid[0].plot(tem, lhp, label=r"$C_\mathrm{H^+}$", color='r')
grid[0].plot(tem, ltot, label=r"$C_\mathrm{tot}$", color='k')
elif plot_type == "ssw":
grid[0].plot(tem, lmp, label=r"$C_\mathrm{M^+}$", color='g')
grid[0].plot(tem, lhp, label=r"$C_\mathrm{H^+}$", color='r')
grid[0].plot(tem, lcie, label=r"$C_\mathrm{CIE}$", color='b')
grid[0].plot(tem, ltot, label=r"$C_\mathrm{tot}$", color='k')
grid[0].set_xlim([minlogT, maxlogT])
if plot_type == "ssw":
grid[0].legend(loc='upper right')
else:
grid[0].legend(loc='upper left')
#.........这里部分代码省略.........