现在最简单的方法是使用AxesGrid,如in this yt cookbook example以及this one。
下面是一个使用yt 3.2.1绘制时间序列中气体密度两次的示例。我正在使用的示例数据可以从http://yt-project.org/data下载。
import yt
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
fns = ['enzo_tiny_cosmology/DD0005/DD0005', 'enzo_tiny_cosmology/DD0040/DD0040']
fig = plt.figure()
# See http://matplotlib.org/mpl_toolkits/axes_grid/api/axes_grid_api.html
# These choices of keyword arguments produce a four panel plot with a single
# shared narrow colorbar on the right hand side of the multipanel plot. Axes
# labels are drawn for all plots since we're slicing along different directions
# for each plot.
grid = AxesGrid(fig, (0.075,0.075,0.85,0.85),
nrows_ncols = (2, 1),
axes_pad = 0.05,
label_mode = "L",
share_all = True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad="0%")
for i, fn in enumerate(fns):
# Load the data and create a single plot
ds = yt.load(fn) # load data
# Make a ProjectionPlot with a width of 34 comoving megaparsecs
p = yt.ProjectionPlot(ds, 'z', 'density', width=(34, 'Mpccm'))
# Ensure the colorbar limits match for all plots
p.set_zlim('density', 1e-4, 1e-2)
# This forces the ProjectionPlot to redraw itself on the AxesGrid axes.
plot = p.plots['density']
plot.figure = fig
plot.axes = grid[i].axes
plot.cax = grid.cbar_axes[i]
# Finally, this actually redraws the plot.
p._setup_plots()
plt.savefig('multiplot_1x2_time_series.png', bbox_inches='tight')
你可以做到这一点(使用fig.add_subplots
而不是AxesGrid
)的方式,但你需要手动将轴定位,也调整身材。
最后,如果您希望图形更小,则可以通过在通过plt.figure()
创建图形时传递以英寸为单位的图形大小来控制图形的大小。如果你这样做,你也可以通过调用ProjectionPlot
上的p.set_font_size()
来调整字体大小。
感谢您使用yt!如果遇到更多问题,如果您向我们的邮件列表发送消息,您将获得更多的开发者关注。也就是说,我一定会在StackOverflow上关注未来的问题。 – ngoldbaum