現在最簡單的方法是使用AxesGrid,如in this yt cookbook example以及this one。
下面是一個使用yt 3.2.1繪製時間序列中氣體密度兩次的示例。我正在使用的示例數據可以從http://yt-project.org/data下載。
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')
你可以做到這一點(使用fig.add_subplots
而不是AxesGrid
)的方式,但你需要手動將軸定位,也調整身材。
最後,如果您希望圖形更小,則可以通過在通過plt.figure()
創建圖形時傳遞以英寸爲單位的圖形大小來控制圖形的大小。如果你這樣做,你也可以通過調用ProjectionPlot
上的p.set_font_size()
來調整字體大小。
感謝您使用yt!如果遇到更多問題,如果您向我們的郵件列表發送消息,您將獲得更多的開發者關注。也就是說,我一定會在StackOverflow上關注未來的問題。 – ngoldbaum