ax.set_title()的参数有哪些,分别代表什么意思
时间: 2023-04-07 15:00:31 浏览: 81
ax.set_title()的参数包括:
1. label:标题文本内容
2. fontdict:标题字体的字典,包括字体大小、颜色等属性
3. loc:标题的位置,可以是字符串或数字,如'center'、'left'、'right'、0、1、2等
4. pad:标题与图形边缘的距离
5. **kwargs:其他可选参数,如zorder、alpha等。
这些参数分别代表标题的文本内容、字体样式、位置、与图形边缘的距离以及其他可选参数。
相关问题
def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6): self.ax1 = plt.subplot(self.gs[0, 0]) self.ax1.plot(vals) self.ax1.set_xlim(self.xlim) locs = self.ax1.get_xticks() locs[0] = self.xlim[0] locs[-1] = self.xlim[1] self.ax1.set_xticks(locs) self.ax1.use_sticky_edges = False self.ax1.set_title(f'Connected Clients Ratio') self.ax2 = plt.subplot(self.gs[1, 0]) self.ax2.plot(vals1) self.ax2.set_xlim(self.xlim) self.ax2.set_xticks(locs) self.ax2.yaxis.set_major_formatter(FuncFormatter(format_bps)) self.ax2.use_sticky_edges = False self.ax2.set_title('Total Bandwidth Usage') self.ax3 = plt.subplot(self.gs[2, 0]) self.ax3.plot(vals2) self.ax3.set_xlim(self.xlim) self.ax3.set_xticks(locs) self.ax3.use_sticky_edges = False self.ax3.set_title('Bandwidth Usage Ratio in Slices (Averaged)') self.ax4 = plt.subplot(self.gs[3, 0]) self.ax4.plot(vals3) self.ax4.set_xlim(self.xlim) self.ax4.set_xticks(locs) self.ax4.use_sticky_edges = False self.ax4.set_title('Client Count Ratio per Slice') self.ax5 = plt.subplot(self.gs[0, 1]) self.ax5.plot(vals4) self.ax5.set_xlim(self.xlim) self.ax5.set_xticks(locs) self.ax5.use_sticky_edges = False self.ax5.set_title('Coverage Ratio') self.ax6 = plt.subplot(self.gs[1, 1]) self.ax6.plot(vals5) self.ax6.set_xlim(self.xlim) self.ax6.set_xticks(locs) self.ax6.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax6.use_sticky_edges = False self.ax6.set_title('Block ratio') self.ax7 = plt.subplot(self.gs[2, 1]) self.ax7.plot(vals6) self.ax7.set_xlim(self.xlim) self.ax7.set_xticks(locs) self.ax7.yaxis.set_major_formatter(FormatStrFormatter('%.3f')) self.ax7.use_sticky_edges = False self.ax7.set_title('Handover ratio')修改为一张张输出图片
好的,你可以将这段代码修改为:
```python
def draw_stats(self, vals, vals1, vals2, vals3, vals4, vals5, vals6, save_path):
fig, axs = plt.subplots(4, 2, figsize=(16, 16))
axs[0, 0].plot(vals)
axs[0, 0].set_xlim(self.xlim)
locs = axs[0, 0].get_xticks()
locs[0] = self.xlim[0]
locs[-1] = self.xlim[1]
axs[0, 0].set_xticks(locs)
axs[0, 0].use_sticky_edges = False
axs[0, 0].set_title(f'Connected Clients Ratio')
axs[1, 0].plot(vals1)
axs[1, 0].set_xlim(self.xlim)
axs[1, 0].set_xticks(locs)
axs[1, 0].yaxis.set_major_formatter(FuncFormatter(format_bps))
axs[1, 0].use_sticky_edges = False
axs[1, 0].set_title('Total Bandwidth Usage')
axs[2, 0].plot(vals2)
axs[2, 0].set_xlim(self.xlim)
axs[2, 0].set_xticks(locs)
axs[2, 0].use_sticky_edges = False
axs[2, 0].set_title('Bandwidth Usage Ratio in Slices (Averaged)')
axs[3, 0].plot(vals3)
axs[3, 0].set_xlim(self.xlim)
axs[3, 0].set_xticks(locs)
axs[3, 0].use_sticky_edges = False
axs[3, 0].set_title('Client Count Ratio per Slice')
axs[0, 1].plot(vals4)
axs[0, 1].set_xlim(self.xlim)
axs[0, 1].set_xticks(locs)
axs[0, 1].use_sticky_edges = False
axs[0, 1].set_title('Coverage Ratio')
axs[1, 1].plot(vals5)
axs[1, 1].set_xlim(self.xlim)
axs[1, 1].set_xticks(locs)
axs[1, 1].yaxis.set_major_formatter(FormatStrFormatter('%.3f'))
axs[1, 1].use_sticky_edges = False
axs[1, 1].set_title('Block ratio')
axs[2, 1].plot(vals6)
axs[2, 1].set_xlim(self.xlim)
axs[2, 1].set_xticks(locs)
axs[2, 1].yaxis.set_major_formatter(FormatStrFormatter('%.3f'))
axs[2, 1].use_sticky_edges = False
axs[2, 1].set_title('Handover ratio')
plt.tight_layout()
plt.savefig(save_path)
plt.show()
```
这样就可以一张张输出图片了,你只需要传入一个保存路径参数 `save_path` 即可。
y.plot(ax=ts_ax) ts_ax.set_title(title) y.plot(ax=hist_ax, kind='hist', bins=25) hist_ax.set_title('Histogram') smt.graphics.plot_acf(y, lags=lags, ax=acf_ax) smt.graphics.plot_pacf(y, lags=lags, ax=pacf_ax) [ax.set_xlim(0) for ax in [acf_ax, pacf_ax]] sns.despine() plt.tight_layout() return ts_ax, acf_ax, pacf_ax
这段代码是用于时间序列分析的,它会生成一个时间序列的图表,包括原始数据的折线图、直方图、自相关图和偏自相关图。其中,y.plot(ax=ts_ax)是用于绘制原始数据的折线图,ts_ax.set_title(title)是设置折线图的标题,y.plot(ax=hist_ax, kind='hist', bins=25)是用于绘制直方图,hist_ax.set_title('Histogram')是设置直方图的标题,smt.graphics.plot_acf(y, lags=lags, ax=acf_ax)和smt.graphics.plot_pacf(y, lags=lags, ax=pacf_ax)分别是用于绘制自相关图和偏自相关图,[ax.set_xlim(0) for ax in [acf_ax, pacf_ax]]是设置自相关图和偏自相关图的x轴范围,sns.despine()是用于去除图表的边框,plt.tight_layout()是用于调整图表的布局。最后,函数会返回折线图、自相关图和偏自相关图的轴对象。