plt.subplots.set_xticks

`plt.subplots.set_xticks()` is a method in the `matplotlib` library that is used to set the x-axis tick locations on a plot created using `subplots()`. This method takes in a list or an array of values as an argument, which represent the locations at which the ticks should be placed on the x-axis.

For example, if you have a plot created using `subplots()` and you want to set the x-axis tick locations to be at 0, 2, 4, and 6, you can use the following code:

fig, ax = plt.subplots()
ax.set_xticks([0, 2, 4, 6])

This will set the x-axis tick locations on the plot to be at 0, 2, 4, and 6.

相关问题

plt.subplots.set_xticks的全部参数

`plt.subplots()` 函数返回一个元组，其中包含两个对象：一个 `Figure` 对象和一个 `Axes` 对象或者是一个包含多个 `Axes` 对象的数组。因此，`plt.subplots()` 返回的对象是一个 `Figure` 对象和一个或多个 `Axes` 对象，这些对象可以用来创建绘图并在其中添加元素。

`set_xticks()` 是 `Axes` 对象的方法，用于设置 x 轴刻度的位置。它的参数包括：

- `ticks`：要设置的刻度位置的列表。
- `minor`：如果为 True，则设置次要刻度线；否则为主要刻度线。
- `minor_locator`：用于设置次要刻度线位置的 `Locator` 对象。
- `major_formatter`：用于设置主要刻度线标签格式的 `Formatter` 对象。
- `minor_formatter`：用于设置次要刻度线标签格式的 `Formatter` 对象。

其中，`ticks` 参数是必需的，其他参数是可选的。

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：

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。