如何使用新的mplfinance软件包编辑无花果? [英] How to edit the fig with the new mplfinance package?

问题描述

使用新的mplfinance，我似乎无法添加任何文本，旋转轴，更改背景颜色等.

I can't seem to add any text, rotate axis, change the background color, etc with the new mplfinance.

使用旧的 mpl-finance，我只做 fig, ax = plt.subplots() 并编辑 fig 和 ax 但是我想要:fig.text(0.96,1，某些文本"，size = 9，fontweight ='bold'，color ='black'，ha ="right")或 plt.legend(loc ='upper left')

With the old mpl-finance, I just do fig, ax = plt.subplots() and edit the fig and ax however I want to like: fig.text(0.96, 1, 'some text', size=9, fontweight='bold',color='black', ha="right") or plt.legend( loc='upper left')

有谁知道如何使用新软件包来做到这一点?

Does anyone know how to do that with the new package?

推荐答案

要访问mplfinance的Figure和Axes对象，有两种方法:

方法一.调用plot时设置returnfig=True:

fig, axlist = mpf.plot(data,...,returnfig=True,...)

axlist 将是与面板从上到下，每个面板有两个轴，其中第一个是主要em> 轴，下一个是 _secondary 轴.例如，如果您有3个面板，则 returnfig = True 将返回6个轴对象. axlist [0] 和 axlist [1] 将分别是面板 0 的主轴和辅助轴.axlist[2] 和 axlist[3] 将分别是面板 1 等的主轴和副轴.

axlist will be a list of axes corresponding to the panels from top to bottom, two axes per panel where the first is the primary axes and the next is the _secondary axes. For example, if you have 3 panels then returnfig=True will return 6 Axes objects. axlist[0] and axlist[1] will be the primary and secondary axes, respectively, for panel 0. axlist[2] and axlist[3] will be the primary and secondary axes, respectively, for panel 1, etc.

方法2.创建自己的Figure和Axes对象，并将它们传递给mplfinance.> 您可以在此处查看如何执行此操作的示例.

Method 2. Create your own Figure and Axes objects and pass these into mplfinance. You can see examples of how to do this here.

还请注意，当指定 x,y 坐标以定位文本、图例等时:

Please note also that, when specifying x,y coordinates for positioning of text, legends, etc. then:

如果 show_nontrading kwarg 是 False(即默认值，如果未指定)那么 x 轴值实际上不是日期，因为它们出现, 但是是数据框中从零到行数的整数值.

if show_nontrading kwarg is False (i.e. the default value if unspecified) then the x-axis values are not actually dates as they appear, but are integer values from zero up to the number of rows in your dataframe.

HTH

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