为什么此代码中需要numpy.ravel()才能产生较小的倍数? [英] Why is numpy.ravel() required in this code that produces small multiples?

问题描述

我找到了一些代码来生成一组小倍数，并且运行良好.

  fig，axes = plt.subplots(6,3，figsize =(21,21))fig.subplots_adjust(hspace=.3, wspace=.175)对于 ax，zip 中的数据(axes.ravel(), clean_sets):ax.plot(data.ETo，o")

行 for ax, data in zip(axes.ravel(), clean_sets): contians .ravel() 但我不明白这实际上在做什么或为什么有必要.

如果我看看 解决方案

您的猜测是正确的. plt.subplots()返回一个由多个轴组成的 Axes 或 numpy 数组，具体取决于输入.如果用参数 nrows 和 ncols 定义2D网格，则返回的 numpy 数组也将是2D数组.

此行为在 pyplot.subplots squeeze 参数中的文档，

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squeeze :布尔，可选，默认值:True
如果为True，则从返回的Axes对象中挤出额外的尺寸:

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• 如果仅构造了一个子图(nrows = ncols = 1)，则返回的单个Axes对象将作为标量返回.

• 对于 Nx1 或 1xN 子图，返回的对象是一个 1D numpy 对象数组，Axes 对象作为 numpy 1D 数组返回.
• 对于 NxM，N>1 和 M>1 的子图作为二维数组返回.

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如果为 False，则根本不进行压缩:返回的 Axes 对象始终是包含 Axes 实例的二维数组，即使它最终是 1x1.

因为这里有 plt.subplots(6,3)，因此 N>1, M>1，结果对象必然是一个 2D 数组，独立于 squeeze 设置为什么.

这使得有必要展平此数组，以便能够对其进行 zip 压缩.选项是

• zip(axes.ravel())
• zip(axes.flatten())
• zip(axes.flat)

I found some code to generate a set of small multiples and it is working perfectly.

fig, axes = plt.subplots(6,3, figsize=(21,21))
fig.subplots_adjust(hspace=.3, wspace=.175)
for ax, data in zip(axes.ravel(), clean_sets):
    ax.plot(data.ETo, "o")

The line for ax, data in zip(axes.ravel(), clean_sets): contians .ravel() but I do not understand what this is actually doing or why it is necessary.

If I take a look at the docs I find the following:

Return a contiguous flattened array.

A 1-D array, containing the elements of the input, is returned. A copy is made only if needed.

I guess the return that corresponds to axes from plt.subplot() is a multidimensional array that can't be iterated over, but really I'm not sure. A simple explanation would be greatly appreciated.

What is the purpose of using .ravel() in this case?

解决方案

Your guess is correct. plt.subplots() returns either an Axes or a numpy array of several axes, depending on the input. In case a 2D grid is defined by the arguments nrows and ncols, the returned numpy array will be a 2D array as well.

This behaviour is explained in the pyplot.subplots documentation inside the squeeze argument,

squeeze : bool, optional, default: True
If True, extra dimensions are squeezed out from the returned Axes object:

• if only one subplot is constructed (nrows=ncols=1), the resulting single Axes object is returned as a scalar.

• for Nx1 or 1xN subplots, the returned object is a 1D numpy object array of Axes objects are returned as numpy 1D arrays.
• for NxM, subplots with N>1 and M>1 are returned as a 2D arrays.

If False, no squeezing at all is done: the returned Axes object is always a 2D array containing Axes instances, even if it ends up being 1x1.

Since here you have plt.subplots(6,3) and hence N>1, M>1, the resulting object is necessarily a 2D array, independent of what squeeze is set to.

This makes it necessary to flatten this array in order to be able to zip it. Options are

• zip(axes.ravel())
• zip(axes.flatten())
• zip(axes.flat)

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