使matplotlib图默认情况下看起来像R? [英] making matplotlib graphs look like R by default?

问题描述

在绘制默认值方面，是否有办法使matplotlib的行为与R相同，或几乎与R相似?例如，R将其轴与matplotlib完全不同.以下直方图

Is there a way to make matplotlib behave identically to R, or almost like R, in terms of plotting defaults? For example R treats its axes pretty differently from matplotlib. The following histogram

具有带有向外刻度的浮动轴"，这样就没有内部刻度(与matplotlib不同)，并且这些轴不会越过原点近".而且，直方图可以溢出"到未用刻度标记的值，例如x轴以3结束，但直方图略微超出它.对于matplotlib中的所有直方图如何自动实现?

has "floating axes" with outward ticks, such that there are no inner ticks (unlike matplotlib) and the axes do not cross "near" the origin. Also, the histogram can "spillover" to values that are not marked by the tick - e.g. the x-axis ends at 3 but the histograms extends slightly beyond it. How can this be achieved automatically for all histograms in matplotlib?

相关问题:散点图和折线图在R中具有不同的默认轴设置，例如:

Related question: scatter plots and line plots have different default axes settings in R, for example:

没有内部刻度线，并且刻度线朝外.同样，刻度线在原点之后稍稍开始(y和x轴在轴的左下角交叉)，刻度线在轴终点之前稍稍结束.这样，最低的x轴刻度线和最低的y轴刻度线的标签就无法真正交叉，因为它们之间有一定的空间，这使绘图具有非常优雅的整洁外观.请注意，轴刻度标签和刻度本身之间也有相当大的空间.

There no inner ticks again and the ticks face outward. Also, the ticks start slightly after the origin point (where the y and x axes cross at the bottom left of the axes) and the ticks end slightly before the axes end. This way the labels of the lowest x-axis tick and lowest y-axis tick can't really cross, because there's a space between them and this gives the plots a very elegant clean look. Note that there's also considerably more space between the axes ticklabels and the ticks themselves.

此外，默认情况下，未标记的x或y轴上没有刻度线，这意味着左侧的y轴与右侧的标记的y轴平行没有刻度线，并且x相同轴，再次消除了图中的混乱情况.

Also, by default there are no ticks on the non-labeled x or y axes, meaning the y-axis on the left that is parallel to the labeled y-axis on the right has no ticks, and same for the x-axis, again removing clutter from the plots.

有没有办法使matplotlib看起来像这样?通常情况下，默认情况下看起来与默认R图一样多吗?我非常喜欢matplotlib，但是我认为R默认值/开箱即用的绘图行为确实可以解决问题，并且其默认设置很少会导致刻度标签重叠，数据混乱或混乱，因此我希望使用默认值尽可能地像这样.

Is there a way to make matplotlib look like this? And in general to look by default as much as default R plots? I like matplotlib a lot but I think the R defaults / out-of-the-box plotting behavior really have gotten things right and its default settings rarely lead to overlapping tick labels, clutter or squished data, so I would like the defaults to be as much like that as possible.

推荐答案

一年后

使用seaborn，下面的示例变为:

Edit 1 year later:

With seaborn, the example below becomes:

import numpy as np
import matplotlib.pyplot as plt
import seaborn
seaborn.set(style='ticks')
# Data to be represented
X = np.random.randn(256)

# Actual plotting
fig = plt.figure(figsize=(8,6), dpi=72, facecolor="white")
axes = plt.subplot(111)
heights, positions, patches = axes.hist(X, color='white')
seaborn.despine(ax=axes, offset=10, trim=True)
fig.tight_layout()
plt.show()

当当很简单.

这篇博客文章是迄今为止我所见过的最好的文章. http://messymind.net/making-matplotlib-look-like-ggplot/

This blog post is the best I've seen so far. http://messymind.net/making-matplotlib-look-like-ggplot/

它不像您在大多数入门"类型示例中看到的那样专注于您的标准R图.相反，它尝试模仿ggplot2的样式，该样式似乎被普遍认为是时尚且设计精美的.

It doesn't focus on your standard R plots like you see in most of the "getting started"-type examples. Instead it tries to emulate the style of ggplot2, which seems to be nearly universally heralded as stylish and well-designed.

要像看到条形图中那样获得轴刺，请尝试遵循此处的前几个示例之一: http://www.loria.fr/~rougier/coding/gallery/

To get the axis spines like you see the in bar plot, try to follow one of the first few examples here: http://www.loria.fr/~rougier/coding/gallery/

最后，要使轴刻度线朝外指向，您可以编辑matplotlibrc文件以说出xtick.direction : out和ytick.direction : out.

Lastly, to get the axis tick marks pointing outward, you can edit your matplotlibrc files to say xtick.direction : out and ytick.direction : out.

将这些概念结合在一起，我们得到的东西是这样的:

Combining these concepts together we get something like this:

import numpy as np
import matplotlib
import matplotlib.pyplot as plt
# Data to be represented
X = np.random.randn(256)

# Actual plotting
fig = plt.figure(figsize=(8,6), dpi=72, facecolor="white")
axes = plt.subplot(111)
heights, positions, patches = axes.hist(X, color='white')

axes.spines['right'].set_color('none')
axes.spines['top'].set_color('none')
axes.xaxis.set_ticks_position('bottom')

# was: axes.spines['bottom'].set_position(('data',1.1*X.min()))
axes.spines['bottom'].set_position(('axes', -0.05))
axes.yaxis.set_ticks_position('left')
axes.spines['left'].set_position(('axes', -0.05))

axes.set_xlim([np.floor(positions.min()), np.ceil(positions.max())])
axes.set_ylim([0,70])
axes.xaxis.grid(False)
axes.yaxis.grid(False)
fig.tight_layout()
plt.show()

可以用多种方法指定棘突的位置.如果您在IPython中运行以上代码，则可以执行axes.spines['bottom'].set_position?来查看所有选项.

The position of the spines can be specified a number of ways. If you run the code above in IPython, you can then do axes.spines['bottom'].set_position? to see all of your options.

是的.这并不简单，但是您可以接近.

So yeah. It's not exactly trivial, but you can get close.

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