在matplotlib轴上设置科学限制后，调整指数文本 [英] Adjust exponent text after setting scientific limits on matplotlib axis

问题描述

目前，如果我将matplotlib的y轴ticklabel设置为科学模式，它会以1e-5

At the moment if I set matplotlib y axis ticklabels to scientific mode it gives me an exponent at the top of the y axis of the form 1e-5

我想将其调整为读取r'$\mathregular{10^{-5}}$'，以便打印出精美的文字.

I'd like to adjust this to read r'$\mathregular{10^{-5}}$' so that it prints out nicely.

这是我的示例代码:

# Create a figure and axis
fig, ax = plt.subplots()

# Plot 100 random points 
# the y values of which are very small
ax.scatter(np.random.rand(100), np.random.rand(100)/100000.0)

# Set the y limits appropriately
ax.set_ylim(0, 1/100000.0)

# Change the y ticklabel format to scientific format
ax.ticklabel_format(axis='y', style='sci', scilimits=(-2, 2))

# Get the offset value
offset = ax.yaxis.get_offset_text()

# Print it out
print '1st offset printout: {}'.format(offset)

# Run plt.tight_layout()
plt.tight_layout()

# Print out offset again - you can see the value now!
print '2nd offset printout: {}'.format(offset)

# Change it to latex format
offset.set_text(r'$\mathregular{10^{-5}}$')

# Print it out
print '3rd offset printout: {}'.format(offset)

# Add some text to the middle of the figure just to 
# check that it isn't the latex format that's the problem
ax.text(0.5, 0.5/100000.0, r'$\mathregular{10^{-2}}$')

# And show the figure
plt.show()

我的输出如下:

1st offset printout: Text(0,0.5,u'')
2nd offset printout: Text(0,636.933,u'1e\u22125')
3rd offset printout: Text(0,636.933,u'$\\mathregular{10^{-5}}$')

您可以在此处找到代码和输出图.

You can find the code and output figure here.

有两个奇怪的地方:一个是我无法覆盖y轴顶部的1e-5(这是目标)，另一个是我必须运行plt.tight_layout()才能使看到该unicode值作为偏移量.

There are two oddities: One is that I can't overwrite the 1e-5 at the top of the y axis (which is the goal), and the other is that I have to run plt.tight_layout() in order to even see that unicode value as the offset.

谁能告诉我我要去哪里错了?

Can anyone tell me where I'm going wrong?

谢谢

原始问题并未明确说明我想自动检测ticklabel_format当前计算的指数.因此，与其将设置的字符串传递给偏移文本，不如将其自动检测到该值并相应地调整乳胶字符串.

The original question didn't make clear that I'd like to automatically detect the exponent as is currently calculated by ticklabel_format. So instead of passing a set string to the offset text it should automatically detect that value and adjust the latex string accordingly.

推荐答案

以@edsmith的答案为基础，一种可能的解决方法是我要获取偏移文本，将其转换为乳胶字符串，然后关闭偏移并在轴的顶部添加该字符串.

Building on @edsmith's answer one possible work around which does what I'd like is to get the offset text, convert it to a latex string, turn off the offset and add in that string at the top of the axis.

def format_exponent(ax, axis='y'):

    # Change the ticklabel format to scientific format
    ax.ticklabel_format(axis=axis, style='sci', scilimits=(-2, 2))

    # Get the appropriate axis
    if axis == 'y':
        ax_axis = ax.yaxis
        x_pos = 0.0
        y_pos = 1.0
        horizontalalignment='left'
        verticalalignment='bottom'
    else:
        ax_axis = ax.xaxis
        x_pos = 1.0
        y_pos = -0.05
        horizontalalignment='right'
        verticalalignment='top'

    # Run plt.tight_layout() because otherwise the offset text doesn't update
    plt.tight_layout()
    ##### THIS IS A BUG 
    ##### Well, at least it's sub-optimal because you might not
    ##### want to use tight_layout(). If anyone has a better way of 
    ##### ensuring the offset text is updated appropriately
    ##### please comment!

    # Get the offset value
    offset = ax_axis.get_offset_text().get_text()

    if len(offset) > 0:
        # Get that exponent value and change it into latex format
        minus_sign = u'\u2212'
        expo = np.float(offset.replace(minus_sign, '-').split('e')[-1])
        offset_text = r'x$\mathregular{10^{%d}}$' %expo

        # Turn off the offset text that's calculated automatically
        ax_axis.offsetText.set_visible(False)

        # Add in a text box at the top of the y axis
        ax.text(x_pos, y_pos, offset_text, transform=ax.transAxes,
               horizontalalignment=horizontalalignment,
               verticalalignment=verticalalignment)
    return ax

请注意，您应该能够通过调用pos = ax_axis.get_offset_text().get_position()使用偏移文本的位置，但是这些值不是以轴为单位的(它们很可能是像素单位-感谢@EdSmith-因此不是很有用).因此，我只是根据要查看的轴设置了x_pos和y_pos值.

Note that you should be able to use the position of the offset text by calling pos = ax_axis.get_offset_text().get_position() but these values are not in axis units (they're likely pixel units - thanks @EdSmith - and thus not very helpful). Therefore I've just set the x_pos and y_pos values according to whichever axis we're looking at.

我还编写了一个小函数来自动检测适当的x和y限制(即使我知道matplotlib有很多不错的方法可以做到这一点).

I also wrote a little function to automatically detect appropriate x and y limits (even though I know that matplotlib has lots of fancy ways of doing this).

def get_min_max(x, pad=0.05):
    '''
    Find min and max values such that
    all the data lies within 90% of
    of the axis range
    '''
    r = np.max(x) - np.min(x)
    x_min = np.min(x) - pad * r
    x_max = np.max(x) + pad * r
    return x_min, x_max

因此，要从问题中更新我的示例(稍作更改以使两个轴都需要指数):

So, to update my example from the question (with a slight change to make both axes need the exponent):

import matplotlib.pylab as plt
import numpy as np

# Create a figure and axis
fig, ax = plt.subplots()

# Plot 100 random points that are very small
x = np.random.rand(100)/100000.0
y = np.random.rand(100)/100000.0
ax.scatter(x, y)

# Set the x and y limits
x_min, x_max = get_min_max(x)
ax.set_xlim(x_min, x_max)
y_min, y_max = get_min_max(y)    
ax.set_ylim(y_min, y_max)

# Format the exponents nicely
ax = format_exponent(ax, axis='x')
ax = format_exponent(ax, axis='y')

# And show the figure
plt.show()

可以使用此处

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