Proposal for Broken Axes

It's my understanding that there is no built-in method for generating a
"broken axis" (where you skip over some range of values, indicating this
with some graphical mark). I wanted to do this, so I've put together a
function which seems to be fairly robust, and I thought I might propose it
as a starting point if there's interest in having a built-in facility for
broken axes.

Please let me know if this is not the appropriate place to be submitting
this suggestion.

The basic idea of the below function is that you feed is an axes object
along with an iterable giving the bounds of each section of the y-axis. It
then returns new upper and lower axes objects, after masking spines,
calculating distances, etc. The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven't
figured out how to push out the y-axis label of the main axes object so it
doesn't overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

http://old.nabble.com/file/p27909750/broken.png

···

----------
from matplotlib import pyplot as plt

def axes_broken_y(axes, upper_frac=0.5, break_frac=0.02, ybounds=None,
                  xlabel=None, ylabel=None):
    """
    Replace the current axes with a set of upper and lower axes.

    The new axes will be transparent, with a breakmark drawn between them.
They
    share the x-axis. Returns (upper_axes, lower_axes).

    If ybounds=[ymin_lower, ymax_lower, ymin_upper, ymax_upper] is defined,
    upper_frac will be ignored, and the y-axis bounds will be fixed with the
    specified values.
    """
    def breakmarks(axes, y_min, y_max, xwidth=0.008):
        x1, y1, x2, y2 = axes.get_position().get_points().flatten().tolist()
        segment_height = (y_max - y_min) / 3.
        xoffsets = [0, +xwidth, -xwidth, 0]
        yvalues = [y_min + (i * segment_height) for i in range(4)]
        # Get color of y-axis
        for loc, spine in axes.spines.iteritems():
            if loc == 'left':
                color = spine.get_edgecolor()
        for x_position in [x1, x2]:
            line = matplotlib.lines.Line2D(
                [x_position + offset for offset in xoffsets], yvalues,
                transform=plt.gcf().transFigure, clip_on=False,
                color=color)
            axes.add_line(line)
    # Readjust upper_frac if ybounds are defined
    if ybounds:
        if len(ybounds) != 4:
            print "len(ybounds) != 4; aborting..."
            return
        ymin1, ymax1, ymin2, ymax2 = [float(value) for value in ybounds]
        data_height1, data_height2 = (ymax1 - ymin1), (ymax2 - ymin2)
        upper_frac = data_height2 / (data_height1 + data_height2)
    x1, y1, x2, y2 = axes.get_position().get_points().flatten().tolist()
    width = x2 - x1
    lower_height = (y2 - y1) * ((1 - upper_frac) - 0.5 * break_frac)
    upper_height = (y2 - y1) * (upper_frac - 0.5 * break_frac)
    upper_bottom = (y2 - y1) - upper_height + y1
    lower_axes = plt.axes([x1, y1, width, lower_height], axisbg='None')
    upper_axes = plt.axes([x1, upper_bottom, width, upper_height],
                          axisbg='None', sharex=lower_axes)
    # Erase the edges between the axes
    for loc, spine in upper_axes.spines.iteritems():
        if loc == 'bottom':
            spine.set_color('none')
    for loc, spine in lower_axes.spines.iteritems():
        if loc == 'top':
            spine.set_color('none')
    upper_axes.get_xaxis().set_ticks_position('top')
    lower_axes.get_xaxis().set_ticks_position('bottom')
    plt.setp(upper_axes.get_xticklabels(), visible=False)
    breakmarks(upper_axes, y1 + lower_height, upper_bottom)
    # Set ylims if ybounds are defined
    if ybounds:
        lower_axes.set_ylim(ymin1, ymax1)
        upper_axes.set_ylim(ymin2, ymax2)
        lower_axes.set_autoscaley_on(False)
        upper_axes.set_autoscaley_on(False)
        upper_axes.yaxis.get_label().set_position((0, 1 - (0.5 /
(upper_frac/(1+break_frac)))))
        lower_axes.yaxis.get_label().set_position((0, 0.5 / ((1 -
upper_frac)/(1+break_frac))))
    # Make original axes invisible
    axes.set_xticks([])
    axes.set_yticks([])
    print upper_axes.yaxis.get_label().get_position()
    print lower_axes.yaxis.get_label().get_position()
    print axes.yaxis.get_label().get_position()
    print axes.yaxis.labelpad
    for loc, spine in axes.spines.iteritems():
        spine.set_color('none')
    return upper_axes, lower_axes

def prepare_efficiency(axes, lower_bound=0.69):
    """
    Set up an efficiency figure with breakmarks to indicate a suppressed
zero.

    The y-axis limits are set to (lower_bound, 1.0), as appropriate for an
    efficiency plot, and autoscaling is turned off.
    """
    upper_axes, lower_axes = axes_broken_y(axes, upper_frac=0.97)
    lower_axes.set_yticks([])
    upper_axes.set_ylim(lower_bound, 1.)
    upper_axes.set_autoscaley_on(False)
    return upper_axes, lower_axes

# test these
ax = plt.axes()
upper, lower = axes_broken_y(ax, ybounds=[-2., 2.9, 22.1, 30.])
upper.plot(range(30), range(30))
lower.plot(range(30), range(30))
upper.set_ylabel('Data')
plt.savefig('test')

--
View this message in context: http://old.nabble.com/Proposal-for-Broken-Axes-tp27909750p27909750.html
Sent from the matplotlib - devel mailing list archive at Nabble.com.

It's my understanding that there is no built-in method for generating a
"broken axis" (where you skip over some range of values, indicating this
with some graphical mark). I wanted to do this, so I've put together a
function which seems to be fairly robust, and I thought I might propose it
as a starting point if there's interest in having a built-in facility for
broken axes.

Please let me know if this is not the appropriate place to be submitting
this suggestion.

This is a nice start of an oft requested feature, and we are
definitely interested. It is enabled by the spine contribution of
Andrew, so you can turn off the upper and lower spines between the
break, so it is nice to see some unintended benefits of his
refactoring.

From a usability standpoint, one thing we try to do is make pyplot a

thin wrapper around functionality that exists in the API proper in
matplotlib.figure, matplotlib.axes, etc. Functionally and in terms of
implementation, this broken axes implementation is in the style of
"twinx" which makes two axes for plotting on different scales

  http://matplotlib.sourceforge.net/examples/api/two_scales.html
  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.Axes.twinx
  http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.twinx

What would be great is if you could refactor the basic functionality
into a matplotlib.Axes.breaky method (and possibly breakx but most
people request a broken y axis), which would resize the "self" axes
and return the broken compliment which could be plotted onto. Then
you could provide a thin pyplot wrapper much like pyplot.twinx, so
that pyplot as well as API users could benefit.

Finally, an svn patch which provided an example and patches to axes.py
and pyplot.py would be most helpful.

http://matplotlib.sourceforge.net/faq/howto_faq.html#submit-a-patch

An alternative implementation could craft a custom transform using
some custom artists for spines, but this might be a good bit harder.
Do you have an opinion Andrew on this approach?

JDH

···

On Mon, Mar 15, 2010 at 3:16 PM, klukas <klukas@...45...> wrote:

John Hunter wrote:

  

It's my understanding that there is no built-in method for generating a
"broken axis" (where you skip over some range of values, indicating this
with some graphical mark). I wanted to do this, so I've put together a
function which seems to be fairly robust, and I thought I might propose it
as a starting point if there's interest in having a built-in facility for
broken axes.

This is a nice start of an oft requested feature, and we are
definitely interested. It is enabled by the spine contribution of
Andrew, so you can turn off the upper and lower spines between the
break, so it is nice to see some unintended benefits of his
refactoring.

An alternative implementation could craft a custom transform using
some custom artists for spines, but this might be a good bit harder.
Do you have an opinion Andrew on this approach?
  
John, I'm attaching a helper function I wrote to do just this.
Unfortunately, I don't have time to attempt to merge this into MPL right
now...

spine_breaks.py (1.97 KB)

···

On Mon, Mar 15, 2010 at 3:16 PM, klukas <klukas@...45...> wrote:

On Mon, Mar 15, 2010 at 3:16 PM, klukas <klukas@...45...> wrote:

The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven't
figured out how to push out the y-axis label of the main axes object so it
doesn't overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

klukas, I'm afraid I don't understand your issue... Can you explain using it differently?

-Andrew

What would be great is if you could refactor the basic functionality
into a matplotlib.Axes.breaky method (and possibly breakx but most
people request a broken y axis), which would resize the "self" axes
and return the broken compliment which could be plotted onto. Then
you could provide a thin pyplot wrapper much like pyplot.twinx, so
that pyplot as well as API users could benefit.

I can try to do this. I think I would prefer, however, not to resize
the "self" axes and continue with my current approach of creating two
new axes within the original axes. On the user end, I think it makes
more sense to set the title and ylabel of the main axes, rather than
setting them for the individual upper and lower axes. More on that
below.

The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven't
figured out how to push out the y-axis label of the main axes object so it
doesn't overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

klukas, I'm afraid I don't understand your issue... Can you explain using it differently?

In my approach, you end up with a main axes object that is invisible,
and then two visible axes objects (upper and lower) within the main
axes. I would ideally like to have the y label display in the middle
of the main y-axis, independent of where the break lies. If I place a
y label on the main axes (which has ticks or tick labels), though, it
appears right up against the axis line. I'd like it to be placed
further to the left, clear of the tick labels that appear on the upper
and lower axes. So, I'd like to be able to access whatever algorithm
is used to choose the offset of the axis label, and explicitly set the
offset of the ylabel for the main axes so that it clears the tick
labels.

// Jeff

I have implemented breakx and breaky methods for the Axes class and
attached the diff for axes.py to this message.

You can test out the function with the following examples:

brokenaxes.diff (7.5 KB)

···

------------------
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

# Broken y
fig = plt.figure()
main_axes = plt.axes()
plt.title('Broken x-axis example')
plt.xlabel('x-axis label')
subaxes = main_axes.breaky([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
    axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.ylabel('y-axis label')
plt.show()

------------------
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
# Broken x
fig = plt.figure()
main_axes = plt.axes()
plt.title('Broken x-axis example')
plt.ylabel('y-axis label')
subaxes = main_axes.breakx([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
    axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.xlabel('x-axis label')
plt.show()
---------------------

I've included in the docstrings some of the TODO items, but this is
pretty stable in its current form.

Cheers,
Jeff

Jeff Klukas, Research Assistant, Physics
University of Wisconsin -- Madison
jeff.klukas@...830... | jeffyklukas@...831... | jeffklukas@...832...
http://www.hep.wisc.edu/~jklukas/

On Tue, Mar 16, 2010 at 1:08 PM, Jeff Klukas <klukas@...45...> wrote:

What would be great is if you could refactor the basic functionality
into a matplotlib.Axes.breaky method (and possibly breakx but most
people request a broken y axis), which would resize the "self" axes
and return the broken compliment which could be plotted onto. Then
you could provide a thin pyplot wrapper much like pyplot.twinx, so
that pyplot as well as API users could benefit.

I can try to do this. I think I would prefer, however, not to resize
the "self" axes and continue with my current approach of creating two
new axes within the original axes. On the user end, I think it makes
more sense to set the title and ylabel of the main axes, rather than
setting them for the individual upper and lower axes. More on that
below.

The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven't
figured out how to push out the y-axis label of the main axes object so it
doesn't overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

klukas, I'm afraid I don't understand your issue... Can you explain using it differently?

In my approach, you end up with a main axes object that is invisible,
and then two visible axes objects (upper and lower) within the main
axes. I would ideally like to have the y label display in the middle
of the main y-axis, independent of where the break lies. If I place a
y label on the main axes (which has ticks or tick labels), though, it
appears right up against the axis line. I'd like it to be placed
further to the left, clear of the tick labels that appear on the upper
and lower axes. So, I'd like to be able to access whatever algorithm
is used to choose the offset of the axis label, and explicitly set the
offset of the ylabel for the main axes so that it clears the tick
labels.

// Jeff

I haven't heard a response back about the proposal I posted for broken
axes. Hopefully that just means people are busy :). If there are
concerns about the method or interface, I'm certainly open to hearing
them.

In the meantime, I've been thinking about the interface, and I think
the more correct and more ambitious thing to do would be to create a
new BrokenAxes class that inherits from Axes. The class could
redefine __getattribute__ to pass most function calls straight to the
subaxes. So in the end a session could look like the following:

# Create BrokenAxes with bottom from 0 to 5 and top from 30 to 35
ax = plt.broken_axes(ybounds=[0.,5.,30.,35.])
# Plot a line onto BOTH subaxes
ax.plot(range(35),range(35))

The call to plot would get routed through __getattribute__, which
would then call plot for each of the subaxes. This would be much more
intuitive than my existing breaky solution, where you have to loop
over all subaxes and plot on each individually.

The more ambitious thing to do would be to also define a BrokenAxis
class that inherits from Axis and would redefine get_ticklabel_extents
to look as each subaxis and push the axis label far enough out to
clear the ticklabels on all subaxes.

Does that new interface sound like a good idea? Are there any
show-stopping problems that seem apparent. If it sounds like
something worth trying, I could take a stab at writing an
implementation.

Cheers,
Jeff

···

Jeff Klukas, Research Assistant, Physics
University of Wisconsin -- Madison
jeff.klukas@...830... | jeffyklukas@...831... | jeffklukas@...832...
http://www.hep.wisc.edu/~jklukas/

On Thu, Mar 18, 2010 at 1:38 PM, Jeff Klukas <klukas@...45...> wrote:

I have implemented breakx and breaky methods for the Axes class and
attached the diff for axes.py to this message.

You can test out the function with the following examples:
------------------
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

# Broken y
fig = plt.figure()
main_axes = plt.axes()
plt.title('Broken x-axis example')
plt.xlabel('x-axis label')
subaxes = main_axes.breaky([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.ylabel('y-axis label')
plt.show()

------------------
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
# Broken x
fig = plt.figure()
main_axes = plt.axes()
plt.title('Broken x-axis example')
plt.ylabel('y-axis label')
subaxes = main_axes.breakx([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.xlabel('x-axis label')
plt.show()
---------------------

I've included in the docstrings some of the TODO items, but this is
pretty stable in its current form.

Cheers,
Jeff

>> Jeff Klukas, Research Assistant, Physics
>> University of Wisconsin -- Madison
>> jeff.klukas@...830... | jeffyklukas@...831... | jeffklukas@...832...
>> http://www.hep.wisc.edu/~jklukas/

On Tue, Mar 16, 2010 at 1:08 PM, Jeff Klukas <klukas@...45...> wrote:

What would be great is if you could refactor the basic functionality
into a matplotlib.Axes.breaky method (and possibly breakx but most
people request a broken y axis), which would resize the "self" axes
and return the broken compliment which could be plotted onto. Then
you could provide a thin pyplot wrapper much like pyplot.twinx, so
that pyplot as well as API users could benefit.

I can try to do this. I think I would prefer, however, not to resize
the "self" axes and continue with my current approach of creating two
new axes within the original axes. On the user end, I think it makes
more sense to set the title and ylabel of the main axes, rather than
setting them for the individual upper and lower axes. More on that
below.

The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven't
figured out how to push out the y-axis label of the main axes object so it
doesn't overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

klukas, I'm afraid I don't understand your issue... Can you explain using it differently?

In my approach, you end up with a main axes object that is invisible,
and then two visible axes objects (upper and lower) within the main
axes. I would ideally like to have the y label display in the middle
of the main y-axis, independent of where the break lies. If I place a
y label on the main axes (which has ticks or tick labels), though, it
appears right up against the axis line. I'd like it to be placed
further to the left, clear of the tick labels that appear on the upper
and lower axes. So, I'd like to be able to access whatever algorithm
is used to choose the offset of the axis label, and explicitly set the
offset of the ylabel for the main axes so that it clears the tick
labels.

// Jeff

How do you want to handle

l1, = ax.plot(range(35), range(35))
l1.set_color("r")

then?

I think keeping two (or more) separate artists for each axes while an
user think there is only one artist (because only one axes is exposed
to the user) is not a good idea.

Regards,

-JJ

···

On Mon, Mar 29, 2010 at 12:30 PM, Jeff Klukas <klukas@...45...> wrote:

# Create BrokenAxes with bottom from 0 to 5 and top from 30 to 35
ax = plt.broken_axes(ybounds=[0.,5.,30.,35.])
# Plot a line onto BOTH subaxes
ax.plot(range(35),range(35))

The call to plot would get routed through __getattribute__, which
would then call plot for each of the subaxes. This would be much more
intuitive than my existing breaky solution, where you have to loop
over all subaxes and plot on each individually.

First of all, thanks, klukas for the useful piece of code.

Jae-Joon Lee wrote:

# Create BrokenAxes with bottom from 0 to 5 and top from 30 to 35
ax = plt.broken_axes(ybounds=[0.,5.,30.,35.])
# Plot a line onto BOTH subaxes
ax.plot(range(35),range(35))

The call to plot would get routed through __getattribute__, which
would then call plot for each of the subaxes. This would be much more
intuitive than my existing breaky solution, where you have to loop
over all subaxes and plot on each individually.

How do you want to handle

l1, = ax.plot(range(35), range(35))
l1.set_color("r")

then?

Well, I guess BrokenAxes.plot should return a list of lines instead of a
line in ll.
i.e. something like "[[x.lines[-1] for x in ax.subaxes]]"
would replace "[ax.lines[-1]]" as the return value.
Better yet, instead of a list we should have a "vector-type" proxy
container that should transfer method calls to the contained items.

I think keeping two (or more) separate artists for each axes while an
user think there is only one artist (because only one axes is exposed
to the user) is not a good idea.

Ideally this should really be one artist.
However from JDH's response I understand this would be harder to
implement (using custom transforms or something). Maybe emulating one
using the current implementation (as I suggested above) is good enough.

Meanwhile, this redundant looping for each plot call is annoying, so I
can offer the following compromise: store the subaxes in the parent
(broken)Axes (add "self._subaxes = subaxes" before returning from breakx
and breaky), then add a new plot_subs method:

def plot_subs(self,*args,**keys):
    for sub in self._subaxes:
        res = sub.plot(*args,**keys)
    return res

This is a simplified version, returning just the lines of the last
subaxes, but at least this way you can avoid the looping.

Regards,
     Amit A.

···

On Mon, Mar 29, 2010 at 12:30 PM, Jeff Klukas <klukas@...45...> wrote:

Have your changes to axes.py, namely breakx and breaky, been accepted? If not, could you post your axes.py file.
Thanks in advance,
yuffa

···

klukas wrote:

I have implemented breakx and breaky methods for the Axes class and
attached the diff for axes.py to this message.
You can test out the function with the following examples:

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

Broken y

fig = plt.figure()
main_axes = plt.axes()
plt.title(‘Broken x-axis example’)
plt.xlabel(‘x-axis label’)
subaxes = main_axes.breaky([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.ylabel(‘y-axis label’)
plt.show()

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

Broken x

fig = plt.figure()
main_axes = plt.axes()
plt.title(‘Broken x-axis example’)
plt.ylabel(‘y-axis label’)
subaxes = main_axes.breakx([0., 1.9, 5.1, 6.9, 9.1, 12])
for axes in subaxes:
axes.plot(np.linspace(0,12,13),np.linspace(0,12,13))
plt.xlabel(‘x-axis label’)
plt.show()

I’ve included in the docstrings some of the TODO items, but this is
pretty stable in its current form.
Cheers,
Jeff

Jeff Klukas, Research Assistant, Physics
University of Wisconsin – Madison
jeff.klukas@…830… | jeffyklukas@…831… | jeffklukas@…832…
http://www.hep.wisc.edu/~jklukas/
On Tue, Mar 16, 2010 at 1:08 PM, Jeff Klukas wrote:

What would be great is if you could refactor the basic functionality
into a matplotlib.Axes.breaky method (and possibly breakx but most
people request a broken y axis), which would resize the “self” axes
and return the broken compliment which could be plotted onto. Then
you could provide a thin pyplot wrapper much like pyplot.twinx, so
that pyplot as well as API users could benefit.

I can try to do this. I think I would prefer, however, not to resize
the “self” axes and continue with my current approach of creating two
new axes within the original axes. On the user end, I think it makes
more sense to set the title and ylabel of the main axes, rather than
setting them for the individual upper and lower axes. More on that
below.

The only real problems here is that you need to
explicitly plot things on both the upper and lower axes, and then I haven’t
figured out how to push out the y-axis label of the main axes object so it
doesn’t overlap with the tick labels of the upper and lower axes. So, I
instead moved the y-labels of the upper and lower axes so that they appear
at the center of the axis, but this is problematic. Any thoughts on how to
do that part better?

klukas, I’m afraid I don’t understand your issue… Can you explain using it differently?

In my approach, you end up with a main axes object that is invisible,
and then two visible axes objects (upper and lower) within the main
axes. I would ideally like to have the y label display in the middle
of the main y-axis, independent of where the break lies. If I place a
y label on the main axes (which has ticks or tick labels), though, it
appears right up against the axis line. I’d like it to be placed
further to the left, clear of the tick labels that appear on the upper
and lower axes. So, I’d like to be able to access whatever algorithm
is used to choose the offset of the axis label, and explicitly set the
offset of the ylabel for the main axes so that it clears the tick
labels.

// Jeff


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View this message in context: Re: Proposal for Broken Axes

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ayuffa, on 2011-07-07 13:54, wrote:

Have your changes to axes.py, namely breakx and breaky, been accepted? If
not, could you post your axes.py file.

Here's an example, I'm looking into why it's not making it to the
official docs right now, but you should be able to run it
locally:

https://github.com/matplotlib/matplotlib/blob/master/examples/pylab_examples/broken_axis.py

best,

···

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Paul Ivanov
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