[Matplotlib-users] Understanding axes position

[Jody Klymak]

As pointed out by Eric Firing 
([here](https://github.com/matplotlib/matplotlib/issues/9207)) you can 
also do:

```python

ax.set_aspect(1.)
ax.apply_aspect()
pos = ax.get_position(original=False)

```

Cheers,   Jody


On 20 Sep 2017, at 12:30, Jody Klymak wrote:

> On 20 Sep 2017, at 11:32, Klymak Jody wrote:
>
>> Oops.  Just realized you can also just do
>>
>> Pos =ax._postion
>>
>> To get the current position.  Of course this could break because you 
>> are accessing a private variable.
>
> oops again, no you can’t, you need to use the formula below.  The 
> reason is that `apply_aspect` doesn’t get called until the axes is 
> drawn, so the new `_position` isn’t set until then.
>
> Sorry, I should have checked before I wrote….
>
> Cheers,   Jody
>
>
>
>>
>> Cheers.  Jody
>>
>> Sent from my iPhone
>>
>>> On Sep 20, 2017, at 11:07, Jody Klymak <jklymak at uvic.ca> wrote:
>>>
>>> Hi Nunzio,
>>>
>>> The issue is that you call ax.set_aspect(‘equal’), and that 
>>> changes the axes box. However, ax.get_position returns the frozen 
>>> position, i.e. the old position. I don’t see a method to return 
>>> the new position (and I wonder why get_position behaves this way).
>>>
>>> As a work around, you can get the aspect-ratio changed position as:
>>>
>>> figW, figH = fig.get_size_inches()
>>> fig_aspect = figH / figW
>>> newpos = pp.shrunk_to_aspect(ax.get_aspect() * ax.get_data_ratio(), 
>>> pp, fig_aspect).anchored(ax.get_anchor(), pp))
>>> which I appreciate is a bit of a pain….
>>>
>>> Cheers, Jody
>>>
>>> On 20 Sep 2017, at 7:06, Nunzio Losacco wrote:
>>>
>>> Hi all,
>>>
>>> what I’m trying to do here is having third plot with its base 
>>> aligned with the others and with reduced height (the final aim is 
>>> custom positioning a colorbar).
>>> As you can see I’m getting the wrong position. What am I missing?
>>>
>>> Thanks for any help
>>>
>>> NL
>>>
>>> # -*- coding: utf-8 -*-
>>>
>>> from __future__ import unicode_literals
>>> import numpy as np
>>> from scipy.interpolate import griddata
>>> import matplotlib
>>> import matplotlib.pyplot as plt
>>> from matplotlib.patches import Circle
>>> from matplotlib.pylab import cm
>>> import matplotlib.colors as colors
>>> from mpl_toolkits.axes_grid1 import make_axes_locatable, axes_size
>>>
>>> matplotlib.rcParams.update({'font.size': 8})
>>>
>>> fig = plt.figure()
>>> fig.set_size_inches(6.3,6.3)
>>>
>>> ax1 = plt.subplot(111)
>>> divider = make_axes_locatable(ax1)
>>> ax2 = divider.append_axes('right', size='100%', pad=0.3)
>>>
>>> axes = [ax1, ax2]
>>> ltypes = ['dashed', 'solid']
>>>
>>> xi = np.linspace(-18.125, 18.125, 11)
>>> yi = np.linspace(0, 28, 9)
>>> xv, yv = np.meshgrid(xi, yi)
>>>
>>> xcOdd = 0.2
>>> zcOdd = 0.725
>>> xcEven = 0.6
>>> zcEven = 0.725
>>>
>>> maskRadius = 0.15
>>>
>>> for i in range(2):
>>> ax = axes[i]
>>> ax.set_xlabel('distance [m]')
>>> if i == 0:
>>> ax.set_ylabel('depth [m]')
>>> if i == 1:
>>> ax.set_yticklabels([])
>>> ax.invert_yaxis()
>>> ax.tick_params(direction='in')
>>> ax.set_aspect('equal')
>>> odd = Circle((xcOdd, zcOdd), .15, linewidth=1.2, color='k', 
>>> fill=False)
>>> even = Circle((xcEven, zcEven), .15, linewidth=1.2, 
>>> linestyle=ltypes[i], color='k', fill=False)
>>>
>>> vmax = 15.
>>> vmin = 0.
>>> norm = matplotlib.colors.Normalize(vmin,vmax, clip=False)
>>>
>>> color_map = 
>>> matplotlib.colors.ListedColormap(plt.cm.Greys(np.linspace(0.25, 1, 
>>> 5)), "name")
>>>
>>> ax.add_patch(odd)
>>> ax.add_patch(even)
>>>
>>> pad = 0.03
>>> width = 0.03
>>>
>>> pos = ax2.get_position()
>>>
>>> ax3 = fig.add_axes([pos.xmax + pad, pos.ymin, width, 
>>> 0.7*(pos.ymax-pos.ymin) ])
>>>
>>> plt.savefig('prova-vect-paper-test-2.eps', format='eps')
>>>
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>
>
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