Axes class – set explicitly size (width/height) of axes in given units
Question:
I want to to create a figure using matplotlib where I can explicitly specify the size of the axes, i.e. I want to set the width and height of the axes bbox.
I have looked around all over and I cannot find a solution for this. What I typically find is how to adjust the size of the complete Figure (including ticks and labels), for example using fig, ax = plt.subplots(figsize=(w, h))
This is very important for me as I want to have a 1:1 scale of the axes, i.e. 1 unit in paper is equal to 1 unit in reality. For example, if xrange is 0 to 10 with major tick = 1 and x axis is 10cm, then 1 major tick = 1cm. I will save this figure as pdf to import it to a latex document.
This question brought up a similar topic but the answer does not solve my problem (using plt.gca().set_aspect('equal', adjustable='box') code)
From this other question I see that it is possible to get the axes size, but not how to modify them explicitly.
Any ideas how I can set the axes box size and not just the figure size. The figure size should adapt to the axes size.
Thanks!
For those familiar with pgfplots in latex, it will like to have something similar to the scale only axis option (see here for example).
Answers:
The axes size is determined by the figure size and the figure spacings, which can be set using figure.subplots_adjust(). In reverse this means that you can set the axes size by setting the figure size taking into acount the figure spacings:
import matplotlib.pyplot as plt
def set_size(w,h, ax=None):
""" w, h: width, height in inches """
if not ax: ax=plt.gca()
l = ax.figure.subplotpars.left
r = ax.figure.subplotpars.right
t = ax.figure.subplotpars.top
b = ax.figure.subplotpars.bottom
figw = float(w)/(r-l)
figh = float(h)/(t-b)
ax.figure.set_size_inches(figw, figh)
fig, ax=plt.subplots()
ax.plot([1,3,2])
set_size(5,5)
plt.show()
It appears that Matplotlib has helper classes that allow you to define axes with a fixed size Demo fixed size axes
I have found that ImportanceofBeingErnests answer which modifies that figure size to adjust the axes size provides inconsistent results with the paticular matplotlib settings I use to produce publication ready plots. Slight errors were present in the final figure size, and I was unable to find a way to solve the issue with his approach. For most use cases I think this is not a problem, however the errors were noticeable when combining multiple pdf’s for publication.
In lieu of developing a minimum working example to find the real issue I am having with the figure resizing approach I instead found a work around which uses the fixed axes size utilising the divider class.
from mpl_toolkits.axes_grid1 import Divider, Size
def fix_axes_size_incm(axew, axeh):
axew = axew/2.54
axeh = axeh/2.54
#lets use the tight layout function to get a good padding size for our axes labels.
fig = plt.gcf()
ax = plt.gca()
fig.tight_layout()
#obtain the current ratio values for padding and fix size
oldw, oldh = fig.get_size_inches()
l = ax.figure.subplotpars.left
r = ax.figure.subplotpars.right
t = ax.figure.subplotpars.top
b = ax.figure.subplotpars.bottom
#work out what the new ratio values for padding are, and the new fig size.
neww = axew+oldw*(1-r+l)
newh = axeh+oldh*(1-t+b)
newr = r*oldw/neww
newl = l*oldw/neww
newt = t*oldh/newh
newb = b*oldh/newh
#right(top) padding, fixed axes size, left(bottom) pading
hori = [Size.Scaled(newr), Size.Fixed(axew), Size.Scaled(newl)]
vert = [Size.Scaled(newt), Size.Fixed(axeh), Size.Scaled(newb)]
divider = Divider(fig, (0.0, 0.0, 1., 1.), hori, vert, aspect=False)
# the width and height of the rectangle is ignored.
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
#we need to resize the figure now, as we have may have made our axes bigger than in.
fig.set_size_inches(neww,newh)
Things worth noting:
- Once you call
set_axes_locator() on an axis instance you break the tight_layout() function.
- The original figure size you choose will be irrelevent, and the final figure size is determined by the axes size you choose and the size of the labels/tick labels/outward ticks.
- This approach doesn’t work with colour scale bars.
- This is my first ever stack overflow post.
another method using fig.add_axes was quite accurate. I have included 1 cm grid aswell
import matplotlib.pyplot as plt
import matplotlib as mpl
# This example fits a4 paper with 5mm margin printers
# figure settings
figure_width = 28.7 # cm
figure_height = 20 # cm
left_right_magrin = 1 # cm
top_bottom_margin = 1 # cm
# Don't change
left = left_right_magrin / figure_width # Percentage from height
bottom = top_bottom_margin / figure_height # Percentage from height
width = 1 - left*2
height = 1 - bottom*2
cm2inch = 1/2.54 # inch per cm
# specifying the width and the height of the box in inches
fig = plt.figure(figsize=(figure_width*cm2inch,figure_height*cm2inch))
ax = fig.add_axes((left, bottom, width, height))
# limits settings (important)
plt.xlim(0, figure_width * width)
plt.ylim(0, figure_height * height)
# Ticks settings
ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(5))
ax.xaxis.set_minor_locator(mpl.ticker.MultipleLocator(1))
ax.yaxis.set_major_locator(mpl.ticker.MultipleLocator(5))
ax.yaxis.set_minor_locator(mpl.ticker.MultipleLocator(1))
# Grid settings
ax.grid(color="gray", which="both", linestyle=':', linewidth=0.5)
# your Plot (consider above limits)
ax.plot([1,2,3,5,6,7,8,9,10,12,13,14,15,17])
# save figure ( printing png file had better resolution, pdf was lighter and better on screen)
plt.show()
fig.savefig('A4_grid_cm.png', dpi=1000)
fig.savefig('tA4_grid_cm.pdf')
result:
I want to to create a figure using matplotlib where I can explicitly specify the size of the axes, i.e. I want to set the width and height of the axes bbox.
I have looked around all over and I cannot find a solution for this. What I typically find is how to adjust the size of the complete Figure (including ticks and labels), for example using fig, ax = plt.subplots(figsize=(w, h))
This is very important for me as I want to have a 1:1 scale of the axes, i.e. 1 unit in paper is equal to 1 unit in reality. For example, if xrange is 0 to 10 with major tick = 1 and x axis is 10cm, then 1 major tick = 1cm. I will save this figure as pdf to import it to a latex document.
This question brought up a similar topic but the answer does not solve my problem (using plt.gca().set_aspect('equal', adjustable='box') code)
From this other question I see that it is possible to get the axes size, but not how to modify them explicitly.
Any ideas how I can set the axes box size and not just the figure size. The figure size should adapt to the axes size.
Thanks!
For those familiar with pgfplots in latex, it will like to have something similar to the scale only axis option (see here for example).
The axes size is determined by the figure size and the figure spacings, which can be set using figure.subplots_adjust(). In reverse this means that you can set the axes size by setting the figure size taking into acount the figure spacings:
import matplotlib.pyplot as plt
def set_size(w,h, ax=None):
""" w, h: width, height in inches """
if not ax: ax=plt.gca()
l = ax.figure.subplotpars.left
r = ax.figure.subplotpars.right
t = ax.figure.subplotpars.top
b = ax.figure.subplotpars.bottom
figw = float(w)/(r-l)
figh = float(h)/(t-b)
ax.figure.set_size_inches(figw, figh)
fig, ax=plt.subplots()
ax.plot([1,3,2])
set_size(5,5)
plt.show()
It appears that Matplotlib has helper classes that allow you to define axes with a fixed size Demo fixed size axes
I have found that ImportanceofBeingErnests answer which modifies that figure size to adjust the axes size provides inconsistent results with the paticular matplotlib settings I use to produce publication ready plots. Slight errors were present in the final figure size, and I was unable to find a way to solve the issue with his approach. For most use cases I think this is not a problem, however the errors were noticeable when combining multiple pdf’s for publication.
In lieu of developing a minimum working example to find the real issue I am having with the figure resizing approach I instead found a work around which uses the fixed axes size utilising the divider class.
from mpl_toolkits.axes_grid1 import Divider, Size
def fix_axes_size_incm(axew, axeh):
axew = axew/2.54
axeh = axeh/2.54
#lets use the tight layout function to get a good padding size for our axes labels.
fig = plt.gcf()
ax = plt.gca()
fig.tight_layout()
#obtain the current ratio values for padding and fix size
oldw, oldh = fig.get_size_inches()
l = ax.figure.subplotpars.left
r = ax.figure.subplotpars.right
t = ax.figure.subplotpars.top
b = ax.figure.subplotpars.bottom
#work out what the new ratio values for padding are, and the new fig size.
neww = axew+oldw*(1-r+l)
newh = axeh+oldh*(1-t+b)
newr = r*oldw/neww
newl = l*oldw/neww
newt = t*oldh/newh
newb = b*oldh/newh
#right(top) padding, fixed axes size, left(bottom) pading
hori = [Size.Scaled(newr), Size.Fixed(axew), Size.Scaled(newl)]
vert = [Size.Scaled(newt), Size.Fixed(axeh), Size.Scaled(newb)]
divider = Divider(fig, (0.0, 0.0, 1., 1.), hori, vert, aspect=False)
# the width and height of the rectangle is ignored.
ax.set_axes_locator(divider.new_locator(nx=1, ny=1))
#we need to resize the figure now, as we have may have made our axes bigger than in.
fig.set_size_inches(neww,newh)
Things worth noting:
- Once you call
set_axes_locator()on an axis instance you break thetight_layout()function. - The original figure size you choose will be irrelevent, and the final figure size is determined by the axes size you choose and the size of the labels/tick labels/outward ticks.
- This approach doesn’t work with colour scale bars.
- This is my first ever stack overflow post.
another method using fig.add_axes was quite accurate. I have included 1 cm grid aswell
import matplotlib.pyplot as plt
import matplotlib as mpl
# This example fits a4 paper with 5mm margin printers
# figure settings
figure_width = 28.7 # cm
figure_height = 20 # cm
left_right_magrin = 1 # cm
top_bottom_margin = 1 # cm
# Don't change
left = left_right_magrin / figure_width # Percentage from height
bottom = top_bottom_margin / figure_height # Percentage from height
width = 1 - left*2
height = 1 - bottom*2
cm2inch = 1/2.54 # inch per cm
# specifying the width and the height of the box in inches
fig = plt.figure(figsize=(figure_width*cm2inch,figure_height*cm2inch))
ax = fig.add_axes((left, bottom, width, height))
# limits settings (important)
plt.xlim(0, figure_width * width)
plt.ylim(0, figure_height * height)
# Ticks settings
ax.xaxis.set_major_locator(mpl.ticker.MultipleLocator(5))
ax.xaxis.set_minor_locator(mpl.ticker.MultipleLocator(1))
ax.yaxis.set_major_locator(mpl.ticker.MultipleLocator(5))
ax.yaxis.set_minor_locator(mpl.ticker.MultipleLocator(1))
# Grid settings
ax.grid(color="gray", which="both", linestyle=':', linewidth=0.5)
# your Plot (consider above limits)
ax.plot([1,2,3,5,6,7,8,9,10,12,13,14,15,17])
# save figure ( printing png file had better resolution, pdf was lighter and better on screen)
plt.show()
fig.savefig('A4_grid_cm.png', dpi=1000)
fig.savefig('tA4_grid_cm.pdf')
result: