Matplotlib 2 Subplots 1 Colorbar

Question

I ve spent entirely too long researching how to get two subplots to share the same y-axis with a single colorbar shared between the two in Matplotlib    What was happening was that when I called the colorbar   function in either subplot1 or subplot2  it would autoscale the plot such that the colorbar plus the plot would fit inside the  subplot  bounding box  causing the two side-by-side plots to be two very different sizes   To get around this  I tried to create a third subplot which I then hacked to render no plot with just a colorbar present   The only problem is  now the heights and widths of the two plots are uneven  and I can t figure out how to make it look okay   Here is my code   from   future   import division import matplotlib pyplot as plt import numpy as np from matplotlib import patches from matplotlib ticker import NullFormatter    SIS Functions TE   1   Einstein radius g1   lambda x y   TE 2     y  2-x  2    x  2 y  2    3 2    g2   lambda x y  -1 TE x y     x  2 y  2    3 2   kappa   lambda x y  TE    2 np sqrt x  2 y  2    coords   np linspace -2 2 400  X Y   np meshgrid coords coords  g1out   g1 X Y  g2out   g2 X Y  kappaout   kappa X Y  for i in range len coords        for j in range len coords            if np sqrt coords i   2 coords j   2   lt   TE              g1out i  j  0             g2out i  j  0  fig   plt figure   fig subplots adjust wspace 0 hspace 0     subplot number 1 ax1   fig add subplot 1 2 1 aspect  equal  xlim  -2 2  ylim  -2 2   plt title r   gamma  1    fontsize  18   plt xlabel r x    theta  E     fontsize  15   plt ylabel r y    theta  E     rotation  horizontal  fontsize  15   plt xticks  -2 0 -1 5 -1 0 -0 5 0 0 5 1 0 1 5   plt xticks  -2 0 -1 5 -1 0 -0 5 0 0 5 1 0 1 5   plt imshow g1out extent  -2 2 -2 2   plt axhline y 0 linewidth 2 color  k  linestyle  --   plt axvline x 0 linewidth 2 color  k  linestyle  --   e1   patches Ellipse  0 0  2 2 color  white   ax1 add patch e1     subplot number 2 ax2   fig add subplot 1 2 2 sharey ax1 xlim  -2 2  ylim  -2 2   plt title r   gamma  2    fontsize  18   plt xlabel r x    theta  E     fontsize  15   ax2 yaxis set major formatter  NullFormatter     plt axhline y 0 linewidth 2 color  k  linestyle  --   plt axvline x 0 linewidth 2 color  k  linestyle  --   plt imshow g2out extent  -2 2 -2 2   e2   patches Ellipse  0 0  2 2 color  white   ax2 add patch e2     subplot for colorbar ax3   fig add subplot 1 1 1  ax3 axis  off   cbar   plt colorbar ax ax2   plt show

User · Answer

Shared colormap and colorbar This is for the more complex case where the values are not just between 0 and 1  the cmap needs to be shared instead of just using the last one  import numpy as np from matplotlib colors import Normalize import matplotlib pyplot as plt import matplotlib cm as cm fig  axes   plt subplots nrows 2  ncols 2  cmap cm get cmap  viridis   normalizer Normalize 0 4  im cm ScalarMappable norm normalizer  for i ax in enumerate axes flat       ax imshow i np random random  10 10   cmap cmap norm normalizer      ax set title str i   fig colorbar im  ax axes ravel   tolist    plt show

User · Answer

You can simplify Joe Kington s code using the axparameter of figure colorbar   with a list of axes  From the documentation      ax             None   parent axes object s  from which space for a new colorbar axes will be stolen  If a list of axes is given they will all be resized to make room for the colorbar axes       import numpy as np import matplotlib pyplot as plt  fig  axes   plt subplots nrows 2  ncols 2  for ax in axes flat      im   ax imshow np random random  10 10    vmin 0  vmax 1   fig colorbar im  ax axes ravel   tolist     plt show

User · Answer

I noticed that almost every solution posted involved ax imshow im       and did not normalize the colors displayed to the colorbar for the multiple subfigures  The im mappable is taken from the last instance  but what if the values of the multiple im-s are different   I m assuming these mappables are treated in the same way that the contour-sets and surface-sets are treated   I have an example using a 3d surface plot below that creates two colorbars for a 2x2 subplot  one colorbar per one row   Although the question asks explicitly for a different arrangement  I think the example helps clarify some things  I haven t found a way to do this using plt subplots      yet because of the 3D axes unfortunately     If only I could position the colorbars in a better way     There is probably a much better way to do this  but at least it should be not too difficult to follow    import matplotlib from matplotlib import cm import matplotlib pyplot as plt import numpy as np from mpl toolkits mplot3d import Axes3D  cmap    plasma  ncontours   5  def get data row  col           get X  Y  Z  and plot number of subplot         Z  gt  0 for top row  Z  lt  0 for bottom row         if row    0          x   np linspace 1  10  10  dtype int          X  Y   np meshgrid x  x          Z   np sqrt X  2   Y  2          if col    0              pnum   1         else              pnum   2     elif row    1          x   np linspace 1  10  10  dtype int          X  Y   np meshgrid x  x          Z   -np sqrt X  2   Y  2          if col    0              pnum   3         else              pnum   4     print   nPNUM      Zmin       Zmax      n  format pnum  np min Z   np max Z        return X  Y  Z  pnum  fig   plt figure   nrows  ncols   2  2 zz      axes      for row in range nrows       for col in range ncols           X  Y  Z  pnum   get data row  col          ax   fig add subplot nrows  ncols  pnum  projection  3d           ax set title  row       col       format row  col           fhandle   ax plot surface X  Y  Z  cmap cmap          zz append Z          axes append ax      get full range of Z data as flat list for top and bottom rows zz top   zz 0  reshape -1  tolist     zz 1  reshape -1  tolist   zz btm   zz 2  reshape -1  tolist     zz 3  reshape -1  tolist      get top and bottom axes ax top    axes 0   axes 1   ax btm    axes 2   axes 3      normalize colors to minimum and maximum values of dataset norm top   matplotlib colors Normalize vmin min zz top   vmax max zz top   norm btm   matplotlib colors Normalize vmin min zz btm   vmax max zz btm   cmap   cm get cmap cmap  ncontours    number of colors on colorbar mtop   cm ScalarMappable cmap cmap  norm norm top  mbtm   cm ScalarMappable cmap cmap  norm norm btm  for m in  mtop  mbtm       m set array           create cax to draw colorbar in   cax top   fig add axes  0 9  0 55  0 05  0 4     cax btm   fig add axes  0 9  0 05  0 05  0 4   cbar top   fig colorbar mtop  ax ax top  orientation  vertical   shrink 0 75  pad 0 2     cax cax top  cbar top set ticks np linspace min zz top   max zz top   ncontours   cbar btm   fig colorbar mbtm  ax ax btm  orientation  vertical   shrink 0 75  pad 0 2     cax cax btm  cbar btm set ticks np linspace min zz btm   max zz btm   ncontours    plt show   plt close fig     orientation of colorbar    horizontal  if done by column

User · Answer

Using make axes is even easier and gives a better result  It also provides possibilities to customise the positioning of the colorbar  Also note the option of subplots to share x and y axes   import numpy as np import matplotlib pyplot as plt import matplotlib as mpl  fig  axes   plt subplots nrows 2  ncols 2  sharex True  sharey True  for ax in axes flat      im   ax imshow np random random  10 10    vmin 0  vmax 1   cax kw   mpl colorbar make axes  ax for ax in axes flat   plt colorbar im  cax cax    kw   plt show

User · Answer

To add to  abevieiramota s excellent answer  you can get the euqivalent of tight layout with constrained layout   You will still get large horizontal gaps if you use imshow instead of pcolormesh because of the 1 1 aspect ratio imposed by imshow       import numpy as np import matplotlib pyplot as plt  fig  axes   plt subplots nrows 2  ncols 2  constrained layout True  for ax in axes flat      im   ax pcolormesh np random random  10 10    vmin 0  vmax 1   fig colorbar im  ax axes flat  plt show

User · Answer

The solution of using a list of axes by abevieiramota works very well until you use only one row of images  as pointed out in the comments   Using a reasonable aspect ratio for figsize helps  but is still far from perfect   For example   import numpy as np import matplotlib pyplot as plt  fig  axes   plt subplots nrows 1  ncols 3  figsize  9 75  3   for ax in axes flat      im   ax imshow np random random  10 10    vmin 0  vmax 1   fig colorbar im  ax axes ravel   tolist     plt show       The colorbar function provides the shrink parameter which is a scaling factor for the size of the colorbar axes   It does require some manual trial and error   For example   fig colorbar im  ax axes ravel   tolist    shrink 0 75

User · Answer

As a beginner who stumbled across this thread  I d like to add a python-for-dummies adaptation of abevieiramota s very neat answer  because I m at the level that I had to look up  ravel  to work out what their code was doing    import numpy as np import matplotlib pyplot as plt  fig    ax1 ax2 ax3   ax4 ax5 ax6     plt subplots 2 3   axlist    ax1 ax2 ax3 ax4 ax5 ax6   first   ax1 imshow np random random  10 10    vmin 0  vmax 1  third   ax3 imshow np random random  12 12    vmin 0  vmax 1   fig colorbar first  ax axlist   plt show     Much less pythonic  much easier for noobs like me to see what s actually happening here

User · Answer

This topic is well covered but I still would like to propose another approach in a slightly different philosophy   It is a bit more complex to set-up but it allow  in my opinion  a bit more flexibility  For example  one can play with the respective ratios of each subplots   colorbar   import matplotlib pyplot as plt import numpy as np from matplotlib gridspec import GridSpec    Define number of rows and columns you want in your figure nrow   2 ncol   3    Make a new figure fig   plt figure constrained layout True     Design your figure properties widths    3 4 5 1  gs   GridSpec nrow  ncol   1  figure fig  width ratios widths     Fill your figure with desired plots axes      for i in range nrow       for j in range ncol           axes append fig add subplot gs i  j            im   axes -1  pcolormesh np random random  10 10       Shared colorbar     axes append fig add subplot gs    ncol    fig colorbar im  cax axes -1    plt show

User · Answer

As pointed out in other answers  the idea is usually to define an axes for the colorbar to reside in  There are various ways of doing so  one that hasn t been mentionned yet would be to directly specify the colorbar axes at subplot creation with plt subplots    The advantage is that the axes position does not need to be manually set and in all cases with automatic aspect the colorbar will be exactly the same height as the subplots  Even in many cases where images are used the result will be satisfying as shown below    When using plt subplots    the use of gridspec kw argument allows to make the colorbar axes much smaller than the other axes    fig   ax  ax2  cax    plt subplots ncols 3 figsize  5 5 3                      gridspec kw   width ratios   1 1  0 05      Example    import matplotlib pyplot as plt import numpy as np  np random seed 1   fig   ax  ax2  cax    plt subplots ncols 3 figsize  5 5 3                      gridspec kw   width ratios   1 1  0 05    fig subplots adjust wspace 0 3  im    ax imshow np random rand 11 8   vmin 0  vmax 1  im2   ax2 imshow np random rand 11 8   vmin 0  vmax 1  ax set ylabel  y label    fig colorbar im  cax cax   plt show       This works well  if the plots  aspect is autoscaled or the images are shrunk due to their aspect in the width direction  as in the above   If  however  the images are wider then high  the result would look as follows  which might be undesired     A solution to fix the colorbar height to the subplot height would be to use mpl toolkits axes grid1 inset locator InsetPosition to set the colorbar axes relative to the image subplot axes   import matplotlib pyplot as plt import numpy as np  np random seed 1  from mpl toolkits axes grid1 inset locator import InsetPosition  fig   ax  ax2  cax    plt subplots ncols 3 figsize  7 3                      gridspec kw   width ratios   1 1  0 05    fig subplots adjust wspace 0 3  im    ax imshow np random rand 11 16   vmin 0  vmax 1  im2   ax2 imshow np random rand 11 16   vmin 0  vmax 1  ax set ylabel  y label    ip   InsetPosition ax2   1 05 0 0 05 1    cax set axes locator ip   fig colorbar im  cax cax  ax  ax ax2    plt show

User · Answer

This solution does not require manual tweaking of axes locations or colorbar size  works with multi-row and single-row layouts  and works with tight layout     It is adapted from a gallery example  using ImageGrid from matplotlib s AxesGrid Toolbox   import numpy as np import matplotlib pyplot as plt from mpl toolkits axes grid1 import ImageGrid    Set up figure and image grid fig   plt figure figsize  9 75  3    grid   ImageGrid fig  111             as in plt subplot 111                   nrows ncols  1 3                    axes pad 0 15                   share all True                   cbar location  right                    cbar mode  single                    cbar size  7                     cbar pad 0 15                        Add data to image grid for ax in grid      im   ax imshow np random random  10 10    vmin 0  vmax 1     Colorbar ax cax colorbar im  ax cax toggle label True    plt tight layout        Works  but may still require rect paramater to keep colorbar labels visible plt show

User · Answer

Just place the colorbar in its own axis and use subplots adjust to make room for it   As a quick example   import numpy as np import matplotlib pyplot as plt  fig  axes   plt subplots nrows 2  ncols 2  for ax in axes flat      im   ax imshow np random random  10 10    vmin 0  vmax 1   fig subplots adjust right 0 8  cbar ax   fig add axes  0 85  0 15  0 05  0 7   fig colorbar im  cax cbar ax   plt show       Note that the color range will be set by the last image plotted  that gave rise to im  even if the range of values is set by vmin and vmax  If another plot has  for example  a higher max value  points with higher values than the max of im will show in uniform color

[python] Matplotlib 2 Subplots, 1 Colorbar

Shared colormap and colorbar

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