Wsrtjtyk

In the figure below (1) there is a lot of white space around the hexagonal grid that I cannot figure out how to remove. I've tried different methods i.e. tight_layout etc.

The code is

import matplotlib.pyplot as plt

from matplotlib.patches import RegularPolygon

import matplotlib.cm as cm

import matplotlib.colors as colors

import numpy



def plot_som_hm(hm,colormap,a=1):

    # setup hexagon offsets

    m,n = hm.shape

    offsety = .75 * 2*a

    offsetx = numpy.sqrt(3) * a

    evenrow = numpy.sqrt(3)/2 * a



    # set up the figure

    fig,ax = plt.subplots(figsize=(2,2))

    ax.set_aspect('equal')



    # define colormap

    cmap = cm.ScalarMappable(None,colormap)

    norm = colors.Normalize(vmin=hm.min(),vmax=hm.max())



    # iterate over the hitmap, drawing a hexagon 

    xs = 

    ys = 

    for i in range(m):

        for j in range(n):

            # calculate center point for current hexagonal grid & draw it

            offsetr = evenrow if i % 2 == 0 else 0

            x,y = (j*offsetx+offsetr,-i*offsety)

            hexg = RegularPolygon(

                (x,y),numVertices=6,radius=a,facecolor=cmap.cmap(norm(hm[i][j]))

            )

            ax.add_patch(hexg)

            xs.append(x)

            ys.append(y)



    # add a scatter plot so all hexagons show up & turn off ticks

    ax.scatter(xs,ys,alpha=1.0)

    ax.set_xticks()

    ax.set_yticks()



    # add a colorbar

    sm = plt.cm.ScalarMappable(cmap=colormap,norm=norm)

    sm._A = 

    plt.colorbar(sm,ticks=range(int(hm.min()),int(hm.max())+1))



    # and show the hitmap

    plt.show()

which can be called by plot_som_hm(hitmap,'inferno',-0.5)

I am not sure if the whitespace is the result of calling subplots (figsize=(2,2)) or something else. Being relatively new to matplotlib I am not sure where the whitespace is coming from i.e. if it is the figure, the axis or even the plt so searching on Google has not provided any relevant answers.

II suggest to read the x- and y-limits to see how you can adjust them to your needs, i.e.:

print(ax.get_xlim())

and then e.g.

ax.set_xlim(0.5, 5.5)

or whatever fits.

The same then with the y-axis.