Matplotlib RegularPolygon collection location on the canvas

Question

I am trying to plot a feature map (SOM) using python. To keep it simple, imagine a 2D plot where each unit is represented as an hexagon. As it is shown on this topic: Hexagonal Self-Organizing map in Python the hexagons are located side-by-side formated as a grid. I manage to write the following piece of code and it works perfectly for a set number of polygons and for only few shapes (6 x 6 or 10 x 4 hexagons for example). However one important feature of a method like this is to support any grid shape from 3 x 3. ``` def plot_map(grid, d_matrix, w=10, title='SOM Hit map'): """ Plot hexagon map where each neuron is represented by a hexagon. The hexagon color is given by the distance between the neurons (D-Matrix) Scaled hexagons will appear on top of the background image whether the hits array is provided. They are scaled according to the number of hits on each neuron. Args: - grid: Grid dictionary (keys: centers, x, y ), - d_matrix: array contaning the distances between each neuron -…

Accepted Answer

I've manage to find a workaround by calculating the figure size of inches according the given dpi. After, I compute the pixel distance between two adjacent points (by plotting it using a hidden scatter plot). This way I could calculate the hexagon apothem and estimate correctly the size of the hexagon's inner circle (as the matplotlib expects).

No gaps in the end!

```
import matplotlib.pyplot as plt
from matplotlib import colors, cm
from matplotlib.collections import RegularPolyCollection
from mpl_toolkits.axes_grid1 import make_axes_locatable
import math
import numpy as np

def plot_map(grid,
             d_matrix,
             w=1080,
            dpi=72.,
            title='SOM Hit map'):
    """
    Plot hexagon map where each neuron is represented by a hexagon. The hexagon
    color is given by the distance between the neurons (D-Matrix)

Args:
    - grid: Grid dictionary (keys: centers, x, y ),
    - d_matrix: array contaning the distances between each neuron
    - w: width of the map in inches
    - title: map title

Returns the Matplotlib SubAxis instance
    """
    n_centers = grid['centers']
    x, y = grid['x'], grid['y']
    # Size of figure in inches
    xinch = (x * w / y) / dpi
    yinch = (y * w / x) / dpi
    fig = plt.figure(figsize=(xinch, yinch), dpi=dpi)
    ax = fig.add_subplot(111, aspect='equal')
    # Get pixel size between to data points
    xpoints = n_centers[:, 0]
    ypoints = n_centers[:, 1]
    ax.scatter(xpoints, ypoints, s=0.0, marker='s')
    ax.axis([min(xpoints)-1., max(xpoints)+1.,
             min(ypoints)-1., max(ypoints)+1.])
    xy_pixels = ax.transData.transform(np.vstack([xpoints, ypoints]).T)
    xpix, ypix = xy_pixels.T

# In matplotlib, 0,0 is the lower left corner, whereas it's usually the
    # upper right for most image software, so we'll flip the y-coords
    width, height = fig.canvas.get_width_height()
    ypix = height - ypix

# discover radius and hexagon
    apothem = .9 * (xpix[1] - xpix[0]) / math.sqrt(3)
    area_inner_circle = math.pi * (apothem ** 2)
    collection_bg = RegularPolyCollection(
        numsides=6,  # a hexagon
        rotation=0,
        sizes=(area_inner_circle,),
        edgecolors = (0, 0, 0, 1),
        array= d_matrix,
        cmap = cm.gray,
        offsets = n_centers,
        transOffset = ax.transData,
    )
    ax.add_collection(collection_bg, autolim=True)

ax.axis('off')
    ax.autoscale_view()
    ax.set_title(title)
    divider = make_axes_locatable(ax)
    cax = divider.append_axes("right", size="10%", pad=0.05)
    plt.colorbar(collection_bg, cax=cax)

return ax
```

Matplotlib RegularPolygon collection location on the canvas

Solution

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