Example illustrating `imshow` usage, with `origin`, `extent` and `ogrid`.

imshow.png

imshow_example.py

import numpy as np
from matplotlib import pyplot, colors, cm
from mpl_toolkits.axes_grid1 import make_axes_locatable


def main():
    left = -0.5
    bottom = -0.5
    right = 6.5
    top = 5.5

    y, x = np.ogrid[
        int(bottom + 0.5) : int(top + 0.5), int(left + 0.5) : int(right + 0.5)
    ]
    data = x + y

    fig, ax = pyplot.subplots()
    img = ax.imshow(
        data,
        origin="lower",
        extent=(left, right, bottom, top),
        norm=colors.Normalize(vmin=data.min(), vmax=data.max()),
        cmap=cm.get_cmap("cividis"),
    )
    divider = make_axes_locatable(ax)
    cax = divider.append_axes("right", size="4%", pad=0.02)
    cbar = ax.figure.colorbar(
        img,
        cax=cax,
    )
    cbar.set_label(r"data ($\mathrm{\#}$)")

    ax.set_xlabel(r"$x$ ($\mathrm{\#}$)")
    ax.set_ylabel(r"$y$ ($\mathrm{\#}$)")

    fig.savefig("imshow.png")
    pyplot.close(fig)


if __name__ == "__main__":
    main()

out.txt

# data: (6, 7)
[[ 0  1  2  3  4  5  6]
[ 1  2  3  4  5  6  7]
[ 2  3  4  5  6  7  8]
[ 3  4  5  6  7  8  9]
[ 4  5  6  7  8  9 10]
[ 5  6  7  8  9 10 11]]

# x: (1, 7)
[[0 1 2 3 4 5 6]]

# y: (6, 1)
[[0]
 [1]
 [2]
 [3]
 [4]
 [5]]

# x_edges
[-0.5  0.5  1.5  2.5  3.5  4.5  5.5  6.5]
# y_edges
[-0.5  0.5  1.5  2.5  3.5  4.5  5.5]

pcolorfast.py

import numpy as np
from matplotlib import pyplot, colors, cm
from mpl_toolkits.axes_grid1 import make_axes_locatable

def corners(centers):
    """
    Given a 1d array of center positions, compute the positions of the edges
    between them.
    """
    lengths = np.diff(centers)
    inside_corners = centers[:-1] + lengths / 2
    leftmost_corner = centers[0] - lengths[0] / 2
    rightmost_corner = centers[-1] + lengths[-1] / 2
    c = np.insert(inside_corners, 0, leftmost_corner)
    corners = np.append(c, rightmost_corner)

    return corners


def main():
    left = -0.5
    bottom = -0.5
    right = 6.5
    top = 5.5

    y, x = np.ogrid[
        int(bottom + 0.5) : int(top + 0.5), int(left + 0.5) : int(right + 0.5)
    ]
    data = x + y

    x_edges = corners(np.array([0, 1, 2, 3, 4, 5, 6]))
    y_edges = corners(np.array([0, 1, 2, 3, 4, 5]))

    fig, ax = pyplot.subplots()
    img = ax.pcolormesh(
        x_edges,
        y_edges,
        data,
        norm=colors.Normalize(vmin=data.min(), vmax=data.max()),
        cmap=cm.get_cmap("cividis"),
        edgecolor="black",
    )
    divider = make_axes_locatable(ax)
    cax = divider.append_axes("right", size="4%", pad=0.02)
    cbar = ax.figure.colorbar(
        img,
        cax=cax,
    )
    cbar.set_label(r"data ($\mathrm{\#}$)")

    ax.set_xlabel(r"$x$ ($\mathrm{\#}$)")
    ax.set_ylabel(r"$y$ ($\mathrm{\#}$)")

    fig.savefig("pcolorfast.png")
    pyplot.close(fig)


if __name__ == "__main__":
    main()