FAOD-DUI5/grand_carre.py

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Python
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"""
"""
from random import random
import matplotlib.pyplot as plt
import numpy as np
def generate_grid(proportion, n, m=0):
"""Generate a grid nxm with random 1 (with proportion) or 0"""
if m == 0:
m = n
return [[int(random() < proportion) for _ in range(m)] for _ in range(n)]
def trim_axs(axs, N):
"""
Reduce *axs* to *N* Axes. All further Axes are removed from the figure.
"""
axs = axs.flat
for ax in axs[N:]:
ax.remove()
return axs[:N]
def draw_image(grid, ax):
hight = len(grid)
lenght = len(grid[0])
ax.tick_params(left=False, bottom=False, labelleft=False, labelbottom=False)
ax.imshow(grid, cmap="binary")
ax.hlines(
y=np.arange(0, hight) + 0.5,
xmin=np.full(lenght, 0) - 0.5,
xmax=np.full(lenght, hight) - 0.5,
color="gray",
)
ax.vlines(
x=np.arange(0, lenght) + 0.5,
ymin=np.full(lenght, 0) - 0.5,
ymax=np.full(lenght, hight) - 0.5,
color="gray",
)
return ax
def grid_to_image(grids, filename):
""" """
plt.clf()
n_cols = 3
n_rows = len(grids) // 3
axs = plt.figure(constrained_layout=True).subplots(n_rows, n_cols)
axs = trim_axs(axs, len(grids))
for ax, grid in zip(axs, grids):
draw_image(grid, ax)
plt.savefig(filename)
if __name__ == "__main__":
specs = [
{"proportion": 0.2, "n": 5},
{"proportion": 0.3, "n": 5},
{"proportion": 0.2, "n": 8},
{"proportion": 0.3, "n": 8},
{"proportion": 0.2, "n": 10},
{"proportion": 0.3, "n": 10},
]
grids = [generate_grid(**spec) for spec in specs]
grid_to_image(grids, "grids.pdf")