[Python] Matplotlib Makes Trippy Incorrect plots

I fill a numpy array with 0 or 1 depending if a computed array indexed value is more or less than a given value. This results in an array of zeros and ones. Matplotlib doesnt think so

The comparison is computed d=sin(bpi/180)x+sin(api/180)cos(bpi180)*y

The unique statement prints " unique values in space [0. 1.]"

Last image shows same code with True/False array instead of 0/1

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
tan=np.tan
sin=np.sin
cos=np.cos
pi=np.pi
x=4
y=3
Max=.3

sizeOfSpace=2000
alpha=np.linspace(-10, 10,sizeOfSpace)
beta=np.linspace(-10, 10,sizeOfSpace)

space=np.zeros((sizeOfSpace,sizeOfSpace))
for i,a in enumerate(alpha):
for j,b in enumerate(beta):
d=sin(b*pi/180)*x+sin(a*pi/180)*cos(b*pi*180)*y
space[i,j]=int(0) if d<Max else int(1)
plt.imshow(space,cmap=plt.cm.gray)
plt.colorbar()
print(f'unique valeus in space {np.unique(space)}')








Any suggestions how to make the binary image?

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