Can I do a mathematical-shape mask for a (Nx,Ny) matrix?

I have a matrix of numbers (Nx,Ny) and I would like to select from that matrix a mathematical shape coordinates/components as it could be a line with a given slope.

I learned how to create a mask and how to do it in a random way but I cannot think of how to generate a mathematical-shape mask in python.

This is some of the code that I've been able to develop. If you know a better way to do this I will be also grateful of being told.

import random
import numpy as np

threshold = 0.85 
radius=40 
sq7=1/(radius*radius)

matrix=np.zeros((Nx,Ny))

for i in range(0,Nx):
    for j in range(0,Ny):
        if ((i-Nx*0.5)*(i-Nx*0.5)*sq7+(j-Ny*0.5)*(j-Ny*0.5)*sq7<=1.0):
            matrix[i,j]= 1.0 - 0.1*random.random();
        else:
            matrix[i,j]=-1.0 + random.random();

randoms = np.random.normal(0,scale=0.002, size=matrix[mask].shape)
mask = matrix**2 < threshold
matrix[mask] += randoms * (1 - matrix[mask]**2)

At the end I found a very easy way of doing so. What I just did was to create a new matrix of the same dimensions as the one that I want to mask and then just by going through the matrix itself and comparing with the values of my function I could do it so easily. I will leave the code here.

def func_normaldist(x,Ny):
    y = np.exp(-0.5*(x-int(Ny/2))**2)/np.sqrt(np.pi*2.)
    return y

def mask_uvalues_centered_geometry(Nx, Ny): #u 
    mask = np.zeros((Nx,Ny))
    # Initial configuration: rectangle of Nx x Ny
    for j in range(0,Ny):
        for i in range(0,Nx):
            if (i < Ny*Nx*func_normaldist(j,Ny)):# and (i > int(Nx/2 + 1)):
                mask[j,i] = True

            else:
                mask[j,i] = False;
    return mask
Nx = 50
Ny = 50
a = mask_uvalues_centered_geometry(Nx,Ny)
print(a)