How do i go about seperating my numerical data into fuzzy sections and putting it into code in Python ?

Question

My inputs X1 and X2 are the values from -12 and 12 including 0 (i.e:(-12,-11,-10,-9,-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8,9,10,11,12) for both X1 and X2 and my output y is the function y=(2*(X1^2))+(X2^2),. In my code I got the values for y as [432 363 300 243 192 147 108 75 48 27 12 3 0 3 12 27 48 75 108 147 192 243 300 363 432]

Answer 1

import numpy as np

# Define the function y = (2 * (X1^2)) + (X2^2)

def compute_y(X1, X2):

return 2 * (X1**2) + (X2**2)

# Generate all combinations of X1 and X2 values from -12 to 12

X1_values = np.arange(-12, 13)

X2_values = np.arange(-12, 13)

# Compute y for all combinations of X1 and X2

y_values = np.array([[compute_y(x1, x2) for x1 in X1_values] for x2 in X2_values])

# Flatten y_values into a 1D array

y_flat = y_values.flatten()

# Define bins for y

bins = [0, 50, 100, 150, 200, 250, 300, 350, 400, 450]

# Initialize counts for each bin

bin_counts = [0] * (len(bins) - 1)

# Count how many values fall into each bin

for value in y_flat:

for i in range(len(bins) - 1):

if bins[i] <= value < bins[i + 1]:

bin_counts[i] += 1

break

# Print the counts for each bin

for i in range(len(bins) - 1):

print(f"Values in bin [{bins[i]}, {bins[i + 1]}): {bin_counts[i]}")

Answer 2

for loops and dictionaries are your best friends in the world

 

#declare y as a dictionary to allow for negative indexing
y = {}

#calculate all y
for x1 in range(-12,13):
    #add a new dictionary to the main dictionary at the key of x1's current value to allow multidimensional space
    y[x1] = {}
    for x2 in range(-12,13):
        y[x1][x2] = 2*x1*x1 + x2*x2

#print all y (could be done in line with calculation for efficiency but done separately for understanding
for x1 in range(-12, 13):
    for x2 in range(-12,13):
        print "y[%d][%d] = %d" %(x1, x2, y[x1][x2])