MATLAB to Python Converter

% MATLAB matrix operations (1-based indexing)
A = [1 2 3; 4 5 6; 7 8 9];
B = [2 0 1; 1 3 2; 0 1 4];

% Element-wise operations
C = A .* B;  % Element-wise multiplication
D = A ./ B;  % Element-wise division

% Matrix multiplication
E = A * B;

% Indexing (1-based)
first_element = A(1, 1);
last_row = A(3, :);
column_sum = sum(A(:, 2));

% Vectorized operations
squared = A.^2;
result = sqrt(sum(squared, 2));  % Row-wise sum then sqrt

disp('First element:');
disp(first_element);

import numpy as np

# Python matrix operations (0-based indexing)
A = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
B = np.array([[2, 0, 1], [1, 3, 2], [0, 1, 4]])

# Element-wise operations (no dot needed)
C = A * B  # Element-wise multiplication
D = A / B  # Element-wise division

# Matrix multiplication (use @ operator)
E = A @ B

# Indexing (0-based)
first_element = A[0, 0]
last_row = A[2, :]
column_sum = np.sum(A[:, 1])

# Vectorized operations
squared = A ** 2
result = np.sqrt(np.sum(squared, axis=1))  # Row-wise sum then sqrt

print('First element:')
print(first_element)

% MATLAB plotting
x = linspace(0, 2*pi, 100);
y1 = sin(x);
y2 = cos(x);

% Create figure with subplots
figure;

% First subplot
subplot(2, 1, 1);
plot(x, y1, 'b-', 'LineWidth', 2);
title('Sine Wave');
xlabel('x');
ylabel('sin(x)');
grid on;

% Second subplot
subplot(2, 1, 2);
plot(x, y2, 'r--', 'LineWidth', 2);
title('Cosine Wave');
xlabel('x');
ylabel('cos(x)');
grid on;
legend('cos(x)');

% Save figure
saveas(gcf, 'waves.png');

import numpy as np
import matplotlib.pyplot as plt

# Python plotting with Matplotlib
x = np.linspace(0, 2*np.pi, 100)
y1 = np.sin(x)
y2 = np.cos(x)

# Create figure with subplots
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))

# First subplot
ax1.plot(x, y1, 'b-', linewidth=2)
ax1.set_title('Sine Wave')
ax1.set_xlabel('x')
ax1.set_ylabel('sin(x)')
ax1.grid(True)

# Second subplot
ax2.plot(x, y2, 'r--', linewidth=2)
ax2.set_title('Cosine Wave')
ax2.set_xlabel('x')
ax2.set_ylabel('cos(x)')
ax2.grid(True)
ax2.legend(['cos(x)'])

# Adjust layout and save
plt.tight_layout()
plt.savefig('waves.png', dpi=300)
plt.show()