import numpy as np

# The first two lines of the A matrix represent the coordinates of each rotor in the X,Y plane,
# and the third line the direction in which they spin.
# Note that in this example the X axis is vertical, and the Y coordinates are in the top row of A.
A = np.array([[-0.17,  0.17, -0.25,  0.25, -0.33,  0.33],
             [-0.35, -0.35,  0.,    0.,    0.35,  0.35],
             [-0.1,   0.1,   0.1,  -0.1,  -0.1,   0.1 ]])

# Moore-Penrose pseudoinverse of A
B = np.linalg.pinv(A)
# normalizing columns of B and transpose
B_normalized = (B.T / B.max(axis=0)[:, np.newaxis])

# scale and round to 256 to return final coefficients
coeffs = np.around(256 * B_normalized).astype(int)
print(coeffs)

# output defines
import string
rows = ['ROLL_COEF"  ', 'PITCH_COEF" ', 'YAW_COEF"   ']
for i, r in enumerate(rows):
    print('<define name="' + r + 'value="{' + string.join(['{:>4d}'.format(c) for c in coeffs[i]], ', ') + '}"/>')