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SciPy / Optimization

constraints in minimize()

Learn constraints in minimize() in SciPy with a dedicated explanation, a concept-specific example, practical cautions, and a mastery check.

12 min read • Beginner

scipy-003.py

python

from scipy.optimize import minimize

def f(x): return x[0]**2+x[1]**2
constraint={'type':'eq','fun':lambda x:x[0]+x[1]-1}
print(minimize(f,[0.5,0.5],constraints=[constraint]).x)

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constraints in minimize() Mastery Check →

bounds in optimization

least_squares()