Python scipy.optimize Module

This page shows the popular functions and classes defined in the scipy.optimize module. The items are ordered by their popularity in 40,000 open source Python projects. If you can not find a good example below, you can try the search function to search modules.

• 1. minimize()    
  Used in 273 projects
• 2. curve_fit()    
  Used in 93 projects
• 3. linear_sum_assignment()    
  Used in 64 projects
• 4. fmin_l_bfgs_b()    
  Used in 63 projects
• 5. brentq()    
  Used in 54 projects
• 6. fsolve()    
  Used in 44 projects
• 7. fmin()    
  Used in 43 projects
• 8. leastsq()    
  Used in 43 projects
• 9. minimize_scalar()    
  Used in 40 projects
• 10. least_squares()    
  Used in 33 projects
• 11. newton()    
  Used in 26 projects
• 12. OptimizeResult()    
  Used in 24 projects
• 13. fmin_bfgs()    
  Used in 24 projects
• 14. nnls()    
  Used in 24 projects
• 15. root()    
  Used in 23 projects
• 16. fminbound()    
  Used in 21 projects
• 17. approx_fprime()    
  Used in 21 projects
• 18. linprog()    
  Used in 18 projects
• 19. differential_evolution()    
  Used in 18 projects
• 20. basinhopping()    
  Used in 18 projects
• 21. check_grad()    
  Used in 17 projects
• 22. bisect()    
  Used in 17 projects
• 23. fmin_cg()    
  Used in 14 projects
• 24. brute()    
  Used in 13 projects
• 25. brent()    
  Used in 12 projects
• 26. fmin_slsqp()    
  Used in 12 projects
• 27. fmin_powell()    
  Used in 10 projects
• 28. rosen()    
  Used in 8 projects
• 29. fmin_cobyla()    
  Used in 8 projects
• 30. newton_krylov()    
  Used in 8 projects
• 31. fmin_tnc()    
  Used in 8 projects
• 32. rosen_der()    
  Used in 6 projects
• 33. golden()    
  Used in 6 projects
• 34. brenth()    
  Used in 6 projects
• 35. OptimizeWarning()    
  Used in 6 projects
• 36. fmin_ncg()    
  Used in 5 projects