optimize.fmin_cg fails when the function to be minimized returns a numpy scalar:

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from numpy import * from scipy import optimize f = lambda x: exp(x)-x df = lambda x: exp(x)-1.0 scipy.optimize.fmin(f, [0.2])

Traceback (most recent call last): File "<pyshell#4>", line 1, in <module> scipy.optimize.fmin(f, [0.2]) NameError: name 'scipy' is not defined

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optimize.fmin(f, [0.2]) Optimization terminated successfully. Current function value: 1.000000 Iterations: 15 Function evaluations: 30 array([ 3.88578059e-16]) optimize.fmin_cg(f, [0.2], df)

Traceback (most recent call last): File "<pyshell#6>", line 1, in <module> optimize.fmin_cg(f, [0.2], df) File "C:\Python25\Lib\site-packages\scipy\optimize\optimize.py", line 855, in fmin_cg old_fval_backup,old_old_fval_backup) File "C:\Python25\Lib\site-packages\scipy\optimize\optimize.py", line 471, in line_search phi0, derphi0, c1, c2) File "C:\Python25\Lib\site-packages\scipy\optimize\optimize.py", line 359, in zoom a_j = _cubicmin(a_lo, phi_lo, derphi_lo, a_hi, phi_hi, a_rec, phi_rec) File "C:\Python25\Lib\site-packages\scipy\optimize\optimize.py", line 309, in _cubicmin [A,B] = numpy.dot([[dc**2, -db**2],[-dc**3, db**3]],[fb-fa-C*db,fc-fa-C*dc]) ValueError: objects are not aligned # Here is the cure: Make f return a python float

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f = lambda x: float(exp(x)-x) optimize.fmin_cg(f, [0.2], df) Optimization terminated successfully. Current function value: 1.000000 Iterations: 2 Function evaluations: 14 Gradient evaluations: 8 array([ -8.15285339e-14])

I had this error with scipy 0.5.2 and scipy from svn. Nadav.