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Problem Synopsis: When attempting to use the scipy.optimize.fmin_bfgs minimization (optimization) function, the function throws a derphi0 = np.dot(gfk, pk) ValueError: matrices are not aligned error. According to my error checking this occurs at the very end of the first iteration through fmin_bfgs--just before any values are returned or any calls to callback. Configuration: Windows Vista Python 3.2.2 SciPy 0.10 IDE = Eclipse with PyDev Detailed Description: I am using the scipy.optimize.fmin_bfgs to minimize the cost of a simple logistic regression implementation (converting from Octave to Python/SciPy). Basically, the cost function is named cost_arr function and the gradient descent is in gradient_descent_arr function. I have manually tested and fully verified that *cost_arr* and *gradient_descent_arr* work properly and return all values properly. I also tested to verify that the proper parameters are passed to the *fmin_bfgs* function. Nevertheless, when run, I get the ValueError: matrices are not aligned. According to the source review, the exact error occurs in the def line_search_wolfe1 function in # Minpack's Wolfe line and scalar searches as supplied by the scipy packages. Notably, if I use scipy.optimize.fmin instead, the fmin function runs to completion. Exact Error: File "D:\Users\Shannon\Programming\Eclipse\workspace\SBML\sbml\LogisticRegression.py", line 395, in fminunc_opt optcost = scipy.optimize.fmin_bfgs(self.cost_arr, initialtheta, fprime=self.gradient_descent_arr, args=myargs, maxiter=maxnumit, callback=self.callback_fmin_bfgs, retall=True) File "C:\Python32x32\lib\site-packages\scipy\optimize\optimize.py", line 533, in fmin_bfgs old_fval,o

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