I was writing code to do bootstrapping on a set of data. I wanted a test case where if I asked for one bootstrap I would be returned the original data. lambdas and function references saved me from inefficient code. if bootstraps == 1 : srri = lambda low , high , size : range ( size ) else : srri = scipy . random . random_integers for boot in range ( bootstraps ): for r in range ( n1 ): for c in range ( n0 ): sample_size = trial_result [ r ][ c ] . size choices = srri ( 0 , sample_size - 1 , sample_size ) meas_grid [ r , c ] = pylab . array ( trial_result [ r ][ c ][ choices ], dtype = float ) . mean () model_grid [:,:,:, boot ], params [:, boot ] = \ process_grid ( s0 , s1 , meas_grid ) Instead of srri = scipy . random . random_integers if bootstraps == 1 : for r in range ( n1 ): for c in range ( n0 ): meas_grid [ r , c ] = pylab . array ( trial_result [ r ][ c ], dtype = float ) . mean () model_grid [:,:,:, boot ...
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