Hi, I can't help you with the first issues, but the display has nothing to do with the quality of the computation. Numpy only prints a part of a float value, but fir the computations, it obviously uses the correct value. All this can be parametrized by using set_printoptions().
Matthieu 2008/9/3, Hanni Ali <[EMAIL PROTECTED]>: > Hi, > > I have encountered a worrying problem, during migration of software from > numarray to numpy, perhaps someone could help me determine how this could be > addressed. > > I have a large array or values 10000 long 12 items per line. The matrix > contains floats, dtype=float32 in numpy and type=Float32 in numarray. > > When I perform a mean of one of the columns we observe a discrepancies in > the output values. > > numarray: > >>> port_result.agg_matrix._array[::,2].mean() > 193955925.49500328 > > numpy: > > >>> port_result.agg_matrix._array[::,2].mean() > 193954536.48896 > > If we examine a specific line in the matrix the arrays appear identical: > > numarray: > >>> port_result.agg_matrix[0] > array([ 2.11549568e+08, 4.03735232e+08, 8.47466400e+07, > 3.99625600e+07, 7.99853550e+06, 6.68247100e+06, > 0.00000000e+00, 1.00018790e+07, 3.43065200e+07, > 1.75261240e+07, 4.89246450e+06, 2.06562788e+06], type=Float32) > > numpy: > >>> port_result.agg_matrix[0] > array([ 2.11549568e+08, 4.03735232e+08, 8.47466400e+07, > 3.99625600e+07, 7.99853550e+06, 6.68247100e+06, > 0.00000000e+00, 1.00018790e+07, 3.43065200e+07, > 1.75261240e+07, 4.89246450e+06, 2.06562788e+06], dtype=float32) > > However when examining a specific item numpy appears to report a value to 8 > significant figures regardless of the true value, whereas numarray reported > the full value, however if I cast the output as a float the full value is > present, just not being output. Could this explain the difference in the > mean values? How can I get numpy to always provide the exact value in the > array, so behave in the same manner as numarray? > > numarray: > >>> port_result.agg_matrix[0][4] > 7998535.5 > >>> port_result.agg_matrix[0][11] > 2065627.875 > > numpy: > >>> port_result.agg_matrix[0][4] > 7998535.5 > >>> port_result.agg_matrix[0][11] > 2065627.9 > >>> float(port_result.agg_matrix[0][4]) > 7998535.5 > >>> float(port_result.agg_matrix[0][11]) > 2065627.875 > > I appreciate any help anyone can give, thank you. > > Hanni > > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > > -- French PhD student Information System Engineer Website: http://matthieu-brucher.developpez.com/ Blogs: http://matt.eifelle.com and http://blog.developpez.com/?blog=92 LinkedIn: http://www.linkedin.com/in/matthieubrucher _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
