import MA I have been using add.reduce on some arrays with single precision data in them. At some point, the reduction seems to be producing incorrect values, caused I presume by floating point rounding errors. THe values are correct if the same array is created as double precision. The odd things is that I can do a straight summing of those values into long, single or double variable and get correct answers. Is this a bug or what? If the difference is due to rounding error, I would expect the same errors to show up in the cases of summing the individual values. The output from the following code shows the following. Note that the add.reduce from the single precision array is different from all the others. It doesn't matter the rank or size of array, just so sum of values gets to certain size. accumulated sums float 75151440.0 long 75151440 accumulated from raveled array float 75151440.0 double 75151440.0 add.reduce single 75150288.0 double 75151440.0 --- code --- import MA # this causes same problem if array is 1d of [amax*bmax*cmax] in len amax = 4 bmax = 31 cmax = 12 farr = MA.zeros((amax, bmax, cmax), 'f') # single float darr = MA.zeros((amax, bmax, cmax), 'd') # double float sum = 0.0 lsum = 0 value = 50505 # reducing this can cause all values to agree for a in range (0, amax): for b in range (0, bmax): for c in range (0, cmax): farr[a, b, c] = value darr[a, b, c] = value sum = sum + value lsum = lsum + value fflat = MA.ravel(farr) dflat = MA.ravel(darr) fsum = dsum = 0.0 for value in fflat: fsum = fsum + value for value in dflat: dsum = dsum + value freduce = MA.add.reduce(fflat) dreduce = MA.add.reduce(dflat) print "accumulated sums" print "\tfloat\t", sum, "\tlong ", lsum print "accumulated from raveled array" print "\tfloat\t", fsum, "\tdouble", dsum print "add.reduce" print "\tsingle\t", freduce, "\tdouble", dreduce