[Numpy-discussion] Rounding errors in add.reduce?
Sue Giller
sag at hydrosphere.com
Thu Dec 6 12:30:19 CST 2001
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
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