Clipping, casting, and maximum values
#! /usr/bin/env python import numarray from numarray.numerictypes import * # Is this program too complicated? # On my machine (AMD64 chip, Debian unstable i386, numarray 1.5.0): # float(2**63-1) == float(2**63) def clipcast(farr): if farr.type() != Float64: raise TypeError('input must be a Float64 array') farr = numarray.clip(farr, 0.0, float(2**63)) print 'L13 %30.4f' % farr[0] top = (farr == float(2**63)) numarray.Error.pushMode(invalid='ignore') arr = farr.astype(Int64) numarray.Error.popMode() return numarray.where(top, 2**63-1, arr) farr = numarray.array([1.0e300], Float64) print farr.type(), farr[0] arr = clipcast(farr) print arr.type(), arr[0]
On my machine running FC4 x86_64, I get: Float64 1e+300 L13 9223372036854775808.0000 Int64 9223372036854775807 What are you getting? What did you expect to get? At 19 digits, the numbers we're talking about are outside the precision of Float64 which is ~16 digits. I did see one (for me) surprise:
farr = numarray.clip(farr, 0.0, float(2**63)) farr array([ 9.22337204e+18]) numarray.Error.pushMode(invalid='ignore') arr = farr.astype(Int64) numarray.Error.popMode() arr array([-9223372036854775808])
Removing the Error suppression, I also got: Warning: Encountered invalid numeric result(s) during type conversion That makes it (for me) much less surprising: since you can't stuff 2**63 into Int64, there is no right answer for the astype(). Everything else looked OK to me on Fedora Core 4. Regards, Todd Edward C. Jones wrote:
#! /usr/bin/env python
import numarray from numarray.numerictypes import *
# Is this program too complicated? # On my machine (AMD64 chip, Debian unstable i386, numarray 1.5.0): # float(2**63-1) == float(2**63) def clipcast(farr): if farr.type() != Float64: raise TypeError('input must be a Float64 array') farr = numarray.clip(farr, 0.0, float(2**63)) print 'L13 %30.4f' % farr[0] top = (farr == float(2**63)) numarray.Error.pushMode(invalid='ignore') arr = farr.astype(Int64) numarray.Error.popMode() return numarray.where(top, 2**63-1, arr)
farr = numarray.array([1.0e300], Float64) print farr.type(), farr[0] arr = clipcast(farr) print arr.type(), arr[0]
------------------------------------------------------- This SF.net email is sponsored by: Splunk Inc. Do you grep through log files for problems? Stop! Download the new AJAX search engine that makes searching your log files as easy as surfing the web. DOWNLOAD SPLUNK! http://ads.osdn.com/?ad_id=7637&alloc_id=16865&op=click _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
participants (2)
-
Edward C. Jones -
Todd Miller