Hi,
mlab.defaultformatd sets the default float formatter for rec2csv() to be something that doesn't keep the full representation of a floating point number. Obviously, I can pass in my own formatd argument to rec2csv(), but I wonder if there's any reason why defaultformatd shouldn't use repr() for numpy.float32 and numpy.float64?
+1 for repr() in general as the default output method, as it is
supposed (though not guaranteed) in general to be more faithful to the
original object.
cheers,
f
On Dec 15, 2007 2:13 PM, Andrew Straw <strawman@...36...> wrote:
Hi,
mlab.defaultformatd sets the default float formatter for rec2csv() to be
something that doesn't keep the full representation of a floating point
number. Obviously, I can pass in my own formatd argument to rec2csv(),
but I wonder if there's any reason why defaultformatd shouldn't use
repr() for numpy.float32 and numpy.float64?
I'll be happy to make repr the default. I was using %g because I
mistakenly though this provided the appropriate number of significant
digits. I changed this to %r in the csvformat_factory in svn.
JDJ
On Dec 15, 2007 3:13 PM, Andrew Straw <strawman@...36...> wrote:
mlab.defaultformatd sets the default float formatter for rec2csv() to be
something that doesn't keep the full representation of a floating point
number. Obviously, I can pass in my own formatd argument to rec2csv(),
but I wonder if there's any reason why defaultformatd shouldn't use
repr() for numpy.float32 and numpy.float64?
Hang on a minute, it looks like numpy.float64.__repr__() itself isn't reproducing all significant digits... I'm writing up a test now and will move this to the numpy list. I'm not sure how much is MPL and how much is numpy at this point.
Trying to make a roundtrip through a .csv file not loose precision,
Andrew
John Hunter wrote:
On Dec 15, 2007 3:13 PM, Andrew Straw <strawman@...36...> wrote:
mlab.defaultformatd sets the default float formatter for rec2csv() to be
something that doesn't keep the full representation of a floating point
number. Obviously, I can pass in my own formatd argument to rec2csv(),
but I wonder if there's any reason why defaultformatd shouldn't use
repr() for numpy.float32 and numpy.float64?
I'll be happy to make repr the default. I was using %g because I
mistakenly though this provided the appropriate number of significant
digits. I changed this to %r in the csvformat_factory in svn.JDJ
you may want to ping also at #scipy on irc.freenode.net, where the
sprint participants are all hanging out.
cheers,
f
On Dec 15, 2007 2:52 PM, Andrew Straw <strawman@...36...> wrote:
Hang on a minute, it looks like numpy.float64.__repr__() itself isn't
reproducing all significant digits... I'm writing up a test now and will
move this to the numpy list. I'm not sure how much is MPL and how much
is numpy at this point.
OK, I created a test for numpy to isolate an issue: http://scipy.org/scipy/numpy/ticket/629
I think setting MPL's behavior to repr() is good, though. John, I see you did that r4745 -- thanks.
-Andrew
Fernando Perez wrote:
On Dec 15, 2007 2:52 PM, Andrew Straw <strawman@...36...> wrote:
Hang on a minute, it looks like numpy.float64.__repr__() itself isn't
reproducing all significant digits... I'm writing up a test now and will
move this to the numpy list. I'm not sure how much is MPL and how much
is numpy at this point.you may want to ping also at #scipy on irc.freenode.net, where the
sprint participants are all hanging out.cheers,
f
OK, I added unit/mlab_unit.py to svn. This checks that double precision floats can round-trip through rec2csv and csv2rec. To pass requires not only svn matplotlib (due to John's change), but also svn numpy (to be included with 1.0.5).
Also, it doesn't seem to me that rec2csv should close a file handle passed to it. This prevents use with StringIO, for example. So, I added a test for that, too. John, if it's not going to break anything for you, I'll go ahead and fix that.
John Hunter wrote:
On Dec 15, 2007 3:13 PM, Andrew Straw <strawman@...36...> wrote:
mlab.defaultformatd sets the default float formatter for rec2csv() to be
something that doesn't keep the full representation of a floating point
number. Obviously, I can pass in my own formatd argument to rec2csv(),
but I wonder if there's any reason why defaultformatd shouldn't use
repr() for numpy.float32 and numpy.float64?
I'll be happy to make repr the default. I was using %g because I
mistakenly though this provided the appropriate number of significant
digits. I changed this to %r in the csvformat_factory in svn.JDJ
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Yes, please do. You might want to modify cbook.to_filehandle to
optionally return a tuple specifying whether the returned fh is owned
by the caller. Something like:
fh, owner = cbook.to_filehandle(fname, returnowner=True)
and then later
if owner:
fh.close()
JDH
On Dec 16, 2007 1:33 PM, Andrew Straw <strawman@...36...> wrote:
OK, I added unit/mlab_unit.py to svn. This checks that double precision
floats can round-trip through rec2csv and csv2rec. To pass requires not
only svn matplotlib (due to John's change), but also svn numpy (to be
included with 1.0.5).Also, it doesn't seem to me that rec2csv should close a file handle
passed to it. This prevents use with StringIO, for example. So, I added
a test for that, too. John, if it's not going to break anything for you,
I'll go ahead and fix that.
Done in r4748. I added the kwarg "return_opened" to cbook.to_filehandle().
John Hunter wrote:
On Dec 16, 2007 1:33 PM, Andrew Straw <strawman@...36...> wrote:
OK, I added unit/mlab_unit.py to svn. This checks that double precision
floats can round-trip through rec2csv and csv2rec. To pass requires not
only svn matplotlib (due to John's change), but also svn numpy (to be
included with 1.0.5).Also, it doesn't seem to me that rec2csv should close a file handle
passed to it. This prevents use with StringIO, for example. So, I added
a test for that, too. John, if it's not going to break anything for you,
I'll go ahead and fix that.Yes, please do. You might want to modify cbook.to_filehandle to
optionally return a tuple specifying whether the returned fh is owned
by the caller. Something like:fh, owner = cbook.to_filehandle(fname, returnowner=True)
and then later
if owner:
fh.close()JDH
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