Re: [Numpy-discussion] annoying numpy string to float conversion behaviour

[David M. Cooke]

On Jun 20, 2007, at 04:35 , Torgil Svensson wrote:

Hi

Is there a reason for numpy.float not to convert it's own string
representation correctly?

numpy.float is the Python float type, so there's nothing we can do. I am working on adding NaN and Inf support for numpy dtypes, though, so that, for instance, numpy.float64('-1.#IND') would work as expected. I'll put it higher on my priority list :-)

Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit
(Intel)] on win32>>> import numpy

numpy.__version__

'1.0.3'

numpy.float("1.0")

1.0

numpy.nan

-1.#IND

numpy.float("-1.#IND")

Traceback (most recent call last):
 File "<pyshell#20>", line 1, in <module>
   numpy.float("-1.#IND")
ValueError: invalid literal for float(): -1.#IND

Also, nan and -nan are represented differently for different float to
string conversion methods. I guess the added zeros are a bug
somewhere.

str(nan)

'-1.#IND'

"%f" % nan

'-1.#IND00'

str(-nan)

'1.#QNAN'

"%f" % -nan

'1.#QNAN0'

This is a problem when floats are stored in text-files that are later
read to be numerically processed. For now I use the following to
convert the number.

special_numbers=dict([('-1.#INF',-inf),('1.#INF',inf),
                      ('-1.#IND',nan),('-1.#IND00',nan),
                      ('1.#QNAN',-nan),('1.#QNAN0',-nan)])
def string_to_number(x):
   if x in special_numbers:
       return special_numbers[x]
   return float(x) if ("." in x) or ("e" in x) else int(x)

Is there a simpler way that I missed?

Best Regards,

//Torgil
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