On Sat, Apr 28, 2012 at 11:18 AM, Charles R Harris <[email protected]> wrote: > > > On Sat, Apr 28, 2012 at 9:13 AM, Wes McKinney <[email protected]> wrote: >> >> On Fri, Apr 27, 2012 at 4:57 PM, Robert Kern <[email protected]> >> wrote: >> > On Fri, Apr 27, 2012 at 21:52, Travis Vaught <[email protected]> wrote: >> >> With NumPy 1.6.1 (from EPD 7.2-2) I get this behavior: >> >> >> >> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >> >> >> >> In [1]: import numpy as np >> >> >> >> In [2]: schema = np.dtype({'names':['symbol', 'date', 'open', 'high', >> >> 'low', >> >> ...: 'close', 'volume', 'adjclose'], >> >> ...: 'formats':['S8', 'M8', float, float, float, >> >> float, >> >> ...: float, float]}) >> >> >> >> In [3]: data = [("AAPL", "2012-04-12", 600.0, 605.0, 598.0, 602.0, >> >> 50000000, >> >> 602.0),] >> >> >> >> In [4]: recdata = np.array(data, dtype=schema) >> >> >> >> In [5]: recdata >> >> Out[5]: >> >> array([ ('AAPL', datetime.datetime(2012, 4, 12, 0, 0), 600.0, 605.0, >> >> 598.0, >> >> 602.0, 50000000.0, 602.0)], >> >> dtype=[('symbol', '|S8'), ('date', ('<M8[us]', {})), ('open', >> >> '<f8'), >> >> ('high', '<f8'), ('low', '<f8'), ('close', '<f8'), ('volume', '<f8'), >> >> ('adjclose', '<f8')]) >> >> >> >> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >> >> >> >> >> >> With numpy-1.7.0.dev_3cb783e I get this: >> >> >> >>>>> import numpy as np >> >> >> >>>>> schema = >> >>>>> >> >>>>> np.dtype({'names':['symbol','data','open','high','low','close','volume','adjclose'], >> >>>>> 'formats':['S8','M8',float,float,float,float,float,float]}) >> >> >> >>>>> data = [("AAPL", "2012-04-12", 600.0, 605.0, 598.0, 602.0, >> >>>>> 50000000, >> >>>>> 602.0),] >> >> >> >>>>> recdata = np.array(data, dtype=schema) >> >> Traceback (most recent call last): >> >> File "<stdin>", line 1, in <module> >> >> ValueError: Cannot create a NumPy datetime other than NaT with generic >> >> units >> >> >> >>>>> np.version.version >> >> '1.7.0.dev-3cb783e' >> >> >> >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ >> >> >> >> Any hints about a regression I can check for? Or perhaps I missed an >> >> api >> >> change for specifying datetime dtypes? >> > >> > Judging from the error message, it looks like an intentional API change. >> > >> > -- >> > Robert Kern >> > _______________________________________________ >> > NumPy-Discussion mailing list >> > [email protected] >> > http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> Maybe this should be raised as a bug (where do we report NumPy bugs >> these days, still Trac?). As I'm moving to datetime64 in pandas if >> NumPy 1.6.1 data has unpickling issues on NumPy 1.7+ it's going to be >> very problematic. > > > I was wondering what datetime you were using since the version in 1.6 had > issues. Have you tested with both? > > Chuck > > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
Could you define issues? I haven't had a chance to make the library compatible with both 1.6.1 and 1.7.0 yet (like Travis I'm using NumPy 1.6.1 from EPD); it's important though as pandas will be the first widely used library I know of that will make heavy use of datetime64. - Wes _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
