Sebastian Haase wrote: > On Friday 18 August 2006 15:25, Travis Oliphant wrote: > >> Sebastian Haase wrote: >> >>> On Friday 18 August 2006 11:38, Travis Oliphant wrote: >>> >>>> Sebastian Haase wrote: >>>> >>>>> Hi, >>>>> array dtype descriptors have an attribute itemsize that gives the >>>>> total number of bytes required for an item of that dtype. >>>>> >>>>> Scalar types, like numy.int32, also have that attribute, >>>>> but it returns "something else" - don't know what: >>>>> >>>>> >>>>> Furthermore there are *lot's* of more attributes to a scalar dtype, >>>>> e.g. >>>>> >>>> The scalar types are actual Python types (classes) whereas the dtype >>>> objects are instances. >>>> >>>> The attributes you are seeing of the typeobject are very useful when you >>>> have an instance of that type. >>>> >>>> With numpy.int32.itemsize you are doing the equivalent of >>>> numpy.dtype.itemsize >>>> >>> but why then do I not get the result 4 ? >>> >> Because it's not a "class" attribute, it's an instance attribute. >> >> What does numpy.dtype.itemsize give you? >> >> > I'm really sorry for being so dumb - but HOW can I get then the number of > bytes needed by a given scalar type ? > > Ah, the real question. Sorry for not catching it earlier. I've been in "make sure this isn't a bug mode" for a long time.
If you have a scalar type you could create one and then check the itemsize: int32(0).itemsize Or you could look at the name and parse out how big it is. There is also a stored dictionary-like object that returns the number of bytes for any data-type recognized: numpy.nbytes[int32] -Travis ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
