On Thu, June 25, 2009 7:59 pm, Mag Gam wrote:
> I am very new to NumPy and Python. We are doing some research in our
> Physics lab and we need to store massive amounts of data (100GB
> daily). I therefore, am going to use hdf5 and h5py. The problem is I
> am using np.loadtxt() to create my array an
2009/6/25 Mag Gam :
> Hello.
>
> I am very new to NumPy and Python. We are doing some research in our
> Physics lab and we need to store massive amounts of data (100GB
> daily). I therefore, am going to use hdf5 and h5py. The problem is I
> am using np.loadtxt() to create my array and create a data
Hello.
I am very new to NumPy and Python. We are doing some research in our
Physics lab and we need to store massive amounts of data (100GB
daily). I therefore, am going to use hdf5 and h5py. The problem is I
am using np.loadtxt() to create my array and create a dataset
according to that. np.loadt
This does not exactly answer your question, but you can use the dtype
string representation and positional parameter to make things nicer.
For example:
a = numpy.array( [1.0, 2.0, 3.0], 'f' )
instead of
a = numpy.array( [1.0, 2.0, 3.0], dtype=numpy.float32 )
-Geoff
On Jun 25, 2009, at 6:43
I'm trying to reduce the memory used in a calculation, so I'd like to
switch my program to float32 instead of float64. Is it possible to
change the numpy default float size, so I don't have to explicitly
state dtype=np.float32 everywhere?
Thanks,
John
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