On 07 Jul 2017, at 4:24 PM, paul.carr...@free.fr wrote:
>
> ps : I'd like to use the following code that is much more familiar for me :-)
>
> COMP_list = np.asarray(COMP_list, dtype = np.float64)
> i = np.arange(1,NumberOfRecords,2)
> COMP_list = np.delete(COMP_list,i)
>
Not sure about the
Hi (all)
Ounce again I would like to thanks the community for the supports.
I progressing in moving my code to Python ..
In my mind some parts remains quite hugly (and burns me the eyes), but
it works and I'll optimized it in the future ; so far I can work with
the data in a single reading
On 7 Jul 2017, at 1:59 am, Chris Barker wrote:
>
> On Thu, Jul 6, 2017 at 10:55 AM, wrote:
> It's is just a reflexion, but for huge files one solution might be to
> split/write/build first the array in a dedicated file (2x o(n) iterations -
> one
On Thu, Jul 6, 2017 at 10:55 AM, wrote:
>
> It's is just a reflexion, but for huge files one solution might be to
> split/write/build first the array in a dedicated file (2x o(n) iterations -
> one to identify the blocks size - additional one to get and write), and
> then to
OK, you have two performance "issues"
1) memory use: IF yu need to read a file to build a numpy array, and dont
know how big it is when you start, you need to accumulate the values
first, and then make an array out of them. And numpy arrays are fixed size,
so they can not efficiently accumulate
Thanks Rober for your effort - I'll have a look on it
... the goal is be guide in how to proceed (and to understand), and not
to have a "ready-made solution" ... but I appreciate honnestly :-)
Paul
Le 2017-07-06 11:51, Robert Kern a écrit :
> On Thu, Jul 6, 2017 at 1:49 AM,
On Thu, Jul 6, 2017 at 1:49 AM, wrote:
>
> Dear All
>
> First of all thanks for the answers and the information’s (I’ll ding into
it) and let me trying to add comments on what I want to :
>
> My asci file mainly contains data (float and int) in a single column
> (it is not
Dear All
First of all thanks for the answers and the information's (I'll ding
into it) and let me trying to add comments on what I want to :
* My asci file mainly contains data (float and int) in a single column
* (it is not always the case but I can easily manage it - as well I
While I'm going to bet that the fastest way to build a ndarray from ascii
is with a 'io.ByteIO` stream, NumPy does have a function to load from text,
`numpy.loadtxt` that works well enough for most purposes.
https://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
It's hard to
Hi Paul,
> ascii file is an input format (and the only one I can deal with)
>
> HDF5 one might be an export one (it's one of the options) in order to speed
> up the post-processing stage
>
>
>
> Paul
>
>
>
>
>
> Le 2017-07-05 20:19, Thomas Caswell a écrit :
>
>> Are you tied to ASCII
On Wed, Jul 5, 2017 at 5:41 AM, wrote:
>
> Dear all
>
> I’m sorry if my question is too basic (not fully in relation to Numpy –
while it is to build matrices and to work with Numpy afterward), but I’m
spending a lot of time and effort to find a way to record data from an
Hi
Thanks for the answer:
ascii file is an input format (and the only one I can deal with)
HDF5 one might be an export one (it's one of the options) in order to
speed up the post-processing stage
Paul
Le 2017-07-05 20:19, Thomas Caswell a écrit :
> Are you tied to ASCII files? HDF5
Are you tied to ASCII files? HDF5 (via h5py or pytables) might be a
better storage format for what you are describing.
Tom
On Wed, Jul 5, 2017 at 8:42 AM wrote:
> Dear all
>
>
> I’m sorry if my question is too basic (not fully in relation to Numpy –
> while it is to
Dear all
I'm sorry if my question is too basic (not fully in relation to Numpy -
while it is to build matrices and to work with Numpy afterward), but I'm
spending a lot of time and effort to find a way to record data from an
asci while, and reassign it into a matrix/array … with unsuccessfully!
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