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Because, using it offline you would want to work with a exhaustive .par file, but only request lines within a certain wavenumber range.
The problem is that, as far as I understand, the storage2cache() method loads the entire .par file.
(btw, the pos=None parameter is not even used in this method, so you could at least add
if pos:
for i in range(0, min([pos, line_count])):
InfileData.readline())
)
A lot of time would be saved by loading only lines within a certain wavenumber range (except maybe when the seeked range is at the end of the .par file).
I am not sure it is possible with the current code as it is, because lines are all read as strings, and then converted to numbers.
For this reason, I continue to use our former matlab code which is faster because it has this functionality, which is sad because I like Python better.
Am I the only one to needthis functionality?
tx
The text was updated successfully, but these errors were encountered:
jmmelko
changed the title
Partial loading of storage in cache
[FEATURE REQUEST] Partial loading in storage2cache()?
Nov 5, 2021
I think HAPI2 will include HDF5 support ; it would become very easy to only select specific waveranges.
If it can help : to improve performances in RADIS, we benchmarked a few HDF5 librairies to handle large line databases; and I'd definitly suggest to give a try to Vaex which proved extremelly efficient in our case (2nd link below) :
Hi,
HAPI is great, but not for offline usage.
Because, using it offline you would want to work with a exhaustive .par file, but only request lines within a certain wavenumber range.
The problem is that, as far as I understand, the storage2cache() method loads the entire .par file.
(btw, the pos=None parameter is not even used in this method, so you could at least add
)
A lot of time would be saved by loading only lines within a certain wavenumber range (except maybe when the seeked range is at the end of the .par file).
I am not sure it is possible with the current code as it is, because lines are all read as strings, and then converted to numbers.
For this reason, I continue to use our former matlab code which is faster because it has this functionality, which is sad because I like Python better.
Am I the only one to needthis functionality?
tx
The text was updated successfully, but these errors were encountered: