How to do multithreading for PyRate?
Closed this issue · 3 comments
Dear Expert,
I'm new in PyRate and after the first 10 million run with the mG model the ESS values are very small. I think at least 100 million runs with multiple replicates may give some satisfactory outome. However, the first 10 million runs took more than 65 hrs. Therefore, I wonder to know that is it possible to do multithreading of PyRate.
Thanks a bunch,
Debajyoti
Dear Sir,
Thank you very much for your kind response, however I did according to your suggestion and invoked the program using following command
python PyRate.py dip_pbdb_dataSSF_PyRate.py -A 2 -mG -j 1 -n 50000000 -s 5000
And it is showing that
Module FastPyRateC was loaded. However, previously it was also showing similar message.
More essentially, it seems that -n and -s parameters are not working and by default the program sample the parameters every 1,000 iterations and it is displaying message...
PyRate.py:2373: DeprecationWarning: This function is deprecated. Please call randint(0, 1 + 1) instead
ind=np.random.random_integers(0,len(M))
PyRate.py:2369: DeprecationWarning: This function is deprecated. Please call randint(0, 1 + 1) instead
ind=np.random.random_integers(0,len(L))
PyRate.py:2369: DeprecationWarning: This function is deprecated. Please call randint(0, 2 + 1) instead
ind=np.random.random_integers(0,len(L))
PyRate.py:2369: DeprecationWarning: This function is deprecated. Please call randint(0, 3 + 1) instead
ind=np.random.random_integers(0,len(L))
PyRate.py:2369: DeprecationWarning: This function is deprecated. Please call randint(0, 4 + 1) instead
ind=np.random.random_integers(0,len(L))
PyRate.py:2369: DeprecationWarning: This function is deprecated. Please call randint(0, 5 + 1) instead
ind=np.random.random_integers(0,len(L))
PyRate.py:2373: DeprecationWarning: This function is deprecated. Please call randint(0, 2 + 1) instead
ind=np.random.random_integers(0,len(M))
PyRate.py:2373: DeprecationWarning: This function is deprecated. Please call randint(0, 3 + 1) instead
ind=np.random.random_integers(0,len(M))
Another thing I want know that approximately how much time require for 10 million iteration as my analysis included 2023 fossil record.
Thanks,
Debajyoti
Thank you for pointing out this warning, I just pushed an update that should fix it.
Running 10M iterations on a standard dataset should definitely take less than 65 hours! Please note that the -A 4
algorithm (implementing RJMCMC) should be preferred over the -A 2
.
If you send us the data by email we can take a look and see if there is any reason any particular issue with the input data.
Cheers,
Daniele