No trees shown in PhyloWGS Witness

[SwaggerNiels]

After installing a fresh git clone and compiling the mh file, im able to succesfully run the program using:

python2 multievolve.py --num-chains 4 --ssms ssm_data.txt --cnvs cnv_data.txt --burnin-samples 1 --mcmc-samples 1

however, viewing the results gives me an empty window (whenever I open the index.html), while earlier I did see trees there, now somehow it does not work anymore.

after the above succesfull run I use:

mkdir run_name
/usr/bin/python2 write_results.py run_name [mypath]/phylowgs/chains/trees.zip run_name.summ.json.gz run_name.muts.json.gz run_name.mutass.zip
mv ./run_name.* run_name
mv run_name [mypath]/phylowgs/witness/data
cd [mypath]/phylowgs/witness/
gunzip data/run_name/*.gz
python2 index_data.py 

What am i doing wrong? (I am on a remote terminal, so cannot view the http://127.0.0.1:8000 using a server)

Is there another way of opening the visualized output?

[serpei]

Please,
can you suggest how to interpret output files without opening the html file? I have the same problem.
Thank you,
S

[SwaggerNiels]

It has been quite a while, but I believe you can go into the results folder that you defined (in "data") and quite easily retrieve the output data from a json formatted file (ends in "summ.json" i believe).

if you are using python, this file can easily be converted to a dictionary, using the "json" module in python. Be careful and triple check the "negative log likelihood" values that have been defined for each tree, such that you pick the most accurate tree. All the information about the prevalences of the subpopulations and the connections should be in the data structure.

The structure of the json file is quite obvious if you have a look through it.

I hope that helps!

[serpei]

Thank you very much for the suggestion! I will go through the son file you mentioned. I have to select the inferred tree that has the minimum "negative log likelihood” as result right? Thank you again, Serena

…

On 23 Jul 2021, at 10:51, SwaggerNiels ***@***.***> wrote: It has been quite a while, but I believe you can go into the results folder that you defined (in "data") and quite easily retrieve the output data from a json formatted file (ends in "summ.json" i believe). if you are using python, this file can easily be converted to a dictionary, using the "json" module in python. Be careful and triple check the "negative log likelihood" values that have been defined for each tree, such that you pick the most accurate tree. All the information about the prevalences of the subpopulations and the connections should be in the data structure. The structure of the json file is quite obvious if you have a look through it. I hope that helps! — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#123 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AKVUNQF3HQHMCGRGBNCOQBLTZEUSLANCNFSM4MDDH5RQ>.

-- ------------------------ Indirizzo istituzionale di posta elettronica degli studenti e dei laureati dell'Università degli Studi di TorinoOfficial  University of Turin email address for students and graduates 

[SwaggerNiels]

Correct

[serpei]

Thank you. Have a nice weekend, Serena Il ven 23 lug 2021, 22:19 SwaggerNiels ***@***.***> ha scritto:

…

Correct — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#123 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AKVUNQCWWQ7QO7A4CKPI6MDTZHFEZANCNFSM4MDDH5RQ> .

-- ------------------------ Indirizzo istituzionale di posta elettronica degli studenti e dei laureati dell'Università degli Studi di TorinoOfficial  University of Turin email address for students and graduates