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uncommented some debug output for mcsm, pandas and numpy conflict. So temporarily resolved it by running from base env

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This commit is contained in:
Tanushree Tunstall 2021-02-11 10:53:23 +00:00
parent acd51ab3e4
commit e302aafacf
3 changed files with 9 additions and 4 deletions
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8
dynamut/submit.py
View file

@ -60,8 +60,12 @@ with open("/home/tanu/git/Data/streptomycin/input/gid_complex.pdb", "rb") as pdb
failed_muts.close() failed_muts.close()
#%% #%%
def request_calculation(pdb_file, mutation_list, chain, my_email, prediction_url def request_calculation(pdb_file, mutation_list
#, output_dir, gene_name , chain
, my_email
, prediction_url
, output_dir
, gene_name
, url_file): , url_file):
""" """
Makes a POST request for a ligand affinity prediction. Makes a POST request for a ligand affinity prediction.

1
mcsm/mcsm.py
View file

@ -166,6 +166,7 @@ def build_result_dict(web_result_raw):
if len(fields) > 1: # since Mutaton information is empty if len(fields) > 1: # since Mutaton information is empty
dict_entry = dict([(x, y) for x, y in zip(fields[::2], fields[1::2])]) dict_entry = dict([(x, y) for x, y in zip(fields[::2], fields[1::2])])
result_dict.update(dict_entry) result_dict.update(dict_entry)
print(result_dict)
return result_dict return result_dict
#%% #%%
#======================================================================= #=======================================================================

4
mcsm/run_mcsm.py
View file

@ -163,7 +163,7 @@ def get_results():
output_df = pd.DataFrame() output_df = pd.DataFrame()
url_counter = 1 # HURR DURR COUNT STARTEDS AT ONE1`!1 url_counter = 1 # HURR DURR COUNT STARTEDS AT ONE1`!1
success_counter = 1 success_counter = 1
infile_len = os.popen('wc -l < %s' % result_urls).read() # quicker than using Python :-) #FIXME filenme (infile_urls) infile_len = os.popen('wc -l < %s' % result_urls).read() # quicker than using Python :-)
print('Total URLs:', infile_len) print('Total URLs:', infile_len)
@ -181,7 +181,7 @@ def get_results():
url_counter += 1 url_counter += 1
print('Total URLs: %s Successful: %s Failed: %s' % (url_counter-1, success_counter-1, (url_counter - success_counter))) print('Total URLs: %s Successful: %s Failed: %s' % (url_counter-1, success_counter-1, (url_counter - success_counter)))
#print('\nOutput file created:', output_dir + gene.lower() + '_mcsm_output.csv')
output_df.to_csv(mcsm_output, index = None, header = True) output_df.to_csv(mcsm_output, index = None, header = True)
#%%===================================================================== #%%=====================================================================
def format_results(): def format_results():