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minor edits to format mcsm data like sorting df

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This commit is contained in:
Tanushree Tunstall 2020-07-09 11:15:56 +01:00
parent 8931441fa5
commit 6961a9cdb3
4 changed files with 127 additions and 85 deletions
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44
mcsm/ind_scripts/format_results.py
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@ -264,19 +264,29 @@ def format_mcsm_output(mcsm_outputcsv):
, '\nScaled affinity scores:\n', mcsm_data['affinity_scaled'])
#=============================================================================
# Adding colname: wild_pos: sometimes useful for plotting and db
print('Creating column: wild_position')
mcsm_data['wild_position'] = mcsm_data['wild_type'] + mcsm_data['position'].astype(str)
print(mcsm_data['wild_position'].head())
print('Creating column: wild_pos')
mcsm_data['wild_pos'] = mcsm_data['wild_type'] + mcsm_data['position'].astype(str)
print(mcsm_data['wild_pos'].head())
# Remove spaces b/w pasted columns
print('removing white space within column: wild_position')
mcsm_data['wild_position'] = mcsm_data['wild_position'].str.replace(' ', '')
print('Correctly formatted column: wild_position\n', mcsm_data['wild_position'].head()
print('removing white space within column: wild_pos')
mcsm_data['wild_pos'] = mcsm_data['wild_pos'].str.replace(' ', '')
print('Correctly formatted column: wild_pos\n', mcsm_data['wild_pos'].head()
, '\n===================================================================')
#=============================================================================
# Adding colname: wild_chain_pos: sometimes useful for plotting and db and is explicit
print('Creating column: wild_chain_pos')
mcsm_data['wild_chain_pos'] = mcsm_data['wild_type'] + mcsm_data['chain'] + mcsm_data['position'].astype(str)
print(mcsm_data['wild_chain_pos'].head())
# Remove spaces b/w pasted columns
print('removing white space within column: wild_chain_pos')
mcsm_data['wild_chain_pos'] = mcsm_data['wild_chain_pos'].str.replace(' ', '')
print('Correctly formatted column: wild_chain_pos\n', mcsm_data['wild_chain_pos'].head()
, '\n===================================================================')
#=============================================================================
#%% ensuring dtypes are string for the non-numeric cols
#) char cols
char_cols = ['PredAffLog', 'mutation_information', 'wild_type', 'mutant_type', 'chain'
, 'ligand_id', 'duet_outcome', 'ligand_outcome', 'wild_position']
, 'ligand_id', 'duet_outcome', 'ligand_outcome', 'wild_pos', 'wild_chain_pos']
#mcsm_data[char_cols] = mcsm_data[char_cols].astype(str)
cols_check_char = mcsm_data.select_dtypes(include='object').columns.isin(char_cols)
@ -292,7 +302,12 @@ def format_mcsm_output(mcsm_outputcsv):
#=============================================================================
# Removing PredAff log column as it is not needed?
print('Removing col: PredAffLog since relevant info has been extracted from it')
mcsm_dataf = mcsm_data.drop(columns = ['PredAffLog'])
mcsm_data_f = mcsm_data.drop(columns = ['PredAffLog'])
#=============================================================================
#sort df by position for convenience
print('Sorting df by position')
mcsm_data_fs = mcsm_data_f.sort_values(by = ['position'])
print('sorted df:\n', mcsm_data_fs.head())
#%%===========================================================================
#############
# sanity check before writing file
@ -300,29 +315,28 @@ def format_mcsm_output(mcsm_outputcsv):
expected_ncols_toadd = 5 # beware of hardcoded numbers
dforig_len = dforig_shape[1]
expected_cols = dforig_len + expected_ncols_toadd
if len(mcsm_dataf.columns) == expected_cols:
if len(mcsm_data_fs.columns) == expected_cols:
print('PASS: formatting successful'
, '\nformatted df has expected no. of cols:', expected_cols
, '\ncolnames:', mcsm_dataf.columns
, '\ncolnames:', mcsm_data_fs.columns
, '\n----------------------------------------------------------------'
, '\ndtypes in cols:', mcsm_dataf.dtypes
, '\ndtypes in cols:', mcsm_data_fs.dtypes
, '\n----------------------------------------------------------------'
, '\norig data shape:', dforig_shape
, '\nformatted df shape:', mcsm_dataf.shape
, '\nformatted df shape:', mcsm_data_fs.shape
, '\n===============================================================')
else:
print('FAIL: something went wrong in formatting df'
, '\nLen of orig df:', dforig_len
, '\nExpected number of cols to add:', expected_ncols_toadd
, '\nExpected no. of cols:', expected_cols, '(', dforig_len, '+', expected_ncols_toadd, ')'
, '\nGot no. of cols:', len(mcsm_dataf.columns)
, '\nGot no. of cols:', len(mcsm_data_fs.columns)
, '\nCheck formatting:'
, '\ncheck hardcoded value:', expected_ncols_toadd
, '\nis', expected_ncols_toadd, 'the no. of expected cols to add?'
, '\n===============================================================')
return mcsm_dataf
return mcsm_data_fs
#=======================================================================
# call function
mcsm_df_formatted = format_mcsm_output(infile)