trying to resolve copy warning in code
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1 changed files with 10 additions and 9 deletions
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@ -34,8 +34,8 @@ arg_parser.add_argument('-i', '--input_dir', help = 'Input dir containing pdb fi
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arg_parser.add_argument('-o', '--output_dir', help = 'Output dir for results. By default, it assmes homedir + <drug> + output')
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# FIXME: remove defaults
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arg_parser.add_argument('-s', '--start_coord', help = 'start of coding region (cds) of gene', default = 2288681) # pnca cds
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arg_parser.add_argument('-e', '--end_coord', help = 'end of coding region (cds) of gene', default = 2289241) # pnca cds
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arg_parser.add_argument('-sc', '--start_coord', help = 'start of coding region (cds) of gene', default = None, type = int) # pnca cds
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arg_parser.add_argument('-ec', '--end_coord', help = 'end of coding region (cds) of gene', default = None, type = int) # pnca cds
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arg_parser.add_argument('--debug', action ='store_true', help = 'Debug Mode')
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@ -314,18 +314,21 @@ print('No. of cols pre-formatting data:', df_ncols
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#1) Add column: OR for kinship calculated from beta coef
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ncols_add = 0
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if not 'or_kin' in dfm2_mis.columns:
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dfm2_mis['or_kin'] = np.exp(dfm2_mis['beta'])
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#dfm2_mis['or_kin'] = np.exp(dfm2_mis['beta']) # gives copy warning
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dfm2_mis.loc[:,'or_kin'] = np.exp(dfm2_mis.loc[:,'beta'])
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print(dfm2_mis['or_kin'].head())
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ncols_add+=1
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print('Calculating OR from beta coeff by exponent function and adding column:'
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, '\nNo. of cols added:', ncols_add, '\n'
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, dfm2_mis['beta'].head()
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, '\nNo. of cols added:', ncols_add
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, '\n', dfm2_mis['beta'].head()
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, '\nNo. of cols after adding OR_kin:', len(dfm2_mis.columns)
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, '\n===================================================================')
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if dfm2_mis.shape[1] == df_ncols + ncols_add:
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print('PASS: Dimension of df match'
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, '\nDim of df:', dfm2_mis.shape
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, 'n================================================================')
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, '\n================================================================')
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else:
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print('FAIL: Dim mismatch'
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, '\nOriginal no. of cols:', df_ncols
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@ -333,8 +336,6 @@ else:
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, '\nGot:', dfm2_mis.shape[1])
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sys.exit()
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print('No. of cols after adding OR_kin:', len(dfm2_mis.columns))
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#2) rename columns to reflect that it is coming from kinship matrix adjustment
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dfm2_mis.rename(columns = {'af': 'af_kin'
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, 'beta': 'beta_kin'
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@ -399,7 +400,7 @@ else:
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sys.exit()
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del(df_ncols)
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#%%
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#%%=====================================================================
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#4) reorder columnn
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print('Reordering', dfm2_mis.shape[1], 'columns'
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, '\n===============================================')
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