class jade.RAbD_BM.AnalyzeRecovery.AnalyzeRecovery(pyig_design_db_path, analysis_info, native_info, cdrs=None)

Pools Recovery and RR data, outputs to DB

apply(db_path, drop_tables=False)

Calculate and Output all the data to the given database.

Parameters:db_path – str

initialize()

Initialize ALL input data before calculating and outputing everything.

class jade.RAbD_BM.AnalyzeRecovery.ObservedRecoveryCalculator(native_db_path)

Bases: jade.RAbD_BM.AnalyzeRecovery.RecoveryCalculator

apply(exp_name, pdbids, cdrs, bm_decoy_path, output_dir='data')

Calculates the number of times the native clusters and lengths were observed during the experiment, for each PDB. Returns the resulting dataframe.

Return type:pandas.DataFrame

class jade.RAbD_BM.AnalyzeRecovery.PyIgClassifyDBRepresentationCalculator(native_db_path)

Bases: jade.RAbD_BM.AnalyzeRecovery.RecoveryCalculator

apply(exp_name, cdrs, pyig_db_path, lambda_kappa_dict, output_dir='data')

Calculates the number of times lengths and clusters are present in the PyIgClassify database. :param lambda_kappa_dict : dict-like [‘lambda’] = [pdbid,]

Return type:pandas.DataFrame

class jade.RAbD_BM.AnalyzeRecovery.RecoveryCalculator(native_db_path)

Bases: object

class jade.RAbD_BM.AnalyzeRecovery.TopRecoveryCalculator(native_db_path)

Bases: jade.RAbD_BM.AnalyzeRecovery.RecoveryCalculator

apply(exp_name, pdbids, cdrs, bm_db_path, output_dir='data')

Calculate length and cluster recoveries. Store them the same way we used to for the recovery parser. Returns the resulting dataframe of recoveries. :rtype: pandas.DataFrame

jade.RAbD_BM.AnalyzeRecovery.calculate_exp_rr_and_recovery(exp, result_df)

Calculate the overall recovery and risk ratio. :param exp: :param result_df: :rtype: pandas.DataFrame

jade.RAbD_BM.AnalyzeRecovery.calculate_per_cdr_rr_and_recovery(exp, cdrs, result_df)

Calculate the recovery and risk-ratios PER CDR. :rtype: pandas.DataFrame

jade.RAbD_BM.AnalyzeRecovery.calculate_recovery_and_risk_ratios(top_recovery_df, observed_df)

Calculate the Risk Ratio and Recovery Percent for each pdb/cdr given dataframes output by the calculators below.

Return a merged dataframe of the top recovery and observed, with the resulting risk ratio data.

Parameters:

• top_recovery_df – pandas.DataFrame
• observed_df – pandas.DataFrame

Return type:

pandas.DataFrame

jade.RAbD_BM.AnalyzeRecovery.get_decoys(input_dir, pdbid)

Use GLOB to Match on pdbid for file names in the input dir. This should skip all the extra PDBs like excn, initial, relax, etc. :param input_dir: str :param tag: str