Mercurial > repos > bgruening > sklearn_numeric_clustering
diff simple_model_fit.py @ 36:73e7f1c76ece draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit ea12f973df4b97a2691d9e4ce6bf6fae59d57717"
author | bgruening |
---|---|
date | Sat, 01 May 2021 00:48:46 +0000 |
parents | e7f047a9dca9 |
children | 06d772036a62 |
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--- a/simple_model_fit.py Tue Apr 13 22:08:10 2021 +0000 +++ b/simple_model_fit.py Sat May 01 00:48:46 2021 +0000 @@ -7,7 +7,6 @@ from scipy.io import mmread from sklearn.pipeline import Pipeline - N_JOBS = int(__import__("os").environ.get("GALAXY_SLOTS", 1)) @@ -36,7 +35,7 @@ if name == "memory" or name.endswith("__memory") or name.endswith("_path"): new_p = {name: None} estimator.set_params(**new_p) - elif n_jobs is not None and (name == 'n_jobs' or name.endswith('__n_jobs')): + elif n_jobs is not None and (name == "n_jobs" or name.endswith("__n_jobs")): new_p = {name: n_jobs} estimator.set_params(**new_p) elif name.endswith("callbacks"): @@ -68,7 +67,9 @@ # tabular input if input_type == "tabular": header = "infer" if params["input_options"]["header1"] else None - column_option = params["input_options"]["column_selector_options_1"]["selected_column_selector_option"] + column_option = params["input_options"]["column_selector_options_1"][ + "selected_column_selector_option" + ] if column_option in [ "by_index_number", "all_but_by_index_number", @@ -90,7 +91,9 @@ # Get target y header = "infer" if params["input_options"]["header2"] else None - column_option = params["input_options"]["column_selector_options_2"]["selected_column_selector_option2"] + column_option = params["input_options"]["column_selector_options_2"][ + "selected_column_selector_option2" + ] if column_option in [ "by_index_number", "all_but_by_index_number", @@ -108,12 +111,9 @@ infile2 = pd.read_csv(infile2, sep="\t", header=header, parse_dates=True) loaded_df[df_key] = infile2 - y = read_columns(infile2, - c=c, - c_option=column_option, - sep='\t', - header=header, - parse_dates=True) + y = read_columns( + infile2, c=c, c_option=column_option, sep="\t", header=header, parse_dates=True + ) if len(y.shape) == 2 and y.shape[1] == 1: y = y.ravel()