| Previous changeset 14:adb084b901cc (2023-08-09) Next changeset 16:8f469d961e30 (2023-11-03) |
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Commit message:
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 80417bf0158a9b596e485dd66408f738f405145a |
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modified:
keras_train_and_eval.py ml_visualization_ex.py |
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removed:
pdb70_cs219.ffdata |
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| diff -r adb084b901cc -r 8e447b95e6a8 keras_train_and_eval.py --- a/keras_train_and_eval.py Wed Aug 09 14:26:26 2023 +0000 +++ b/keras_train_and_eval.py Mon Oct 02 09:58:11 2023 +0000 |
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| @@ -188,6 +188,7 @@ infile1, infile2, outfile_result, + outfile_history=None, outfile_object=None, outfile_y_true=None, outfile_y_preds=None, @@ -215,6 +216,9 @@ outfile_result : str File path to save the results, either cv_results or test result. + outfile_history : str, optional + File path to save the training history. + outfile_object : str, optional File path to save searchCV object. @@ -253,9 +257,7 @@ swapping = params["experiment_schemes"]["hyperparams_swapping"] swap_params = _eval_swap_params(swapping) estimator.set_params(**swap_params) - estimator_params = estimator.get_params() - # store read dataframe object loaded_df = {} @@ -448,12 +450,20 @@ # train and eval if hasattr(estimator, "config") and hasattr(estimator, "model_type"): if exp_scheme == "train_val_test": - estimator.fit(X_train, y_train, validation_data=(X_val, y_val)) + history = estimator.fit(X_train, y_train, validation_data=(X_val, y_val)) else: - estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) + history = estimator.fit(X_train, y_train, validation_data=(X_test, y_test)) else: - estimator.fit(X_train, y_train) - + history = estimator.fit(X_train, y_train) + if "callbacks" in estimator_params: + for cb in estimator_params["callbacks"]: + if cb["callback_selection"]["callback_type"] == "CSVLogger": + hist_df = pd.DataFrame(history.history) + hist_df["epoch"] = np.arange(1, estimator_params["epochs"] + 1) + epo_col = hist_df.pop('epoch') + hist_df.insert(0, 'epoch', epo_col) + hist_df.to_csv(path_or_buf=outfile_history, sep="\t", header=True, index=False) + break if isinstance(estimator, KerasGBatchClassifier): scores = {} steps = estimator.prediction_steps @@ -526,6 +536,7 @@ aparser.add_argument("-X", "--infile1", dest="infile1") aparser.add_argument("-y", "--infile2", dest="infile2") aparser.add_argument("-O", "--outfile_result", dest="outfile_result") + aparser.add_argument("-hi", "--outfile_history", dest="outfile_history") aparser.add_argument("-o", "--outfile_object", dest="outfile_object") aparser.add_argument("-l", "--outfile_y_true", dest="outfile_y_true") aparser.add_argument("-p", "--outfile_y_preds", dest="outfile_y_preds") @@ -542,6 +553,7 @@ args.infile1, args.infile2, args.outfile_result, + outfile_history=args.outfile_history, outfile_object=args.outfile_object, outfile_y_true=args.outfile_y_true, outfile_y_preds=args.outfile_y_preds, |
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| diff -r adb084b901cc -r 8e447b95e6a8 ml_visualization_ex.py --- a/ml_visualization_ex.py Wed Aug 09 14:26:26 2023 +0000 +++ b/ml_visualization_ex.py Mon Oct 02 09:58:11 2023 +0000 |
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| @@ -15,6 +15,7 @@ from sklearn.metrics import ( auc, average_precision_score, + confusion_matrix, precision_recall_curve, roc_curve, ) @@ -258,6 +259,30 @@ os.rename(os.path.join(folder, "output.svg"), os.path.join(folder, "output")) +def get_dataframe(file_path, plot_selection, header_name, column_name): + header = "infer" if plot_selection[header_name] else None + column_option = plot_selection[column_name]["selected_column_selector_option"] + if column_option in [ + "by_index_number", + "all_but_by_index_number", + "by_header_name", + "all_but_by_header_name", + ]: + col = plot_selection[column_name]["col1"] + else: + col = None + _, input_df = read_columns( + file_path, + c=col, + c_option=column_option, + return_df=True, + sep="\t", + header=header, + parse_dates=True, + ) + return input_df + + def main( inputs, infile_estimator=None, @@ -271,6 +296,10 @@ targets=None, fasta_path=None, model_config=None, + true_labels=None, + predicted_labels=None, + plot_color=None, + title=None, ): """ Parameter @@ -311,6 +340,18 @@ model_config : str, default is None File path to dataset containing JSON config for neural networks + + true_labels : str, default is None + File path to dataset containing true labels + + predicted_labels : str, default is None + File path to dataset containing true predicted labels + + plot_color : str, default is None + Color of the confusion matrix heatmap + + title : str, default is None + Title of the confusion matrix heatmap """ warnings.simplefilter("ignore") @@ -534,6 +575,36 @@ return 0 + elif plot_type == "classification_confusion_matrix": + plot_selection = params["plotting_selection"] + input_true = get_dataframe( + true_labels, plot_selection, "header_true", "column_selector_options_true" + ) + header_predicted = "infer" if plot_selection["header_predicted"] else None + input_predicted = pd.read_csv( + predicted_labels, sep="\t", parse_dates=True, header=header_predicted + ) + true_classes = input_true.iloc[:, -1].copy() + predicted_classes = input_predicted.iloc[:, -1].copy() + axis_labels = list(set(true_classes)) + c_matrix = confusion_matrix(true_classes, predicted_classes) + fig, ax = plt.subplots(figsize=(7, 7)) + im = plt.imshow(c_matrix, cmap=plot_color) + for i in range(len(c_matrix)): + for j in range(len(c_matrix)): + ax.text(j, i, c_matrix[i, j], ha="center", va="center", color="k") + ax.set_ylabel("True class labels") + ax.set_xlabel("Predicted class labels") + ax.set_title(title) + ax.set_xticks(axis_labels) + ax.set_yticks(axis_labels) + fig.colorbar(im, ax=ax) + fig.tight_layout() + plt.savefig("output.png", dpi=125) + os.rename("output.png", "output") + + return 0 + # save pdf file to disk # fig.write_image("image.pdf", format='pdf') # fig.write_image("image.pdf", format='pdf', width=340*2, height=226*2) @@ -553,6 +624,10 @@ aparser.add_argument("-t", "--targets", dest="targets") aparser.add_argument("-f", "--fasta_path", dest="fasta_path") aparser.add_argument("-c", "--model_config", dest="model_config") + aparser.add_argument("-tl", "--true_labels", dest="true_labels") + aparser.add_argument("-pl", "--predicted_labels", dest="predicted_labels") + aparser.add_argument("-pc", "--plot_color", dest="plot_color") + aparser.add_argument("-pt", "--title", dest="title") args = aparser.parse_args() main( @@ -568,4 +643,8 @@ targets=args.targets, fasta_path=args.fasta_path, model_config=args.model_config, + true_labels=args.true_labels, + predicted_labels=args.predicted_labels, + plot_color=args.plot_color, + title=args.title, ) |
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| diff -r adb084b901cc -r 8e447b95e6a8 pdb70_cs219.ffdata --- a/pdb70_cs219.ffdata Wed Aug 09 14:26:26 2023 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -1,189 +0,0 @@ - - - - -<!DOCTYPE HTML> -<html> - <!--base.mako--> - - - - <head> - <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /> - <meta name = "viewport" content = "maximum-scale=1.0"> - <meta http-equiv="X-UA-Compatible" content="IE=Edge,chrome=1"> - - <title> - Galaxy - | Europe - | - </title> - - <link rel="index" href="/"/> - - - - <link href="/static/style/bootstrap-tour.css?v=1618364054" media="screen" rel="stylesheet" type="text/css" /> - <link href="/static/dist/base.css?v=1618364054" media="screen" rel="stylesheet" type="text/css" /> - - - <script src="/static/dist/libs.chunk.js?v=1618364054" type="text/javascript"></script> -<script src="/static/dist/base.chunk.js?v=1618364054" type="text/javascript"></script> -<script src="/static/dist/generic.bundled.js?v=1618364054" type="text/javascript"></script> - - - <!-- message.mako javascript_app() --> - - - - <script type="text/javascript"> - // galaxy_client_app.mako, load - - var bootstrapped; - try { - bootstrapped = -{} -; - } catch(err) { - console.warn("Unable to parse bootstrapped variable", err); - bootstrapped = {}; - } - - var options = { - root: '/', - config: - -{ -"display_galaxy_brand": true, -"chunk_upload_size": 104857600, -"use_remote_user": null, -"enable_oidc": true, -"mailing_join_addr": null, -"select_type_workflow_threshold": -1, -"myexperiment_target_url": "www.myexperiment.org:80", -"tool_recommendation_model_path": "https://github.com/galaxyproject/galaxy-test-data/raw/master/tool_recommendation_model.hdf5", -"simplified_workflow_run_ui_target_history": "current", -"interactivetools_enable": true, -"is_admin_user": false, -"show_welcome_with_login": true, -"welcome_url": "/static/welcome.html", -"allow_user_impersonation": true, -"overwrite_model_recommendations": false, -"topk_recommendations": 10, -"user_library_import_dir_available": false, -"ga_code": null, -"enable_beta_markdown_export": true, -"visualizations_visible": true, -"enable_tool_recommendations": true, -"enable_unique_workflow_defaults": false, -"registration_warning_message": "Please register only one account. 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Feel free to browse around and see what's available, but you won't be able to upload data or run jobs until you have verified your email address.", -"nginx_upload_path": "/_upload" -} -, - user: - -{ -"total_disk_usage": 0, -"nice_total_disk_usage": "0 bytes", -"quota_percent": null -} -, - session_csrf_token: 'c3ae71f65be7de55dd5bd5f97f316000' - }; - - config.set({ - options: options, - bootstrapped: bootstrapped - }); - - - </script> - - - - - - - - - - <script type="text/javascript"> - config.addInitialization(function() { - if (parent.handle_minwidth_hint) { - parent.handle_minwidth_hint(-1); - } - }); - </script> - - </head> - <body class="inbound"> - - - - <div class="message mt-2 alert alert-danger">You are not allowed to access this dataset</div> - - - </body> -</html> - - - - - - - - - - - - |