pyNNsMD.plots package

Submodules

pyNNsMD.plots.error module

pyNNsMD.plots.error.find_max_relative_error(preds, yval)[source]

Find maximum error and its relative value if possible.

Parameters
  • preds (np.array) – Prediction array.

  • yval (np.array) – Validation array.

Returns

Flatten maximum error along axis=0 prelm (np.array): Flatten Relative maximum error along axis=0

Return type

pred_err (np.array)

pyNNsMD.plots.error.plot_error_vec_max(y_pred, y_true, label_curves='Vector', unit_predicted='#', filename='fit', dir_save='', save_plot_to_file=False, filetypeout='.png', x_label='Vector components', plot_title='Component max error')[source]
pyNNsMD.plots.error.plot_error_vec_mean(y_pred, y_true, label_curves='Vector', unit_predicted='#', filename='fit', dir_save='', save_plot_to_file=False, filetypeout='.png', x_label='Vector components', plot_title='Component mean error')[source]

pyNNsMD.plots.loss module

pyNNsMD.plots.loss.plot_learning_curve(learningall, filename='fit', dir_save='', filetypeout='.png')[source]
pyNNsMD.plots.loss.plot_loss_curves(train_loss, val_loss, test_loss=None, test_step=1, val_step=1, save_plot_to_file=False, dir_save='', filename='fit', filetypeout='.png', unit_loss='#', loss_name='MAE', plot_title='MAE vs. epochs', label_curves='loss')[source]

pyNNsMD.plots.pred module

pyNNsMD.plots.pred.plot_scatter_prediction(y_pred, y_val, save_plot_to_file=False, dir_save='', filename='fit', filetypeout='.png', unit_actual='#', unit_predicted='#', plot_title='Prediction')[source]

Module contents