Loading deepchem/dock/pose_generation.py +1 −1 Original line number Diff line number Diff line Loading @@ -47,7 +47,7 @@ class PoseGenerator(object): Parameters ---------- molecular_complexes: Tuple[str] molecular_complexes: Tuple[str, str] A representation of a molecular complex. This tuple is (protein_file, ligand_file). centroid: np.ndarray, optional (default None) Loading deepchem/hyper/base_classes.py +3 −3 Original line number Diff line number Diff line Loading @@ -98,11 +98,11 @@ class HyperparamOpt(object): ints/floats/strings/lists/etc. Read the documentation for the concrete hyperparameter optimization subclass you're using to learn more about what's expected. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) metric: `dc.metrics.Metric` metric: Metric metric used for evaluation use_max: bool, optional If True, return the model with the highest score. Else return Loading deepchem/hyper/gaussian_process.py +3 −3 Original line number Diff line number Diff line Loading @@ -150,11 +150,11 @@ class GaussianProcessHyperparamOpt(HyperparamOpt): which is used as the center of a search with radius `search_range` since pyGPGO can only optimize numerical hyperparameters. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) metric: `dc.metrics.Metric` metric: Metric metric used for evaluation use_max: bool, (default True) Specifies whether to maximize or minimize `metric`. Loading deepchem/hyper/grid_search.py +4 −4 Original line number Diff line number Diff line Loading @@ -82,16 +82,16 @@ class GridHyperparamOpt(HyperparamOpt): params_dict: Dict Maps hyperparameter names (strings) to lists of possible parameter values. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) output_transformers: list[dc.trans.Transformer] output_transformers: list[Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. metric: dc.metrics.Metric metric: Metric metric used for evaluation use_max: bool, optional If True, return the model with the highest score. Else return Loading setup.cfg +1 −0 Original line number Diff line number Diff line Loading @@ -13,6 +13,7 @@ ignore = E121, # continuation line under-indented for hanging indent E124, # Closing bracket does not match visual indentation E125, # Continuation line with same indent as next logical line E127, # Continuation line over-indented for visual indent E129, # Visually indented line with same indent as next logical line W503, # Line break before binary operator W504, # Line break after binary operator Loading Loading
deepchem/dock/pose_generation.py +1 −1 Original line number Diff line number Diff line Loading @@ -47,7 +47,7 @@ class PoseGenerator(object): Parameters ---------- molecular_complexes: Tuple[str] molecular_complexes: Tuple[str, str] A representation of a molecular complex. This tuple is (protein_file, ligand_file). centroid: np.ndarray, optional (default None) Loading
deepchem/hyper/base_classes.py +3 −3 Original line number Diff line number Diff line Loading @@ -98,11 +98,11 @@ class HyperparamOpt(object): ints/floats/strings/lists/etc. Read the documentation for the concrete hyperparameter optimization subclass you're using to learn more about what's expected. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) metric: `dc.metrics.Metric` metric: Metric metric used for evaluation use_max: bool, optional If True, return the model with the highest score. Else return Loading
deepchem/hyper/gaussian_process.py +3 −3 Original line number Diff line number Diff line Loading @@ -150,11 +150,11 @@ class GaussianProcessHyperparamOpt(HyperparamOpt): which is used as the center of a search with radius `search_range` since pyGPGO can only optimize numerical hyperparameters. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) metric: `dc.metrics.Metric` metric: Metric metric used for evaluation use_max: bool, (default True) Specifies whether to maximize or minimize `metric`. Loading
deepchem/hyper/grid_search.py +4 −4 Original line number Diff line number Diff line Loading @@ -82,16 +82,16 @@ class GridHyperparamOpt(HyperparamOpt): params_dict: Dict Maps hyperparameter names (strings) to lists of possible parameter values. train_dataset: `dc.data.Dataset` train_dataset: Dataset dataset used for training valid_dataset: `dc.data.Dataset` valid_dataset: Dataset dataset used for validation(optimization on valid scores) output_transformers: list[dc.trans.Transformer] output_transformers: list[Transformer] Transformers for evaluation. This argument is needed since `train_dataset` and `valid_dataset` may have been transformed for learning and need the transform to be inverted before the metric can be evaluated on a model. metric: dc.metrics.Metric metric: Metric metric used for evaluation use_max: bool, optional If True, return the model with the highest score. Else return Loading
setup.cfg +1 −0 Original line number Diff line number Diff line Loading @@ -13,6 +13,7 @@ ignore = E121, # continuation line under-indented for hanging indent E124, # Closing bracket does not match visual indentation E125, # Continuation line with same indent as next logical line E127, # Continuation line over-indented for visual indent E129, # Visually indented line with same indent as next logical line W503, # Line break before binary operator W504, # Line break after binary operator Loading
