From 84c316b84f892d75171e04b43a22f3e0bd442908 Mon Sep 17 00:00:00 2001 From: David Nicholson Date: Sat, 4 May 2024 22:57:02 -0400 Subject: [PATCH] Apply linting to src/ --- src/vak/config/dataset.py | 9 ++++----- src/vak/datasets/frame_classification/window_dataset.py | 2 +- src/vak/eval/eval_.py | 4 ++-- src/vak/eval/frame_classification.py | 4 ++-- src/vak/learncurve/frame_classification.py | 4 +++- src/vak/predict/parametric_umap.py | 3 ++- src/vak/train/frame_classification.py | 6 +++--- src/vak/train/train_.py | 4 ++-- 8 files changed, 19 insertions(+), 17 deletions(-) diff --git a/src/vak/config/dataset.py b/src/vak/config/dataset.py index dc86ec963..f75c34b73 100644 --- a/src/vak/config/dataset.py +++ b/src/vak/config/dataset.py @@ -38,18 +38,17 @@ class DatasetConfig: name: str | None = field( converter=attr.converters.optional(str), default=None ) - params : dict | None = field( + params: dict | None = field( # we default to an empty dict instead of None # so we can still do **['dataset']['params'] everywhere we do when params are specified - converter=attr.converters.optional(dict), default={} + converter=attr.converters.optional(dict), + default={}, ) @classmethod def from_config_dict(cls, config_dict: dict) -> DatasetConfig: - return cls( - **config_dict - ) + return cls(**config_dict) def asdict(self): """Convert this :class:`DatasetConfig` instance diff --git a/src/vak/datasets/frame_classification/window_dataset.py b/src/vak/datasets/frame_classification/window_dataset.py index c4781f07f..d916a6bcc 100644 --- a/src/vak/datasets/frame_classification/window_dataset.py +++ b/src/vak/datasets/frame_classification/window_dataset.py @@ -281,7 +281,7 @@ def shape(self): tmp_item = self.__getitem__(tmp_x_ind) # used by vak functions that need to determine size of window, # e.g. when initializing a neural network model - return tmp_item['frames'].shape + return tmp_item["frames"].shape def _load_frames(self, frames_path): """Helper function that loads "frames", diff --git a/src/vak/eval/eval_.py b/src/vak/eval/eval_.py index d8a13e663..fa1209f1d 100644 --- a/src/vak/eval/eval_.py +++ b/src/vak/eval/eval_.py @@ -93,13 +93,13 @@ def eval( f"value for ``{path_name}`` not recognized as a file: {path}" ) - dataset_path = pathlib.Path(dataset_config['path']) + dataset_path = pathlib.Path(dataset_config["path"]) if not dataset_path.exists() or not dataset_path.is_dir(): raise NotADirectoryError( f"`dataset_path` not found or not recognized as a directory: {dataset_path}" ) - model_name = model_config['name'] + model_name = model_config["name"] try: model_family = models.registry.MODEL_FAMILY_FROM_NAME[model_name] except KeyError as e: diff --git a/src/vak/eval/frame_classification.py b/src/vak/eval/frame_classification.py index 0cc4bb41f..1be124758 100644 --- a/src/vak/eval/frame_classification.py +++ b/src/vak/eval/frame_classification.py @@ -95,7 +95,7 @@ def eval_frame_classification_model( f"value for ``{path_name}`` not recognized as a file: {path}" ) - dataset_path = pathlib.Path(dataset_config['path']) + dataset_path = pathlib.Path(dataset_config["path"]) if not dataset_path.exists() or not dataset_path.is_dir(): raise NotADirectoryError( f"`dataset_path` not found or not recognized as a directory: {dataset_path}" @@ -143,7 +143,7 @@ def eval_frame_classification_model( ) transform_params = { "spect_standardizer": spect_standardizer, - "window_size": window_size + "window_size": window_size, } item_transform = transforms.defaults.get_default_transform( diff --git a/src/vak/learncurve/frame_classification.py b/src/vak/learncurve/frame_classification.py index 76364679d..8ca2e11b7 100644 --- a/src/vak/learncurve/frame_classification.py +++ b/src/vak/learncurve/frame_classification.py @@ -158,7 +158,9 @@ def learning_curve_for_frame_classification_model( # ---- main loop that creates "learning curve" --------------------------------------------------------------------- logger.info("Starting training for learning curve.") - model_name = model_config["name"] # used below when getting checkpoint path, etc + model_name = model_config[ + "name" + ] # used below when getting checkpoint path, etc for train_dur, replicate_num in to_do: logger.info( f"Training model with training set of size: {train_dur}s, replicate number {replicate_num}.", diff --git a/src/vak/predict/parametric_umap.py b/src/vak/predict/parametric_umap.py index bcc9250e9..4e54336f4 100644 --- a/src/vak/predict/parametric_umap.py +++ b/src/vak/predict/parametric_umap.py @@ -105,7 +105,8 @@ def predict_with_parametric_umap_model( # TODO: fix this when we build transforms into datasets transform_params = { "padding": dataset_config["params"].get( - "padding", models.convencoder_umap.get_default_padding(metadata.shape) + "padding", + models.convencoder_umap.get_default_padding(metadata.shape), ) } item_transform = transforms.defaults.get_default_transform( diff --git a/src/vak/train/frame_classification.py b/src/vak/train/frame_classification.py index 99dd93734..da9a13c54 100644 --- a/src/vak/train/frame_classification.py +++ b/src/vak/train/frame_classification.py @@ -127,7 +127,7 @@ def train_frame_classification_model( f"value for ``{path_name}`` not recognized as a file: {path}" ) - dataset_path = pathlib.Path(dataset_config['path']) + dataset_path = pathlib.Path(dataset_config["path"]) if not dataset_path.exists() or not dataset_path.is_dir(): raise NotADirectoryError( f"`dataset_path` not found or not recognized as a directory: {dataset_path}" @@ -209,7 +209,7 @@ def train_frame_classification_model( ) spect_standardizer = None - model_name = model_config['name'] + model_name = model_config["name"] # TODO: move this into datapipe once each datapipe uses a fixed set of transforms # that will require adding `spect_standardizer`` as a parameter to the datapipe, # maybe rename to `frames_standardizer`? @@ -233,7 +233,7 @@ def train_frame_classification_model( split="train", subset=subset, item_transform=train_transform, - **dataset_config['params'], + **dataset_config["params"], ) logger.info( f"Duration of WindowDataset used for training, in seconds: {train_dataset.duration}", diff --git a/src/vak/train/train_.py b/src/vak/train/train_.py index 7d3597179..96926967d 100644 --- a/src/vak/train/train_.py +++ b/src/vak/train/train_.py @@ -130,13 +130,13 @@ def train( f"value for ``{path_name}`` not recognized as a file: {path}" ) - dataset_path = pathlib.Path(dataset_config['path']) + dataset_path = pathlib.Path(dataset_config["path"]) if not dataset_path.exists() or not dataset_path.is_dir(): raise NotADirectoryError( f"`dataset_path` not found or not recognized as a directory: {dataset_path}" ) - model_name = model_config['name'] + model_name = model_config["name"] try: model_family = models.registry.MODEL_FAMILY_FROM_NAME[model_name] except KeyError as e: