🔥 Remove unnecessary code.

Author: shaneahmed

tests/test_utils.py

@@ -1742,43 +1742,6 @@ def test_patch_pred_store_sf() -> None:
         assert annotation.geometry.area == 4
 
 
-def test_patch_pred_store_zarr(tmp_path: pytest.TempPathFactory) -> None:
-    """Test patch_pred_store_zarr."""
-    # Define a mock patch_output
-    patch_output = {
-        "predictions": [1, 0, 1],
-        "coordinates": [(0, 0, 1, 1), (1, 1, 2, 2), (2, 2, 3, 3)],
-        "probabilities": [[0.1, 0.9], [0.9, 0.1], [0.4, 0.6]],
-        "labels": [1, 0, 1],
-    }
-
-    save_path = tmp_path / "patch_output" / "output.zarr"
-
-    store_path = misc.dict_to_zarr(patch_output, save_path=save_path)
-
-    print("Zarr path: ", store_path)
-    assert Path.exists(store_path), "Zarr output file does not exist"
-
-
-def test_patch_pred_store_zarr_ext(tmp_path: pytest.TempPathFactory) -> None:
-    """Test patch_pred_store_zarr and ensures the output file extension is `.zarr`."""
-    # Define a mock patch_output
-    patch_output = {
-        "predictions": [1, 0, 1],
-        "coordinates": [(0, 0, 1, 1), (1, 1, 2, 2), (2, 2, 3, 3)],
-        "probabilities": [[0.1, 0.9], [0.9, 0.1], [0.4, 0.6]],
-        "labels": [1, 0, 1],
-    }
-
-    # sends the path of a jpeg source image, expects .zarr file in the same directory
-    save_path = tmp_path / "patch_output" / "patch.jpeg"
-
-    store_path = misc.dict_to_zarr(patch_output, save_path=save_path)
-
-    print("Zarr path: ", store_path)
-    assert Path.exists(store_path), "Zarr output file does not exist"
-
-
 def test_patch_pred_store_persist(tmp_path: pytest.TempPathFactory) -> None:
     """Test patch_pred_store. and persists store output to a .db file."""
     # Define a mock patch_output

tiatoolbox/utils/misc.py

@@ -13,7 +13,6 @@
 import cv2
 import dask.array as da
 import joblib
-import numcodecs
 import numpy as np
 import pandas as pd
 import requests
@@ -1628,187 +1627,6 @@ def write_probability_heatmap_as_ome_tiff(
     logger.info(msg)
 
 
-def dict_to_zarr(
-    raw_predictions: dict,
-    save_path: Path,
-    **kwargs: dict,
-) -> Path:
-    """Saves the output of TIAToolbox engines to a zarr file.
-
-    Args:
-        raw_predictions (dict):
-            A dictionary in the TIAToolbox Engines output format.
-        save_path (str or Path):
-            Path to save the zarr file.
-        **kwargs (dict):
-            Keyword Args to update patch_pred_store_zarr attributes.
-
-
-    Returns:
-        Path to zarr file storing the patch predictor output
-
-    """
-    # Default values for Compressor and Chunks set if not received from kwargs.
-    compressor = kwargs.get("compressor", numcodecs.Zstd(level=1))
-
-    # ensure proper zarr extension
-    save_path = save_path.parent.absolute() / (save_path.stem + ".zarr")
-
-    z = zarr.open(str(save_path), mode="w")
-
-    for key, value in raw_predictions.items():
-        # save to zarr
-        array = np.array(value)
-        z.create_dataset(
-            name=key,
-            data=value,
-            compression=compressor,
-            shape=array.shape,
-            chunks=array.shape,
-        )
-
-    return save_path
-
-
-def wsi_batch_output_to_zarr_group(
-    wsi_batch_zarr_group: zarr.group | None,
-    batch_output_probabilities: np.ndarray,
-    batch_output_predictions: np.ndarray,
-    batch_output_coordinates: np.ndarray | None,
-    batch_output_label: np.ndarray | None,
-    save_path: Path,
-    **kwargs: dict,
-) -> zarr.group | Path:
-    """Saves the intermediate batch outputs of TIAToolbox engines to a zarr file.
-
-    Args:
-        wsi_batch_zarr_group (zarr.group):
-            Optional zarr group name consisting of zarrs to save the batch output
-            values.
-        batch_output_probabilities (np.ndarray):
-            Probability batch output from infer wsi.
-        batch_output_predictions (np.ndarray):
-            Predictions batch output from infer wsi.
-        batch_output_coordinates (np.ndarray):
-            Coordinates batch output from infer wsi.
-        batch_output_label (np.ndarray):
-            Labels batch output from infer wsi.
-        save_path (str or Path):
-            Path to save the zarr file.
-        **kwargs (dict):
-            Keyword Args to update wsi_batch_output_to_zarr_group attributes.
-
-    Returns:
-        Path to the zarr file storing the :class:`EngineABC` output.
-
-    """
-    # Default values for Compressor and Chunks set if not received from kwargs.
-    compressor = kwargs.get("compressor", numcodecs.Zstd(level=1))
-
-    # case 1 - new zarr group
-    if not wsi_batch_zarr_group:
-        # ensure proper zarr extension and create persistant zarr group
-        save_path = save_path.parent.absolute() / (save_path.stem + ".zarr")
-        wsi_batch_zarr_group = zarr.open(save_path, mode="w")
-
-        # populate the zarr group for the first time
-        probabilities_zarr = wsi_batch_zarr_group.create_dataset(
-            name="probabilities",
-            shape=batch_output_probabilities.shape,
-            chunks=batch_output_probabilities.shape,
-            compressor=compressor,
-        )
-        probabilities_zarr[:] = batch_output_probabilities
-
-        predictions_zarr = wsi_batch_zarr_group.create_dataset(
-            name="predictions",
-            shape=batch_output_predictions.shape,
-            chunks=batch_output_predictions.shape,
-            compressor=compressor,
-        )
-        predictions_zarr[:] = batch_output_predictions
-
-        if batch_output_coordinates is not None:
-            coordinates_zarr = wsi_batch_zarr_group.create_dataset(
-                name="coordinates",
-                shape=batch_output_coordinates.shape,
-                chunks=batch_output_coordinates.shape,
-                compressor=compressor,
-            )
-            coordinates_zarr[:] = batch_output_coordinates
-
-        if batch_output_label is not None:
-            labels_zarr = wsi_batch_zarr_group.create_dataset(
-                name="labels",
-                shape=batch_output_label.shape,
-                chunks=batch_output_label.shape,
-                compressor=compressor,
-            )
-            labels_zarr[:] = batch_output_label
-
-    # case 2 - append to existing zarr group
-    probabilities_zarr = wsi_batch_zarr_group["probabilities"]
-    probabilities_zarr.append(batch_output_probabilities)
-
-    predictions_zarr = wsi_batch_zarr_group["predictions"]
-    predictions_zarr.append(batch_output_predictions)
-
-    if batch_output_coordinates is not None:
-        coordinates_zarr = wsi_batch_zarr_group["coordinates"]
-        coordinates_zarr.append(batch_output_coordinates)
-
-    if batch_output_label is not None:
-        labels_zarr = wsi_batch_zarr_group["labels"]
-        labels_zarr.append(batch_output_label)
-
-    return wsi_batch_zarr_group
-
-
-def write_to_zarr_in_cache_mode(
-    zarr_group: zarr.group,
-    output_data_to_save: dict,
-    **kwargs: dict,
-) -> zarr.group | Path:
-    """Saves the intermediate batch outputs of TIAToolbox engines to a zarr file.
-
-    Args:
-        zarr_group (zarr.group):
-            Zarr group name consisting of zarr(s) to save the batch output
-            values.
-        output_data_to_save (dict):
-            Output data from the Engine to save to Zarr. Expects the data saved in
-            dictionary to be a numpy array.
-        **kwargs (dict):
-            Keyword Args to update zarr_group attributes.
-
-    Returns:
-        Path to the zarr file storing the :class:`EngineABC` output.
-
-    """
-    # Default values for Compressor and Chunks set if not received from kwargs.
-    compressor = kwargs.get("compressor", numcodecs.Zstd(level=1))
-
-    # case 1 - new zarr group
-    if not zarr_group:
-        for key, value in output_data_to_save.items():
-            # populate the zarr group for the first time
-            zarr_dataset = zarr_group.create_dataset(
-                name=key,
-                shape=value.shape,
-                compressor=compressor,
-                chunks=value.shape,
-            )
-            zarr_dataset[:] = value
-
-        return zarr_group
-
-    # case 2 - append to existing zarr group
-    for key, value in output_data_to_save.items():
-        zarr_group[key].append(value)
-
-    return zarr_group
-
-
 def get_tqdm() -> type[tqdm_notebook | tqdm]:
     """Returns appropriate tqdm tqdm object."""
     if is_notebook():  # pragma: no cover