diff --git a/examples/starter_tutorial/minimal_tutorial.py b/examples/starter_tutorial/minimal_tutorial.py index bf54a893f..677b72331 100644 --- a/examples/starter_tutorial/minimal_tutorial.py +++ b/examples/starter_tutorial/minimal_tutorial.py @@ -184,57 +184,10 @@ # experiments, but is useful for this tutorial. # %% -from dacapo.experiments.datasplits import TrainValidateDataSplitConfig -from dacapo.experiments.datasplits.datasets import RawGTDatasetConfig -from dacapo.experiments.datasplits.datasets.arrays import ( - ZarrArrayConfig, - IntensitiesArrayConfig, -) +from dacapo.experiments.datasplits.simple_config import SimpleDataSplitConfig from funlib.geometry import Coordinate -datasplit_config = TrainValidateDataSplitConfig( - name="example_datasplit", - train_configs=[ - RawGTDatasetConfig( - name="example_dataset", - raw_config=IntensitiesArrayConfig( - name="example_raw_normalized", - source_array_config=ZarrArrayConfig( - name="example_raw", - file_name="cells3d.zarr", - dataset="raw", - ), - min=0, - max=255, - ), - gt_config=ZarrArrayConfig( - name="example_gt", - file_name="cells3d.zarr", - dataset="mask", - ), - ) - ], - validate_configs=[ - RawGTDatasetConfig( - name="example_dataset", - raw_config=IntensitiesArrayConfig( - name="example_raw_normalized", - source_array_config=ZarrArrayConfig( - name="example_raw", - file_name="cells3d.zarr", - dataset="raw", - ), - min=0, - max=255, - ), - gt_config=ZarrArrayConfig( - name="example_gt", - file_name="cells3d.zarr", - dataset="labels", - ), - ) - ], -) +datasplit_config = SimpleDataSplitConfig(name="cells3d", path="cells3d.zarr") datasplit = datasplit_config.datasplit_type(datasplit_config) config_store.store_datasplit_config(datasplit_config) @@ -497,8 +450,8 @@ # break raw = zarr.open(f"{run_path}/validation.zarr/inputs/{dataset}/raw") gt = zarr.open(f"{run_path}/validation.zarr/inputs/{dataset}/gt") - pred_path = f"{run_path}/validation.zarr/{validation_it}/ds_{dataset}/prediction" - out_path = f"{run_path}/validation.zarr/{validation_it}/ds_{dataset}/output/WatershedPostProcessorParameters(id=2, bias=0.5, context=(32, 32, 32))" + pred_path = f"{run_path}/validation.zarr/{validation_it}/{dataset}/prediction" + out_path = f"{run_path}/validation.zarr/{validation_it}/{dataset}/output/WatershedPostProcessorParameters(id=2, bias=0.5, context=(32, 32, 32))" output = zarr.open(out_path)[:] prediction = zarr.open(pred_path)[0] c = (raw.shape[2] - gt.shape[1]) // 2