Datasets:
updates to downloading, dataset updates
Browse files
ark_example.py
CHANGED
@@ -21,6 +21,8 @@ import os
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import datasets
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import pathlib
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import glob
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@@ -48,17 +50,17 @@ _LICENSE = "https://github.com/angelolab/ark-analysis/blob/main/LICENSE"
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_URL_DATA = {
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"
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"
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"
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}
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_URL_DATASET_CONFIGS = {
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"nb1": {"
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"nb2": {
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"
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"
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"
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},
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}
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@@ -112,12 +114,12 @@ class ArkExample(datasets.GeneratorBasedBuilder):
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def _info(self):
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# This is the name of the configuration selected in BUILDER_CONFIGS above
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if self.config.name
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features = datasets.Features(
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else:
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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@@ -142,29 +144,19 @@ class ArkExample(datasets.GeneratorBasedBuilder):
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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urls = _URL_DATASET_CONFIGS[self.config.name]
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return [
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datasets.SplitGenerator(
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name=self.config.name,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={"
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),
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]
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self,
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# Get all TMA paths
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file_paths = list(pathlib.Path(filepath / "input_data").glob("*"))
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# Loop over all the TMAs
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for fp in file_paths:
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# Get the file Name
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fn = fp.stem
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if self.config.name == "fovs":
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yield fn, {
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"Data Path": filepath.as_posix(),
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}
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import datasets
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import pathlib
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import glob
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import pyarrow
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import pprint
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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_URL_DATA = {
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"image_data": "./data/image_data.zip",
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"cell_table": "./data/segmentation/cell_table.zip",
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"deepcell_output": "./data/segmentation/deepcell_output.zip",
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}
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_URL_DATASET_CONFIGS = {
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"nb1": {"image_data": _URL_DATA["image_data"]},
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"nb2": {
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"image_data": _URL_DATA["image_data"],
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"cell_table": _URL_DATA["cell_table"],
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"deepcell_output": _URL_DATA["deepcell_output"],
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},
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}
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def _info(self):
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# This is the name of the configuration selected in BUILDER_CONFIGS above
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if self.config.name in ["nb1", "nb2", "nb3", "nb4"]:
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features = datasets.Features(
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{f: datasets.Value("string") for f in _URL_DATASET_CONFIGS[self.config.name].keys()}
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)
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else:
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ValueError("dataset name is incorrect.")
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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urls = _URL_DATASET_CONFIGS[self.config.name]
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data_dirs = {}
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for data_name, url in urls.items():
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dl_path = pathlib.Path(dl_manager.download_and_extract(url))
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data_dirs[data_name] = dl_path
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return [
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datasets.SplitGenerator(
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name=self.config.name,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={"dataset_paths": data_dirs},
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),
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]
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self, dataset_paths: dict[str, pathlib.Path]):
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yield self.config.name, dataset_paths
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data/{input_data.zip → image_data.zip}
RENAMED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 400326580
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version https://git-lfs.github.com/spec/v1
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oid sha256:ed9e347c43a846d4fb795d5c139fbb9dd3b1dc112df39a8ff90a79455b8d1420
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size 400326580
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data/segmentation/deepcell_output.zip
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 916593
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:1de1fc3a72b500f2862d194b1f2c832af9097cb5139c35d1c5fdda1fc7178473
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size 916593
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