"""Splice Dataset""" from typing import List from functools import partial import datasets import pandas VERSION = datasets.Version("1.0.0") _ENCODING_DICS = {} DESCRIPTION = "Splice dataset." _HOMEPAGE = "https://archive-beta.ics.uci.edu/dataset/69/molecular+biology+splice+junction+gene+sequences" _URLS = ("https://archive-beta.ics.uci.edu/dataset/69/molecular+biology+splice+junction+gene+sequences") _CITATION = """ @misc{misc_molecular_biology_(splice-junction_gene_sequences)_69, title = {{Molecular Biology (Splice-junction Gene Sequences)}}, year = {1992}, howpublished = {UCI Machine Learning Repository}, note = {{DOI}: \\url{10.24432/C5M888}} } """ # Dataset info urls_per_split = { "train": "https://huggingface.co/datasets/mstz/splice/raw/main/splice.data" } features_types_per_config = { "splice": { "position_0": datasets.Value("string"), "position_1": datasets.Value("string"), "position_2": datasets.Value("string"), "position_3": datasets.Value("string"), "position_4": datasets.Value("string"), "position_5": datasets.Value("string"), "position_6": datasets.Value("string"), "position_7": datasets.Value("string"), "position_8": datasets.Value("string"), "position_9": datasets.Value("string"), "position_10": datasets.Value("string"), "position_11": datasets.Value("string"), "position_12": datasets.Value("string"), "position_13": datasets.Value("string"), "position_14": datasets.Value("string"), "position_15": datasets.Value("string"), "position_16": datasets.Value("string"), "position_17": datasets.Value("string"), "position_18": datasets.Value("string"), "position_19": datasets.Value("string"), "position_20": datasets.Value("string"), "position_21": datasets.Value("string"), "position_22": datasets.Value("string"), "position_23": datasets.Value("string"), "position_24": datasets.Value("string"), "position_25": datasets.Value("string"), "position_26": datasets.Value("string"), "position_27": datasets.Value("string"), "position_28": datasets.Value("string"), "position_29": datasets.Value("string"), "position_30": datasets.Value("string"), "position_31": datasets.Value("string"), "position_32": datasets.Value("string"), "position_33": datasets.Value("string"), "position_34": datasets.Value("string"), "position_35": datasets.Value("string"), "position_36": datasets.Value("string"), "position_37": datasets.Value("string"), "position_38": datasets.Value("string"), "position_39": datasets.Value("string"), "position_40": datasets.Value("string"), "position_41": datasets.Value("string"), "position_42": datasets.Value("string"), "position_43": datasets.Value("string"), "position_44": datasets.Value("string"), "position_45": datasets.Value("string"), "position_46": datasets.Value("string"), "position_47": datasets.Value("string"), "position_48": datasets.Value("string"), "position_49": datasets.Value("string"), "position_50": datasets.Value("string"), "position_51": datasets.Value("string"), "position_52": datasets.Value("string"), "position_53": datasets.Value("string"), "position_54": datasets.Value("string"), "position_55": datasets.Value("string"), "position_56": datasets.Value("string"), "position_57": datasets.Value("string"), "position_58": datasets.Value("string"), "position_59": datasets.Value("string"), "class": datasets.ClassLabel(num_classes=3, names=("EI", "IE", "N")) }, "splice_EI": { "position_0": datasets.Value("string"), "position_1": datasets.Value("string"), "position_2": datasets.Value("string"), "position_3": datasets.Value("string"), "position_4": datasets.Value("string"), "position_5": datasets.Value("string"), "position_6": datasets.Value("string"), "position_7": datasets.Value("string"), "position_8": datasets.Value("string"), "position_9": datasets.Value("string"), "position_10": datasets.Value("string"), "position_11": datasets.Value("string"), "position_12": datasets.Value("string"), "position_13": datasets.Value("string"), "position_14": datasets.Value("string"), "position_15": datasets.Value("string"), "position_16": datasets.Value("string"), "position_17": datasets.Value("string"), "position_18": datasets.Value("string"), "position_19": datasets.Value("string"), "position_20": datasets.Value("string"), "position_21": datasets.Value("string"), "position_22": datasets.Value("string"), "position_23": datasets.Value("string"), "position_24": datasets.Value("string"), "position_25": datasets.Value("string"), "position_26": datasets.Value("string"), "position_27": datasets.Value("string"), "position_28": datasets.Value("string"), "position_29": datasets.Value("string"), "position_30": datasets.Value("string"), "position_31": datasets.Value("string"), "position_32": datasets.Value("string"), "position_33": datasets.Value("string"), "position_34": datasets.Value("string"), "position_35": datasets.Value("string"), "position_36": datasets.Value("string"), "position_37": datasets.Value("string"), "position_38": datasets.Value("string"), "position_39": datasets.Value("string"), "position_40": datasets.Value("string"), "position_41": datasets.Value("string"), "position_42": datasets.Value("string"), "position_43": datasets.Value("string"), "position_44": datasets.Value("string"), "position_45": datasets.Value("string"), "position_46": datasets.Value("string"), "position_47": datasets.Value("string"), "position_48": datasets.Value("string"), "position_49": datasets.Value("string"), "position_50": datasets.Value("string"), "position_51": datasets.Value("string"), "position_52": datasets.Value("string"), "position_53": datasets.Value("string"), "position_54": datasets.Value("string"), "position_55": datasets.Value("string"), "position_56": datasets.Value("string"), "position_57": datasets.Value("string"), "position_58": datasets.Value("string"), "position_59": datasets.Value("string"), "is_ei": datasets.ClassLabel(num_classes=2, names=("no", "yes")) }, "splice_IE": { "position_0": datasets.Value("string"), "position_1": datasets.Value("string"), "position_2": datasets.Value("string"), "position_3": datasets.Value("string"), "position_4": datasets.Value("string"), "position_5": datasets.Value("string"), "position_6": datasets.Value("string"), "position_7": datasets.Value("string"), "position_8": datasets.Value("string"), "position_9": datasets.Value("string"), "position_10": datasets.Value("string"), "position_11": datasets.Value("string"), "position_12": datasets.Value("string"), "position_13": datasets.Value("string"), "position_14": datasets.Value("string"), "position_15": datasets.Value("string"), "position_16": datasets.Value("string"), "position_17": datasets.Value("string"), "position_18": datasets.Value("string"), "position_19": datasets.Value("string"), "position_20": datasets.Value("string"), "position_21": datasets.Value("string"), "position_22": datasets.Value("string"), "position_23": datasets.Value("string"), "position_24": datasets.Value("string"), "position_25": datasets.Value("string"), "position_26": datasets.Value("string"), "position_27": datasets.Value("string"), "position_28": datasets.Value("string"), "position_29": datasets.Value("string"), "position_30": datasets.Value("string"), "position_31": datasets.Value("string"), "position_32": datasets.Value("string"), "position_33": datasets.Value("string"), "position_34": datasets.Value("string"), "position_35": datasets.Value("string"), "position_36": datasets.Value("string"), "position_37": datasets.Value("string"), "position_38": datasets.Value("string"), "position_39": datasets.Value("string"), "position_40": datasets.Value("string"), "position_41": datasets.Value("string"), "position_42": datasets.Value("string"), "position_43": datasets.Value("string"), "position_44": datasets.Value("string"), "position_45": datasets.Value("string"), "position_46": datasets.Value("string"), "position_47": datasets.Value("string"), "position_48": datasets.Value("string"), "position_49": datasets.Value("string"), "position_50": datasets.Value("string"), "position_51": datasets.Value("string"), "position_52": datasets.Value("string"), "position_53": datasets.Value("string"), "position_54": datasets.Value("string"), "position_55": datasets.Value("string"), "position_56": datasets.Value("string"), "position_57": datasets.Value("string"), "position_58": datasets.Value("string"), "position_59": datasets.Value("string"), "is_ie": datasets.ClassLabel(num_classes=2, names=("no", "yes")) }, "splice_N": { "position_0": datasets.Value("string"), "position_1": datasets.Value("string"), "position_2": datasets.Value("string"), "position_3": datasets.Value("string"), "position_4": datasets.Value("string"), "position_5": datasets.Value("string"), "position_6": datasets.Value("string"), "position_7": datasets.Value("string"), "position_8": datasets.Value("string"), "position_9": datasets.Value("string"), "position_10": datasets.Value("string"), "position_11": datasets.Value("string"), "position_12": datasets.Value("string"), "position_13": datasets.Value("string"), "position_14": datasets.Value("string"), "position_15": datasets.Value("string"), "position_16": datasets.Value("string"), "position_17": datasets.Value("string"), "position_18": datasets.Value("string"), "position_19": datasets.Value("string"), "position_20": datasets.Value("string"), "position_21": datasets.Value("string"), "position_22": datasets.Value("string"), "position_23": datasets.Value("string"), "position_24": datasets.Value("string"), "position_25": datasets.Value("string"), "position_26": datasets.Value("string"), "position_27": datasets.Value("string"), "position_28": datasets.Value("string"), "position_29": datasets.Value("string"), "position_30": datasets.Value("string"), "position_31": datasets.Value("string"), "position_32": datasets.Value("string"), "position_33": datasets.Value("string"), "position_34": datasets.Value("string"), "position_35": datasets.Value("string"), "position_36": datasets.Value("string"), "position_37": datasets.Value("string"), "position_38": datasets.Value("string"), "position_39": datasets.Value("string"), "position_40": datasets.Value("string"), "position_41": datasets.Value("string"), "position_42": datasets.Value("string"), "position_43": datasets.Value("string"), "position_44": datasets.Value("string"), "position_45": datasets.Value("string"), "position_46": datasets.Value("string"), "position_47": datasets.Value("string"), "position_48": datasets.Value("string"), "position_49": datasets.Value("string"), "position_50": datasets.Value("string"), "position_51": datasets.Value("string"), "position_52": datasets.Value("string"), "position_53": datasets.Value("string"), "position_54": datasets.Value("string"), "position_55": datasets.Value("string"), "position_56": datasets.Value("string"), "position_57": datasets.Value("string"), "position_58": datasets.Value("string"), "position_59": datasets.Value("string"), "is_n": datasets.ClassLabel(num_classes=2, names=("no", "yes")) } } features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config} class SpliceConfig(datasets.BuilderConfig): def __init__(self, **kwargs): super(SpliceConfig, self).__init__(version=VERSION, **kwargs) self.features = features_per_config[kwargs["name"]] class Splice(datasets.GeneratorBasedBuilder): # dataset versions DEFAULT_CONFIG = "splice1" BUILDER_CONFIGS = [ SpliceConfig(name="splice", description="Splice for multiclass classification."), SpliceConfig(name="splice_IE", description="Splice for binary classification."), SpliceConfig(name="splice_EI", description="Splice for binary classification."), SpliceConfig(name="splice_N", description="Splice for binary classification."), ] def _info(self): info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE, features=features_per_config[self.config.name]) return info def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: downloads = dl_manager.download_and_extract(urls_per_split) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}), ] def _generate_examples(self, filepath: str): data = pandas.read_csv(filepath) data = self.preprocess(data) for row_id, row in data.iterrows(): data_row = dict(row) yield row_id, data_row def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame: if self.config.name == "splice_IE": data["class"] = data["class"].apply(lambda x: 1 if x == "IE" else 0) data = data.rename(columns={"class": "is_ie"}) elif self.config.name == "splice_EI": data["class"] = data["class"].apply(lambda x: 1 if x == "EI" else 0) data = data.rename(columns={"class": "is_ei"}) elif self.config.name == "splice_N": data["class"] = data["class"].apply(lambda x: 1 if x == "N" else 0) data = data.rename(columns={"class": "is_n"}) else: data["class"] = data["class"].apply(lambda x: { "EI": 0, "IE": 1, "N": 2, }[x]) for feature in _ENCODING_DICS: encoding_function = partial(self.encode, feature) data.loc[:, feature] = data[feature].apply(encoding_function) return data[list(features_types_per_config[self.config.name].keys())] def encode(self, feature, value): if feature in _ENCODING_DICS: return _ENCODING_DICS[feature][value] raise ValueError(f"Unknown feature: {feature}")