Delete Mimic4Dataset.py

Mimic4Dataset.py

@@ -1,270 +0,0 @@
-import csv
-import json
-import os
-import pandas as pd
-import datasets
-import sys
-import pickle
-import subprocess
-import shutil
-from urllib.request import urlretrieve
-
-_DESCRIPTION = """\
-Dataset for mimic4 data, by default for the Mortality task.
-Available tasks are: Mortality, Length of Stay, Readmission, Phenotype.
-The data is extracted from the mimic4 database using this pipeline: 'https://github.com/healthylaife/MIMIC-IV-Data-Pipeline/tree/main'
-mimic path should have this form : "absolute/path/to/mimic4data/mimiciv/2.2"
-"""
-
-_HOMEPAGE = "https://huggingface.co/datasets/thbndi/Mimic4Dataset"
-_CITATION = "https://proceedings.mlr.press/v193/gupta22a.html"
-_URL = "https://github.com/healthylaife/MIMIC-IV-Data-Pipeline"
-_DATA_GEN = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/data_generation_icu_modify.py'
-_COHORT = 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/cohort.py'
-_CONFIG_URLS = {'los' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/blob/main/config/los.config',
-                'mortality' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/los.config',
-                'phenotype' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/phenotype.config',
-                'readmission' : 'https://huggingface.co/datasets/thbndi/Mimic4Dataset/resolve/main/config/readmission.config'
-        }
-class Mimic4DatasetConfig(datasets.BuilderConfig):
-    """BuilderConfig for Mimic4Dataset."""
-
-    def __init__(
-        self,
-        **kwargs,
-    ):
-        super().__init__(**kwargs)
-        
-class Mimic4Dataset(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    def __init__(self, **kwargs):
-        self.mimic_path = kwargs.pop("mimic_path", None)
-        if self.mimic_path is None:
-            raise ValueError("You must specify the path of the mimic4 data")
-        if not os.path.exists(self.mimic_path):
-            raise ValueError("The path of the mimic4 data does not exist")
-        
-        self.config_path = kwargs.pop("config_path",None)
-        super().__init__(**kwargs)
-        
-
-    BUILDER_CONFIGS = [
-        Mimic4DatasetConfig(
-            name="Phenotype",
-            version=VERSION,
-            description="Dataset for mimic4 Phenotype task"
-        ),
-        Mimic4DatasetConfig(
-            name="Readmission",
-            version=VERSION,
-            description="Dataset for mimic4 Readmission task"
-        ),
-        Mimic4DatasetConfig(
-            name="Length of Stay",
-            version=VERSION,
-            description="Dataset for mimic4 Length of Stay task"
-        ),
-        Mimic4DatasetConfig(
-            name="Mortality",
-            version=VERSION,
-            description="Dataset for mimic4 Mortality task"
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = "Mortality"
-
-    def _info(self):
-
-        features = datasets.Features(
-            {
-                "label": datasets.ClassLabel(names=["0", "1"]),
-                "gender": datasets.Value("string"),
-                "ethnicity": datasets.Value("string"),
-                "age": datasets.Value("int32"),
-                "COND": datasets.Sequence(datasets.Value("string")),
-                "MEDS": {
-                            "signal": 
-                                {
-                                    "id": datasets.Sequence(datasets.Value("int32")),
-                                    "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                }
-                            ,
-                            "rate": 
-                                {
-                                    "id": datasets.Sequence(datasets.Value("int32")),
-                                    "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                }
-                            ,
-                            "amount": 
-                                {
-                                    "id": datasets.Sequence(datasets.Value("int32")),
-                                    "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                }
-                            
-                        },
-                "PROC":  {
-                            "id": datasets.Sequence(datasets.Value("int32")),
-                            "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                },
-                "CHART":
-                    {
-                        "signal" : {
-                            "id": datasets.Sequence(datasets.Value("int32")),
-                            "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                },
-                        "val" : {
-                            "id": datasets.Sequence(datasets.Value("int32")),
-                            "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                },
-                    },
-                "OUT":  {
-                            "id": datasets.Sequence(datasets.Value("int32")),
-                            "value": datasets.Sequence(datasets.Sequence(datasets.Value("float32")))
-                                },
-                
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager()):
-        if self.config.name == 'Phenotype' and self.config_path is None : self.config_path = _CONFIG_URLS['phenotype'] 
-        if self.config.name == 'Readmission' and self.config_path is None : self.config_path = _CONFIG_URLS['readmission'] 
-        if self.config.name == 'Length of Stay' and self.config_path is None : self.config_path = _CONFIG_URLS['los'] 
-        if self.config.name == 'Mortality' and self.config_path is None : self.config_path = _CONFIG_URLS['mortality']
-
-        repo_url='https://github.com/healthylaife/MIMIC-IV-Data-Pipeline'
-        if os.path.exists(os.path.dirname(os.path.abspath('MIMIC-IV-Data-Pipeline-main'))):
-            path_bench = os.path.dirname(os.path.abspath('MIMIC-IV-Data-Pipeline-main'))+'/MIMIC-IV-Data-Pipeline-main'
-        else:
-            repodir = os.getcwd()
-            path_bench = repodir+'/MIMIC-IV-Data-Pipeline-main'
-            subprocess.run(["git", "clone", repo_url, path_bench])
-        
-        
-        if self.config_path[0:4] == 'http':
-            file_path, head = urlretrieve(self.config_path)
-        else :
-            file_path = self.config_path
-        
-        conf=path_bench+'/config/'+file_path.split('/')[-1]
-        print(conf)
-        
-        if not os.path.exists(conf):
-            shutil.move(file_path, path_bench+'/config')
-        
-
-        if not os.path.exists(path_bench+'/model/data_generation_icu_modify.py'):
-            file_path, head = urlretrieve(_DATA_GEN, "data_generation_icu_modify.py")
-            shutil.move(file_path, path_bench+'/model')
-        
-        if not os.path.exists(path_bench+'/cohort.py'):
-            file_path, head = urlretrieve(_COHORT, "cohort.py")
-            shutil.move(file_path, path_bench)
-        
-        data_dir = path_bench + "/data/dataDic"
-        sys.path.append(path_bench)
-        config = self.config_path.split('/')[-1]
-        script = 'python cohort.py '+ self.config.name +" "+ self.mimic_path+ " "+path_bench+ " "+config
-        #print(script)
-        #os.system(script)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir}),
-        ]
-
-
-    def _generate_examples(self, filepath):
-        with open(filepath, 'rb') as fp:
-            dataDic = pickle.load(fp)
-        for hid, data in dataDic.items():
-            proc_features = data['Proc']
-            chart_features = data['Chart']
-            meds_features = data['Med']
-            out_features = data['Out']
-            cond_features = data['Cond']['fids']
-            eth= data['ethnicity']
-            age = data['age']
-            gender = data['gender']
-            label = data['label']
-            
-            items = list(proc_features.keys())
-            values =[proc_features[i] for i in items ]
-            procs = {"id" : items,
-                  "value": values}
-            
-            items_outs = list(out_features.keys())
-            values_outs =[out_features[i] for i in items_outs ]
-            outs = {"id" : items_outs,
-                  "value": values_outs}
-
-            #chart signal
-            if ('signal' in chart_features):
-                items_chart_sig = list(chart_features['signal'].keys())
-                values_chart_sig =[chart_features['signal'][i] for i in items_chart_sig ]
-                chart_sig = {"id" : items_chart_sig,
-                        "value": values_chart_sig}
-            else:
-                chart_sig = {"id" : [],
-                        "value": []}
-            #chart val
-            if ('val' in chart_features):
-                items_chart_val = list(chart_features['val'].keys())
-                values_chart_val =[chart_features['val'][i] for i in items_chart_val ]
-                chart_val = {"id" : items_chart_val,
-                        "value": values_chart_val}
-            else:
-                chart_val = {"id" : [],
-                        "value": []}
-                
-            charts = {"signal" : chart_sig,
-                    "val" : chart_val}
-
-            #meds signal
-            if ('signal' in meds_features):
-                items_meds_sig = list(meds_features['signal'].keys())
-                values_meds_sig =[meds_features['signal'][i] for i in items_meds_sig ]
-                meds_sig = {"id" : items_meds_sig,
-                    "value": values_meds_sig}
-            else:
-                meds_sig = {"id" : [],
-                    "value": []}
-            #meds rate
-            if ('rate' in meds_features):
-                items_meds_rate = list(meds_features['rate'].keys())
-                values_meds_rate =[meds_features['rate'][i] for i in items_meds_rate ]
-                meds_rate = {"id" : items_meds_rate,
-                        "value": values_meds_rate}
-            else:
-                meds_rate = {"id" : [],
-                        "value": []}
-            #meds amount
-            if ('amount' in meds_features):
-                items_meds_amount = list(meds_features['amount'].keys())
-                values_meds_amount =[meds_features['amount'][i] for i in items_meds_amount ]
-                meds_amount = {"id" : items_meds_amount,
-                        "value": values_meds_amount}
-            else:
-                meds_amount = {"id" : [],
-                        "value": []}
-            
-            meds = {"signal" : meds_sig,
-                    "rate" : meds_rate,
-                    "amount" : meds_amount}
-            
-            yield int(hid), {
-                "label" : label,
-                "gender" : gender,
-                "ethnicity" : eth,
-                "age" : age,
-                "COND" : cond_features,
-                "PROC" : procs,
-                "CHART" : charts,
-                "OUT" : outs,
-                "MEDS" : meds
-            }
-