fix timeframe filter

examples/definitions/concepts/ICUEncounter.yml

@@ -0,0 +1,15 @@
+name: ICUEncounter
+description: Period of time during which a patient is admitted to the ICU
+identifiers:
+  loinc: ''
+  snomed: ''
+unit: {}
+limits:
+  lower: ''
+  upper: ''
+
+sources:
+  - source: mimic
+    extractor: open_icu.steps.source.mimic.encounter.ICUEncounterExtractor
+    unit: {}
+    params: {}

examples/pipeline.ipynb

@@ -55,15 +55,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "d.data[\"aki_urineoutput_stage\"]"
+    "d.data[\"BodyWeight\"]"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "d.data[\"BodyWeight\"][\"identifier__coding\"].values[0]"
+   ]
   }
  ],
  "metadata": {

open_icu/steps/cohort/base.py

@@ -17,14 +17,15 @@ def __init__(
     ) -> None:
         super().__init__(configs=configs, concept_configs=concept_configs, parent=parent)
 
-        self._filter_conigs: list[CohortFilterConfig] = []
+        self._filter_configs: list[CohortFilterConfig] = []
         if isinstance(configs, list):
-            self._filter_conigs = configs
+            self._filter_configs = configs
         elif self._config_path is not None:
-            self._filter_conigs = self._read_config(self._config_path / "cohort", CohortFilterConfig)
+            self._filter_configs = self._read_config(self._config_path / "cohort", CohortFilterConfig)
 
     def filter(self, subject_data: SubjectData) -> bool:
-        for conf in self._filter_conigs:
+        for conf in self._filter_configs:
+            print(conf)
             if not all(concept in subject_data.data.keys() for concept in conf.concepts):
                 continue
 

open_icu/steps/cohort/filters/timeframe.py

@@ -2,10 +2,11 @@
 
 import pandas as pd
 from pandera.errors import SchemaError
+from pandera.typing import DataFrame
 
 from open_icu.steps.cohort.filters.base import CohortFilter
 from open_icu.types.base import SubjectData
-from open_icu.types.fhir import FHIRObjectEncounter, Period
+from open_icu.types.fhir.encounter import FHIREncounter
 
 
 class TimeframeFilter(CohortFilter):
@@ -32,16 +33,18 @@ def __init__(
         self._weeks = weeks
         self._strategy = strategy
 
-    def _get_delta(self, period: Period) -> pd.Timedelta:
-        return period["end"] - period["start"]
+    def _get_delta(self, df: DataFrame[FHIREncounter]) -> pd.Timedelta:
+        dt = df[FHIREncounter.actual_period__end] - df[FHIREncounter.actual_period__start]
+        assert isinstance(dt, pd.Timedelta)
+        return dt
 
     def filter(self, subject_data: SubjectData) -> bool:
         for concept in self.concepts:
             if (concept_data := subject_data.data.get(concept, None)) is None:
                 continue
 
             try:
-                FHIRObjectEncounter.validate(concept_data)
+                FHIREncounter.validate(concept_data)
             except SchemaError:
                 continue
 
@@ -56,8 +59,8 @@ def filter(self, subject_data: SubjectData) -> bool:
             )
 
             if self._strategy == "all":
-                return not (concept_data[FHIRObjectEncounter.actual_period].map(self._get_delta) >= td).all()
+                return not (concept_data.apply(self._get_delta, axis=1) >= td).all()
 
-            return not (concept_data[FHIRObjectEncounter.actual_period].map(self._get_delta) >= td).any()
+            return not (concept_data.apply(self._get_delta, axis=1) >= td).any()
 
         return False

open_icu/types/base.py

@@ -5,6 +5,19 @@
 
 
 class SubjectData(BaseModel):
+    """
+    Subject data model.
+
+    Attributes
+    ----------
+    id: str
+        Subject identifier.
+    source: str
+        Source of the data.
+    data: dict[str, DataFrame[FHIRSchema]]
+        Dataframes of Concept data extracted from the source for a subject.
+    """
+
     id: str
     source: str
     data: dict[str, DataFrame[FHIRSchema]]