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import csv |
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from typing import Optional, Dict, List, Tuple |
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from kerapu import clean_code, clean_date, clean_str, LEN_DIAGNOSE_CODE, LEN_SPECIALISME_CODE |
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class Diagnose: |
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""" |
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Klasse voor diagnosen. |
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""" |
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# ------------------------------------------------------------------------------------------------------------------ |
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__diagnose_tabel: Dict[Tuple[str, str], List[Dict[str, str]]] = {} |
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""" |
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De diagnosen referentietabel. |
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""" |
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# ------------------------------------------------------------------------------------------------------------------ |
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def __init__(self, specialisme_code: str, diagnose_code: str): |
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""" |
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Object constructor. |
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:param str specialisme_code: De code van het uitvoerend specialisme. |
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:param str diagnose_code: De code van deze diagnose. |
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""" |
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self.__specialisme_code: str = clean_code(specialisme_code, LEN_SPECIALISME_CODE) |
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""" |
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De code van het uitvoerend specialisme. |
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""" |
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self.__diagnose_code: str = clean_code(diagnose_code, LEN_DIAGNOSE_CODE) |
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""" |
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De code van deze diagnose. |
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""" |
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# ------------------------------------------------------------------------------------------------------------------ |
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@staticmethod |
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def __lees_diagnose_tabel(folder: str) -> None: |
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""" |
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Leest de diagnose referentietabel (opgeslagen in CSV). |
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:param str folder: De folder met alle goupertabellen. |
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""" |
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with open(folder + '/Diagnosen.csv', 'r', encoding='utf-8') as csv_file: |
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reader = csv.reader(csv_file) |
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regel_nummer = 0 |
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for regel in reader: |
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regel_nummer += 1 |
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# Sla de eerste regel met koppen over. |
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if regel_nummer == 1: |
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continue |
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specialisme_code = clean_code(regel[0], LEN_SPECIALISME_CODE) |
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diagnose_code = clean_code(regel[1], LEN_DIAGNOSE_CODE) |
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diagnose_attribute_code = clean_str(regel[3]) |
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diagnose_cluster01 = clean_str(regel[5]) |
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diagnose_cluster02 = clean_str(regel[6]) |
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diagnose_cluster03 = clean_str(regel[7]) |
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diagnose_cluster04 = clean_str(regel[8]) |
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diagnose_cluster05 = clean_str(regel[9]) |
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diagnose_cluster06 = clean_str(regel[10]) |
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begin_datum = clean_date(regel[11]) |
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eind_datum = clean_date(regel[12]) |
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sleutel = (specialisme_code, diagnose_code) |
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rij = {'specialisme_code': specialisme_code, |
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'diagnose_code': diagnose_code, |
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'diagnose_attribute_code': diagnose_attribute_code, |
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'diagnose_cluster1': diagnose_cluster01, |
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'diagnose_cluster2': diagnose_cluster02, |
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'diagnose_cluster3': diagnose_cluster03, |
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'diagnose_cluster4': diagnose_cluster04, |
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'diagnose_cluster5': diagnose_cluster05, |
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'diagnose_cluster6': diagnose_cluster06, |
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'begin_datum': begin_datum, |
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'eind_datum': eind_datum} |
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if sleutel not in Diagnose.__diagnose_tabel: |
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Diagnose.__diagnose_tabel[sleutel] = [] |
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Diagnose.__diagnose_tabel[sleutel].append(rij) |
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print("Aantal diagnosen: %d" % (regel_nummer - 1)) |
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# ------------------------------------------------------------------------------------------------------------------ |
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@staticmethod |
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def init_static(folder: str) -> None: |
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""" |
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Initialiseert alle statistische data. |
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:param str folder: De folder met alle goupertabellen. |
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""" |
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Diagnose.__lees_diagnose_tabel(folder) |
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# ------------------------------------------------------------------------------------------------------------------ |
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def __diagnose_referentie(self, datum: str) -> Optional[Dict]: |
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""" |
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Zoekt de referentie data voor deze diagnose in de diagnosen referentietabel. |
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:param str datum: De begindatum van het subtraject. |
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:rtype: dict[str,str] |
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""" |
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if (self.__specialisme_code, self.__diagnose_code) in self.__diagnose_tabel: |
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for referentie in self.__diagnose_tabel[(self.__specialisme_code, self.__diagnose_code)]: |
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if referentie['begin_datum'] <= datum <= referentie['eind_datum']: |
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# Een geldige referentie rij gevonden. |
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return referentie |
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# Er is geen geldige referentie rij gevonden. |
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return None |
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else: |
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return None |
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# ------------------------------------------------------------------------------------------------------------------ |
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def diagnose_attribute_aantal(self, diagnose_attribute_code: str, datum: str) -> int: |
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""" |
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Geeft het aantal malen (d.w.z. 0 of 1) data deze diagnose voldoet aan een (specialismecode, diagnosecode) |
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op een peildatum. |
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:param str diagnose_attribute_code: De attribuutcode voor de (specialismecode, diagnosecode) combinatie. |
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:param str datum: De peildatum. |
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:rtype: int |
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""" |
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referentie = self.__diagnose_referentie(datum) |
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if not referentie: |
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# De diagnose komt niet voor in de referentie tabel. Geef 0 terug. |
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return 0 |
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if referentie['diagnose_attribute_code'] == diagnose_attribute_code: |
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return 1 |
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return 0 |
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# ------------------------------------------------------------------------------------------------------------------ |
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def diagnose_cluster_aantal(self, cluster_code: str, cluster_nummer: int, datum: str) -> int: |
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""" |
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Geeft het aantal malen (d.w.z. 0 of 1) data deze diagnose voorkomt in een diagnosecodecluster op een peildatum. |
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:param str cluster_code: De diagnoseclustercode. |
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:param int cluster_nummer: De clusternummer (0..6). |
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:param str datum: De peildatum. |
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:rtype: int |
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""" |
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referentie = self.__diagnose_referentie(datum) |
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if not referentie: |
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# De diagnose komt niet voor in de referentie tabel. Geef 0 terug. |
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return 0 |
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if cluster_nummer == 0: |
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return 1 |
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if 1 <= cluster_nummer <= 6: |
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if referentie['diagnose_cluster%d' % cluster_nummer] == cluster_code: |
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# Deze diagnose komt voor in het gevraagde cluster. |
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return 1 |
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return 0 |
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raise RuntimeError("Onbekend clusternummer %d." % cluster_nummer) |
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# ---------------------------------------------------------------------------------------------------------------------- |
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SetBased /
py-kerapu
