prototype fuzzy system engine

engine.py

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+from simpful import *
+
+FS = FuzzySystem()
+
+# Define fuzzy sets for the variable # Define fuzzy sets for the variable 
+# RELEASE_YEAR
+release_year_newer = FuzzySet(points=[[-68.0, 0.0],  [68.0, 1.0]], term="newer")
+release_year_similar = FuzzySet(points=[[-68.0, 0.0],  [0.0, 1.0],  [68.0, 0.0]], term="similar")
+release_year_older = FuzzySet(points=[[-68.0, 1.0], [68.0, 0.0]], term="older")
+FS.add_linguistic_variable("RELEASE_YEAR", LinguisticVariable( [release_year_newer, release_year_similar, release_year_older] ))
+
+# RUNTIME
+runtime_shorter = FuzzySet(points=[[-238.0, 0.0],  [238.0, 1.0]], term="shorter")
+runtime_similar = FuzzySet(points=[[-238.0, 0.0],  [0.0, 1.0],  [238.0, 0.0]], term="similar")
+runtime_longer = FuzzySet(points=[[-238.0, 1.0], [238.0, 0]], term="longer")
+FS.add_linguistic_variable("RUNTIME", LinguisticVariable( [runtime_shorter, runtime_similar, runtime_longer] ))
+
+# SEASONS
+seasons_less = FuzzySet(points=[[-42.0, 0.0],  [42.0, 1.0]], term="less")
+seasons_similar = FuzzySet(points=[[-42.0, 0.0],  [0.0, 1.0],  [42.0, 0.0]], term="similar")
+seasons_more = FuzzySet(points=[[-42.0, 1.0], [42.0, 0.0]], term="more")
+FS.add_linguistic_variable("SEASONS", LinguisticVariable( [seasons_less, seasons_similar, seasons_more] ))
+
+# GENRES
+genres_different = FuzzySet(points=[[-100.0, 0.0],  [100.0, 1.0]], term="different")
+genres_similar = FuzzySet(points=[[-100.0, 0.0],  [0.0, 1.0],  [100.0, 0.0]], term="similar")
+genres_same = FuzzySet(points=[[-100.0, 1.0], [100.0, 0.0]], term="same")
+FS.add_linguistic_variable("GENRES", LinguisticVariable( [genres_different, genres_similar, genres_same] ))
+
+# EMOTIONS
+emotions_different = FuzzySet(points=[[-4.0, 0.0],  [4.0, 1.0]], term="different")
+emotions_similar = FuzzySet(points=[[-4.0, 0.0],  [0.0, 1.0],  [4.0, 0.0]], term="similar")
+emotions_same = FuzzySet(points=[[-4.0, 1.0], [4.0, 0.0]], term="same")
+FS.add_linguistic_variable("EMOTIONS", LinguisticVariable( [emotions_different, emotions_similar, emotions_same] ))
+
+FS.set_crisp_output_value("low_recomendation", 0)
+FS.set_crisp_output_value("medium_recomendation", 50)
+FS.set_crisp_output_value("high_recomendation", 100)
+
+RULE1 = "IF (RELEASE_YEAR IS older) AND (RUNTIME IS longer) AND (SEASONS IS more) THEN (RECOMENDATION IS low_recomendation)"
+RULE2 = "IF (EMOTIONS IS different) AND (GENRES IS different) THEN (RECOMENDATION IS low_recomendation)"
+RULE3 = "IF (RELEASE_YEAR IS newer) AND (RUNTIME IS similar) AND (SEASONS IS less) THEN (RECOMENDATION IS medium_recomendation)"
+RULE4 = "IF (EMOTIONS IS similar) AND (GENRES IS similar) THEN (RECOMENDATION IS medium_recomendation)"
+RULE5 = "IF (RELEASE_YEAR IS similar) AND (RUNTIME IS similar) AND (SEASONS IS similar) AND (EMOTIONS IS same) AND (GENRES IS same) THEN (RECOMENDATION IS high_recomendation)"
+
+FS.add_rules([RULE1, RULE2, RULE3, RULE4, RULE5])
+
+FS.set_variable("RELEASE_YEAR", -12.0)
+FS.set_variable("RUNTIME", -10.0)
+FS.set_variable("SEASONS", -2.0)
+FS.set_variable("GENRES", 50.0)
+FS.set_variable("EMOTIONS", 1.0)
+
+print(FS.Sugeno_inference(["RECOMENDATION"]))

notes.txt

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+rok: 1999
+czas_trwania: 25
+sezony: 4
+gatunek: komedia, dramat
+emocje: funny 50, Sad 50
+
+nowszy, dluzszy, wiecej, podobny, podobne
+
+ROK PREMIERY
+
+nowszy = 
+taki_sam_jak_wybrany =
+starszy =
+
+CZAS TRWANIA
+
+krotszy =
+taki_sam_jak_wybrany =
+dluzszy =
+
+SEZONY
+
+mniej =
+podobnie_jak_wybrane =
+wiecej =
+
+GATUNEK
+
+inny =
+podobny =
+taki_sam_jak_wybrany =
+
+EMOCJE
+
+inne =
+podobne =
+takie_same_jak_wybrane =
+
+OCENA - sortuje
+
+OUTPUT rekomendacja - 
+(DEFUZZIFY srodek ciezkosci)
+wysoka = 
+srednia =
+mala =
+
+RULE 1: IF rok_premiery IS starszy AND czas_trwania IS dluzszy AND sezony IS wiecej THEN rekomendacja IS mala;
+RULE 2: IF emocje IS inne AND gatunek IS inny THEN rekomendacja IS mala;
+RULE 3: IF rok_premiery IS nowszy AND sezony IS mniej AND czas_trwania IS taki_sam_jak_wybrany THEN rekomendacja IS srednia;
+RULE 4: IF emocje IS podobne AND gatunek IS podobny THEN rekomendacja IS srednia;
+RULE 5: IF emocje IS takie_same_jak_wybrane AND gatunek IS taki_sam_jak_wybrany AND sezony IS podobnie_jak_wybrane 
+AND czas_trwania IS taki_sam_jak_wybrany AND rok_premiery IS taki_sam_jak_wybrany THEN rekomendacja IS wysoka;
+
+
+
+rok: 1999
+czas_trwania: 25
+sezony: 4
+gatunek: komedia, dramat
+emocje: funny 50, Sad 50
+
+nowszy, dluzszy, wiecej, podobny, podobne
+
+ROK PREMIERY
+
+nowszy = 
+taki_sam_jak_wybrany =
+starszy =
+
+CZAS TRWANIA
+
+krotszy =
+taki_sam_jak_wybrany =
+dluzszy =
+
+SEZONY
+
+mniej =
+podobnie_jak_wybrane =
+wiecej =
+
+GATUNEK
+
+inny =
+podobny =
+taki_sam_jak_wybrany =
+
+EMOCJE
+
+inne =
+podobne =
+takie_same_jak_wybrane =
+
+OCENA - sortuje
+
+OUTPUT rekomendacja - 
+(DEFUZZIFY srodek ciezkosci)
+wysoka = 
+srednia =
+mala =
+
+RULE 1: IF rok_premiery IS starszy AND czas_trwania IS dluzszy AND sezony IS wiecej THEN rekomendacja IS mala;
+RULE 2: IF emocje IS inne AND gatunek IS inny THEN rekomendacja IS mala;
+RULE 3: IF rok_premiery IS nowszy AND sezony IS mniej AND czas_trwania IS taki_sam_jak_wybrany THEN rekomendacja IS srednia;
+RULE 4: IF emocje IS podobne AND gatunek IS podobny THEN rekomendacja IS srednia;
+RULE 5: IF emocje IS takie_same_jak_wybrane AND gatunek IS taki_sam_jak_wybrany AND sezony IS podobnie_jak_wybrane 
+AND czas_trwania IS taki_sam_jak_wybrany AND rok_premiery IS taki_sam_jak_wybrany THEN rekomendacja IS wysoka;