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fuzzy operations added (#1310)
* fuzzy operations added * fuzzy inference system added * unnecessary files removed * requirements added * Modified requirements for travis ci * Modified requirements for travis ci * Add scikit-fuzzy to requirements.txt
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fuzzy_logic/fuzzy_operations.py
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fuzzy_logic/fuzzy_operations.py
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"""README, Author - Jigyasa Gandhi(mailto:jigsgandhi97@gmail.com)
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Requirements:
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- scikit-fuzzy
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- numpy
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- matplotlib
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Python:
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- 3.5
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"""
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# Create universe of discourse in python using linspace ()
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import numpy as np
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X = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
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# Create two fuzzy sets by defining any membership function (trapmf(), gbellmf(),gaussmf(), etc).
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import skfuzzy as fuzz
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abc1=[0,25,50]
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abc2=[25,50,75]
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young = fuzz.membership.trimf(X,abc1)
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middle_aged = fuzz.membership.trimf(X,abc2)
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# Compute the different operations using inbuilt functions.
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one = np.ones(75)
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zero = np.zeros((75,))
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#1. Union = max(µA(x), µB(x))
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union = fuzz.fuzzy_or(X, young, X, middle_aged)[1]
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#2. Intersection = min(µA(x), µB(x))
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intersection = fuzz.fuzzy_and(X, young, X, middle_aged)[1]
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#3. Complement (A) = (1- min(µA(x))
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complement_a = fuzz.fuzzy_not(young)
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#4. Difference (A/B) = min(µA(x),(1- µB(x)))
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difference = fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
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#5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
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alg_sum = young + middle_aged - (young*middle_aged)
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#6. Algebraic Product = (µA(x) * µB(x))
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alg_product = young*middle_aged
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#7. Bounded Sum = min[1,(µA(x), µB(x))]
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bdd_sum = fuzz.fuzzy_and(X, one, X, young+middle_aged)[1]
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#8. Bounded difference = min[0,(µA(x), µB(x))]
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bdd_difference = fuzz.fuzzy_or(X, zero, X, young-middle_aged)[1]
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#max-min composition
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#max-product composition
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# Plot each set A, set B and each operation result using plot() and subplot().
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import matplotlib.pyplot as plt
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plt.figure()
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plt.subplot(4,3,1)
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plt.plot(X,young)
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plt.title("Young")
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plt.grid(True)
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plt.subplot(4,3,2)
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plt.plot(X,middle_aged)
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plt.title("Middle aged")
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plt.grid(True)
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plt.subplot(4,3,3)
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plt.plot(X,union)
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plt.title("union")
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plt.grid(True)
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plt.subplot(4,3,4)
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plt.plot(X,intersection)
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plt.title("intersection")
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plt.grid(True)
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plt.subplot(4,3,5)
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plt.plot(X,complement_a)
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plt.title("complement_a")
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plt.grid(True)
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plt.subplot(4,3,6)
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plt.plot(X,difference)
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plt.title("difference a/b")
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plt.grid(True)
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plt.subplot(4,3,7)
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plt.plot(X,alg_sum)
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plt.title("alg_sum")
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plt.grid(True)
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plt.subplot(4,3,8)
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plt.plot(X,alg_product)
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plt.title("alg_product")
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plt.grid(True)
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plt.subplot(4,3,9)
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plt.plot(X,bdd_sum)
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plt.title("bdd_sum")
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plt.grid(True)
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plt.subplot(4,3,10)
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plt.plot(X,bdd_difference)
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plt.title("bdd_difference")
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plt.grid(True)
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plt.subplots_adjust(hspace = 0.5)
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plt.show()
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@ -8,6 +8,7 @@ pandas
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pillow
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pytest
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requests
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scikit-fuzzy
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sklearn
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sympy
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tensorflow
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