mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-23 21:11:08 +00:00
9b5641d2d3
* balance parenthesis (add closing bracket) * Apply suggestions from code review --------- Co-authored-by: Tianyi Zheng <tianyizheng02@gmail.com>
104 lines
2.8 KiB
Plaintext
104 lines
2.8 KiB
Plaintext
"""
|
||
README, Author - Jigyasa Gandhi(mailto:jigsgandhi97@gmail.com)
|
||
Requirements:
|
||
- scikit-fuzzy
|
||
- numpy
|
||
- matplotlib
|
||
Python:
|
||
- 3.5
|
||
"""
|
||
import numpy as np
|
||
import skfuzzy as fuzz
|
||
|
||
if __name__ == "__main__":
|
||
# Create universe of discourse in Python using linspace ()
|
||
X = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
|
||
|
||
# Create two fuzzy sets by defining any membership function
|
||
# (trapmf(), gbellmf(), gaussmf(), etc).
|
||
abc1 = [0, 25, 50]
|
||
abc2 = [25, 50, 75]
|
||
young = fuzz.membership.trimf(X, abc1)
|
||
middle_aged = fuzz.membership.trimf(X, abc2)
|
||
|
||
# Compute the different operations using inbuilt functions.
|
||
one = np.ones(75)
|
||
zero = np.zeros((75,))
|
||
# 1. Union = max(µA(x), µB(x))
|
||
union = fuzz.fuzzy_or(X, young, X, middle_aged)[1]
|
||
# 2. Intersection = min(µA(x), µB(x))
|
||
intersection = fuzz.fuzzy_and(X, young, X, middle_aged)[1]
|
||
# 3. Complement (A) = (1 - min(µA(x)))
|
||
complement_a = fuzz.fuzzy_not(young)
|
||
# 4. Difference (A/B) = min(µA(x),(1- µB(x)))
|
||
difference = fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
|
||
# 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
|
||
alg_sum = young + middle_aged - (young * middle_aged)
|
||
# 6. Algebraic Product = (µA(x) * µB(x))
|
||
alg_product = young * middle_aged
|
||
# 7. Bounded Sum = min[1,(µA(x), µB(x))]
|
||
bdd_sum = fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
|
||
# 8. Bounded difference = min[0,(µA(x), µB(x))]
|
||
bdd_difference = fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]
|
||
|
||
# max-min composition
|
||
# max-product composition
|
||
|
||
# Plot each set A, set B and each operation result using plot() and subplot().
|
||
from matplotlib import pyplot as plt
|
||
|
||
plt.figure()
|
||
|
||
plt.subplot(4, 3, 1)
|
||
plt.plot(X, young)
|
||
plt.title("Young")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 2)
|
||
plt.plot(X, middle_aged)
|
||
plt.title("Middle aged")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 3)
|
||
plt.plot(X, union)
|
||
plt.title("union")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 4)
|
||
plt.plot(X, intersection)
|
||
plt.title("intersection")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 5)
|
||
plt.plot(X, complement_a)
|
||
plt.title("complement_a")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 6)
|
||
plt.plot(X, difference)
|
||
plt.title("difference a/b")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 7)
|
||
plt.plot(X, alg_sum)
|
||
plt.title("alg_sum")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 8)
|
||
plt.plot(X, alg_product)
|
||
plt.title("alg_product")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 9)
|
||
plt.plot(X, bdd_sum)
|
||
plt.title("bdd_sum")
|
||
plt.grid(True)
|
||
|
||
plt.subplot(4, 3, 10)
|
||
plt.plot(X, bdd_difference)
|
||
plt.title("bdd_difference")
|
||
plt.grid(True)
|
||
|
||
plt.subplots_adjust(hspace=0.5)
|
||
plt.show()
|