├── LICENSE
├── README.md
└── perlin_noise
    ├── graph_noise.py
    └── perlin.py


/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2019 Supreme Sector
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


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/README.md:
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1 | # Python-Perlin-Noise
2 | An instantiation of the Python Perlin class allows you to generate Perlin Noise
3 | 
4 | ## Video
5 | https://youtu.be/QHdU1XRB9uw
6 | 


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/perlin_noise/graph_noise.py:
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 1 | import perlin
 2 | import matplotlib.pyplot as plt
 3 | 
 4 | noise=perlin.Perlin()
 5 | 
 6 | time=[i*0.01 for i in range(600)]
 7 | values=[noise.valueAt(i) for i in time]
 8 | 
 9 | plt.title("Perlin Noise")
10 | plt.xlabel("Time")
11 | plt.ylabel("Value")
12 | plt.plot(time, values)
13 | plt.show()
14 | 
15 | noise.discard(2.2)
16 | values = [noise.valueAt(i) if noise.valueAt(i) else 0 for i in time]
17 | plt.title("Perlin Noise - Discard")
18 | plt.xlabel("Time")
19 | plt.ylabel("Value")
20 | plt.plot(time, values)
21 | plt.show()
22 | 


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/perlin_noise/perlin.py:
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 1 | import random
 2 | 
 3 | class Perlin:
 4 |     def __init__(self):
 5 |         self.gradients = []
 6 |         self.lowerBound = 0
 7 | 
 8 | 
 9 |     def valueAt(self, t):
10 |         if(t<self.lowerBound):
11 |             print("ERROR: Input parameter out of bounds!")
12 |             return
13 |         # Add to gradients until it covers t
14 |         while t >= len(self.gradients)-1+self.lowerBound:
15 |             self.gradients.append(random.uniform(-1, 1))
16 | 
17 |         discarded = int(self.lowerBound) # getting number of gradients that have been discarded
18 |         # Compute products between surrounding gradients and distances from them
19 |         d1 = (t-t//1)
20 |         d2 = d1-1
21 |         a1 = self.gradients[(int)(t//1)-discarded]*d1
22 |         a2 = self.gradients[(int)(t//1+1)-discarded]*d2
23 | 
24 |         amt = self.__ease(d1)
25 | 
26 |         return self.__lerp(a1,a2,amt)
27 | 
28 |     def discard(self, amount):
29 |         gradientsToDiscard = int(amount+self.lowerBound%1)
30 |         self.gradients = self.gradients[gradientsToDiscard:]
31 |         self.lowerBound += amount
32 | 
33 |     def __ease(self, x):
34 |         return 6*x**5-15*x**4+10*x**3
35 | 
36 | 
37 |     def __lerp(self, start, stop, amt):
38 |         return amt*(stop-start)+start
39 | 


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