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pythonmatplotlibfractals

How to visualize fractals in python

This is the code for generating the fractals. 

import matplotlib.pyplot as plt

def makes(self, fractal):
    if (fractal == "SierpinskiTriangle"):
        SierpinskiTriangle(self.dimensions)
        for i in range(len(SierpinskiTriangle.verticies)):
            plotPoint(i, self.vertexColor, self.vertexRadius)
        for i in range(SierpinskiTriangle.numPoints):
            listVertices = SierpinskiTriangle.verticies
            randVert = randint(0, len(listVertices)-1)
            newVertexPoint = listVertices[randVert]
            m1 = Point.midpt(m1, newVertexPoint)
            self.plot(m1)

    elif (fractal == "SierpinskiCarpet"):
        SierpinskiCarpet(self.dimensions)
        for i in range(len(SierpinskiCarpet.verticies)):
            plotPoint(i, self.vertexColor, self.vertexRadius)
        for i in range(SierpinskiCarpet.numPoints):
            listVertices = SierpinskiCarpet
            randVert = randint(0, len(listVertices)-1)
            newVertexPoint = listVertices[randVert]
            m1 = Point.midpt(m1, newVertexPoint)
            self.plot(m1)

    else:
        Pentagon(self.dimensions)
        for i in range(len(Pentagon.verticies)):
            plotPoint(i, self.vertexColor, self.vertexRadius)
        for i in range(Pentagon.numPoints):
            listVertices = SierpinskiCarpet
            randVert = randint(0, len(listVertices)-1)
            newVertexPoint = listVertices[randVert]
            m1 = Point.midpt(m1, newVertexPoint)
            self.plot(m1)

At the end I don't know how to visualize the fractals.
I think it has to do with matplot.lib but I'm not sure how

Solution

  • Although matplotplib is primarily suited for plotting graphs, but you can draw points and polygons using it if you wish as well; see also: How to draw a triangle using matplotlib.pyplot based on 3 dots (x,y) in 2D?

    For instance, to compose a Sierpinski triangle from polygons, and plot those polygons onto a figure:

    import numpy as np
import matplotlib.pyplot as plt

MAX_LEVEL = 6


def sierpinski(p1, p2, p3, level=0):
    if level >= MAX_LEVEL:
        yield plt.Polygon([p1, p2, p3], color='red')
        return

    yield from sierpinski(p1, (p1+p2) / 2, (p1+p3) / 2, level+1)
    yield from sierpinski((p1+p2) / 2, p2, (p2+p3) / 2, level+1)
    yield from sierpinski((p1+p3) / 2, (p2+p3) / 2, p3, level+1)


plt.figure()
plt.scatter([0, 0, 10, 10], [0, 10, 0, 10], color='blue')

for patch in sierpinski(
        np.array([1.0, 1.0]), np.array([9.0, 1.0]), np.array([5.0, 9.0])):
    plt.gca().add_patch(patch)

plt.show()

    The above code generates the following image output for me:

    matplotlib output