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166 changes: 166 additions & 0 deletions fractals/julia_sets.py
Original file line number Diff line number Diff line change
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"""Author Alexandre De Zotti

Draws Julia sets of quadratic polynomials and exponential maps.
More specifically, this iterates the function a fixed number of times
then plots whether the absolute value of the last iterate is greater than
a fixed threshold (named "escape radius"). For the exponential map this is not
really an escape radius but rather a convenient way to approximate the Julia
set with bounded orbits.

The examples presented here are:
- The Cauliflower Julia set, see e.g.
https://en.wikipedia.org/wiki/File:Julia_z2%2B0,25.png
- Other examples from https://en.wikipedia.org/wiki/Julia_set
- An exponential map Julia set, ambiantly homeomorphic to the examples in
http://www.math.univ-toulouse.fr/~cheritat/GalII/galery.html
and
https://ddd.uab.cat/pub/pubmat/02141493v43n1/02141493v43n1p27.pdf
"""

from typing import Any, Callable

import numpy
from matplotlib import pyplot

c_cauliflower = 0.25 + 0.0j
c_polynomial_1 = -0.4 + 0.6j
c_polynomial_2 = -0.1 + 0.651j
c_exponential = -2.0
nb_iterations = 56
window_size = 2.0
nb_pixels = 666


def eval_exponential(c: complex, z: numpy.ndarray) -> numpy.ndarray:
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Please provide descriptive name for the parameter: c

Please provide descriptive name for the parameter: z

"""
>>> eval_exponential(0, 0)
1.0
"""
return numpy.exp(z) + c


def eval_quadratic_polynomial(c: complex, z: numpy.ndarray) -> numpy.ndarray:
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Please provide descriptive name for the parameter: c

Please provide descriptive name for the parameter: z

"""
>>> eval_quadratic_polynomial(0, 2)
4
>>> eval_quadratic_polynomial(-1, 1)
0
>>> eval_quadratic_polynomial(1.j, 0)
1j
"""
return z * z + c


def prepare_grid(window_size: float, nb_pixels: int) -> numpy.ndarray:
"""
Create a grid of complex values of size nb_pixels*nb_pixels with real and
imaginary parts ranging from -window_size to window_size (inclusive).
Returns a numpy array.

>>> prepare_grid(1,3)
array([[-1.-1.j, -1.+0.j, -1.+1.j],
[ 0.-1.j, 0.+0.j, 0.+1.j],
[ 1.-1.j, 1.+0.j, 1.+1.j]])
"""
x = numpy.linspace(-window_size, window_size, nb_pixels)
x = x.reshape((nb_pixels, 1))
y = numpy.linspace(-window_size, window_size, nb_pixels)
y = y.reshape((1, nb_pixels))
return x + 1.0j * y


def iterate_function(
eval_function: Callable[[Any, numpy.ndarray], numpy.ndarray],
function_params: Any,
nb_iterations: int,
z_0: numpy.ndarray,
infinity: float = None,
) -> numpy.ndarray:
"""
Iterate the function "eval_function" exactly nb_iterations times.
The first argument of the function is a parameter which is contained in
function_params. The variable z_0 is an array that contains the initial
values to iterate from.
This function returns the final iterates.

>>> iterate_function(eval_quadratic_polynomial, 0, 3, numpy.array([0,1,2]))
array([ 0, 1, 256])
"""

z_n = z_0
for i in range(nb_iterations):
z_n = eval_function(function_params, z_n)
if infinity is not None:
numpy.nan_to_num(z_n, copy=False, nan=infinity)
z_n[abs(z_n) == numpy.inf] = infinity
return z_n


def show_results(
function_label: str,
function_params: Any,
escape_radius: float,
z_final: numpy.ndarray,
) -> None:
"""
Plots of whether the absolute value of z_final is greater than
the value of escape_radius. Adds the function_label and function_params to
the title.

>>> show_results('80', 0, 1, numpy.array([[0,1,.5],[.4,2,1.1],[.2,1,1.3]]))
"""

abs_z_final = (abs(z_final)).transpose()
abs_z_final[:, :] = abs_z_final[::-1, :]
pyplot.matshow(abs_z_final < escape_radius)
pyplot.title(f"Julia set of {function_label}\n c={function_params}")
pyplot.show()


if __name__ == "__main__":

z_0 = prepare_grid(window_size, nb_pixels)

nb_iterations = 24
escape_radius = 2 * abs(c_cauliflower) + 1
z_final = iterate_function(
eval_quadratic_polynomial,
c_cauliflower,
nb_iterations,
z_0,
infinity=1.1 * escape_radius,
)
show_results("z²+c", c_cauliflower, escape_radius, z_final)

nb_iterations = 64
escape_radius = 2 * abs(c_polynomial_1) + 1
z_final = iterate_function(
eval_quadratic_polynomial,
c_polynomial_1,
nb_iterations,
z_0,
infinity=1.1 * escape_radius,
)
show_results("z²+c", c_polynomial_1, escape_radius, z_final)

nb_iterations = 161
escape_radius = 2 * abs(c_polynomial_2) + 1
z_final = iterate_function(
eval_quadratic_polynomial,
c_polynomial_2,
nb_iterations,
z_0,
infinity=1.1 * escape_radius,
)
show_results("z²+c", c_polynomial_2, escape_radius, z_final)

nb_iterations = 12
escape_radius = 10000.0
z_final = iterate_function(
eval_exponential,
c_exponential,
nb_iterations,
z_0 + 2,
infinity=1.0e10,
)
show_results("exp(z)+c", c_exponential, escape_radius, z_final)