-
-
Notifications
You must be signed in to change notification settings - Fork 7.9k
Showcase example: (kind of mandatory) Mandelbrot set #7447
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Changes from all commits
2af3aae
7fe3739
7c0d92a
9542a8e
68247ea
fc5668f
30c894d
78fc1fa
File filter
Filter by extension
Conversations
Jump to
Diff view
Diff view
There are no files selected for viewing
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,74 @@ | ||
""" | ||
=================================== | ||
Shaded & power normalized rendering | ||
=================================== | ||
|
||
The Mandelbrot set rendering can be improved by using a normalized recount | ||
associated with a power normalized colormap (gamma=0.3). Rendering can be | ||
further enhanced thanks to shading. | ||
|
||
The `maxiter` gives the precision of the computation. `maxiter=200` should | ||
take a few seconds on most modern laptops. | ||
""" | ||
import numpy as np | ||
|
||
|
||
def mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon=2.0): | ||
X = np.linspace(xmin, xmax, xn, dtype=np.float32) | ||
Y = np.linspace(ymin, ymax, yn, dtype=np.float32) | ||
C = X + Y[:, None]*1j | ||
N = np.zeros(C.shape, dtype=int) | ||
Z = np.zeros(C.shape, np.complex64) | ||
for n in range(maxiter): | ||
I = np.less(abs(Z), horizon) | ||
N[I] = n | ||
Z[I] = Z[I]**2 + C[I] | ||
N[N == maxiter-1] = 0 | ||
return Z, N | ||
|
||
|
||
if __name__ == '__main__': | ||
import time | ||
import matplotlib | ||
from matplotlib import colors | ||
import matplotlib.pyplot as plt | ||
|
||
xmin, xmax, xn = -2.25, +0.75, 3000/2 | ||
ymin, ymax, yn = -1.25, +1.25, 2500/2 | ||
maxiter = 200 | ||
horizon = 2.0 ** 40 | ||
log_horizon = np.log(np.log(horizon))/np.log(2) | ||
Z, N = mandelbrot_set(xmin, xmax, ymin, ymax, xn, yn, maxiter, horizon) | ||
|
||
# Normalized recount as explained in: | ||
# https://linas.org/art-gallery/escape/smooth.html | ||
# https://www.ibm.com/developerworks/community/blogs/jfp/entry/My_Christmas_Gift | ||
|
||
# This line will generate warnings for null values but it is faster to | ||
# process them afterwards using the nan_to_num | ||
with np.errstate(invalid='ignore'): | ||
M = np.nan_to_num(N + 1 - np.log(np.log(abs(Z)))/np.log(2) + log_horizon) | ||
|
||
dpi = 72 | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Is changing dpi important? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. More or less. I wanted to be sure of the approximate pixel resolution. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I'm not sure I understand. The dataset is 3000 samples wide ( There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Oops, just realized I missed the /2, so it's really 1500 samples wide with effective resolution of 150 dpi, and resampling ratio of 25:12 = ~2.083333. But in that case, how about making it exactly 2 by setting dpi=75? |
||
width = 10 | ||
height = 10*yn/xn | ||
fig = plt.figure(figsize=(width, height), dpi=dpi) | ||
ax = fig.add_axes([0.0, 0.0, 1.0, 1.0], frameon=False, aspect=1) | ||
|
||
# Shaded rendering | ||
light = colors.LightSource(azdeg=315, altdeg=10) | ||
M = light.shade(M, cmap=plt.cm.hot, vert_exag=1.5, | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Should we use our fancy new colour maps (magma, inferno, or plasma)? I'm not sure how well they work with shading though. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I tried but output was not as nice as with the hot colormap. |
||
norm=colors.PowerNorm(0.3), blend_mode='hsv') | ||
plt.imshow(M, extent=[xmin, xmax, ymin, ymax], interpolation="bicubic") | ||
ax.set_xticks([]) | ||
ax.set_yticks([]) | ||
|
||
# Some advertisement for matplotlib | ||
year = time.strftime("%Y") | ||
major, minor, micro = matplotlib.__version__.split('.', maxsplit=2) | ||
text = ("The Mandelbrot fractal set\n" | ||
"Rendered with matplotlib %s.%s, %s — http://matplotlib.org" | ||
% (major, minor, year)) | ||
ax.text(xmin+.025, ymin+.025, text, color="white", fontsize=12, alpha=0.5) | ||
|
||
plt.show() |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I don't think this conditional block is necessary.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
It doesn't hurt and allow to import mandelbrot if you want to experience with it.