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rm foo*.png | |
convert -delay 10x100 foo*.png foo.gif |
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[1] I tried using Python's matplotlib on the logarithm and here is what I got, a kind of starburst pattern. Since the angle jumps between
Perhaps instead of matplotlib.pyplot.contour
the contour lines can be connected with meshgrid
and numpy.where
statements.
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize']=4,4
plt.contour(
np.arange(-1,1,0.01),
np.arange(-1,1,0.01),
np.angle(t[...,None] + 1j*t[None,...]) ,
levels = 2*np.pi*np.arange(-1,1,0.025)
)
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# plt.contour assumes there are lines between theta = 0 and theta = 2*np.pi | |
import numpy as np | |
import matplotlib.pyplot as plt | |
#%matplotlib inline | |
plt.rcParams['figure.figsize']=7,7 | |
# rm foo*.png | |
# convert foo*.png foo.gif | |
dt = 0.01 | |
L = 5 | |
t = np.arange(-L,L+dt, dt) | |
z = t[...,None]+1j*t[None,...] | |
N = 20 | |
PP = np.polyval(P,z) | |
for k in np.arange(N): | |
print "%02d" %(k) | |
w = np.log(np.exp(2j*np.pi*(k*1.0/N))*PP) | |
ds = 0.05 | |
plt.contour(t, t, w.imag%(2*np.pi), levels = 2*np.pi*np.arange(0,1, ds), colors=('#505050','#707070'), linewidth=1) | |
plt.contour(t, t, w.imag%(2*np.pi), levels = 2*np.pi*np.arange(0,1, 0.5), colors='w', linewidth=50) | |
plt.contour(t, t, w.real, levels = np.arange(0,5,0.1)**1, colors=('#A2D426','#6B6CED')) | |
L = 3 | |
plt.xlim([-L,L]) | |
plt.ylim([-L,L]) | |
#plt.show() | |
plt.savefig('/home/jdm/Documents/math/foo-%02d.png'%(k)) | |
plt.clf() |
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