Mandelbrot set: Difference between revisions

Line 7,226:

G = (X - 1) + (Y - h / d) * 1j # rectangular grid around zero

C = (-0.8 + 0.2 * 1j) + 1.5 * G

C = (-0.7 + 0.1 * 1j) + 2.0 * G

A, B = C.real, C.imag

Line 7,240:

fig, ax = plt.subplots(figsize=(4, 3))

ax.imshow(T ** 0.2, cmap=plt.cm.nipy_spectral)

ax.imshow(T ** 0.5, cmap=plt.cm.nipy_spectral)

plt.savefig("Mandelbrot_set.png", dpi=100)

Line 7,247:

fig, ax = plt.subplots(figsize=(6, 4))

ax.scatter(A, B, s=S, c=T ** 0.4, cmap=plt.cm.nipy_spectral)

ax.scatter(A, B, s=S, c=T**0.5, cmap=plt.cm.nipy_spectral)

plt.savefig("Mandelbrot_plot.png", dpi=100)</lang>

A small change in the code above allows Mercator zooms of the Mandelbrot set (cf. David Madore: [http://www.madore.org/~david/math/mandelbrot.html ''Mandelbrot set images and videos'']). Compression is used as described by David Madore.

Line 7,262:

G = np.exp(X * 1j - Y) # circular grid around zero

C = (-0.~~7894~~ + 0.~~1631~~ * 1j) + 1.5 * G

C = (-0.7437 + 0.1319 * 1j) + 1.5 * G

A, B = C.real, C.imag

Line 7,283:

fig, ax = plt.subplots(2, 2, figsize=(12, 12))

ax[0, 0].scatter(A[0:300], B[0:300], s=S[0:300], c=T[0:300] ** 0.1, cmap=plt.cm.nipy_spectral)

ax[0, 0].scatter(A[0:300], B[0:300], s=S[0:300], c=T[0:300]**0.5, cmap=plt.cm.nipy_spectral)

ax[0, 1].scatter(A[100:400], B[100:400], s=S[0:300], c=T[100:400] ** 0.2, cmap=plt.cm.nipy_spectral)

ax[0, 1].scatter(A[100:400], B[100:400], s=S[0:300], c=T[100:400]**0.4, cmap=plt.cm.nipy_spectral)

ax[1, 0].scatter(A[200:500], B[200:500], s=S[0:300], c=T[200:500] ** 0.3, cmap=plt.cm.nipy_spectral)

ax[1, 0].scatter(A[200:500], B[200:500], s=S[0:300], c=T[200:500]**0.3, cmap=plt.cm.nipy_spectral)

ax[1, 1].scatter(A[300:600], B[300:600], s=S[0:300], c=T[300:600] ** 0.4, cmap=plt.cm.nipy_spectral)

ax[1, 1].scatter(A[300:600], B[300:600], s=S[0:300], c=T[300:600]**0.2, cmap=plt.cm.nipy_spectral)

plt.savefig("Mercator_zoom.png", dpi=100)</lang>