Prompt:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from mpmath import mp, mpc, mpf
def mandelbrot_mp(width, height, max_iter, center_real=' -0.75035', center_imag='0.07109', zoom=mpf('5.009e633')):
mp.dps = 700 # Digits for 10^633 precision; increase to 800 if artifacts
center = mpc(center_real, center_imag)
scale = mpf(4) / zoom # Extent ~4/zoom for symmetric framing
half_scale = scale / mpf(2)
# Precompute linspaces as lists for mpmath compatibility
x_list = [mpf(center.real) + half_scale * (mpf(2*i)/ (width-1) - 1) for i in range(width)]
y_list = [mpf(center.imag) + half_scale * (mpf(2*i)/ (height-1) - 1) for i in range(height)]
iter_count = np.zeros((height, width), dtype=float)
for row in range(height):
cy = y_list[row]
for col in range(width):
cx = x_list[col]
c = mpc(cx, cy)
z = mpc(0)
it = 0
while abs(z) <= mpf(2) and it < max_iter:
z = z**2 + c
it += 1
if it == max_iter:
iter_count[row, col] = 0 # Inside: black
else:
# Smooth fractional iter
mu = it - mp.log(mp.log(abs(z))) / mp.log(2)
iter_count[row, col] = float(mu)
# Norm with cycles for deep gradient layers (pink/red bulbs)
raw_norm = np.log1p(np.abs(iter_count)) / np.log1p(max_iter)
norm = (raw_norm * 5) % 1.0 # 5 cycles for recursion hues
return norm
# Parameters from sample (test low first!)
width, height = 400, 400 # Start low; ramp to 800+
max_iter = 10000 # Test; set to 2146123 for full
center_real = '-0.75035' # Paste exact long string here if found
center_imag = '0.07109'
zoom = mpf('5.009e633') # Or smaller like 1e10 for testing
# Compute (slow—patience!)
fractal = mandelbrot_mp(width, height, max_iter, center_real, center_imag, zoom)
# Colormap: blue far → green/purple spirals → pink/red strawberry bulbs
colors = ['#00008b', '#228b22', '#4b0082', '#ff69b4', '#b22222', '#ffff00', '#ff00ff']
cmap = LinearSegmentedColormap.from_list('deep_strawberry', colors[::-1], N=256) # Reverse for pink-high iter
# Plot
plt.figure(figsize=(10, 10))
half_s = float(2 / zoom) # Approx for extent
center_r, center_i = float(center_real), float(center_imag)
plt.imshow(fractal, origin='lower', cmap=cmap, extent=[center_r - half_s, center_r + half_s, center_i - half_s, center_i + half_s])
plt.axis('off')
plt.show()
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