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import numpy as np
import multiprocessing as mp
# Local import
from optimised import numpylota
# c-mesh limits
limitre = ( -2, 1 )
limitim = ( -1.5, 1.5 )
def createmangelctx(pre, pim, T, l, savez):
"""
Calculates the context used when calculating mangelbrot
:param pre: Number of real numbers in cmatrix
:param pim: Number of imaginary numbers in cmatrix
:param T: Mangelbrot threshold
:param l: Iterations
"""
sre = ( limitre[1] - limitre[0] ) / (pre-1)
ctx = (sre, pim, T, l, savez)
return ctx
def mangelstep(ctx, re):
"""
Calculates a single mangelbrot row.
:param ctx: Context containing information about mangelbrot
:param re: Row to calculate
"""
# Unpack context
(sre, pim, T, l, savez) = ctx
# Create c-mesh row
im = np.linspace(limitim[0], limitim[1], pim, dtype=complex)
np.add(1j * im, limitre[0] + sre * re, im)
# Calculate ι
rs = numpyiota(im, T, l, savez)
if savez:
return rs
else:
# It takes some time to unpack a list of tuples
# So if no savez do not return a tuple
return rs[0]
def mangel(pre, pim, T, l, savez):
"""
Calculate the mangelbrot image
(pre, pim) discribes the image size. Use T and l to tune the mangelbrot
This function uses the global variables limitre and limitim to determine
the c-mesh range.
:param pre: Number of real numbers used
:param pim: Number of imaginary numbers
:param T: Mangelbrot threshold
:param l: Iterations
:param savez: Return z as the second element of returned tuple
"""
ctx = createmangelctx(pre, pim, T, l, savez)
# Number of processes
procs = mp.cpu_count()
pool = mp.Pool(processes=procs)
args = ((ctx, i) for i in range(pre))
result = pool.starmap_async(mangelstep, args)
pool.close()
pool.join()
result = result.get()
if savez:
z = [None] * pre
rs = [None] * pre
# Unzip rs
for i, r in enumerate(result):
rs[i] = r[0]
z[i] = r[1]
return (np.vstack(rs), np.vstack(z))
else:
return (np.vstack(result), None)
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