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From Python to Numpy

> *Temporal vectorization* is where elements share the same computation but necessitate a different number of iterations.


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# Problem Description

**The Mandelbrot** set is the set of complex numbers $c$ for which
the function $f_c(z) = z^2+ c$ does not diverge when iterated
from $z=0$, i.e., for which the sequence $f_c(0), f_c(f_c(0)) $, etc., remains bounded in an absolute value. It is very easy
to compute, but it can take a very long time because you need to
ensure a given number does not diverge. This is generally done by
iterating the computation up to a maximum number of iterations, after
which, if the number is still within some bounds, it is considered
non-divergent.


Of course, the more iterations you do, the more
precision you get.



This lesson explains temporal vectorization with an interesting case study called "Mandelbrot set".

Temporal Vectorization