DOC: Update link to boolean indexing.

Author: rossbar

content/tutorial-plotting-fractals.md

@@ -207,7 +207,7 @@ def divergence_rate(mesh, num_iter=10, radius=2):
 
 The behaviour of this function may look confusing at first glance, so it will help to explain some of the notation.
 
-Our goal is to iterate over each value in the mesh and to tally the number of iterations before the value diverges. Since some values will diverge quicker than others, we need a procedure that only iterates over values that have an absolute value that is sufficiently small enough. We also want to stop tallying values once they surpass the radius. For this, we can use **[Boolean Indexing](https://numpy.org/devdocs/reference/arrays.indexing.html#boolean-array-indexing)**, a NumPy feature that when paired with universal functions is unbeatable. Boolean Indexing allows for operations to be performed conditionally on a NumPy array without having to resort to looping over and checking for each array value individually.
+Our goal is to iterate over each value in the mesh and to tally the number of iterations before the value diverges. Since some values will diverge quicker than others, we need a procedure that only iterates over values that have an absolute value that is sufficiently small enough. We also want to stop tallying values once they surpass the radius. For this, we can use **[Boolean Indexing](https://numpy.org/devdocs/user/basics.indexing.html#boolean-array-indexing)**, a NumPy feature that when paired with universal functions is unbeatable. Boolean Indexing allows for operations to be performed conditionally on a NumPy array without having to resort to looping over and checking for each array value individually.
 
 In our case, we use a loop to apply iterations to our function $f(z) = z^2 -1 $ and keep tally. Using Boolean indexing, we only apply the iterations to values that have an absolute value less than 2.