fix code linking reference issues

Author: kp992

lectures/functions.md

@@ -286,7 +286,6 @@ We will break this program into two parts:
 
 This is accomplished in the next program
 
-(funcloopprog)=
 ```{code-cell} python3
 def generate_data(n):
     ϵ_values = []
@@ -313,7 +312,6 @@ Let's make it slightly more useful by giving it the ability to return either sta
 
 This is achieved in the next piece of code.
 
-(funcloopprog2)=
 ```{code-cell} python3
 def generate_data(n, generator_type):
     ϵ_values = []
@@ -345,7 +343,6 @@ For example, we can get rid of the conditionals all together by just passing the
 
 To understand this, consider the following version.
 
-(test_program_6)=
 ```{code-cell} python3
 def generate_data(n, generator_type):
     ϵ_values = []
@@ -439,7 +436,6 @@ This example is somewhat contrived, since the first (iterative) solution would u
 We'll meet less contrived applications of recursion later on.
 
 
-(factorial_exercise)=
 ## Exercises
 
 ```{exercise-start}

lectures/python_advanced_features.md

@@ -41,7 +41,7 @@ Formally, an *iterator* is an object with a `__next__` method.
 
 For example, file objects are iterators .
 
-To see this, let's have another look at the {ref}`US cities data <us_cities_data>`,
+To see this, let's have another look at the {ref}`US cities data <us_cities_data-code>`,
 which is written to the present working directory in the following cell
 
 ```{code-cell} ipython

lectures/python_by_example.md

@@ -344,7 +344,6 @@ The `for` loop is the most common technique for iteration in Python.
 
 But, for the purpose of illustration, let's modify {ref}`the program above <firstloopprog-code>` to use a `while` loop instead.
 
-(whileloopprog)=
 ```{code-cell} python3
 ts_length = 100
 ϵ_values = []

lectures/python_essentials.md

@@ -407,8 +407,9 @@ Many Python objects are "iterable", in the sense that they can be looped over.
 
 To give an example, let's write the file us_cities.txt, which lists US cities and their population, to the present working directory.
 
-(us_cities_data)=
 ```{code-cell} ipython
+:name: us_cities_data
+
 %%writefile us_cities.txt
 new york: 8244910
 los angeles: 3819702
@@ -657,7 +658,7 @@ We've all heard the saying about consistency and little minds.
 
 In programming, as in mathematics, the opposite is true
 
-* A mathematical paper where the symbols $\cup$ and $\cap$ were
+* A mathematical paper where the symbols `$\cup$` and `$\cap$` were
   reversed would be very hard to read, even if the author told you so on the
   first page.
 

lectures/scipy.md

@@ -215,8 +215,9 @@ Here's a simplistic implementation of the algorithm in Python.
 
 It works for all sufficiently well behaved increasing continuous functions with $f(a) < 0 < f(b)$
 
-(bisect_func)=
 ```{code-cell} python3
+:name: bisect_func
+
 def bisect(f, a, b, tol=10e-5):
     """
     Implements the bisection root finding algorithm, assuming that f is a
@@ -538,7 +539,7 @@ print(f"The Monte Carlo option price is {P:3f}")
 
 In [this lecture](functions.md), we discussed the concept of {ref}`recursive function calls <recursive_functions>`.
 
-Try to write a recursive implementation of the homemade bisection function {ref}`described above <bisect_func>`.
+Try to write a recursive implementation of the homemade bisection function {ref}`described above <bisect_func-code>`.
 
 Test it on the function {eq}`root_f`.
 ```