remove warnings

Author: Smit-create

lectures/cobweb.md

@@ -448,7 +448,7 @@ TODO check / fix exercises
 ## Exercises
 
 ```{exercise-start}
-:label: ex1
+:label: cobweb_ex1
 ```
 Using the default Market model and naive expectations, plot a time series simulation of supply (rather than the price).
 
@@ -457,7 +457,7 @@ Show, in particular, that supply also cycles.
 ```{exercise-end}
 ```
 
-```{solution-start} ex1
+```{solution-start} cobweb_ex1
 :class: dropdown
 ```
 
@@ -498,7 +498,7 @@ ts_plot_supply(m, 5, 15)
 ```
 
 ```{exercise-start}
-:label: ex2
+:label: cobweb_ex2
 ```
 **Backward looking average expectations**
 
@@ -519,7 +519,7 @@ Simulate and plot the price dynamics for $\alpha \in \{0.1, 0.3, 0.5, 0.8\}$ whe
 ```{exercise-end}
 ```
 
-```{solution-start} ex2
+```{solution-start} cobweb_ex2
 :class: dropdown
 ```
 

lectures/lp_intro.md

@@ -478,7 +478,7 @@ Once we solve the problem, we can check whether the solver was successful in sol
 ```{code-cell} ipython3
 # Solve the problem
 # we put a negative sign on the objective as linprog does minimization
-res_ex1 = linprog(-c_ex1, A_ub=A_ex1, b_ub=b_ex1, method='revised simplex')
+res_ex1 = linprog(-c_ex1, A_ub=A_ex1, b_ub=b_ex1)
 
 if res_ex1.success:
     # We use negative sign to get the optimal value (maximized value)
@@ -570,7 +570,7 @@ Let's solve the problem and check the status using `success` attribute.
 ```{code-cell} ipython3
 # Solve the problem
 res_ex2 = linprog(-c_ex2, A_eq=A_ex2, b_eq=b_ex2,
-                  bounds=bounds_ex2, method='revised simplex')
+                  bounds=bounds_ex2)
 
 if res_ex2.success:
     # We use negative sign to get the optimal value (maximized value)
@@ -692,7 +692,7 @@ Find the number of units of $A$ and product $B$ that he should manufacture in or
 ```
 
 
-```{solution-start} lp_intro_ex1
+```{solution-start} lp_intro_ex2
 :class: dropdown
 ```