Merge pull request #2561 from SciML/ChrisRackauckas-patch-5

Update for StructuralIdentifiability API changes

Author: ChrisRackauckas

docs/src/tutorials/parameter_identifiability.md

@@ -69,7 +69,7 @@ After that, we are ready to check the system for local identifiability:
 ```julia
 # query local identifiability
 # we pass the ode-system
-local_id_all = assess_local_identifiability(de, p = 0.99)
+local_id_all = assess_local_identifiability(de, prob_threshold = 0.99)
 ```
 
 We can see that all unknowns (except $x_7$) and all parameters are locally identifiable with probability 0.99.
@@ -78,7 +78,7 @@ Let's try to check specific parameters and their combinations
 
 ```julia
 to_check = [de.k5, de.k7, de.k10 / de.k9, de.k5 + de.k6]
-local_id_some = assess_local_identifiability(de, funcs_to_check = to_check, p = 0.99)
+local_id_some = assess_local_identifiability(de, funcs_to_check = to_check, prob_threshold = 0.99)
 ```
 
 Notice that in this case, everything (except the unknown variable $x_7$) is locally identifiable, including combinations such as $k_{10}/k_9, k_5+k_6$
@@ -183,7 +183,7 @@ end
 # check only 2 parameters
 to_check = [ode.b, ode.c]
 
-global_id = assess_identifiability(ode, funcs_to_check = to_check, p = 0.9)
+global_id = assess_identifiability(ode, funcs_to_check = to_check, prob_threshold = 0.9)
 ```
 
 Both parameters `b, c` are globally identifiable with probability `0.9` in this case.