Merge pull request #240 from StructuralEquationModels/rename_sem_summary

close #158

Author: Maximilian-Stefan-Ernst

docs/src/tutorials/collection/multigroup.md

@@ -83,7 +83,7 @@ We now fit the model and inspect the parameter estimates:
 ```@example mg; ansicolor = true
 solution = sem_fit(model_ml_multigroup)
 update_estimate!(partable, solution)
-sem_summary(partable)
+details(partable)
 ```
 
 Other things you can query about your fitted model (fit measures, standard errors, etc.) are described in the section [Model inspection](@ref) and work the same way for multigroup models.

docs/src/tutorials/constraints/constraints.md

@@ -52,7 +52,7 @@ model_fit = sem_fit(model)
 
 update_estimate!(partable, model_fit)
 
-sem_summary(partable)
+details(partable)
 ```
 
 ### Define the constraints
@@ -165,7 +165,7 @@ update_partable!(
     solution(model_fit_constrained), 
     )
 
-sem_summary(partable)
+details(partable)
 ```
 
 As we can see, the constrained solution is very close to the original solution (compare the columns estimate and estimate_constr), with the difference that the constrained parameters fulfill their constraints. 

docs/src/tutorials/first_model.md

@@ -119,10 +119,10 @@ and compute fit measures as
 fit_measures(model_fit)
 ```
 
-We can also get a bit more information about the fitted model via the `sem_summary()` function:
+We can also get a bit more information about the fitted model via the `details()` function:
 
 ```@example high_level; ansicolor = true
-sem_summary(model_fit)
+details(model_fit)
 ```
 
 To investigate the parameter estimates, we can update our `partable` object to contain the new estimates:
@@ -134,7 +134,7 @@ update_estimate!(partable, model_fit)
 and investigate the solution with
 
 ```@example high_level; ansicolor = true
-sem_summary(partable)
+details(partable)
 ```
 
 Congratulations, you fitted and inspected your very first model! 

docs/src/tutorials/inspection/inspection.md

@@ -53,10 +53,10 @@ model_fit = sem_fit(model)
 
 you end up with an object of type [`SemFit`](@ref).
 
-You can get some more information about it by using the `sem_summary` function:
+You can get some more information about it by using the `details` function:
 
 ```@example colored; ansicolor = true
-sem_summary(model_fit)
+details(model_fit)
 ```
 
 To compute fit measures, we use
@@ -73,12 +73,12 @@ AIC(model_fit)
 
 A list of available [Fit measures](@ref) is at the end of this page.
 
-To inspect the parameter estimates, we can update a `ParameterTable` object and call `sem_summary` on it:
+To inspect the parameter estimates, we can update a `ParameterTable` object and call `details` on it:
 
 ```@example colored; ansicolor = true; output = false
 update_estimate!(partable, model_fit)
 
-sem_summary(partable)
+details(partable)
 ```
 
 We can also update the `ParameterTable` object with other information via [`update_partable!`](@ref). For example, if we want to compare hessian-based and bootstrap-based standard errors, we may write
@@ -90,7 +90,7 @@ se_he = se_hessian(model_fit)
 update_partable!(partable, :se_hessian, params(model_fit), se_he)
 update_partable!(partable, :se_bootstrap, params(model_fit), se_bs)
 
-sem_summary(partable)
+details(partable)
 ```
 
 ## Export results
@@ -106,7 +106,7 @@ parameters_df = DataFrame(partable)
 # API - model inspection
 
 ```@docs
-sem_summary
+details
 update_estimate!
 update_partable!
 ```

docs/src/tutorials/regularization/regularization.md

@@ -148,7 +148,7 @@ update_estimate!(partable, fit)
 
 update_partable!(partable, :estimate_lasso, params(fit_lasso), solution(fit_lasso))
 
-sem_summary(partable)
+details(partable)
 ```
 
 ## Second example - mixed l1 and l0 regularization
@@ -182,5 +182,5 @@ Let's again compare the different results:
 ```@example reg
 update_partable!(partable, :estimate_mixed, params(fit_mixed), solution(fit_mixed))
 
-sem_summary(partable)
+details(partable)
 ```

src/StructuralEquationModels.jl

@@ -131,7 +131,7 @@ export AbstractSem,
     SemFit,
     minimum,
     solution,
-    sem_summary,
+    details,
     objective!,
     gradient!,
     hessian!,

src/frontend/fit/summary.jl

@@ -1,4 +1,4 @@
-function sem_summary(
+function details(
     sem_fit::SemFit;
     show_fitmeasures = false,
     color = :light_cyan,
@@ -45,7 +45,7 @@ function sem_summary(
     print("\n")
 end
 
-function sem_summary(
+function details(
     partable::ParameterTable;
     color = :light_cyan,
     secondary_color = :light_yellow,
@@ -250,7 +250,7 @@ function sem_summary(
 
 end
 
-function sem_summary(
+function details(
     partable::EnsembleParameterTable;
     color = :light_cyan,
     secondary_color = :light_yellow,
@@ -291,7 +291,7 @@ function sem_summary(
         print("\n")
         printstyled(rpad(" Group: $k", 78), reverse = true)
         print("\n")
-        sem_summary(
+        details(
             partable.tables[k];
             color = color,
             secondary_color = secondary_color,
@@ -333,9 +333,9 @@ function Base.findall(fun::Function, partable::ParameterTable)
 end
 
 """
-    (1) sem_summary(sem_fit::SemFit; show_fitmeasures = false)
+    (1) details(sem_fit::SemFit; show_fitmeasures = false)
 
-    (2) sem_summary(partable::AbstractParameterTable; ...)
+    (2) details(partable::AbstractParameterTable; ...)
 
 Print information about (1) a fitted SEM or (2) a parameter table to stdout.
 
@@ -347,4 +347,4 @@ Print information about (1) a fitted SEM or (2) a parameter table to stdout.
 - `show_variables = true`
 - `show_columns = nothing`: columns names to include in the output e.g.`[:from, :to, :estimate]`)
 """
-function sem_summary end
+function details end