Add restore!

Author: scheinerman

README.md

@@ -13,7 +13,7 @@ As a demonstration project, this is not suitable for solving actual linear progr
 At present it will fail if:
 * The LP is infeasible.
 * The LP is unbounded.
-* Other unidentified reasons.
+* Other unidentified reasons. (In other words, still buggy.)
 
 It is also set up for maximization problems only. To solve a minimization problem use the dual LP by
 replacing the inputs `A`, `b`, and `c` with `A'`, `c`, and `b` respectively. 

docs/build/.documenter-siteinfo.json

@@ -1 +1 @@
-{"documenter":{"julia_version":"1.11.4","generation_timestamp":"2025-04-03T11:08:57","documenter_version":"1.10.0"}}
+{"documenter":{"julia_version":"1.11.4","generation_timestamp":"2025-04-03T14:12:03","documenter_version":"1.10.0"}}

docs/build/index.html

@@ -123,9 +123,11 @@ julia> lp_solve(T)
  1.599999999999999
 ```
 
-## The `restore` function
+## The `restore!` function
 
-As mentioned, the `pivot!` and `pivot_solve!` functions modify the `Tableau`. Use `restore` to return a `Tableau` to its original state like this: `T = restore(T)`. 
+As mentioned, the `pivot!` and `pivot_solve!` functions modify the `Tableau`. Use `restore!` to return a `Tableau` to its original state like this: `restore!(T)`. 
+
+There is also `restore(T)` which does not reset `T`, but creates a new `Tableau` equal to the original state of `T`.
 
 ```
 julia> T
@@ -150,15 +152,15 @@ julia> T
    3 │ 0      29/8   -1/8   0      1      0      9
    4 │ 0      -1/4   1/4    0      0      1      6
 
-julia> T = restore(T)
+julia> restore!(T)
 4×7 DataFrame
  Row │ x1     x2     s1     s2     s3     val    RHS   
      │ Exact  Exact  Exact  Exact  Exact  Exact  Exact 
 ─────┼─────────────────────────────────────────────────
-   1 │ 8      3      1      0      0      0      24
-   2 │ 1      1      0      1      0      0      4
-   3 │ 1      4      0      0      1      0      12
-   4 │ -2     -1     0      0      0      1      0
+   1 │ 8      3      1/5    -3/5   0      0      12/5
+   2 │ 1      1      -1/5   8/5    0      0      8/5
+   3 │ 1      4      3/5    -29/5  1      0      16/5
+   4 │ 0      0      1/5    2/5    0      1      32/5
 ```
 
 

docs/build/objects.inv

@@ -22,6 +22,7 @@ export Tableau,
     pivot_solve,
     pivot_solve!,
     restore,
+    restore!,
     visualize
 
 """
@@ -55,12 +56,27 @@ end
 
 Create a new `Tableau` based on the original data used to create `T`.
 
-Recommended usage: `T = restore(T)` to reset `T` to its original state. 
+See also `restore!`.
 """
 function restore(T::Tableau)
     return Tableau(T.A, T.b, T.c)
 end
 
+"""
+    restore!(T::Tableau)
+
+Restore a `Tableau` based on the original data used to create it. 
+"""
+function restore!(T::Tableau)
+    TT = restore(T)
+    for i in 1:(T.n_cons)
+        for j in 1:(T.n_vars)
+            T.M[i, j] = TT.M[i, j]
+        end
+    end
+    return T
+end
+
 include("Exact.jl")
 include("DataFrame.jl")