datasparsity docu

Project.toml

@@ -4,7 +4,6 @@ authors = ["Michal Kocvara <[email protected]>"]
 version = "0.2.5"
 
 [deps]
-CSDP = "0a46da34-8e4b-519e-b418-48813639ff34"
 ConjugateGradients = "f59de78d-195d-4e7b-a078-2e47da4c3ad6"
 Dualization = "191a621a-6537-11e9-281d-650236a99e60"
 FameSVD = "9ba2d756-9ce3-11e9-1a71-0ffcb019784d"

README.md

@@ -96,6 +96,8 @@ datarank        # 0..full rank matrices expected [0]
 initpoint       # 0..Loraine heuristics, 1..SDPT3-like heuristics [0]
 timing          # 1..yes, 0..no
 maxit           # maximal number of global iterations [200]
+datasparsity    # data matrices treated as sparse when number of their 
+                # non-zero elements is below this parameter [8]
 ```
 
 ## Citing

docs/src/Loraine_options.md

@@ -17,6 +17,8 @@ datarank        # 0..full rank matrices expected [0]
 initpoint       # 0..Loraine heuristics, 1..SDPT3-like heuristics [0]
 timing          # 1..yes, 0..no
 maxit           # maximal number of global iterations [200]
+datasparsity    # data matrices treated as sparse when number of their 
+                # non-zero elements is below this parameter [8]
 ```
 
 ## Comments
@@ -44,3 +46,10 @@ maxit           # maximal number of global iterations [200]
 - `timing` is not used when Loraine is called from JuMP
 
 - `tol_cg, tol_cg_up, aamat`: it is not recommended to change values of these options, unless you really want to
+
+- `datasparsity` 
+    - data matrices treated as sparse when number of their non-zero elements is below `datasparsity` as as    dense otherwise; used when computing the Schur complement matrix
+    - when set to zero, all matrices treated as dense
+    - set to high number to treat all matrices as sparse
+    - recommended setting between 1-16, default value is 8
+    - wrong setting can very significantly influence the CPU time

examples/solve_sdpa.jl

@@ -3,7 +3,7 @@
 
 using JuMP
 import Loraine 
-import CSDP
+# import CSDP
 # import SCS
 # using Mosek
 # using MosekTools