fixed

Project.toml

@@ -5,7 +5,6 @@ version = "0.1.0-dev"
 
 [deps]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LinearOperators = "5c8ed15e-5a4c-59e4-a42b-c7e8811fb125"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
@@ -22,6 +21,7 @@ Printf = "1.9, 1.10"
 QRupdate = "1.0"
 Random = "1.9, 1.10"
 SparseArrays = "1.9, 1.10"
+Logging = "1.11"
 julia = "1.9, 1.10"
 
 [extras]

src/bpdn.jl

@@ -1,15 +1,29 @@
-function asp_bpdn(A, b, lambda; kwargs...)
-
-"""
-    asp_bpdn(A,B) solves the basis pursuit problem.
 
-    (BP)   minimize_x  ||x||_1  subject to  Ax = B.
 
-    AS_BPDN(A,B,LAM) solves the basis pursuit denoise problem
+@doc raw"""
+```julia
+    asp_bpdn(A,B)```
+    solves the basis pursuit problem.
 
-    (BPDN) minimize_x  1/2 ||Ax - B||_2^2 + LAM ||x||_1.
+    (BP)
+    ```math 
+    \min_x   \|x \|_1 
+    ```
+      subject to 
+    ```math 
+       Ax = B.
+    ```
+    ```julia
+    asp_bpdn(A,B,λ)
+    ```
+    solves the basis pursuit denoise problem
 
+    (BPDN) 
+    ```math 
+    \min_x  \frac{1}{2} \|Ax - B\|_2^2 + λ \|x\|_1
+    ```
 """
+function asp_bpdn(A, b, lambda; kwargs...)
     n = size(A, 2)
     bl = -ones(n)
     bu = +ones(n)

src/omp.jl

@@ -16,6 +16,25 @@ end
 
 Base.lastindex(t::OMPTracer) = lastindex(t.active)
 
+@doc raw"""
+    ```julia
+    asp_omp(A,B)```
+    Orthogonal matching pursuit for sparse 
+    ```math 
+    Ax=b
+    ```
+    Applies the orthogonal matching pursuit (OMP) algorithm to
+    estimate a sparse solution of the underdetermined system `Ax=b`.
+
+    (BP)   
+    ```math 
+    \min_x  \|x\|_1  
+    ```
+    subject to  
+    ```math 
+    Ax = b.
+    ```
+"""
 function asp_omp(
     A::Union{AbstractMatrix, AbstractLinearOperator},
     b::Vector,
@@ -33,16 +52,6 @@ function asp_omp(
     pivTol::Real = 1e-12,
     actMax::Real = Inf)
 
-    """
-        Orthogonal matching pursuit for sparse Ax=b
-
-        asp_omp applies the orthogonal matching pursuit (OMP) algorithm to
-        estimate a sparse solution of the underdetermined system Ax=b.
-
-        (BP)   minimize_x  ||x||_1  subject to  Ax = b.
-
-        asp_omp(A, b, λ) solves the basis pursuit problem.
-    """
     # Start the clock and size up the problem.
     time0 = time()