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set progressbar lenght and some formatting #142

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merged 3 commits into from
Jan 4, 2024
Merged

set progressbar lenght and some formatting #142

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3cedec3
set progressbar lenght to 50
oameye Jan 3, 2024
9ab4be7
formatting and spacing in sorting.jl file
oameye Jan 3, 2024
8fcdfe5
Merge branch 'master' into length-ProgressBar
oameye Jan 4, 2024
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4 changes: 2 additions & 2 deletions src/solve_homotopy.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -277,9 +277,9 @@ function _get_raw_solution(problem::Problem, parameter_values;
threading=threading, show_progress=show_progress, seed=seed
)
elseif method==:total_degree
result_full = Array{Vector{Any}, 1}(undef, length(parameter_values))
result_full = Array{Vector{Any}, 1}(undef, length(params_1D))
if show_progress
bar = Progress(length(parameter_values), 1, "Solving via total degree homotopy ...", 50)
bar = Progress(length(params_1D), dt=1, desc="Solving via total degree homotopy ...", barlen=50)
end
for i in eachindex(parameter_values) # do NOT thread this
p = parameter_values[i]
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56 changes: 29 additions & 27 deletions src/sorting.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -15,10 +15,10 @@ function sort_solutions(solutions::Array; sorting="nearest", show_progress=true)
sorting_schemes = ["none", "hilbert", "nearest"]
sorting ∈ sorting_schemes || error("Only the following sorting options are allowed: ", sorting_schemes)
sorting == "none" && return solutions
l = length(size(solutions))
l == 1 && return sort_1D(solutions, show_progress=show_progress)
l == 2 && return sort_2D(solutions, sorting=sorting, show_progress=show_progress)
error("do not know how to solve solution which are not 1D or 2D")
l = length(size(solutions))
l == 1 && return sort_1D(solutions, show_progress=show_progress)
l == 2 && return sort_2D(solutions, sorting=sorting, show_progress=show_progress)
error("do not know how to solve solution which are not 1D or 2D")
end


Expand All @@ -35,7 +35,7 @@ Removes rows and columns with given idices from the Matrix M.
The row/column indices are defined with respect to the original M!
"""
function remove_rows_columns(M::Matrix, rows::Vector{Int64}, cols::Vector{Int64})
a,b = size(M)
a, b = size(M)
M[[!in(i, rows) for i in 1:a], [!in(j, cols) for j in 1:b]]
end

Expand All @@ -61,10 +61,10 @@ end

"Match each solution from to_sort to a closest partner from refs"
function get_distance_matrix(refs::Vector{Vector{SteadyState}}, to_sort::Vector{SteadyState})
distances = map( ref -> get_distance_matrix(ref, to_sort), refs)
distances = map(ref -> get_distance_matrix(ref, to_sort), refs)
lowest_distances = similar(distances[1])
for idx in CartesianIndices(lowest_distances)
lowest_distances[idx] = minimum( x[idx] for x in distances )
lowest_distances[idx] = minimum(x[idx] for x in distances)
end
lowest_distances
end
Expand All @@ -88,7 +88,7 @@ function align_pair(reference, to_sort::Vector{SteadyState})
sorted = Vector{CartesianIndex}(undef, n)

for idx in sorted_cartesians
j,k = idx[1], idx[2]
j, k = idx[1], idx[2]
if !matched[k] && !matched_ref[j]
matched[k] = true
matched_ref[j] = true
Expand All @@ -106,10 +106,10 @@ Go through a vector of solution and sort each according to Euclidean norm.
"""
function sort_1D(solns::Vector{Vector{SteadyState}}; show_progress=true)
sorted_solns = similar(solns) # preallocate
sorted_solns[1] = sort(solns[1], by= x->abs.(imag(x))) # prefer real solution at first position
sorted_solns[1] = sort(solns[1], by=x -> abs.(imag(x))) # prefer real solution at first position

if show_progress
bar = Progress(length(solns), dt=1, desc="Ordering solutions into branches ...", output=stdout)
bar = Progress(length(solns), dt=1, desc="Ordering solutions into branches ...", barlen=50)
end
for i in eachindex(solns[1:end-1])
show_progress ? next!(bar) : nothing
Expand All @@ -122,38 +122,39 @@ end

function hilbert_indices(solns::Matrix{Vector{Vector{ComplexF64}}})
"""Get mapping between 2D indexes (parameter space) and a 1D Hilbert curve"""
Lx,Ly = size(solns)
Lx, Ly = size(solns)
mapping = [] # compute mapping between Hilbert indices and 2Ds
for j in 1:Ly # length of parameter sweep 1
for i in 1:Lx # length of parameter sweep 2
X = [i, j]
h = encode_hilbert(Simple2D(Int), X)
X .= 0
push!(mapping,(h=>decode_hilbert!(Simple2D(Int), X, h)))
push!(mapping, (h => decode_hilbert!(Simple2D(Int), X, h)))
end
end
idx_pairs = [el[2] for el in sort(mapping)] # sort along the Hilbert curve. Now we can iterate over these indexes
# sort along the Hilbert curve. Now we can iterate over these indexes
idx_pairs = [el[2] for el in sort(mapping)]
end

function naive_indices(solns::Matrix{Vector{Vector{ComplexF64}}})
idx_pairs = []
for i in 1:size(solns,1)
for j in 1:size(solns,2)
push!(idx_pairs,[i,j])
for i in 1:size(solns, 1)
for j in 1:size(solns, 2)
push!(idx_pairs, [i, j])
end
end
idx_pairs
end

function get_nn_2D(idx::Vector{Int64},Nx::Int64,Ny::Int64)
function get_nn_2D(idx::Vector{Int64}, Nx::Int64, Ny::Int64)
"returns all neighbors from a point, including diagonal ones"
x, y = idx[1],idx[2]
x, y = idx[1], idx[2]
max_n = 1
neighbors = []
for x2 in x-max_n:x+max_n
for y2 in y-max_n:y+max_n
if (0<x<=Nx) && (0<y<=Ny) && (x != x2 || y != y2) && (1 <= x2 <= Nx) && (1 <= y2 <= Ny)
push!(neighbors,[x2,y2])
if (0 < x <= Nx) && (0 < y <= Ny) && (x != x2 || y != y2) && (1 <= x2 <= Nx) && (1 <= y2 <= Ny)
push!(neighbors, [x2, y2])
end
end
end
Expand All @@ -163,22 +164,23 @@ end

function sort_2D(solns::Matrix{Vector{Vector{ComplexF64}}}; sorting="nearest", show_progress=true)
"""match each 2D solution with all its surrounding neighbors, including the diagonal ones"""
# determine a trajectory in 2D space where nodes will be visited
if sorting=="hilbert" # propagating matching of solutions along a hilbert_curve in 2D
# determine a trajectory in 2D space where nodes will be visited
if sorting == "hilbert" # propagating matching of solutions along a hilbert_curve in 2D
idx_pairs = hilbert_indices(solns)
elseif sorting=="nearest" # propagate matching of solutions along rows
elseif sorting == "nearest" # propagate matching of solutions along rows
idx_pairs = naive_indices(solns)
end

sorted_solns = Inf.*copy(solns) # infinite solutions are ignored by the align_pair function. This trick allows a consistent ordering "propagation"
sorted_solns[1,1] = sort(solns[1,1], by= x->abs.(imag(x))) # prefer real solution at first position
# infinite solutions are ignored by the align_pair function. This trick allows a consistent ordering "propagation"
sorted_solns = Inf .* copy(solns)
sorted_solns[1, 1] = sort(solns[1, 1], by=x -> abs.(imag(x))) # prefer real solution at first position

if show_progress
bar = Progress(length(idx_pairs), dt=1, desc="Ordering solutions into branches ...", output=stdout)
bar = Progress(length(idx_pairs), dt=1, desc="Ordering solutions into branches ...", barlen=50)
end
for i in 1:length(idx_pairs)-1
show_progress ? next!(bar) : nothing
neighbors = get_nn_2D(idx_pairs[i+1],size(solns,1),size(solns,2))
neighbors = get_nn_2D(idx_pairs[i+1], size(solns, 1), size(solns, 2))
reference = [sorted_solns[ind...] for ind in neighbors]
matched_indices = align_pair(reference, solns[idx_pairs[i+1]...]) # pairs of matching indices
next_indices = getindex.(matched_indices, 2) # indices of the next solution
Expand Down
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