Update dependencies, prepare tag

NEWS.md

@@ -2,20 +2,20 @@
 
 - no changes thus far
 
-# v0.18.2 (latest)
+# v0.19.0 (latest)
 
 ### general
 
 - add support for shared-memory OTU tables (sparse and dense), invoked via the `share_data` flag in `learn_network`
+- improve speed and edge case behaviour for non-recursive partial correlations
 - improve freeing of memory (in particular on parallel workers) between major network inference steps
 - improve error reporting on parallel workers
 
 ### bug fixes
 
-- fix numerical edge case for recursive partial correlations, improve speed and edge case behaviour for non-recursive partial correlations
+- fix numerical edge case for recursive partial correlations
 - fix handling of variables with no absences when `heterogeneous=true`
 
-
 # v0.18.1
 
 ### bug fixes

Project.toml

@@ -4,7 +4,7 @@ keywords = ["metagenomics", "microbiome", "probabilistic-graphical-models", "hig
 license = "GPL-3.0"
 desc = "Inference of microbial interaction networks from large-scale heterogeneous abundance data"
 authors = ["Janko Tackmann <[email protected]>"]
-version = "0.18.1"
+version = "0.19.0"
 
 [deps]
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
@@ -17,7 +17,7 @@ FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
-LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
+Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SharedArrays = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
@@ -31,13 +31,13 @@ Combinatorics = "0.7, 1"
 DataStructures = "0.17, 0.18"
 Distributions = "0.21, 0.22, 0.23, 0.24, 0.25"
 FileIO = "1, 1.1, 1.2, 1.3, 1.4, 1.11"
-HDF5 = "0.12, 0.13, 0.15"
+HDF5 = "0.12, 0.13, 0.15, 0.16"
 JLD2 = "0.2, 0.3, 0.4"
 JSON = "0.21"
-LightGraphs = "1, 1.1, 1.2, 1.3"
+Graphs = "1, 1.6"
 SimpleWeightedGraphs = "1, 1.1, 1.2"
 StatsBase = "0.32, 0.33"
-julia = "1.2"
+julia = "1.6"
 StableRNGs = "1"
 
 [extras]

README.md

@@ -14,11 +14,11 @@ To install Julia, please follow instructions on https://github.com/JuliaLang/jul
 In an interactive Julia session, you can then install FlashWeave after typing `]` via
 
 ```julia
-(v1.2) pkg> add FlashWeave
-# to run tests: (v1.2) pkg> test FlashWeave
+(@v1.6) pkg> add FlashWeave
+# to run tests: (@v1.6) pkg> test FlashWeave
 ```
 
-**Important note: from version 0.17, FlashWeave dropped support for Julia versions < 1.2. If you want to use FlashWeave with older Julia installations, make sure to install FlashWeave 0.16.0 (or lower) via `]` + `add FlashWeave@0.16.0`.**
+**Important note: from version 0.19, FlashWeave dropped support for Julia versions < 1.6 (the new LTS version). If you want to use FlashWeave with older Julia installations, make sure to install FlashWeave 0.18.1 (or lower) via `]` + `add FlashWeave@0.18`.**
 
 ## Latest changes ##
 

src/FlashWeave.jl

@@ -6,7 +6,7 @@ using SharedArrays, LinearAlgebra, Dates
 
 # data structures
 using DataStructures
-using LightGraphs, SimpleWeightedGraphs
+using Graphs, SimpleWeightedGraphs
 import SimpleWeightedGraphs: nv, edges, ne, vertices
 
 # statistics

src/interleaved.jl

@@ -191,7 +191,7 @@ function interleaved_backend(target_vars::AbstractVector{Int}, data::AbstractMat
                 println("\nTime passed: ", Int(round(curr_time - start_time)), ". Finished nodes: ", length(target_vars) - remaining_jobs, ". Remaining nodes: ", remaining_jobs)
 
                 if check_convergence
-                    println("Convergence times: $last_conv_time $(curr_time - last_conv_time - start_time) $((curr_time - last_conv_time - start_time) / last_conv_time) $(LightGraphs.ne(graph) - last_conv_num_edges)")
+                    println("Convergence times: $last_conv_time $(curr_time - last_conv_time - start_time) $((curr_time - last_conv_time - start_time) / last_conv_time) $(Graphs.ne(graph) - last_conv_num_edges)")
                 end
 
                 print_network_stats(graph)
@@ -204,15 +204,15 @@ function interleaved_backend(target_vars::AbstractVector{Int}, data::AbstractMat
             if !check_convergence && remaining_jobs / jobs_total <= conv_check_start
                 check_convergence = true
                 global last_conv_time = curr_time - start_time
-                global last_conv_num_edges = LightGraphs.ne(graph)
+                global last_conv_num_edges = Graphs.ne(graph)
 
                 verbose && println("Starting convergence checks at $last_conv_num_edges edges.")
 
             elseif check_convergence
                 delta_time = (curr_time - start_time - last_conv_time) / last_conv_time
 
                 if delta_time > conv_time_step
-                    new_num_edges = LightGraphs.ne(graph)
+                    new_num_edges = Graphs.ne(graph)
                     delta_num_edges = (new_num_edges - last_conv_num_edges) / last_conv_num_edges
                     conv_level = delta_num_edges / delta_time
 

src/misc.jl

@@ -185,12 +185,12 @@ function level_map!(Zs::NTuple{N,T} where {N,T<:Integer}, data::AbstractMatrix{E
 end
 
 
-function print_network_stats(graph::LightGraphs.Graph)
-    n_nodes = LightGraphs.nv(graph)
-    n_edges = LightGraphs.ne(graph)
+function print_network_stats(graph::Graphs.Graph)
+    n_nodes = Graphs.nv(graph)
+    n_edges = Graphs.ne(graph)
     println("Current nodes/edges: $n_nodes / $n_edges")
     println("Degree stats:")
-    deg = LightGraphs.degree(graph)
+    deg = Graphs.degree(graph)
     println(summarystats(deg))
     deg_median = median(deg)
     if deg_median > n_nodes/4

test/learning.jl

@@ -1,7 +1,7 @@
 using FlashWeave
 using Test, Random, StableRNGs
 using SimpleWeightedGraphs
-using LightGraphs
+using Graphs
 using SparseArrays, DelimitedFiles, Statistics, Distributed, Logging
 import SimpleWeightedGraphs: nv, edges, ne, vertices, neighbors