diff --git a/Project.toml b/Project.toml index 95002ec..0b721e6 100644 --- a/Project.toml +++ b/Project.toml @@ -2,7 +2,7 @@ name = "Microgrids" uuid = "bd581358-d3fa-499e-a26e-e70307242c03" authors = ["Pierre Haessig ", "evelisea <59697806+evelisea@users.noreply.github.com>"] -version = "0.10.0" +version = "0.10.1" [compat] julia = "1.6" diff --git a/README.md b/README.md index e648b20..8444762 100644 --- a/README.md +++ b/README.md @@ -44,9 +44,9 @@ The work on the Julia package specifically focuses on: (with respect to sizing parameters) can be computed using [ForwardDiff](http://www.juliadiff.org/ForwardDiff.jl/). - - Thanks to our careful treatment of types (and the thanks to ForwardDiff and Julia), - computing the gradient with respect to n=3 parameters is performed in less than - 2×simulation time (whereas finite difference would take n+1=4 × simulation time) + - Thanks to our careful treatment of types (and thanks to ForwardDiff and Julia), + computing the gradient with respect to n=3 parameters with ForwardDiff should run + faster than with finite differences (which take n+1 = 4× simulation time) ### Documentation diff --git a/perf/MicrogridsBenchmark.jl b/perf/MicrogridsBenchmark.jl index a2a92d1..fb69083 100644 --- a/perf/MicrogridsBenchmark.jl +++ b/perf/MicrogridsBenchmark.jl @@ -3,7 +3,7 @@ using BenchmarkTools using CSV, DataFrames using ForwardDiff -const data = DataFrame(CSV.File("$(@__DIR__)/../examples/microgrid_with_PV_BT_DG/data/Ouessant_data_2016.csv")) +const data = DataFrame(CSV.File("$(@__DIR__)/../examples/data/Ouessant_data_2016.csv")) # Simulation steps const nsteps = length(data.Load) diff --git a/perf/MicrogridsBenchmark_output.md b/perf/MicrogridsBenchmark_output.md index 2757198..6aa9325 100644 --- a/perf/MicrogridsBenchmark_output.md +++ b/perf/MicrogridsBenchmark_output.md @@ -1,7 +1,5 @@ # Run of MicrogridsBenchmark.jl on Dell notebook (i7-1165G7) -**Benchmark results outdated** -> to be run again on Dell i7 - ## System configuration Julia version 1.9.2