From 130ddad681f494bdb24f477e3c70f336b4a017b9 Mon Sep 17 00:00:00 2001 From: JanJereczek Date: Sat, 13 Jul 2024 17:05:09 +0200 Subject: [PATCH] minors for joss publication --- paper/paper.bib | 2 +- paper/paper.md | 12 ++++++------ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/paper/paper.bib b/paper/paper.bib index 7456aee..e27f5b3 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -69,7 +69,7 @@ @article{scheffer_early-warning_2009 } @article{bury_ewstools_2023, - title = {ewstools: {A} {Python} package for early warning signals ofbifurcations in time series data}, + title = {ewstools: {A} {Python} package for early warning signals of bifurcations in time series data}, volume = {8}, issn = {2475-9066}, shorttitle = {ewstools}, diff --git a/paper/paper.md b/paper/paper.md index e0891db..95af338 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -45,7 +45,7 @@ and 2095 has led to no less than 870 news outlets and 4100 tweets [@ditlevsen_wa largely because of the substantial implications of such a collapse for human societies. A common concern in the scientific community is that published work on the topic is difficult to reproduce, despite the impact it implies for humanity. Additionally, existing softwares -[@dakos_methods_2012, @bury_ewstools_2023] are well suited to apply some state-of-the-art +[@dakos_methods_2012,@bury_ewstools_2023] are well suited to apply some state-of-the-art techniques but lack the possibility of being easily extended by the users, thus making them unsuited for some research task. Both of these issues can be largely addressed by a unifying software that is accessible, @@ -106,12 +106,12 @@ fig = plot_changes_significance(results, signif) We apply this code to data generated by a Ricker model presenting an abrupt transition at $t = 860$, which is used in the first tutorial of `ewstools` [@bury_ewstools_2023], the most recent software covering similar functionalities. -The results are shown in [Fig. 1](@figure1) and display, as expected from CSD theory, an +The results are shown in \autoref{fig:figure1} and display, as expected from CSD theory, an increase in both variance and AR1 coefficient, which is exactly the same as computed by `ewstools`. However, calling `signif.pvalues` shows that the increase in variance is not significant ($p = 0.284$), whereas the increase in AR1 coefficient is ($p = 0.001$). -![Output of plotting function in usage example.\label{fig: fig1}](figures/figure1.png) +![Output of plotting function in usage example.\label{fig:figure1}](figures/figure1.png) We believe that a concise and unambiguous code will greatly reduce the programming effort of many researchers and ease the code reviewing process. Finally, the code @@ -228,13 +228,13 @@ TransitionsInTimeseries.jl. Using TransitionsInTimeseries.jl, we reproduced the computations showcased in Tutorial 1 and Tutorial 2 of the `ewstools` (v2.1.0) documentation, along with the block bootstrapping. -The runtimes of both softwares are benchmarked in [Fig. 2](@figure2). +The runtimes of both softwares are benchmarked in \autoref{fig:figure2}. It appears that most computations are faster in TransitionsInTimeseries, with a speed-up factor ranging from 0 to 3.5 orders of magnitude. The implementation of the deep-learning -classifiers for transition prediction developed in [@bury_deep_2021], as well as dealing with +classifiers for transition prediction developed in @bury_deep_2021, as well as dealing with multidimensional timeseries, are part of future developments of TransitionsInTimeseries.jl. -![Performance comparison between `ewstools` and TransitionsInTimeseries.jl.\label{fig: fig2}](figures/figure2.png) +![Performance comparison between `ewstools` and TransitionsInTimeseries.jl.\label{fig:figure2}](figures/figure2.png) # Documentation