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@ -28,6 +28,7 @@ The **Gnuplot.jl** package allows easy and fast use of [gnuplot](http://gnuplot.
- save sessions into gnuplot scripts, to enable easy plot customization and reproducibility. - save sessions into gnuplot scripts, to enable easy plot customization and reproducibility.
If you're unfamiliar with gnuplot have a look at: If you're unfamiliar with gnuplot have a look at:
- [Main gnuplot site](http://gnuplot.info/) - [Main gnuplot site](http://gnuplot.info/)
- [gnuplot FAQ](http://gnuplot.info/faq/index.html) - [gnuplot FAQ](http://gnuplot.info/faq/index.html)
@ -37,11 +38,12 @@ If you're unfamiliar with gnuplot have a look at:
A powerful plotting framework is among the most important tool in the toolbox of any modern scientist and engineer. As such, it is hard to find a single package to fit all needs, and many solutions are indeed available in the Julia [ecosystem](https://github.com/JuliaPlots). A powerful plotting framework is among the most important tool in the toolbox of any modern scientist and engineer. As such, it is hard to find a single package to fit all needs, and many solutions are indeed available in the Julia [ecosystem](https://github.com/JuliaPlots).
**Gnuplot.jl** package fills the niche of users who needs: **Gnuplot.jl** package fills the niche of users who needs:
1. publication-quality plots, by exploiting the capabilities of a widely used tool such as gnuplot, and its many output formats available; 1. publication-quality plots, by exploiting the capabilities of a widely used tool such as gnuplot, and its many output formats available;
1. a well-documented framework, by taking advantage of all the gnuplot documentation, tutorials and examples available on the web; 2. a well-documented framework, by taking advantage of all the gnuplot documentation, tutorials and examples available on the web;
1. a fast response, by relying on an external program (rather than on a large Julia code base); 3. a fast response, by relying on an external program (rather than on a large Julia code base);
1. an interactive data exploration framework, by exposing a carefully designed, extremely concise and easy to remember syntax (at least for users with minimal gnuplot knowledge); 4. an interactive data exploration framework, by exposing a carefully designed, extremely concise and easy to remember syntax (at least for users with minimal gnuplot knowledge);
1. a procedure to decouple plot data and aesthetics from the Julia code used to generate them. 5. a procedure to decouple plot data and aesthetics from the Julia code used to generate them.
Unlike other packages **Gnuplot.jl** is not a pure Julia solution as it depends on an external package to actually generate plots. However, if gnuplot is not available on a given platform, the package could still be used in "*dry*" mode, and no error for a missing dependency will be raised (see [Dry sessions](@ref)). Unlike other packages **Gnuplot.jl** is not a pure Julia solution as it depends on an external package to actually generate plots. However, if gnuplot is not available on a given platform, the package could still be used in "*dry*" mode, and no error for a missing dependency will be raised (see [Dry sessions](@ref)).
@ -50,7 +52,7 @@ The **Gnuplot.jl** package development follows a minimalistic approach: it is es
The functionalities 1, 2 and 3 listed above are similar to those provided by the [Gaston](https://github.com/mbaz/Gaston.jl) package. **Gnuplot.jl** also provides features 4 and 5, as well as the minimalistic approach. The functionalities 1, 2 and 3 listed above are similar to those provided by the [Gaston](https://github.com/mbaz/Gaston.jl) package. **Gnuplot.jl** also provides features 4 and 5, as well as the minimalistic approach.
## Do Gnuplot.jl suits my needs? ## Does Gnuplot.jl suit my needs?
Any modern plotting package is able to produce a simple scatter plot, with custom symbols, line styles, colors and axis labels. Indeed, this is exactly the example that is reported in every package documentation (also here: see [2D plots](@ref plots2d)). Still, producing complex and publication-quality plots is not an easy task. As a consequence is also not easy to determine whether a package can cope with the most difficult cases (unless you actually try it out) and a reasonable choice is typically to rely on the size of the user base, the availability of documentation / tutorials, and the possibility to preview complex examples. Any modern plotting package is able to produce a simple scatter plot, with custom symbols, line styles, colors and axis labels. Indeed, this is exactly the example that is reported in every package documentation (also here: see [2D plots](@ref plots2d)). Still, producing complex and publication-quality plots is not an easy task. As a consequence is also not easy to determine whether a package can cope with the most difficult cases (unless you actually try it out) and a reasonable choice is typically to rely on the size of the user base, the availability of documentation / tutorials, and the possibility to preview complex examples.