Why do you save figure (.fig) files?
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I rarely/never save .fig files
47%
Continue working on it later
16%
Archive for future reference
23%
Share within my organization
10%
Share outside my organization
2%
Other (please leave a comment)
2%
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I would say "rarely" but I came up with at least a theoretical use case in a personal project yesterday: saving an image version captures the manually changed aspect ratio by dragging window on screen, so it occurred to me to save a Fig before such changes since it would be a reusable snapshot of the version generated by code. Wasn't compelling enough to actually do for my case, but it occurred to me.
Thanks for participating in the poll! Your comments have been helpful to understand how you are saved figures.
Generally, I try to store the results of my data analysis jobs in a structured and reusable form in Matlab files. In these files I try to store these data in Matlab native data types (like structs, arrays, tables, ...).
For the visualization I create functions that creates the visualization based on these data structures. Therefore, I don't need to store Matlab figures because they can be reconstructed quickly. For improving my visualization, I only must tweak my visualization functions.
For sharing my results, I typically use graphics files like (pdf, svg, png or jpeg). But I would prefer to share more interactive results in a vendor neutral format like it's done in plotly (Plotly Open Source Graphing Libraries). In this case I can share results to colleagues who are not using Matlab in a very user-friendly form.
I am very dissatisfied with the Matlab implementation of the data analysis functions (histogram, boxplot, Rainflow counting and spectral analysis). I therefore had to implement these functions myself. For each of these analysis functions I have a class that implements methods for scaling, shifting, weighting, combining and visualization. These objects can be easily saved and loaded. It is therefore not necessary to save Matlab Figures.
Matlab has a non-transparent user interface for these analysis functions. A negative example is the histogram function: If I use the histogram function with outputs, I get the results but then I must create my visualization with basic Matlab plot functions. If I use histogram to create the visualization, then all my samples (typically millions to billions of data points) are included in the figure which increases the size of the figure file (e.g. 100 million data points creates a file size of 1.44GB). Nevertheless, it’s not possible to scale the data or combine different results.
From my point of view the demand to store figures comes from the bad design of MATLAB’s basic data analysis functions. Matlab should encourage user to separate data and analysis results from visualization code. First, in their own functions. To share results vendor neutral interactive html graphics like it’s produced by plotly would be the best.
> If I use the histogram function with outputs, I get the results but then I must create my visualization with basic Matlab plot functions.
Thanks for the comment, Martin. The histogram function returns a Histogram graphics object after it creates the histogram chart. No need to use the output to produce the visualization. Perhaps you are refrerring to histcounts that bins the input data and returns the bin count and edges. Those outputs can be directly fed into the histogram function using the following.
[N, edges] = histcounts(randn(1,10000));
histogram('BinEdges',edges,'BinCounts',N)
Thanks for this hint. This is a very good extension of the histogram function.
I recently discovered also that this function was added. I'm sure it wasn't included from the beginning. Normally I'm reading the release notes, but I can't remember for any hints to this new possibility.
If you could tell my how to create a boxchart out of a histogram or the given relevant statistic value (minimum, maximum, lower and upper quantile, median value) I would be very happy.
histcounts() and histogram() were introduced in R2014b. Before that one used histc() to (just) do counting, and hist() to do count-and-display.
histogram() and histcounts() are more flexible, especially towards recalculating when the number of bins or bin boundaries change.
For figures that will eventually go in a report of some kind, I like to save one PDF or SVG version (for use in the document) and one copy of the .fig. With that, it's easy to make edits to the figure appearance to match formats, address editor requests, etc., without having to rerun the whole code. With smaller datasets, rerunning the code can be fine, but for bigger ones, it can be time consuming for small edits.
Fig file is one of the importnat tools in Matlab. One can run many separated scripts independentelly and collect their results on one Fig file.
I save fig files when there are multiple signals on the figure and it would be harder to analyse them when it is as pdf or an image file and if they are very close to one another.
I save fig files if I want to annotate data in more than one way, or show a complex diagram being built up in stages. I don't want to have to recalculate every step for each annotation.
I only save as .svg for school lab reports
I tend to only safe .fig files if I have a unique sort of figure that involved manual property editing. Otherwise, I'll just script the format as needed and directly save as a vector file. With that being said, I can only recall having that .fig coming in handy once or twice so rarely would bother these days.
I always alwasy always save a .fig along with a viewable format. I make figures primarily to present design results and probably 30% of figures I have to go back and edit (label, add a notation). Epecially when dealing with complicated derived data based off of GBs of information that I can't trivially just 'run again'; its essential for me to be able to go back an manipulate a figure directly and quickly.
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