In programming, for loops are used to automate repetitive tasks, such as analysing similar datasets from different subjects. Sometimes, a dataset might be slightly different to another such that the data can be used but needs to be analysed differently in the loop. For example, data might have been accidentally sampled at a higher rate, or a nested trial needs
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Spike2 is a piece of software written by the folks at CED (Cambridge Electronic Design) to collect data with their data acquisition boards. As pointed out in a previous post, Spike2 can be used to analyse data. However, the drop-down menus and options make it difficult to ensure processing is consistent from session to session. Spike2 comes with its own
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We have seen how Matplotlib’s ginput() function can be used to mark regions of interest on plots. Sometimes, the fine details of a plot can only be viewed by using the zoom and pan features to visualise the data. Zoom (magnifying glass icon) and pan buttons (square with 4 arrows icon) are available by default in the toolbar of a
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Suppose you have some big data files to analyse, and you would like to know roughly how long it takes to run the analysis. This is so that in future, if you had to re-run the analysis, you could gauge that it will take long enough to go get a coffee or work on another job while you wait for
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In a previous post we learned how to use matplotlib’s gridspec to make subplots of unequal size. gridspec is quite powerful, but can be a little complicated to use. This is especially true if you are coming to Python from Matlab. In the current post we learn how to make figures and subplots in a manner that will be more
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Scientific figures are at their most informative when they include the individual data used to calculate summary statistics such as means and standard deviations. Why is showing data important? As previously pointed out here and here, figures with means, standard deviations, standard errors, etc. can be misleading and conceal the nature of the underlying data. As highlighted in our previous
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