2019b | Material de clase de la cursada 2019 , segundo cuatrimestre

Tl; Dr: Is there a way to have unmatched optional name-value arguments in Matlab's new (2019b) function argument validation?

I have existing Matlab code that uses an input parser to dispatch optional arguments to my sim. The sim is set up such that you choose a few functions that dictate how your object behaves in its environment, and you call runSim. In this imaginary example, my sim is being defined with two functions that take both unique and common optional inputs.

runSim('sharedArg', sa, 'func1Arg1', f1a1, 'func1Arg1', f1a2, 'func2Arg1', f2a1)

runSim will call the appropriate functions that you chose to define your sim, and pass those optional arguments along to each function. In this case, the input parser in func1 will ignore func2arg1 and the input parser in func2 will ignore func1Arg1 and func1Arg2.

Everything works great, but my sim spends a third of its time doing input parsing, as these functions are called thousands of times in a loop. And Matlab's input parser has a documented history of being slow as (insert profanity here).

Having recently updated to 2020a, I have discovered function argument validation, which is a lot less terrible than input parsers. Having tested it out on a few of much functions, not only is the code much more readable, but I'm seeing a huge boost in performance.

I have two rules for STAR, STAR_genome does some indexing for the STAR rule, therefore the input of STAR is the direct output from STAR_genome - so far so simple. But when I try to run this, the STAR_genome rule is ignored (not listed in job count) and I get the following exception:

FileNotFoundError: [Errno 2] No such file or directory: '[...]STAR/cauliflower/genome/genome.ok'

I don't understand why snakemake would ignore the generating rule and just complain about a missing file instead, as it even takes the path from the very rule that should generate it...

Using MATLAB Coder in 2019b, the following line:

I have a working Azure CI pipeline doing building code gen operations with Matlab 2019. The Matlab project is written for Matlab 2017B. it also builds/work locally with Matlab 2017b or 2019b.

ENV:

It's a self-hosted windows 10 computer connected to Azure Pipelines with multiple version of Matlab. Matlab 2017B is a node-locked license. Matlab2019B is a floating license.

ACTION:

I changed the Matlab version used by the script to 2017B and ran my script to match production server specification.

I'm trying to compile a Fortran subroutine in the remote machine, when I run:

R CMD SHLIB -fPIC vintp2p_afterburner_wind.f

I get the following error:

How can I delete all-zero pages from a 3D matrix in a loop?

I have come up with the following code, though it is not 'entirely' correct, if at all. I am using MATLAB 2019b.

I have two threshold values (scalars) that I would like to run through my for loop, and subsequently plot each 'meanMUA' (for that particular threshold value) as a subplot.

I attempted the following, but the 'meanMUA' for threshold1 is subplotted in both specified positions, rather than the 'meanMUA' for threshold1 (in position 1) and threshold2 (in position 2):

I would like to non-circularly shift my matrix and then have zeros padded to either the left or right (depending on the shift) i.e. if the matrix shifts to the right, zeros would be padded to the left.

I am using MATLAB 2019b and my code so far looks like this:

I have neural data collected across 16 different channels. This data was recorded over a 30 second period.

Over a 10s period (from 20 - 30s), I want to record the number of neural data points that are greater than or equal to a specified threshold. I would like to do this according to bins of 0.001s.

I am using MATLAB 2019b.

My code so far looks like this: