The ndgrid function almost gives the answer, but has one caveat: n output variables must be explicitly defined to call it. Since n is arbitrary, the best way is to use a comma-separated list (generated from a cell array with ncells) to serve as output. The resulting n matrices are then concatenated into the desired … Read more
MATLAB has a notion of packages which can be nested and include both classes and functions. Just make a directory somewhere on your path with a + as the first character, like +mypkg. Then, if there is a class or function in that directory, it may be referred to as mypkg.mything. You can also import … Read more
A quick way of finding the elbow is to draw a line from the first to the last point of the curve and then find the data point that is farthest away from that line. This is of course somewhat dependent on the number of points you have in the flat part of the line, … Read more
I have been using Matlab and C++ for about 10 years. For every numerical algorithms implemented for my research, I always start from prototyping with Matlab and then translate the project to C++ to gain a 10x to 100x (I am not kidding) performance improvement. Of course, I am comparing optimized C++ code to the … Read more
The one built-in to python would be multiprocessing docs are here. I always use multiprocessing.Pool with as many workers as processors. Then whenever I need to do a for-loop like structure I use Pool.imap As long as the body of your function does not depend on any previous iteration then you should have near linear … Read more
A procedure can’t return a table as such. However you can select from a table in a procedure and direct it into a table (or table variable) like this: create procedure p_x as begin declare @t table(col1 varchar(10), col2 float, col3 float, col4 float) insert @t values(‘a’, 1,1,1) insert @t values(‘b’, 2,2,2) select * from … Read more
Looping through all the files in the folder is relatively easy: files = dir(‘*.csv’); for file = files’ csv = load(file.name); % Do some stuff end
Fully numpy vectorized and generic RLE for any array (works with strings, booleans etc too). Outputs tuple of run lengths, start positions, and values. import numpy as np def rle(inarray): “”” run length encoding. Partial credit to R rle function. Multi datatype arrays catered for including non Numpy returns: tuple (runlengths, startpositions, values) “”” ia … Read more
This is strange, I am seeing f being faster while g being slower than what you are seeing. But both of them are identical for me. Perhaps a different version of MATLAB ? >> g = @() zeros(1000, 0) * zeros(0, 1000); >> f = @() zeros(1000) f = @()zeros(1000) >> timeit(f) ans = 8.5019e-04 … Read more