R VERSION OF MATLAB INTERP1 FULL
R VERSION OF MATLAB INTERP1 CODE
R VERSION OF MATLAB INTERP1 DOWNLOAD

Yes, they are important, but supporting tensor operations, introducing state-of-the-art ODE solvers (as Julia's wonderful DifferentialEquations.jl ) would be more useful for a scientist. To me, MATLAB's focus should be on computational mathematics (as it originally was) and not polishing the IDE and other secondary issues. The core numerical algorithms changed very little in the past 20 years.

TMW's focus on shiny features and the toolboxes.

R VERSION OF MATLAB INTERP1 DOWNLOAD

Moreover, the MATLAB runtime is huge, so for a simple application, you have to download hundreds of megabytes.

To generate standalone application, you need an additional toolbox.

R VERSION OF MATLAB INTERP1 CODE

You also cannot debug MEX code with MATLAB Editor. The really powerful MEX commands (see on UndocumentedMATLAB) are not documented and change all the time. Invoking C code, let alone C++, is difficult with the MEX interface.Moreover, launching parallel pools open new MATLAB workers that spend about 700 MB each! I didn't see any efficient massively parallel applications done by MATLAB. The fact that open source tools support many levels of parallelism and MATLAB offers it in a toolbox is a big drawback. Complex problems require fast hash maps, linked lists and other data structures. I would love to have (nearly) costless abstraction as in Julia or in C++ it happened to be that because of speed issues I had to sacrifice readability and turn to built-in types to achieve reasonable speed. To me, it is not a problem (Python also explicitly needs the instance as the first method parameter), but custom types are really slow in MATLAB. Reading the threads, people criticize the OOP syntax of MATLAB. As if the MATLAB linter was available for other editors too!

The MATLAB Editor (the classical one, not the Live Editor) is useful but misses some features that others have. MATLAB toolboxes sometimes provide a solution but university clusters often miss many toolboxes.

I can only talk about areas I experienced, but Python (and now Julia) has such an extensive ecosystem and an active and responsive community, that one does not have to start reimplementing everything. Being closed-source really hampers the development. There are too many awesome projects that stop because the maintainer a) lost interest or b) left the university and has no access to MATLAB any more. Related: I also feel that the open-source nature of Python produces quality contributors. When Python users raise issues on GitHub/Gitlab, etc., I don't have this feeling. They expect complete solutions without showing any effort.

R VERSION OF MATLAB INTERP1 FULL

However, the forum is full of people whose posts do not show any research work.

There are some heavyweight MATLAB users (Walter Roberson, Image Analyst, John D'Errico, Jan, and I'm sure I missed many of you) who have immense knowledge and are also very active on MATLAB Answers. I do not indend to start a flame war, especially because I see the merits in both languages. I will sometimes refer to Python because that's what I have experience with. I still like MATLAB because I am efficient in it, but here are some things I don't like about it. I know the thread using interp1 in R for matrix but I do not have a matrix.Before I started using Python this year, I was a happy MATLAB user. # Wanted, MATLAB: u = interp1(u, linspace(1, numel(u), numel(u)-1)) Points 'xi' outside of range of argument 'x'. I am not sure about the second interp1 parameter what is not required in MATLAB so I just let unsuccessufully y 500 k points so linear will work) and its output at the top List of 2Įrror in interp1(x, y, xi, method = 'linear') :

approx rule=1 is equivalent to MATLAB pseudocode.

Pseudocode is u = interp1(u, linspace(1, numel(u), numel(u)-1)) in MATLAB where extrapolation returns NaN if the point is outside the domain (default, more here). I am trying to interpolate linearly in R.

R version of matlab interp1