These rules are adopted from the AngularJS commit conventions.
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I have to be frank here, this is going to be | |
- criticism of thrust | |
- Showing off ArrayFire (of which I am a core developer) | |
*Criticism of thrust* | |
They do a good job at optimizing parallel algorithms for vector inputs. | |
They use data level parallelism (among other things) to parllelize algorithms that work really well for large, vector inputs. | |
But they fail to improve upon it and go all the way to perfom true data level parallelism. i.e. a large number of small problems. |
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function [fx,fy] = polyDer2D(p,x,y,n,m) | |
%POLYDER2D Evaluate derivatives of 2-D polynomial using Horner's method. | |
% F = POLYDER2D(P,X,Y,N,M) evaluates the derivatives of 2-D polynomial P at | |
% the points specified by X and Y, which must have the same dimensions. The | |
% outputs FX and FY will have the same dimensions as X and Y. N and M specify | |
% the order of X and Y respectively. Polynomial coefficients are in the | |
% following order. | |
% | |
% F(X,Y) = P_1 * X^N * Y^M + P_2 * X^{N-1} * Y^M + ... + P_{N+1} * Y^M + ... | |
% P_{N+2} * X^N * Y^{M-1} + P_{N+3} * X^{N-1} * Y^{M-1} + ... + P_{2*(N+1)} * Y^{M-1} + ... |
Python version of the MATLAB code in this Stack Overflow post: https://stackoverflow.com/a/18648210/97160
The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.
Implemented in Python + NumPy + SciPy + matplotlib.
- Install FSL using a compatible shell (bash or tcsh), using the usual method.
- Copy
fsl.fish
to the appropriate location (usually/usr/local/fsl/etc/fslconf/
). - Append the contents of
config.fish
to your ownconfig.fish