ferryzhou

select repository_url, repository_language, repository_created_at, repository_description, MAX(repository_watchers) as watches
from [githubarchive:github.timeline]
where repository_watchers > 20
group each by repository_url, repository_language, repository_created_at, repository_description
order by watches desc

ferryzhou

def initialize(args = {})
  defaults = {
    :file_list_cache_dir    => 'cache/filelists/',
    :img_root    => 'cache/img/',
    :sensor_res_img_root => 'cache/srimg/'
  }
  defaults.merge(args).each do |attr, val|
    instance_variable_set("@#{attr}", val) if defaults.has_key?(attr) && (not val.nil?)
  end if args
  setup

ferryzhou

// nY(dst_r_from + (0:rows-1), dst_c_from + (0:cols-1), :) = YY(src_r_from + (0:rows-1), src_c_from + (0:cols-1), :);
void copy_patch(Mat& nY, const Mat& YY, int dst_r_from, int dst_c_from, int src_r_from, int src_c_from, int rows, int cols) {
    int row_bytes = cols * YY.channels() * YY.elemSize1();
    const uchar* pYY = (const uchar*)YY.data + YY.step[0] * src_r_from + YY.step[1] * src_c_from;
    uchar* pnY = (uchar*)nY.data + nY.step[0] * dst_r_from + nY.step[1] * dst_c_from;
    for (int i = 0; i < rows; i++, pnY += nY.step[0], pYY += YY.step[0]) {
        memcpy(pnY, pYY, row_bytes); 
    }
}

ferryzhou

#include "mex.h"
// undef needed for LCC compiler
#undef EXTERN_C

// mex mex_show_sparse.cpp -O -largeArrayDims
// a = sparse(rand(10)<0.1)
// mex_show_sparse(a);
// b = a .* rand(10)
// mex_show_sparse(b);
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) {

ferryzhou

# given a directory or a set of files
# concatenate the binary files
# output a single binary file

# usage:
# ruby concatenate_binary_files "/xxx/xx/*.bin" "/xxx/xx.bin"

infiles = ARGV[0]
outpath = ARGV[1]
File.open(outpath, 'wb') do |outfile|

ferryzhou

int nextpow2 (int x) {
    if (x < 0)
        return 0;
    --x;
    x |= x >> 1;
    x |= x >> 2;
    x |= x >> 4;
    x |= x >> 8;
    x |= x >> 16;
    return x+1;

ferryzhou

function [I, J, xvals] = get_local_maxima(imcor, radius)
% a = rand(10);
% [I, J, xvals] = get_local_maxima(a, 3);
% figure, imagesc(a); hold on; scatter(J, I);

[m, n] = size(imcor);
nim = ones(m + radius * 2, n + radius * 2) * 1e-10;
nim(radius + (1:m), radius + (1:n)) = imcor;

cols = im2col(nim, [2*radius + 1, 2 * radius + 1], 'sliding');

ferryzhou

function val = init_option(options, name, default_val)
% usage lamda = init_option(options, 'lamda', 0.01);
    if isfield(options, name), val = options.(name); else val = default_val; end
end

ferryzhou

function t = get_threshold(v)
% pitch the lowest 20% 

[m, inds] = sort(v);

P = fix(0.2 * length(v));
nt = m(P);

P = fix(0.8 * length(v));
nt2 = m(P);

ferryzhou

function [ao, bo, offset, y] = align(a, b)
% align two signals a and b
% ao and bo are aligned ones with same length
% y is the correlation xcorr(a, b)
% a_ind + offset -> b_ind
% if offset >= 0, cut a, else cut b

an = length(a); bn = length(b);

N = max(an, bn);