A V0 implementation tested against matlab

Supports:
 - HDF5 file load and store
 - Precision timing of the process to stdout
 - logging (verbose mode) to stdout
 - Command line arguments and help

homework_1/matlab/.gitignore

@@ -0,0 +1,2 @@
+# matlab
+*.m~

homework_1/matlab/dist2.m

@@ -1,10 +1,12 @@
 function [D2] = dist2(X, Y)
 % Calculates the squares of the distances of X and Y
 %
-% X: A mxd array with m d-dimentional points
-% Y: A nxd array with n d-dimentional points
+% X: A Mxd array with m d-dimentional points
+% Y: A Nxd array with n d-dimentional points
 % d: Must be the same
-
+%
+% D2: The MxN matrix with the distances
+%
     [~, d1] = size(X);
     [~, d2] = size(Y);
     if d1 ~= d2

homework_1/matlab/knnsearch2.m

@@ -1,8 +1,12 @@
 function [idx, dst] = knnsearch2(C, Q, k)
-% C: Is a mxd matrix (Corpus)
-% Q: Is a nxd matrix (Query)
-% k: The number of nearest neighbors needded
-
+% C:   Is a MxD matrix (Corpus)
+% Q:   Is a NxD matrix (Query)
+% k:   The number of nearest neighbors needded
+% idx: Is the Nxk matrix with the k indexes of the C points, that are
+%      neighbors of the nth point of Q
+% dst: Is the Nxk matrix with the k distances to the C points of the nth
+%      point of Q
+%
     % Calculate the distance matrix between C and Q
     % D is an m x n matrix where each element D(i, j) is the distance 
     % between the i-th point in C and the j-th point in Q.