GeCo3

GeCo3 is a DNA compressor that uses a neural network to do the mixing of experts.

Build

GeCo3 depends on make and gcc.

cd src
make

Example usage

Reference free:

# Compression of file BuEb, using level 1, learning rate 0.06 and 8 hidden nodes
./GeCo3 -l 1 -lr 0.06 -hs 8 BuEb

# Decompression
./GeDe3 BuEd.co

Referential:

# Compression of file GG_C4 using as reference file PT_C4.
./GeCo3 -rm 20:500:1:35:0.95/3:100:0.95 -rm 13:200:1:1:0.95/0:0:0 -rm 10:10:0:0:0.95/0:0:0 -lr 0.03 -hs 64 -r PT_C4 GG_C4

# Decompression
./GeDe3 -r PT_C4 GG_C4.co

A complete description of the parameters can be read by invoking:

./GeCo3 -h
./GeDe3 -h

Export mixer to other compressors

The mixer interface and implementation is done in:

mix.h
mix.c

The neural network implementation used by the mixer is done in:

nn.h
nn.c

fastonebigheader.h contains fast math functions, and is used by the neural network and the mixer.

NOTE: #include "defs.h" should be removed from nn.h.

With these five files integrated into the project, the compressor now needs to #include "mix.h" in the file where the mixing will occur.

The mixer is initialized with: mix_state_t *mxs = mix_init(NUMBER_OF_MODELS, ALPHABET_SIZE, NUMBER_OF_HIDDEN_NODES);

Every time a new symbol is seen the mixing is done with const float* y = mix(mxs, probs);.

probs[MODEL_IDX][SYMBOL_IDX]is a matrix with the probabilities (]0,1[) for each model and for each symbol in the alphabet. The return value contains the non-normalized probabilities for each symbol. One way of normalizing these probabilities is to divide each by the total sum.

Training must be done after invoking the mixing with mix_update_state(mxs, probs, sym, lr);. Where sym is the actual symbol seen encoded as an int [0, ALPHABET_SIZE[ andlris the learning rate.

Finally, the mixer can be freed with mix_free(mxs);