ecoz2 python wrapper

WIP

Development

Setup

pip3 install [--user] virtualenv

virtualenv -p python3 .env
source .env/bin/activate    
pip install -r requirements.txt

Build

ecoz2 is included as a submodule.

git submodule foreach "(git checkout master; git pull)"

cffi based wrapper

$ cd ecoz2py

# on a mac with gcc (not clang):
$ CC=gcc-9 make

# on linux  (build ok on a centos7 docker container)
$ make

$ cd ..

A more regular test as "client" of the lib:

$ export PYTHONPATH=.:ecoz2py

$ python ecoz2_hmm_learn_test.py
USE_WANDB: False
ECOZ2 C version: b'0.3.0'
ecoz2_set_random_seed: seed=1
hmm_learn: num_sequences = 11
  0: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__10079.092_10080.35.seq
  1: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__680.14154_680.8046.seq
  2: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__1089.723_1090.6355.seq
  3: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__5067.5444_5070.2764.seq
  4: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__12907.783_12909.293.seq
  5: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__588.77454_591.3191.seq
  6: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__15415.037_15417.307.seq
  7: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__1068.8552_1069.205.seq
  8: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__2926.575_2929.6223.seq
  9: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__10540.822_10543.197.seq
 10: ecoz2py/data/sequences/TRAIN/M1024/B/from_MARS_20161221_000046_SongSession_16kHz_HPF5Hz.wav__7145.495_7147.0107.seq

N=8 M=1024 type=3  #sequences = 11  max_T=201
val_auto = 0.3   log=-1.20397
max_iterations= -1
. 1: Δ = +43.4016  sum_log_prob = -5228.75 sum_log_prob_prev = -5272.16  'B'  (0.012s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5228.7540730621
. 2: Δ = +14.7201  sum_log_prob = -5214.03 sum_log_prob_prev = -5228.75  'B'  (0.010s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5214.033997162085
. 3: Δ = +7.04086  sum_log_prob = -5206.99 sum_log_prob_prev = -5214.03  'B'  (0.011s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5206.993136338338
. 4: Δ = +20.8825  sum_log_prob = -5186.11 sum_log_prob_prev = -5206.99  'B'  (0.010s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5186.110655885082
. 5: Δ = +36.1808  sum_log_prob = -5149.93 sum_log_prob_prev = -5186.11  'B'  (0.012s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5149.9298841011805
. 6: Δ = +48.584  sum_log_prob = -5101.35 sum_log_prob_prev = -5149.93  'B'  (0.010s)
P: hmm_learn_callback: variable=sum_log_prob, value=-5101.345860730357
. 7: Δ = +258.061  sum_log_prob = -4843.29 sum_log_prob_prev = -5101.35  'B'  (0.010s)
P: hmm_learn_callback: variable=sum_log_prob, value=-4843.285099164055
. 8: Δ = +0.660446  sum_log_prob = -4842.62 sum_log_prob_prev = -4843.29  'B'  (0.010s)
P: hmm_learn_callback: variable=sum_log_prob, value=-4842.624653418044


    Model: data/hmms/N8__M1024_t3__a0.3/B.hmm   className: 'B'
    N=8 M=1024 type: cascade-3
    restriction: 1e-05
            #sequences: 11
            auto value: 0.3
          #refinements: 8
              Σ log(P): -4.842625e+03
training took 0.10s

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Note: ecoz2_vq_learn_test.py also runs fine, but requires some data from the ecoz2-whale project.