diff options
| -rwxr-xr-x | gen-prime.sh | 4 | ||||
| -rw-r--r-- | model.py | 16 |
2 files changed, 11 insertions, 9 deletions
diff --git a/gen-prime.sh b/gen-prime.sh index e1b0d1d..32eace3 100755 --- a/gen-prime.sh +++ b/gen-prime.sh @@ -46,11 +46,11 @@ function gen_prime () { echo "__________________" echo ">> saving $exp_name - $tag" - ./latest.pl -nl $tag $exp_name + ./latest.pl -n $tag -l $exp_name } function gen_prime_set () { - gen_prime $1 6 44100 'zero' + # gen_prime $1 6 44100 'zero' gen_prime $1 6 44100 'noise' gen_prime $1 6 44100 'sin' 440 gen_prime $1 6 44100 'noise' 0 0 True @@ -332,25 +332,27 @@ class PrimedGenerator(Runner): print("_______-___-_---_-____") print("_____________--_-_-_______") - print("INITTTTTTTT") + print("INITTTTTTTT {}".format(primer)) + if recursive: + print "RECURSIVE" print(sequences.shape) print("__________________--_-__--_________________") print("__-__________-_______________") - def noise(x): - for i in xrange(n_samples): + def _noise(x): + for i in range(n_samples): x[:, i] = random.triangular(q_min, q_max) return x - def sin(x): + def _sin(x): primer_freq = prime_param_a - for i in xrange(n_samples): + for i in range(n_samples): x[:, i] = (math.sin(i/44100 * primer_freq) + 1) / 2 * (q_max - q_min) + q_min return x sequences = { 'zero': lambda x: x.fill_(utils.q_zero(self.model.q_levels)), - 'noise': noise, - 'sin': sin, + 'noise': _noise, + 'sin': _sin, }.get(primer, 'zero')(sequences) for i in range(self.model.lookback, self.model.lookback + seq_len): |