ó ½h9Tc@sâddlTddlTddlTddedded„Zdd eed „Zd d „Zd d„Ze dkrÞe ƒGHeƒZ dGHdZ ee ƒ\Z Zee eƒZeeƒZeeƒZdGeƒe GdGHndS(iÿÿÿÿ(t*tdb2iii(tenergyc Cs²t|d|d|ƒ}t|dƒtkrgt|dtjdƒ}t|dtjdƒ} n|d}|d} |dkrµ||| …dd…f} | jdƒ} n|dkr ||| …dd…f} | jdƒ} t| ƒ} td| fƒ} n|dkrt||| …dd…f} | jdƒ} t| ƒ} t| ƒ} tdd| fƒ} n|tkr¨t | t |ƒt |ƒd d ƒ} n|| fS( s Computes a DWT (Discrete Wavelet Transform) and a detector based on the energy of the signal @signal: numerized audio signal @wavelet: PyWavelets wavelet type @level: level of decomposition. Level=6 gives 2 ^ 6 = 64 rows @normalized: normalization of the scalogram @freq_range: frequency range where we look for information @detector_type: energy, diff(energy) or diff(diff(energy)) @smooth: smoothing of the detector with a moving average ie convolution with ones(x) returns: an array detector made accordingly to the specified rulestwavelettleveliiRNtd_energyt d2_energytmodetsame( t scalogramttypetinttvaluestshapetsumtdiffthstacktFalsetconvolvetonestfloat( tsignalRRt normalizedt freq_ranget detector_typetsmoothtscaloth_freqtl_freqtdetector((sK/net/nas-lsis-3/SABIOD/METHODES/NICOLAS/NORTEK/CODE/transient_detector_2.pyRs.          (tmeangà?cCs®|s‰|dkrF|r/d||jƒ}q†d||jƒ}q‰|dkr‰|rod|t|ƒ}q†d|t|ƒ}q‰n|rž||k}n ||k}|S(sÊTransforms a detector array into a boolean array, with 1 where there is a detection and 0 otherwise @scalo: scalogram @detector: detector previously computed on the scalogram @threshold_type: mean or average @threshold_coeff: if threshold_coeff == 0.3, values 30% above the signal.mean() will trigger a detection @external: absolute threshold, if previously computed on a broader time window @above: > or < threshold returns: a booleanized detectorRitmedian(RR(RRtthreshold_typetthreshold_coefftexternaltabovet thresholdt booleanized((sK/net/nas-lsis-3/SABIOD/METHODES/NICOLAS/NORTEK/CODE/transient_detector_2.pyR%7s    gš™™™™™É?cCs5t|ƒtt|ƒƒ|kr+t}nt}|S(sÍReturns the decision based on the per sample detection @booleanized: booleanized detector @threshold: % of detection above which we decide the window is actually positive returns: a decision (boolean)(RRtlentTrueR(R%R$tdecision((sK/net/nas-lsis-3/SABIOD/METHODES/NICOLAS/NORTEK/CODE/transient_detector_2.pyR(Vs" gš™™™™™¹?cCsOt|ƒ}t|ƒtt|ƒt|dAƒƒ|krEt}nt}|S(sReturns the decision based on decisions made on several windows of signal @decisions: decisions made upon several windows of signal @threshold: % of positive decisions above which we decide the group is positive as a whole returns: a decision (boolean)i(tarrayRRR'R(t decisionsR$R(((sK/net/nas-lsis-3/SABIOD/METHODES/NICOLAS/NORTEK/CODE/transient_detector_2.pyt agregatedes  0 t__main__s Testing ...sO/NAS3/SABIOD/SITE/NORTEKMED/SAMPLE_SOUNDS/BOTTLENOSE/04._Bottlenose_dolphin.wavsDone in s3seconds (the count can be wrong if on utln servers)N(ii((tpylabttimetdwt_1RRR'R%R(R+t__name__tasctimettict soundfiletscaltdetectbtdta(((sK/net/nas-lsis-3/SABIOD/METHODES/NICOLAS/NORTEK/CODE/transient_detector_2.pyts   0