From 4a2ed4aa9aa7831f0e0fb2ca71061bdecbfe052c Mon Sep 17 00:00:00 2001 From: nilomr Date: Sat, 7 May 2022 15:41:06 +0100 Subject: [PATCH] DOCS: update --- docs/contents/basic-workflow.ipynb | 4 ++-- docs/contents/kantodata-dataset.ipynb | 2 +- docs/doctrees/environment.pickle | Bin 393725 -> 393725 bytes docs/html/_autosummary/pykanto.dataset.html | 4 ++-- docs/html/_modules/pykanto/dataset.html | 2 +- .../contents/basic-workflow.ipynb.txt | 2 +- .../contents/kantodata-dataset.ipynb.txt | 2 +- docs/html/contents/basic-workflow.html | 14 +++++++------- docs/html/contents/kantodata-dataset.html | 2 +- docs/html/contents/segmenting-files.html | 4 ++-- docs/html/genindex.html | 2 +- docs/html/searchindex.js | 2 +- 12 files changed, 20 insertions(+), 20 deletions(-) diff --git a/docs/contents/basic-workflow.ipynb b/docs/contents/basic-workflow.ipynb index d446255..d31fab6 100644 --- a/docs/contents/basic-workflow.ipynb +++ b/docs/contents/basic-workflow.ipynb @@ -352,7 +352,7 @@ "\n", "# Plot an example:\n", "for vocalisation in dataset.vocs.index[:1]:\n", - " dataset.plot_voc_seg(vocalisation)" + " dataset.plot_segments(vocalisation)" ] }, { @@ -506,4 +506,4 @@ }, "nbformat": 4, "nbformat_minor": 2 -} +} \ No newline at end of file diff --git a/docs/contents/kantodata-dataset.ipynb b/docs/contents/kantodata-dataset.ipynb index d1b7889..44ab574 100644 --- a/docs/contents/kantodata-dataset.ipynb +++ b/docs/contents/kantodata-dataset.ipynb @@ -45,7 +45,7 @@ " :linenos:\n", "\n", " # Plot some information about the dataset\n", - " dataset.summary_plot(variable='all')\n", + " dataset.plot_summary(variable='all')\n", "\n", "\n", "Check sample size per individual ID in the dataset:\n", diff --git a/docs/doctrees/environment.pickle b/docs/doctrees/environment.pickle index e1b9cb8a874d85f85bfc488edefbcb0b8002d48f..d805ea691172a184423d9d3a69e18b7fa0ef21a7 100644 GIT binary patch delta 18525 zcmaicd3;sXwZHq4fiNaO!b}2*ii&Widj@7uvB)401Qj8i5pu{x24)PPBEie#PP?_$ zifz@_UsY^uZ>?3pA&MYiRfZN3Z1uH$eYU=-@73w|-TT}d5??=F{>VOi?RECr!&=|9 z_B#9W#a)BGxNFdXZ%v>V9v;r}&%|>3wI+JGwKa`?O=H8jm33}wVmRG8ad@}Z#7Met z%1}1tTGE{i2B|Q&uBx`NH8BL_Ayk@F#y;6ha;S{T?3fzUVL~Mo0pHtw9?=H%MjXc@^E@!LTY!lNCv-DmfQuXWV++C9U!I%*FNog2Q=QG5LD1>y0I zTHD5M;n{A@soC#*?np)Wc1PpScUFb%9kpM){d{<)qm~>$B|P6zYtK0np6;lMqhKJLQ`#!4wEPTDA_VN72@Hgq& z{Zl9ZSNPkG+O!=Xg}>{lO~2#&;k)S?9Wng6@Xd}|vGTX3L@&>;^P#>qZl&MQx^j7f zp16K=9^dCZt)mm=^wZfhb3MD!ZtxrFp4m6j{om?N>t^<&Yv$iZ_4!ljzQyzD|K8Y( z&Y$rDJr~TQQ|BzC2X4=yb@O`05)<*dN~hkqB5$uy7IaCUU3y)rlRTO~vrjHp8%{qw z^A2jxzJn%jm`eY&@+Nxo!dyC`Jf8-)&!Yz`^1AH}-=K$Xo=J;m_om6Y%V?7~9nVb| z2rqN!RkI4{X(xI+!eQodaugbabB%Ewr+iE;tmXHn&{-#x%ss4=0y;2JAHhP zOIv48?-w0c=UM=tR?Hji&)=Mg?WXF7d-$w<0zDPQL$^k++#r}m-8 z*EgBI7v7HbxQ@2nR)n!1g`CI4Oyl#X{gZv{fjwFRzSrpA7S9yR&6VYY<$dzFjq>^2 zBxW!<98CG{8Fn>272ZZ~a<0$icFQ$o>&&}4-Zbx60+s7Qukdb$Cfp=;=)?+-k1Cd! zEV_Er=>_%UW*)sfjn-D&o|;CFuf23f?%7U!N2-=!YO_SA#X)y0I>!S($mQtyX1Z(T zfLx9V>3;vT(#hkfz&S2WWBv>=tf386P4(5|8vTYwzdlkbju~BfG1auy91VLybEaVE z98A(8_|UKL=7P#WB~4wpG|~>fmK&@3bf|J(^*2=b>+I^f zDt~NU&5BlfZFMzmtDa9zv}M=4M97D9%j%ctwz~7=J!-EWLEdlMvie~{4$~10#pHF6 z`uF;I_-58+m(3zg4dHL-(uNPoZ|T&=V)Aa=^2R3#IYE1_c^BP$x@i=RtzAx?t)=u| z_6(a75C)P;~O{8zild|)tm038#ag+>9Eb~==eK1EuTq4NiIFUxr(-~ zE2YiP=h3lG6w`m*)`RZ3^ESGFTPf|?yqeC1^hcVvl2_=+Esv7plx&kD-~5j)E9vNa z`3Ump?ydFo-TO*u@!fst@hMo>=X%kct@+~l_H8rh4>ocEg;8v9ep?-F-OLH2A+3l$ zbJrYNwPQG4{#+rQcXtle?p{g%a8DUMboVCu@)kaoduT6o@WP>yboBN+=s(t$(!Q^j z(l@s+qc33q@4q&TuDEwGop?_veeCtoG;fDXOSTMeYuT}s(9sxG-pTM7ogGDw z?p#V8bTI3_7Wzl5!_p6nX;A_yzP^;M`gkaPI9-5WtRzu9xmcf9OOfnKXFGM zuI5i1jl*XC#2t9Ji$8Ja9e$5LamOA0gg#$eMF-i>tMLuGB{hZhk*>60)2ole`wMOZZd)h0Uf z{xbTLSKF!ndL;J!*J^3W8)dYvy`64)Dca4)Uf)QagJo^kzi|x!xUKHUt{93hkM1Fq zKFwKF+OngB79IZ!UGq#?+Z87af`@{(nv)Mk4}*U5K=g3|9tzsloL)ufXCDoxC%?A<$kIg5eq7e}r?ZO*9tzs#|L)t-!{5)LYfgFe z{6<2@?}_$q)_qsfXD^h~#e1Qm7u)I1AJ+nj>gkG~l(qfGhatfOM)ikXgqA+QS7!*u zKAu*6TurkcETdn1e1N>!_Vm9j>V|4TTj9SB>?Sa4Rs>imI9kmj0;*7OoI=4t3I#_f z6dayVaBM=sfe8giB@`TzP;fj#!4C^4I1r)WD1?GT5DJbzD9-YO2ucn;C^+t*;Glzo zBMu4c46_N9Lsfl@~eOyo5i#m>ws!bqDD={^#fX&oB6&B>wmau3G;p4d4UkeCK+g z;eGt^!#C-fzt%VNKKF{w5I=|o-77ldHNJLxMX#4?y!%TvF6UB>3%peOZC+I4>$*4m zU65mv+?Pi}r>U z9aUblyVTq+HNQ)3MVDG-m)fc>wYDy`=PuQB2>kh_Dr&#zQcHHJ{W4u^`{L8jNnd_A zU)n01IEssH-T(86?&M{9;PV^FN%m-e0;ltNcP8CNvfE0(D9Iuh*n4Ipi&acA+NEaSCMJtEinN0!5osq>c)`Vzu_89xcSkfnXd=B|dY$`W9tOfV&D7e|7;AV${yL1%XpQGSrhk~0O z3T}2N-eec%k=X)lTEx1x2&ichhS4H`rbXaPi-4IHfif+^P+A1WvTEw(k#H?Dxq*^ei|D8|D$wfA20kKfryMRo};Q$)WVDd6j$Uay=B+&EA$@GXm zJEB*YlhG03W=Dh&3 zF1h%fTgW_A=HEhQqxk+UWGadeZXq+G_d{02-@kPc=>z(TMWXq~i^vSr{lc#+U^=##d<#Y4t(d{fY{sob7Ab`A-h3weq=^3S#NPCwFZ!k5 zJIP+SmE4pg;@Vy8(5++uE540fLrx}V-9~!GU?7W^V2v)YeM>Nj3+(g~GAlGGo4PS;uy1>RPBR58GAC2DLy^M?n{l#VJA-x^(PpuIA zH&>+Trz8Hh3Sxr)FBRCC3vAMIQS4q$%A;O?A8|c=FUGXqAw_JcP5OgzoSj~ZKZ*Va zG&DI#19chcU!r$A=EFX>Nj~1~?T~Lpz5ly-m+f)H*uL)oC@!!I4jDsUWxZXZ=ZHha zSJBoibxB!7h_Puau~*-7$tWsyQ=;ZaRuU^BOpgdZ-H4fgwvv>BySP%kR8dK0=8BhQ6|nhB$#8a{ z3gS-|0-66>NV>DPib!Afw@Q*5am^K61K6T^OhRyt4oUAw%KS*m%^{FMbh)sr*govX zAt{9HmqKjqk?*X64GX@d5g%5sm>gr9SCR3#;xyts=8foT~zoh<+N_#VT?&J20H|?O4uZEUX3y9b?Z| z1OJY(-ZkWA6iaK!A{5Wnkhzh7dkWZ#8^{p$r;!jazLxZgy4(>Bd3i0l7VNugvGhXJ z?hg83cBmFB`9U$sNh8cLR$M2f)Yhf>S;Rk>D-JRe-Pxb(NI&%WMI9_z^!RYZv1~Ol zBEtTN@XTre;xYEO)j-clF%e}zigIaUwHrwf_L59` zrg!f+8?lMp7_kpYv5R%$Q5d6}NMY1AJk>T~3FdKh6O{EVJHLrc5b4mcEY*sY@5`od zCPfkX$`l#15-GB@(6`y1%|u54*S?ud6A98#NwNN5Gbu!JtUH^0C&@ucUZ2`|h!=KXBd%;F`BB?-skS?I zWBALPp@`?%x@LI$^X#Q&=-7Goc{8~l#k4IjU?Fb-+uDLKNw~G`xGuMTE<@kt^Be@#t~fz0g$A zWOp=~7|yb7@X&(3BBCGL29p(pFd`th&>}*0M5w)sOval}-vu)}|DC(ZbBs7- z0l8zh!7vU@!ZO@>HyIGUxjuUHk$cGHMNVbcU_{8;bcunDnL_f?iY*$OqsHbP*g9!4 zaG~KIQV?~#t>e8ohV`cG(Lev=+IVDcI4?%+H@1>{-FbH`?!~lEu{nDY?VMt}_M($h?D$@Ub*EUtKA6BM zHg6x64+#D;`zbF@vN!jU2}?wT{bc@Sm#y5eazjgF>(zkBazdMnt2Z zcWE7Wsa2%C3ky2Gt6XY5$Clp@IfvMtyg0%h;>9ucD_$IBXHYB=sqf!(>7b;rLwL#; zcJBVhORd6_{8yKE7hP&S&gN0bIm>Ez@it5FqMbd-i! ze%qz>u1l?_lA~J5qFCO3eD&cOm-pG$?~uWLA5B*go$O6qPp4Gh&}(~Z_=7Z={o^}i zNYB0lA*C1p(=S=f$kW;61Uvo^DH()I2KLH+iQM|8n#Rg%zxBqcIsbmoU$!l0IS-Tl zC4nI;j%3PlRnxS1+_WuKQUfW7tFEN#aXz{1?W$ay&Q7}7R9h;L$ zE|bT^29%g_!!=!uC~o*#AUn1qsj@5SzV67rYs-8N^RkLvQ&Uvm)^sWGG}ka3OEOKz zlO@Mc0#{=P4w3=ML+_D0Nr@}Fp6l4QWm~%DxH7nO+s1+@p6$u1m6RvMo+lXvvn?ly zRFXli#7>?hb4qN((@kBm4c!Se38PbVSCTO;TTyhyv7<6CY*s5jfsaa%_9L*x5;AP8V1KIb_ zlKe4JW#hPprK2`)9#b+(Q61g%VElty5c!8qEHOVtA-!n|pb9BS-;)coQKLbTB z{+Qeci`0Bo3vBd@B-;(FNL^r&?~zQxxk1h@$spSk7Fn$NaWyVG z7EDLhG&8UiU6O6d*Oho&x7_6Z?Xd+}#gfH`E_*6e+4LQ*`WT$5d9voiIyMy*rOFxP%8@GTnFI@iw6LI35U7p@EHib}Gy=s`0!ddT z*#HctG*<$^7?PkQJb> zA$h4;6lajknoknBB%|E4J@&oUkUJTqfCMRS=$0;PmZRCWp~k&HaV1;!T+4~3RqSe> zWf+R$17$Q>ave-l(Sc2-7q>Kt9d3h;Nz-FHNpq&X>1t+~G_osqrWNZj%1qOWjFM-r z|EW>#yD*HUjB?_X!#jt3!i{ov2|R`&}C0h^D=!LxoxEVTl zY%PFg#wE%0p*+5&T9&M)+@q|UlBB7&WBaZa_&{&Zb>k9NR8n2V>*5|WNoH^ViOjhr zlVHA>YwW5ff7JLAMH(v!NQSD&JE07rknykB~uQ-k)Sq?aT7*X2KWRS~^Q!e&1$bIqO z$u-3a%*a(G>;sI>RN<%1xC&S3xLzF47HQ|ax5=ceVuUx?969inK-SbaMy0xd(!hpA zE2`Dm>#LFxcWqCKYaZeV-*kKn-I|u?*`^)0mk7&%dY%iVy9R+q6z>`Xj51;M;sdUS8eF@=-Y-qlpa+jGl z=4-Z=K|Q;2XIiYZW!~Uqm{Jrc`0==`J8{L+9Z9pLz?9tpMx^VW?0a2yv?T6ZlCD{X zt7x7E{j!a~1&+z8t+M^qPRMqDxCwygqZ97yst z+vU#P2;zQVbasWsnkB(ZbrXtdYO3x7zkS*CEnSgK-7{0Vzd80eDaj-~($tK?;SLMg z>-}S+N-W(s006)POV)H#wiI{;RaT&_GPXla`$SdM;RNB>5Pcx{uoY9~z+q{gsrh=) z$tM=Oz!l(!E*qYsDJD(|2xVo@4{SrzWG5+2i2aIW6dcV&$|SdZSnP^%%2-3~WO4{3 z5ZhXof^bSREFb6<*A-WV$-x3)_0j18<{Sh70bex`KEZt}rsn8@k8=(V34RoGMGi5; z4jEky$;+UqUAZ$XmzFlW8JVUPnVpGnOY*p3aInFaYC+&gacriJ6NsjyHZ;&Q*RkN< zeAB{70uwhKV6LUAMjXc^gy*l4N5}{S^*HJ|Y7lo2yea@Mz>^-hE)3LGBdCo|f0^V) z!Dc40(ecl=Tw&6I0X)D?BG^^odQCkr3_z!qd~|yZM_A2t5LqIMlMHN7+|*qUpsA@` z*DSNMPL{-Z|PZc13uE_!`c`jT}L72EokkACrr5miZ>R`1Br|UTgux z5g8*U&>amxX1O>xyPE15cHBc?Afhed&q|=Cx}rE9PPaS~R&X4|J_Ls1DV}3_T@HW< zhiwa?bRYo(b!>?5U@NcyaIyf;v}4X7J>}3c3Qh-{y~n9z<5njN^RUnW2US<$oZyBn zA45SPh0wy195bzCK7wXLiAx?73ZGDa%|zw`)~30ttzmH-Xua=wu5RK4hy{&6H8QUZf+b;I#Tf*%X?tRYB|Lu+ zV6^;9hV+4inK+ga4}!pj$HJLKSl0+cMh?bQ;Sm6$IQkgAt=oibaBx7hjL;GXGQ1yjc3qjoMu4w>vsi;YcS~$)35H<$CSVTv5e@DVRxby# zVf!8uCvhcptS-UyWDEGGz*B3;S>Z4$#~oydp!rtZ?qXTG<0G?#fLXQ!ykc26e#?>v zXXhI{@01D^Gf9qSkx?+WtO@!RRgDuQX}lzjDJjv%O7Vtqm5r$^i)rde=pe&};7_wL zT_p~$?wX#a7>X~Y6ixPh-Nn8j3g$UF-!>gr4P+oTj@8K1qzo*>E`7~?Wm3zo29{~v z(grpo!;GZJz--M4_;EwSK@0gyAE4rEhOS~60$;Y$;j)XPuI}m*GHC|VlJFJ?sImX> zP6oDEPPs4BvJq6`B!&ze^c#Gth42Qx1gQzLv-`>qj8?MwF@|&4-8~(0!yYRMoK&nIcsh zutRO6Fd6wSoH>zLR&lOEmd}?|I0Aqka$HEg*>T;yefGGT5$z7)-^|>Yd$KCfVG~<{-lQ2GM~V z1&K0Jk352vkz~fP%E#9N*GDkuBmC24MN00A@gUJeR01F|T|^ufaiviEl0+VM>xzu0sQ1(`_|9zM{JrnV53!QkSCXCdq7MzKM$flW|Nq_1I3 z_)uUtSYsqQ`6o45RX}D1kUZ!WiL3I$Hqp z`p8$>uI=*`0`5zaEORVW7N)B6cYiP8CQUtHeem;Sry8qA$BqxV67X4_J=0L zCTA7nqaHpG<9nb;aU%JHpwPhQA0NTC8pm-*eCo@zHC?SUlTLQ!&a`0MmT%aOPkk9? zWpG=rOy2)a?4!rC_}y=ozqVUpwz%BRu36V@2yRCl*wAelinlg&yIkD6PL$A%|1&a% zE8Rmkb}L28l#Sg6MlYAF?>1yG?is&q-mmcZZ_sO->RsHF7A?K1YHhE=StVK`T2rEsemb!zsqF2x>2};Qe&)~JhG_h{ zN1|Y!U2j+W_~mWG*rq!4gey7z&?WWRsyHsqQG{60vcPqkmwQ0Kdi z^|dR|Pph~klIYdtKVC@DsvGL?1>CEswi{NZ_hO2zf$L?PQh zCabU;h{=ORS${4P*NzhdneCCmgZUNYL_S})YTvG@Xh5IHR<(xb*u`tJN^^O06L_cP zlYz-mW3#qhF^JzsPV`;rISnpeaI5fRUoPI=Ney!DRsPHOX+*QY2+EZCY=py%Y zRAkE7DyuMjLF?UMukrCqEb+fHdNs2 zRV7p=#T@a84mdMAbUKUQ{yBd-Yv5IarAL7OCnRkIg3_n91{dlZDr$p(m;9{}XR=1% ztx0FHu4E-cva@mHb7Vd4S077a$6lW*Zq_CSuz6*qaG3a+NuqBZ?4XNw^4quH8I(OB zi$AatgR+O<`q8t4vxlKLJ~(^$FiubO;VXy{tw|3_PzSP4&%_26v_^gBtOY~uTGZIM zA=yPE1V%N{_nw%9_U1 z&Ik(r%Y^Dm`~p2{@9ElAZiTzDsb&>Aj9%fR?4U4P&F()~H01OBg|anr)rt1{Ew)R| z9wKfOa}6pu8!Jq{qGlHs_2XBk5_z@wpDrp^Y^bbj4PRk@o|!!?o70=_e+CA0Q+C~i zEPm0Jjl4U%a1nn>^qp5<8(v=t%&_bDf0EHEe!r6#+(C|@q#|snt*NNuzyFOG3RAk- zP_eecuBoX_{nsqvaYnXh7Y!7Bi`D1KR#9g+uHo;6^h1Qb?aAgkWFFR@#K>2 z*`s?F@!vxy^7#J%BSf}}9}+dO!??zqe0pE@*h12teE;$6oBGYRTgsIfLpSj5$uPa6bQ_k8xC$%3)(v?i~zc3P+T2y&1A zL+L)pZ?rjHM;$iN`7abD&pn^Lpf9fajXRQEcn!a5mdF$4#n-M?{NyRoYi?6@-TE79 z+**&rmS7sdKHW`<28-uj)%GgCqS3C8Y?RZQ=!LtBlFuE delta 18370 zcmai6d3;sHy?1Ul!jcdmfdohbiHeGF&OPVcb1ulHf(xL52#6TMSs{mPWMRiBDiXb{ z6P;R1ajA8w3pTb_>%vlvD~nYTSHQMfTc1ncd+mF5d*7LJZ%BOoaR157{N^|Fo8QcD zo8Ot6?`|CS-HpTcTso0n{BXg}&okNKe3F&c5i6%pJUpC@uOQiU!sKFhVgkvabjmb3 zWlBCh`J2(~iwz`Gpq<<`f>jJ8eb5*s#!NY%^r7Yj1+ zgjmVc&$H>TCKu-P??ztMXm`-PpAHMfMhc8l+J{zOFpLhoAd@b6IGgTy_~OpDru-0U zJCt_D8JA2u_OmZ1DPuqPf8X8udf|Eg`^nbijGy%Lk9W5+57_=|-L3xFivMzVYsg=| z@?Y(46>h)Tf2F%+#E5`TM$CiyzVbW8E!(?Bo9H z-L0mTp8r;NtECU~Pjt7|uRqIwsk?RS@FxFgcWc}IpZX`$+7jGP-u}-<|Ksk?9rr)t zzu4W{`L|2`gWWB<@Du+)ck98mrT&}Utw%E+@b`DOo>)RzwWXz@zIj~ZnvU4D-6KDkJ&>O5aT)`t zG;=YjO!Q=Cw=|jc&0a%O9i3!eg8t0GH4WpP2AfZ?U5F~yPWMc|hTd*20ykV-IX82} z3?*|0(Oc$L(eO1>du{-|YWhXA|J)){Be2>k*VA9lumncQoPGlu%@%u^8?13&VxE2j zT59a&Zc{+_ZTfwsN4oI$YWmz&1HkF!v~g}0T|ci1GnrTi*9E?g85pn7SLUxESBRO; zoS#ds61DXU^0ANi(SeI{>4TRJ$m06KdD*_;B6|DPE3w9zi8=eGZTFASuNK%efAQ6{ z!wmT8dC)5sI*D`Ga%~^FW>F!|;8*mx)3^J?-d3tZznRXoF3RTG z%DJ8_pd;P>-K!16FDJdpHJzPR)$}&|%ETJ8!QD|I!lzE@6kbx|4!RZKhvS~4+pJ3x zrdVFYzpBZkQ)>EWaf85l*j;0W zVo4^3Vfq8~izQcy&3M9}BDOCe`=*%Y&E;3n^r|^f0=|^}5CGJ%Ezi{EV9Z8Zx`1yQ zEQ6SQMqM2}zpjvW*3BV@Iy35@C*=3^`W4U9jg23Xcc{6dn7rG0{fb?Ld`OF%OUOq6 z4etLN|JC#}&X`GBoBboSs`+E`0iD`XLf+_H((*7NhiJc*Z(*9R*N>*5RZHlY+sf#t z+eXrxRt=(0u9`t_+EhmO>?o!aS1+U!t}COv+p;_NtsX&WW2}t+ux1_oYJC~qwYGu& z>E<#zeqA%Ydt(``zB!v7TDP7Y7SqRTaFRt2ZK$Ok z8_HJ|qU+n}1t3*&Q!Xu; zlu7?}{W5B;;!DY9;qI>}=m$MQF$BGMats26`_htax`ceeKpN`bm2koq1dPPV7k4$0f8N zb`9NhYZ+bs$#D8uY^iXz{-lgE&Jd2)pU-RD$@(_0aR=+K;5F`C{Wf0Xj@947Yuu^& zckvpxQ2s-_#+|7j=d~_gdy&_;-SFS!HEs|5lf1@#r~hRJoSkr-{&yV6ou=O}6Mwim z`h~p4)z3eh*SMqfHC{W(YZvhvR}y~?uW{e#SMwTI1HX>fxKH%g@f!Dsemk#mU+6Pl z<9@K#zn@pR6ZAWIjf=UzpVzqW^AGbH_j~?_yvBW=|2?m9f9Lnl!XNJI{32fCe$F4m zYuv~A5!6~^=`9U*bH|2`G5#Uiw$-Kdv0{2~=ehL6ojG*GiDG*7wjXHv$#S}Gdl$Xu z_Yu19!6;;X1-?eHoGCKd!N}7IWIX(Dj7u|9&LM!ewpkSkE+2fUT&zpI4>i)s>r;m5h_0QM$P`Li| z%RQCU+FMS&C%Wi_ZN+r_(-jE?97=!p>q@#{dpVUmyXc>`7Srk-bHvy$9?qoeo~(v~ z%J-Iae*fgu5WV%mfMgF%9YEiTSJI^qmD8C|bcX{V$?=B$ZgU)I1-_MIrKX`~2J3hLNP~+`@^O?7uO`kYXNrxYWpq}ia z|LkmlEo!3gJz3uQpC9`K6|Cn^TL?XQjPFSiRy~2%eo{xLz8{?bcc1Jb?{z-*>HIW+ z26YzvtsqTUu9<<^Lcwj;Od<>x3T~}Xa8reX+bI;>NTJ{s3I#V$D7bAx!3`4%Zk15* zP#y(0M<}>0Lct9Y3T}l^oaEO8l-vNJ;MNBPH$5o0-9f>P4hn8@P;hfIGbBt6THMZ{ z;6`RZdCx}CS_)*HI@T=Qr+y@^xQAi2)EBwFfGqg)s1ll;$b_@CeMKXLqV{kLexm(mcvaE|vuUvzwkKd%2CJ@#c&8=rH#m<+Lm z*wF1_GT!2Qw_VJ7s>P>2)#7wcwK&03t@pBn7T?$H{`F@JQSJ>h30QnY~(eua?`ZwX|2OrdMlu zuU2QT)|01N5fJ>%sU}*#?bV9+YCV-~b$<8twm`?B8- zL+6=gTWt6_WEwdkmcfqCCYh{pEXj&*K8Nf~BQM2=pHJ>0XJQUowqu`Dm1=ls@X%`lzT^N{lVPD#Xd1)5` zPP-7>c41oD{exFvG3~;#vIXFe~kXw|2o=yWp%{FxD>kY8Py^3$EG)Q|;jC zf9H@&@;;kAmqbzAGM7xs6mj1SCNC!W?D$+F0Y0#jTo}M-1@O8`GA00A$pOXe=}J-# z#E&Y;^Z-7OJvyJ9&-B%4Ia#HH&p2a@|2|uO6`2mCC$1t_koWJHM=H>mGmp$d@$-3P zDvIOt$c$jT&uaPjtLKv(z?aS!-4D(uGtl~SKDj8sTFDx(BInaR-}LX}C#kGiK;{DJ z^#$Zo6!}+!gX3(*)kMw`(d#V(ne37RHfABop}W4zOAdUEJ##g=JX7FoVf(HoLs-c| zavpgtK64@I7lM*3ScFY_mF-vrE?#BtEFv>AMeN%d?8&5Si41tdwdAq@{&WBzdn?Ii zA6!e$4WQ2k&{0+7oB*&l0F>ScwE8M?UI0B1K$p}4x@Qq7DDb?N>L#dh22`4)Es|Cztd_fIqcb;9pstgufHucUBVv_@7tfXkKNL zmWX2O5>gq=`o{ok*DYAn8Vh?k+$4j6INnTd#b;vvA}X z=WQ}EfcFXDgB>y|0Q3t0dsk!i3mkF|uy1h4#X)CY(0SY;Lt*s(=@5lGD}9&-v5u>Hlg(id`XnE;pZ9UJ`|el{B^G#90Uma* z1kPi_axx)H+zXvNRuUtHY)=E$P*Q}|e1Q!H$`8xQi~z;YV>_ zS~3&G2emLIVxDGpvX-37_KYOC-P?JL`E{^D$Jo<#Fo4I{fO>KzimG}tAH|dP1AS`)wqB6h+6^yc`x>y5$4f|N(!v~LC5?hg zLt_%31^9(raFB!O!~WVx24TkU8llNz#$5r%;uS;>0Cxv~$5+529%EmvfcZSeCN+@@ z$m?uv6GW7Ut^T6{)<;dm2mpHmfYeNs0MHo#HZ&780Q@!pyw*%61c0XlKuHVaNKE={ zH^vAiolVl&GiQ;(N$y@}kG8-J2*d*c;^w8Ctusk~j-A7PI2OugpROPS*xXh!CBS?+ zz{Ijfu$Nk)e6O?Ptx&hunY@yWN4Q|FgyH6~w|_K`ZQBO4l6RpS&#ojx5JkMPl1xI8 zy9)kEARQ0pTfPcm!3nlw6=Y1n{~W+iY=bEAfP>+#)SnGpO|pXizXbiT_}Q#-tO4^POYuJeeCrx=b^!P$0D#AAwr>;W z-g`b4aOXHuFd$*e#klVSv=M7T_$Z66#mR|WM+PI;lTvo~cruJVzLsR6GrpEwgyNgE zWHyS+)4dXjy#o=nUVd6@DV`pT+M|{)9p79uICu9MEo!9IK;)%^Th_lO~N)@cM};B zj9e3p+;581gU7N`40B1)q7GYO5%ee(kM~v*~4IRp6 zZA=nlK^MZ8FeW;33oPdWHga?F5bh4Tu}nRf>b?LlsEwcU4DNn5lRg;o&&|nYJ``Y7 zv?ESDz}C0J`iez7&fyCCp`8p00KaBW#NdL&ESKF%3V^-jRwyry;nw7!XM)MF$q91O zZHN!Ve9s462VaCfc?I+WaQ#+Cp>`-)|uoXNhF%iBo!YRsi{9 z0wPQdzAg`9&ut}rG6nW0tn>z$IzWdf4aJ)*XB#}-o9xPMh`#r;_HATRmdM`z=c$R# z2_XMC1u0|~YzN!>+3f8IboR3?+cC+0c4#{yy8SF~2UK7`tJr}pd7o|F0SkVdJ;ICE z*sD9p#6=>wet6&+XDnO0Y;Ai>#|<6+z#*_ezbN2084-wn+pBl{sa}!$&d=*PHhikL zi!Ip+I)~YHyx7Nn#*1U@cf5F=9Ye85b>z)@BaAc4l+NK zeJ?)p@Px~|?1no?VfNkK&HL^kS7hJQ-Tc=bq^RGZp_sit|C1XpVdSw4a)=%J87Uox zFaPqyCu3Pnt@SN6b#BKcQ?vYm#?U=1a~HY0)Nu@1m!gJjo2IJClBLUSiG6v+y!5!LWi(=%L0HEq|^qmmhA`#Z^yc*!T^Hd3nEs;Wqy?AWTI zMr6m-O;d4P$+KMD(sYYGv6l>vw>=eli=-sZ4%LNbmB=ZGOJhU%rD4gmOk1%%$-^40 za5St)y5$*)>nV;QMFT!cG)0#sTXR%PQNyZkYObfMvf-JE>>7>~ENX{ShLS%Bct+IYMTahFv|XYqlA-Y)i$) zSrJ>dY#Yo-;fQQI@f{%?Mu}oM1|U{6DytG!ZyLHH>x!a8T;0|6UQ9&7x~h8-$5t?- zCr2G8?BZx;*K{?_k&{fMARI8Er6Rm|acC&}`MV_d{D@rBGQPQL^o9*%OGm4U>qhLb zp-VcX$5Eq}tviloyQ(Z>$#xtfQITG%DiK+W%90FmQ6mQ5aL;obQ`WF}N3r6g?9eXK zmg-zagW_cs3#(^edGYjF)v3g>H@22yyGB=yWm+gyfVG~UCHBPg#6Oq6w&CBZ9H=EP zJ(R&)oUi_HxxbXRre;0*zki>0DU(i;3s}ytLjy})$&h5zRUFH;AZW5-JCZC#EeL}n zTdowpXA>6!*NoaxJuJ&gM76OyQBzW#sNzXZ7<;G2N4-FPPD-S(V(OM{$g=LLjv_~0 zLvu}8cWl=*9GA^`9Euw#V=B5r8B5I+beTLhG^Esk94b)@MZ{HgJ#46o?nO0AhLGx} zq9%Bdq8fNrT-7sF*>X%f9F|nmgv`5AB&_rlWYtijP(@dE6iJOJx@AaV-7{@XH&hEc zkPzflgabh~QxO*0sM!&ymZyg8sHQrWYK3)MGfl&Aqq1W_9wD|cjS)+U>bhq|+^8Cs zBm;)j)?oL%D7bRsFpWD&sieXVMLkDBp9Lb{_W4oi-PbxRH>mY<5GSbm9edXlVa zacEeehMLkt4Q(jC>w&BVTL49jMl{)Ua8j;;1-VHzjA&8KiRgv`aRZuZdX|Y(_h5k} zM>Fh%8m2ms-inn%4$U87r`Rp7hH4qqFcnLI8uA?Vzg5HOKVAJoLJcSG{{8>F`U|dx zvr5fyIBMv2H0tof(ltXi!w@;xB+YZ=a5!OxAq!?ylPqYes#<1LaV=rJ&2Va-~_@>W-cO z=QK_dCRkETLxIQ8yoid;4I5BGCk*k^H5o=DdG-(qh$$?t=6I^3>yZA46t!*7gQGDe zxu-^Y4g}qXyM^AWQA08;+cRAR4VL6ZAZZDaPDMG;$drVi`#U+W)Rqic@)XaF7+f$l z)6v2e!t3A|GcOo7v0!#>OC8DILt(dX`8yD8Vfhs4M zGHlm~x|U_ACJ(H*U2-Cti$jIB!u|!$G1Z~;)-x#oX@#>lcB;KfYUPYn90gHLhL+1`imk~?2QMPAq($STqAk1Fu8@gg%DzZJbOipT<1Nw@oL=_EzBHXd% z*q&oY!%#UaPeu?bSV9n~7#0jm)JF6fRxJ3iuw@_=ipr6&5oSOe92Ze&F+x;Fab-0M zNmjuVLREyXh+ZWG1ZI5v#LzQ{qf^ig#4{yXc)fh~(%{hOQm6x5HdF!npdxy-Ae^e_ z!4X0`bUTt{M6tA}7j|7}z6vXX!!upO48!$Hj-&T-;I3>d2vjWDlp(+x93XBN2BO*s z?iG;bgr=pUoM0st;mQ%Av&JjqBE3RqNH-!pjq+%(dX_gNE z?!jg_rYhm4^^PnbalRKN03yilS+9STW%L;MM{&5Zvz&Dnq7mIdV1J7#+=m=;E$q!QH`8 zbPHrExcy8A-BQC;7TvlNSlVN2F!huq0sR$>p zcLT<&20T*l68?Xu&ff(g~}G3b2eovn*Uhpl^<(DGtnqYj{f7#ywYZ zu~S}T*c&_5h9!O2bUg)2fo3_ldBaX{hH#>$YayP(T|t8M!IVou zUZmm;GAX?TLB3|os*dy0RYW9F#4ZT6EX2{a9JYg-Sdc=|pq03<;j(N))Ln!(VMJ@V z4H`1sL^6O8Dprze1qbUwvrALZHUkX{o3@2pp{$z`PemRgY8%KHz;oeT9o#|azKt6K_URcX<7;KOhq^l zPdOFgC+CHxmOzv&PqiFZ;khb!8<-$i4P1R;{7of}H~@DxPcB)NHfO-mx160sxUFt*zXhhYw&I1Vn5Rs=Z% zZpsq5I3aVT8f>@)C6pq#{lkzWcno7>aC6oqMb(vr!lgQ<-YS$zI(uWM*grF=a5GY{ zr6p2HUO24q*u*m7t7P0Y4CE^n7s4gsj;SQP0F(=N_9*UIvI?=|nFqMNu%_x^q)pW7U}iOBEBO`~QJg=d%!?|f1gQxOZQ#k&6m)}3rFnX~Y|hIhztqHq#ewm+ zcp?$^Cw{>;5MUt5V`@0kgt7EsDHSZm@xX;4!95wcWFdj7hxzgM%JPM|wYB7ktRT~( zn^6P#LDM#($U15fJrYUiSt`nbo~0!G)XLDs-~wxf5wIhkf`oz_l_cB3l{q3ukcd)~ z(YtC#p?XNiMl>4^4E78WSj00u>@W7;?&-`-L=bRZVOxenc95nDo4SJ-KY}<-Md~Qv zq9g@nM!q339AgT)Nnh4qib&&nWh;^AMs5@l4;KqW=-5bC#{JCGkp+%OB3eTJO~z*1`&g=z>8&iOB(gVls{QI#tyCNZs%7AAg+M7Rxv(k` z4M{`@DsH1;NpU45EbgJWk3}?O=UfCQuq!Hj9D-xSicWHiBN3|Ns%a$ zNbq8k<-%1fVLhTrvfHg&M@jMN$tGgN6jT!)Ob_e2BqL%sH5Dg=$Vhi2kLOWgFCxh- zha(%f;lqLHiixZSK48FdI*J`}P0euK#NtGhSfXe$Y=-XIChlrBVoziN4abyVHZ=Il zxHK{JJA4F4K{zn|smShQp$Vn%jb_w~f($-Q;HyIvE?Kx+FRDVl#T^pjhmQoFgOFZE z(2gaVI)dGZZ2^dMsv7O7SNtnM)OI1kW&{Qhk%@}0GRRsY&nF|+O<0FigahlKq#~SD zEPMm#ndN{&;s%Uu)Ex+f>tLn$5(73(e*DO(1tB8rHLer5D%u9bN3w9cRFQDS6~S`D zVKtl#5l??AKe~K5DTJ}NTBX`9u2#V}fD|n8=Lp1wb{#N$iW-Mp?dj8dkjAiE1ZTHUI+~dPR1Q}`@8A^yJ>?bZX zPy;iJv{w{2AkUT)Nq59w_yp!kNTu_8Fg_v~5FLbZNK$x^=){KuWHpg|f{VqK7k5NU zNA?qm2pwN1Tshn$pHiBNZsNm13c86~9!TNK5a$5Y9Yk+%@iI^KTLx}UN#_VF>*-js zW+AZAWF)A)uw*Mv6h=&gQ|cl9B@V)7&(T%WjUvA$$uRF4Y*85g5*b@Jp}~3z!h!Us zq$@rgL@Wo%8GKc=5$t*vmd?Mt;p0IRAtHj&;GS2kL?em>tAdX*Y8d`qLT(ZXWLZTt z>R8DS2cGUB+Jxe|h6-Z~g~z24pUMoRk|j5ppiD(lEFWJ#PfN1rhXbw0_09?-*z`;Z z`AB@Th{7pqIxG$@01+NvMG}IAgbpHUWQ|~aktjjJ*#vuGd;mgTSdAuw&C?&pk5pGW zy%_!|Zz84GtfWUQNx>1@gRgh-oo|Nz{L6IyjGGNym6o3&-l?|u1tFq*yJ{vO>VUVdd&^3O*Y;)-PqBqU*V&5d|c;8fR{&C3(8e)w^>Q|;HZfIL9# zx`OmF@zNOUy?bnWej0%By#?uiEf6n=V?&wgkitU#nm9I)Z(N;g)>k)UPS3VG{4RF# z{PeOc-rWk^X#>g7_~>!z8_ycXpBBe*mpN9mjRAITYqOwum_2({dZBnO92?H=UWx}E zhuQVV((}dB;&}eN^zFmM>)Tino{gs$wRMQ!CBz0SHCvmTYcQ2n+lrO%a%hpyyMzDF+wKY}}i#GvXwl)Fi$2T{C1hb}tuY9&Y zA17H=pDr!KlbEeX(}xb@Z(w7&bMe#a1?I|ed}CIbkiKK=xufaBf7EL>S35N}o}J@a z?9ucBOp*0YdWm>78ymr&|BeiyYvw!Y#S6r=$+N8XYHG230UOY4u5|IkD)C=1urvW2 zm}pnmG*{ybRSiTYfgIq82{cfKg)o<(ymv$S@!u;M`2~acQ>a*W1OBZ<_0qL9jUE0=?5~$)jL6{d)}4<-fiBNz zoS4oZ&azQAW#rH2wODRNQ-gnT4Qz(l$p0fnhxjc{tgss#n38J0xuL$gmj9?XK*&$X zW^?tbYO}t+p+)=)6?8JPDWhPhm|N^V7q)8rABJUoBpbIWV_3fE?BBR%Ik&P2<90N@ zXj8_Reg*t-Z7iGrZvjEFL;NVHmF>r~-1uWVGREbT7vmrPGUM_=m+_Zdu^fn~*q{cl zy14}kETDb7YIilZ4J1W7ds<6N6F6#VNCM__vF2<8z#5;<7&ciT=1yyMY8s~X;75S_ z{y#{c*=`HcXf0+iVJn^UOhNpEr!(f};_2S_S2FU?<4?z8*+RYe-gStdFU9&_(OTEI zW_rEd;BZ4JkcP0Yw~~TFQSV=8E_bV2%%(s`IjohQxTzri}e1dk+ zhV<5RSJ5GU92LuGY;9T!1s9!}j#~?#kZAQ;3hCg(6Ycamvj$7!nB2~esvtwNI$Anf ITdi^b2N)hF&j0`b diff --git a/docs/html/_autosummary/pykanto.dataset.html b/docs/html/_autosummary/pykanto.dataset.html index d9861c3..6a4aeb6 100644 --- a/docs/html/_autosummary/pykanto.dataset.html +++ b/docs/html/_autosummary/pykanto.dataset.html @@ -739,8 +739,8 @@

pykanto.dataset

-
-plot_voc_seg(key: str, **kwargs) → None[source]#
+
+plot_segments(key: str, **kwargs) → None[source]#

Plots a vocalisation and overlays the results of the segmentation process.

diff --git a/docs/html/_modules/pykanto/dataset.html b/docs/html/_modules/pykanto/dataset.html index 430098f..2a141f9 100644 --- a/docs/html/_modules/pykanto/dataset.html +++ b/docs/html/_modules/pykanto/dataset.html @@ -1217,7 +1217,7 @@

Source code for pykanto.dataset

         """
         return pickle.load(open(self.DIRS.DATASET, "rb"))
-
[docs] def plot_voc_seg(self, key: str, **kwargs) -> None: +
[docs] def plot_segments(self, key: str, **kwargs) -> None: """ Plots a vocalisation and overlays the results of the segmentation process. diff --git a/docs/html/_sources/contents/basic-workflow.ipynb.txt b/docs/html/_sources/contents/basic-workflow.ipynb.txt index d446255..d79e038 100644 --- a/docs/html/_sources/contents/basic-workflow.ipynb.txt +++ b/docs/html/_sources/contents/basic-workflow.ipynb.txt @@ -352,7 +352,7 @@ "\n", "# Plot an example:\n", "for vocalisation in dataset.vocs.index[:1]:\n", - " dataset.plot_voc_seg(vocalisation)" + " dataset.plot_segments(vocalisation)" ] }, { diff --git a/docs/html/_sources/contents/kantodata-dataset.ipynb.txt b/docs/html/_sources/contents/kantodata-dataset.ipynb.txt index d1b7889..44ab574 100644 --- a/docs/html/_sources/contents/kantodata-dataset.ipynb.txt +++ b/docs/html/_sources/contents/kantodata-dataset.ipynb.txt @@ -45,7 +45,7 @@ " :linenos:\n", "\n", " # Plot some information about the dataset\n", - " dataset.summary_plot(variable='all')\n", + " dataset.plot_summary(variable='all')\n", "\n", "\n", "Check sample size per individual ID in the dataset:\n", diff --git a/docs/html/contents/basic-workflow.html b/docs/html/contents/basic-workflow.html index 0673eb5..bd122de 100644 --- a/docs/html/contents/basic-workflow.html +++ b/docs/html/contents/basic-workflow.html @@ -42,7 +42,7 @@ - + @@ -472,7 +472,7 @@

Basic workflow -
Done
+
Done

-
2022-05-05 13:03:13,519	INFO services.py:1456 -- View the Ray dashboard at http://127.0.0.1:8265
+
2022-05-07 13:46:41,670	INFO services.py:1456 -- View the Ray dashboard at http://127.0.0.1:8265
 

 

-
Found and segmented 169 units.
+
Found and segmented 169 units.
 

 

 ../_images/fe64fcde9cc5447d338f3d91f69506c9cdf78220d06be5dedb65175690819e8b.png
@@ -636,10 +636,10 @@ 
Basic workflow
-
Found 1 individual IDs. They will be processed in 1 chunks of length 1.
+
Found 1 individual IDs. They will be processed in 1 chunks of length 1.
 

 

-

+

 

 
Now you can start the interactive app on your browser by simply running dataset.open_label_app().

 
There are not enough data in this minimal dataset to show how the app works - clustering doesn’t work well with such small sample sizes. Here is a gif showing how it would look with real data from these birds:

diff --git a/docs/html/contents/kantodata-dataset.html b/docs/html/contents/kantodata-dataset.html
index d31156c..f758431 100644
--- a/docs/html/contents/kantodata-dataset.html
+++ b/docs/html/contents/kantodata-dataset.html
@@ -514,7 +514,7 @@ 
Parameters
# Plot some information about the dataset
-dataset.summary_plot(variable='all')
+dataset.plot_summary(variable='all')
 

 

 
Check sample size per individual ID in the dataset:

diff --git a/docs/html/contents/segmenting-files.html b/docs/html/contents/segmenting-files.html
index 0d9757a..7b214bb 100644
--- a/docs/html/contents/segmenting-files.html
+++ b/docs/html/contents/segmenting-files.html
@@ -42,7 +42,7 @@
     
     
     
-    
+    
     
     
     
@@ -623,7 +623,7 @@ 
Segmenting files with custom metadata fields
-
+

Note: if you want to run this in paralell with ray (as in segment_files_parallel) monkey-patching will not work: for now, you will have diff --git a/docs/html/genindex.html b/docs/html/genindex.html index ffbbbd1..870c0ad 100644 --- a/docs/html/genindex.html +++ b/docs/html/genindex.html @@ -881,7 +881,7 @@

P

  • parse_sonic_visualiser_xml() (in module pykanto.utils.custom)
    • -
  • plot_voc_seg() (pykanto.dataset.KantoData method) +
  • plot_segments() (pykanto.dataset.KantoData method)
  • prepare_datasource() (in module pykanto.labelapp.data)
    • diff --git a/docs/html/searchindex.js b/docs/html/searchindex.js index 489de4a..5a61532 100644 --- a/docs/html/searchindex.js +++ b/docs/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({docnames:[".jupyter_cache/executed/4be61595053b03a6ed91d71d556fc094/base",".jupyter_cache/executed/7ac60efd3a39fdcb79fd6d274fe03b84/base","_autosummary/pykanto.dataset","_autosummary/pykanto.labelapp","_autosummary/pykanto.labelapp.data","_autosummary/pykanto.labelapp.main","_autosummary/pykanto.parameters","_autosummary/pykanto.plot","_autosummary/pykanto.signal","_autosummary/pykanto.signal.analysis","_autosummary/pykanto.signal.cluster","_autosummary/pykanto.signal.filter","_autosummary/pykanto.signal.segment","_autosummary/pykanto.signal.spectrogram","_autosummary/pykanto.utils","_autosummary/pykanto.utils.compute","_autosummary/pykanto.utils.custom","_autosummary/pykanto.utils.paths","_autosummary/pykanto.utils.read","_autosummary/pykanto.utils.slurm","_autosummary/pykanto.utils.slurm.launch","_autosummary/pykanto.utils.slurm.tester","_autosummary/pykanto.utils.types","_autosummary/pykanto.utils.write","_autosummary/pykanto.utils.xenocanto","contents/FAQs","contents/analysis","contents/basic-workflow","contents/hpc","contents/installation","contents/kantodata-dataset","contents/project-setup","contents/segmentation","contents/segmenting-files","index"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":5,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":3,"sphinx.domains.rst":2,"sphinx.domains.std":2,"sphinx.ext.viewcode":1,sphinx:56},filenames:[".jupyter_cache/executed/4be61595053b03a6ed91d71d556fc094/base.ipynb",".jupyter_cache/executed/7ac60efd3a39fdcb79fd6d274fe03b84/base.ipynb","_autosummary/pykanto.dataset.rst","_autosummary/pykanto.labelapp.rst","_autosummary/pykanto.labelapp.data.rst","_autosummary/pykanto.labelapp.main.rst","_autosummary/pykanto.parameters.rst","_autosummary/pykanto.plot.rst","_autosummary/pykanto.signal.rst","_autosummary/pykanto.signal.analysis.rst","_autosummary/pykanto.signal.cluster.rst","_autosummary/pykanto.signal.filter.rst","_autosummary/pykanto.signal.segment.rst","_autosummary/pykanto.signal.spectrogram.rst","_autosummary/pykanto.utils.rst","_autosummary/pykanto.utils.compute.rst","_autosummary/pykanto.utils.custom.rst","_autosummary/pykanto.utils.paths.rst","_autosummary/pykanto.utils.read.rst","_autosummary/pykanto.utils.slurm.rst","_autosummary/pykanto.utils.slurm.launch.rst","_autosummary/pykanto.utils.slurm.tester.rst","_autosummary/pykanto.utils.types.rst","_autosummary/pykanto.utils.write.rst","_autosummary/pykanto.utils.xenocanto.rst","contents/FAQs.md","contents/analysis.rst","contents/basic-workflow.ipynb","contents/hpc.md","contents/installation.md","contents/kantodata-dataset.ipynb","contents/project-setup.md","contents/segmentation.rst","contents/segmenting-files.ipynb","index.rst"],objects:{"pykanto.dataset":[[2,1,1,"","KantoData"]],"pykanto.dataset.KantoData":[[2,2,1,"","DIRS"],[2,3,1,"","__init__"],[2,3,1,"","cluster_ids"],[2,3,1,"","get_units"],[2,2,1,"","noise"],[2,3,1,"","open_label_app"],[2,2,1,"","parameters"],[2,3,1,"","plot_voc_seg"],[2,3,1,"","prepare_interactive_data"],[2,3,1,"","relabel_noise_segments"],[2,3,1,"","reload"],[2,3,1,"","sample_info"],[2,3,1,"","save_to_disk"],[2,3,1,"","segment_into_units"],[2,3,1,"","show_extreme_samples"],[2,3,1,"","subset"],[2,3,1,"","summary_plot"],[2,3,1,"","to_csv"],[2,2,1,"","units"],[2,2,1,"","vocalisations"]],"pykanto.labelapp":[[4,0,0,"-","data"],[5,0,0,"-","main"]],"pykanto.labelapp.data":[[4,4,1,"","embeddable_image"],[4,4,1,"","load_bk_data"],[4,4,1,"","prepare_datasource"]],"pykanto.labelapp.main":[[5,4,1,"","build_legend"],[5,4,1,"","get_markers"],[5,4,1,"","parse_boolean"],[5,4,1,"","prepare_legend"],[5,4,1,"","set_range"],[5,4,1,"","update_feedback_text"]],"pykanto.parameters":[[6,1,1,"","Parameters"]],"pykanto.parameters.Parameters":[[6,3,1,"","__init__"],[6,3,1,"","add"],[6,2,1,"","dB_delta"],[6,2,1,"","dereverb"],[6,2,1,"","fft_rate"],[6,2,1,"","fft_size"],[6,2,1,"","gauss_sigma"],[6,2,1,"","highcut"],[6,2,1,"","hop_length"],[6,2,1,"","hop_length_ms"],[6,2,1,"","lowcut"],[6,2,1,"","max_dB"],[6,2,1,"","max_unit_length"],[6,2,1,"","min_silence_length"],[6,2,1,"","min_unit_length"],[6,2,1,"","num_cpus"],[6,2,1,"","num_mel_bins"],[6,2,1,"","silence_threshold"],[6,2,1,"","song_level"],[6,2,1,"","sr"],[6,2,1,"","subset"],[6,2,1,"","top_dB"],[6,3,1,"","update"],[6,2,1,"","verbose"],[6,2,1,"","window_length"]],"pykanto.plot":[[7,4,1,"","melspectrogram"],[7,4,1,"","mspaced_mask"],[7,4,1,"","rand_jitter"],[7,4,1,"","segmentation"],[7,4,1,"","show_minmax_frequency"],[7,4,1,"","show_spec_centroid_bandwidth"],[7,4,1,"","sns_histoplot"]],"pykanto.signal":[[9,0,0,"-","analysis"],[10,0,0,"-","cluster"],[11,0,0,"-","filter"],[12,0,0,"-","segment"],[13,0,0,"-","spectrogram"]],"pykanto.signal.analysis":[[9,4,1,"","approximate_minmax_frequency"],[9,4,1,"","get_mean_sd_mfcc"],[9,4,1,"","get_peak_freqs"],[9,4,1,"","spec_centroid_bandwidth"]],"pykanto.signal.cluster":[[10,4,1,"","hdbscan_cluster"],[10,4,1,"","reduce_and_cluster"],[10,4,1,"","reduce_and_cluster_parallel"],[10,4,1,"","umap_reduce"]],"pykanto.signal.filter":[[11,4,1,"","dereverberate"],[11,4,1,"","dereverberate_jit"],[11,4,1,"","gaussian_blur"],[11,4,1,"","get_norm_spectral_envelope"],[11,4,1,"","hz_to_mel_lib"],[11,1,1,"","kernels"],[11,4,1,"","mel_to_hz"],[11,4,1,"","mels_to_hzs"],[11,4,1,"","norm"],[11,4,1,"","normalise"]],"pykanto.signal.filter.kernels":[[11,2,1,"","dilation_kern"],[11,2,1,"","erosion_kern"]],"pykanto.signal.segment":[[12,1,1,"","ReadWav"],[12,1,1,"","SegmentMetadata"],[12,4,1,"","drop_zero_len_units"],[12,4,1,"","find_units"],[12,4,1,"","get_segment_info"],[12,4,1,"","onsets_offsets"],[12,4,1,"","save_segments"],[12,4,1,"","segment_file"],[12,4,1,"","segment_files"],[12,4,1,"","segment_files_parallel"],[12,4,1,"","segment_is_valid"],[12,4,1,"","segment_song_into_units"],[12,4,1,"","segment_song_into_units_parallel"]],"pykanto.signal.segment.ReadWav":[[12,3,1,"","__init__"],[12,3,1,"","as_dict"],[12,3,1,"","get_metadata"],[12,3,1,"","get_wav"],[12,2,1,"","wav_dir"]],"pykanto.signal.segment.SegmentMetadata":[[12,3,1,"","__init__"],[12,2,1,"","all_metadata"],[12,3,1,"","as_dict"],[12,3,1,"","get_metadata"],[12,2,1,"","index"]],"pykanto.signal.spectrogram":[[13,4,1,"","crop_spectrogram"],[13,4,1,"","cut_or_pad_spectrogram"],[13,4,1,"","extract_windows"],[13,4,1,"","flatten_spectrograms"],[13,4,1,"","get_indv_units"],[13,4,1,"","get_indv_units_parallel"],[13,4,1,"","get_unit_spectrograms"],[13,4,1,"","get_vocalisation_units"],[13,4,1,"","pad_spectrogram"],[13,4,1,"","retrieve_spectrogram"],[13,4,1,"","save_melspectrogram"],[13,4,1,"","window"]],"pykanto.utils":[[15,0,0,"-","compute"],[16,0,0,"-","custom"],[17,0,0,"-","paths"],[18,0,0,"-","read"],[19,0,0,"-","slurm"],[22,0,0,"-","types"],[23,0,0,"-","write"],[24,0,0,"-","xenocanto"]],"pykanto.utils.compute":[[15,4,1,"","calc_chunks"],[15,4,1,"","dictlist_to_dict"],[15,4,1,"","flatten_list"],[15,4,1,"","get_chunks"],[15,4,1,"","print_dict"],[15,4,1,"","print_parallel_info"],[15,4,1,"","timing"],[15,4,1,"","to_iterator"],[15,4,1,"","tqdmm"]],"pykanto.utils.custom":[[16,4,1,"","chipper_units_to_json"],[16,4,1,"","open_gzip"],[16,4,1,"","parse_sonic_visualiser_xml"]],"pykanto.utils.paths":[[17,1,1,"","ProjDirs"],[17,4,1,"","change_data_loc"],[17,4,1,"","get_file_paths"],[17,4,1,"","get_wavs_w_annotation"],[17,4,1,"","link_project_data"],[17,4,1,"","pykanto_data"]],"pykanto.utils.paths.ProjDirs":[[17,3,1,"","__init__"],[17,3,1,"","append"],[17,3,1,"","update_json_locs"]],"pykanto.utils.read":[[18,4,1,"","open_dataset"],[18,4,1,"","read_json"]],"pykanto.utils.slurm":[[20,0,0,"-","launch"],[21,0,0,"-","tester"]],"pykanto.utils.slurm.launch":[[20,4,1,"","submit_job"]],"pykanto.utils.types":[[22,1,1,"","Annotation"],[22,1,1,"","AttrProto"],[22,1,1,"","AudioAnnotation"],[22,1,1,"","Chunkinfo"],[22,1,1,"","Metadata"],[22,1,1,"","SegmentAnnotation"],[22,1,1,"","ValidDirs"],[22,4,1,"","f_exists"],[22,4,1,"","is_list_of_int"],[22,4,1,"","is_list_of_str"]],"pykanto.utils.types.Annotation":[[22,2,1,"","ID"],[22,3,1,"","__init__"],[22,2,1,"","annotation_file"],[22,2,1,"","durations"],[22,2,1,"","end_times"],[22,2,1,"","label"],[22,2,1,"","lower_freq"],[22,2,1,"","start_times"],[22,2,1,"","upper_freq"]],"pykanto.utils.types.AttrProto":[[22,3,1,"","__init__"]],"pykanto.utils.types.AudioAnnotation":[[22,3,1,"","__init__"],[22,2,1,"","bit_rate"],[22,2,1,"","length_s"],[22,2,1,"","sample_rate"],[22,2,1,"","source_wav"]],"pykanto.utils.types.Chunkinfo":[[22,2,1,"","chunksize"],[22,2,1,"","last_chunk"],[22,2,1,"","len_iterable"],[22,2,1,"","n_chunks"],[22,2,1,"","n_workers"]],"pykanto.utils.types.Metadata":[[22,2,1,"","ID"],[22,3,1,"","__init__"],[22,2,1,"","annotation_file"],[22,2,1,"","label"],[22,2,1,"","lower_freq"],[22,2,1,"","max_amplitude"],[22,2,1,"","min_amplitude"],[22,2,1,"","source_wav"],[22,2,1,"","upper_freq"],[22,2,1,"","wav_file"]],"pykanto.utils.types.SegmentAnnotation":[[22,2,1,"","ID"],[22,3,1,"","__init__"],[22,2,1,"","annotation_file"],[22,2,1,"","durations"],[22,2,1,"","end_times"],[22,2,1,"","label"],[22,2,1,"","lower_freq"],[22,2,1,"","start_times"],[22,2,1,"","upper_freq"]],"pykanto.utils.types.ValidDirs":[[22,2,1,"","PROJECT"],[22,2,1,"","RAW_DATA"],[22,3,1,"","__init__"]],"pykanto.utils.write":[[23,1,1,"","NumpyEncoder"],[23,4,1,"","copy_xml_files"],[23,4,1,"","make_tarfile"],[23,4,1,"","makedir"],[23,4,1,"","save_json"]],"pykanto.utils.write.NumpyEncoder":[[23,3,1,"","default"]],"pykanto.utils.xenocanto":[[24,4,1,"","delete"],[24,4,1,"","download"],[24,4,1,"","gen_meta"],[24,4,1,"","main"],[24,4,1,"","metadata"],[24,4,1,"","purge"],[24,4,1,"","read_json"]],pykanto:[[2,0,0,"-","dataset"],[3,0,0,"-","labelapp"],[6,0,0,"-","parameters"],[7,0,0,"-","plot"],[8,0,0,"-","signal"],[14,0,0,"-","utils"]]},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","attribute","Python attribute"],"3":["py","method","Python method"],"4":["py","function","Python function"]},objtypes:{"0":"py:module","1":"py:class","2":"py:attribute","3":"py:method","4":"py:function"},terms:{"0":[0,1,6,7,9,10,11,12,13,15,17,22,25,27,28,33],"00":[0,1,27,28,33],"000":[28,32],"001":[6,7],"01":[0,1,12,33],"02":[0,1,33],"03":[6,27],"04":[0,1,27,33],"0415_05":27,"05":[0,1,27,33],"07":27,"08":27,"09":27,"0_build":28,"1":[0,1,2,6,10,11,12,17,22,25,27,28,30,33],"10":[2,10,11],"100":[0,1,2,7,11,28,33],"1000":6,"10000":6,"1010":16,"1024":[6,16],"11":27,"117":30,"12":2,"127":27,"128":[6,11],"13":27,"132":[28,32],"134":30,"139250":27,"1456":27,"15":[10,27],"150":16,"157":30,"159":30,"16":[0,1,27,28,32,33],"169":27,"188250":27,"188388":27,"189776":27,"194375":27,"1d":13,"1m":27,"2":[0,1,6,9,10,15,22,30,33],"20":[2,28,32],"200":[28,32],"2018":4,"2021":[0,1,20,27,33],"20210502_040000":[0,1,33],"2022":[20,27],"21":27,"22":27,"22050":[6,11,12,13],"224":6,"22518":25,"22m":27,"23":[0,1,33],"2392":27,"247aa5075e06337d":[0,1,33],"24f319055fdf2205":27,"2506":27,"27":27,"2d":[2,11,13],"2v":[0,1,33],"3":[6,9,11,22,27,29,30],"30":[6,28],"300":28,"32mhttp":27,"351275":27,"356706":27,"39m":27,"4":[0,1,6,22,33],"40000":28,"41":4,"44":25,"472":[28,32],"48":[0,1,28,32,33],"5":[5,6,10,11,27,32],"50":2,"500":4,"512":13,"519":27,"520000":27,"54032744":15,"556":[28,32],"5694":27,"5739":27,"5922":27,"60":30,"600000":27,"64":4,"65":6,"65db":6,"666701":27,"673711":27,"740":30,"768":[0,1,33],"8":[0,1,28,29,33],"800":30,"80b1d3":2,"8265":27,"83":[0,1,33],"866667":27,"8dd3c7":2,"90000":28,"92":[0,1,33],"break":15,"case":[2,29,31],"class":[0,1,2,6,7,11,12,15,17,22,23,25,27,33,34],"default":[2,4,6,7,9,10,11,12,13,15,16,17,23,24,27],"do":[2,25,28,30,31,33],"final":13,"float":[2,6,7,9,10,11,12,13,15,16,22],"function":[2,4,5,7,9,10,11,12,13,15,16,17,18,20,22,23,24,26,27,28,30,31],"import":[0,1,2,27,28,31,33],"int":[2,4,6,7,9,10,11,12,13,15,16,22,24],"long":31,"new":[2,6,12,17,33],"return":[0,1,2,4,6,7,9,10,11,12,13,15,16,17,18,23,24,30,33],"short":[0,1,28,33],"switch":29,"throw":25,"true":[2,4,9,12,13,15,16,17,23,24,26,27,29,30,31,32],"try":[2,23,25],"while":[0,1,33],A:[2,4,7,9,13,15,17,23,28],And:29,As:28,For:[12,23,27,28,31,33],If:[2,13,24,25,27,28,29,31],In:[2,12,30],Is:12,It:[17,29,31],NO:12,No:17,Not:6,ONE:22,One:2,That:11,The:[2,6,13,16,17,26,27,29,34],Then:33,There:[27,28],These:[2,17,26],To:[28,29,30,33],_:30,__dict__:[0,1,15,33],__init__:[0,1,2,6,12,17,22,33],_colourmap:30,_description_:[12,16],_redis_password:28,abc:2,abl:27,about:[15,30],abov:2,acceler:10,access:31,account:11,accuraci:2,acess:33,acoust:28,actual:31,adapt:15,add:[2,6,26,28,33],add_to_dict:[0,1,33],address:28,advis:29,after:[2,28],again:33,agnost:33,agre:33,aim:26,algorithm:[27,28,29],alia:22,all:[2,4,6,10,12,13,27,30,31],all_metadata:[0,1,12,33],allow:[2,6],allow_nan:23,along:[2,12,33],alreadi:[2,17,22,26,27,30],also:[20,28,29,30],am:[0,1,17,33],among:[2,27,31],amplitud:[12,27],an:[2,11,12,13,15,16,17,22,28,30,31,33],analys:26,analysi:34,ani:[0,1,2,6,12,15,16,23,26,28,29,30,31,33],anim:2,annot:[0,1,12,16,17,22,33],annotation_fil:22,annotation_path:17,anyth:6,app:[2,4,5,27],append:[16,17],appli:13,applic:[3,4,28,29,33],approxim:[7,9,10,11,28],approximate_minmax_frequ:[9,26],ar:[2,10,12,17,20,22,26,27,28,31,33],arbitrari:23,arc:20,arg:[17,22],argument:[2,7,12,20,23,28,30],argv:28,around:[15,32,33],arr:7,arrai:[7,9,10,11,12,13],artist:[0,1,33],as_dict:12,ascend:2,assign:[2,17,27],assum:[17,31],attach:12,attr:[0,1,22,33],attribut:[2,12,15,17,22,33],attrproto:22,audio:[2,9,12,13,16,22,24,26,27,33],audio_format:[0,1,33],audio_sect:12,audioannot:[12,22],audiomoth:[0,1,33],auto_type_label:[5,10],automat:[2,6,27],automaticali:2,autoreload:25,avail:[6,12,25,33],averag:[2,4,6,10,13,27],avg_unit:2,ax_percentag:5,b108:30,b119:30,b163:30,b216:30,b226:30,b32:27,b3de69:2,b:[5,22,28],background:4,badwidth:7,bandpass:13,bandpassio:11,bandwidth:[9,26],bandwith:7,bar:[12,15],base:[2,4,12,23,27],bash:[20,28],basic:[9,30,34],batteri:[0,1,33],bc80bd:2,bebada:2,been:2,befor:[22,28,31],behaviour:20,belong:[2,13],below:[2,6,20,31,33],benefit:27,bengales:32,bengalese_finch:17,better:26,between:6,bigbird2020:28,bigbird:30,bigbird_2021:31,bigexternaldr:17,bin:[2,6,11,28],binari:7,bird:[2,27],bit:28,bit_depth:[0,1,27,33],bit_rat:22,bitrat:[0,1,33],block:30,blur:11,bokeh:[2,5],bone:7,bool:[2,4,6,7,9,10,12,13,15,16,17,23,24],both:[2,28],bound:[2,13],bout:22,box:[2,13,20,33],broken:17,browser:[2,27],build:[2,15,28,31],build_legend:5,c:[20,28,29],calc_chunk:15,calcul:[6,9,15,28],call:[20,23,25,28,30,33],callabl:12,can:[0,1,2,7,9,12,17,20,25,26,27,28,29,30,31,33],canto:24,carri:28,categori:2,category20_20:2,caus:[2,17],cba:2,ccebc5:2,cd:29,cell:30,centr:13,centroid:[7,9,26],cepstral:9,chain:15,challeng:29,chanc:20,chang:[2,17,20,31],change_data_loc:17,channel:[0,1,33],characteris:11,check:[2,12,17,22,27,28,30],check_circular:23,chipper:16,chipper_units_to_json:16,choic:33,choos:2,christiansen:32,chunk:[12,15,27],chunk_length:15,chunkinfo:[15,22],chunksiz:[15,22],clariti:31,clean:29,clone:29,cluster:[2,27,30],cluster_id:[2,27],cluster_resourc:28,cmap:[7,30],code:[4,5,12,20,23,24,27,30,31],coeffici:9,coincid:17,collaps:13,collect:[13,15,23],color:30,colormap:30,colour:2,colour_bar:7,colourmap:30,column:[10,27],columndatasourc:[4,5],com:[15,29],combin:[12,22],come:2,command:28,comment:[0,1,33],common:[2,15,29,31],compat:[24,25],composit:23,compress:27,comput:[6,12,13,14,20,32,34],computation:[28,30],concis:33,conda:29,conserv:10,consid:[10,12,28],consist:27,consolid:12,construct:17,contain:[2,7,9,12,13,15,16,17,24,27,29,33],content:[15,30],control:[10,17,31],conveni:[10,12,31],convert:11,coordin:[2,10],copi:[2,23],copy_xml_fil:23,core:[28,32],correspond:2,could:[0,1,23,33],count:13,cover:22,cpu:[2,6,12,25,28],crash:25,creat:[2,12,13,17,23,24,26,27,28,29,30,31,33],criteria:12,crop:13,crop_i:13,crop_spectrogram:13,crop_x:13,csv:2,cuda:29,cuml:[10,29],current:[2,17,24],custom:[0,1,15,22],customannot:[0,1,33],cut:13,cut_or_pad_spectrogram:13,d9d9d9:2,d:33,dashboard:27,data:[0,1,2,7,9,10,12,13,17,22,23,27,30,32,33],data_dir:12,data_loc:31,data_path:32,databas:[2,33],datafram:10,dataloc:4,datapath:12,dataset:[0,1,4,6,7,9,10,11,12,13,17,18,24,25,26,27,28,30,32,33],dataset_id:[2,27,30,32],dataset_loc:30,date:[27,33],datetim:[0,1,27,33],dateutil:[0,1,33],daunt:28,db:[6,30],db_delta:6,de:27,declar:10,decod:4,decor:[15,22],def:[0,1,23,33],defaul:24,defin:[12,30,33],delet:24,denmark:32,densiyi:2,depend:[28,31],dereverb:[6,13],dereverber:[11,13],dereverberate_jit:11,deriv:30,desc:15,descend:2,descript:[7,10,11,15,24],design:26,desir:[4,11,13],desktop:[28,32],dest_dir:23,destin:23,detail:[6,27],detect:29,dev:[0,1,27,29,33],deviat:11,devic:[12,33],dict:[0,1,12,13,15,16,18,23,33],dictionari:[2,12,13,15,16,18,22,23],dictlist:15,dictlist_to_dict:15,did:12,differ:[2,17,31],dilation_kern:11,dimens:13,dimension:[2,10,28],diminut:27,dir:[0,1,2,12,17,23,27,28,30,31,32,33],directli:[7,9],directori:[2,12,16,17,20,23,24,28,30],discret:[27,28],disk:[2,23],displai:2,distanc:10,distribut:[2,11,20,28,30],divid:6,doc:[10,29,31],document:[2,10,27,29],doe:[2,29],doesn:[2,17,23,27],don:[17,27],done:27,dougi:32,download:24,downstream:2,draw:33,drive:31,drop:2,drop_zero_len_unit:12,dt:[0,1,33],durat:[0,1,2,12,13,22,33],dure:6,e:[2,12,13,15,17,18,22,23,24,28,29,30],each:[2,6,9,10,13,15,27],eas:[26,31],easier:[28,31,33],easili:[20,29],echo:27,echo_rang:11,echo_reduct:11,edit:20,effici:18,either:[7,9,10],element:[15,27,30],els:[2,23],emb:4,embed:10,embedd:4,embeddable_imag:4,emploi:20,empti:31,enabl:[17,26],end:2,end_tim:22,enough:[2,27,28],ensur:22,ensure_ascii:23,entri:2,env:[0,1,27,29,33],envelop:11,environ:[28,29],epoll1:25,erosion_kern:11,error:[22,25,28],estim:2,etc:[9,11],european:32,even:17,event:8,ever:31,everi:13,everyth:27,exactli:28,exampl:[0,1,2,6,12,17,23,25,26,27,28,31,33],except:23,exclud:12,exclus:2,execut:2,exist:[2,17,22,23,29,30],exp:28,expect:2,explor:[2,3],ext:[0,1,32,33],extend:[12,23,33],extens:[0,1,17,25,33],extern:[17,18,31],extra:[29,33],extract:[9,12,13,26,33],extract_window:13,f:[15,22,30],f_exist:22,factor:[2,10,15],fail:[2,30],fals:[2,4,6,7,9,10,13,15,16,17,23,30],familiar:28,familiaris:27,faq:34,faster:29,fb8072:2,fccde5:2,fdb462:2,featur:[9,12,26],few:27,fewer:25,ffed6f:2,ffffb3:2,ffrom:9,fft_rate:6,fft_size:6,field:[12,17,22],fieldrecord:17,figur:17,file:[0,1,2,12,13,16,17,18,20,22,23,24,27,28,30,31,32,34],file_list:23,fileexistserror:[2,16,17],filenotfounderror:17,filepath:[0,1,33],files:[0,1,33],files_to_seg:[0,1,32,33],filt:24,filter:17,finch:32,find:[12,28,31,32],find_unit:12,first:[6,12,16,29,31,33],fix:[17,25],flatten:15,flatten_list:15,flatten_spectrogram:13,flexibl:33,focal:12,folder:[2,12,16,17,23,24,28,31],follow:[25,28,31],foolproof:20,forc:17,forg:29,fork:25,format:[12,33],found:[2,17,27,33],frame:[4,6,13],freez:25,frequenc:[2,6,7,9,11,12,13,33],fresh:29,friendli:33,from:[0,1,2,4,6,9,10,11,12,13,15,16,17,20,23,24,26,27,28,31,33],full:[2,13,33],fulli:2,funtion:2,g:[2,12,13,15,17,18,22,23,28,30],gain:[0,1,33],gauss_sigma:[6,11],gaussian:[6,11],gaussian_blur:11,gen_meta:24,gener:[2,4,6,12,14,16,17,24,29],georg:23,get:[2,12,13,17,25,30,31,32],get_chunk:15,get_file_path:[0,1,17,32,33],get_indv_unit:13,get_indv_units_parallel:13,get_mark:5,get_mean_sd_mfcc:9,get_metadata:[0,1,12,33],get_norm_spectral_envelop:11,get_peak_freq:9,get_segment_info:12,get_unit:[2,27],get_unit_spectrogram:13,get_vocalisation_unit:13,get_wav:12,get_wavs_w_annot:[0,1,17,32,33],gif:27,git:[15,29,31],github:29,given:[2,12,13,17,23,24],global:2,go:[15,27,28],good:2,gpu:[10,20,28],gre:28,great:[27,32],great_tit:[17,27],greatli:26,grei:4,group:[0,1,2,10,33],grouping_label:5,grpcio:25,guid:[20,33],gz:[23,28],gzip:16,ha:[2,16,17,27,28],half:[28,32],happen:[2,30],happi:27,have:[2,17,25,27,28,29,30,31,33],hdbscan:[2,10],hdbscan_clust:10,hdd:17,head:27,held:17,help:[20,24,28,29],here:[27,30,33],hertz:[11,12],high:34,highcut:6,highli:27,hint:22,histogram:[2,7],home:[0,1,17,27,33],hood:29,hop:13,hop_length:[6,11,13],hop_length_m:6,hopefulli:28,hover:27,how:[6,10,17,27,28,33],hpc:20,html:30,html_marker:5,http:[15,29,30],hz:[6,11,13],hz_to_mel_lib:11,i:[2,12,14,24,27,28,29,31,33],ib:[0,1,33],id:[2,4,10,12,13,16,22,30,33],identif:2,identifi:12,idx:10,ignor:12,ignore_check:17,ignore_label:12,imag:[4,29],immut:17,implement:[10,13,23,29],in_dir:28,includ:[0,1,6,17,31,32,33],incorpor:12,indent:23,index:[0,1,11,12,16,27,33],indic:[6,7],individu:[2,4,6,13,16,27,30,33],indv_list:5,info:[15,25,27,30],inform:[2,12,15,30,31,33],inherit:22,init:28,initialis:17,input:[22,30],inset:12,instal:34,instanc:[12,17,22,27],instance_of:[0,1,33],instanti:[2,22],instead:10,instruct:[20,28],intend:[0,1,17,20,33],intens:[28,30],interact:[2,3,4,5,27,28],interactib:4,interct:4,interest:[22,33],interfer:29,interpol:11,interpret:28,invert:4,involv:28,io:15,ip_head:28,ipython:25,is_list_of_int:22,is_list_of_str:22,isft:[0,1,33],issu:34,item:[6,15,17],iter:[12,13,15,23],iterable_nam:15,its:[2,7,9,12,13,17,27,31,33],jit:13,jitter:7,jmv6r:15,job:[20,28],json:[0,1,2,12,16,17,18,22,23,28,33],json_fil:2,json_loc:[18,23,24],json_object:23,json_outdir:[0,1,12,33],jsonencod:23,just:[15,17,31,32,33],kantodata:[2,4,6,7,9,10,11,12,13,15,17,18,25,27,28,34],karlb:23,kbp:[0,1,33],keep:[2,6,17],kei:[2,7,9,12,13,16,26],kernel:[2,6,11,25],kernel_s:11,keyerror:6,keys_to_mov:2,keyword:[2,7,12],khz:[0,1,33],kib:[0,1,33],kingdom:32,known:[29,34],kwarg:[2,6,7,10,12,15,22],lab:5,label:[2,3,4,5,10,12,22,27],labels_:10,labels_to_ignor:[12,32],lachlan:27,languag:28,larg:[2,3,12,28,31],larger:10,last:[2,6,15,30],last_chunk:[15,22],later:33,launch:21,lavf57:[0,1,33],learn:27,least:[28,30],leav:2,legibl:15,leland:4,len:[9,15],len_iter:[15,22],lenght:[2,4,7,13],length:[2,6,7,12,13,15,27,30],length_:[22,27],less:24,let:[23,27,31,33],level:28,lib:[0,1,27,33],librari:[24,26,28],lightweigth:2,like:[2,10,17,23,25,28,29,31,33],limit:2,line:30,lineno:30,link:[2,17],link_project_data:[17,31],list:[2,5,7,12,13,15,16,17,22,23,24],littl:28,live:[17,24,31],load:[0,1,2,4,13,17,27,30,33],load_bk_data:4,locat:[2,12,13,17,31],log:[9,20,28],logfil:28,longer:2,look:[17,27,28],lose:2,loss:11,lot:[2,28],lowcut:6,lower:25,lower_freq:[22,27],lst:15,luscinia:27,m:[7,20,28],machin:[2,17,25,32],magic:25,main:[2,22,24],maintain:24,major:27,make:[0,1,2,23,28,31,33],make_tarfil:[23,28],makedir:[0,1,23,33],male:27,manag:15,mani:[6,27,28],manifold:10,manipul:13,manual:33,map:5,marker_typ:5,mask:[6,7],match:[12,24],matplotlib:30,matrix:10,max:[11,12],max_amplitud:[22,27],max_db:6,max_lenght:7,max_n_lab:2,max_unit_length:6,maxfreq:[2,7,26],maximum:[2,6,7,9,13],mcinn:4,me:28,mean:9,mel:[2,6,7,9,11],mel_bin:11,mel_spectrogram:11,mel_to_hz:11,mels_to_hz:11,melscal:9,melspectrogram:[2,7,13],mem:28,membership:2,memori:[2,28],merino:27,messag:[24,25],meta:[0,1,33],metadata:[0,1,2,12,16,17,22,24],metadata_dir:12,method:[2,6,7,11,23,26,27,30,31,33],method_parallel:30,method_r:30,mfcc:9,might:[17,25,26,27,28,30,33],million:[28,32],min:[11,12],min_amplitud:[22,27],min_cluster_s:10,min_dist:10,min_dur:[12,32],min_freqrang:[12,32],min_level_db:11,min_sampl:[2,10,27],min_silence_length:6,min_unit_length:6,mindb:11,minfreq:[2,7,26],miniconda3:[0,1,27,33],minim:[17,27],minimum:[2,6,7,9,10,12,13,24],minmax:11,minmax_freq:11,miss:2,mk_colour:5,mkdir:[17,31,32],model:[5,28],modif:20,modifi:[6,7,15,23],modul:[3,8,14,19,22],monkei:33,more:[6,10,20,27,28,31],most:[28,30,33],move:[2,17],mspaced_mask:7,much:[6,26,29],multi:[20,28],multipl:[13,28],must:2,my:[27,32],mykin:32,myproject:17,n:[6,7,9,15,28,29,30],n_chunk:[15,22],n_compon:10,n_featur:10,n_fft:16,n_mfcc:9,n_neighbor:10,n_sampl:10,n_song:2,n_worker:[15,22],name:[2,6,12,16,17,23,24,30],nameerror:30,natur:26,nbin:[2,7],ndarrai:[4,5,7,9,10,11,12,13,23],necessari:[22,29],need:[26,27,28,29,31,33],nest:23,network:2,neural:2,never:31,new_attr:17,new_dataset:2,new_project:17,new_valu:17,newli:2,next:[27,31],nilo:[20,27],nilomr:[0,1,27,29,33],node:[20,28,32],nois:[2,10,12,30,32],non:33,none:[2,6,7,9,10,12,13,15,17,22,23,24,30,32],norm:11,normal:[12,28,33],normalis:11,note:[2,27,30,33],now:[13,27,31,33],nox:29,np:[4,7,9,10,11,12,13],nparray_dir:13,nparray_or_dir:7,num:24,num_cpu:[2,6,10,12,13,25],num_mel_bin:6,numba:[13,28],number:[2,3,6,7,9,10,12,15,22,24,25,31],numpi:[4,5,9,10,11,12,13,23],numpyencod:23,nvidia:[28,29],o:[14,23],obj:23,obj_id:15,object:[0,1,6,7,9,10,11,12,13,15,16,17,23,25,27,33],offset:[2,7,12,13,16,27],old:17,onc:[2,27],one:[2,4,6,12,13,17,26,27,28],ones:[2,17],onli:[12,17,25,28,29],onset:[2,7,12,13,16,27],onsets_offset:[7,12],open:[2,13,30],open_dataset:[18,30],open_gzip:16,open_label_app:[2,27],oper:15,optim:28,optimis:[15,28],option:[2,4,6,7,9,10,11,12,13,15,16,17,23,24],order:[2,9,29],org:30,organis:2,origin:[2,11,17],os:[17,24,28],other:[2,12,22,26,27],otherwis:31,our:33,out:[2,20,25,28],out_dir:[20,28,30],out_directori:24,outlier:2,output:[2,12,16,20,23,26],output_filenam:23,outsid:29,over:[7,28,32],overflow:23,overhead:28,overkil:28,overlai:[2,7],overlap:16,overwrit:[2,17],overwrite_data:[2,30],overwrite_dataset:[2,27,30],overwrite_json:16,own:[2,27,33],oxford:20,oxfordshir:27,p:[27,28],packag:[0,1,27,28,29,33],pad:[2,13,16],pad_length:13,pad_spectrogram:13,pair:12,palett:[2,5,30],paralel:[15,33],parallel:[2,6,10,12,13,15,20,25,28],parallelis:[15,28,30],param:[27,28,30],paramet:[2,4,7,9,10,11,12,13,15,16,17,18,23,24,25,27,28],parent:[17,23,32],pars:[0,1,12,16,20,33],parse_boolean:5,parse_sonic_visualiser_xml:[0,1,12,16,32,33],parser:[0,1,14,33],parser_func:[0,1,12,32,33],particular:28,paru:27,pass:[2,6,7,10,12,23,28],patch:33,path:[0,1,2,4,7,12,13,16,18,22,23,24,27,32,33],pathlib:[2,12,13,16,17,18,22,23,31],pathlik:[17,24],pbar:[12,16],pcm:[0,1,33],pd:10,peak:9,peng:[20,28],peopl:33,per:[2,4,6,13,30],perform:[10,11,34],person:28,petrel:[17,32],pickl:[13,25,30],pictur:[0,1,33],pip:29,pkg_resourc:32,placehold:2,platform:[26,28],plot:[2,4,9,26,27,30],plot_voc_seg:[2,27],png:4,point:[2,10,17,27,31],poll:25,popul:[2,27],popular:28,possibl:[7,28,29],power:9,precis:26,prefer:29,prepar:[2,4,27],prepare_datasourc:4,prepare_interactive_data:[2,27],prepare_legend:5,present:[2,12,13,22,27],preserv:33,preston:32,pretti:15,print:[0,1,2,12,15,17,24,28,30,31,33],print_dict:15,print_parallel_info:15,probabl:[28,31],problem:17,process:[2,4,7,8,15,21,27],produc:2,programmat:[2,24],progress:[12,15],projdir:[2,12,17,22,31,32],project:[2,10,12,17,22,27,32,33,34],project_data_dir:17,project_root:31,projroot:17,promot:31,prompt:2,properli:33,provid:[2,6,7,9,12,17,22,24,26,28,31,33],pty:28,purg:24,purpos:22,purr:32,py:[27,28],pycharm:27,pykanto:[0,1,25,26,27,31,32,33,34],pykanto_data:[0,1,17,27,33],pyrigh:22,pytest:29,python3:[0,1,33],python:[28,29,30],pytorch:29,queri:[2,24],quickli:[2,11,28],r:[0,1,28,33],rai:[15,19,20,21,25,27,28,30,33],raid:31,rais:[2,6,16,17,23],ram:25,rand_jitt:7,random:[2,28],random_subset:[2,28],rang:[2,11,12],rapid:29,rapidsai:29,rate:[6,12,13],ratio:12,raw:[0,1,12,17,27,28,32,33],raw_data:[0,1,17,22,31,32,33],raw_data_dir:12,rb:30,re:[0,1,33],reach:6,read:[12,16,31,33],read_json:[18,24],readi:[4,31],readwav:[0,1,12,33],readwav_patch:[0,1,33],real:[27,28],realiti:[0,1,33],reallist:2,reason:27,rec_unit:[0,1,33],recald:[20,27],recent:30,recommend:[27,29,31],record:[0,1,12,24,27,33],recordist:27,recurs:17,redis_password:28,reduc:[6,10,28],reduce_and_clust:10,reduce_and_cluster_parallel:10,reduct:[2,10,28],refer:[13,20,28,33],region:[22,33],regular:10,regularli:7,reilli:23,relabel:2,relabel_noise_seg:2,relabel_seg:2,relat:[8,22],releas:29,relev:[12,16,33],reload:[2,27],remain:12,remaining_indv:5,rememb:2,remot:[30,31],remov:[12,24,29],repo:31,report:17,repositori:31,repres:28,represent:[2,13,27],reproduc:[2,26],request:28,requir:[2,11,17,33],resampl:[12,32],rescal:11,research:[12,26],resourc:[2,17,28],resource_filenam:32,respect:2,rest:17,restart:25,result:[2,7,9,12,13],retriev:33,retrieve_spectrogram:13,return_kei:2,return_path:23,reverber:6,rgb:4,rifftag:[0,1,33],right:28,robert:27,rolloff_max:7,rolloff_min:7,root:[17,31],root_dir:17,row:[6,27],run:[2,20,25,26,27,28,29,33],runtim:28,s:[0,1,2,5,9,11,12,13,15,17,22,25,26,27,29,31,32,33],safe:23,sai:[28,30,33],sainburg:[12,23,27],same:[2,4,13,17,25,28,29,31],sampl:[0,1,2,6,10,12,13,17,27,30,32,33],sample_info:[2,30],sample_r:[0,1,22,33],sample_s:2,save:[2,4,12,13,20,23,24,30,33],save_json:23,save_melspectrogram:[10,12,13],save_seg:12,save_to_disk:2,schedul:[19,21,28],scienc:27,scikit:29,scratch:33,script:[20,28],sd:9,sdata:5,seaborn:7,search:[0,1,17,33],search_parent_directori:31,second:[0,1,2,6,12,13,16,28,32,33],section:31,see:[2,10,12,17,20,24,25,27,28,29,30,31,33],seekabl:12,seg:27,segment:[0,1,2,6,7,8,13,16,17,22,27,28,31,34],segment_fil:[0,1,12,33],segment_files_parallel:[12,32,33],segment_into_unit:[2,27,28,32],segment_is_valid:12,segment_song_into_unit:12,segment_song_into_units_parallel:12,segmentannot:[12,16,22,33],segmentmetadata:[0,1,12,33],segmentmetadata_patch:[0,1,33],segmet:12,select:7,selector:29,self:[0,1,2,10,23,33],separ:[6,12,23],serializ:[22,23],server:31,servic:27,session:28,set3_12:2,set:[0,1,2,6,11,25,33,34],set_rang:5,setup:27,sf:12,sh:28,shape:10,share:17,shetland:32,shorter:[2,15],should:[2,27,28],show:[2,9,26,27],show_extreme_sampl:2,show_extreme_song:2,show_minmax_frequ:7,show_spec_centroid_bandwidth:7,sigma:6,signal:[0,1,33],silenc:[2,6,22],silence_threshold:6,simon:32,simpl:[27,28],simpli:[27,31],simplic:27,singl:[12,13,28,30],site:[0,1,33],size:[2,6,10,15,27,30],skip:2,skipkei:23,slaunch:[20,28],slice:28,slightli:28,slow:28,slurm:28,small:[2,10,27,28],smaller:2,sns_histoplot:7,so:[2,26,28,33],some:[26,28,29,30,33],someth:[28,30],song:[2,4,11,13,22,27,32],song_level:[2,4,6,10,13],sonic:[12,16,33],sort:11,sort_kei:23,sound:24,soundfil:12,sourc:[2,4,5,6,7,9,10,11,12,13,15,16,17,18,20,22,23,24,28],source_datetim:27,source_dir:23,source_wav:[22,27],space:7,span_mk_siz:5,spec:[7,9],spec_bw:7,spec_centroid_bandwidth:[9,26],spec_length:[2,4],speci:27,specif:12,spectral:[7,9,11],spectrogram:[2,4,6,7,8,9,11,12,27,28,30],spectrogram_loc:27,sphinx:29,spot:2,sr:[6,11,12,13],srun:28,stabl:30,stack:23,stackoverflow:15,standard:[11,12,28,33],standardis:31,start:[0,1,2,27,33],start_tim:[0,1,22,33],state:[0,1,33],std:9,step:6,still:[28,33],storag:22,store:[6,7,17,22,23,26,31,33],storm:[17,32],str:[0,1,2,4,5,7,9,10,12,13,15,16,17,22,24,33],strategi:25,streaminfo:[0,1,33],string:[0,1,7,9,16,33],strongli:31,structur:[2,12,17],studi:27,subclass:23,subdirectori:17,subfold:12,submit:[20,28],submit_job:20,submodul:20,subset:[2,6,28],succesfulli:30,success:[6,15,24],suggest:33,sumbiss:28,summari:12,summary_plot:[2,30],support:[23,25,29],sure:[0,1,2,33],sw83:27,sy:28,syllabl:16,symlink:17,system:[17,28,29,31],t:[2,17,23,25,27],tab:2,tag:[0,1,33],take:[28,32],taken:6,tar:[23,28],tarfil:23,target:17,task:28,tech_com:27,tell:[31,33],tend:[6,33],term:24,termin:28,test:[2,17,21,29,32],than:[20,24,25,28],thei:[2,17,26,27,28,29],them:[16,27,31,32],thi:[0,1,2,9,12,15,17,20,22,23,24,25,27,28,29,30,31,33],think:33,those:33,three:[30,32],threshold:[6,9,11],tidi:17,tim:[12,23,27],time:[2,12,15,27,28,33],timeaxisconvers:16,timedelta:[0,1,33],timer:15,timezon:27,tip:33,tit:[27,32],titl:7,to_csv:2,to_iter:15,todo:12,togeth:31,too:[2,10],took:32,tool:[8,14,28],top:[6,28],top_db:6,torchaudio:29,torchvis:29,total:[15,30],touch:31,tqdm:15,tqdmm:15,traceback:30,trail:2,train:[2,28],transfer:17,translat:28,tree:[17,31],trim:2,troubl:2,truli:28,tupl:[4,6,7,9,10,11,12,13,16,17],tutori:[17,30],two:[2,16,27,28],type:[0,1,2,4,7,9,10,11,12,13,14,15,16,17,18,23,24,27,33],typeerror:23,ugli:33,ujson:[18,23],uk:27,umap:[2,10,29],umap_:10,umap_i:10,umap_reduc:10,umap_x:10,under:[12,17,29],uniform:10,uniqu:30,unit:[2,4,6,7,10,12,13,16,27,28,32],unit_label:[2,4],univers:20,unix:17,unless:15,unsupervis:2,up:34,updat:[6,17,25],update_feedback_text:5,update_json_loc:[17,31],upper_freq:[22,27],us:[2,4,6,7,10,11,12,13,15,17,18,19,20,23,25,29,30,31,32,33],user:[6,15,17,22,28],utc:[0,1,27,33],util:[0,1,12,27,28,31,33],v100:28,v:23,valid:[0,1,6,10,12,17,22,33],validdir:22,valu:[4,10,11],value_count:30,valueerror:[2,17],vari:26,variabl:[2,17,30],vector:10,verbos:[2,6,10,12,15,17,24],veri:2,version:[2,10,12,17,29,30,31],via:29,view:27,virtual:29,visualis:[2,12,16,33],voc:[2,27,30],vocal:2,vocalis:[2,3,4,6,7,9,10,12,13,27,30,34],vocalisation_kei:10,vocalisation_label:[2,4],vocalseg:[12,27],voic:6,vscode:27,w:30,wa:[0,1,13,33],wai:[15,20,26,28,31,33],want:[17,27,28,29,31,33],wav:[0,1,2,12,13,17,32,33],wav_dir:[0,1,12,33],wav_fil:[17,22,27],wav_filepath:[0,1,17,32,33],wav_out:12,wav_outdir:[0,1,12,33],wave:[0,1,33],waveaudioformat:[0,1,33],wavestreaminfo:[0,1,33],wavfil:[12,17],we:[27,33],web:[2,3,4],well:[6,12,27,28],were:30,wether:[6,17],what:[2,12,15,33],when:[2,17,25],where:[2,12,15,17,24,28,31],wherev:31,wheter:12,whether:[2,4,6,9,10,12,13,17,23,24],which:[2,12,17,20,26,27,28,30],whose:22,why:31,wil:31,window:[6,13,17],window_length:6,window_offset:16,within:[2,12,15,17,20,28],without:[13,25],wlength:13,wood:27,work:[2,6,12,17,20,27,28,33],worker:25,workflow:34,working_tree_dir:31,world:28,would:[12,27,28,29,33],wrapper:[10,15,28],writabl:15,write:[0,1,27,28,33],wrong:23,wytham:27,wytham_gretis_2021_test:30,x11:28,x:[11,13],xc46092:32,xc663885:32,xeno:24,xml:[0,1,12,16,32,33],xml_filepath:[0,1,16,32,33],y:13,year:12,yield:[13,15],you:[0,1,2,7,9,12,17,20,23,25,26,27,28,29,30,31,33],your:[2,7,9,12,17,24,25,27,29,33],yourself:27,zero:12,zhenghao:[20,28]},titles:["<no title>","<no title>","pykanto.dataset","pykanto.labelapp","pykanto.labelapp.data","pykanto.labelapp.main","pykanto.parameters","pykanto.plot","pykanto.signal","pykanto.signal.analysis","pykanto.signal.cluster","pykanto.signal.filter","pykanto.signal.segment","pykanto.signal.spectrogram","pykanto.utils","pykanto.utils.compute","pykanto.utils.custom","pykanto.utils.paths","pykanto.utils.read","pykanto.utils.slurm","pykanto.utils.slurm.launch","pykanto.utils.slurm.tester","pykanto.utils.types","pykanto.utils.write","pykanto.utils.xenocanto","FAQs & known issues","Vocalisation analysis","Basic workflow","High Performance Computing","Installing pykanto","The KantoData class","Setting up a project","Vocalisation segmentation","File segmentation","Documentation"],titleterms:{"1":31,"2":31,"class":30,The:30,an:27,analysi:[9,26],area:28,avoid:29,basic:[27,29],cluster:[10,28],code:28,comput:[15,28],custom:[16,33],data:[4,28,31],dataset:[2,31],depend:29,deriv:31,develop:29,directori:31,document:34,faq:25,field:33,file:33,filter:11,first:28,freez:31,gpu:29,guid:34,hell:29,high:28,hpc:28,id:27,instal:29,introduct:28,issu:25,kantodata:30,known:25,labelapp:[3,4,5],launch:20,librari:29,link:31,local:28,machin:28,main:5,metadata:33,ml:29,modul:34,onli:31,paramet:[6,30],path:[17,31],perform:28,plot:7,programmat:31,project:31,pykanto:[2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,28,29],raw:31,read:18,segment:[12,32,33],set:31,signal:[8,9,10,11,12,13],slurm:[19,20,21],spectrogram:13,storag:28,test:28,tester:21,tip:[27,28,29,31],type:22,up:31,upload:28,us:[27,28],user:34,util:[14,15,16,17,18,19,20,21,22,23,24],vocalis:[26,32],work:31,workflow:27,write:23,xenocanto:24,your:[28,31]}}) \ No newline at end of file +Search.setIndex({ docnames: [".jupyter_cache/executed/4be61595053b03a6ed91d71d556fc094/base", ".jupyter_cache/executed/7ac60efd3a39fdcb79fd6d274fe03b84/base", "_autosummary/pykanto.dataset", "_autosummary/pykanto.labelapp", "_autosummary/pykanto.labelapp.data", "_autosummary/pykanto.labelapp.main", "_autosummary/pykanto.parameters", "_autosummary/pykanto.plot", "_autosummary/pykanto.signal", "_autosummary/pykanto.signal.analysis", "_autosummary/pykanto.signal.cluster", "_autosummary/pykanto.signal.filter", "_autosummary/pykanto.signal.segment", "_autosummary/pykanto.signal.spectrogram", "_autosummary/pykanto.utils", "_autosummary/pykanto.utils.compute", "_autosummary/pykanto.utils.custom", "_autosummary/pykanto.utils.paths", "_autosummary/pykanto.utils.read", "_autosummary/pykanto.utils.slurm", "_autosummary/pykanto.utils.slurm.launch", "_autosummary/pykanto.utils.slurm.tester", "_autosummary/pykanto.utils.types", "_autosummary/pykanto.utils.write", "_autosummary/pykanto.utils.xenocanto", "contents/FAQs", "contents/analysis", "contents/basic-workflow", "contents/hpc", "contents/installation", "contents/kantodata-dataset", "contents/project-setup", "contents/segmentation", "contents/segmenting-files", "index"], envversion: { "sphinx.domains.c": 2, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 5, "sphinx.domains.index": 1, "sphinx.domains.javascript": 2, "sphinx.domains.math": 2, "sphinx.domains.python": 3, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.viewcode": 1, sphinx: 56 }, filenames: [".jupyter_cache/executed/4be61595053b03a6ed91d71d556fc094/base.ipynb", ".jupyter_cache/executed/7ac60efd3a39fdcb79fd6d274fe03b84/base.ipynb", "_autosummary/pykanto.dataset.rst", "_autosummary/pykanto.labelapp.rst", "_autosummary/pykanto.labelapp.data.rst", "_autosummary/pykanto.labelapp.main.rst", "_autosummary/pykanto.parameters.rst", "_autosummary/pykanto.plot.rst", "_autosummary/pykanto.signal.rst", "_autosummary/pykanto.signal.analysis.rst", "_autosummary/pykanto.signal.cluster.rst", "_autosummary/pykanto.signal.filter.rst", "_autosummary/pykanto.signal.segment.rst", "_autosummary/pykanto.signal.spectrogram.rst", "_autosummary/pykanto.utils.rst", "_autosummary/pykanto.utils.compute.rst", "_autosummary/pykanto.utils.custom.rst", "_autosummary/pykanto.utils.paths.rst", "_autosummary/pykanto.utils.read.rst", "_autosummary/pykanto.utils.slurm.rst", "_autosummary/pykanto.utils.slurm.launch.rst", "_autosummary/pykanto.utils.slurm.tester.rst", "_autosummary/pykanto.utils.types.rst", "_autosummary/pykanto.utils.write.rst", "_autosummary/pykanto.utils.xenocanto.rst", "contents/FAQs.md", "contents/analysis.rst", "contents/basic-workflow.ipynb", "contents/hpc.md", "contents/installation.md", "contents/kantodata-dataset.ipynb", "contents/project-setup.md", "contents/segmentation.rst", "contents/segmenting-files.ipynb", "index.rst"], objects: { "pykanto.dataset": [[2, 1, 1, "", "KantoData"]], "pykanto.dataset.KantoData": [[2, 2, 1, "", "DIRS"], [2, 3, 1, "", "__init__"], [2, 3, 1, "", "cluster_ids"], [2, 3, 1, "", "get_units"], [2, 2, 1, "", "noise"], [2, 3, 1, "", "open_label_app"], [2, 2, 1, "", "parameters"], [2, 3, 1, "", "plot_segments"], [2, 3, 1, "", "prepare_interactive_data"], [2, 3, 1, "", "relabel_noise_segments"], [2, 3, 1, "", "reload"], [2, 3, 1, "", "sample_info"], [2, 3, 1, "", "save_to_disk"], [2, 3, 1, "", "segment_into_units"], [2, 3, 1, "", "show_extreme_samples"], [2, 3, 1, "", "subset"], [2, 3, 1, "", "summary_plot"], [2, 3, 1, "", "to_csv"], [2, 2, 1, "", "units"], [2, 2, 1, "", "vocalisations"]], "pykanto.labelapp": [[4, 0, 0, "-", "data"], [5, 0, 0, "-", "main"]], "pykanto.labelapp.data": [[4, 4, 1, "", "embeddable_image"], [4, 4, 1, "", "load_bk_data"], [4, 4, 1, "", "prepare_datasource"]], "pykanto.labelapp.main": [[5, 4, 1, "", "build_legend"], [5, 4, 1, "", "get_markers"], [5, 4, 1, "", "parse_boolean"], [5, 4, 1, "", "prepare_legend"], [5, 4, 1, "", "set_range"], [5, 4, 1, "", "update_feedback_text"]], "pykanto.parameters": [[6, 1, 1, "", "Parameters"]], "pykanto.parameters.Parameters": [[6, 3, 1, "", "__init__"], [6, 3, 1, "", "add"], [6, 2, 1, "", "dB_delta"], [6, 2, 1, "", "dereverb"], [6, 2, 1, "", "fft_rate"], [6, 2, 1, "", "fft_size"], [6, 2, 1, "", "gauss_sigma"], [6, 2, 1, "", "highcut"], [6, 2, 1, "", "hop_length"], [6, 2, 1, "", "hop_length_ms"], [6, 2, 1, "", "lowcut"], [6, 2, 1, "", "max_dB"], [6, 2, 1, "", "max_unit_length"], [6, 2, 1, "", "min_silence_length"], [6, 2, 1, "", "min_unit_length"], [6, 2, 1, "", "num_cpus"], [6, 2, 1, "", "num_mel_bins"], [6, 2, 1, "", "silence_threshold"], [6, 2, 1, "", "song_level"], [6, 2, 1, "", "sr"], [6, 2, 1, "", "subset"], [6, 2, 1, "", "top_dB"], [6, 3, 1, "", "update"], [6, 2, 1, "", "verbose"], [6, 2, 1, "", "window_length"]], "pykanto.plot": [[7, 4, 1, "", "melspectrogram"], [7, 4, 1, "", "mspaced_mask"], [7, 4, 1, "", "rand_jitter"], [7, 4, 1, "", "segmentation"], [7, 4, 1, "", "show_minmax_frequency"], [7, 4, 1, "", "show_spec_centroid_bandwidth"], [7, 4, 1, "", "sns_histoplot"]], "pykanto.signal": [[9, 0, 0, "-", "analysis"], [10, 0, 0, "-", "cluster"], [11, 0, 0, "-", "filter"], [12, 0, 0, "-", "segment"], [13, 0, 0, "-", "spectrogram"]], "pykanto.signal.analysis": [[9, 4, 1, "", "approximate_minmax_frequency"], [9, 4, 1, "", "get_mean_sd_mfcc"], [9, 4, 1, "", "get_peak_freqs"], [9, 4, 1, "", "spec_centroid_bandwidth"]], "pykanto.signal.cluster": [[10, 4, 1, "", "hdbscan_cluster"], [10, 4, 1, "", "reduce_and_cluster"], [10, 4, 1, "", "reduce_and_cluster_parallel"], [10, 4, 1, "", "umap_reduce"]], "pykanto.signal.filter": [[11, 4, 1, "", "dereverberate"], [11, 4, 1, "", "dereverberate_jit"], [11, 4, 1, "", "gaussian_blur"], [11, 4, 1, "", "get_norm_spectral_envelope"], [11, 4, 1, "", "hz_to_mel_lib"], [11, 1, 1, "", "kernels"], [11, 4, 1, "", "mel_to_hz"], [11, 4, 1, "", "mels_to_hzs"], [11, 4, 1, "", "norm"], [11, 4, 1, "", "normalise"]], "pykanto.signal.filter.kernels": [[11, 2, 1, "", "dilation_kern"], [11, 2, 1, "", "erosion_kern"]], "pykanto.signal.segment": [[12, 1, 1, "", "ReadWav"], [12, 1, 1, "", "SegmentMetadata"], [12, 4, 1, "", "drop_zero_len_units"], [12, 4, 1, "", "find_units"], [12, 4, 1, "", "get_segment_info"], [12, 4, 1, "", "onsets_offsets"], [12, 4, 1, "", "save_segments"], [12, 4, 1, "", "segment_file"], [12, 4, 1, "", "segment_files"], [12, 4, 1, "", "segment_files_parallel"], [12, 4, 1, "", "segment_is_valid"], [12, 4, 1, "", "segment_song_into_units"], [12, 4, 1, "", "segment_song_into_units_parallel"]], "pykanto.signal.segment.ReadWav": [[12, 3, 1, "", "__init__"], [12, 3, 1, "", "as_dict"], [12, 3, 1, "", "get_metadata"], [12, 3, 1, "", "get_wav"], [12, 2, 1, "", "wav_dir"]], "pykanto.signal.segment.SegmentMetadata": [[12, 3, 1, "", "__init__"], [12, 2, 1, "", "all_metadata"], [12, 3, 1, "", "as_dict"], [12, 3, 1, "", "get_metadata"], [12, 2, 1, "", "index"]], "pykanto.signal.spectrogram": [[13, 4, 1, "", "crop_spectrogram"], [13, 4, 1, "", "cut_or_pad_spectrogram"], [13, 4, 1, "", "extract_windows"], [13, 4, 1, "", "flatten_spectrograms"], [13, 4, 1, "", "get_indv_units"], [13, 4, 1, "", "get_indv_units_parallel"], [13, 4, 1, "", "get_unit_spectrograms"], [13, 4, 1, "", "get_vocalisation_units"], [13, 4, 1, "", "pad_spectrogram"], [13, 4, 1, "", "retrieve_spectrogram"], [13, 4, 1, "", "save_melspectrogram"], [13, 4, 1, "", "window"]], "pykanto.utils": [[15, 0, 0, "-", "compute"], [16, 0, 0, "-", "custom"], [17, 0, 0, "-", "paths"], [18, 0, 0, "-", "read"], [19, 0, 0, "-", "slurm"], [22, 0, 0, "-", "types"], [23, 0, 0, "-", "write"], [24, 0, 0, "-", "xenocanto"]], "pykanto.utils.compute": [[15, 4, 1, "", "calc_chunks"], [15, 4, 1, "", "dictlist_to_dict"], [15, 4, 1, "", "flatten_list"], [15, 4, 1, "", "get_chunks"], [15, 4, 1, "", "print_dict"], [15, 4, 1, "", "print_parallel_info"], [15, 4, 1, "", "timing"], [15, 4, 1, "", "to_iterator"], [15, 4, 1, "", "tqdmm"]], "pykanto.utils.custom": [[16, 4, 1, "", "chipper_units_to_json"], [16, 4, 1, "", "open_gzip"], [16, 4, 1, "", "parse_sonic_visualiser_xml"]], "pykanto.utils.paths": [[17, 1, 1, "", "ProjDirs"], [17, 4, 1, "", "change_data_loc"], [17, 4, 1, "", "get_file_paths"], [17, 4, 1, "", "get_wavs_w_annotation"], [17, 4, 1, "", "link_project_data"], [17, 4, 1, "", "pykanto_data"]], "pykanto.utils.paths.ProjDirs": [[17, 3, 1, "", "__init__"], [17, 3, 1, "", "append"], [17, 3, 1, "", "update_json_locs"]], "pykanto.utils.read": [[18, 4, 1, "", "open_dataset"], [18, 4, 1, "", "read_json"]], "pykanto.utils.slurm": [[20, 0, 0, "-", "launch"], [21, 0, 0, "-", "tester"]], "pykanto.utils.slurm.launch": [[20, 4, 1, "", "submit_job"]], "pykanto.utils.types": [[22, 1, 1, "", "Annotation"], [22, 1, 1, "", "AttrProto"], [22, 1, 1, "", "AudioAnnotation"], [22, 1, 1, "", "Chunkinfo"], [22, 1, 1, "", "Metadata"], [22, 1, 1, "", "SegmentAnnotation"], [22, 1, 1, "", "ValidDirs"], [22, 4, 1, "", "f_exists"], [22, 4, 1, "", "is_list_of_int"], [22, 4, 1, "", "is_list_of_str"]], "pykanto.utils.types.Annotation": [[22, 2, 1, "", "ID"], [22, 3, 1, "", "__init__"], [22, 2, 1, "", "annotation_file"], [22, 2, 1, "", "durations"], [22, 2, 1, "", "end_times"], [22, 2, 1, "", "label"], [22, 2, 1, "", "lower_freq"], [22, 2, 1, "", "start_times"], [22, 2, 1, "", "upper_freq"]], "pykanto.utils.types.AttrProto": [[22, 3, 1, "", "__init__"]], "pykanto.utils.types.AudioAnnotation": [[22, 3, 1, "", "__init__"], [22, 2, 1, "", "bit_rate"], [22, 2, 1, "", "length_s"], [22, 2, 1, "", "sample_rate"], [22, 2, 1, "", "source_wav"]], "pykanto.utils.types.Chunkinfo": [[22, 2, 1, "", "chunksize"], [22, 2, 1, "", "last_chunk"], [22, 2, 1, "", "len_iterable"], [22, 2, 1, "", "n_chunks"], [22, 2, 1, "", "n_workers"]], "pykanto.utils.types.Metadata": [[22, 2, 1, "", "ID"], [22, 3, 1, "", "__init__"], [22, 2, 1, "", "annotation_file"], [22, 2, 1, "", "label"], [22, 2, 1, "", "lower_freq"], [22, 2, 1, "", "max_amplitude"], [22, 2, 1, "", "min_amplitude"], [22, 2, 1, "", "source_wav"], [22, 2, 1, "", "upper_freq"], [22, 2, 1, "", "wav_file"]], "pykanto.utils.types.SegmentAnnotation": [[22, 2, 1, "", "ID"], [22, 3, 1, "", "__init__"], [22, 2, 1, "", "annotation_file"], [22, 2, 1, "", "durations"], [22, 2, 1, "", "end_times"], [22, 2, 1, "", "label"], [22, 2, 1, "", "lower_freq"], [22, 2, 1, "", "start_times"], [22, 2, 1, "", "upper_freq"]], "pykanto.utils.types.ValidDirs": [[22, 2, 1, "", "PROJECT"], [22, 2, 1, "", "RAW_DATA"], [22, 3, 1, "", "__init__"]], "pykanto.utils.write": [[23, 1, 1, "", "NumpyEncoder"], [23, 4, 1, "", "copy_xml_files"], [23, 4, 1, "", "make_tarfile"], [23, 4, 1, "", "makedir"], [23, 4, 1, "", "save_json"]], "pykanto.utils.write.NumpyEncoder": [[23, 3, 1, "", "default"]], "pykanto.utils.xenocanto": [[24, 4, 1, "", "delete"], [24, 4, 1, "", "download"], [24, 4, 1, "", "gen_meta"], [24, 4, 1, "", "main"], [24, 4, 1, "", "metadata"], [24, 4, 1, "", "purge"], [24, 4, 1, "", "read_json"]], pykanto: [[2, 0, 0, "-", "dataset"], [3, 0, 0, "-", "labelapp"], [6, 0, 0, "-", "parameters"], [7, 0, 0, "-", "plot"], [8, 0, 0, "-", "signal"], [14, 0, 0, "-", "utils"]] }, objnames: { "0": ["py", "module", "Python module"], "1": ["py", "class", "Python class"], "2": ["py", "attribute", "Python attribute"], "3": ["py", "method", "Python method"], "4": ["py", "function", "Python function"] }, objtypes: { "0": "py:module", "1": "py:class", "2": "py:attribute", "3": "py:method", "4": "py:function" }, terms: { "0": [0, 1, 6, 7, 9, 10, 11, 12, 13, 15, 17, 22, 25, 27, 28, 33], "00": [0, 1, 27, 28, 33], "000": [28, 32], "001": [6, 7], "01": [0, 1, 12, 33], "02": [0, 1, 33], "03": 6, "04": [0, 1, 27, 33], "0415_05": 27, "05": [0, 1, 27, 33], "07": 27, "08": 27, "09": 27, "0_build": 28, "1": [0, 1, 2, 6, 10, 11, 12, 17, 22, 25, 27, 28, 30, 33], "10": [2, 10, 11], "100": [0, 1, 2, 7, 11, 28, 33], "1000": 6, "10000": 6, "1010": 16, "1024": [6, 16], "11": 27, "117": 30, "12": 2, "127": 27, "128": [6, 11], "13": 27, "132": [28, 32], "134": 30, "139250": 27, "1456": 27, "15": [10, 27], "150": 16, "157": 30, "159": 30, "16": [0, 1, 27, 28, 32, 33], "169": 27, "188250": 27, "188388": 27, "189776": 27, "194375": 27, "1d": 13, "1m": 27, "2": [0, 1, 6, 9, 10, 15, 22, 30, 33], "20": [2, 28, 32], "200": [28, 32], "2018": 4, "2021": [0, 1, 20, 27, 33], "20210502_040000": [0, 1, 33], "2022": [20, 27], "21": 27, "22": 27, "22050": [6, 11, 12, 13], "224": 6, "22518": 25, "22m": 27, "23": [0, 1, 33], "2392": 27, "247aa5075e06337d": [0, 1, 33], "24f319055fdf2205": 27, "2506": 27, "27": 27, "2d": [2, 11, 13], "2v": [0, 1, 33], "3": [6, 9, 11, 22, 27, 29, 30], "30": [6, 28], "300": 28, "32mhttp": 27, "351275": 27, "356706": 27, "39m": 27, "4": [0, 1, 6, 22, 33], "40000": 28, "41": [4, 27], "44": 25, "46": 27, "472": [28, 32], "48": [0, 1, 28, 32, 33], "5": [5, 6, 10, 11, 27, 32], "50": 2, "500": 4, "512": 13, "520000": 27, "54032744": 15, "556": [28, 32], "5694": 27, "5739": 27, "5922": 27, "60": 30, "600000": 27, "64": 4, "65": 6, "65db": 6, "666701": 27, "670": 27, "673711": 27, "740": 30, "768": [0, 1, 33], "8": [0, 1, 28, 29, 33], "800": 30, "80b1d3": 2, "8265": 27, "83": [0, 1, 33], "866667": 27, "8dd3c7": 2, "90000": 28, "92": [0, 1, 33], "break": 15, "case": [2, 29, 31], "class": [0, 1, 2, 6, 7, 11, 12, 15, 17, 22, 23, 25, 27, 33, 34], "default": [2, 4, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 23, 24, 27], "do": [2, 25, 28, 30, 31, 33], "final": 13, "float": [2, 6, 7, 9, 10, 11, 12, 13, 15, 16, 22], "function": [2, 4, 5, 7, 9, 10, 11, 12, 13, 15, 16, 17, 18, 20, 22, 23, 24, 26, 27, 28, 30, 31], "import": [0, 1, 2, 27, 28, 31, 33], "int": [2, 4, 6, 7, 9, 10, 11, 12, 13, 15, 16, 22, 24], "long": 31, "new": [2, 6, 12, 17, 33], "return": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 18, 23, 24, 30, 33], "short": [0, 1, 28, 33], "switch": 29, "throw": 25, "true": [2, 4, 9, 12, 13, 15, 16, 17, 23, 24, 26, 27, 29, 30, 31, 32], "try": [2, 23, 25], "while": [0, 1, 33], A: [2, 4, 7, 9, 13, 15, 17, 23, 28], And: 29, As: 28, For: [12, 23, 27, 28, 31, 33], If: [2, 13, 24, 25, 27, 28, 29, 31], In: [2, 12, 30], Is: 12, It: [17, 29, 31], NO: 12, No: 17, Not: 6, ONE: 22, One: 2, That: 11, The: [2, 6, 13, 16, 17, 26, 27, 29, 34], Then: 33, There: [27, 28], These: [2, 17, 26], To: [28, 29, 30, 33], _: 30, __dict__: [0, 1, 15, 33], __init__: [0, 1, 2, 6, 12, 17, 22, 33], _colourmap: 30, _description_: [12, 16], _redis_password: 28, abc: 2, abl: 27, about: [15, 30], abov: 2, acceler: 10, access: 31, account: 11, accuraci: 2, acess: 33, acoust: 28, actual: 31, adapt: 15, add: [2, 6, 26, 28, 33], add_to_dict: [0, 1, 33], address: 28, advis: 29, after: [2, 28], again: 33, agnost: 33, agre: 33, aim: 26, algorithm: [27, 28, 29], alia: 22, all: [2, 4, 6, 10, 12, 13, 27, 30, 31], all_metadata: [0, 1, 12, 33], allow: [2, 6], allow_nan: 23, along: [2, 12, 33], alreadi: [2, 17, 22, 26, 27, 30], also: [20, 28, 29, 30], am: [0, 1, 17, 33], among: [2, 27, 31], amplitud: [12, 27], an: [2, 11, 12, 13, 15, 16, 17, 22, 28, 30, 31, 33], analys: 26, analysi: 34, ani: [0, 1, 2, 6, 12, 15, 16, 23, 26, 28, 29, 30, 31, 33], anim: 2, annot: [0, 1, 12, 16, 17, 22, 33], annotation_fil: 22, annotation_path: 17, anyth: 6, app: [2, 4, 5, 27], append: [16, 17], appli: 13, applic: [3, 4, 28, 29, 33], approxim: [7, 9, 10, 11, 28], approximate_minmax_frequ: [9, 26], ar: [2, 10, 12, 17, 20, 22, 26, 27, 28, 31, 33], arbitrari: 23, arc: 20, arg: [17, 22], argument: [2, 7, 12, 20, 23, 28, 30], argv: 28, around: [15, 32, 33], arr: 7, arrai: [7, 9, 10, 11, 12, 13], artist: [0, 1, 33], as_dict: 12, ascend: 2, assign: [2, 17, 27], assum: [17, 31], attach: 12, attr: [0, 1, 22, 33], attribut: [2, 12, 15, 17, 22, 33], attrproto: 22, audio: [2, 9, 12, 13, 16, 22, 24, 26, 27, 33], audio_format: [0, 1, 33], audio_sect: 12, audioannot: [12, 22], audiomoth: [0, 1, 33], auto_type_label: [5, 10], automat: [2, 6, 27], automaticali: 2, autoreload: 25, avail: [6, 12, 25, 33], averag: [2, 4, 6, 10, 13, 27], avg_unit: 2, ax_percentag: 5, b108: 30, b119: 30, b163: 30, b216: 30, b226: 30, b32: 27, b3de69: 2, b: [5, 22, 28], background: 4, badwidth: 7, bandpass: 13, bandpassio: 11, bandwidth: [9, 26], bandwith: 7, bar: [12, 15], base: [2, 4, 12, 23, 27], bash: [20, 28], basic: [9, 30, 34], batteri: [0, 1, 33], bc80bd: 2, bebada: 2, been: 2, befor: [22, 28, 31], behaviour: 20, belong: [2, 13], below: [2, 6, 20, 31, 33], benefit: 27, bengales: 32, bengalese_finch: 17, better: 26, between: 6, bigbird2020: 28, bigbird: 30, bigbird_2021: 31, bigexternaldr: 17, bin: [2, 6, 11, 28], binari: 7, bird: [2, 27], bit: 28, bit_depth: [0, 1, 27, 33], bit_rat: 22, bitrat: [0, 1, 33], block: 30, blur: 11, bokeh: [2, 5], bone: 7, bool: [2, 4, 6, 7, 9, 10, 12, 13, 15, 16, 17, 23, 24], both: [2, 28], bound: [2, 13], bout: 22, box: [2, 13, 20, 33], broken: 17, browser: [2, 27], build: [2, 15, 28, 31], build_legend: 5, c: [20, 28, 29], calc_chunk: 15, calcul: [6, 9, 15, 28], call: [20, 23, 25, 28, 30, 33], callabl: 12, can: [0, 1, 2, 7, 9, 12, 17, 20, 25, 26, 27, 28, 29, 30, 31, 33], canto: 24, carri: 28, categori: 2, category20_20: 2, caus: [2, 17], cba: 2, ccebc5: 2, cd: 29, cell: 30, centr: 13, centroid: [7, 9, 26], cepstral: 9, chain: 15, challeng: 29, chanc: 20, chang: [2, 17, 20, 31], change_data_loc: 17, channel: [0, 1, 33], characteris: 11, check: [2, 12, 17, 22, 27, 28, 30], check_circular: 23, chipper: 16, chipper_units_to_json: 16, choic: 33, choos: 2, christiansen: 32, chunk: [12, 15, 27], chunk_length: 15, chunkinfo: [15, 22], chunksiz: [15, 22], clariti: 31, clean: 29, clone: 29, cluster: [2, 27, 30], cluster_id: [2, 27], cluster_resourc: 28, cmap: [7, 30], code: [4, 5, 12, 20, 23, 24, 27, 30, 31], coeffici: 9, coincid: 17, collaps: 13, collect: [13, 15, 23], color: 30, colormap: 30, colour: 2, colour_bar: 7, colourmap: 30, column: [10, 27], columndatasourc: [4, 5], com: [15, 29], combin: [12, 22], come: 2, command: 28, comment: [0, 1, 33], common: [2, 15, 29, 31], compat: [24, 25], composit: 23, compress: 27, comput: [6, 12, 13, 14, 20, 32, 34], computation: [28, 30], concis: 33, conda: 29, conserv: 10, consid: [10, 12, 28], consist: 27, consolid: 12, construct: 17, contain: [2, 7, 9, 12, 13, 15, 16, 17, 24, 27, 29, 33], content: [15, 30], control: [10, 17, 31], conveni: [10, 12, 31], convert: 11, coordin: [2, 10], copi: [2, 23], copy_xml_fil: 23, core: [28, 32], correspond: 2, could: [0, 1, 23, 33], count: 13, cover: 22, cpu: [2, 6, 12, 25, 28], crash: 25, creat: [2, 12, 13, 17, 23, 24, 26, 27, 28, 29, 30, 31, 33], criteria: 12, crop: 13, crop_i: 13, crop_spectrogram: 13, crop_x: 13, csv: 2, cuda: 29, cuml: [10, 29], current: [2, 17, 24], custom: [0, 1, 15, 22], customannot: [0, 1, 33], cut: 13, cut_or_pad_spectrogram: 13, d9d9d9: 2, d: 33, dashboard: 27, data: [0, 1, 2, 7, 9, 10, 12, 13, 17, 22, 23, 27, 30, 32, 33], data_dir: 12, data_loc: 31, data_path: 32, databas: [2, 33], datafram: 10, dataloc: 4, datapath: 12, dataset: [0, 1, 4, 6, 7, 9, 10, 11, 12, 13, 17, 18, 24, 25, 26, 27, 28, 30, 32, 33], dataset_id: [2, 27, 30, 32], dataset_loc: 30, date: [27, 33], datetim: [0, 1, 27, 33], dateutil: [0, 1, 33], daunt: 28, db: [6, 30], db_delta: 6, de: 27, declar: 10, decod: 4, decor: [15, 22], def: [0, 1, 23, 33], defaul: 24, defin: [12, 30, 33], delet: 24, denmark: 32, densiyi: 2, depend: [28, 31], dereverb: [6, 13], dereverber: [11, 13], dereverberate_jit: 11, deriv: 30, desc: 15, descend: 2, descript: [7, 10, 11, 15, 24], design: 26, desir: [4, 11, 13], desktop: [28, 32], dest_dir: 23, destin: 23, detail: [6, 27], detect: 29, dev: [0, 1, 27, 29, 33], deviat: 11, devic: [12, 33], dict: [0, 1, 12, 13, 15, 16, 18, 23, 33], dictionari: [2, 12, 13, 15, 16, 18, 22, 23], dictlist: 15, dictlist_to_dict: 15, did: 12, differ: [2, 17, 31], dilation_kern: 11, dimens: 13, dimension: [2, 10, 28], diminut: 27, dir: [0, 1, 2, 12, 17, 23, 27, 28, 30, 31, 32, 33], directli: [7, 9], directori: [2, 12, 16, 17, 20, 23, 24, 28, 30], discret: [27, 28], disk: [2, 23], displai: 2, distanc: 10, distribut: [2, 11, 20, 28, 30], divid: 6, doc: [10, 29, 31], document: [2, 10, 27, 29], doe: [2, 29], doesn: [2, 17, 23, 27], don: [17, 27], done: 27, dougi: 32, download: 24, downstream: 2, draw: 33, drive: 31, drop: 2, drop_zero_len_unit: 12, dt: [0, 1, 33], durat: [0, 1, 2, 12, 13, 22, 33], dure: 6, e: [2, 12, 13, 15, 17, 18, 22, 23, 24, 28, 29, 30], each: [2, 6, 9, 10, 13, 15, 27], eas: [26, 31], easier: [28, 31, 33], easili: [20, 29], echo: 27, echo_rang: 11, echo_reduct: 11, edit: 20, effici: 18, either: [7, 9, 10], element: [15, 27, 30], els: [2, 23], emb: 4, embed: 10, embedd: 4, embeddable_imag: 4, emploi: 20, empti: 31, enabl: [17, 26], end: 2, end_tim: 22, enough: [2, 27, 28], ensur: 22, ensure_ascii: 23, entri: 2, env: [0, 1, 27, 29, 33], envelop: 11, environ: [28, 29], epoll1: 25, erosion_kern: 11, error: [22, 25, 28], estim: 2, etc: [9, 11], european: 32, even: 17, event: 8, ever: 31, everi: 13, everyth: 27, exactli: 28, exampl: [0, 1, 2, 6, 12, 17, 23, 25, 26, 27, 28, 31, 33], except: 23, exclud: 12, exclus: 2, execut: 2, exist: [2, 17, 22, 23, 29, 30], exp: 28, expect: 2, explor: [2, 3], ext: [0, 1, 32, 33], extend: [12, 23, 33], extens: [0, 1, 17, 25, 33], extern: [17, 18, 31], extra: [29, 33], extract: [9, 12, 13, 26, 33], extract_window: 13, f: [15, 22, 30], f_exist: 22, factor: [2, 10, 15], fail: [2, 30], fals: [2, 4, 6, 7, 9, 10, 13, 15, 16, 17, 23, 30], familiar: 28, familiaris: 27, faq: 34, faster: 29, fb8072: 2, fccde5: 2, fdb462: 2, featur: [9, 12, 26], few: 27, fewer: 25, ffed6f: 2, ffffb3: 2, ffrom: 9, fft_rate: 6, fft_size: 6, field: [12, 17, 22], fieldrecord: 17, figur: 17, file: [0, 1, 2, 12, 13, 16, 17, 18, 20, 22, 23, 24, 27, 28, 30, 31, 32, 34], file_list: 23, fileexistserror: [2, 16, 17], filenotfounderror: 17, filepath: [0, 1, 33], files: [0, 1, 33], files_to_seg: [0, 1, 32, 33], filt: 24, filter: 17, finch: 32, find: [12, 28, 31, 32], find_unit: 12, first: [6, 12, 16, 29, 31, 33], fix: [17, 25], flatten: 15, flatten_list: 15, flatten_spectrogram: 13, flexibl: 33, focal: 12, folder: [2, 12, 16, 17, 23, 24, 28, 31], follow: [25, 28, 31], foolproof: 20, forc: 17, forg: 29, fork: 25, format: [12, 33], found: [2, 17, 27, 33], frame: [4, 6, 13], freez: 25, frequenc: [2, 6, 7, 9, 11, 12, 13, 33], fresh: 29, friendli: 33, from: [0, 1, 2, 4, 6, 9, 10, 11, 12, 13, 15, 16, 17, 20, 23, 24, 26, 27, 28, 31, 33], full: [2, 13, 33], fulli: 2, funtion: 2, g: [2, 12, 13, 15, 17, 18, 22, 23, 28, 30], gain: [0, 1, 33], gauss_sigma: [6, 11], gaussian: [6, 11], gaussian_blur: 11, gen_meta: 24, gener: [2, 4, 6, 12, 14, 16, 17, 24, 29], georg: 23, get: [2, 12, 13, 17, 25, 30, 31, 32], get_chunk: 15, get_file_path: [0, 1, 17, 32, 33], get_indv_unit: 13, get_indv_units_parallel: 13, get_mark: 5, get_mean_sd_mfcc: 9, get_metadata: [0, 1, 12, 33], get_norm_spectral_envelop: 11, get_peak_freq: 9, get_segment_info: 12, get_unit: [2, 27], get_unit_spectrogram: 13, get_vocalisation_unit: 13, get_wav: 12, get_wavs_w_annot: [0, 1, 17, 32, 33], gif: 27, git: [15, 29, 31], github: 29, given: [2, 12, 13, 17, 23, 24], global: 2, go: [15, 27, 28], good: 2, gpu: [10, 20, 28], gre: 28, great: [27, 32], great_tit: [17, 27], greatli: 26, grei: 4, group: [0, 1, 2, 10, 33], grouping_label: 5, grpcio: 25, guid: [20, 33], gz: [23, 28], gzip: 16, ha: [2, 16, 17, 27, 28], half: [28, 32], happen: [2, 30], happi: 27, have: [2, 17, 25, 27, 28, 29, 30, 31, 33], hdbscan: [2, 10], hdbscan_clust: 10, hdd: 17, head: 27, held: 17, help: [20, 24, 28, 29], here: [27, 30, 33], hertz: [11, 12], high: 34, highcut: 6, highli: 27, hint: 22, histogram: [2, 7], home: [0, 1, 17, 27, 33], hood: 29, hop: 13, hop_length: [6, 11, 13], hop_length_m: 6, hopefulli: 28, hover: 27, how: [6, 10, 17, 27, 28, 33], hpc: 20, html: 30, html_marker: 5, http: [15, 29, 30], hz: [6, 11, 13], hz_to_mel_lib: 11, i: [2, 12, 14, 24, 27, 28, 29, 31, 33], ib: [0, 1, 33], id: [2, 4, 10, 12, 13, 16, 22, 30, 33], identif: 2, identifi: 12, idx: 10, ignor: 12, ignore_check: 17, ignore_label: 12, imag: [4, 29], immut: 17, implement: [10, 13, 23, 29], in_dir: 28, includ: [0, 1, 6, 17, 31, 32, 33], incorpor: 12, indent: 23, index: [0, 1, 11, 12, 16, 27, 33], indic: [6, 7], individu: [2, 4, 6, 13, 16, 27, 30, 33], indv_list: 5, info: [15, 25, 27, 30], inform: [2, 12, 15, 30, 31, 33], inherit: 22, init: 28, initialis: 17, input: [22, 30], inset: 12, instal: 34, instanc: [12, 17, 22, 27], instance_of: [0, 1, 33], instanti: [2, 22], instead: 10, instruct: [20, 28], intend: [0, 1, 17, 20, 33], intens: [28, 30], interact: [2, 3, 4, 5, 27, 28], interactib: 4, interct: 4, interest: [22, 33], interfer: 29, interpol: 11, interpret: 28, invert: 4, involv: 28, io: 15, ip_head: 28, ipython: 25, is_list_of_int: 22, is_list_of_str: 22, isft: [0, 1, 33], issu: 34, item: [6, 15, 17], iter: [12, 13, 15, 23], iterable_nam: 15, its: [2, 7, 9, 12, 13, 17, 27, 31, 33], jit: 13, jitter: 7, jmv6r: 15, job: [20, 28], json: [0, 1, 2, 12, 16, 17, 18, 22, 23, 28, 33], json_fil: 2, json_loc: [18, 23, 24], json_object: 23, json_outdir: [0, 1, 12, 33], jsonencod: 23, just: [15, 17, 31, 32, 33], kantodata: [2, 4, 6, 7, 9, 10, 11, 12, 13, 15, 17, 18, 25, 27, 28, 34], karlb: 23, kbp: [0, 1, 33], keep: [2, 6, 17], kei: [2, 7, 9, 12, 13, 16, 26], kernel: [2, 6, 11, 25], kernel_s: 11, keyerror: 6, keys_to_mov: 2, keyword: [2, 7, 12], khz: [0, 1, 33], kib: [0, 1, 33], kingdom: 32, known: [29, 34], kwarg: [2, 6, 7, 10, 12, 15, 22], lab: 5, label: [2, 3, 4, 5, 10, 12, 22, 27], labels_: 10, labels_to_ignor: [12, 32], lachlan: 27, languag: 28, larg: [2, 3, 12, 28, 31], larger: 10, last: [2, 6, 15, 30], last_chunk: [15, 22], later: 33, launch: 21, lavf57: [0, 1, 33], learn: 27, least: [28, 30], leav: 2, legibl: 15, leland: 4, len: [9, 15], len_iter: [15, 22], lenght: [2, 4, 7, 13], length: [2, 6, 7, 12, 13, 15, 27, 30], length_: [22, 27], less: 24, let: [23, 27, 31, 33], level: 28, lib: [0, 1, 27, 33], librari: [24, 26, 28], lightweigth: 2, like: [2, 10, 17, 23, 25, 28, 29, 31, 33], limit: 2, line: 30, lineno: 30, link: [2, 17], link_project_data: [17, 31], list: [2, 5, 7, 12, 13, 15, 16, 17, 22, 23, 24], littl: 28, live: [17, 24, 31], load: [0, 1, 2, 4, 13, 17, 27, 30, 33], load_bk_data: 4, locat: [2, 12, 13, 17, 31], log: [9, 20, 28], logfil: 28, longer: 2, look: [17, 27, 28], lose: 2, loss: 11, lot: [2, 28], lowcut: 6, lower: 25, lower_freq: [22, 27], lst: 15, luscinia: 27, m: [7, 20, 28], machin: [2, 17, 25, 32], magic: 25, main: [2, 22, 24], maintain: 24, major: 27, make: [0, 1, 2, 23, 28, 31, 33], make_tarfil: [23, 28], makedir: [0, 1, 23, 33], male: 27, manag: 15, mani: [6, 27, 28], manifold: 10, manipul: 13, manual: 33, map: 5, marker_typ: 5, mask: [6, 7], match: [12, 24], matplotlib: 30, matrix: 10, max: [11, 12], max_amplitud: [22, 27], max_db: 6, max_lenght: 7, max_n_lab: 2, max_unit_length: 6, maxfreq: [2, 7, 26], maximum: [2, 6, 7, 9, 13], mcinn: 4, me: 28, mean: 9, mel: [2, 6, 7, 9, 11], mel_bin: 11, mel_spectrogram: 11, mel_to_hz: 11, mels_to_hz: 11, melscal: 9, melspectrogram: [2, 7, 13], mem: 28, membership: 2, memori: [2, 28], merino: 27, messag: [24, 25], meta: [0, 1, 33], metadata: [0, 1, 2, 12, 16, 17, 22, 24], metadata_dir: 12, method: [2, 6, 7, 11, 23, 26, 27, 30, 31, 33], method_parallel: 30, method_r: 30, mfcc: 9, might: [17, 25, 26, 27, 28, 30, 33], million: [28, 32], min: [11, 12], min_amplitud: [22, 27], min_cluster_s: 10, min_dist: 10, min_dur: [12, 32], min_freqrang: [12, 32], min_level_db: 11, min_sampl: [2, 10, 27], min_silence_length: 6, min_unit_length: 6, mindb: 11, minfreq: [2, 7, 26], miniconda3: [0, 1, 27, 33], minim: [17, 27], minimum: [2, 6, 7, 9, 10, 12, 13, 24], minmax: 11, minmax_freq: 11, miss: 2, mk_colour: 5, mkdir: [17, 31, 32], model: [5, 28], modif: 20, modifi: [6, 7, 15, 23], modul: [3, 8, 14, 19, 22], monkei: 33, more: [6, 10, 20, 27, 28, 31], most: [28, 30, 33], move: [2, 17], mspaced_mask: 7, much: [6, 26, 29], multi: [20, 28], multipl: [13, 28], must: 2, my: [27, 32], mykin: 32, myproject: 17, n: [6, 7, 9, 15, 28, 29, 30], n_chunk: [15, 22], n_compon: 10, n_featur: 10, n_fft: 16, n_mfcc: 9, n_neighbor: 10, n_sampl: 10, n_song: 2, n_worker: [15, 22], name: [2, 6, 12, 16, 17, 23, 24, 30], nameerror: 30, natur: 26, nbin: [2, 7], ndarrai: [4, 5, 7, 9, 10, 11, 12, 13, 23], necessari: [22, 29], need: [26, 27, 28, 29, 31, 33], nest: 23, network: 2, neural: 2, never: 31, new_attr: 17, new_dataset: 2, new_project: 17, new_valu: 17, newli: 2, next: [27, 31], nilo: [20, 27], nilomr: [0, 1, 27, 29, 33], node: [20, 28, 32], nois: [2, 10, 12, 30, 32], non: 33, none: [2, 6, 7, 9, 10, 12, 13, 15, 17, 22, 23, 24, 30, 32], norm: 11, normal: [12, 28, 33], normalis: 11, note: [2, 27, 30, 33], now: [13, 27, 31, 33], nox: 29, np: [4, 7, 9, 10, 11, 12, 13], nparray_dir: 13, nparray_or_dir: 7, num: 24, num_cpu: [2, 6, 10, 12, 13, 25], num_mel_bin: 6, numba: [13, 28], number: [2, 3, 6, 7, 9, 10, 12, 15, 22, 24, 25, 31], numpi: [4, 5, 9, 10, 11, 12, 13, 23], numpyencod: 23, nvidia: [28, 29], o: [14, 23], obj: 23, obj_id: 15, object: [0, 1, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 23, 25, 27, 33], offset: [2, 7, 12, 13, 16, 27], old: 17, onc: [2, 27], one: [2, 4, 6, 12, 13, 17, 26, 27, 28], ones: [2, 17], onli: [12, 17, 25, 28, 29], onset: [2, 7, 12, 13, 16, 27], onsets_offset: [7, 12], open: [2, 13, 30], open_dataset: [18, 30], open_gzip: 16, open_label_app: [2, 27], oper: 15, optim: 28, optimis: [15, 28], option: [2, 4, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 23, 24], order: [2, 9, 29], org: 30, organis: 2, origin: [2, 11, 17], os: [17, 24, 28], other: [2, 12, 22, 26, 27], otherwis: 31, our: 33, out: [2, 20, 25, 28], out_dir: [20, 28, 30], out_directori: 24, outlier: 2, output: [2, 12, 16, 20, 23, 26], output_filenam: 23, outsid: 29, over: [7, 28, 32], overflow: 23, overhead: 28, overkil: 28, overlai: [2, 7], overlap: 16, overwrit: [2, 17], overwrite_data: [2, 30], overwrite_dataset: [2, 27, 30], overwrite_json: 16, own: [2, 27, 33], oxford: 20, oxfordshir: 27, p: [27, 28], packag: [0, 1, 27, 28, 29, 33], pad: [2, 13, 16], pad_length: 13, pad_spectrogram: 13, pair: 12, palett: [2, 5, 30], paralel: [15, 33], parallel: [2, 6, 10, 12, 13, 15, 20, 25, 28], parallelis: [15, 28, 30], param: [27, 28, 30], paramet: [2, 4, 7, 9, 10, 11, 12, 13, 15, 16, 17, 18, 23, 24, 25, 27, 28], parent: [17, 23, 32], pars: [0, 1, 12, 16, 20, 33], parse_boolean: 5, parse_sonic_visualiser_xml: [0, 1, 12, 16, 32, 33], parser: [0, 1, 14, 33], parser_func: [0, 1, 12, 32, 33], particular: 28, paru: 27, pass: [2, 6, 7, 10, 12, 23, 28], patch: 33, path: [0, 1, 2, 4, 7, 12, 13, 16, 18, 22, 23, 24, 27, 32, 33], pathlib: [2, 12, 13, 16, 17, 18, 22, 23, 31], pathlik: [17, 24], pbar: [12, 16], pcm: [0, 1, 33], pd: 10, peak: 9, peng: [20, 28], peopl: 33, per: [2, 4, 6, 13, 30], perform: [10, 11, 34], person: 28, petrel: [17, 32], pickl: [13, 25, 30], pictur: [0, 1, 33], pip: 29, pkg_resourc: 32, placehold: 2, platform: [26, 28], plot: [2, 4, 9, 26, 27, 30], plot_summari: 30, plot_segments: [2, 27], png: 4, point: [2, 10, 17, 27, 31], poll: 25, popul: [2, 27], popular: 28, possibl: [7, 28, 29], power: 9, precis: 26, prefer: 29, prepar: [2, 4, 27], prepare_datasourc: 4, prepare_interactive_data: [2, 27], prepare_legend: 5, present: [2, 12, 13, 22, 27], preserv: 33, preston: 32, pretti: 15, print: [0, 1, 2, 12, 15, 17, 24, 28, 30, 31, 33], print_dict: 15, print_parallel_info: 15, probabl: [28, 31], problem: 17, process: [2, 4, 7, 8, 15, 21, 27], produc: 2, programmat: [2, 24], progress: [12, 15], projdir: [2, 12, 17, 22, 31, 32], project: [2, 10, 12, 17, 22, 27, 32, 33, 34], project_data_dir: 17, project_root: 31, projroot: 17, promot: 31, prompt: 2, properli: 33, provid: [2, 6, 7, 9, 12, 17, 22, 24, 26, 28, 31, 33], pty: 28, purg: 24, purpos: 22, purr: 32, py: [27, 28], pycharm: 27, pykanto: [0, 1, 25, 26, 27, 31, 32, 33, 34], pykanto_data: [0, 1, 17, 27, 33], pyrigh: 22, pytest: 29, python3: [0, 1, 33], python: [28, 29, 30], pytorch: 29, queri: [2, 24], quickli: [2, 11, 28], r: [0, 1, 28, 33], rai: [15, 19, 20, 21, 25, 27, 28, 30, 33], raid: 31, rais: [2, 6, 16, 17, 23], ram: 25, rand_jitt: 7, random: [2, 28], random_subset: [2, 28], rang: [2, 11, 12], rapid: 29, rapidsai: 29, rate: [6, 12, 13], ratio: 12, raw: [0, 1, 12, 17, 27, 28, 32, 33], raw_data: [0, 1, 17, 22, 31, 32, 33], raw_data_dir: 12, rb: 30, re: [0, 1, 33], reach: 6, read: [12, 16, 31, 33], read_json: [18, 24], readi: [4, 31], readwav: [0, 1, 12, 33], readwav_patch: [0, 1, 33], real: [27, 28], realiti: [0, 1, 33], reallist: 2, reason: 27, rec_unit: [0, 1, 33], recald: [20, 27], recent: 30, recommend: [27, 29, 31], record: [0, 1, 12, 24, 27, 33], recordist: 27, recurs: 17, redis_password: 28, reduc: [6, 10, 28], reduce_and_clust: 10, reduce_and_cluster_parallel: 10, reduct: [2, 10, 28], refer: [13, 20, 28, 33], region: [22, 33], regular: 10, regularli: 7, reilli: 23, relabel: 2, relabel_noise_seg: 2, relabel_seg: 2, relat: [8, 22], releas: 29, relev: [12, 16, 33], reload: [2, 27], remain: 12, remaining_indv: 5, rememb: 2, remot: [30, 31], remov: [12, 24, 29], repo: 31, report: 17, repositori: 31, repres: 28, represent: [2, 13, 27], reproduc: [2, 26], request: 28, requir: [2, 11, 17, 33], resampl: [12, 32], rescal: 11, research: [12, 26], resourc: [2, 17, 28], resource_filenam: 32, respect: 2, rest: 17, restart: 25, result: [2, 7, 9, 12, 13], retriev: 33, retrieve_spectrogram: 13, return_kei: 2, return_path: 23, reverber: 6, rgb: 4, rifftag: [0, 1, 33], right: 28, robert: 27, rolloff_max: 7, rolloff_min: 7, root: [17, 31], root_dir: 17, row: [6, 27], run: [2, 20, 25, 26, 27, 28, 29, 33], runtim: 28, s: [0, 1, 2, 5, 9, 11, 12, 13, 15, 17, 22, 25, 26, 27, 29, 31, 32, 33], safe: 23, sai: [28, 30, 33], sainburg: [12, 23, 27], same: [2, 4, 13, 17, 25, 28, 29, 31], sampl: [0, 1, 2, 6, 10, 12, 13, 17, 27, 30, 32, 33], sample_info: [2, 30], sample_r: [0, 1, 22, 33], sample_s: 2, save: [2, 4, 12, 13, 20, 23, 24, 30, 33], save_json: 23, save_melspectrogram: [10, 12, 13], save_seg: 12, save_to_disk: 2, schedul: [19, 21, 28], scienc: 27, scikit: 29, scratch: 33, script: [20, 28], sd: 9, sdata: 5, seaborn: 7, search: [0, 1, 17, 33], search_parent_directori: 31, second: [0, 1, 2, 6, 12, 13, 16, 28, 32, 33], section: 31, see: [2, 10, 12, 17, 20, 24, 25, 27, 28, 29, 30, 31, 33], seekabl: 12, seg: 27, segment: [0, 1, 2, 6, 7, 8, 13, 16, 17, 22, 27, 28, 31, 34], segment_fil: [0, 1, 12, 33], segment_files_parallel: [12, 32, 33], segment_into_unit: [2, 27, 28, 32], segment_is_valid: 12, segment_song_into_unit: 12, segment_song_into_units_parallel: 12, segmentannot: [12, 16, 22, 33], segmentmetadata: [0, 1, 12, 33], segmentmetadata_patch: [0, 1, 33], segmet: 12, select: 7, selector: 29, self: [0, 1, 2, 10, 23, 33], separ: [6, 12, 23], serializ: [22, 23], server: 31, servic: 27, session: 28, set3_12: 2, set: [0, 1, 2, 6, 11, 25, 33, 34], set_rang: 5, setup: 27, sf: 12, sh: 28, shape: 10, share: 17, shetland: 32, shorter: [2, 15], should: [2, 27, 28], show: [2, 9, 26, 27], show_extreme_sampl: 2, show_extreme_song: 2, show_minmax_frequ: 7, show_spec_centroid_bandwidth: 7, sigma: 6, signal: [0, 1, 33], silenc: [2, 6, 22], silence_threshold: 6, simon: 32, simpl: [27, 28], simpli: [27, 31], simplic: 27, singl: [12, 13, 28, 30], site: [0, 1, 33], size: [2, 6, 10, 15, 27, 30], skip: 2, skipkei: 23, slaunch: [20, 28], slice: 28, slightli: 28, slow: 28, slurm: 28, small: [2, 10, 27, 28], smaller: 2, sns_histoplot: 7, so: [2, 26, 28, 33], some: [26, 28, 29, 30, 33], someth: [28, 30], song: [2, 4, 11, 13, 22, 27, 32], song_level: [2, 4, 6, 10, 13], sonic: [12, 16, 33], sort: 11, sort_kei: 23, sound: 24, soundfil: 12, sourc: [2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17, 18, 20, 22, 23, 24, 28], source_datetim: 27, source_dir: 23, source_wav: [22, 27], space: 7, span_mk_siz: 5, spec: [7, 9], spec_bw: 7, spec_centroid_bandwidth: [9, 26], spec_length: [2, 4], speci: 27, specif: 12, spectral: [7, 9, 11], spectrogram: [2, 4, 6, 7, 8, 9, 11, 12, 27, 28, 30], spectrogram_loc: 27, sphinx: 29, spot: 2, sr: [6, 11, 12, 13], srun: 28, stabl: 30, stack: 23, stackoverflow: 15, standard: [11, 12, 28, 33], standardis: 31, start: [0, 1, 2, 27, 33], start_tim: [0, 1, 22, 33], state: [0, 1, 33], std: 9, step: 6, still: [28, 33], storag: 22, store: [6, 7, 17, 22, 23, 26, 31, 33], storm: [17, 32], str: [0, 1, 2, 4, 5, 7, 9, 10, 12, 13, 15, 16, 17, 22, 24, 33], strategi: 25, streaminfo: [0, 1, 33], string: [0, 1, 7, 9, 16, 33], strongli: 31, structur: [2, 12, 17], studi: 27, subclass: 23, subdirectori: 17, subfold: 12, submit: [20, 28], submit_job: 20, submodul: 20, subset: [2, 6, 28], succesfulli: 30, success: [6, 15, 24], suggest: 33, sumbiss: 28, summari: 12, summary_plot: 2, support: [23, 25, 29], sure: [0, 1, 2, 33], sw83: 27, sy: 28, syllabl: 16, symlink: 17, system: [17, 28, 29, 31], t: [2, 17, 23, 25, 27], tab: 2, tag: [0, 1, 33], take: [28, 32], taken: 6, tar: [23, 28], tarfil: 23, target: 17, task: 28, tech_com: 27, tell: [31, 33], tend: [6, 33], term: 24, termin: 28, test: [2, 17, 21, 29, 32], than: [20, 24, 25, 28], thei: [2, 17, 26, 27, 28, 29], them: [16, 27, 31, 32], thi: [0, 1, 2, 9, 12, 15, 17, 20, 22, 23, 24, 25, 27, 28, 29, 30, 31, 33], think: 33, those: 33, three: [30, 32], threshold: [6, 9, 11], tidi: 17, tim: [12, 23, 27], time: [2, 12, 15, 27, 28, 33], timeaxisconvers: 16, timedelta: [0, 1, 33], timer: 15, timezon: 27, tip: 33, tit: [27, 32], titl: 7, to_csv: 2, to_iter: 15, todo: 12, togeth: 31, too: [2, 10], took: 32, tool: [8, 14, 28], top: [6, 28], top_db: 6, torchaudio: 29, torchvis: 29, total: [15, 30], touch: 31, tqdm: 15, tqdmm: 15, traceback: 30, trail: 2, train: [2, 28], transfer: 17, translat: 28, tree: [17, 31], trim: 2, troubl: 2, truli: 28, tupl: [4, 6, 7, 9, 10, 11, 12, 13, 16, 17], tutori: [17, 30], two: [2, 16, 27, 28], type: [0, 1, 2, 4, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 23, 24, 27, 33], typeerror: 23, ugli: 33, ujson: [18, 23], uk: 27, umap: [2, 10, 29], umap_: 10, umap_i: 10, umap_reduc: 10, umap_x: 10, under: [12, 17, 29], uniform: 10, uniqu: 30, unit: [2, 4, 6, 7, 10, 12, 13, 16, 27, 28, 32], unit_label: [2, 4], univers: 20, unix: 17, unless: 15, unsupervis: 2, up: 34, updat: [6, 17, 25], update_feedback_text: 5, update_json_loc: [17, 31], upper_freq: [22, 27], us: [2, 4, 6, 7, 10, 11, 12, 13, 15, 17, 18, 19, 20, 23, 25, 29, 30, 31, 32, 33], user: [6, 15, 17, 22, 28], utc: [0, 1, 27, 33], util: [0, 1, 12, 27, 28, 31, 33], v100: 28, v: 23, valid: [0, 1, 6, 10, 12, 17, 22, 33], validdir: 22, valu: [4, 10, 11], value_count: 30, valueerror: [2, 17], vari: 26, variabl: [2, 17, 30], vector: 10, verbos: [2, 6, 10, 12, 15, 17, 24], veri: 2, version: [2, 10, 12, 17, 29, 30, 31], via: 29, view: 27, virtual: 29, visualis: [2, 12, 16, 33], voc: [2, 27, 30], vocal: 2, vocalis: [2, 3, 4, 6, 7, 9, 10, 12, 13, 27, 30, 34], vocalisation_kei: 10, vocalisation_label: [2, 4], vocalseg: [12, 27], voic: 6, vscode: 27, w: 30, wa: [0, 1, 13, 33], wai: [15, 20, 26, 28, 31, 33], want: [17, 27, 28, 29, 31, 33], wav: [0, 1, 2, 12, 13, 17, 32, 33], wav_dir: [0, 1, 12, 33], wav_fil: [17, 22, 27], wav_filepath: [0, 1, 17, 32, 33], wav_out: 12, wav_outdir: [0, 1, 12, 33], wave: [0, 1, 33], waveaudioformat: [0, 1, 33], wavestreaminfo: [0, 1, 33], wavfil: [12, 17], we: [27, 33], web: [2, 3, 4], well: [6, 12, 27, 28], were: 30, wether: [6, 17], what: [2, 12, 15, 33], when: [2, 17, 25], where: [2, 12, 15, 17, 24, 28, 31], wherev: 31, wheter: 12, whether: [2, 4, 6, 9, 10, 12, 13, 17, 23, 24], which: [2, 12, 17, 20, 26, 27, 28, 30], whose: 22, why: 31, wil: 31, window: [6, 13, 17], window_length: 6, window_offset: 16, within: [2, 12, 15, 17, 20, 28], without: [13, 25], wlength: 13, wood: 27, work: [2, 6, 12, 17, 20, 27, 28, 33], worker: 25, workflow: 34, working_tree_dir: 31, world: 28, would: [12, 27, 28, 29, 33], wrapper: [10, 15, 28], writabl: 15, write: [0, 1, 27, 28, 33], wrong: 23, wytham: 27, wytham_gretis_2021_test: 30, x11: 28, x: [11, 13], xc46092: 32, xc663885: 32, xeno: 24, xml: [0, 1, 12, 16, 32, 33], xml_filepath: [0, 1, 16, 32, 33], y: 13, year: 12, yield: [13, 15], you: [0, 1, 2, 7, 9, 12, 17, 20, 23, 25, 26, 27, 28, 29, 30, 31, 33], your: [2, 7, 9, 12, 17, 24, 25, 27, 29, 33], yourself: 27, zero: 12, zhenghao: [20, 28] }, titles: ["<no title>", "<no title>", "pykanto.dataset", "pykanto.labelapp", "pykanto.labelapp.data", "pykanto.labelapp.main", "pykanto.parameters", "pykanto.plot", "pykanto.signal", "pykanto.signal.analysis", "pykanto.signal.cluster", "pykanto.signal.filter", "pykanto.signal.segment", "pykanto.signal.spectrogram", "pykanto.utils", "pykanto.utils.compute", "pykanto.utils.custom", "pykanto.utils.paths", "pykanto.utils.read", "pykanto.utils.slurm", "pykanto.utils.slurm.launch", "pykanto.utils.slurm.tester", "pykanto.utils.types", "pykanto.utils.write", "pykanto.utils.xenocanto", "FAQs & known issues", "Vocalisation analysis", "Basic workflow", "High Performance Computing", "Installing pykanto", "The KantoData class", "Setting up a project", "Vocalisation segmentation", "File segmentation", "Documentation"], titleterms: { "1": 31, "2": 31, "class": 30, The: 30, an: 27, analysi: [9, 26], area: 28, avoid: 29, basic: [27, 29], cluster: [10, 28], code: 28, comput: [15, 28], custom: [16, 33], data: [4, 28, 31], dataset: [2, 31], depend: 29, deriv: 31, develop: 29, directori: 31, document: 34, faq: 25, field: 33, file: 33, filter: 11, first: 28, freez: 31, gpu: 29, guid: 34, hell: 29, high: 28, hpc: 28, id: 27, instal: 29, introduct: 28, issu: 25, kantodata: 30, known: 25, labelapp: [3, 4, 5], launch: 20, librari: 29, link: 31, local: 28, machin: 28, main: 5, metadata: 33, ml: 29, modul: 34, onli: 31, paramet: [6, 30], path: [17, 31], perform: 28, plot: 7, programmat: 31, project: 31, pykanto: [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 28, 29], raw: 31, read: 18, segment: [12, 32, 33], set: 31, signal: [8, 9, 10, 11, 12, 13], slurm: [19, 20, 21], spectrogram: 13, storag: 28, test: 28, tester: 21, tip: [27, 28, 29, 31], type: 22, up: 31, upload: 28, us: [27, 28], user: 34, util: [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], vocalis: [26, 32], work: 31, workflow: 27, write: 23, xenocanto: 24, your: [28, 31] } }) \ No newline at end of file