From e160b88167712b03e3752ae8a5549ee925d01e88 Mon Sep 17 00:00:00 2001 From: philipMartini Date: Sun, 7 Mar 2021 18:46:03 +0000 Subject: [PATCH] Update documentation --- .../doctrees/PyCTBN.PyCTBN.estimators.doctree | Bin 252784 -> 253064 bytes docs-out/_build/doctrees/environment.pickle | Bin 148538 -> 148538 bytes .../_build/html/PyCTBN.PyCTBN.estimators.html | 24 ++++++++---------- docs-out/_build/html/searchindex.js | 2 +- docs/PyCTBN.PyCTBN.estimators.html | 24 ++++++++---------- docs/searchindex.js | 2 +- 6 files changed, 24 insertions(+), 28 deletions(-) diff --git a/docs-out/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree b/docs-out/_build/doctrees/PyCTBN.PyCTBN.estimators.doctree index 86a89d34b528bda65502996928b0e07daefcc4aa..94d843830b612e391b8ce9eb5f75f9dcd94a542b 100644 GIT binary patch delta 21172 zcma)kd3?=B_rEzG7t5OTiR-AR9jlA8xK{#v)nc5%dh_M$!BKH`<$6MbIzGF^SM9QwOO*G z&7#%HO9gIktzN0qmugg(jzedc&zU}P{Ot03rpzjzIc;)qucC;w~q0O(T zHv0Z8Dp9S{SvysbC9{VQEDy6Bf2boqbk-j#OZ|sxx>*)I=%JqFMysZI>G9iDq~8l+ zO`4eBh9*sx%qb5qKUN-KMw;4U`vva zZqVQ1a3M^W1*tH-cBi@%0>UjJZ-s$>xUSxzI_sS?p_hu#Gv8EEo)O`U5EZUhzM-O; zw??$Ea7*RQSSqgpBRqM95)t5@O z)gebzEVPcWgxnpaf_0Vct?F)nEYv=^kfjo+jjtuxKSA$#M@6gNb{ehjQc=(%!V>qR zuP%F64Z)FNxDtW8OW^R0;7V+84>W+AXQ#2l>3Q#~$!d!fZxpCk1Pb2>YGZ`ny$*8J z+fJyxzd>_7WIcH4%t8oM`|Q*V+Pp;sDW5(a1hdt5QdKX&zY8$F5paEku1zwsR7)N5 zu`0BjS?Qy<98;Z@hps(NLlD=Qn%KInBlBRUigs3oNAf79O35N@j3opc9x1Rx8^9L1 z(mG&$B4C1=HIF%JP^6xgijO_Ku970Ca-%%Z>=~h-cof>{ z%O9yY^&+wUKU~0w7250d09Jdq#-wvab0$tH@AAOvUgg1KSDSwcx0G#YuVa5vg}UH` zO7`-^VMN7Ls9nFI_VriYt*@O>mzC%7NX9!Fsn2dzvHJ5*)j9Qn-us!Frp^(^Aj`f- zTY8?QRxH<*d^JeFbW%N_Zb>!Snj4X9Yw%H(*;Q|eP(8pe%2Kv441A(2`@4+rYai9n z#@xVxB^!e@Xk&2kFZ*1LrZ=)B*97|K#Vz6YNXwP^UG>y2)NB|OrLUBz7$}TlcKC3x zn<(tYM_J-NjDRrY8WQd|xe?dGDB+5v#I;aoomPYKvGTNvgFGzE4YPCf`ASWL4K|Kz zg(E(QXT}Ultk;i!qw=9XYVAO{145!LDnF8~7S^y7XWXPXUa$VG zvUTwVn;%J!=D|*n7C$mVYPM`{sfN*?k+#A1EsbtC#p$~0Th$Q|fW%1GJHAy@>5XPM zMPP7-)$e-Ic@?gH;W^h6cB+N{1Wo|49-h#Qa#E25<~tf%#b?^K$C zSEx&|xK2oB22dNc&qc&!`cTWy2VzjCxkrTYo-2k9x`1o!EY(t1^p(R9uJ@VHB)xh; zwN|GEwB~+gQlGmpc#j#tS1c$xuyyp!!N4J z^GTu$Ft3jhyD|Ba`qqP6t&P$9K2vwASD3$L!nO{cFH+k;b4rY6>v7-jXwKe~>V3OA z!@(HRFm+I8{-LsQ&Zy&-iU&KWFXYc)e}Cy)nsRW_PTmfO?EP$5NlDtcT%wqlcMH1`Oj_0 z|Gq~2C)oHS4)uM4{_;+xo=UBO*(mg5&=U{V}K z128AfayB7GP0}Hr&=CvuLq3oLkCW^LWFlhVQEu;SVfp#PDA*cjDNAxC^YDefurtn5 zTbV~F9D|HU&L7EY3?3Ng5PTf{*Dm^s!Aq)mi514tLiE=aEn$J@H$)O(J`+a^ zF~-kaz!2Q-v<+BSPFKM^MuoN#oZxYBI7aRCqE_G!SFukxKsRWB0#$+a!&cZ~@afH? z175wYL2cj-rF!YCwh#;5dvmaqKyQAQSie9j!C*;s*Nc6izZyst5_QrjsR9QXMO4@p zM@dZ;>P53%sGIvjg1S#CYL3QZQywe~ZV6CqAx26eUcDUy7DRtG7%)?ByZI{A6a66F zOB(TzwCF81ENC0tWqO8)1I*Rd%y!U8!KU71xza5a6GK%Uvt;Y_I<*Qk2leI!5zqm~ z!#lls1-vbC@rruAx2&idjIn6}eCq`G#tq=u%aEb2ORdeaMd~{`;<*1IaG6T^sb5{7 zzi~o46rY4;XVZefMe9*QayF)T(Rx!nJDa$8ayA;BO`i2qC#VC+j~A`av3}7R<^qh1 zXRRL<&ssk%p0pnDjb>{Uf?-$<560`WW@8kG=&*nZ)F{0&5<=NK4cGo%;aPZ2kg5gg zbwR>6Lc&MZ;PbjB6yAe_0#NM=Fs}y!{3rn53&3>&z&8TGN7mqP^`$WM%?Xjv+ETN6 zy`B*TomDFx7YVWIdsn#6d%;u{&lM2UhZQ!9-b7)sgdp)zS(~e$j)34*)6#TCA%gu& zz|gOSL$n&My(6GZ&6mQt^l&<57>=Vtf&D6}UhZCv#5h3FUODlODJqF~3G8dQIq%MR zoxJ2A4+wFiLGlJFo*wU1@qW>e=2b#GB)-p#m-v2bG*l|nr+u&@zSUNDe!?FFWk1jYKN4iG&E`FpG4vM3@KoM*Ig5eYll*QX(#9JRXgHp<4@Z=4od_X1tsfKu){!LZSQ0c5sDMG1pC4(d zu8Lxiol)ndxF)wH)b|nReO)BMB#Y-&#O1l<@YpLAf)un&AY%ol1Wt}z?JIT)iOEhu zSOR5OJbNa%5OPcm=?Uzlqx&|9iJ@NtrChpW>L*b!dnQP@UN5qF-`SG%jLlP~tM0RT zLOgcLI8EepW?SPj$q4;BL5$KP)~~YR5e3x=Y?Pit@z52&n!rX0-*DODe!x2yvf*HY zu6|F=h5h!X;w{$eh&-r(@1^vd0Q?~U_(tpgT!L7&R*5cF&6LO-v5r0TdVb2*{1F-* zF|z9tWCd?Lj624@i5v^KXD}cxk$t;;tL{dOI1QF^Rf2OVx4Z)ec&#I5vXmEN4{@um zAH4&9zzj|00E|B-Cer9j-U-W24}cJ<>ZE`AM#brFMbJ$@FQ?cG%lI-(T9)Uv`tbLZ_PV>cK zFyCaa(v?%-Io-24mU|6{jnE}YSAU3GzE6h3^Drz)<36vCX^0Jn8b71QjD#wf#8t80 zYtfk6t8t}G)Ip^%1QR_KrO>yPYlXG86j~}w8v2Y!E4Mg_UCO#a z)nx~WkZ>sGt>Y$QytZ(5X9Tfh70)x`QOmey!uCD{&&y&VKY3XMyLOjGtbt|^(8ngg zz>c%9iZaU&&~R}xj>HDxz>{v5mO%#OC+h`XMn@gkRt3Y*WS!nt1z~=Hxa)DPjb3U9 z{hbKolJ&mUMw}@p8QJ||o~56ehy#|70WNSBxml|Us*%;x-@0lN8Nhp!G4m0qk4}bY z{m7m6)p2h!uMVu$D+fZXo{f3|{Sp5&+`Mikc9QzqNPr}{xW~=D#x}K6swwqVm&~gK zAGAs?zo?>crkI#gBp=Y9!Im>!lKhS%j{9ntr9j=5<+=8O;GOgSmckYlYl=T6*^{NcG|_J=|J8uD-2PxvDO@&|lP znFbHylLb(Mh539{L*v^`pSh_#)XOZFWLY*+c{r?3CO_0uGX9f@EZlPfa>G$umyC9$ zo!-4eb%j~|^jSO;FwLT>0P`GOJR3nP_N%6?*2$!KU~wh0)yFzuLS;ffPJny4R3ooV z9~$BM$W9fbRtm4>ZoGEPgfOV?rz_r6k)~?l^-N=4Cgio*h1YU-UQ})8^;reP(GHpV zwabmy>0PQ@i=$NJF?Mx%dtF=!e!9zU)xyMu0p{b48G9l!Zk=(Sq?5bc8B?{L@#Wok zr1O(7zTnE(T7M73E4bB9kK3z~z?9;22~-w}*crA-Qh{A) zeJ(Xs%Vn{X=Y|(LOZn-GndosB3|D?| zD@FUf0wXjIkf$E82>jp%OG|;&HG%!k3G3YHRbeYiE2g@RJBLzUcwRwiMXywLkqN2f zA`LT6WLc@o(Z5!~5t+!nxF@e#41G-nsWNvuZYjK>=RO33)o7}T(?2g%P21S3aZE;G zOTF?SrXV{%3^SlIm4l<{sT__iOyzJ4-^h(jPi4;oYfuc#j5xf`ZM9&f9Z=lL)Ko`4 zq?M}_dc~u#5cUZ2$R!YSThN_?VplC!AnJGn)yheAs8-5ja0PNxW#csT-_Tt_eJZQf z%EuuJeoS>PurBoo#akKGZ}r2gt5(yQOS7f;g1TLg4au4GSqeMhOsY7OR=Uc9RvF`S zlV=($+$eqg2?*8Om*E~YglZ)n**T3ZIzAj09V2U^rDNN8X}IYAe!hs}?n*kRi77`? zGUfQXa0L|LlTCRiq6`PmG*Q~-X|ivq6l{`fhKpQF;lVUcZ!8qD8BQ|JY;0jNUGtYR zdAN{;>b0w&P;IALPMi)%lZ``?1%g#A6?e7#e5$#CKIH^;YB~-WYkICtOIZzB(-Dg` zeLxy(`o%PNO+T|5KDC>yZ`Pn6$I}KrEWK&nvlfOb%#~HH!?^31Zy@-kb0pT2N@D4a zRM;`&4G>6JnZh#CgX~Xf* z^)!ix&TfFyo->Fxz&tHovg=o$gaa@&UDT;cxY0?*0%{g$Zj;XTYtd714<7rEUg#$@f? z3^%vwhKYCg8R0B zO#6iSXVQe>0e!U<7Y`*gK4C1|X&MT{b2ig;Sb5H(GG)%9GHK2*%U1g;IzhYFYgvPP zWn1_XTnlSpS|)GmRJrxXT1ZlGUnbjzHsvIv%-4MUQ|9ab*P#+tX0o$ehJC@@!{$tO zcKAk?Vp*m*yY0yQAJ1Ja1LFBVb~PF=kXX0FP&g@EP6(It!Uf-m%L(ivrCtBTV?a#1 z-qz_|6Yvvu@MBgm<2h*c4m588S#0d0=uNhrSV9Z}vgC$Hj;?)|%yl?j5NUf`!-pCq zkYe;6(`qL~hcp<)hI%+Dll9P(Bf#>#OELTO8YJjXcET~3k}3Z7@SD(0;j!iAU68CE zAc4Aa0t1VRcS8is&SFojcS8^Lgj@BuyI~%-8ovhy>rwkKqUOBE>@3;Y;gg;5V|jRK zDfTsZOmBG;nn7ij*wF(7#ctViZx*ZT{7l*7eX$R7i>G;H_$t+@EH+UGc?F({>d%Z>K2!>Cssq&C>UBY0r94?{MFwnU)$yv1Ao=A)cjPGF}CL9JnP zG{x0wusK3Fb|E+|WR3>uvLi0$=*=T=&Tftle+YYFQjUZs2QiKVmOrdb=*7GN-2rysFkyvN& zr+7g0eU7ZrCOYeLbPgCzm~K+DK+F%EJq7J8XD0gSuRnt+s-3i;c*mzdDWS=yzbK*J zdlFB3>rO%_)zErt&22^NZsv&gT+bn`>#3KW!u&~=lU+KZAiMt&yJ%Icy+6kjrr}gS z1CNMEDt4T$v59nyPQM4cFi7t&$qSciYidXr|N7K@0ulS5So+D->C- z!PWI=O?y{L=&l= zC>w8Oc<8Dt}vyM+tA?O?T3p)pK``mf-+;-hmPSc( z2OIlKJaqCKc+4{@7s~_85xJs)`yLU0G1)=i272X^LQ3u&@8)0^#B-z(X(0BHtyJ4@ z@yM!#rDn%boXd^_ALKa5uqw0AlH72>@HP z&C|xuc>Elj=iKM3NPX;Q2!zNyx!T*4$fbE01A2xEJQ9m%>EcY-iV{t4IVKz@m9^$Iyn{ko^I9IexG%K& zLtI?!E+f)w5GD1cV-u6O{W;2PV+(v91Jw>s=9vJ`T9Clc)XSWTBunw|e3#M9`r{wC zuY%w5_y|W`(T`t)FX2j_uKW`YTl-vxW{TeUkY>saI02#g63=(DR{V($0226JPG-90 zJ4ETLJNyNcp+6oD;I-*Ct~J<5qWzEmf-287zF#)sf4ci9SckV7LckzX?_(Izs+`_9 za>kNM!|14nucQvhh<4COE57A4xPWds zA&s3ht{;lNH>nep74S_bM56;EJi$L}GN!|P0hud|mk48g<1nW{_Eeh+-1k%t2{t&0 zr8!IRrbr+dxG|sC(ujp4!hEiSISxQ{NQ235Xj{7E^AT*?t43;<^5*4x&3ULH_9Lsl zq*7v6g7d{`-2E(GVEjct;APChdka^*j8eE&pvSjW{oqCc9*qX+*3YXB;91CrRi2j$ z5aAC5)n(74=`Ltvyo1!<-bQGvfIlyMpqxH|p@Fzk}mO;fRl_%v{U@GPBpX9uJ|^{kpoN5#eiX z#B!tF;*ZPi2onI4qo)ip=<+XPe9-{I?@VJ1o7hNAV&h}M|5nk1eC2wg?`CmG-Caip z7;9B~T@`2>thRUXVBv#AkB|yVk@ccKBki(B-O+Hk@Dq#>lpP~Ufw1i3w+nQPHQo*xh(Gf-sWS@n@`p<=2;J|gFu#lUnBGy)j4@*40 z)k-QaCa7ctaDJ3N2ArbPBO~^}B^AAVzf&5Vt+HH=5?&x+V$L9>+4}pUQ<>U?%{f((K;LGSQo$ z#`ePifgsTzZ@QrkQ(;(T7Voz<-NsjV%tK@(K zPY_r-jFfQ15RawXq^G4BNf;#|Do07gh^7@1SqJ3{38zglCy;q*up0>)V2>Em@YBM* z=|-BDG~@h6$N-5GqB0Ea*|~`Qc|ei)^P3sQN$@Y?^ajKhao8V4O#+dTq#u)CGs<8< zk=(+{FCyneS6s4<0+>+5iNLW%d;x1B(z!eEeEcqru9P4Zc|v@>^}3NtuV{RsKbB$& zFiVFFGP>!~hm6-?y^YNpVY7zVbkl9#h9G!Fc)eIeNk{yut#XnP-p*Xpi07IjUF~ng zz#(q0Y!Kwa;WL3a;SO=??;u!gl!C-Y#1|el>hQ^8uW}Rn%o5`b^n?40Y~H)&VD{cE zG512>xptQta^E5JXQV^&o`V~X7SfR9_-zfNkpo9GhtC`2C{}m4Lk<2rDDDB$V-H%i z#0H!Q&DATG8ol(LON|P`CKqTDSn}aK6W^j!bo8c5dQ)ZV%?76k+FgW=jYL2i?#*is z8bCBhZ{Bhg<0qDG19R~2ptv_kkG(Nf*?ObnRvLHfOZi3%9aM}lJyuhP76`JVL)~=n zDq|;pP2lL&Rq54LTd%zJ+3^^XQ4YjQ?;qweM{S2RoFk;+UiEU&0HQg1mFy@+L+1vS z@^?_&E2O7hUA6b>>>9k-&b>NXVvHep>eX+JdbM}0@fP0nLoOU-tLeIWgwY8fS4P^_ z40?V?&lbCjv!szY(}zgUHaTe+YM^@6S@M!Ail4c*F^aAnhkkJS5MDWm8N9*RO0U!h zGXaI$7kuH9#xcyyIOMMv`Rhe~&QAU5xDSwpIWPQ*NuSHMM~hKdLgxnI zMRM|dw{WFzn97j{8&uAtJYQzS={w7eS#W1n5=ONgFfZ7S@%&efj=gdloBT_|U&zX`rWUw()G6zj0-g5o6Sn_cg z=<*ewq$$QFN7Os?PV|^?qnM*!{0{ucT}F4n@4%}n(7UxB%KklApS8V_18j}g=jo$p zyhT#+PaQmdY~qH%F7#hiD1jz2vO#m;F-2-9JVI{lM_UZl?@u!xK)b+5^F^|yA{o9B z`FxvXPg9$J7!u(Qh9q+!uw;9MKZU@K3OzO!t@?4PA<2-NU9!LmV>1300VACk$*zfH z_(qbQw@KDom)-MEC2K)#<$8$&g{6z2ide+7L-UxW>9hA3`NYXCRcaq&IwqJLC`13n zvpHEx=o2d}A?b$xOJ;OF)%?S8o9l)vC@h_(idY*orVob9Gy32!H?VNX$S&OGxyHlz zF{MMeJtEvODIwvogkbmBggZ|)|4_JZ+;9bjgacz3Czu3U?P1}d-7wBAAtSqRH|H5s zA$k~RwZezds6py5%4#Y6y@Z8m8N-Kh7zsm%(boc_y4)^&EMgodB?~f>1+f+4W7Yje z5>$yG2u^~SS_~zBZ>Fo4_zicg2i}C(ATq5LnYM~dYelBD!{l4SJ;ONRgp-d3)i zBA0`j<@!S8aujO*&hRG@3^~|G2%mCY`zjeU$-5P zM7JDv=9EZun^D5STSkeTbB`?H@V2Cc!du@_Na!BkX6U#_P+=>j84}y$0C-S}7M5_Z zI$f(3Mugu(jR8s|K1Nau0Wc-7^-;qL_=esRQn3)f|4%OA>(&%!!cLoR&*j)Z^RP52SZj05;< z4sok(L2~499_L8hy-|>yOEuy6l|MBg=WH9W{NW8p94R>b8p{-bIQBlM83J;5Ly(HU z1EIhRPgK+fqq8Xz8*qB7K{$!v6tv){*K3V%`!sMU`8@OBBekccCr{gY@}>y!MnfTX zHxdFVxF;Vo1t5;2C+7s@Y(tRqe+R-nd0Kk%w7n+{LP!Lsp5Xm*m!5F=7^sWa+vdc7 z1n=zpb@fyB@G*{R!|{hnsFBOO#E)n=Fa9H>H-$pMAOmqD&-C~k4es<~{*InwVH5&2 z3lNUuMtmi~+YtcgOzqRavEwSnm0uSU;g^f>96SC;m_OT)`3sGhFSiN5S11@{pgJaR zM;g+9^mp_u{BjmvEw}F4WZ)?gzLM~d6M&oW*;|ZLxa}(5hE9ooaG>c(UJdvl6?nYb z2*ocaxR!o(pp*QGH%08rB4}j8;cq%ph95KU1d3z?>QJaWM=>UcxrGZ_!QY{Ae-MHu z1Htz{WBiv8sXs~(w&0hM$#}L*LGZzc?Llx4ETQ=RvjbHF8(~$ode?jd?Nvyt%lG+lhxN7W)Rcp};1}OC|i4_ZP zkK{-NuQJ)*(1qi#`~11hcnPly+WMZL!@X60=i9m7@9l8xx0>%m*7&nOM;EE#xY>`} zjtQeP_ZeMODRb-0B^J87(6W?6kCvs9EQ+TZTspSZv_UNy43q#3)&ZKxmgannz)8ik%yO4(6PDiudLv&Q%mCX{jp zNc|tn%NJbcP_sbuUS0Nv5oigX*IQE}NLi>wEUYMHoy7-h8C@mVDzud9cuxMLQ=M%H z95CV7;Dj`wtT3thPjUFe#}RlHh66=Y{oe!f#|@s4bV z$30lu)w1Q0X83~~PSkQIs&iw9)5yzhn`5P*vhZ?4L|SfYw^qB14p29WmK&Ha>zG|e zlvgkXSrUr%&FA*_(-{^nPkhpmIlRRLh8d5(>CC)oFLRrGeR`Mim*;WnM}YY#enf!Z zJmM#2?e-WOO&?GxBI?bjj9EHzuhCllU`^R;oBI!`5%AKkU-*?e5?;8_M+p!E=yiUmBEo-D9wWo$X^uiAe z4}JZ8!@nt2S@!34)k%kq4AW5|JHlj`y5Dvfla!}N>!TkTolK{t@@tlsev+=4j{VT^ zXx0=NeL;mb^?HA_{GuB&X-Svoju{cU?gJyLZ^;1MH8;kQ2OsGanhlhmUb zT^O^GzxyG6)7WPW_o+9v4_7fd@~Ba0%9FzWR489Kicrmw81FUPk+J!e<3?OFDrU@q zrb$9sCUE1dPaHG)DmBxEW*pJ3DbDOgHt-lknQ8xt#tRg_r)!ba&Fc0dHrS>0+CCKi;@8(*-Eo@}t$*22F%{ zB6ij`*1G(Z;R9#{Y%<+_(x}O~LKlB<)uT*Zs6AbDFb83l$xH_r=3g)hFw?frymci0 zM=s5LiPkn*3-b^3pA0ShfYwd=y781T4~XuhX zQ?o4eS5amvW|_NYrly(R@?Mt~y;kPU>UWlR1wY>W<9&E$=6uhYnKS2{IWvz--uJ)$ zuK)Zp<)@5y8mc$n)lVtaN{6I@x4!beda|9@)Z*#IlglP}KTtNId8t=FetW8HLD}50 z4img4)SD1!mPgpaK8k=f5jty!3U1Q#kqI*=j~@BRgz4jEOemQ&wo9n~`aRVpk|92c zuv40q5q0X=QSVNXU0>P+n%g3D+%#yfOLi*ndOpbU%?Mk?Ys|4YL`CRhSgw3@?+;as zK05{4!4Z+@ph%>9mOvPskI<7#pqA`!hEes?9;E@! zS+!~e36|4DsU{fu$5ZN``t?uLO}J^bEl7-kACb+&QJ^~7F3Q`2hg)KyzIXw$phZXB z_&w;MA6%#!>)-Ps2m(6VskC}XMZqE&gC+UtN?eN2^rf23aVmJzEfjv=$) zNE$EIK&#{GK4=h0;}xJ|j$>7)NE$RdQj8F(NXK~Th)5U(gCltu`$yWUTeY%eWkmTo=5RugdDW`Fje_n_ihP^EW3WV8PffAt&~Lyy)T1fRd~m_c z(c>nxBJ&XXK$&@B^-1-j-&N9y;9d$9=%iIwQkzjf-TsE zH=wIto`)0uaU?AmpFPxs<+zcj`slr9)Lgg_sc#Iz`8^kDJHGfndMwCnt;;*AcJOng zt$1F9-t%u2YMcK=O4D0NZtjITb(YMWV4ZLbB{&zUw-&0FMAdkHQ2le*VCHBvZehBl z5CZl7vnolQ)9RdxgEQD9Hv+zhwB4B9S}!=K9)aj6VQr0K*7$I;&WU*Q&X0dQr6ntRwc1c(Bjx1WEe(MKlnf+GW@) zGVG1g)t6Kjd?oz9^x*$>E&h9jKN1uFy$=2@^r+6zLVxs)3I{}7UJCbVuWxbGAzByD zgIFwNp{hNEy7H}hMzzs#S5=5Dvt45diKcl_A$s>E)lDT+MH}1vh2E+&w^=#K&ps1P zyF}NViI8Z~1jL}J2+_y?r6v+0j)e*msLCR5oPV;Wt=TQYiAXl^d$=qDc17x}?W(

gaIwq>xPA?CmoLnX%T|wnntqFI-V$b-OF-3_KrgQ+ctflv-M0PBa0#K(6nJQCnOf zn;js!@inydd#EPF*`o-(`x-8qomAS|R{pe?`an=OyHHu|(2vkRZXu11vQ_q|>vz&_ zp+&yx9?fxt^u=?~j7BQ%UY%FaFouo0Z~YkT78>^nL8TXU zRwFo~D}O*^``~r;cW4*Gh9)e=VQ5sa9(F?&LAq3=I4dAHhHZK8|EQ)q{XZ%f21%1b z_a>T5QK*Zf8AQx$*cUGycT=tPlPWea-Z5-owE9Uc@Ogqr0?pYm`r;-Pt3UWjU4_SD z+>FfgF>GW?sa+6q&}?LEzo0qaj4xzlHpK8s-w-28zbl4U`3@3wNI*3bdYYFFI__6o z-bh6{wLwq(6@v(TqxH283vqdu$FM!=aU1Q)uXZj!374OQi}KT30Ys7O>%!kvBz%qx z(VqCn)@1mTFhl@k2nZ1Ln;L;n=6J({h=Zpt zen)i-sKqlYR#pxIAX7^gHXxg#)BeCE*y#`SmsmrqsHcoqHer|Pt-3(SVCvAl@hq=r^l6HB=58?J&nst*0b33uSpf;#HL zJLG})y@D9^t)r(nx)Hj(HPq9y0UD|cL?z4WE8%m9`LL|cWyQ)gSH=2ylLGO=Kqa!# zn))1dj@A^;8?CAP<6LX1QC)ZiATEyA6hy^oUoZGhhc|{#AwP~6QBE93HiP3hRKhn3 zm2%?r%S|8~CdG*>p5Sb2uU+w|5d}-*Y{khj*w{f6(iA$wOL4ZX)4CG`2UD4Gyhx{} z_=iQsIVI1aKWi+oaHKe?M(PM(=;9|0c$rz_XqmON{h8K4+k9b$&qqWYXjY?en^cUS z8Np!OcBk&;2Oa&a?woLpn&}t(prtykxB5W~IOiN7Z!adc6@T2dD!d__R`4Gb0%J?~ zA+9Q^5xl3sC!U5$dFikw5DhKjIYRQ%3!1=vSol&C$Wc-HLKAo#A{;HL4!q(u4^q!~ z8YFCLr)bp_5@AF1}(6$qbFV5j>b`DjCLST(j89J^#y7Sadq|+F};agK% zY||hrq1ZT8Ukt~HmSSTyhHCNenMOXx$EbNkjBQjKh*n8@MSF}H^4h?&>S=*pD6nNN zSS%sfg#`OAwV4rZm1QsLJNXcd7MTGTx&f|NhXrfDV4ZbgVF_XF7pxmKu)Y_p{cczR z+RF-qp=koI<3t9zsrZ<-H5ZZ-FitFDp&-H0oK;V{8K6@mp#X}cYDfZW zBgXHJ+TSCg7tD~_68Bmhsc_rW6W+eA2{9A(H&KuWD-y(XJS*)TQGA$tOPa+RMj!-d zn2bRG7)bX^~QNP!ZOuKA5R5#f0!;fo&xtnOlJA1U`mkuApcgSuF z#BoD?y#&1BbZ1W>GDh_id4|0c9WzXUD}*HSj);d*qE-k@bl9Voi7b|Pq7%(!k4SsS z9)&qA3u+D9Bmd59kCeZT!`uN3LJ&v9x-JXt9Xy=KMoB$X^-DH9tzcmyFUTiRK+Hib zPvixOZ?qtvOq3kNhQyjVh*um`;u2;juBPqzekuJ}uucgUz7f{PjAh@Sf6svS{rMFK zl>>_dT)&5CtR!-nm8cJI!o7C$B)42clO($vk_~s5M|&i#u~bJV%2I993wrs@B5c`r zkHx$Q?z{EcUg&qaB*}JbU2lkh>?F<^sV@5G-nglB)bUnqu+&lE^<5B%PgJjHeX0-q zie~6o0X(cn_rdj29%1pBp2U+rE0Hy4RbQA4&m_sJemaR)H9lzX%KP-Sh=iNvm#KF{ znpPmK=emA6NtPDUka|C@#}~pdz&DDc7bUUIOivP>DZw_mtu^g)APHRrsmxgSVP%zh z8%LE~*xO0$!mc2OsEnWPatm7PE(4$te&N!p@&T|x0VM0=&#GAXGfB@L1RvqEDq}D# zR8&yi4Xpb6A+P~DCu?O<2`Wx^9SocGBg0?;?ajbw?JZX|P1=_LPQ z6h>o43dc*>hU2AC$*j;}9=)oqppnUX+HB~qV@8A5eFJf9C@(V?O-?qAlPGI+GApa? z9iOgXcF z0dzN`Ff>IL!MEce4vJGGaf*ek=tEOj(VrO)8=+l_%ZKS^ z<3-&qa|scp*2f=$U*V+`(R7`{nvM_B^dDcxJXR$_p{8#kd51LJhGd?au2V$Qk%l}N zz8-0Ayn#aT|6jDod}JiEFWP z8d&_?njojb4=GnR6=THd!mh-F-2*#R1crRSO@%1SLSeVKHaiQloA1W1q&7QhBJ7G( zxo}$J!D-@jXrn6iv(q8mQYoCa)#k+K6mFc>xH$RRJ4Q`r>wYs}v^pY;4!Sd{`fUbu zQn(R~nF%TC3bWA5Co3;3!a)jmz|=<=%vU;x@Suy6V+g4U_DP*IqAcxb;L+dc<8e6J zFFy)9Nx|8iJ^dJ(uC^Fzqj6H9y6fX`$2T-pn&ZUA>+Z8)7!pmJ5159sYX4*v6ikb* z)G~EemobxyXUr%w9ZQ;0t?As<<_I%G-N6XAhVKg0Q)ffIg%Bp}Ds7{0e1%(q^10Bs znZriJGZn|4!KvcVg6F_47?&z*`PLjrRa1y-YZy66d*smAH!Pr$!nbSkanaq2m0 zVf9%?XxOh*_E@u?gypc-9cYstH4oy{S|W}y0?n6+OcWKCrHb!alIq-wse=OhsR!(V z`H+n>Mq`Ev>15q7S=HAi3!o_`nMqF0+?{bl{?vu+jD*x^l0njU!2~Y>14>S*h97VT zMV{@4RPt=9h2FXl-*8rohpBAcU=bX4PI2AEPzF(H;;|yCjxNSj2c+RUPPuPHniDxy zhdd37p?{j~__bJ-#*S!I8atwbG!AqM()84kkPVNfxtvI=dnvL1xp#p2QbWJmrjhH(b0}E2C|E;{IiKs#g1=t)4D5mS zX|ks=mqA;F=Qhum;=bu{n#4$Z^`E5}2JKB_@6hvE*a6jPF7E)}<4EBS=PEG|GE>u7 zu?{~66BX!bWwPynKX4%M)B+z4wXJQjT`iaq<%V>2abJ2(>-|TX_zI*YUxBX= zmqR{5k;(oojm`7bG*Qier@12h{=$Ibw7!Vy60Xro%s-4t=Y-lQdn2m_`lfqgP$F%C z3*$)-j5lr2L#<}HX}c7e&bhR{We}!TQfat)-i7?63)!jOJctyvwRh7%oLkiG$aK+d z1f?|Ep>&Gc4AY_9zpjEWoXY**)$l6(GhOW0`Km88^jGROu@10>#s$OA>7>WXTNl5A zCG(|(!knMeS(hM`yfADhhR$~uS-rw*11EuEb#m4>8)&moLwyfOoGx^#Yq zv=o`o&}KPK{|sHd9u3s)*>%-aqPD7$x^V^We@Aq6Y2iL$LE`Q85br*m5PhoxlHhb# zR>hNovDXuWwD1=f#!Ux?&RPd!pg{(QJ{4VA{qC&8h3bvDCrNwN&7ifRZZe=6L60`P zV^BRw@;JY(!ilgsvozHH7NiZZs?COB3*o|OOFdpA2 z&L5EB)P`{x66Y`91hKyE<@(Sjv@;7c{-QB`GQ(~@?Uv6Sin!HKxPlB1g=;4Ym$?B) zy|NkJ^%%Mt-iLk}qH3J3e2q{7&5bA!C38-_j%nBRdifhL9(H7qk+Zx{ErQH(y82BB zmu%(X49->_;IW4HF)XLkt#>n=E)uQ@?PWLG@lYodJ7Z5&-f_;@Z9%#0LUGxP^%=6u z>qj`U&c@-0puK3A$&;oU>aCTyok_~{oU}Guar^6-wB&8D3i@R7r1|#9bU>Bv(ib(X z(Qo`81_UFpn&!||Z5Cz99G1Ne(_nfg@71PcvWuLb$u1J#Xqz=fZ+!>1S*uYb`_+La z_jG3~9av&dOnvlS=nwBp={v$mW^&7jMxiB;M+~MnU-$M*3wPVq+#87i`l9h8^Ft1y!UIGA`3eD-lSHb8s2aUis{n;X?&_=YKbF4!qD*)dief)x1GP4oyIe;7}Se(L7% z95)2)f`Gvq7R8=zB7LE_rMuI3pmkt7bQup-$$8*pkn@Pn_OwGMj=;B0JM_&_+`{B! zOWcxKb>&iG2p?MH5)`(0HH;C!~Yt+UyX#4(t#dfA z56NNJFSAj1nrZ*D(6Vkk7TFdwZJ{skgXWNw!>+9IEc%{=98#h7eqTygyin@c99GPb z9KO}(UW43ddk*`vMWfP*NIYBrY|IppTBLQO#=_h@9|SMaWCr$f(U2)sB) zRB3+Io%4{a;H4b)Q5ySzx$oC<*hk?Tc@V8HT!3z{E60`kzNZWMz=0(u-A4UwMVjL` zpTOOJLoZ`EfHkCY zc=&{Pa+K04R}594lyM>(?{*L_&ow2aCX(=sZTHDOh*rzS*Sh3!t$()1d}{jbvq zMCeAXm9N^UKfDJ2_1j3@m&tlRmrotkr`#*b>-^8n&t4e-M_wn)1C1ub^Ag}IxsLe? z`~f5F_ldX6*ZN$VuluWJ`~bU^NJ%TYvR4G=v4+9nR)S0i5gtbOpUv>>9D&B`bmP)$TQU5>#LN6Bg*vtJDjSnnza4KMAR4j$V~>mag`osm-!QK#x2&VM*8m zy3{-HeqS_<2Vs$v&dXzKxI&=tjiBb`x!tba zn8&wkVOpO4vqCk8bxuNiQ@%>FH;<1-1OPp8NIfGSzR0uDbsL1UbKYOi7!5xPz%}9g zyKu%gg1hF@I+u^@N{)o!YQ8@0Z^T)S<|D!{W_VTOMn-c5C-R+E!_T}!b%K7Zs;IG1qI|r1 zU{RoH^pNPn2r%}+F|_yOIa=!C`wdC1G^1ugX7fDR5rj;D&8S{jE$$+{);sb_u|a zngG>z1E5_6UX*9K=jxb1!-hC4_iUnXV{^*AUEN|tPD0%jk@0~dgKtmX#Q5~&O^jXM zhCOQz(@l{V+DdbLC3&H@mPqbgAuyAtCu6`$BQB?D&8Xa}nn)3a6_#V9^XTa0 z_-AB0<0|Pl9sg9#Y;T0()w*61JbG0f3O8;jJO{cMX-NJws2A@;qNRlPAy`6YA*h$^ zLvpC5r))uJ;klm+IhHk@3t>XUg(=peWiLJL5hFmqWg5fPL$3NU7si+Sw@E=FvW@Eb$jd~}6YS@&w)CZ!C zC(!^odvH`n<)W03h*(0Sa@1YKTU32-5pQ~6+7Z~?Hto%p-i2E_6_u%dZ#MPF#x7Y< zyfFqcdXulf3v*lJjcDl8n=C!PHST2G2dTZ?+}oJm>||QqYt%+Mz=#}C;t~*ZK1*ZA z#K-FiX#7`-Fvx+8zf9+3cwGQCiZt(wG#f>ljqcJM{R`3@bbzrm8%3J$L>d<+%^dt8 z;vftA*u0o*EP@t&*pCMEVK3OO4|_p;qp=R?<2E*_eg5~@BsszCiL&P4tKe!&ir<8Og9n0OyHxD?~bcBlvkNT^4L)!Q?Zkd(PZC zCzzd_rQ0jg2`C0Di@PGB0aSQL$ zumIZWYPN8FRJcA`z)3ee(_%Knv6TNLH#@k1-Rz25 ze2I$OEb1wBuzanrDiBZmo};7zrgN#%4QKn^aM&H7FqFq2*d@lh_~Z`E5G=P2{JPY5 zPhF?tSolsl@SSu3y!x`kg}&@??UH-xH<&gLuQ;h*{>*eOYG2I=aHR4ERbucO;gg&$TN^vd!2I=j`&H7I{y*$$LXs z{@}s#W-XSdMPB@jb-{2}j|O-z9(&ze-R~-CL4QU%bS$V}&6z?Fmix5GjjzjB8=nBa zlH4cVo1UP7(wYtzPadQqOvzth^fv zi;Z%iidYJ;0jEsn6&byB=1QZ!o?m42Au&m1dI_+biWiJ9j$!t~*`K}AAAC5i!&fe8 zzVwjh>sr$6wfE^~CkbE?$HevY@i7?8(g`WXPh&h*s->{zY#|W3Bc~<$j5gN81BI0P z#;y?1c-?7450B; z#49I31P_arO+{0_jitc1tVgf`3Xw3)7z+ovA8Mb7afSy4-&l}+?t=XI7X-QH0Ao@1 zi737UXiVHNc}!XjpfSNxhcp<j4nxakv+=iuS!2h12Axh&TxE7$S~9UF+YxN~WMj1bU*- z8G&MEb;?2`!%v!V#Cft%@%f+y<<};F=>(6eN6CrT~0p!7;)jfZjC$3hxF$ zLgPoc(^g|9&QBj%VO&8R7P>ysb4JTC>J$R1zcDPQwHArsi|m5GEPP+A$@d?%_!0#P z{x(wpzOvvS3&5V50Q>F+z=AIl!58W0S7ZJXPxKywpVG!h>UV}^!EcM;x9x&A z(KlYi0mDyh)*6ux{cJj<=5SMUlG@760bg0_RH4Q%^4+M@??%lc<25}TYs+oy)7^qU z6pi}uORYX|@Hc~aN$Ry^2x|>KoWb7`k>n|NNdlg!B}s|i{h|?zcfP6DP%=ciu~mrQ zbSG~5f3=B+NU(=|QP1m_U<2w#=@YtSgb}a(%Z&r7L|=T#h*OgY(PJKlR~Tn-E9C6M zCF#SZA$q|pMi2Fei13@c2my75)|`h+B7bvT{f6uy00DR^!ktBUaR+OilNnJP#NH1S z0sBD+XVx2Ut4kvKKb@lEwj^tVBjwnFO@gEx>ruHC<72Xs@<|RFT8<1)I>R|M=NuUp z43fyOU=T-!PYkt3hE*6DCMri%sBN2!6R>iqd7W2>>dyY^b^N>&YnIB#pw?iX0;ipS++a3kIDJ zn0S}X(D=Vx&;T;eox&3z#Phv(jVyJ_$y0sK4Jldjk71m2Ia7=GPCIWzAn&tNe_CY} z0=|(g`M{lZ^;^jE`qK?C^-P@-T}H!3#g(}YV8Afv77T)i^U3i2!yN;5{4`#Gta#s8 z0@1_y{!z!_d@OwbaM^=7i0N3kw-EPm5cB?R$}z*&w!C9F6c6WI40kBPHb23lTPf8L z9vH6e*I0)Oat}dP14P0`;~Vgt(*A3iyZZ1d`v*=vT}47v+<&1Dj{DGPMvDv2dL#W5 zOj?i-Npq_b*d6RGS(XPzQo4nDShS>BWTi{B>ej}{TxM1 z^AP=PruvQa^BMgd#h;m_K2wS(k9%a+)NwQDe;zXlqhLa}0`qc9{KGuej(!QOfPo4a zq<{emW=;qtl2f{PpE20dt%zo=beU~I;4qYv*6Gn%+JE_fzrY(F-`U^34vwZT^ z)X~OR6x^#W7Vn^9`~4B5<^OFg__*O+k1976>B1S%Q6D{Q#9Ph_&N=3z&Qv8FF+!BO z>PCOYjb2wCHR=KZ&<9r+j^Y_=vk@#vfL?I|O?xAqbIj;r375ilRLI|S=?_qg@p=uu z+r?@$!YNh*C*r{4Mwlf>h`R}5M%AX{MrWn^xzT30Xua#vH(3se%o9e4WscC#68cB= zjuS>i-KAJaBNt-QUr6#T{(m6O|8S1W@V~J$m+O$vjd>WbxdeUGjhPpHmbGd1Nn;Lv zJ5%w65vcV^qqXX$x1TglHDX=;64lN8m43KII#z!Dg>kg^2`d)Se~4vz#o!P9*EME% z9RAS%v0+}JANrpp%n8>izNm_kL`Yv>nt`eKLmyk2ZPW0FK8rEW;Qe-!zDqC*@Y1wN7skz; zO#GqSxMnI|H#6zlo;e5a8<}(g%X|gznV597$G#eAanjN^vy1BJbzfj|<2s$)dx}>< ziJFRD4)H$2_IC09BvQHzVAjDDkx9o3=7~c5p>3YIbSVCi>*ED)ZlR@rfPU;FabUQU iRb5)c`uHwm2C4cM9evjL4X-R)&l#;$q3&_c$oPMTpiG4T diff --git a/docs-out/_build/doctrees/environment.pickle b/docs-out/_build/doctrees/environment.pickle index 381826a46435bb3b58a0867c1c4f22c596708efa..73cc95323e5747cdd9506eb85884df4a094b5971 100644 GIT binary patch delta 7264 zcmbVRdstP~ws%a0jexNC1{4(J{ZQnsycCcWOp(yAho&Nef(sBmK%ppRnz|7Ro#;q= zQJvE@?IyM=vQjY1%u=wYrj{C(W%%f5Wu~4n=Y%bEzx&7Zd6l^(i=?*Af`$3>DjRCud1{#lzwYUbx5~jDUuy?XR_n$WuXp1^J$=!C z3>#=yYpdMot-wls5Wic?wNl^I zoYyofbzx>7E#FH0a`)R>UN`lP?QavcLM!EPbC*^$$4dH!FVc#wROp4*wb@o`#2Y_p z^Q=_Z_6``t+JSjkMJ`-qYdJaPd0?`T@mB?rXVxV@^j#q!aR71 ze=K*8N#zqm#_&QvGe7NT$CD!m^7+F?K?uJbHJ(wIB!aH;ERF+`M#I{ z@)FCp`bP7w!o&Ele(t<5egt0=8O7&>#qiZ3(f#XXD*yj`dIo#{pZgw&{rjGxVE@~m zbVj&`n}(0%FNJz?-@u1?TDY07@OR)P!w1N{`h_O(c|nmq&j*>(qK-M)l`qaOi6|@2 z=SRc;@wcOj&Jf!k4T}>A>5;m$@Zr2~#8{pdFoti7O5z;>G5k=xBVXh@j8Y_es5{)p zL;U&PVb1(oL@IXVU0BIr0ks2Mu3*y7%9`mTc-Gw|C z6V|t0%ja5jkU{iePrJ89Ch*gv0=P(H+K5;Rd%E}cd?d=&>9V0S7yZvO zLo^SM3*=M72J?jp!=!CPd>qe<8_Bm1ci{1Hp`t7hDzz@f*>z{1)e4pme<*$ce>^0L z0uuK}1Qfw{C3@k9?|_l>z*rF#_!G;WR1+>#W{v&!uGisWjZIgT=s@)Gw*_2*Scz(DsRy$d=Y7R$|gUNGrBDA5Bl?q-6eFV9>e zWx642A@K5DrIcHLZkU?Qm+v<5y%jEc^;EK6zT3=wHhJ^o_clR}UX%R^6D+;p{&L`! zg6gh9xbeydvw2gAGQ9L)Fc4wp)tN)}^cmX(F${OMfVUny^KD6yoj2F!nDx77ACkIy zz?{F7(b^UxH_kNkvA10K#TU)`lDVx)BP0L6)xv)M3g9OmsP3w~8xJbX=00=P=Fb+= z=00=P=2sWIAqoARqTl3Vxx_Vt_a+q`&6|l#xsW`gBw?vur(MQ_<`Lf zJ#G1my`;Kv#Yc+aQ#0uGm1?aYf9zSw)Yq+E4Se+0QtIexUiY#(qt{wGW8KRtkn(j~ zC87J&yss8l*B?}iBXwUWy(iu@^2i!zY`qE2{Kz4*e)Y*2N@dQ5Wz+_1O6itVaHksO zzk^fdooYno+aO=Ryy*ZFq<-+JGJrhZc4{HrqcHyU)@)v!sZ8#9nnEhhjMV@2Op{oc zdB&>)`OZco&bbdoOJTN>?|T)g?Bn_8Uw=Po6B{^e@m6VAl)ISmPPM<3;W zX9M)eSAqcwc}Zr3zIOZTwA2${y&*UUAM@qy2W-XL#Ss3^VzXZJ+6=*e;^koZ#=)nT zne~vS$-qx;ETtHV+GKn2{ zW3wAx_GS+Hhr8cWDz)z_U0(Zc7}gJCcKV(@)Z64!U(-S*7K?;^RJ>Kky!g(xd-FaGn75tD z<};=S@bt4MHSr>n(NE5_jJ|T9W!TASmSK>iETg}iV?>D|Mk->05hcb~hK-zEq#_1a zhOL}h86Za%$;7zIU~*Owb1tv_ew>roZdQY~k_J|;mcvhd?+N+*Px?Eb59%1dLe4dz zBaQ2|bQ}5jkm1#9clV+u^`a*CqSo3gI}vleX6Z$(??u)1q?|Q7qcW6%%-4VF_zURK z^TQ9LAcuSYm|XOVTY$g){v z)hx1T7FjckESW_n-6D6e&;~YpVIq`Z)?NsO9IV<46JP=E-wQJchPFTvK}`#k6Wnfr zN`lH(c#PmiE3C1VkH#pBKS*y0P3MF8qF?Oz!p=}f?YJvdS4v0X#~&yuUV0w_@yYkW zj?ABWAJ!50?uQJ5lKt=y!N>byDZ%&;UH_y5niBBE@ zTM{}SfF%T$15iWY`VnkUst=lQwj*=L(i33dm#$^w(1YMg8Zif<9#4M(HhAzLtS82_ zkKtKml5av|7?~Ik!3Yv09fIiucnC_Ayu^fcam<}p-b&#YZaN#f&WM$tz*41AX2KC( zQX_#^-FCsw&%pr;KZRxF=iH~TlAz!)XiAwL6)m2$-Q~k@4+&C^!2JZ9k3cDbZ5ymo z$z8vBA7!upnmsnzK)Q12)-DsXwH;zf_h>t0LIHXoh4}<)j>0lDw$lL(pHV3bFzYjz zM)1$iKvR5|&tVKPrhE?R1o%13RQx|ahh$>JeL?+DfGfYCZjgS?eF4$LaQ~A0Jf!zX4m^aUA@}^2l+h zCdm8-)+o&m6IRF5KC`caL3tr{1A2LYw>7w_C!m&$zCA$|l!xgw;nB`+_ph7;N5#I} zGnf=l`ocAy0$U~fw+WN4cL&<&1^uw-6d1|tvQw}`sa!W0v*AcJke z;BQUUrSGXtb1}ICatRtcV4jL60+YU@D2*e?dH8S`fH~*7GZSsblEajlmQV=7W5ati z#nE#xle~og0ENoSXsZ`@?Dzr9Dv;!^K+Z>k-SNLxB=cK_iJbM?s+VFf~8X-Ok01pCC=`G~JA*+u({zqp90Uf2Prrix2+{ z4-g#rx%;Sd@ya#IUc@LGfjYMOBG@YD%dztUjK?Dv!A#m`F4D}*#iUCx zUmao%rOQZl`^gOkZCvGGJ?(`{GGPgqA)oZ0yG(;77q4BGr^~z|E3y3wj3(v}S0I(f zM98mn88xi>6&4e8{z?s{;naUqn`*f4-*nG39D9|fnudF>LXoZf0(wJa*+)DQLvcVF z&ArRlDT^AezXo#%ez^v-l;R$&zXln2F&*r?BGholZ&JzecSs=J^xr8M4Ild*#uI#` z!0`_lN7R%*WP}_4fJsE1`hy-*8pdCzlWF+ub*id{zh8$L@;R+_n9)0!60+z|7_T<} z5trYfyl#tSMy2xe9hE4|zX2}fpz;O{A$h3Fcdm{BTeBb$Z+FO3CI1Ea%HwaM;33%l z7etaN+>}wK-K5K+VZ%+BtsF5IOr$3lMrK2FcV?#EqWh|0(=CW0=(t7Qn~x5+>3Nuk z58S2`<>7m`VV(T_K=W|H>QBHO&rgHlo2SFzP5;H*A#YPFTS;nn0V^YT3z&sqEMt!l zyvCF-!lLt{%<9OE&Bt(nz*txde^2tdziL zU{wUQ2DXC0(T=SpXs}~-%1IX5`7v*7oKM$D4fH(R*q^N?r9t*Gm?!O}pWF6q1~F$i zNakk_>~W$VbY!*4PXW$yWGgVshS@2GCK)}VyFGv*nV=IJMR3@OWzc(-hclZ?u*{h) zBItBx6}IxT`%(0?r?9%;xJF>6kvZAtbf2{lPZ(J`S@@aQRDyC7%P~m9S{E_W-Eq!n zCO{F@C%7_@Z6H`Rh&@4IcBiu!;dXac zs9d)S*AHN+2Qw1?Q4i^_(}OJ~s&FuCAhfS}Zya$SV)db9hLTBi%9T&AHP;ln1VcrK&K zj`AJ;gm`NCGCO?8ml^SiC&0CPco*SqAGVC#Ec0b+2>SZ5QswQhuKs>{6+PFRe3(DB z`LUs-a?y|dgCN(RNa3CvE zK@P$*i4oOAraq$Bf?0vm^~c&c(p|U(!f@}?6xfsyW~-tIaz#@o zC8=-=#Nf6NS%KXlY@#w8flh%eN_;F1#H?Y=ptupZB9RTnh^;VCh(c(u-NRUk5{|OQ zH4r01nI|qE&YVf3Za6DcTaI=Wk5hNt(Ma!s^Qktt>aq-ubg3z5%FhETj>0vGPL@V*#n_xCJj-(<nR^K7NG9#;labzjrzm9>2ob0Fc#QPeHPI60OTE1fMkHI}Z} zb8pZqpLblh-)CIKyD7aO3Dae9%${u4#!;UZDeUNZdKoEcb-zCsl5#1N67?&o}pr*(Z**vB8 zj;nQerK>~i5v`SlH%7|@3>d?r$zbdl7E7OfkBnhnN#egR+F(m1WEGMdAhmhS(*k~qm@!iFX=};q_|6X(y&cIrvir* z$sDF&0zs1esn^-1=Pok`S$C07R+nDVsvc5&L3ql;76qpi+z>zyv#}E52$JN(Xj3mg z{oJj)$YH&umvl%EDQ*y+ig2fb!wN1a=$|TO!30V2GR&fS->JSk6~3$bQd-(eTG~U3 OD}|@x=I2w{)9gPdmT&C< delta 7180 zcmb7JdtB93ws&oX!<%ysAfUYDAqawi@>Cw?YZOV%v^4by9uM$C#I8^%ikYPzghDsA zdP~ks*J^H3ziAjN1+&a76|;wqnvcj#!^fnPX6jvgZ#cr8`}y3@{fF;fkG=MK?e+Wp z4)3pbeSf`cb65}r;cL|pp2eoPPNv*^|y|g%6vpJ~u zk}hag2lZ*+|I|ty)V`o^HO)bt`{rG(%t8HJWza11yUBH6o1zssD9@%F+B^s4b>Vw$ zp@Z^XvsGKauvyCx)e(dA?x9DU(I3j@$iW7G{M8|;d`9F@{#~X!Z%B;d zM~08*n-fOybCF3rC1as$gG}82=LBK>7mKB2 zaY=>6!kCuGSmjIq;r?$D|7uzz=5)KwhtT5Kw5q;lFt#!Zny{DTxv8Ky{+ zaCqm?T>iJ1;e8u48{e3mAyasL*l2DU9MYAFWd3yGy>yZ;rAG9Iu)ifbil=6(KQgf@@e6L-rd0@ELqmrpp|khd9bVK9@<@(#&?Yf!^eR6@%AD8r~>P#TETqD@IYD7 z;><`{RZ*p#BgPRgf_o0}Vs)vsFBa#!GB^J8@ca4f5ko`>p98)o^=OGM}>4jjzhC;nCwF zcv#LK`Qy0}yn1aMH|5&6{k{mE$HV!DxpVoRoCrQ@^kyg%hU&J(^ODitJn_C+{D)By z{4e*t#&2gw=u5`50M8#2p-&nY0sQdj2;MOM2{}Tvw7z}%$XlRI6D!fRnnkQcdue52 zB}Rr;Emoo>G`m=dQK6w&i9&0C7AsL1O&2SRSnU=oktOYrSc$2iofIoE5wweauGPqmbId&Vjt{@I)vPZoY*QL}*8frqH`^-U#~-Tc zsywxD@pK+ms1ARnm<|ssREJ+H`Ku)K_e=jJ7n|nz<6T#BK@Y1w zq!=&nmke%PWx}>-aOZn>nDlWgxAv0i##NsxMp&)?yQ|e&KlbD+lButM>M7tSHkDIX z*YGwTsRys47~8msugnkCE7rd#2|cuSk6Qe);WM>3Q2({ktAEeL6KlP(?KXJxgZs_; zwP$B570bqzz$@MD;SUZMgp>a>%PzW#!K=H!C9VFa7!UCL_+D0lu=>`m0|_iT*;98x#8adt3d~;>4fc zQKBuc*8r69Lnjy09esi?%2y{OzCkA}%1_kSz4@+KnDxBBT#yTX>`5bU-|LKbDqtXg z|53AE`!)qfDtyc9{RP*J&su8MW11%eubf&=SA96||L$}?ds?Jk|1O!GJxyh@Lw{Zp zdi{GB)xzF#O^NS5ViITYrWQZE63X25Pj>uGsnmU-ba~we@z^kgx#&B0Qje2OeQhh1 zSu8SkQvq8l%K4Hpv3%y9>HP8v71e<~bo}KNDsPdW)Jj5c+xv~;hSiG5e6YD0Jo#_+ zX8poG>e|aI!XNj^iQdkxwjdQp>lQImU7>)g~n;d6s#??r9s zMb-DDyfqi2+NgZcf9m)h=s|SuTndfDpdUv=kv{LoQ=w4Ol5K!61K3(DUa&6FAm;wu z#u(g{1R-e2g+Q!*159{mB3-ntCVNtnKmULKmyNAo2=yYR)GaUR++UwU*& z=?MJnV^#p_VKpsKa9(aV{vpuk!VC=`Ris0jq;VFWNpFoL0 znwo6FOBW%OPq~(e&mIJ45_<22Wd!!UP)p$ZDQr}#51VkF2MfUR<6z*IuTRI2ec($P z!}mc0p8g7)aNj=IK#T`JgIClRs|k(qw8gj|hLRv_Kg=S){ZOXlWhSgoV*$MCP7c3# z+uP6;BUXJ5%az7b6AlfQ8X3I$t`Bw|0e39^0#=ZnAHIOq1VslxQ_A$fXbqy{t{i~- zNsx08W)eJi5XuRh55XFh+zrp|rtCFbcf)2U7_UtFwadi3*bb?rd$=9)p#(z@gNwO6{l#H(rNOTy+}aaO^QKD)w;`=AVaQ*ggOT zV#q(h8Q(ev;k5JMF{mNP{|Bs9njI#rNvCt>T?2!%Lh1$#4unvLbJLDP9c}vVI8{&v z(`mxPo!#c&H~}7teWj-}IYHot#*^TzWWSg&`)0SJO~KF)OHYE4tgbi-%aqDZ6E+8s zD{Vi6zw%t_P5O>n(uS7rWJV8t2gO9Cp8|`s^u-C=J0Vf&pFag2itB<|Hz7;}l!SSw z!Hc%cJ`D>9cAbWK1i@z{wfYPcs?+_=m@}A8-_=26qjI+|gNoVO=+pzU4U2+@7 zeGk=YLxdU6WYC6f(GcNC)#dN0O>LOn0R;q29k5XOGYqp%k(b7yWIQ1jJkjz)cV?2! zSayIi(;5eZ@n~$1ra1fq%pofY=b%_w8R@VRfF0++tQ^Via^!p>gx_nGoFA#*ZCL*! z%u$;sh(sk}*m)RC{0Zl2O4+dOJQOMMR5X(Kxg>~k1XKGH-EA9o`~>6FNwdsox(mLz zoW6;$`~r;@8$Nac9wIn+p*z$}z*!kziJcc=EFQcB zX3{=$iDsq^vo3>81+kXWWu&_O2!U0#huu29rEzfcyR0T(28&UODcK%3K^t3 z{#SCwickIuV+lT0;Bf=S5Huf;*KMiHs8lZ8Q%OSWE$|@&Rkvse$)K*>yE+DJn*y15w?jsi z{X1Bd#ea!{$6)*KkVsqMw)Aq`ZMrO0Y`hKglp*GWne^ns#OaXSotbHO=)PL9`3?*x z=(t1OTZ-;?>3OK(Lw6}64L`gK>kaa=GSCNWK8FB2{~*LZHwy-A{!bPF+U7R4n$+$C zwv^y+!0ZIMj6F{9cg8FP0ez*)i+$O%M8)=F&k^h{f)QQ6;z%_FGvVT%aP`miUQ z<+uM<+!e$|VEb}vlHBFs)RiC$w);xWEI&4xHq`pDSp*$^tcqZ6f5r)}_GcRj*7&n$ z2+RQ#y9M72V8zOGn=t(lmIpE;@t+8k_BsREa-xa{uttL01K1{lhJjRl3x)-;=LvQM zNzK8*lrIZnFjc{V!6B@|AU!_ggAJ_|eRBw#NdiMCD60pfAjOXS$p z80M_J80?FtPD)bo3osnF#mEZmh+z}e#-ZpH#gfG5Vt<@6gc%ff7_Q1>Avo+s=r2Su zbk>d`tV{`09Deo3#5fj&D`S~AY1GHEVs+$5U-38%z_*&{J+L8|(YFH@#IZ_(Z{yfv zr8Kt7FPAMeXqx{>??*2WW$sEg;eW`wpAZ&wi)WL_%#3(8gW#=rwt&DpLBi4mmPypx z2`mE&@O%OrLojq0U6}%`QP8d+JdsT$=F&tqj$lV3dw{?riOn_0-@Yolj$fZ7O?;6= zfk{ENucP6d@nAAb!-ixQNPFK*W{(mC4QJI#^C@3^^jk_n+;%APRFg(pSVuk4M*M(g zn1@Xxs7R7s>x(&N%J`kP==I?D5zIu!yi(XgXDMyK)zMVlw{?1DZBJqDBs`Hq-BN&) zQ`sVH{{fuf1)P>jSM1fl(kowRTDRSoeZ{*ey&#FLE7F)7?OB&beOiFOrBM?WU{yL> zp?uipE4~T3e2Cux-gv5oUe4!bFoRNft7r7mQ_|{we=fk|8Ek@5e8(4ehq3|a^&t%F zzEB0YJd*}Bd7jA@Dz*209m8w93UsGvttohGq)dS4D3(kca!0XL`s{mr6bsH0|1;4B znELc7o?JZHUeUO^Q9CWZ-!=sH=@X;A;zD{!4Sx5ec$iGkXUJs*o>`KLQ!r6L2^JA# z$)8bQ>t(0mo*gNDvzPRx9#Y(`ES(Zy!`li5W=o2GSr*KP2(sj>^DJ}ESepAgyp>XW zFX^W}r1*}oWW_@YIu*F*Nahd)69}^8kG|eMJx`hA?>I$1S$%p*t9wZCHDO7^Rs|;& z+!8>xXo4(x8Rk;G e?^Qp53g1b5mRZ diff --git a/docs-out/_build/html/PyCTBN.PyCTBN.estimators.html b/docs-out/_build/html/PyCTBN.PyCTBN.estimators.html index a316357..b76ff0c 100644 --- a/docs-out/_build/html/PyCTBN.PyCTBN.estimators.html +++ b/docs-out/_build/html/PyCTBN.PyCTBN.estimators.html @@ -400,25 +400,23 @@ in the graph _net_g

  • exp_test_alfa (float) – the significance level for the exponential Hp test

  • chi_test_alfa (float) – the significance level for the chi Hp test

  • known_edges (List) – the prior known edges in the net structure if present

  • +
  • thumb_threshold (int) – the threshold value to consider a valid independence test

  • -
    Param
    -

    thumb_threshold: the threshold value to consider a valid independence test

    -
    -
    _nodes
    -

    the nodes labels

    +
    _nodes
    +

    the nodes labels

    -
    _nodes_vals
    -

    the nodes cardinalities

    +
    _nodes_vals
    +

    the nodes cardinalities

    -
    _nodes_indxs
    -

    the nodes indexes

    +
    _nodes_indxs
    +

    the nodes indexes

    -
    _complete_graph
    -

    the complete directed graph built using the nodes labels in _nodes

    +
    _complete_graph
    +

    the complete directed graph built using the nodes labels in _nodes

    -
    _cache
    -

    the Cache object

    +
    _cache
    +

    the Cache object

    diff --git a/docs-out/_build/html/searchindex.js b/docs-out/_build/html/searchindex.js index e239f42..c34509d 100644 --- a/docs-out/_build/html/searchindex.js +++ b/docs-out/_build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({docnames:["PyCTBN","PyCTBN.PyCTBN","PyCTBN.PyCTBN.estimators","PyCTBN.PyCTBN.optimizers","PyCTBN.PyCTBN.structure_graph","PyCTBN.PyCTBN.utility","PyCTBN.tests","PyCTBN.tests.estimators","PyCTBN.tests.optimizers","PyCTBN.tests.structure_graph","PyCTBN.tests.utility","basic_main","examples","index","modules","setup"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":3,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,sphinx:56},filenames:["PyCTBN.rst","PyCTBN.PyCTBN.rst","PyCTBN.PyCTBN.estimators.rst","PyCTBN.PyCTBN.optimizers.rst","PyCTBN.PyCTBN.structure_graph.rst","PyCTBN.PyCTBN.utility.rst","PyCTBN.tests.rst","PyCTBN.tests.estimators.rst","PyCTBN.tests.optimizers.rst","PyCTBN.tests.structure_graph.rst","PyCTBN.tests.utility.rst","basic_main.rst","examples.rst","index.rst","modules.rst","setup.rst"],objects:{"":{PyCTBN:[0,0,0,"-"]},"PyCTBN.PyCTBN":{estimators:[2,0,0,"-"],optimizers:[3,0,0,"-"],structure_graph:[4,0,0,"-"],utility:[5,0,0,"-"]},"PyCTBN.PyCTBN.estimators":{fam_score_calculator:[2,0,0,"-"],parameters_estimator:[2,0,0,"-"],structure_constraint_based_estimator:[2,0,0,"-"],structure_estimator:[2,0,0,"-"],structure_score_based_estimator:[2,0,0,"-"]},"PyCTBN.PyCTBN.estimators.fam_score_calculator":{FamScoreCalculator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.fam_score_calculator.FamScoreCalculator":{get_fam_score:[2,2,1,""],marginal_likelihood_q:[2,2,1,""],marginal_likelihood_theta:[2,2,1,""],single_cim_xu_marginal_likelihood_q:[2,2,1,""],single_cim_xu_marginal_likelihood_theta:[2,2,1,""],single_internal_cim_xxu_marginal_likelihood_theta:[2,2,1,""],variable_cim_xu_marginal_likelihood_q:[2,2,1,""],variable_cim_xu_marginal_likelihood_theta:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator":{ParametersEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator.ParametersEstimator":{compute_parameters_for_node:[2,2,1,""],compute_state_res_time_for_node:[2,2,1,""],compute_state_transitions_for_a_node:[2,2,1,""],fast_init:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator":{StructureConstraintBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator":{complete_test:[2,2,1,""],compute_thumb_value:[2,2,1,""],ctpc_algorithm:[2,2,1,""],estimate_structure:[2,2,1,""],independence_test:[2,2,1,""],one_iteration_of_CTPC_algorithm:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator":{StructureEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator":{adjacency_matrix:[2,2,1,""],build_complete_graph:[2,2,1,""],build_removable_edges_matrix:[2,2,1,""],estimate_structure:[2,2,1,""],generate_possible_sub_sets_of_size:[2,2,1,""],save_plot_estimated_structure_graph:[2,2,1,""],save_results:[2,2,1,""],spurious_edges:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator":{StructureScoreBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator.StructureScoreBasedEstimator":{estimate_parents:[2,2,1,""],estimate_structure:[2,2,1,""],get_score_from_graph:[2,2,1,""]},"PyCTBN.PyCTBN.optimizers":{constraint_based_optimizer:[3,0,0,"-"],hill_climbing_search:[3,0,0,"-"],optimizer:[3,0,0,"-"],tabu_search:[3,0,0,"-"]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer":{ConstraintBasedOptimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer.ConstraintBasedOptimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search":{HillClimbing:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search.HillClimbing":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer":{Optimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer.Optimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search":{TabuSearch:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search.TabuSearch":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.structure_graph":{conditional_intensity_matrix:[4,0,0,"-"],network_graph:[4,0,0,"-"],sample_path:[4,0,0,"-"],set_of_cims:[4,0,0,"-"],structure:[4,0,0,"-"],trajectory:[4,0,0,"-"]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix":{ConditionalIntensityMatrix:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix":{cim:[4,2,1,""],compute_cim_coefficients:[4,2,1,""],state_residence_times:[4,2,1,""],state_transition_matrix:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph":{NetworkGraph:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph":{add_edges:[4,2,1,""],add_nodes:[4,2,1,""],build_p_comb_structure_for_a_node:[4,2,1,""],build_time_columns_filtering_for_a_node:[4,2,1,""],build_time_scalar_indexing_structure_for_a_node:[4,2,1,""],build_transition_filtering_for_a_node:[4,2,1,""],build_transition_scalar_indexing_structure_for_a_node:[4,2,1,""],clear_indexing_filtering_structures:[4,2,1,""],edges:[4,2,1,""],fast_init:[4,2,1,""],get_node_indx:[4,2,1,""],get_ordered_by_indx_set_of_parents:[4,2,1,""],get_parents_by_id:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],has_edge:[4,2,1,""],nodes:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_values:[4,2,1,""],p_combs:[4,2,1,""],remove_edges:[4,2,1,""],remove_node:[4,2,1,""],time_filtering:[4,2,1,""],time_scalar_indexing_strucure:[4,2,1,""],transition_filtering:[4,2,1,""],transition_scalar_indexing_structure:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path":{SamplePath:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath":{build_structure:[4,2,1,""],build_trajectories:[4,2,1,""],clear_memory:[4,2,1,""],has_prior_net_structure:[4,2,1,""],structure:[4,2,1,""],total_variables_count:[4,2,1,""],trajectories:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims":{SetOfCims:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims":{actual_cims:[4,2,1,""],build_cims:[4,2,1,""],build_times_and_transitions_structures:[4,2,1,""],filter_cims_with_mask:[4,2,1,""],get_cims_number:[4,2,1,""],p_combs:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.structure":{Structure:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.structure.Structure":{add_edge:[4,2,1,""],clean_structure_edges:[4,2,1,""],contains_edge:[4,2,1,""],edges:[4,2,1,""],get_node_id:[4,2,1,""],get_node_indx:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_labels:[4,2,1,""],nodes_values:[4,2,1,""],remove_edge:[4,2,1,""],remove_node:[4,2,1,""],total_variables_number:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory":{Trajectory:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory.Trajectory":{complete_trajectory:[4,2,1,""],size:[4,2,1,""],times:[4,2,1,""],trajectory:[4,2,1,""]},"PyCTBN.PyCTBN.utility":{abstract_importer:[5,0,0,"-"],cache:[5,0,0,"-"],json_importer:[5,0,0,"-"],sample_importer:[5,0,0,"-"]},"PyCTBN.PyCTBN.utility.abstract_importer":{AbstractImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter":{build_list_of_samples_array:[5,2,1,""],build_sorter:[5,2,1,""],clear_concatenated_frame:[5,2,1,""],compute_row_delta_in_all_samples_frames:[5,2,1,""],compute_row_delta_sigle_samples_frame:[5,2,1,""],concatenated_samples:[5,2,1,""],dataset_id:[5,2,1,""],file_path:[5,2,1,""],sorter:[5,2,1,""],structure:[5,2,1,""],variables:[5,2,1,""]},"PyCTBN.PyCTBN.utility.cache":{Cache:[5,1,1,""]},"PyCTBN.PyCTBN.utility.cache.Cache":{clear:[5,2,1,""],find:[5,2,1,""],put:[5,2,1,""]},"PyCTBN.PyCTBN.utility.json_importer":{JsonImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.json_importer.JsonImporter":{build_sorter:[5,2,1,""],clear_data_frame_list:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""],import_sampled_cims:[5,2,1,""],import_structure:[5,2,1,""],import_trajectories:[5,2,1,""],import_variables:[5,2,1,""],normalize_trajectories:[5,2,1,""],one_level_normalizing:[5,2,1,""],read_json_file:[5,2,1,""]},"PyCTBN.PyCTBN.utility.sample_importer":{SampleImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.sample_importer.SampleImporter":{build_sorter:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""]},"PyCTBN.tests":{estimators:[7,0,0,"-"],optimizers:[8,0,0,"-"],structure_graph:[9,0,0,"-"],utility:[10,0,0,"-"]},"PyCTBN.tests.estimators":{test_parameters_estimator:[7,0,0,"-"],test_structure_constraint_based_estimator:[7,0,0,"-"],test_structure_estimator:[7,0,0,"-"],test_structure_score_based_estimator:[7,0,0,"-"]},"PyCTBN.tests.estimators.test_parameters_estimator":{TestParametersEstimatior:[7,1,1,""]},"PyCTBN.tests.estimators.test_parameters_estimator.TestParametersEstimatior":{aux_import_sampled_cims:[7,2,1,""],cim_equality_test:[7,2,1,""],equality_of_cims_of_node:[7,2,1,""],setUpClass:[7,2,1,""],test_compute_parameters_for_node:[7,2,1,""],test_fast_init:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator":{TestStructureConstraintBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator.TestStructureConstraintBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_estimator":{TestStructureEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_estimator.TestStructureEstimator":{setUpClass:[7,2,1,""],test_adjacency_matrix:[7,2,1,""],test_build_complete_graph:[7,2,1,""],test_build_removable_edges_matrix:[7,2,1,""],test_generate_possible_sub_sets_of_size:[7,2,1,""],test_init:[7,2,1,""],test_save_plot_estimated_graph:[7,2,1,""],test_save_results:[7,2,1,""],test_time:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator":{TestStructureScoreBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator.TestStructureScoreBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""],test_structure_monoprocesso:[7,2,1,""]},"PyCTBN.tests.optimizers":{test_hill_climbing_search:[8,0,0,"-"],test_tabu_search:[8,0,0,"-"]},"PyCTBN.tests.optimizers.test_hill_climbing_search":{TestHillClimbingSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_hill_climbing_search.TestHillClimbingSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.optimizers.test_tabu_search":{TestTabuSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_tabu_search.TestTabuSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.structure_graph":{test_cim:[9,0,0,"-"],test_networkgraph:[9,0,0,"-"],test_sample_path:[9,0,0,"-"],test_setofcims:[9,0,0,"-"],test_structure:[9,0,0,"-"],test_trajectory:[9,0,0,"-"]},"PyCTBN.tests.structure_graph.test_cim":{TestConditionalIntensityMatrix:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_cim.TestConditionalIntensityMatrix":{setUpClass:[9,2,1,""],test_compute_cim_coefficients:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph":{TestNetworkGraph:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph.TestNetworkGraph":{aux_build_p_combs_structure:[9,2,1,""],aux_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],aux_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],aux_build_transition_columns_filtering_structure:[9,2,1,""],aux_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_add_edges:[9,2,1,""],test_add_nodes:[9,2,1,""],test_build_p_combs_structure:[9,2,1,""],test_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],test_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],test_build_transition_columns_filtering_structure:[9,2,1,""],test_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],test_fast_init:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_ordered_by_indx_set_of_parents:[9,2,1,""],test_get_parents_by_id:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_sample_path":{TestSamplePath:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_sample_path.TestSamplePath":{setUpClass:[9,2,1,""],test_buid_samplepath_no_concatenated_samples:[9,2,1,""],test_buid_samplepath_no_variables:[9,2,1,""],test_build_saplepath_no_prior_net_structure:[9,2,1,""],test_build_structure:[9,2,1,""],test_build_structure_bad_sorter:[9,2,1,""],test_build_trajectories:[9,2,1,""],test_init:[9,2,1,""],test_init_not_filled_dataframse:[9,2,1,""],test_init_not_initialized_importer:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_setofcims":{TestSetOfCims:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_setofcims.TestSetOfCims":{another_filtering_method:[9,2,1,""],aux_test_build_cims:[9,2,1,""],aux_test_init:[9,2,1,""],build_p_comb_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_build_cims:[9,2,1,""],test_filter_cims_with_mask:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_structure":{TestStructure:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_structure.TestStructure":{setUpClass:[9,2,1,""],test_edges_operations:[9,2,1,""],test_equality:[9,2,1,""],test_get_node_id:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_positional_node_indx:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_trajectory":{TestTrajectory:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_trajectory.TestTrajectory":{setUpClass:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.utility":{test_cache:[10,0,0,"-"],test_json_importer:[10,0,0,"-"],test_sample_importer:[10,0,0,"-"]},"PyCTBN.tests.utility.test_cache":{TestCache:[10,1,1,""]},"PyCTBN.tests.utility.test_cache.TestCache":{test_clear:[10,2,1,""],test_find:[10,2,1,""],test_init:[10,2,1,""],test_put:[10,2,1,""]},"PyCTBN.tests.utility.test_json_importer":{TestJsonImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_json_importer.TestJsonImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_build_sorter:[10,2,1,""],test_clear_concatenated_frame:[10,2,1,""],test_clear_data_frame_list:[10,2,1,""],test_compute_row_delta_in_all_frames:[10,2,1,""],test_compute_row_delta_in_all_frames_not_init_sorter:[10,2,1,""],test_compute_row_delta_single_samples_frame:[10,2,1,""],test_dataset_id:[10,2,1,""],test_file_path:[10,2,1,""],test_import_data:[10,2,1,""],test_import_sampled_cims:[10,2,1,""],test_import_structure:[10,2,1,""],test_import_variables:[10,2,1,""],test_init:[10,2,1,""],test_normalize_trajectories:[10,2,1,""],test_normalize_trajectories_wrong_indx:[10,2,1,""],test_normalize_trajectories_wrong_key:[10,2,1,""],test_read_json_file_found:[10,2,1,""],test_read_json_file_not_found:[10,2,1,""]},"PyCTBN.tests.utility.test_sample_importer":{TestSampleImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_sample_importer.TestSampleImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_init:[10,2,1,""],test_order:[10,2,1,""]},PyCTBN:{PyCTBN:[1,0,0,"-"],tests:[6,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method"},terms:{"abstract":[2,3,4,5,12],"boolean":[2,4],"case":[7,8,9,10],"class":[2,3,4,5,7,8,9,10,12],"default":[2,3],"float":2,"function":2,"import":[4,5,13,14],"int":[2,3,4,5],"null":2,"return":[2,3,4,5,9,12],"static":[2,4],"super":12,"true":[2,12],"var":12,HAS:5,Has:[2,4],NOT:2,The:[2,4,5,12],Use:[2,12],__actual_cach:5,__init__:12,__list_of_sets_of_par:5,_actual_cim:4,_actual_trajectori:4,_aggregated_info_about_nodes_par:4,_array_indx:5,_cach:2,_cim:4,_complete_graph:2,_df_samples_list:[5,12],_df_structur:5,_df_variabl:[5,12],_file_path:12,_graph:[4,12],_import:4,_net_graph:2,_node:2,_node_id:4,_nodes_indx:2,_nodes_v:2,_p_combs_structur:4,_raw_data:5,_sample_path:2,_single_set_of_cim:2,_sorter:[5,12],_state_residence_tim:4,_structur:4,_structure_label:5,_time:4,_time_filt:4,_time_scalar_indexing_structur:4,_total_variables_count:4,_total_variables_numb:4,_trajectori:4,_transition_filt:4,_transition_matric:4,_transition_scalar_indexing_structur:4,_variables_label:5,abc:[3,5],about:[3,4],abstract_import:[0,1,4,13,14],abstractimport:[4,5,12],act:5,actual:[2,4],actual_cim:[4,12],add:[4,5],add_edg:4,add_nod:4,added:2,addit:2,adjac:[2,12],adjacency_matrix:[2,12],after:5,against:2,aggreg:4,algorithm:[2,3,12],all:[2,3,4,5,9,12],alpha_xu:2,alpha_xxu:2,alreadi:[5,12],also:[2,4],ani:[2,3],anoth:4,another_filtering_method:9,approach:2,arc:5,arrai:[2,4,5,12],assign:2,assum:2,aux_build_p_combs_structur:9,aux_build_time_columns_filtering_structure_for_a_nod:9,aux_build_time_scalar_indexing_structure_for_a_nod:9,aux_build_transition_columns_filtering_structur:9,aux_build_transition_scalar_indexing_structure_for_a_nod:9,aux_import_sampled_cim:7,aux_test_build_cim:9,aux_test_init:9,axi:12,base:[2,3,4,5,7,8,9,10],bayesian:2,befor:[2,3,7,8,9,10],belong:2,best:2,between:5,bool:[2,4],both:[2,5],bound:4,build:[2,4,5,9,12],build_cim:4,build_complete_graph:2,build_list_of_samples_arrai:5,build_p_comb_structure_for_a_nod:[4,9],build_removable_edges_matrix:2,build_sort:[5,12],build_structur:[4,12],build_time_columns_filtering_for_a_nod:4,build_time_scalar_indexing_structure_for_a_nod:4,build_times_and_transitions_structur:4,build_trajectori:[4,12],build_transition_filtering_for_a_nod:4,build_transition_scalar_indexing_structure_for_a_nod:4,built:2,cach:[0,1,2,13,14],calcul:2,call:[5,12],cardin:[2,4,5,9],cardinalit:[4,5],caridin:4,caridinalit:4,chang:[4,5],check:4,chi:2,chi_test:2,chi_test_alfa:2,child:[2,3],child_indx:2,child_states_numb:2,child_val:2,cim1:[2,7],cim2:[2,7],cim:[2,4,5,12],cim_equality_test:7,cims_kei:5,cims_label:7,classmethod:[7,8,9,10],clean_structure_edg:4,clear:[4,5],clear_concatenated_fram:5,clear_data_frame_list:5,clear_indexing_filtering_structur:4,clear_memori:4,climb:[2,3],coeffici:4,col:4,color:2,cols_filt:2,column:[2,4,5,12],columns_head:5,comb:4,combin:[4,5,9],combinatori:[4,9],common:2,complet:[2,4,5],complete_test:2,complete_trajectori:4,comput:[2,3,4,5,12],compute_cim_coeffici:4,compute_parameters_for_nod:[2,12],compute_row_delta_in_all_samples_fram:[5,12],compute_row_delta_sigle_samples_fram:5,compute_state_res_time_for_nod:2,compute_state_transitions_for_a_nod:2,compute_thumb_valu:2,concatanated_sampl:5,concaten:[4,5],concatenated_sampl:5,condit:4,conditional_intensity_matrix:[0,1,2,13,14],conditionalintensitymatrix:[2,4],consid:[2,4],constraint:2,constraint_based_optim:[0,1,13,14],constraintbasedoptim:3,construct:[4,5,12],conta:5,contain:[2,4,5,9],contains_edg:4,content:[13,14],convert:[2,5],copi:5,core:5,correct:[4,5],could:2,count:4,creat:[2,4,12],csv:12,csvimport:12,ctbn:2,ctpc:[2,3,12],ctpc_algorithm:[2,12],current:[2,3,5],cut:5,dafram:5,data:[2,3,4,5,13,14],datafram:[4,5,12],dataset:[3,4,5],dataset_id:[5,12],datfram:5,def:12,defin:5,definit:5,defualt:2,delta:[2,4,5],demonstr:12,describ:5,desir:[2,4],df_samples_list:5,dict:[5,12],dictionari:5,differ:5,differt:2,digraph:2,dimens:4,dir:12,direct:[2,4],directli:5,disabl:[2,3],disable_multiprocess:2,distribuit:2,doc:5,doubl:4,download:12,drop:12,duplic:4,dyn:12,each:[2,3,5],edg:[2,4,5,12],edges_list:4,end:5,entir:2,equal:4,equality_of_cims_of_nod:7,est:12,estim:[0,1,3,4,6,13,14],estimate_par:2,estimate_structur:2,estimated_cim:7,everi:[4,5],exam:12,exampl:[5,13,14],exclud:2,exctract:5,exist:5,exp_test_alfa:2,exponenti:2,expos:5,extend:12,extens:[2,5],extract:[4,5],fals:2,fam_score_calcul:[0,1,13,14],famscor:2,famscorecalcul:2,fast_init:[2,4,12],file:[2,5,12],file_path:[2,5,12],filepath:5,fill:[2,12],filter:[2,4],filter_cims_with_mask:4,find:[2,5],first:[2,12],fixtur:[7,8,9,10],follow:[4,5],form:4,format:12,formula:2,found:5,frame:5,from:[4,5,12],from_nod:5,gener:2,generate_possible_sub_sets_of_s:2,get:[2,5],get_cims_numb:4,get_fam_scor:2,get_node_id:4,get_node_indx:4,get_ordered_by_indx_set_of_par:4,get_parents_by_id:4,get_positional_node_indx:4,get_score_from_graph:2,get_states_numb:4,given:[2,4,5],glob:12,graph:[2,4,9,12],graph_struct:4,graphic:2,grid:[4,9],grpah:12,has:[5,12],has_edg:4,has_prior_net_structur:4,have:5,header:5,header_column:5,hill:[2,3],hill_climbing_search:[0,1,13,14],hillclimb:3,hold:[2,4],hook:[7,8,9,10],how:5,hyperparamet:2,hypothesi:2,identifi:[2,4,5],iff:2,implement:[3,5,13,14],import_data:[5,12],import_sampled_cim:5,import_structur:5,import_trajectori:5,import_vari:[5,12],improv:[2,3],includ:2,independ:2,independence_test:2,index:[2,4,5,12,13],indic:4,indx:5,info:[4,12],inform:[3,4],init:12,initi:[2,4,5,12],inplac:12,insid:12,instal:[13,14],interest:4,interfac:3,intes:4,iter:[2,3],iterations_numb:[2,3],its:[2,3],join:12,json:[2,5,12],json_import:[0,1,13,14],jsonarrai:5,jsonimport:[5,12],keep:[2,3,5],kei:5,kind:2,knowledg:2,known:2,known_edg:2,label:[2,3,4,5],lenght:[2,3],level:[2,5],likelihood:2,list:[2,3,4,5,12],list_of_column:4,list_of_edg:4,list_of_nod:4,load:5,loop:2,m_xu_suff_stat:2,m_xxu_suff_stat:2,main:12,margin:2,marginal_likelihood_q:2,marginal_likelihood_theta:2,mask:[4,9],mask_arr:4,matric:[2,4],matrix:[2,4,5,9,12],max_par:[2,3],maximum:[2,3],member:[4,5],mention:4,merg:5,method:[2,5,7,8,9,10],methodnam:[7,8,9,10],model:2,modul:[13,14],multipl:5,multiprocess:2,name:[2,4,5,12],ndarrai:[2,4,5],necessari:[2,4,5],nest:5,net:[2,3,4,5,12],net_graph:2,network:[2,4,5],network_graph:[0,1,2,13,14],networkgraph:[2,4,12],networkx:2,node:[2,3,4,5,9,12],node_id:[2,3,4,9],node_index:4,node_indx:[2,4],node_st:[4,9],node_states_numb:[4,9],nodes_index:4,nodes_indexes_arr:4,nodes_label:4,nodes_labels_list:4,nodes_numb:4,nodes_vals_arr:4,nodes_valu:[4,12],none:[2,3,4,5,7,9,10,12],normal:5,normalize_trajectori:5,number:[2,3,4],numpi:[2,4,5,9],obj:[10,12],object:[2,3,4,5,12],one:[4,5],one_iteration_of_ctpc_algorithm:2,one_level_norm:5,onli:5,oper:2,optim:[0,1,2,6,13,14],optimize_structur:3,option:[2,3],order:[2,5,10],origin:5,original_cols_numb:4,otherwis:[2,5],out:5,outer:[5,12],over:2,own:[13,14],p_comb:[4,9],p_indx:[4,9],p_val:9,p_valu:9,packag:[13,14],page:13,panda:[5,12],param:[2,4],paramet:[2,3,4,5,9,13,14],parameters_estim:[0,1,13,14],parametersestim:[2,12],parent:[2,3,4,5],parent_indx:2,parent_label:2,parent_set:2,parent_set_v:2,parent_v:2,parent_valu:9,parents_cardin:4,parents_comb:5,parents_index:4,parents_indx:9,parents_label:[4,9],parents_states_numb:[4,9],parents_v:[4,9],parents_valu:[4,9],part:2,particular:[2,5],pass:12,path:[2,5,12],patienc:[2,3],peest:12,perform:2,pip:12,place:5,plot:2,png:2,posit:[4,5],possibl:[2,4],predict:3,prepar:5,present:[2,5],print:12,prior:[2,12],prior_net_structur:5,process:[2,3,4,5],properli:5,properti:[4,5],put:5,pyctbn:12,q_xx:4,rappres:4,raw:5,raw_data:5,read:[5,12],read_csv:12,read_csv_fil:12,read_fil:12,read_json_fil:5,real:[2,4,5,12],red:2,refer:[4,5],reject:2,rel:4,relat:5,releas:12,remain:5,remov:[2,4,5],remove_edg:4,remove_nod:4,repres:4,represent:2,res:4,resid:[2,4],result:[2,5,12],rtype:4,rule:[2,3],run:[7,8,9,10],runtest:[7,8,9,10],same:5,sampl:[4,5,12],sample_fram:[5,12],sample_import:[0,1,13,14],sample_path:[0,1,2,13,14],sampled_cim:7,sampleimport:5,samplepath:[2,4,12],samples_label:5,save:[2,12],save_plot_estimated_structure_graph:2,save_result:[2,12],scalar_index:2,scalar_indexes_struct:2,score:2,se1:12,search:[2,3,13],second:2,see:5,select:12,self:[2,5,12],sep:2,sep_set:2,set:[2,4,5,7,8,9,10],set_of_cim:[0,1,2,5,13,14],setofcim:[2,4,5,12],setupclass:[7,8,9,10],shift:[4,5],shifted_cols_head:5,show:2,signific:2,simbol:5,simpl:12,simpli:12,sinc:4,single_cim_xu_marginal_likelihood_q:2,single_cim_xu_marginal_likelihood_theta:2,single_internal_cim_xxu_marginal_likelihood_theta:2,size:[2,4],socim:5,sofc1:12,sorter:5,specif:[2,4,12],spuriou:2,spurious_edg:2,start:5,state:[2,4],state_res_tim:4,state_residence_tim:4,state_transition_matrix:4,statist:2,stop:[2,3],str:[2,3,4,5,12],string:[2,3,4,5],structur:[0,1,2,3,5,9,13,14],structure_constraint_based_estim:[0,1,13,14],structure_estim:[0,1,3,13,14],structure_estimation_exampl:12,structure_graph:[0,1,2,5,6,13,14],structure_label:5,structure_score_based_estim:[0,1,13,14],structureconstraintbasedestim:2,structureestim:[2,3,12],structurescorebasedestim:2,structut:4,style:2,submodul:[1,6,13,14],subpackag:[13,14],subset:2,suffici:2,suffuci:2,symbol:[4,5],synthet:5,t_xu_suff_stat:2,tabu:[2,3],tabu_length:[2,3],tabu_rules_dur:[2,3],tabu_search:[0,1,13,14],tabusearch:3,take:12,tar:12,task:[2,4],tau_xu:2,ternari:12,test:2,test_add_edg:9,test_add_nod:9,test_adjacency_matrix:7,test_buid_samplepath_no_concatenated_sampl:9,test_buid_samplepath_no_vari:9,test_build_cim:9,test_build_complete_graph:7,test_build_p_combs_structur:9,test_build_removable_edges_matrix:7,test_build_saplepath_no_prior_net_structur:9,test_build_sort:10,test_build_structur:9,test_build_structure_bad_sort:9,test_build_time_columns_filtering_structure_for_a_nod:9,test_build_time_scalar_indexing_structure_for_a_nod:9,test_build_trajectori:9,test_build_transition_columns_filtering_structur:9,test_build_transition_scalar_indexing_structure_for_a_nod:9,test_cach:6,test_child:2,test_cim:6,test_clear:10,test_clear_concatenated_fram:10,test_clear_data_frame_list:10,test_compute_cim_coeffici:9,test_compute_parameters_for_nod:7,test_compute_row_delta_in_all_fram:10,test_compute_row_delta_in_all_frames_not_init_sort:10,test_compute_row_delta_single_samples_fram:10,test_dataset_id:10,test_edges_oper:9,test_equ:9,test_fast_init:[7,9],test_file_path:10,test_filter_cims_with_mask:9,test_find:10,test_generate_possible_sub_sets_of_s:7,test_get_node_id:9,test_get_node_indx:9,test_get_ordered_by_indx_set_of_par:9,test_get_parents_by_id:9,test_get_positional_node_indx:9,test_get_states_numb:9,test_hill_climbing_search:6,test_import_data:10,test_import_sampled_cim:10,test_import_structur:10,test_import_vari:10,test_init:[7,9,10],test_init_not_filled_dataframs:9,test_init_not_initialized_import:9,test_json_import:6,test_networkgraph:6,test_normalize_trajectori:10,test_normalize_trajectories_wrong_indx:10,test_normalize_trajectories_wrong_kei:10,test_ord:10,test_par:2,test_parameters_estim:6,test_put:10,test_read_json_file_found:10,test_read_json_file_not_found:10,test_repr:9,test_sample_import:6,test_sample_path:6,test_save_plot_estimated_graph:7,test_save_result:7,test_setofcim:6,test_structur:[6,8],test_structure_1:7,test_structure_2:7,test_structure_3:[7,8],test_structure_constraint_based_estim:6,test_structure_estim:6,test_structure_monoprocesso:7,test_structure_score_based_estim:6,test_tabu_search:6,test_tim:7,test_trajectori:6,testcach:10,testcas:[7,8,9,10],testconditionalintensitymatrix:9,testhillclimbingsearch:8,testjsonimport:10,testnetworkgraph:9,testparametersestimatior:7,testsampleimport:10,testsamplepath:9,testsetofcim:9,teststructur:9,teststructureconstraintbasedestim:7,teststructureestim:7,teststructurescorebasedestim:7,testtabusearch:8,testtrajectori:9,tha:5,theta:2,thi:[2,4,5,12],three:12,threshold:2,thumb:2,thumb_threshold:2,thumb_valu:2,time:[2,4,5,12],time_filt:4,time_kei:5,time_scalar_indexing_strucur:4,timestamp:5,to_nod:5,tot_vars_count:[2,3],total:[2,4],total_variables_count:4,total_variables_numb:4,traj:5,trajecory_head:5,trajectori:[0,1,2,5,12,13,14],trajectories_kei:5,trajectory_list:5,trajectri:12,transit:[2,4,5],transition_filt:4,transition_matric:4,transition_scalar_indexing_structur:4,tri:5,tupl:4,tutori:5,two:2,type:[2,3,4,5,12],union:5,uniqu:5,unittest:[7,8,9,10],unus:4,usag:[13,14],use:[2,12],used:[2,3,4,5],using:[2,3,4,5],util:[0,1,4,6,13,14],valid:2,valu:[2,3,4,5,9,12],values_list:12,var_id:2,variabl:[2,3,4,5,12],variable_cardin:5,variable_cim_xu_marginal_likelihood_q:2,variable_cim_xu_marginal_likelihood_theta:2,variable_label:5,variables_kei:5,variables_label:5,vector:[2,4],want:12,when:2,where:5,which:[2,3,4,5],whl:12,who:2,without:[2,3],you:[2,5,12],your:[13,14]},titles:["PyCTBN package","PyCTBN.PyCTBN package","PyCTBN.PyCTBN.estimators package","PyCTBN.PyCTBN.optimizers package","PyCTBN.PyCTBN.structure_graph package","PyCTBN.PyCTBN.utility package","PyCTBN.tests package","PyCTBN.tests.estimators package","PyCTBN.tests.optimizers package","PyCTBN.tests.structure_graph package","PyCTBN.tests.utility package","basic_main module","Examples","Welcome to PyCTBN\u2019s documentation!","PyCTBN","setup module"],titleterms:{"import":12,abstract_import:5,basic_main:11,cach:5,conditional_intensity_matrix:4,constraint_based_optim:3,content:[0,1,2,3,4,5,6,7,8,9,10],data:12,document:13,estim:[2,7,12],exampl:12,fam_score_calcul:2,hill_climbing_search:3,implement:12,indic:13,instal:12,json_import:5,modul:[0,1,2,3,4,5,6,7,8,9,10,11,15],network_graph:4,optim:[3,8],own:12,packag:[0,1,2,3,4,5,6,7,8,9,10],paramet:12,parameters_estim:2,pyctbn:[0,1,2,3,4,5,6,7,8,9,10,13,14],sample_import:5,sample_path:4,set_of_cim:4,setup:15,structur:[4,12],structure_constraint_based_estim:2,structure_estim:2,structure_graph:[4,9],structure_score_based_estim:2,submodul:[0,2,3,4,5,7,8,9,10],subpackag:[0,1,6],tabl:13,tabu_search:3,test:[6,7,8,9,10],test_cach:10,test_cim:9,test_hill_climbing_search:8,test_json_import:10,test_networkgraph:9,test_parameters_estim:7,test_sample_import:10,test_sample_path:9,test_setofcim:9,test_structur:9,test_structure_constraint_based_estim:7,test_structure_estim:7,test_structure_score_based_estim:7,test_tabu_search:8,test_trajectori:9,trajectori:4,usag:12,util:[5,10],welcom:13,your:12}}) \ No newline at end of file +Search.setIndex({docnames:["PyCTBN","PyCTBN.PyCTBN","PyCTBN.PyCTBN.estimators","PyCTBN.PyCTBN.optimizers","PyCTBN.PyCTBN.structure_graph","PyCTBN.PyCTBN.utility","PyCTBN.tests","PyCTBN.tests.estimators","PyCTBN.tests.optimizers","PyCTBN.tests.structure_graph","PyCTBN.tests.utility","basic_main","examples","index","modules","setup"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":3,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,sphinx:56},filenames:["PyCTBN.rst","PyCTBN.PyCTBN.rst","PyCTBN.PyCTBN.estimators.rst","PyCTBN.PyCTBN.optimizers.rst","PyCTBN.PyCTBN.structure_graph.rst","PyCTBN.PyCTBN.utility.rst","PyCTBN.tests.rst","PyCTBN.tests.estimators.rst","PyCTBN.tests.optimizers.rst","PyCTBN.tests.structure_graph.rst","PyCTBN.tests.utility.rst","basic_main.rst","examples.rst","index.rst","modules.rst","setup.rst"],objects:{"":{PyCTBN:[0,0,0,"-"]},"PyCTBN.PyCTBN":{estimators:[2,0,0,"-"],optimizers:[3,0,0,"-"],structure_graph:[4,0,0,"-"],utility:[5,0,0,"-"]},"PyCTBN.PyCTBN.estimators":{fam_score_calculator:[2,0,0,"-"],parameters_estimator:[2,0,0,"-"],structure_constraint_based_estimator:[2,0,0,"-"],structure_estimator:[2,0,0,"-"],structure_score_based_estimator:[2,0,0,"-"]},"PyCTBN.PyCTBN.estimators.fam_score_calculator":{FamScoreCalculator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.fam_score_calculator.FamScoreCalculator":{get_fam_score:[2,2,1,""],marginal_likelihood_q:[2,2,1,""],marginal_likelihood_theta:[2,2,1,""],single_cim_xu_marginal_likelihood_q:[2,2,1,""],single_cim_xu_marginal_likelihood_theta:[2,2,1,""],single_internal_cim_xxu_marginal_likelihood_theta:[2,2,1,""],variable_cim_xu_marginal_likelihood_q:[2,2,1,""],variable_cim_xu_marginal_likelihood_theta:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator":{ParametersEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator.ParametersEstimator":{compute_parameters_for_node:[2,2,1,""],compute_state_res_time_for_node:[2,2,1,""],compute_state_transitions_for_a_node:[2,2,1,""],fast_init:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator":{StructureConstraintBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator":{complete_test:[2,2,1,""],compute_thumb_value:[2,2,1,""],ctpc_algorithm:[2,2,1,""],estimate_structure:[2,2,1,""],independence_test:[2,2,1,""],one_iteration_of_CTPC_algorithm:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator":{StructureEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator":{adjacency_matrix:[2,2,1,""],build_complete_graph:[2,2,1,""],build_removable_edges_matrix:[2,2,1,""],estimate_structure:[2,2,1,""],generate_possible_sub_sets_of_size:[2,2,1,""],save_plot_estimated_structure_graph:[2,2,1,""],save_results:[2,2,1,""],spurious_edges:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator":{StructureScoreBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator.StructureScoreBasedEstimator":{estimate_parents:[2,2,1,""],estimate_structure:[2,2,1,""],get_score_from_graph:[2,2,1,""]},"PyCTBN.PyCTBN.optimizers":{constraint_based_optimizer:[3,0,0,"-"],hill_climbing_search:[3,0,0,"-"],optimizer:[3,0,0,"-"],tabu_search:[3,0,0,"-"]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer":{ConstraintBasedOptimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer.ConstraintBasedOptimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search":{HillClimbing:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search.HillClimbing":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer":{Optimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer.Optimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search":{TabuSearch:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search.TabuSearch":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.structure_graph":{conditional_intensity_matrix:[4,0,0,"-"],network_graph:[4,0,0,"-"],sample_path:[4,0,0,"-"],set_of_cims:[4,0,0,"-"],structure:[4,0,0,"-"],trajectory:[4,0,0,"-"]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix":{ConditionalIntensityMatrix:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix":{cim:[4,2,1,""],compute_cim_coefficients:[4,2,1,""],state_residence_times:[4,2,1,""],state_transition_matrix:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph":{NetworkGraph:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph":{add_edges:[4,2,1,""],add_nodes:[4,2,1,""],build_p_comb_structure_for_a_node:[4,2,1,""],build_time_columns_filtering_for_a_node:[4,2,1,""],build_time_scalar_indexing_structure_for_a_node:[4,2,1,""],build_transition_filtering_for_a_node:[4,2,1,""],build_transition_scalar_indexing_structure_for_a_node:[4,2,1,""],clear_indexing_filtering_structures:[4,2,1,""],edges:[4,2,1,""],fast_init:[4,2,1,""],get_node_indx:[4,2,1,""],get_ordered_by_indx_set_of_parents:[4,2,1,""],get_parents_by_id:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],has_edge:[4,2,1,""],nodes:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_values:[4,2,1,""],p_combs:[4,2,1,""],remove_edges:[4,2,1,""],remove_node:[4,2,1,""],time_filtering:[4,2,1,""],time_scalar_indexing_strucure:[4,2,1,""],transition_filtering:[4,2,1,""],transition_scalar_indexing_structure:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path":{SamplePath:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath":{build_structure:[4,2,1,""],build_trajectories:[4,2,1,""],clear_memory:[4,2,1,""],has_prior_net_structure:[4,2,1,""],structure:[4,2,1,""],total_variables_count:[4,2,1,""],trajectories:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims":{SetOfCims:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims":{actual_cims:[4,2,1,""],build_cims:[4,2,1,""],build_times_and_transitions_structures:[4,2,1,""],filter_cims_with_mask:[4,2,1,""],get_cims_number:[4,2,1,""],p_combs:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.structure":{Structure:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.structure.Structure":{add_edge:[4,2,1,""],clean_structure_edges:[4,2,1,""],contains_edge:[4,2,1,""],edges:[4,2,1,""],get_node_id:[4,2,1,""],get_node_indx:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_labels:[4,2,1,""],nodes_values:[4,2,1,""],remove_edge:[4,2,1,""],remove_node:[4,2,1,""],total_variables_number:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory":{Trajectory:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory.Trajectory":{complete_trajectory:[4,2,1,""],size:[4,2,1,""],times:[4,2,1,""],trajectory:[4,2,1,""]},"PyCTBN.PyCTBN.utility":{abstract_importer:[5,0,0,"-"],cache:[5,0,0,"-"],json_importer:[5,0,0,"-"],sample_importer:[5,0,0,"-"]},"PyCTBN.PyCTBN.utility.abstract_importer":{AbstractImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter":{build_list_of_samples_array:[5,2,1,""],build_sorter:[5,2,1,""],clear_concatenated_frame:[5,2,1,""],compute_row_delta_in_all_samples_frames:[5,2,1,""],compute_row_delta_sigle_samples_frame:[5,2,1,""],concatenated_samples:[5,2,1,""],dataset_id:[5,2,1,""],file_path:[5,2,1,""],sorter:[5,2,1,""],structure:[5,2,1,""],variables:[5,2,1,""]},"PyCTBN.PyCTBN.utility.cache":{Cache:[5,1,1,""]},"PyCTBN.PyCTBN.utility.cache.Cache":{clear:[5,2,1,""],find:[5,2,1,""],put:[5,2,1,""]},"PyCTBN.PyCTBN.utility.json_importer":{JsonImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.json_importer.JsonImporter":{build_sorter:[5,2,1,""],clear_data_frame_list:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""],import_sampled_cims:[5,2,1,""],import_structure:[5,2,1,""],import_trajectories:[5,2,1,""],import_variables:[5,2,1,""],normalize_trajectories:[5,2,1,""],one_level_normalizing:[5,2,1,""],read_json_file:[5,2,1,""]},"PyCTBN.PyCTBN.utility.sample_importer":{SampleImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.sample_importer.SampleImporter":{build_sorter:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""]},"PyCTBN.tests":{estimators:[7,0,0,"-"],optimizers:[8,0,0,"-"],structure_graph:[9,0,0,"-"],utility:[10,0,0,"-"]},"PyCTBN.tests.estimators":{test_parameters_estimator:[7,0,0,"-"],test_structure_constraint_based_estimator:[7,0,0,"-"],test_structure_estimator:[7,0,0,"-"],test_structure_score_based_estimator:[7,0,0,"-"]},"PyCTBN.tests.estimators.test_parameters_estimator":{TestParametersEstimatior:[7,1,1,""]},"PyCTBN.tests.estimators.test_parameters_estimator.TestParametersEstimatior":{aux_import_sampled_cims:[7,2,1,""],cim_equality_test:[7,2,1,""],equality_of_cims_of_node:[7,2,1,""],setUpClass:[7,2,1,""],test_compute_parameters_for_node:[7,2,1,""],test_fast_init:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator":{TestStructureConstraintBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator.TestStructureConstraintBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_estimator":{TestStructureEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_estimator.TestStructureEstimator":{setUpClass:[7,2,1,""],test_adjacency_matrix:[7,2,1,""],test_build_complete_graph:[7,2,1,""],test_build_removable_edges_matrix:[7,2,1,""],test_generate_possible_sub_sets_of_size:[7,2,1,""],test_init:[7,2,1,""],test_save_plot_estimated_graph:[7,2,1,""],test_save_results:[7,2,1,""],test_time:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator":{TestStructureScoreBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator.TestStructureScoreBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""],test_structure_monoprocesso:[7,2,1,""]},"PyCTBN.tests.optimizers":{test_hill_climbing_search:[8,0,0,"-"],test_tabu_search:[8,0,0,"-"]},"PyCTBN.tests.optimizers.test_hill_climbing_search":{TestHillClimbingSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_hill_climbing_search.TestHillClimbingSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.optimizers.test_tabu_search":{TestTabuSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_tabu_search.TestTabuSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.structure_graph":{test_cim:[9,0,0,"-"],test_networkgraph:[9,0,0,"-"],test_sample_path:[9,0,0,"-"],test_setofcims:[9,0,0,"-"],test_structure:[9,0,0,"-"],test_trajectory:[9,0,0,"-"]},"PyCTBN.tests.structure_graph.test_cim":{TestConditionalIntensityMatrix:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_cim.TestConditionalIntensityMatrix":{setUpClass:[9,2,1,""],test_compute_cim_coefficients:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph":{TestNetworkGraph:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph.TestNetworkGraph":{aux_build_p_combs_structure:[9,2,1,""],aux_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],aux_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],aux_build_transition_columns_filtering_structure:[9,2,1,""],aux_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_add_edges:[9,2,1,""],test_add_nodes:[9,2,1,""],test_build_p_combs_structure:[9,2,1,""],test_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],test_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],test_build_transition_columns_filtering_structure:[9,2,1,""],test_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],test_fast_init:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_ordered_by_indx_set_of_parents:[9,2,1,""],test_get_parents_by_id:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_sample_path":{TestSamplePath:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_sample_path.TestSamplePath":{setUpClass:[9,2,1,""],test_buid_samplepath_no_concatenated_samples:[9,2,1,""],test_buid_samplepath_no_variables:[9,2,1,""],test_build_saplepath_no_prior_net_structure:[9,2,1,""],test_build_structure:[9,2,1,""],test_build_structure_bad_sorter:[9,2,1,""],test_build_trajectories:[9,2,1,""],test_init:[9,2,1,""],test_init_not_filled_dataframse:[9,2,1,""],test_init_not_initialized_importer:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_setofcims":{TestSetOfCims:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_setofcims.TestSetOfCims":{another_filtering_method:[9,2,1,""],aux_test_build_cims:[9,2,1,""],aux_test_init:[9,2,1,""],build_p_comb_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_build_cims:[9,2,1,""],test_filter_cims_with_mask:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_structure":{TestStructure:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_structure.TestStructure":{setUpClass:[9,2,1,""],test_edges_operations:[9,2,1,""],test_equality:[9,2,1,""],test_get_node_id:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_positional_node_indx:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_trajectory":{TestTrajectory:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_trajectory.TestTrajectory":{setUpClass:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.utility":{test_cache:[10,0,0,"-"],test_json_importer:[10,0,0,"-"],test_sample_importer:[10,0,0,"-"]},"PyCTBN.tests.utility.test_cache":{TestCache:[10,1,1,""]},"PyCTBN.tests.utility.test_cache.TestCache":{test_clear:[10,2,1,""],test_find:[10,2,1,""],test_init:[10,2,1,""],test_put:[10,2,1,""]},"PyCTBN.tests.utility.test_json_importer":{TestJsonImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_json_importer.TestJsonImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_build_sorter:[10,2,1,""],test_clear_concatenated_frame:[10,2,1,""],test_clear_data_frame_list:[10,2,1,""],test_compute_row_delta_in_all_frames:[10,2,1,""],test_compute_row_delta_in_all_frames_not_init_sorter:[10,2,1,""],test_compute_row_delta_single_samples_frame:[10,2,1,""],test_dataset_id:[10,2,1,""],test_file_path:[10,2,1,""],test_import_data:[10,2,1,""],test_import_sampled_cims:[10,2,1,""],test_import_structure:[10,2,1,""],test_import_variables:[10,2,1,""],test_init:[10,2,1,""],test_normalize_trajectories:[10,2,1,""],test_normalize_trajectories_wrong_indx:[10,2,1,""],test_normalize_trajectories_wrong_key:[10,2,1,""],test_read_json_file_found:[10,2,1,""],test_read_json_file_not_found:[10,2,1,""]},"PyCTBN.tests.utility.test_sample_importer":{TestSampleImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_sample_importer.TestSampleImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_init:[10,2,1,""],test_order:[10,2,1,""]},PyCTBN:{PyCTBN:[1,0,0,"-"],tests:[6,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method"},terms:{"abstract":[2,3,4,5,12],"boolean":[2,4],"case":[7,8,9,10],"class":[2,3,4,5,7,8,9,10,12],"default":[2,3],"float":2,"function":2,"import":[4,5,13,14],"int":[2,3,4,5],"null":2,"return":[2,3,4,5,9,12],"static":[2,4],"super":12,"true":[2,12],"var":12,HAS:5,Has:[2,4],NOT:2,The:[2,4,5,12],Use:[2,12],__actual_cach:5,__init__:12,__list_of_sets_of_par:5,_actual_cim:4,_actual_trajectori:4,_aggregated_info_about_nodes_par:4,_array_indx:5,_cach:2,_cim:4,_complete_graph:2,_df_samples_list:[5,12],_df_structur:5,_df_variabl:[5,12],_file_path:12,_graph:[4,12],_import:4,_net_graph:2,_node:2,_node_id:4,_nodes_indx:2,_nodes_v:2,_p_combs_structur:4,_raw_data:5,_sample_path:2,_single_set_of_cim:2,_sorter:[5,12],_state_residence_tim:4,_structur:4,_structure_label:5,_time:4,_time_filt:4,_time_scalar_indexing_structur:4,_total_variables_count:4,_total_variables_numb:4,_trajectori:4,_transition_filt:4,_transition_matric:4,_transition_scalar_indexing_structur:4,_variables_label:5,abc:[3,5],about:[3,4],abstract_import:[0,1,4,13,14],abstractimport:[4,5,12],act:5,actual:[2,4],actual_cim:[4,12],add:[4,5],add_edg:4,add_nod:4,added:2,addit:2,adjac:[2,12],adjacency_matrix:[2,12],after:5,against:2,aggreg:4,algorithm:[2,3,12],all:[2,3,4,5,9,12],alpha_xu:2,alpha_xxu:2,alreadi:[5,12],also:[2,4],ani:[2,3],anoth:4,another_filtering_method:9,approach:2,arc:5,arrai:[2,4,5,12],assign:2,assum:2,aux_build_p_combs_structur:9,aux_build_time_columns_filtering_structure_for_a_nod:9,aux_build_time_scalar_indexing_structure_for_a_nod:9,aux_build_transition_columns_filtering_structur:9,aux_build_transition_scalar_indexing_structure_for_a_nod:9,aux_import_sampled_cim:7,aux_test_build_cim:9,aux_test_init:9,axi:12,base:[2,3,4,5,7,8,9,10],bayesian:2,befor:[2,3,7,8,9,10],belong:2,best:2,between:5,bool:[2,4],both:[2,5],bound:4,build:[2,4,5,9,12],build_cim:4,build_complete_graph:2,build_list_of_samples_arrai:5,build_p_comb_structure_for_a_nod:[4,9],build_removable_edges_matrix:2,build_sort:[5,12],build_structur:[4,12],build_time_columns_filtering_for_a_nod:4,build_time_scalar_indexing_structure_for_a_nod:4,build_times_and_transitions_structur:4,build_trajectori:[4,12],build_transition_filtering_for_a_nod:4,build_transition_scalar_indexing_structure_for_a_nod:4,built:2,cach:[0,1,2,13,14],calcul:2,call:[5,12],cardin:[2,4,5,9],cardinalit:[4,5],caridin:4,caridinalit:4,chang:[4,5],check:4,chi:2,chi_test:2,chi_test_alfa:2,child:[2,3],child_indx:2,child_states_numb:2,child_val:2,cim1:[2,7],cim2:[2,7],cim:[2,4,5,12],cim_equality_test:7,cims_kei:5,cims_label:7,classmethod:[7,8,9,10],clean_structure_edg:4,clear:[4,5],clear_concatenated_fram:5,clear_data_frame_list:5,clear_indexing_filtering_structur:4,clear_memori:4,climb:[2,3],coeffici:4,col:4,color:2,cols_filt:2,column:[2,4,5,12],columns_head:5,comb:4,combin:[4,5,9],combinatori:[4,9],common:2,complet:[2,4,5],complete_test:2,complete_trajectori:4,comput:[2,3,4,5,12],compute_cim_coeffici:4,compute_parameters_for_nod:[2,12],compute_row_delta_in_all_samples_fram:[5,12],compute_row_delta_sigle_samples_fram:5,compute_state_res_time_for_nod:2,compute_state_transitions_for_a_nod:2,compute_thumb_valu:2,concatanated_sampl:5,concaten:[4,5],concatenated_sampl:5,condit:4,conditional_intensity_matrix:[0,1,2,13,14],conditionalintensitymatrix:[2,4],consid:[2,4],constraint:2,constraint_based_optim:[0,1,13,14],constraintbasedoptim:3,construct:[4,5,12],conta:5,contain:[2,4,5,9],contains_edg:4,content:[13,14],convert:[2,5],copi:5,core:5,correct:[4,5],could:2,count:4,creat:[2,4,12],csv:12,csvimport:12,ctbn:2,ctpc:[2,3,12],ctpc_algorithm:[2,12],current:[2,3,5],cut:5,dafram:5,data:[2,3,4,5,13,14],datafram:[4,5,12],dataset:[3,4,5],dataset_id:[5,12],datfram:5,def:12,defin:5,definit:5,defualt:2,delta:[2,4,5],demonstr:12,describ:5,desir:[2,4],df_samples_list:5,dict:[5,12],dictionari:5,differ:5,differt:2,digraph:2,dimens:4,dir:12,direct:[2,4],directli:5,disabl:[2,3],disable_multiprocess:2,distribuit:2,doc:5,doubl:4,download:12,drop:12,duplic:4,dyn:12,each:[2,3,5],edg:[2,4,5,12],edges_list:4,end:5,entir:2,equal:4,equality_of_cims_of_nod:7,est:12,estim:[0,1,3,4,6,13,14],estimate_par:2,estimate_structur:2,estimated_cim:7,everi:[4,5],exam:12,exampl:[5,13,14],exclud:2,exctract:5,exist:5,exp_test_alfa:2,exponenti:2,expos:5,extend:12,extens:[2,5],extract:[4,5],fals:2,fam_score_calcul:[0,1,13,14],famscor:2,famscorecalcul:2,fast_init:[2,4,12],file:[2,5,12],file_path:[2,5,12],filepath:5,fill:[2,12],filter:[2,4],filter_cims_with_mask:4,find:[2,5],first:[2,12],fixtur:[7,8,9,10],follow:[4,5],form:4,format:12,formula:2,found:5,frame:5,from:[4,5,12],from_nod:5,gener:2,generate_possible_sub_sets_of_s:2,get:[2,5],get_cims_numb:4,get_fam_scor:2,get_node_id:4,get_node_indx:4,get_ordered_by_indx_set_of_par:4,get_parents_by_id:4,get_positional_node_indx:4,get_score_from_graph:2,get_states_numb:4,given:[2,4,5],glob:12,graph:[2,4,9,12],graph_struct:4,graphic:2,grid:[4,9],grpah:12,has:[5,12],has_edg:4,has_prior_net_structur:4,have:5,header:5,header_column:5,hill:[2,3],hill_climbing_search:[0,1,13,14],hillclimb:3,hold:[2,4],hook:[7,8,9,10],how:5,hyperparamet:2,hypothesi:2,identifi:[2,4,5],iff:2,implement:[3,5,13,14],import_data:[5,12],import_sampled_cim:5,import_structur:5,import_trajectori:5,import_vari:[5,12],improv:[2,3],includ:2,independ:2,independence_test:2,index:[2,4,5,12,13],indic:4,indx:5,info:[4,12],inform:[3,4],init:12,initi:[2,4,5,12],inplac:12,insid:12,instal:[13,14],interest:4,interfac:3,intes:4,iter:[2,3],iterations_numb:[2,3],its:[2,3],join:12,json:[2,5,12],json_import:[0,1,13,14],jsonarrai:5,jsonimport:[5,12],keep:[2,3,5],kei:5,kind:2,knowledg:2,known:2,known_edg:2,label:[2,3,4,5],lenght:[2,3],level:[2,5],likelihood:2,list:[2,3,4,5,12],list_of_column:4,list_of_edg:4,list_of_nod:4,load:5,loop:2,m_xu_suff_stat:2,m_xxu_suff_stat:2,main:12,margin:2,marginal_likelihood_q:2,marginal_likelihood_theta:2,mask:[4,9],mask_arr:4,matric:[2,4],matrix:[2,4,5,9,12],max_par:[2,3],maximum:[2,3],member:[4,5],mention:4,merg:5,method:[2,5,7,8,9,10],methodnam:[7,8,9,10],model:2,modul:[13,14],multipl:5,multiprocess:2,name:[2,4,5,12],ndarrai:[2,4,5],necessari:[2,4,5],nest:5,net:[2,3,4,5,12],net_graph:2,network:[2,4,5],network_graph:[0,1,2,13,14],networkgraph:[2,4,12],networkx:2,node:[2,3,4,5,9,12],node_id:[2,3,4,9],node_index:4,node_indx:[2,4],node_st:[4,9],node_states_numb:[4,9],nodes_index:4,nodes_indexes_arr:4,nodes_label:4,nodes_labels_list:4,nodes_numb:4,nodes_vals_arr:4,nodes_valu:[4,12],none:[2,3,4,5,7,9,10,12],normal:5,normalize_trajectori:5,number:[2,3,4],numpi:[2,4,5,9],obj:[10,12],object:[2,3,4,5,12],one:[4,5],one_iteration_of_ctpc_algorithm:2,one_level_norm:5,onli:5,oper:2,optim:[0,1,2,6,13,14],optimize_structur:3,option:[2,3],order:[2,5,10],origin:5,original_cols_numb:4,otherwis:[2,5],out:5,outer:[5,12],over:2,own:[13,14],p_comb:[4,9],p_indx:[4,9],p_val:9,p_valu:9,packag:[13,14],page:13,panda:[5,12],param:4,paramet:[2,3,4,5,9,13,14],parameters_estim:[0,1,13,14],parametersestim:[2,12],parent:[2,3,4,5],parent_indx:2,parent_label:2,parent_set:2,parent_set_v:2,parent_v:2,parent_valu:9,parents_cardin:4,parents_comb:5,parents_index:4,parents_indx:9,parents_label:[4,9],parents_states_numb:[4,9],parents_v:[4,9],parents_valu:[4,9],part:2,particular:[2,5],pass:12,path:[2,5,12],patienc:[2,3],peest:12,perform:2,pip:12,place:5,plot:2,png:2,posit:[4,5],possibl:[2,4],predict:3,prepar:5,present:[2,5],print:12,prior:[2,12],prior_net_structur:5,process:[2,3,4,5],properli:5,properti:[4,5],put:5,pyctbn:12,q_xx:4,rappres:4,raw:5,raw_data:5,read:[5,12],read_csv:12,read_csv_fil:12,read_fil:12,read_json_fil:5,real:[2,4,5,12],red:2,refer:[4,5],reject:2,rel:4,relat:5,releas:12,remain:5,remov:[2,4,5],remove_edg:4,remove_nod:4,repres:4,represent:2,res:4,resid:[2,4],result:[2,5,12],rtype:4,rule:[2,3],run:[7,8,9,10],runtest:[7,8,9,10],same:5,sampl:[4,5,12],sample_fram:[5,12],sample_import:[0,1,13,14],sample_path:[0,1,2,13,14],sampled_cim:7,sampleimport:5,samplepath:[2,4,12],samples_label:5,save:[2,12],save_plot_estimated_structure_graph:2,save_result:[2,12],scalar_index:2,scalar_indexes_struct:2,score:2,se1:12,search:[2,3,13],second:2,see:5,select:12,self:[2,5,12],sep:2,sep_set:2,set:[2,4,5,7,8,9,10],set_of_cim:[0,1,2,5,13,14],setofcim:[2,4,5,12],setupclass:[7,8,9,10],shift:[4,5],shifted_cols_head:5,show:2,signific:2,simbol:5,simpl:12,simpli:12,sinc:4,single_cim_xu_marginal_likelihood_q:2,single_cim_xu_marginal_likelihood_theta:2,single_internal_cim_xxu_marginal_likelihood_theta:2,size:[2,4],socim:5,sofc1:12,sorter:5,specif:[2,4,12],spuriou:2,spurious_edg:2,start:5,state:[2,4],state_res_tim:4,state_residence_tim:4,state_transition_matrix:4,statist:2,stop:[2,3],str:[2,3,4,5,12],string:[2,3,4,5],structur:[0,1,2,3,5,9,13,14],structure_constraint_based_estim:[0,1,13,14],structure_estim:[0,1,3,13,14],structure_estimation_exampl:12,structure_graph:[0,1,2,5,6,13,14],structure_label:5,structure_score_based_estim:[0,1,13,14],structureconstraintbasedestim:2,structureestim:[2,3,12],structurescorebasedestim:2,structut:4,style:2,submodul:[1,6,13,14],subpackag:[13,14],subset:2,suffici:2,suffuci:2,symbol:[4,5],synthet:5,t_xu_suff_stat:2,tabu:[2,3],tabu_length:[2,3],tabu_rules_dur:[2,3],tabu_search:[0,1,13,14],tabusearch:3,take:12,tar:12,task:[2,4],tau_xu:2,ternari:12,test:2,test_add_edg:9,test_add_nod:9,test_adjacency_matrix:7,test_buid_samplepath_no_concatenated_sampl:9,test_buid_samplepath_no_vari:9,test_build_cim:9,test_build_complete_graph:7,test_build_p_combs_structur:9,test_build_removable_edges_matrix:7,test_build_saplepath_no_prior_net_structur:9,test_build_sort:10,test_build_structur:9,test_build_structure_bad_sort:9,test_build_time_columns_filtering_structure_for_a_nod:9,test_build_time_scalar_indexing_structure_for_a_nod:9,test_build_trajectori:9,test_build_transition_columns_filtering_structur:9,test_build_transition_scalar_indexing_structure_for_a_nod:9,test_cach:6,test_child:2,test_cim:6,test_clear:10,test_clear_concatenated_fram:10,test_clear_data_frame_list:10,test_compute_cim_coeffici:9,test_compute_parameters_for_nod:7,test_compute_row_delta_in_all_fram:10,test_compute_row_delta_in_all_frames_not_init_sort:10,test_compute_row_delta_single_samples_fram:10,test_dataset_id:10,test_edges_oper:9,test_equ:9,test_fast_init:[7,9],test_file_path:10,test_filter_cims_with_mask:9,test_find:10,test_generate_possible_sub_sets_of_s:7,test_get_node_id:9,test_get_node_indx:9,test_get_ordered_by_indx_set_of_par:9,test_get_parents_by_id:9,test_get_positional_node_indx:9,test_get_states_numb:9,test_hill_climbing_search:6,test_import_data:10,test_import_sampled_cim:10,test_import_structur:10,test_import_vari:10,test_init:[7,9,10],test_init_not_filled_dataframs:9,test_init_not_initialized_import:9,test_json_import:6,test_networkgraph:6,test_normalize_trajectori:10,test_normalize_trajectories_wrong_indx:10,test_normalize_trajectories_wrong_kei:10,test_ord:10,test_par:2,test_parameters_estim:6,test_put:10,test_read_json_file_found:10,test_read_json_file_not_found:10,test_repr:9,test_sample_import:6,test_sample_path:6,test_save_plot_estimated_graph:7,test_save_result:7,test_setofcim:6,test_structur:[6,8],test_structure_1:7,test_structure_2:7,test_structure_3:[7,8],test_structure_constraint_based_estim:6,test_structure_estim:6,test_structure_monoprocesso:7,test_structure_score_based_estim:6,test_tabu_search:6,test_tim:7,test_trajectori:6,testcach:10,testcas:[7,8,9,10],testconditionalintensitymatrix:9,testhillclimbingsearch:8,testjsonimport:10,testnetworkgraph:9,testparametersestimatior:7,testsampleimport:10,testsamplepath:9,testsetofcim:9,teststructur:9,teststructureconstraintbasedestim:7,teststructureestim:7,teststructurescorebasedestim:7,testtabusearch:8,testtrajectori:9,tha:5,theta:2,thi:[2,4,5,12],three:12,threshold:2,thumb:2,thumb_threshold:2,thumb_valu:2,time:[2,4,5,12],time_filt:4,time_kei:5,time_scalar_indexing_strucur:4,timestamp:5,to_nod:5,tot_vars_count:[2,3],total:[2,4],total_variables_count:4,total_variables_numb:4,traj:5,trajecory_head:5,trajectori:[0,1,2,5,12,13,14],trajectories_kei:5,trajectory_list:5,trajectri:12,transit:[2,4,5],transition_filt:4,transition_matric:4,transition_scalar_indexing_structur:4,tri:5,tupl:4,tutori:5,two:2,type:[2,3,4,5,12],union:5,uniqu:5,unittest:[7,8,9,10],unus:4,usag:[13,14],use:[2,12],used:[2,3,4,5],using:[2,3,4,5],util:[0,1,4,6,13,14],valid:2,valu:[2,3,4,5,9,12],values_list:12,var_id:2,variabl:[2,3,4,5,12],variable_cardin:5,variable_cim_xu_marginal_likelihood_q:2,variable_cim_xu_marginal_likelihood_theta:2,variable_label:5,variables_kei:5,variables_label:5,vector:[2,4],want:12,when:2,where:5,which:[2,3,4,5],whl:12,who:2,without:[2,3],you:[2,5,12],your:[13,14]},titles:["PyCTBN package","PyCTBN.PyCTBN package","PyCTBN.PyCTBN.estimators package","PyCTBN.PyCTBN.optimizers package","PyCTBN.PyCTBN.structure_graph package","PyCTBN.PyCTBN.utility package","PyCTBN.tests package","PyCTBN.tests.estimators package","PyCTBN.tests.optimizers package","PyCTBN.tests.structure_graph package","PyCTBN.tests.utility package","basic_main module","Examples","Welcome to PyCTBN\u2019s documentation!","PyCTBN","setup module"],titleterms:{"import":12,abstract_import:5,basic_main:11,cach:5,conditional_intensity_matrix:4,constraint_based_optim:3,content:[0,1,2,3,4,5,6,7,8,9,10],data:12,document:13,estim:[2,7,12],exampl:12,fam_score_calcul:2,hill_climbing_search:3,implement:12,indic:13,instal:12,json_import:5,modul:[0,1,2,3,4,5,6,7,8,9,10,11,15],network_graph:4,optim:[3,8],own:12,packag:[0,1,2,3,4,5,6,7,8,9,10],paramet:12,parameters_estim:2,pyctbn:[0,1,2,3,4,5,6,7,8,9,10,13,14],sample_import:5,sample_path:4,set_of_cim:4,setup:15,structur:[4,12],structure_constraint_based_estim:2,structure_estim:2,structure_graph:[4,9],structure_score_based_estim:2,submodul:[0,2,3,4,5,7,8,9,10],subpackag:[0,1,6],tabl:13,tabu_search:3,test:[6,7,8,9,10],test_cach:10,test_cim:9,test_hill_climbing_search:8,test_json_import:10,test_networkgraph:9,test_parameters_estim:7,test_sample_import:10,test_sample_path:9,test_setofcim:9,test_structur:9,test_structure_constraint_based_estim:7,test_structure_estim:7,test_structure_score_based_estim:7,test_tabu_search:8,test_trajectori:9,trajectori:4,usag:12,util:[5,10],welcom:13,your:12}}) \ No newline at end of file diff --git a/docs/PyCTBN.PyCTBN.estimators.html b/docs/PyCTBN.PyCTBN.estimators.html index a316357..b76ff0c 100644 --- a/docs/PyCTBN.PyCTBN.estimators.html +++ b/docs/PyCTBN.PyCTBN.estimators.html @@ -400,25 +400,23 @@ in the graph _net_g
  • exp_test_alfa (float) – the significance level for the exponential Hp test

  • chi_test_alfa (float) – the significance level for the chi Hp test

  • known_edges (List) – the prior known edges in the net structure if present

  • +
  • thumb_threshold (int) – the threshold value to consider a valid independence test

  • -
    Param
    -

    thumb_threshold: the threshold value to consider a valid independence test

    -
    -
    _nodes
    -

    the nodes labels

    +
    _nodes
    +

    the nodes labels

    -
    _nodes_vals
    -

    the nodes cardinalities

    +
    _nodes_vals
    +

    the nodes cardinalities

    -
    _nodes_indxs
    -

    the nodes indexes

    +
    _nodes_indxs
    +

    the nodes indexes

    -
    _complete_graph
    -

    the complete directed graph built using the nodes labels in _nodes

    +
    _complete_graph
    +

    the complete directed graph built using the nodes labels in _nodes

    -
    _cache
    -

    the Cache object

    +
    _cache
    +

    the Cache object

    diff --git a/docs/searchindex.js b/docs/searchindex.js index e239f42..c34509d 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({docnames:["PyCTBN","PyCTBN.PyCTBN","PyCTBN.PyCTBN.estimators","PyCTBN.PyCTBN.optimizers","PyCTBN.PyCTBN.structure_graph","PyCTBN.PyCTBN.utility","PyCTBN.tests","PyCTBN.tests.estimators","PyCTBN.tests.optimizers","PyCTBN.tests.structure_graph","PyCTBN.tests.utility","basic_main","examples","index","modules","setup"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":3,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,sphinx:56},filenames:["PyCTBN.rst","PyCTBN.PyCTBN.rst","PyCTBN.PyCTBN.estimators.rst","PyCTBN.PyCTBN.optimizers.rst","PyCTBN.PyCTBN.structure_graph.rst","PyCTBN.PyCTBN.utility.rst","PyCTBN.tests.rst","PyCTBN.tests.estimators.rst","PyCTBN.tests.optimizers.rst","PyCTBN.tests.structure_graph.rst","PyCTBN.tests.utility.rst","basic_main.rst","examples.rst","index.rst","modules.rst","setup.rst"],objects:{"":{PyCTBN:[0,0,0,"-"]},"PyCTBN.PyCTBN":{estimators:[2,0,0,"-"],optimizers:[3,0,0,"-"],structure_graph:[4,0,0,"-"],utility:[5,0,0,"-"]},"PyCTBN.PyCTBN.estimators":{fam_score_calculator:[2,0,0,"-"],parameters_estimator:[2,0,0,"-"],structure_constraint_based_estimator:[2,0,0,"-"],structure_estimator:[2,0,0,"-"],structure_score_based_estimator:[2,0,0,"-"]},"PyCTBN.PyCTBN.estimators.fam_score_calculator":{FamScoreCalculator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.fam_score_calculator.FamScoreCalculator":{get_fam_score:[2,2,1,""],marginal_likelihood_q:[2,2,1,""],marginal_likelihood_theta:[2,2,1,""],single_cim_xu_marginal_likelihood_q:[2,2,1,""],single_cim_xu_marginal_likelihood_theta:[2,2,1,""],single_internal_cim_xxu_marginal_likelihood_theta:[2,2,1,""],variable_cim_xu_marginal_likelihood_q:[2,2,1,""],variable_cim_xu_marginal_likelihood_theta:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator":{ParametersEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator.ParametersEstimator":{compute_parameters_for_node:[2,2,1,""],compute_state_res_time_for_node:[2,2,1,""],compute_state_transitions_for_a_node:[2,2,1,""],fast_init:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator":{StructureConstraintBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator":{complete_test:[2,2,1,""],compute_thumb_value:[2,2,1,""],ctpc_algorithm:[2,2,1,""],estimate_structure:[2,2,1,""],independence_test:[2,2,1,""],one_iteration_of_CTPC_algorithm:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator":{StructureEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator":{adjacency_matrix:[2,2,1,""],build_complete_graph:[2,2,1,""],build_removable_edges_matrix:[2,2,1,""],estimate_structure:[2,2,1,""],generate_possible_sub_sets_of_size:[2,2,1,""],save_plot_estimated_structure_graph:[2,2,1,""],save_results:[2,2,1,""],spurious_edges:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator":{StructureScoreBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator.StructureScoreBasedEstimator":{estimate_parents:[2,2,1,""],estimate_structure:[2,2,1,""],get_score_from_graph:[2,2,1,""]},"PyCTBN.PyCTBN.optimizers":{constraint_based_optimizer:[3,0,0,"-"],hill_climbing_search:[3,0,0,"-"],optimizer:[3,0,0,"-"],tabu_search:[3,0,0,"-"]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer":{ConstraintBasedOptimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer.ConstraintBasedOptimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search":{HillClimbing:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search.HillClimbing":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer":{Optimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer.Optimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search":{TabuSearch:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search.TabuSearch":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.structure_graph":{conditional_intensity_matrix:[4,0,0,"-"],network_graph:[4,0,0,"-"],sample_path:[4,0,0,"-"],set_of_cims:[4,0,0,"-"],structure:[4,0,0,"-"],trajectory:[4,0,0,"-"]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix":{ConditionalIntensityMatrix:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix":{cim:[4,2,1,""],compute_cim_coefficients:[4,2,1,""],state_residence_times:[4,2,1,""],state_transition_matrix:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph":{NetworkGraph:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph":{add_edges:[4,2,1,""],add_nodes:[4,2,1,""],build_p_comb_structure_for_a_node:[4,2,1,""],build_time_columns_filtering_for_a_node:[4,2,1,""],build_time_scalar_indexing_structure_for_a_node:[4,2,1,""],build_transition_filtering_for_a_node:[4,2,1,""],build_transition_scalar_indexing_structure_for_a_node:[4,2,1,""],clear_indexing_filtering_structures:[4,2,1,""],edges:[4,2,1,""],fast_init:[4,2,1,""],get_node_indx:[4,2,1,""],get_ordered_by_indx_set_of_parents:[4,2,1,""],get_parents_by_id:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],has_edge:[4,2,1,""],nodes:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_values:[4,2,1,""],p_combs:[4,2,1,""],remove_edges:[4,2,1,""],remove_node:[4,2,1,""],time_filtering:[4,2,1,""],time_scalar_indexing_strucure:[4,2,1,""],transition_filtering:[4,2,1,""],transition_scalar_indexing_structure:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path":{SamplePath:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath":{build_structure:[4,2,1,""],build_trajectories:[4,2,1,""],clear_memory:[4,2,1,""],has_prior_net_structure:[4,2,1,""],structure:[4,2,1,""],total_variables_count:[4,2,1,""],trajectories:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims":{SetOfCims:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims":{actual_cims:[4,2,1,""],build_cims:[4,2,1,""],build_times_and_transitions_structures:[4,2,1,""],filter_cims_with_mask:[4,2,1,""],get_cims_number:[4,2,1,""],p_combs:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.structure":{Structure:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.structure.Structure":{add_edge:[4,2,1,""],clean_structure_edges:[4,2,1,""],contains_edge:[4,2,1,""],edges:[4,2,1,""],get_node_id:[4,2,1,""],get_node_indx:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_labels:[4,2,1,""],nodes_values:[4,2,1,""],remove_edge:[4,2,1,""],remove_node:[4,2,1,""],total_variables_number:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory":{Trajectory:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory.Trajectory":{complete_trajectory:[4,2,1,""],size:[4,2,1,""],times:[4,2,1,""],trajectory:[4,2,1,""]},"PyCTBN.PyCTBN.utility":{abstract_importer:[5,0,0,"-"],cache:[5,0,0,"-"],json_importer:[5,0,0,"-"],sample_importer:[5,0,0,"-"]},"PyCTBN.PyCTBN.utility.abstract_importer":{AbstractImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter":{build_list_of_samples_array:[5,2,1,""],build_sorter:[5,2,1,""],clear_concatenated_frame:[5,2,1,""],compute_row_delta_in_all_samples_frames:[5,2,1,""],compute_row_delta_sigle_samples_frame:[5,2,1,""],concatenated_samples:[5,2,1,""],dataset_id:[5,2,1,""],file_path:[5,2,1,""],sorter:[5,2,1,""],structure:[5,2,1,""],variables:[5,2,1,""]},"PyCTBN.PyCTBN.utility.cache":{Cache:[5,1,1,""]},"PyCTBN.PyCTBN.utility.cache.Cache":{clear:[5,2,1,""],find:[5,2,1,""],put:[5,2,1,""]},"PyCTBN.PyCTBN.utility.json_importer":{JsonImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.json_importer.JsonImporter":{build_sorter:[5,2,1,""],clear_data_frame_list:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""],import_sampled_cims:[5,2,1,""],import_structure:[5,2,1,""],import_trajectories:[5,2,1,""],import_variables:[5,2,1,""],normalize_trajectories:[5,2,1,""],one_level_normalizing:[5,2,1,""],read_json_file:[5,2,1,""]},"PyCTBN.PyCTBN.utility.sample_importer":{SampleImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.sample_importer.SampleImporter":{build_sorter:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""]},"PyCTBN.tests":{estimators:[7,0,0,"-"],optimizers:[8,0,0,"-"],structure_graph:[9,0,0,"-"],utility:[10,0,0,"-"]},"PyCTBN.tests.estimators":{test_parameters_estimator:[7,0,0,"-"],test_structure_constraint_based_estimator:[7,0,0,"-"],test_structure_estimator:[7,0,0,"-"],test_structure_score_based_estimator:[7,0,0,"-"]},"PyCTBN.tests.estimators.test_parameters_estimator":{TestParametersEstimatior:[7,1,1,""]},"PyCTBN.tests.estimators.test_parameters_estimator.TestParametersEstimatior":{aux_import_sampled_cims:[7,2,1,""],cim_equality_test:[7,2,1,""],equality_of_cims_of_node:[7,2,1,""],setUpClass:[7,2,1,""],test_compute_parameters_for_node:[7,2,1,""],test_fast_init:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator":{TestStructureConstraintBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator.TestStructureConstraintBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_estimator":{TestStructureEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_estimator.TestStructureEstimator":{setUpClass:[7,2,1,""],test_adjacency_matrix:[7,2,1,""],test_build_complete_graph:[7,2,1,""],test_build_removable_edges_matrix:[7,2,1,""],test_generate_possible_sub_sets_of_size:[7,2,1,""],test_init:[7,2,1,""],test_save_plot_estimated_graph:[7,2,1,""],test_save_results:[7,2,1,""],test_time:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator":{TestStructureScoreBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator.TestStructureScoreBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""],test_structure_monoprocesso:[7,2,1,""]},"PyCTBN.tests.optimizers":{test_hill_climbing_search:[8,0,0,"-"],test_tabu_search:[8,0,0,"-"]},"PyCTBN.tests.optimizers.test_hill_climbing_search":{TestHillClimbingSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_hill_climbing_search.TestHillClimbingSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.optimizers.test_tabu_search":{TestTabuSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_tabu_search.TestTabuSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.structure_graph":{test_cim:[9,0,0,"-"],test_networkgraph:[9,0,0,"-"],test_sample_path:[9,0,0,"-"],test_setofcims:[9,0,0,"-"],test_structure:[9,0,0,"-"],test_trajectory:[9,0,0,"-"]},"PyCTBN.tests.structure_graph.test_cim":{TestConditionalIntensityMatrix:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_cim.TestConditionalIntensityMatrix":{setUpClass:[9,2,1,""],test_compute_cim_coefficients:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph":{TestNetworkGraph:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph.TestNetworkGraph":{aux_build_p_combs_structure:[9,2,1,""],aux_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],aux_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],aux_build_transition_columns_filtering_structure:[9,2,1,""],aux_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_add_edges:[9,2,1,""],test_add_nodes:[9,2,1,""],test_build_p_combs_structure:[9,2,1,""],test_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],test_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],test_build_transition_columns_filtering_structure:[9,2,1,""],test_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],test_fast_init:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_ordered_by_indx_set_of_parents:[9,2,1,""],test_get_parents_by_id:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_sample_path":{TestSamplePath:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_sample_path.TestSamplePath":{setUpClass:[9,2,1,""],test_buid_samplepath_no_concatenated_samples:[9,2,1,""],test_buid_samplepath_no_variables:[9,2,1,""],test_build_saplepath_no_prior_net_structure:[9,2,1,""],test_build_structure:[9,2,1,""],test_build_structure_bad_sorter:[9,2,1,""],test_build_trajectories:[9,2,1,""],test_init:[9,2,1,""],test_init_not_filled_dataframse:[9,2,1,""],test_init_not_initialized_importer:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_setofcims":{TestSetOfCims:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_setofcims.TestSetOfCims":{another_filtering_method:[9,2,1,""],aux_test_build_cims:[9,2,1,""],aux_test_init:[9,2,1,""],build_p_comb_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_build_cims:[9,2,1,""],test_filter_cims_with_mask:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_structure":{TestStructure:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_structure.TestStructure":{setUpClass:[9,2,1,""],test_edges_operations:[9,2,1,""],test_equality:[9,2,1,""],test_get_node_id:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_positional_node_indx:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_trajectory":{TestTrajectory:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_trajectory.TestTrajectory":{setUpClass:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.utility":{test_cache:[10,0,0,"-"],test_json_importer:[10,0,0,"-"],test_sample_importer:[10,0,0,"-"]},"PyCTBN.tests.utility.test_cache":{TestCache:[10,1,1,""]},"PyCTBN.tests.utility.test_cache.TestCache":{test_clear:[10,2,1,""],test_find:[10,2,1,""],test_init:[10,2,1,""],test_put:[10,2,1,""]},"PyCTBN.tests.utility.test_json_importer":{TestJsonImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_json_importer.TestJsonImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_build_sorter:[10,2,1,""],test_clear_concatenated_frame:[10,2,1,""],test_clear_data_frame_list:[10,2,1,""],test_compute_row_delta_in_all_frames:[10,2,1,""],test_compute_row_delta_in_all_frames_not_init_sorter:[10,2,1,""],test_compute_row_delta_single_samples_frame:[10,2,1,""],test_dataset_id:[10,2,1,""],test_file_path:[10,2,1,""],test_import_data:[10,2,1,""],test_import_sampled_cims:[10,2,1,""],test_import_structure:[10,2,1,""],test_import_variables:[10,2,1,""],test_init:[10,2,1,""],test_normalize_trajectories:[10,2,1,""],test_normalize_trajectories_wrong_indx:[10,2,1,""],test_normalize_trajectories_wrong_key:[10,2,1,""],test_read_json_file_found:[10,2,1,""],test_read_json_file_not_found:[10,2,1,""]},"PyCTBN.tests.utility.test_sample_importer":{TestSampleImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_sample_importer.TestSampleImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_init:[10,2,1,""],test_order:[10,2,1,""]},PyCTBN:{PyCTBN:[1,0,0,"-"],tests:[6,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method"},terms:{"abstract":[2,3,4,5,12],"boolean":[2,4],"case":[7,8,9,10],"class":[2,3,4,5,7,8,9,10,12],"default":[2,3],"float":2,"function":2,"import":[4,5,13,14],"int":[2,3,4,5],"null":2,"return":[2,3,4,5,9,12],"static":[2,4],"super":12,"true":[2,12],"var":12,HAS:5,Has:[2,4],NOT:2,The:[2,4,5,12],Use:[2,12],__actual_cach:5,__init__:12,__list_of_sets_of_par:5,_actual_cim:4,_actual_trajectori:4,_aggregated_info_about_nodes_par:4,_array_indx:5,_cach:2,_cim:4,_complete_graph:2,_df_samples_list:[5,12],_df_structur:5,_df_variabl:[5,12],_file_path:12,_graph:[4,12],_import:4,_net_graph:2,_node:2,_node_id:4,_nodes_indx:2,_nodes_v:2,_p_combs_structur:4,_raw_data:5,_sample_path:2,_single_set_of_cim:2,_sorter:[5,12],_state_residence_tim:4,_structur:4,_structure_label:5,_time:4,_time_filt:4,_time_scalar_indexing_structur:4,_total_variables_count:4,_total_variables_numb:4,_trajectori:4,_transition_filt:4,_transition_matric:4,_transition_scalar_indexing_structur:4,_variables_label:5,abc:[3,5],about:[3,4],abstract_import:[0,1,4,13,14],abstractimport:[4,5,12],act:5,actual:[2,4],actual_cim:[4,12],add:[4,5],add_edg:4,add_nod:4,added:2,addit:2,adjac:[2,12],adjacency_matrix:[2,12],after:5,against:2,aggreg:4,algorithm:[2,3,12],all:[2,3,4,5,9,12],alpha_xu:2,alpha_xxu:2,alreadi:[5,12],also:[2,4],ani:[2,3],anoth:4,another_filtering_method:9,approach:2,arc:5,arrai:[2,4,5,12],assign:2,assum:2,aux_build_p_combs_structur:9,aux_build_time_columns_filtering_structure_for_a_nod:9,aux_build_time_scalar_indexing_structure_for_a_nod:9,aux_build_transition_columns_filtering_structur:9,aux_build_transition_scalar_indexing_structure_for_a_nod:9,aux_import_sampled_cim:7,aux_test_build_cim:9,aux_test_init:9,axi:12,base:[2,3,4,5,7,8,9,10],bayesian:2,befor:[2,3,7,8,9,10],belong:2,best:2,between:5,bool:[2,4],both:[2,5],bound:4,build:[2,4,5,9,12],build_cim:4,build_complete_graph:2,build_list_of_samples_arrai:5,build_p_comb_structure_for_a_nod:[4,9],build_removable_edges_matrix:2,build_sort:[5,12],build_structur:[4,12],build_time_columns_filtering_for_a_nod:4,build_time_scalar_indexing_structure_for_a_nod:4,build_times_and_transitions_structur:4,build_trajectori:[4,12],build_transition_filtering_for_a_nod:4,build_transition_scalar_indexing_structure_for_a_nod:4,built:2,cach:[0,1,2,13,14],calcul:2,call:[5,12],cardin:[2,4,5,9],cardinalit:[4,5],caridin:4,caridinalit:4,chang:[4,5],check:4,chi:2,chi_test:2,chi_test_alfa:2,child:[2,3],child_indx:2,child_states_numb:2,child_val:2,cim1:[2,7],cim2:[2,7],cim:[2,4,5,12],cim_equality_test:7,cims_kei:5,cims_label:7,classmethod:[7,8,9,10],clean_structure_edg:4,clear:[4,5],clear_concatenated_fram:5,clear_data_frame_list:5,clear_indexing_filtering_structur:4,clear_memori:4,climb:[2,3],coeffici:4,col:4,color:2,cols_filt:2,column:[2,4,5,12],columns_head:5,comb:4,combin:[4,5,9],combinatori:[4,9],common:2,complet:[2,4,5],complete_test:2,complete_trajectori:4,comput:[2,3,4,5,12],compute_cim_coeffici:4,compute_parameters_for_nod:[2,12],compute_row_delta_in_all_samples_fram:[5,12],compute_row_delta_sigle_samples_fram:5,compute_state_res_time_for_nod:2,compute_state_transitions_for_a_nod:2,compute_thumb_valu:2,concatanated_sampl:5,concaten:[4,5],concatenated_sampl:5,condit:4,conditional_intensity_matrix:[0,1,2,13,14],conditionalintensitymatrix:[2,4],consid:[2,4],constraint:2,constraint_based_optim:[0,1,13,14],constraintbasedoptim:3,construct:[4,5,12],conta:5,contain:[2,4,5,9],contains_edg:4,content:[13,14],convert:[2,5],copi:5,core:5,correct:[4,5],could:2,count:4,creat:[2,4,12],csv:12,csvimport:12,ctbn:2,ctpc:[2,3,12],ctpc_algorithm:[2,12],current:[2,3,5],cut:5,dafram:5,data:[2,3,4,5,13,14],datafram:[4,5,12],dataset:[3,4,5],dataset_id:[5,12],datfram:5,def:12,defin:5,definit:5,defualt:2,delta:[2,4,5],demonstr:12,describ:5,desir:[2,4],df_samples_list:5,dict:[5,12],dictionari:5,differ:5,differt:2,digraph:2,dimens:4,dir:12,direct:[2,4],directli:5,disabl:[2,3],disable_multiprocess:2,distribuit:2,doc:5,doubl:4,download:12,drop:12,duplic:4,dyn:12,each:[2,3,5],edg:[2,4,5,12],edges_list:4,end:5,entir:2,equal:4,equality_of_cims_of_nod:7,est:12,estim:[0,1,3,4,6,13,14],estimate_par:2,estimate_structur:2,estimated_cim:7,everi:[4,5],exam:12,exampl:[5,13,14],exclud:2,exctract:5,exist:5,exp_test_alfa:2,exponenti:2,expos:5,extend:12,extens:[2,5],extract:[4,5],fals:2,fam_score_calcul:[0,1,13,14],famscor:2,famscorecalcul:2,fast_init:[2,4,12],file:[2,5,12],file_path:[2,5,12],filepath:5,fill:[2,12],filter:[2,4],filter_cims_with_mask:4,find:[2,5],first:[2,12],fixtur:[7,8,9,10],follow:[4,5],form:4,format:12,formula:2,found:5,frame:5,from:[4,5,12],from_nod:5,gener:2,generate_possible_sub_sets_of_s:2,get:[2,5],get_cims_numb:4,get_fam_scor:2,get_node_id:4,get_node_indx:4,get_ordered_by_indx_set_of_par:4,get_parents_by_id:4,get_positional_node_indx:4,get_score_from_graph:2,get_states_numb:4,given:[2,4,5],glob:12,graph:[2,4,9,12],graph_struct:4,graphic:2,grid:[4,9],grpah:12,has:[5,12],has_edg:4,has_prior_net_structur:4,have:5,header:5,header_column:5,hill:[2,3],hill_climbing_search:[0,1,13,14],hillclimb:3,hold:[2,4],hook:[7,8,9,10],how:5,hyperparamet:2,hypothesi:2,identifi:[2,4,5],iff:2,implement:[3,5,13,14],import_data:[5,12],import_sampled_cim:5,import_structur:5,import_trajectori:5,import_vari:[5,12],improv:[2,3],includ:2,independ:2,independence_test:2,index:[2,4,5,12,13],indic:4,indx:5,info:[4,12],inform:[3,4],init:12,initi:[2,4,5,12],inplac:12,insid:12,instal:[13,14],interest:4,interfac:3,intes:4,iter:[2,3],iterations_numb:[2,3],its:[2,3],join:12,json:[2,5,12],json_import:[0,1,13,14],jsonarrai:5,jsonimport:[5,12],keep:[2,3,5],kei:5,kind:2,knowledg:2,known:2,known_edg:2,label:[2,3,4,5],lenght:[2,3],level:[2,5],likelihood:2,list:[2,3,4,5,12],list_of_column:4,list_of_edg:4,list_of_nod:4,load:5,loop:2,m_xu_suff_stat:2,m_xxu_suff_stat:2,main:12,margin:2,marginal_likelihood_q:2,marginal_likelihood_theta:2,mask:[4,9],mask_arr:4,matric:[2,4],matrix:[2,4,5,9,12],max_par:[2,3],maximum:[2,3],member:[4,5],mention:4,merg:5,method:[2,5,7,8,9,10],methodnam:[7,8,9,10],model:2,modul:[13,14],multipl:5,multiprocess:2,name:[2,4,5,12],ndarrai:[2,4,5],necessari:[2,4,5],nest:5,net:[2,3,4,5,12],net_graph:2,network:[2,4,5],network_graph:[0,1,2,13,14],networkgraph:[2,4,12],networkx:2,node:[2,3,4,5,9,12],node_id:[2,3,4,9],node_index:4,node_indx:[2,4],node_st:[4,9],node_states_numb:[4,9],nodes_index:4,nodes_indexes_arr:4,nodes_label:4,nodes_labels_list:4,nodes_numb:4,nodes_vals_arr:4,nodes_valu:[4,12],none:[2,3,4,5,7,9,10,12],normal:5,normalize_trajectori:5,number:[2,3,4],numpi:[2,4,5,9],obj:[10,12],object:[2,3,4,5,12],one:[4,5],one_iteration_of_ctpc_algorithm:2,one_level_norm:5,onli:5,oper:2,optim:[0,1,2,6,13,14],optimize_structur:3,option:[2,3],order:[2,5,10],origin:5,original_cols_numb:4,otherwis:[2,5],out:5,outer:[5,12],over:2,own:[13,14],p_comb:[4,9],p_indx:[4,9],p_val:9,p_valu:9,packag:[13,14],page:13,panda:[5,12],param:[2,4],paramet:[2,3,4,5,9,13,14],parameters_estim:[0,1,13,14],parametersestim:[2,12],parent:[2,3,4,5],parent_indx:2,parent_label:2,parent_set:2,parent_set_v:2,parent_v:2,parent_valu:9,parents_cardin:4,parents_comb:5,parents_index:4,parents_indx:9,parents_label:[4,9],parents_states_numb:[4,9],parents_v:[4,9],parents_valu:[4,9],part:2,particular:[2,5],pass:12,path:[2,5,12],patienc:[2,3],peest:12,perform:2,pip:12,place:5,plot:2,png:2,posit:[4,5],possibl:[2,4],predict:3,prepar:5,present:[2,5],print:12,prior:[2,12],prior_net_structur:5,process:[2,3,4,5],properli:5,properti:[4,5],put:5,pyctbn:12,q_xx:4,rappres:4,raw:5,raw_data:5,read:[5,12],read_csv:12,read_csv_fil:12,read_fil:12,read_json_fil:5,real:[2,4,5,12],red:2,refer:[4,5],reject:2,rel:4,relat:5,releas:12,remain:5,remov:[2,4,5],remove_edg:4,remove_nod:4,repres:4,represent:2,res:4,resid:[2,4],result:[2,5,12],rtype:4,rule:[2,3],run:[7,8,9,10],runtest:[7,8,9,10],same:5,sampl:[4,5,12],sample_fram:[5,12],sample_import:[0,1,13,14],sample_path:[0,1,2,13,14],sampled_cim:7,sampleimport:5,samplepath:[2,4,12],samples_label:5,save:[2,12],save_plot_estimated_structure_graph:2,save_result:[2,12],scalar_index:2,scalar_indexes_struct:2,score:2,se1:12,search:[2,3,13],second:2,see:5,select:12,self:[2,5,12],sep:2,sep_set:2,set:[2,4,5,7,8,9,10],set_of_cim:[0,1,2,5,13,14],setofcim:[2,4,5,12],setupclass:[7,8,9,10],shift:[4,5],shifted_cols_head:5,show:2,signific:2,simbol:5,simpl:12,simpli:12,sinc:4,single_cim_xu_marginal_likelihood_q:2,single_cim_xu_marginal_likelihood_theta:2,single_internal_cim_xxu_marginal_likelihood_theta:2,size:[2,4],socim:5,sofc1:12,sorter:5,specif:[2,4,12],spuriou:2,spurious_edg:2,start:5,state:[2,4],state_res_tim:4,state_residence_tim:4,state_transition_matrix:4,statist:2,stop:[2,3],str:[2,3,4,5,12],string:[2,3,4,5],structur:[0,1,2,3,5,9,13,14],structure_constraint_based_estim:[0,1,13,14],structure_estim:[0,1,3,13,14],structure_estimation_exampl:12,structure_graph:[0,1,2,5,6,13,14],structure_label:5,structure_score_based_estim:[0,1,13,14],structureconstraintbasedestim:2,structureestim:[2,3,12],structurescorebasedestim:2,structut:4,style:2,submodul:[1,6,13,14],subpackag:[13,14],subset:2,suffici:2,suffuci:2,symbol:[4,5],synthet:5,t_xu_suff_stat:2,tabu:[2,3],tabu_length:[2,3],tabu_rules_dur:[2,3],tabu_search:[0,1,13,14],tabusearch:3,take:12,tar:12,task:[2,4],tau_xu:2,ternari:12,test:2,test_add_edg:9,test_add_nod:9,test_adjacency_matrix:7,test_buid_samplepath_no_concatenated_sampl:9,test_buid_samplepath_no_vari:9,test_build_cim:9,test_build_complete_graph:7,test_build_p_combs_structur:9,test_build_removable_edges_matrix:7,test_build_saplepath_no_prior_net_structur:9,test_build_sort:10,test_build_structur:9,test_build_structure_bad_sort:9,test_build_time_columns_filtering_structure_for_a_nod:9,test_build_time_scalar_indexing_structure_for_a_nod:9,test_build_trajectori:9,test_build_transition_columns_filtering_structur:9,test_build_transition_scalar_indexing_structure_for_a_nod:9,test_cach:6,test_child:2,test_cim:6,test_clear:10,test_clear_concatenated_fram:10,test_clear_data_frame_list:10,test_compute_cim_coeffici:9,test_compute_parameters_for_nod:7,test_compute_row_delta_in_all_fram:10,test_compute_row_delta_in_all_frames_not_init_sort:10,test_compute_row_delta_single_samples_fram:10,test_dataset_id:10,test_edges_oper:9,test_equ:9,test_fast_init:[7,9],test_file_path:10,test_filter_cims_with_mask:9,test_find:10,test_generate_possible_sub_sets_of_s:7,test_get_node_id:9,test_get_node_indx:9,test_get_ordered_by_indx_set_of_par:9,test_get_parents_by_id:9,test_get_positional_node_indx:9,test_get_states_numb:9,test_hill_climbing_search:6,test_import_data:10,test_import_sampled_cim:10,test_import_structur:10,test_import_vari:10,test_init:[7,9,10],test_init_not_filled_dataframs:9,test_init_not_initialized_import:9,test_json_import:6,test_networkgraph:6,test_normalize_trajectori:10,test_normalize_trajectories_wrong_indx:10,test_normalize_trajectories_wrong_kei:10,test_ord:10,test_par:2,test_parameters_estim:6,test_put:10,test_read_json_file_found:10,test_read_json_file_not_found:10,test_repr:9,test_sample_import:6,test_sample_path:6,test_save_plot_estimated_graph:7,test_save_result:7,test_setofcim:6,test_structur:[6,8],test_structure_1:7,test_structure_2:7,test_structure_3:[7,8],test_structure_constraint_based_estim:6,test_structure_estim:6,test_structure_monoprocesso:7,test_structure_score_based_estim:6,test_tabu_search:6,test_tim:7,test_trajectori:6,testcach:10,testcas:[7,8,9,10],testconditionalintensitymatrix:9,testhillclimbingsearch:8,testjsonimport:10,testnetworkgraph:9,testparametersestimatior:7,testsampleimport:10,testsamplepath:9,testsetofcim:9,teststructur:9,teststructureconstraintbasedestim:7,teststructureestim:7,teststructurescorebasedestim:7,testtabusearch:8,testtrajectori:9,tha:5,theta:2,thi:[2,4,5,12],three:12,threshold:2,thumb:2,thumb_threshold:2,thumb_valu:2,time:[2,4,5,12],time_filt:4,time_kei:5,time_scalar_indexing_strucur:4,timestamp:5,to_nod:5,tot_vars_count:[2,3],total:[2,4],total_variables_count:4,total_variables_numb:4,traj:5,trajecory_head:5,trajectori:[0,1,2,5,12,13,14],trajectories_kei:5,trajectory_list:5,trajectri:12,transit:[2,4,5],transition_filt:4,transition_matric:4,transition_scalar_indexing_structur:4,tri:5,tupl:4,tutori:5,two:2,type:[2,3,4,5,12],union:5,uniqu:5,unittest:[7,8,9,10],unus:4,usag:[13,14],use:[2,12],used:[2,3,4,5],using:[2,3,4,5],util:[0,1,4,6,13,14],valid:2,valu:[2,3,4,5,9,12],values_list:12,var_id:2,variabl:[2,3,4,5,12],variable_cardin:5,variable_cim_xu_marginal_likelihood_q:2,variable_cim_xu_marginal_likelihood_theta:2,variable_label:5,variables_kei:5,variables_label:5,vector:[2,4],want:12,when:2,where:5,which:[2,3,4,5],whl:12,who:2,without:[2,3],you:[2,5,12],your:[13,14]},titles:["PyCTBN package","PyCTBN.PyCTBN package","PyCTBN.PyCTBN.estimators package","PyCTBN.PyCTBN.optimizers package","PyCTBN.PyCTBN.structure_graph package","PyCTBN.PyCTBN.utility package","PyCTBN.tests package","PyCTBN.tests.estimators package","PyCTBN.tests.optimizers package","PyCTBN.tests.structure_graph package","PyCTBN.tests.utility package","basic_main module","Examples","Welcome to PyCTBN\u2019s documentation!","PyCTBN","setup module"],titleterms:{"import":12,abstract_import:5,basic_main:11,cach:5,conditional_intensity_matrix:4,constraint_based_optim:3,content:[0,1,2,3,4,5,6,7,8,9,10],data:12,document:13,estim:[2,7,12],exampl:12,fam_score_calcul:2,hill_climbing_search:3,implement:12,indic:13,instal:12,json_import:5,modul:[0,1,2,3,4,5,6,7,8,9,10,11,15],network_graph:4,optim:[3,8],own:12,packag:[0,1,2,3,4,5,6,7,8,9,10],paramet:12,parameters_estim:2,pyctbn:[0,1,2,3,4,5,6,7,8,9,10,13,14],sample_import:5,sample_path:4,set_of_cim:4,setup:15,structur:[4,12],structure_constraint_based_estim:2,structure_estim:2,structure_graph:[4,9],structure_score_based_estim:2,submodul:[0,2,3,4,5,7,8,9,10],subpackag:[0,1,6],tabl:13,tabu_search:3,test:[6,7,8,9,10],test_cach:10,test_cim:9,test_hill_climbing_search:8,test_json_import:10,test_networkgraph:9,test_parameters_estim:7,test_sample_import:10,test_sample_path:9,test_setofcim:9,test_structur:9,test_structure_constraint_based_estim:7,test_structure_estim:7,test_structure_score_based_estim:7,test_tabu_search:8,test_trajectori:9,trajectori:4,usag:12,util:[5,10],welcom:13,your:12}}) \ No newline at end of file +Search.setIndex({docnames:["PyCTBN","PyCTBN.PyCTBN","PyCTBN.PyCTBN.estimators","PyCTBN.PyCTBN.optimizers","PyCTBN.PyCTBN.structure_graph","PyCTBN.PyCTBN.utility","PyCTBN.tests","PyCTBN.tests.estimators","PyCTBN.tests.optimizers","PyCTBN.tests.structure_graph","PyCTBN.tests.utility","basic_main","examples","index","modules","setup"],envversion:{"sphinx.domains.c":2,"sphinx.domains.changeset":1,"sphinx.domains.citation":1,"sphinx.domains.cpp":3,"sphinx.domains.index":1,"sphinx.domains.javascript":2,"sphinx.domains.math":2,"sphinx.domains.python":2,"sphinx.domains.rst":2,"sphinx.domains.std":1,sphinx:56},filenames:["PyCTBN.rst","PyCTBN.PyCTBN.rst","PyCTBN.PyCTBN.estimators.rst","PyCTBN.PyCTBN.optimizers.rst","PyCTBN.PyCTBN.structure_graph.rst","PyCTBN.PyCTBN.utility.rst","PyCTBN.tests.rst","PyCTBN.tests.estimators.rst","PyCTBN.tests.optimizers.rst","PyCTBN.tests.structure_graph.rst","PyCTBN.tests.utility.rst","basic_main.rst","examples.rst","index.rst","modules.rst","setup.rst"],objects:{"":{PyCTBN:[0,0,0,"-"]},"PyCTBN.PyCTBN":{estimators:[2,0,0,"-"],optimizers:[3,0,0,"-"],structure_graph:[4,0,0,"-"],utility:[5,0,0,"-"]},"PyCTBN.PyCTBN.estimators":{fam_score_calculator:[2,0,0,"-"],parameters_estimator:[2,0,0,"-"],structure_constraint_based_estimator:[2,0,0,"-"],structure_estimator:[2,0,0,"-"],structure_score_based_estimator:[2,0,0,"-"]},"PyCTBN.PyCTBN.estimators.fam_score_calculator":{FamScoreCalculator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.fam_score_calculator.FamScoreCalculator":{get_fam_score:[2,2,1,""],marginal_likelihood_q:[2,2,1,""],marginal_likelihood_theta:[2,2,1,""],single_cim_xu_marginal_likelihood_q:[2,2,1,""],single_cim_xu_marginal_likelihood_theta:[2,2,1,""],single_internal_cim_xxu_marginal_likelihood_theta:[2,2,1,""],variable_cim_xu_marginal_likelihood_q:[2,2,1,""],variable_cim_xu_marginal_likelihood_theta:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator":{ParametersEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.parameters_estimator.ParametersEstimator":{compute_parameters_for_node:[2,2,1,""],compute_state_res_time_for_node:[2,2,1,""],compute_state_transitions_for_a_node:[2,2,1,""],fast_init:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator":{StructureConstraintBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_constraint_based_estimator.StructureConstraintBasedEstimator":{complete_test:[2,2,1,""],compute_thumb_value:[2,2,1,""],ctpc_algorithm:[2,2,1,""],estimate_structure:[2,2,1,""],independence_test:[2,2,1,""],one_iteration_of_CTPC_algorithm:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator":{StructureEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_estimator.StructureEstimator":{adjacency_matrix:[2,2,1,""],build_complete_graph:[2,2,1,""],build_removable_edges_matrix:[2,2,1,""],estimate_structure:[2,2,1,""],generate_possible_sub_sets_of_size:[2,2,1,""],save_plot_estimated_structure_graph:[2,2,1,""],save_results:[2,2,1,""],spurious_edges:[2,2,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator":{StructureScoreBasedEstimator:[2,1,1,""]},"PyCTBN.PyCTBN.estimators.structure_score_based_estimator.StructureScoreBasedEstimator":{estimate_parents:[2,2,1,""],estimate_structure:[2,2,1,""],get_score_from_graph:[2,2,1,""]},"PyCTBN.PyCTBN.optimizers":{constraint_based_optimizer:[3,0,0,"-"],hill_climbing_search:[3,0,0,"-"],optimizer:[3,0,0,"-"],tabu_search:[3,0,0,"-"]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer":{ConstraintBasedOptimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.constraint_based_optimizer.ConstraintBasedOptimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search":{HillClimbing:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.hill_climbing_search.HillClimbing":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer":{Optimizer:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.optimizer.Optimizer":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search":{TabuSearch:[3,1,1,""]},"PyCTBN.PyCTBN.optimizers.tabu_search.TabuSearch":{optimize_structure:[3,2,1,""]},"PyCTBN.PyCTBN.structure_graph":{conditional_intensity_matrix:[4,0,0,"-"],network_graph:[4,0,0,"-"],sample_path:[4,0,0,"-"],set_of_cims:[4,0,0,"-"],structure:[4,0,0,"-"],trajectory:[4,0,0,"-"]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix":{ConditionalIntensityMatrix:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.conditional_intensity_matrix.ConditionalIntensityMatrix":{cim:[4,2,1,""],compute_cim_coefficients:[4,2,1,""],state_residence_times:[4,2,1,""],state_transition_matrix:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph":{NetworkGraph:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.network_graph.NetworkGraph":{add_edges:[4,2,1,""],add_nodes:[4,2,1,""],build_p_comb_structure_for_a_node:[4,2,1,""],build_time_columns_filtering_for_a_node:[4,2,1,""],build_time_scalar_indexing_structure_for_a_node:[4,2,1,""],build_transition_filtering_for_a_node:[4,2,1,""],build_transition_scalar_indexing_structure_for_a_node:[4,2,1,""],clear_indexing_filtering_structures:[4,2,1,""],edges:[4,2,1,""],fast_init:[4,2,1,""],get_node_indx:[4,2,1,""],get_ordered_by_indx_set_of_parents:[4,2,1,""],get_parents_by_id:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],has_edge:[4,2,1,""],nodes:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_values:[4,2,1,""],p_combs:[4,2,1,""],remove_edges:[4,2,1,""],remove_node:[4,2,1,""],time_filtering:[4,2,1,""],time_scalar_indexing_strucure:[4,2,1,""],transition_filtering:[4,2,1,""],transition_scalar_indexing_structure:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path":{SamplePath:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.sample_path.SamplePath":{build_structure:[4,2,1,""],build_trajectories:[4,2,1,""],clear_memory:[4,2,1,""],has_prior_net_structure:[4,2,1,""],structure:[4,2,1,""],total_variables_count:[4,2,1,""],trajectories:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims":{SetOfCims:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.set_of_cims.SetOfCims":{actual_cims:[4,2,1,""],build_cims:[4,2,1,""],build_times_and_transitions_structures:[4,2,1,""],filter_cims_with_mask:[4,2,1,""],get_cims_number:[4,2,1,""],p_combs:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.structure":{Structure:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.structure.Structure":{add_edge:[4,2,1,""],clean_structure_edges:[4,2,1,""],contains_edge:[4,2,1,""],edges:[4,2,1,""],get_node_id:[4,2,1,""],get_node_indx:[4,2,1,""],get_positional_node_indx:[4,2,1,""],get_states_number:[4,2,1,""],nodes_indexes:[4,2,1,""],nodes_labels:[4,2,1,""],nodes_values:[4,2,1,""],remove_edge:[4,2,1,""],remove_node:[4,2,1,""],total_variables_number:[4,2,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory":{Trajectory:[4,1,1,""]},"PyCTBN.PyCTBN.structure_graph.trajectory.Trajectory":{complete_trajectory:[4,2,1,""],size:[4,2,1,""],times:[4,2,1,""],trajectory:[4,2,1,""]},"PyCTBN.PyCTBN.utility":{abstract_importer:[5,0,0,"-"],cache:[5,0,0,"-"],json_importer:[5,0,0,"-"],sample_importer:[5,0,0,"-"]},"PyCTBN.PyCTBN.utility.abstract_importer":{AbstractImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.abstract_importer.AbstractImporter":{build_list_of_samples_array:[5,2,1,""],build_sorter:[5,2,1,""],clear_concatenated_frame:[5,2,1,""],compute_row_delta_in_all_samples_frames:[5,2,1,""],compute_row_delta_sigle_samples_frame:[5,2,1,""],concatenated_samples:[5,2,1,""],dataset_id:[5,2,1,""],file_path:[5,2,1,""],sorter:[5,2,1,""],structure:[5,2,1,""],variables:[5,2,1,""]},"PyCTBN.PyCTBN.utility.cache":{Cache:[5,1,1,""]},"PyCTBN.PyCTBN.utility.cache.Cache":{clear:[5,2,1,""],find:[5,2,1,""],put:[5,2,1,""]},"PyCTBN.PyCTBN.utility.json_importer":{JsonImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.json_importer.JsonImporter":{build_sorter:[5,2,1,""],clear_data_frame_list:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""],import_sampled_cims:[5,2,1,""],import_structure:[5,2,1,""],import_trajectories:[5,2,1,""],import_variables:[5,2,1,""],normalize_trajectories:[5,2,1,""],one_level_normalizing:[5,2,1,""],read_json_file:[5,2,1,""]},"PyCTBN.PyCTBN.utility.sample_importer":{SampleImporter:[5,1,1,""]},"PyCTBN.PyCTBN.utility.sample_importer.SampleImporter":{build_sorter:[5,2,1,""],dataset_id:[5,2,1,""],import_data:[5,2,1,""]},"PyCTBN.tests":{estimators:[7,0,0,"-"],optimizers:[8,0,0,"-"],structure_graph:[9,0,0,"-"],utility:[10,0,0,"-"]},"PyCTBN.tests.estimators":{test_parameters_estimator:[7,0,0,"-"],test_structure_constraint_based_estimator:[7,0,0,"-"],test_structure_estimator:[7,0,0,"-"],test_structure_score_based_estimator:[7,0,0,"-"]},"PyCTBN.tests.estimators.test_parameters_estimator":{TestParametersEstimatior:[7,1,1,""]},"PyCTBN.tests.estimators.test_parameters_estimator.TestParametersEstimatior":{aux_import_sampled_cims:[7,2,1,""],cim_equality_test:[7,2,1,""],equality_of_cims_of_node:[7,2,1,""],setUpClass:[7,2,1,""],test_compute_parameters_for_node:[7,2,1,""],test_fast_init:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator":{TestStructureConstraintBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_constraint_based_estimator.TestStructureConstraintBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_estimator":{TestStructureEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_estimator.TestStructureEstimator":{setUpClass:[7,2,1,""],test_adjacency_matrix:[7,2,1,""],test_build_complete_graph:[7,2,1,""],test_build_removable_edges_matrix:[7,2,1,""],test_generate_possible_sub_sets_of_size:[7,2,1,""],test_init:[7,2,1,""],test_save_plot_estimated_graph:[7,2,1,""],test_save_results:[7,2,1,""],test_time:[7,2,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator":{TestStructureScoreBasedEstimator:[7,1,1,""]},"PyCTBN.tests.estimators.test_structure_score_based_estimator.TestStructureScoreBasedEstimator":{setUpClass:[7,2,1,""],test_structure_1:[7,2,1,""],test_structure_2:[7,2,1,""],test_structure_3:[7,2,1,""],test_structure_monoprocesso:[7,2,1,""]},"PyCTBN.tests.optimizers":{test_hill_climbing_search:[8,0,0,"-"],test_tabu_search:[8,0,0,"-"]},"PyCTBN.tests.optimizers.test_hill_climbing_search":{TestHillClimbingSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_hill_climbing_search.TestHillClimbingSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.optimizers.test_tabu_search":{TestTabuSearch:[8,1,1,""]},"PyCTBN.tests.optimizers.test_tabu_search.TestTabuSearch":{setUpClass:[8,2,1,""],test_structure:[8,2,1,""],test_structure_3:[8,2,1,""]},"PyCTBN.tests.structure_graph":{test_cim:[9,0,0,"-"],test_networkgraph:[9,0,0,"-"],test_sample_path:[9,0,0,"-"],test_setofcims:[9,0,0,"-"],test_structure:[9,0,0,"-"],test_trajectory:[9,0,0,"-"]},"PyCTBN.tests.structure_graph.test_cim":{TestConditionalIntensityMatrix:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_cim.TestConditionalIntensityMatrix":{setUpClass:[9,2,1,""],test_compute_cim_coefficients:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph":{TestNetworkGraph:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_networkgraph.TestNetworkGraph":{aux_build_p_combs_structure:[9,2,1,""],aux_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],aux_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],aux_build_transition_columns_filtering_structure:[9,2,1,""],aux_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_add_edges:[9,2,1,""],test_add_nodes:[9,2,1,""],test_build_p_combs_structure:[9,2,1,""],test_build_time_columns_filtering_structure_for_a_node:[9,2,1,""],test_build_time_scalar_indexing_structure_for_a_node:[9,2,1,""],test_build_transition_columns_filtering_structure:[9,2,1,""],test_build_transition_scalar_indexing_structure_for_a_node:[9,2,1,""],test_fast_init:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_ordered_by_indx_set_of_parents:[9,2,1,""],test_get_parents_by_id:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_sample_path":{TestSamplePath:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_sample_path.TestSamplePath":{setUpClass:[9,2,1,""],test_buid_samplepath_no_concatenated_samples:[9,2,1,""],test_buid_samplepath_no_variables:[9,2,1,""],test_build_saplepath_no_prior_net_structure:[9,2,1,""],test_build_structure:[9,2,1,""],test_build_structure_bad_sorter:[9,2,1,""],test_build_trajectories:[9,2,1,""],test_init:[9,2,1,""],test_init_not_filled_dataframse:[9,2,1,""],test_init_not_initialized_importer:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_setofcims":{TestSetOfCims:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_setofcims.TestSetOfCims":{another_filtering_method:[9,2,1,""],aux_test_build_cims:[9,2,1,""],aux_test_init:[9,2,1,""],build_p_comb_structure_for_a_node:[9,2,1,""],setUpClass:[9,2,1,""],test_build_cims:[9,2,1,""],test_filter_cims_with_mask:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_structure":{TestStructure:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_structure.TestStructure":{setUpClass:[9,2,1,""],test_edges_operations:[9,2,1,""],test_equality:[9,2,1,""],test_get_node_id:[9,2,1,""],test_get_node_indx:[9,2,1,""],test_get_positional_node_indx:[9,2,1,""],test_get_states_number:[9,2,1,""],test_init:[9,2,1,""],test_repr:[9,2,1,""]},"PyCTBN.tests.structure_graph.test_trajectory":{TestTrajectory:[9,1,1,""]},"PyCTBN.tests.structure_graph.test_trajectory.TestTrajectory":{setUpClass:[9,2,1,""],test_init:[9,2,1,""]},"PyCTBN.tests.utility":{test_cache:[10,0,0,"-"],test_json_importer:[10,0,0,"-"],test_sample_importer:[10,0,0,"-"]},"PyCTBN.tests.utility.test_cache":{TestCache:[10,1,1,""]},"PyCTBN.tests.utility.test_cache.TestCache":{test_clear:[10,2,1,""],test_find:[10,2,1,""],test_init:[10,2,1,""],test_put:[10,2,1,""]},"PyCTBN.tests.utility.test_json_importer":{TestJsonImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_json_importer.TestJsonImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_build_sorter:[10,2,1,""],test_clear_concatenated_frame:[10,2,1,""],test_clear_data_frame_list:[10,2,1,""],test_compute_row_delta_in_all_frames:[10,2,1,""],test_compute_row_delta_in_all_frames_not_init_sorter:[10,2,1,""],test_compute_row_delta_single_samples_frame:[10,2,1,""],test_dataset_id:[10,2,1,""],test_file_path:[10,2,1,""],test_import_data:[10,2,1,""],test_import_sampled_cims:[10,2,1,""],test_import_structure:[10,2,1,""],test_import_variables:[10,2,1,""],test_init:[10,2,1,""],test_normalize_trajectories:[10,2,1,""],test_normalize_trajectories_wrong_indx:[10,2,1,""],test_normalize_trajectories_wrong_key:[10,2,1,""],test_read_json_file_found:[10,2,1,""],test_read_json_file_not_found:[10,2,1,""]},"PyCTBN.tests.utility.test_sample_importer":{TestSampleImporter:[10,1,1,""]},"PyCTBN.tests.utility.test_sample_importer.TestSampleImporter":{ordered:[10,2,1,""],setUpClass:[10,2,1,""],test_init:[10,2,1,""],test_order:[10,2,1,""]},PyCTBN:{PyCTBN:[1,0,0,"-"],tests:[6,0,0,"-"]}},objnames:{"0":["py","module","Python module"],"1":["py","class","Python class"],"2":["py","method","Python method"]},objtypes:{"0":"py:module","1":"py:class","2":"py:method"},terms:{"abstract":[2,3,4,5,12],"boolean":[2,4],"case":[7,8,9,10],"class":[2,3,4,5,7,8,9,10,12],"default":[2,3],"float":2,"function":2,"import":[4,5,13,14],"int":[2,3,4,5],"null":2,"return":[2,3,4,5,9,12],"static":[2,4],"super":12,"true":[2,12],"var":12,HAS:5,Has:[2,4],NOT:2,The:[2,4,5,12],Use:[2,12],__actual_cach:5,__init__:12,__list_of_sets_of_par:5,_actual_cim:4,_actual_trajectori:4,_aggregated_info_about_nodes_par:4,_array_indx:5,_cach:2,_cim:4,_complete_graph:2,_df_samples_list:[5,12],_df_structur:5,_df_variabl:[5,12],_file_path:12,_graph:[4,12],_import:4,_net_graph:2,_node:2,_node_id:4,_nodes_indx:2,_nodes_v:2,_p_combs_structur:4,_raw_data:5,_sample_path:2,_single_set_of_cim:2,_sorter:[5,12],_state_residence_tim:4,_structur:4,_structure_label:5,_time:4,_time_filt:4,_time_scalar_indexing_structur:4,_total_variables_count:4,_total_variables_numb:4,_trajectori:4,_transition_filt:4,_transition_matric:4,_transition_scalar_indexing_structur:4,_variables_label:5,abc:[3,5],about:[3,4],abstract_import:[0,1,4,13,14],abstractimport:[4,5,12],act:5,actual:[2,4],actual_cim:[4,12],add:[4,5],add_edg:4,add_nod:4,added:2,addit:2,adjac:[2,12],adjacency_matrix:[2,12],after:5,against:2,aggreg:4,algorithm:[2,3,12],all:[2,3,4,5,9,12],alpha_xu:2,alpha_xxu:2,alreadi:[5,12],also:[2,4],ani:[2,3],anoth:4,another_filtering_method:9,approach:2,arc:5,arrai:[2,4,5,12],assign:2,assum:2,aux_build_p_combs_structur:9,aux_build_time_columns_filtering_structure_for_a_nod:9,aux_build_time_scalar_indexing_structure_for_a_nod:9,aux_build_transition_columns_filtering_structur:9,aux_build_transition_scalar_indexing_structure_for_a_nod:9,aux_import_sampled_cim:7,aux_test_build_cim:9,aux_test_init:9,axi:12,base:[2,3,4,5,7,8,9,10],bayesian:2,befor:[2,3,7,8,9,10],belong:2,best:2,between:5,bool:[2,4],both:[2,5],bound:4,build:[2,4,5,9,12],build_cim:4,build_complete_graph:2,build_list_of_samples_arrai:5,build_p_comb_structure_for_a_nod:[4,9],build_removable_edges_matrix:2,build_sort:[5,12],build_structur:[4,12],build_time_columns_filtering_for_a_nod:4,build_time_scalar_indexing_structure_for_a_nod:4,build_times_and_transitions_structur:4,build_trajectori:[4,12],build_transition_filtering_for_a_nod:4,build_transition_scalar_indexing_structure_for_a_nod:4,built:2,cach:[0,1,2,13,14],calcul:2,call:[5,12],cardin:[2,4,5,9],cardinalit:[4,5],caridin:4,caridinalit:4,chang:[4,5],check:4,chi:2,chi_test:2,chi_test_alfa:2,child:[2,3],child_indx:2,child_states_numb:2,child_val:2,cim1:[2,7],cim2:[2,7],cim:[2,4,5,12],cim_equality_test:7,cims_kei:5,cims_label:7,classmethod:[7,8,9,10],clean_structure_edg:4,clear:[4,5],clear_concatenated_fram:5,clear_data_frame_list:5,clear_indexing_filtering_structur:4,clear_memori:4,climb:[2,3],coeffici:4,col:4,color:2,cols_filt:2,column:[2,4,5,12],columns_head:5,comb:4,combin:[4,5,9],combinatori:[4,9],common:2,complet:[2,4,5],complete_test:2,complete_trajectori:4,comput:[2,3,4,5,12],compute_cim_coeffici:4,compute_parameters_for_nod:[2,12],compute_row_delta_in_all_samples_fram:[5,12],compute_row_delta_sigle_samples_fram:5,compute_state_res_time_for_nod:2,compute_state_transitions_for_a_nod:2,compute_thumb_valu:2,concatanated_sampl:5,concaten:[4,5],concatenated_sampl:5,condit:4,conditional_intensity_matrix:[0,1,2,13,14],conditionalintensitymatrix:[2,4],consid:[2,4],constraint:2,constraint_based_optim:[0,1,13,14],constraintbasedoptim:3,construct:[4,5,12],conta:5,contain:[2,4,5,9],contains_edg:4,content:[13,14],convert:[2,5],copi:5,core:5,correct:[4,5],could:2,count:4,creat:[2,4,12],csv:12,csvimport:12,ctbn:2,ctpc:[2,3,12],ctpc_algorithm:[2,12],current:[2,3,5],cut:5,dafram:5,data:[2,3,4,5,13,14],datafram:[4,5,12],dataset:[3,4,5],dataset_id:[5,12],datfram:5,def:12,defin:5,definit:5,defualt:2,delta:[2,4,5],demonstr:12,describ:5,desir:[2,4],df_samples_list:5,dict:[5,12],dictionari:5,differ:5,differt:2,digraph:2,dimens:4,dir:12,direct:[2,4],directli:5,disabl:[2,3],disable_multiprocess:2,distribuit:2,doc:5,doubl:4,download:12,drop:12,duplic:4,dyn:12,each:[2,3,5],edg:[2,4,5,12],edges_list:4,end:5,entir:2,equal:4,equality_of_cims_of_nod:7,est:12,estim:[0,1,3,4,6,13,14],estimate_par:2,estimate_structur:2,estimated_cim:7,everi:[4,5],exam:12,exampl:[5,13,14],exclud:2,exctract:5,exist:5,exp_test_alfa:2,exponenti:2,expos:5,extend:12,extens:[2,5],extract:[4,5],fals:2,fam_score_calcul:[0,1,13,14],famscor:2,famscorecalcul:2,fast_init:[2,4,12],file:[2,5,12],file_path:[2,5,12],filepath:5,fill:[2,12],filter:[2,4],filter_cims_with_mask:4,find:[2,5],first:[2,12],fixtur:[7,8,9,10],follow:[4,5],form:4,format:12,formula:2,found:5,frame:5,from:[4,5,12],from_nod:5,gener:2,generate_possible_sub_sets_of_s:2,get:[2,5],get_cims_numb:4,get_fam_scor:2,get_node_id:4,get_node_indx:4,get_ordered_by_indx_set_of_par:4,get_parents_by_id:4,get_positional_node_indx:4,get_score_from_graph:2,get_states_numb:4,given:[2,4,5],glob:12,graph:[2,4,9,12],graph_struct:4,graphic:2,grid:[4,9],grpah:12,has:[5,12],has_edg:4,has_prior_net_structur:4,have:5,header:5,header_column:5,hill:[2,3],hill_climbing_search:[0,1,13,14],hillclimb:3,hold:[2,4],hook:[7,8,9,10],how:5,hyperparamet:2,hypothesi:2,identifi:[2,4,5],iff:2,implement:[3,5,13,14],import_data:[5,12],import_sampled_cim:5,import_structur:5,import_trajectori:5,import_vari:[5,12],improv:[2,3],includ:2,independ:2,independence_test:2,index:[2,4,5,12,13],indic:4,indx:5,info:[4,12],inform:[3,4],init:12,initi:[2,4,5,12],inplac:12,insid:12,instal:[13,14],interest:4,interfac:3,intes:4,iter:[2,3],iterations_numb:[2,3],its:[2,3],join:12,json:[2,5,12],json_import:[0,1,13,14],jsonarrai:5,jsonimport:[5,12],keep:[2,3,5],kei:5,kind:2,knowledg:2,known:2,known_edg:2,label:[2,3,4,5],lenght:[2,3],level:[2,5],likelihood:2,list:[2,3,4,5,12],list_of_column:4,list_of_edg:4,list_of_nod:4,load:5,loop:2,m_xu_suff_stat:2,m_xxu_suff_stat:2,main:12,margin:2,marginal_likelihood_q:2,marginal_likelihood_theta:2,mask:[4,9],mask_arr:4,matric:[2,4],matrix:[2,4,5,9,12],max_par:[2,3],maximum:[2,3],member:[4,5],mention:4,merg:5,method:[2,5,7,8,9,10],methodnam:[7,8,9,10],model:2,modul:[13,14],multipl:5,multiprocess:2,name:[2,4,5,12],ndarrai:[2,4,5],necessari:[2,4,5],nest:5,net:[2,3,4,5,12],net_graph:2,network:[2,4,5],network_graph:[0,1,2,13,14],networkgraph:[2,4,12],networkx:2,node:[2,3,4,5,9,12],node_id:[2,3,4,9],node_index:4,node_indx:[2,4],node_st:[4,9],node_states_numb:[4,9],nodes_index:4,nodes_indexes_arr:4,nodes_label:4,nodes_labels_list:4,nodes_numb:4,nodes_vals_arr:4,nodes_valu:[4,12],none:[2,3,4,5,7,9,10,12],normal:5,normalize_trajectori:5,number:[2,3,4],numpi:[2,4,5,9],obj:[10,12],object:[2,3,4,5,12],one:[4,5],one_iteration_of_ctpc_algorithm:2,one_level_norm:5,onli:5,oper:2,optim:[0,1,2,6,13,14],optimize_structur:3,option:[2,3],order:[2,5,10],origin:5,original_cols_numb:4,otherwis:[2,5],out:5,outer:[5,12],over:2,own:[13,14],p_comb:[4,9],p_indx:[4,9],p_val:9,p_valu:9,packag:[13,14],page:13,panda:[5,12],param:4,paramet:[2,3,4,5,9,13,14],parameters_estim:[0,1,13,14],parametersestim:[2,12],parent:[2,3,4,5],parent_indx:2,parent_label:2,parent_set:2,parent_set_v:2,parent_v:2,parent_valu:9,parents_cardin:4,parents_comb:5,parents_index:4,parents_indx:9,parents_label:[4,9],parents_states_numb:[4,9],parents_v:[4,9],parents_valu:[4,9],part:2,particular:[2,5],pass:12,path:[2,5,12],patienc:[2,3],peest:12,perform:2,pip:12,place:5,plot:2,png:2,posit:[4,5],possibl:[2,4],predict:3,prepar:5,present:[2,5],print:12,prior:[2,12],prior_net_structur:5,process:[2,3,4,5],properli:5,properti:[4,5],put:5,pyctbn:12,q_xx:4,rappres:4,raw:5,raw_data:5,read:[5,12],read_csv:12,read_csv_fil:12,read_fil:12,read_json_fil:5,real:[2,4,5,12],red:2,refer:[4,5],reject:2,rel:4,relat:5,releas:12,remain:5,remov:[2,4,5],remove_edg:4,remove_nod:4,repres:4,represent:2,res:4,resid:[2,4],result:[2,5,12],rtype:4,rule:[2,3],run:[7,8,9,10],runtest:[7,8,9,10],same:5,sampl:[4,5,12],sample_fram:[5,12],sample_import:[0,1,13,14],sample_path:[0,1,2,13,14],sampled_cim:7,sampleimport:5,samplepath:[2,4,12],samples_label:5,save:[2,12],save_plot_estimated_structure_graph:2,save_result:[2,12],scalar_index:2,scalar_indexes_struct:2,score:2,se1:12,search:[2,3,13],second:2,see:5,select:12,self:[2,5,12],sep:2,sep_set:2,set:[2,4,5,7,8,9,10],set_of_cim:[0,1,2,5,13,14],setofcim:[2,4,5,12],setupclass:[7,8,9,10],shift:[4,5],shifted_cols_head:5,show:2,signific:2,simbol:5,simpl:12,simpli:12,sinc:4,single_cim_xu_marginal_likelihood_q:2,single_cim_xu_marginal_likelihood_theta:2,single_internal_cim_xxu_marginal_likelihood_theta:2,size:[2,4],socim:5,sofc1:12,sorter:5,specif:[2,4,12],spuriou:2,spurious_edg:2,start:5,state:[2,4],state_res_tim:4,state_residence_tim:4,state_transition_matrix:4,statist:2,stop:[2,3],str:[2,3,4,5,12],string:[2,3,4,5],structur:[0,1,2,3,5,9,13,14],structure_constraint_based_estim:[0,1,13,14],structure_estim:[0,1,3,13,14],structure_estimation_exampl:12,structure_graph:[0,1,2,5,6,13,14],structure_label:5,structure_score_based_estim:[0,1,13,14],structureconstraintbasedestim:2,structureestim:[2,3,12],structurescorebasedestim:2,structut:4,style:2,submodul:[1,6,13,14],subpackag:[13,14],subset:2,suffici:2,suffuci:2,symbol:[4,5],synthet:5,t_xu_suff_stat:2,tabu:[2,3],tabu_length:[2,3],tabu_rules_dur:[2,3],tabu_search:[0,1,13,14],tabusearch:3,take:12,tar:12,task:[2,4],tau_xu:2,ternari:12,test:2,test_add_edg:9,test_add_nod:9,test_adjacency_matrix:7,test_buid_samplepath_no_concatenated_sampl:9,test_buid_samplepath_no_vari:9,test_build_cim:9,test_build_complete_graph:7,test_build_p_combs_structur:9,test_build_removable_edges_matrix:7,test_build_saplepath_no_prior_net_structur:9,test_build_sort:10,test_build_structur:9,test_build_structure_bad_sort:9,test_build_time_columns_filtering_structure_for_a_nod:9,test_build_time_scalar_indexing_structure_for_a_nod:9,test_build_trajectori:9,test_build_transition_columns_filtering_structur:9,test_build_transition_scalar_indexing_structure_for_a_nod:9,test_cach:6,test_child:2,test_cim:6,test_clear:10,test_clear_concatenated_fram:10,test_clear_data_frame_list:10,test_compute_cim_coeffici:9,test_compute_parameters_for_nod:7,test_compute_row_delta_in_all_fram:10,test_compute_row_delta_in_all_frames_not_init_sort:10,test_compute_row_delta_single_samples_fram:10,test_dataset_id:10,test_edges_oper:9,test_equ:9,test_fast_init:[7,9],test_file_path:10,test_filter_cims_with_mask:9,test_find:10,test_generate_possible_sub_sets_of_s:7,test_get_node_id:9,test_get_node_indx:9,test_get_ordered_by_indx_set_of_par:9,test_get_parents_by_id:9,test_get_positional_node_indx:9,test_get_states_numb:9,test_hill_climbing_search:6,test_import_data:10,test_import_sampled_cim:10,test_import_structur:10,test_import_vari:10,test_init:[7,9,10],test_init_not_filled_dataframs:9,test_init_not_initialized_import:9,test_json_import:6,test_networkgraph:6,test_normalize_trajectori:10,test_normalize_trajectories_wrong_indx:10,test_normalize_trajectories_wrong_kei:10,test_ord:10,test_par:2,test_parameters_estim:6,test_put:10,test_read_json_file_found:10,test_read_json_file_not_found:10,test_repr:9,test_sample_import:6,test_sample_path:6,test_save_plot_estimated_graph:7,test_save_result:7,test_setofcim:6,test_structur:[6,8],test_structure_1:7,test_structure_2:7,test_structure_3:[7,8],test_structure_constraint_based_estim:6,test_structure_estim:6,test_structure_monoprocesso:7,test_structure_score_based_estim:6,test_tabu_search:6,test_tim:7,test_trajectori:6,testcach:10,testcas:[7,8,9,10],testconditionalintensitymatrix:9,testhillclimbingsearch:8,testjsonimport:10,testnetworkgraph:9,testparametersestimatior:7,testsampleimport:10,testsamplepath:9,testsetofcim:9,teststructur:9,teststructureconstraintbasedestim:7,teststructureestim:7,teststructurescorebasedestim:7,testtabusearch:8,testtrajectori:9,tha:5,theta:2,thi:[2,4,5,12],three:12,threshold:2,thumb:2,thumb_threshold:2,thumb_valu:2,time:[2,4,5,12],time_filt:4,time_kei:5,time_scalar_indexing_strucur:4,timestamp:5,to_nod:5,tot_vars_count:[2,3],total:[2,4],total_variables_count:4,total_variables_numb:4,traj:5,trajecory_head:5,trajectori:[0,1,2,5,12,13,14],trajectories_kei:5,trajectory_list:5,trajectri:12,transit:[2,4,5],transition_filt:4,transition_matric:4,transition_scalar_indexing_structur:4,tri:5,tupl:4,tutori:5,two:2,type:[2,3,4,5,12],union:5,uniqu:5,unittest:[7,8,9,10],unus:4,usag:[13,14],use:[2,12],used:[2,3,4,5],using:[2,3,4,5],util:[0,1,4,6,13,14],valid:2,valu:[2,3,4,5,9,12],values_list:12,var_id:2,variabl:[2,3,4,5,12],variable_cardin:5,variable_cim_xu_marginal_likelihood_q:2,variable_cim_xu_marginal_likelihood_theta:2,variable_label:5,variables_kei:5,variables_label:5,vector:[2,4],want:12,when:2,where:5,which:[2,3,4,5],whl:12,who:2,without:[2,3],you:[2,5,12],your:[13,14]},titles:["PyCTBN package","PyCTBN.PyCTBN package","PyCTBN.PyCTBN.estimators package","PyCTBN.PyCTBN.optimizers package","PyCTBN.PyCTBN.structure_graph package","PyCTBN.PyCTBN.utility package","PyCTBN.tests package","PyCTBN.tests.estimators package","PyCTBN.tests.optimizers package","PyCTBN.tests.structure_graph package","PyCTBN.tests.utility package","basic_main module","Examples","Welcome to PyCTBN\u2019s documentation!","PyCTBN","setup module"],titleterms:{"import":12,abstract_import:5,basic_main:11,cach:5,conditional_intensity_matrix:4,constraint_based_optim:3,content:[0,1,2,3,4,5,6,7,8,9,10],data:12,document:13,estim:[2,7,12],exampl:12,fam_score_calcul:2,hill_climbing_search:3,implement:12,indic:13,instal:12,json_import:5,modul:[0,1,2,3,4,5,6,7,8,9,10,11,15],network_graph:4,optim:[3,8],own:12,packag:[0,1,2,3,4,5,6,7,8,9,10],paramet:12,parameters_estim:2,pyctbn:[0,1,2,3,4,5,6,7,8,9,10,13,14],sample_import:5,sample_path:4,set_of_cim:4,setup:15,structur:[4,12],structure_constraint_based_estim:2,structure_estim:2,structure_graph:[4,9],structure_score_based_estim:2,submodul:[0,2,3,4,5,7,8,9,10],subpackag:[0,1,6],tabl:13,tabu_search:3,test:[6,7,8,9,10],test_cach:10,test_cim:9,test_hill_climbing_search:8,test_json_import:10,test_networkgraph:9,test_parameters_estim:7,test_sample_import:10,test_sample_path:9,test_setofcim:9,test_structur:9,test_structure_constraint_based_estim:7,test_structure_estim:7,test_structure_score_based_estim:7,test_tabu_search:8,test_trajectori:9,trajectori:4,usag:12,util:[5,10],welcom:13,your:12}}) \ No newline at end of file