-
-

Welcome to pyFTS’s documentation!¶

+
+

pyFTS - Fuzzy Time Series for Python¶

What is pyFTS Library?¶

https://badges.frapsoft.com/os/v2/open-source.png?v=103 -https://img.shields.io/badge/License-GPLv3-blue.svghttps://img.shields.io/badge/Made%20with-Python-1f425f.svg

This package is intended for students, researchers, data scientists or whose want to exploit the Fuzzy Time Series methods. These methods provide simple, easy to use, computationally cheap and human-readable models, suitable from statistic laymans to experts.

+https://img.shields.io/badge/License-GPLv3-blue.svghttps://img.shields.io/badge/Made%20with-Python-1f425f.svg + Fork me on GitHub

This package is intended for students, researchers, data scientists or whose want to exploit the Fuzzy Time Series methods. These methods provide simple, easy to use, computationally cheap and human-readable models, suitable from statistic laymans to experts.

This tool is developed on MINDS Lab, headed by Prof. Frederico Gadelha Guimarães from Electrical Engineering Departament of Federal University @@ -133,8 +141,8 @@ src="http://www.ifmg.edu.br/portal/imagens/logovertical.jpg" alt="IFMG" width="1

How to reference pyFTS?¶

-https://zenodo.org/badge/DOI/10.5281/zenodo.1405817.svg -

Silva, P. C. L. et al. pyFTS: Fuzzy Time Series for Python (Version v4.0). Belo Horizonte. 2018. DOI: 10.5281/zenodo.1405817. Url: <https://doi.org/10.5281/zenodo.1405817>

+https://zenodo.org/badge/DOI/10.5281/zenodo.597359.svg +

Silva, P. C. L. et al. pyFTS: Fuzzy Time Series for Python. Belo Horizonte. 2018. DOI: 10.5281/zenodo.597359. Url: <https://doi.org/10.5281/zenodo.597359>

Indexes¶

diff --git a/docs/build/html/modules.html b/docs/build/html/modules.html index b6b41fc..109b34d 100644 --- a/docs/build/html/modules.html +++ b/docs/build/html/modules.html @@ -117,21 +117,28 @@
  • pyFTS.data package
  • pyFTS.models package
      diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv index b15edec1fbfef5d00fdb6e387720d0ed6ce79a2c..0481bb4767bf80d8f8f548c98f57cf75eba34f74 100644 GIT binary patch delta 5452 zcmV-S6|?HJE4wR@b$?59+c>tz_x&kcb!Qt^&#k(f**S@m&P<$fTgl9=*{~oIlF%jr z1|V&#Km7pUTYMiJ$cwIaB;ofz01h4p1iHF>`JO3>eagorQU-jSmli-x6$^Vp} zz5C0}yI;yr_moGcl*lJFlBE4|F?DcHi7F(;!UXTd>(@UDet+EMBxfpTkpUkH9_38% zo4-z=7nu)?%7|h@zn>^e)E7>F79?T$83FkN(>@X%5GZ@83ocZVkQ9LyiDxRw5d|eP zg@8HIJdAabOSUfzCRBA5V9^=RseC30J~yL8*Lv8yd`07G%}Rc7YdP`B_e?wI3X zPjt7|n1}?8h{`)qJuav-&rj58uDL`;=$scN>?Fu1Uy421v&3;)Uh14^^c1oq*PU-@ zh$uWsvxG!AKuJkX!{%etViM}=d-OGzB+AVgW=0`L+JW&{Tj-ouJM(Yq{2)ad?qf$L zEq^~}TopRBb~b$(PPZ_k(7Ha3gvcoGcvQT1eRMxS+w zMC_)@xYC=?UE;AFu2&QuvoRs#Av=+dNi;1@1-C+uL`9w{eha#wV)*za64A$%p0rU6 zMyNvylDby1S;TQ=3}&}T4p?w@U^EVGc4I7enSY=nb+{LF3}?JV;y5FbEG3RXj%5V5 zk6-R@4Jk^9QUEJTg8ti@L-Uh};go}(;+knSCMzT-O5)yftp|M9ztPa%Y{s;34b^hGZM3Im%#FNPuR z8{q2Jp$oNJ1W0uzZA^>(AbFsG`Y?Gw$A5dE+(Vb~Yh(H!VvkEM&Bn*}`cpK#EI4j! zF+jY=Vre+BP3KQ#Cto{CWONGACSNLHG2_SZh4EOtg#F1QjQ+&AB*oZOy207O#dX?1G^5io&%_yD=uR00ix(i870PF)_ zP8mGsVSArfuJMm_3gs6Q9YXb`iJycH8mMdf;8XGEpXVLThkZzwvjPy1ETcRgDFYZt zhgmrSET!q5N_Aq{R@kSnkHFH^DSzwK8;Z0_6@2~8ZtW&{*@Mt+sUN|qzwns8(imoV zn^<=n`cI$@N6M)*+Y(NCG7$>10Aa%7LQ1OJ@F9_-v%U3LR+?!@$`QqN+}AVB73d7> zv}B0W)-49uBMj09|A9EcfI^b&L{LbPE?X&Bi~@7$SB9(uib=fM<>m~skAFF-9xN3W zu3SG18;5o-vizLk&~AH}u<1pCu!H&IaCRqXOH@vHL=jO6 zfi<%V3ju{9i5*~OQQiXetVKC;Qu4~uA`ROvra}87J3HJ_>PfMCBQU1eai0RJkoITUK*UUVT2aF9Xh-Q^5IXh-}6wLUu9&o7-v{PVsDezvreh{yY zC0jyp3bSG%m0v|eEwYd7aG++1h?T3@4h7dm;S^twh*XF@CTdac>P_JeWoQ{Vg;%1G zO09&U7FYk@j^)<>H-An6UNDhL@;}?dl}iLU9wj}JoVuf=VD1o=3Xz|5Ot>92aY%Q~ z7+W4Wtk${VeE#C6p6L$8t#I5!ktz zq~=-P=Z)iHlMeXIw@v@(n7(@CE>CLfh}kmC0&^7}!U2hRq0$Wje=>K$VR5t7(w*X1 zu!XK5hjOti>VFUq$)Q2DP8n2})NN@IWvcR_Zx|Ih%;u6&`gA^+xo#@L7M7UjS9Vr; z!BlQgELf2X?Iv+G(*zb;d)`Ly>762YqjvrP;F$yQ8rQqDSoh8$Q9)i&)%xkyiM zqTH0eJ;~xuS=yQiLC$Qf+lE86&DkpRND`XZ^w~eeM}KJY6X_hHsB=`sY(Qr;$Z{(r zBCm7M29K&JQGz!YZ30QF&Uc-dARFIBN zw?D^f5;N{xn!sI7b#hmEA=!~}b5NALqF~BE4v1;CRypOV6PZG4wchdqRM+9Q%pGfW zYWwxt#DA9)Ft{0AQaSx`;1wd)QE?f_Y((UeLN|w-q&95$UNJUI;CpGmiP$-PHI4sp zV#($i&=97FWlNIVw@-}1cDZ!tWF+4ncU#Q9(0K{XpWzGBX^Xt=Ubn4&Sll5Y+m@&J zVf7{C^<736KQkY(?5!rzw1#3QU!HVpz(v`0PF95Jbr%v0IP zxfDr~Ql3K`rjr_)gAoEG8~KS!TBMLXR7s&3xJ(YPUi%)*dCG)9%P$fG?EdoY{_Z=# zY=4{1Mflt8?&Iz60Oc|vu)r=71MJ@Y^V`Q;fY~-3(CU6#h|v%K_v^0^qfI)f(Y>?) zqrcyNx%+>B(Ka2>=zdy&(I!MZu&CNHw9)c5aeGkBZfj?RhvmUts5LFnT(_r#CRd&g zzG9JvFC=*aGhR;2p6z35V<}G_=Upn{YJYC+P{Ak4LCQ8A&@20C0Y)d{SY2L4GJx&f z~r?Et`=-hYCy z5jOVVdNX3~`QLU}Gg>wqRa}Wvi>8aDqk|(IgYUZgi~ntI3(D<<0T5Rjp#(4XA0SV< z#DS`R2x;rA&gK@wC|5MCP9~2RcKwU_Qg43c4H(=e$-T|lUG>Ra3HC*RbbC&8dFKSG z>(tFU7!u1}9DfRa-QEQciZh!CP}Q!PGtYS%yk^nr{jBax@+f+R ze3d_J_Btq!Qd4^mG5GCFa`;pcgTHk21VaP6H&(=KupVE1*vPcIJ?dR7Xrpb98tke+ zFb9!E1z-KuvM^F@FAJ4BD8oX;*lIQl=9&%mY~PmGj>|xQJBjh_xof84Hh*pKo1UuL zTfPC)@DV~i;YhZ}b2BvQPTM@69|G*tZgwop+uX*NFjfU6S>fnX;XqCf@A;9ZDG8hokdT-!_cGWnMI=}O|?)pJtD2n?xqu}mc=9QxTfx@bTG!kt z2(*0S_@bf-?AXXhfoDzwz#{$F!_Ie*B~l37<{_Zm^e z;%G%y9TY^6T5)a5i~X)Sw7&na-QGJ*usl zAiJwHn@K(9#A;lp(6pnKn{_)L;j8Fstrr&OC(lB8A@^o7v}Wq-F4*MAV@+8NuTHV} z;sZ>9nH%a|Wz50^n|N6Q23uFhUQeL~TbW{VzZBg^Jwk8oV{D zWie0P-+EzrRbkXQ*`k)0iP?HpFSD~{DS2;Gv}I}ZiHfgYpv*}343p1pV1=5e=D0@L z!ysSEdTjdR0%k{DJ%5v*4jF&RosW*Ciw_<|a^@ms7p?B0f6pFLlh~-d^qkAT0p+=r z`e(iNs@~ErV-x-&@m4F8dF@IVix>X(Ruq{x8+P_h1lMjJ^QxYkM)~rE-Vef~)Ztve@m_% z#WOe?bYfx&Y&OC5f|2%ab8M+**a({jf~+8~ml-3abKzfX^I?p6SU}=9`&V3qh>>%ahxJCq0oc1W#Ztjji-Ol4$;Q~%^~_&A_I@q z&S5vt;pSoBdBFnKX_#1GgIdn=Wirh*BlE6#dG*Pc_AN<1xWPw~lTT(t?TFy08}#+u zg?d+Yju*K%$#8$JUS@S=al0Ax&D6_OM!wmUdVO_qxOS~8pN>Yqv#YeBF&)26Xjaj) z4^L|QbKH5!x5|I-HJa>_xX%_ls_n1Aezgxdd^guo6_1T|TF<-hPD^|D+(l_`e(T$R zuID*#(Y;@>TYr-#@g|Mo8qFX|=XVfpj7UnH*-)3$*SsLfy*WZ%XJjrS-DdEN!iq2z zUu$Vi8&7d%w2Ud(u2`yT2rk6zV4+51ZdnM0zG|6hwbFmW4FFqPXnByao~F4MM4uPL zxTg86g;v3v zBefF#s=C$iR@tqDzv}i@K8l)W{T|UieY92Z=A*4dSEH7vK=6A)!ix^+2)B} zW`YcAHc)@fJ=9wZ#*H+}`4@V4F^)xyDHa5<0*MJ3*jww52Ix0hL16r$c)>Veb|T=g7$Zu z3t$bNi@;%T(M4*9y+oHJ;NGDwX0t2y6N6pl0^{@!#|zdr-&i>J+B=~(?j*gRe7L8C zu@i7B%j_+jyuN-l?2hMBWM_o>s7UqyacX25>Ru-` z`{9576G|Bdd#dtXmarTLN874#hcVtbH3OIbMid&YL>ZOH%Vv` z7C6P&<9R60`2{S1wT&a<`1u6U-OZ=KCbq9{-N$Cz(^|&Ke84;Lb@vqU@WFty()3FS zoYBqa%9p_Ssv`>5SIuUU9?HcC4+WxaHudSNy!&tc@FZf76hcbBd-80o`|Ex`)&GC> ze)G_tc>Z{KD%KNwPV=JE9ZDi;RSQL9#qV2l?qsk}@nTN?h47+(aYfJbq+G$3lvh%z8i;{I;dS5A8I-2UrRv&eQ z%M$ATrp$83H1oCrJ$0_ia<2!OQ%dBM8YXJL>!k0d=%cD*2m?&DU9f|w4=nVO+tW&e z#OBj(((+7GFJbw#c9^vD6t{o($!Kytb1$nL6Kd|hn9}I&kGYw+H={@Ht)~vKgC&HUvFGu9U~gq%NE~zk zH=`>O74v7oq9E3_++b$`op<2aUv_w^K>nAsMidLm}iJLk1>I-TvZoLv*WVL&7#p-ciy zfV8bz^=r)Q&65lO-o^XDfxO5_St7pw05||~Kmg3npB{HN+4--jh>L{Y{GvbWZ-P^v zCjVZ3_w#?;{QOh-?Vj@JloI)*Mv}BYE~XCdC{cx^SeW3Qcz^x+N5PM~oa9X9EHdCj z!K0iBe)E?J^dj?~Q5jK8=;Mj9M1A4(M?n&npAnGXG3_JK0fDlYy5K?;2}u!Xk$9$( z98pj*QwW$N&BIt1xn%poU_w<_0T!L{oXTgC;FB|<*|^vfCC_KYVv5NMqZq>#Q<706 zOj9Wcyo~WZNq-PYVM+*U7f6M#|B1x55DZwVC=v#Ia3$&JvM7 zc;b37*auTFeoSbHW%Ku(C61nD5CJjv=^JF2lYNm88GptkCkIJV>SkL5);D*93?tn| zrra^d!Jg=DtuYY^8WELup!&X`&OAR+r?KV|8KHAtl(2&!pL{9yWX}@EVR@-@qR~^x zj$C)Xp&_F1B+U{M;Q%EiISreyO^ZpWtMAd*T#_g^_b_u8a-82`yWK~4qwRdG=9KP4OcQml$7J}_ zM}HH8pUre%#$ebw-U`T1vG^;D?2xOEuR7w8^zSmJ@|MT< zMCQyukrZ^xd0#qxj0Oy=X4LlSs_f%EDCoGKQM|GUW6BlF&!O(-bHa}lk$iD0!lAm4 z3NML{W3~aVZXLQ%yG4LhXVS*B*bkBi3V)~%lLvIX2g*Hk8NW8B{~`9cY_C5> z!^?u>wiW}#Yb=(A6Weq?Dm(bvQ6i&Lh&K3A35yv&hA)iA;w9`49%1w+&K*adnh^Z$ zo6ad!`8Udrr@fF07?+K*aHEQGiMkljfKE{XC+wLzR*Pi>-)a(|GCBn3@b*VRcz-VG z(J@msCiu;KUA^%O%mjo9iwh~KZo`K}j*j-$V_9jYAt^@`*KuFZ zG*_TAtkaSqPFuGaV2?0JAN&*I1Op05vJ*ieMY?RIU@;2Jp+yUS7PA+5U$8&m9En*yri zuHU6@zlF5`J?>7D^x$GcaDOC)QjQG8j*bK!SY*x!1|jT(%xU~yBnfRh?d_Fvi5cZ? z7-uZ<0wRqYZ@tGXbN4iVp_Jo;qlAvG#Bjxm?CgVD@Ejj&miqdkhUF7AA7D@A5GKAX zPCQuL+4#qJsKn(y(KBF#y3Ca{70;XPebl1`b$<{tCCy`1z@6cO z65Pfl%h@yi_?np~;edO?3Zj`^O3scM9tAW0tZ%r~2ihqhyA*gQUf+vX$C51}IE7iU zkjk&3p%&Q(b~sQoHN(o;V~2w4qHv0@M?@;b9uu`FclBayhcdJboWd(nNTpW7P>ZYo zw_~~W|Hdi63no%Y{(p0OxN?ag$D^c2l2dn-6wDo>QX%pabfeQH>R>=kaInE{1uqf`tpjxuFCj5c{>)w=mVZti9y9}5lG89n3*^h!ASVB30bS#HN9)X>kNot;9 zTsXu-a%fPkQ-224;c#18M4765*cwJf4zsyrls=sgMy{KRu!SY&$&(#bUNDs#6bn}5 zLc2*^jWmIU*6wo=JUKgnqD1g&qiPd_K(ZCnoRp(ZpdkmAL$yu&Q7+Qcix)SgZ+DQm zQVF(nF&oes4YFKO`iHTCEqW0M&K4Epx|Oom%$1Hu2>E z3~ol3RDTYC9C(F@byQpiG8+-Oq|im#CaDb@9xKL%0emm*HxWChuZHpOPb}Fy0vf{f zZP}9K_T>|!uw5?QIT^{f$K4jQFLYi)^D%s3I&G1+-Rrj54~sh_WZU!G>4rp~hEyU>i|N7+@h|wk;)aYJXfYFb)Uq1d1 zz-XHeXmmd4(OHrv;dXWW6H+LZR8J(giB~DzbX^Kh6U0I!rS$KfctVi(1E+Uv>cCO)o*%2pfBFy?+@o z_xx`=thrk@3sqc+QR{l&kVQ+jf{Q6J(;Bb4C9{sHo&OB|^Bhmf|; z>TGT?jB-WOYDe&RVb@p8mwI!RH(+p^BzHDvAFFTXO0X{iq}v^y%PS{PB^TPuW)Uxi z)it>4UZ+m9!H`();!yDG)-HHZoPSwFfU0)QoO#aE;Pr-9??-i3kw?)haj#Nf9h$>CE)4F1yA6ATUP-dGW{zVAz`ThpD){QJ zmW7dOds(PlK^Ybz##XagFb8C?XZx1A_Pz}Cx04uOp1Wo!Zqo+8>Y=JVU4I)e3?CuX z1CC^SJU2s=?zGM0`60kQ?PkZqyhV*15i9~nha)Jb*l>=gYZ8kIiZ)L#1RQPJv`$Vi z0Ju8A5D0dHAqrH$4Bmy9q`{YJ%(cCAFOzQ>pROd%Z7A7JQuIebc|_+om~7`xZS9yR zsg&r^^g(x!3|fC3MDQieqIEFQy)S~DZUKvQP~UR7 z=y}{nyI0LSZ12kPQ&F9nm|70sywfa$n$h7>0LJ8O!}8D zjS(HeGv~ff3v45=nSU6-5t%td0##>W4#8a{5m9q~!lZNJ$#mXu?NM#b0NGuoSxo9N zCsyM+g{B>?T&&yi2wz24YrU{IKY13)3%NIgp*2Hacflq{9&5^Kcy)@!7Y<+w%$zOn zDq|)l*x~Grt*c}5H3P2v>P3V;3THkbhu`OIaPVI6n3anW?SJrxN3+kcf#y%htO!6o z39fj$fvmhTSVdNCdQ|(q6%yqFxkKG59@g*XxQYb}K`&ITdEoc0`{V2kCBD?E$Nc_e zC9drJ#4)&&vlFE{4?ADAG%m2b1RhlhJ&2mo@-teW6Z8WA6DIiRau%e#^fMEh-a3~FJ@g)> zbI6^Kj-`ta?nQFuB4rn??!JG{9#WIosJ!%?%fA8TzJHYZvR->tZ)umY34fA!s};(; zb|s9(3x9hnip-l0JNqVrYd4R1RnJYMeECA}g77GHc-USPS_|g)4*{&`v@joCUk4x1 z*Gy-mdAF3GOawD$yx<7vKbVMFWz04RXoeTeBn>S<3!vYe=A*V0l{qLW?ety8U)Xu$zS8}PY+?8sg6qMJ? zA8^~uO6=qdHt^spcT8g_LHEzCRk=n^JmtY@mw(h+HgwbMBHzPcpgz~a!`<3td*cGP zc{R$37SjIeOJMof5)i+95ev1iR;Fh6NK*Kb@Kr#d4S@^H>ga`qL})yu4|EN&Nr zzL|QN%E&j1Qm?Nr4%e=A<0I;=%mKz!CVVZkE^m#!{&Zc+L-z{vpbrg7^^vNgxTz@T` zLFb=D;SXHi7|ve#{;IZC@K(3AfVav`8P_zQwa_YfbEHt^qhk9$lxRFLV{z4Bg z#<7So#ex796d~^AdTR&{(nMu6u0Rx1JlMoOBSzLP!F(qjK8#W9!th75_VTX zZLro=P-CzG5jE}_(ib-Z!q5o4)+G?JzZ#&CyO0q+>U_h1@7OsB@GBBbQpXn`jv>tI z(9ZJmFeUoV{knP0!zdZL;A0FXGUGO89X6tcp!FT+0$79RB5+t+bdlO&Eq~D^3AlEs zi`ndo{ls8bxxhHR!|{T(%{LbIz4msfjXO#2lJ|F%a6C};-|R?bNZyE?9Gq+=N4h^E z6Dt9?vdr4T$>Zx+!#?s{itLO~9~G(oAE!p9q3(53v+wUdp_E~;rz+oN3CnSCw5=L< z7~{<$$e*j$?+#Tav$uQkOn(u1?`R@k+<2ef-yt}(rkH;?jy#09JFsEea~;D7p<8Kb zI6aHu^`~FpEEB~c)TqG(i-GMXtAe$0>}u+-1(Bme>8-gfLDhdaIi5ng=lc8jrsJ)7 zHW;&oJkg`B@N(n=_rLGW{$d}@$^Fo)S>|-zB%w)I;1pwz=b=33Cx5U2);5laB`o7lcSbsw8;cWW6Z^8xR~*WF#j!v_P-O4BbTa7H)ZD_;WRvyLcSUp1RadMGC& zJQRqw+0>`6^6tO&!;^^JQV1#i?#{EZ?yvj%RR7nz=DywW{NZv}tS9!I=0&GFltj|1 zCW^+2-?!%6&S0P7&wo^sqYjXc345XmI|*^+?C;rRC+Sht+;+n#K7>E=E0=gAg;JeJ z{EEs&nih%fz@F)Kg=5Oq_}K|QMcLs%Ww}u?6ofw53*mr7OzgwFc6?#-uw10@j8+!Q6K?WXGuilyD z=Zs$6oeB{@qohFgc0eUViavOc!tJ}v^`fr(>k{KTKcr*8| z$}yql=!+?h-tw56iDNT*
      -pyFTS.common.FuzzySet.check_bounds(data, sets, ordered_sets)[source]¶
      +pyFTS.common.FuzzySet.check_bounds(data, fuzzy_sets, ordered_sets)[source]¶
      -pyFTS.common.FuzzySet.check_bounds_index(data, sets, ordered_sets)[source]¶
      +pyFTS.common.FuzzySet.check_bounds_index(data, fuzzy_sets, ordered_sets)[source]¶
      +
      +
      +pyFTS.common.FuzzySet.fuzzyfy(data, partitioner, **kwargs)[source]¶
      +

      A general method for fuzzyfication.

      + +++ + + + +
      Parameters:
        +
      • data – input value to be fuzzyfied
        • +
      • partitioner – a trained pyFTS.partitioners.Partitioner object
        • +
      • kwargs – dict, optional arguments
        • +
      • alpha_cut – the minimal membership value to be considered on fuzzyfication (only for mode=’sets’)
        • +
      • method – the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)
        • +
      • mode – the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership values for all fuzzy sets)
        • +
      +
      +

      :returns a list with the fuzzyfied values, depending on the mode

      +
      +
      -pyFTS.common.FuzzySet.fuzzyfy_instance(inst, fuzzySets, ordered_sets=None)[source]¶
      +pyFTS.common.FuzzySet.fuzzyfy_instance(inst, fuzzy_sets, ordered_sets=None)[source]¶

      Calculate the membership values for a data point given fuzzy sets

      @@ -399,7 +422,8 @@ @@ -412,7 +436,7 @@
      -pyFTS.common.FuzzySet.fuzzyfy_instances(data, fuzzySets, ordered_sets=None)[source]¶
      +pyFTS.common.FuzzySet.fuzzyfy_instances(data, fuzzy_sets, ordered_sets=None)[source]¶

      Calculate the membership values for a data point given fuzzy sets

      Parameters:
      • inst – data point
        • -
      • fuzzySets – dict of fuzzy sets
        • +
      • fuzzy_sets – a dictionary where the key is the fuzzy set name and the value is the fuzzy set object.
        • +
      • ordered_sets – a list with the fuzzy sets names ordered by their centroids.
      @@ -420,7 +444,8 @@ @@ -433,17 +458,17 @@
      -pyFTS.common.FuzzySet.fuzzyfy_series(data, fuzzySets, method='maximum', alpha_cut=0.0)[source]¶
      +pyFTS.common.FuzzySet.fuzzyfy_series(data, fuzzy_sets, method='maximum', alpha_cut=0.0, ordered_sets=None)[source]¶
      -pyFTS.common.FuzzySet.fuzzyfy_series_old(data, fuzzySets, method='maximum')[source]¶
      +pyFTS.common.FuzzySet.fuzzyfy_series_old(data, fuzzy_sets, method='maximum')[source]¶
      -pyFTS.common.FuzzySet.get_fuzzysets(inst, fuzzySets, ordered_sets=None, alpha_cut=0.0)[source]¶
      +pyFTS.common.FuzzySet.get_fuzzysets(inst, fuzzy_sets, ordered_sets=None, alpha_cut=0.0)[source]¶

      Return the fuzzy sets which membership value for a inst is greater than the alpha_cut

      Parameters:
      • inst – data point
        • -
      • fuzzySets – dict of fuzzy sets
        • +
      • fuzzy_sets – a dictionary where the key is the fuzzy set name and the value is the fuzzy set object.
        • +
      • ordered_sets – a list with the fuzzy sets names ordered by their centroids.
      @@ -451,7 +476,8 @@ @@ -465,7 +491,7 @@
      -pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset(inst, fuzzySets, ordered_sets=None)[source]¶
      +pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset(inst, fuzzy_sets, ordered_sets=None)[source]¶

      Fuzzify a data point, returning the fuzzy set with maximum membership value

      Parameters:
      • inst – data point
        • -
      • fuzzySets – dict of fuzzy sets
        • +
      • fuzzy_sets – a dictionary where the key is the fuzzy set name and the value is the fuzzy set object.
        • +
      • ordered_sets – a list with the fuzzy sets names ordered by their centroids.
      • alpha_cut – Minimal membership to be considered on fuzzyfication process
      @@ -473,7 +499,8 @@ @@ -486,7 +513,7 @@
      -pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset_index(inst, fuzzySets)[source]¶
      +pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset_index(inst, fuzzy_sets)[source]¶

      Fuzzify a data point, returning the fuzzy set with maximum membership value

      Parameters:
      • inst – data point
        • -
      • fuzzySets – dict of fuzzy sets
        • +
      • fuzzy_sets – a dictionary where the key is the fuzzy set name and the value is the fuzzy set object.
        • +
      • ordered_sets – a list with the fuzzy sets names ordered by their centroids.
      @@ -494,7 +521,7 @@ @@ -507,13 +534,23 @@
      -pyFTS.common.FuzzySet.grant_bounds(data, sets, ordered_sets)[source]¶
      +pyFTS.common.FuzzySet.grant_bounds(data, fuzzy_sets, ordered_sets)[source]¶
      -pyFTS.common.FuzzySet.set_ordered(fuzzySets)[source]¶
      +pyFTS.common.FuzzySet.set_ordered(fuzzy_sets)[source]¶

      Order a fuzzy set list by their centroids

      +
      Parameters:
      • inst – data point
        • -
      • fuzzySets – dict of fuzzy sets
        • +
      • fuzzy_sets – dict of fuzzy sets
      +++ + + + + + +
      Parameters:fuzzy_sets – a dictionary where the key is the fuzzy set name and the value is the fuzzy set object.
      Returns:a list with the fuzzy sets names ordered by their centroids.
    • @@ -583,6 +620,25 @@ +
    +
    +pyFTS.common.Membership.singleton(x, parameters)[source]¶
    +

    Singleton membership function, a single value fuzzy function

    + +++ + + + +
    Parameters:
      +
    • x –
      • +
    • parameters – a list with one real value
      • +
    +
    +

    :returns

    +
    +
    pyFTS.common.Membership.trapmf(x, parameters)[source]¶
    diff --git a/docs/build/html/pyFTS.data.html b/docs/build/html/pyFTS.data.html index f302829..d9de2ff 100644 --- a/docs/build/html/pyFTS.data.html +++ b/docs/build/html/pyFTS.data.html @@ -194,7 +194,7 @@ If the file don’t already exists, it will be downloaded and decompressed.

    Source: https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD

    -pyFTS.data.Bitcoin.get_data(field='avg')[source]¶
    +pyFTS.data.Bitcoin.get_data(field='AVG')[source]¶

    Get the univariate time series data.

    @@ -230,7 +230,7 @@ If the file don’t already exists, it will be downloaded and decompressed.

    Source: https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC

    -pyFTS.data.DowJones.get_data(field='avg')[source]¶
    +pyFTS.data.DowJones.get_data(field='AVG')[source]¶

    Get the univariate time series data.

    @@ -289,7 +289,7 @@ If the file don’t already exists, it will be downloaded and decompressed.

    Source: https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD

    -pyFTS.data.Ethereum.get_data(field='avg')[source]¶
    +pyFTS.data.Ethereum.get_data(field='AVG')[source]¶

    Get the univariate time series data.

    diff --git a/docs/build/html/quickstart.html b/docs/build/html/quickstart.html index 2b730fc..3c7255e 100644 --- a/docs/build/html/quickstart.html +++ b/docs/build/html/quickstart.html @@ -18,7 +18,7 @@ - +