From 0cb3bccb97728cd9f4378f0aef9808b081f6ce90 Mon Sep 17 00:00:00 2001
From: Tereso del Rio <teresodra@gmail.com>
Date: Sat, 23 Sep 2023 17:18:33 +0100
Subject: [PATCH] Added some untracked files

---
 config/standarizing_values.txt | Bin 0 -> 26291 bytes
 config/unique_features.txt     | Bin 0 -> 24330 bytes
 config/unique_names.txt        | Bin 0 -> 13100 bytes
 main_reinforcement.py          | 134 +++++++++++++++++++++++++++++++++
 4 files changed, 134 insertions(+)
 create mode 100644 config/standarizing_values.txt
 create mode 100644 config/unique_features.txt
 create mode 100644 config/unique_names.txt
 create mode 100644 main_reinforcement.py

diff --git a/config/standarizing_values.txt b/config/standarizing_values.txt
new file mode 100644
index 0000000000000000000000000000000000000000..da16d47c27017f97975b7e6c900b3eeacfe7e7e2
GIT binary patch
literal 26291
zcmb`P2Yij!8^^^+NNr;8J!-^`buX@2tFIL^f><S-V@6T)4Qf>p6qVRpZCVl<d+*UA
zVx?-NR#58y%kOa1y{X=t{`<-2_j&q$|M&Mi_q^wv_ul88{zoMnA(9mH^-hu`$$&w9
z{dxuZ_3zgwXn<e*zx3<w*Dauj3<wwy9}f1Her4nT2Yvem_Uqfrzs~^S)-`ZY-~K_R
zyY`a-rTY%*Gq9Jxl>R}U1G@V6@t2+=sp6j91_t#H@D#~>lOj#`DkAyB3Be+TA>507
zmdw`;*QyJTrcIkRdV_x`pCuV6Qg*46vPH=)M#(KNEh3dEJPq+l&!j!w>!jS&v);Ie
zaj_PW+7xLFk=7LHd@CmO1_t!%5%{lfBE2&GWm66OJ+_DprpRcBOzLX>$9ucBER9r|
zP2pvTET+inI97fAhyMFmWmAT`Z?(r?R;$QviX4W>sjk{WPXBnnU=gdxWs2N}$YYAU
zj_)WwjZ^O^pE6xsxLsJ`c6TizzbOhBqM*8ZyxpAo6ZgkhL?KfYHbfCq6!k4<KY0Fw
z1A6@XTPmg;vkeQ)IxIBKB8r=$gds|*tM#Xi@~Tqqo<)3Wic*FsZHh9!l@iS3)O#wc
zT$8NKzx_!mPpj}YML9#1S67>k8XXg|KCM+$FhxZ}R5C?n-)afw3hXz~Z&-lr_wR46
zin89GuGN4uxn5g@k147eqMEwec#g=tqzK+}byL(ZL`_pzI4$CDk!wrHstkwya6QZN
zZ7HmxmMLl*qK>-ySAp(FzB}Y@6*g1UHAFpA)aSHtNaNHHHc+PJU(~L#;zUZTXlRN?
zhWJcf%@#YfOL&XaR?*lLO$^c06wMspky8`BxiXAsmZU?{^GNf#DGWojP*?8_%r88O
zAWchCv@%3%Q?%ji``{fpH~V~*W3IEwBJXU%7SYxe?F`XgU0olxeA$BaSj`<w(a{i{
zOyS4b=a|Q-q3f(%TXk*s_}KNNR^e}oE{5o;uKsZ1(a7Mm$*iKADFO`9-4s1I`y6vQ
zKl^$r>%jv%&hpvuiB<G6MQ=lVp|1MLH!)u=%wQFLOwrd6fu`ukLFBl(HvRf5$844?
zW&HZ3vI=1eX@~*p>bT22kIa9Z#wrGyVvr#Qn_>tD(J_xxgE&;V`iHLn_H0;|2oYq8
zVTSlpUA<Cud!OQl)hdRYVuT?^n&PVj-jh=kaFlX<G40LsX>TwwMw?=cA;zk!+k{bJ
zXF;szai$n=2-6h73B0HHJWjo*3Ci`W&X0pDheU;oiKdujh_BUEkKP?4i%rXG6_ZUd
z#Sl|XG0nF;wxtip&$-z?U0Kff`SiYL<FTr~F~tl+e5<ZDsaodCBkeFDW}0G_A!eH*
z#J6(7iJW>@bCm6b8cXwCsChG7%r(V4Lwu*M7OCpxpK~?d)qGPdFvLPreD7O5;bhLw
z_eIM4O_MwM3rx>x6``gGGsI$bHTU}0=^9roZWT*RvD6UDOtG8`j3cLWxHj=uDC;qG
zA4G}z<*Z_*DOMR`wYvJUu({*bfreJG#uRG}vCb6heJ$_aV!{cX8rKcVe#pvpzwC*^
zHu8fhHX34+y83y@<USQ`*z7l(Vv8ZRnqu3>-lbDZVY{+^;9sIc!994o>@dYnL;R?&
zzL~V3?a@!M7yo36U540gitzV0((zq7H%}v!_lP6gh9AkA#VYogVy_{7R#(@(3M_mk
zwxm@=nqr?J_M75>ul1kDl^LBH*n`U7wx!I*>9@VC;*cp08{&w%dOG!|UYX*M^{6S1
z8REDpPWaaSm#q5j|Le!clPXE>wWo5dJ%tZjr%Z9$5NFiYq24vll}+`)BF>uPoFUGe
z;(~7#q)zCgwo{+DFDl=g{k$8UKjCc^mrQZl5WlFan~pas^l%HN?XRY|Vu-7zxW*gm
zknQc5I+Za>d1vTfqGqetnIpt?Q$!o$hPv81d7+SXS+Hy0G{r4L+&0A>$M^SkraF}^
z=I#6YI@8ojyZ^L^-%N4W5WlOdHG3CcmT~EGi@0Zs`-XU6iieKx?{8bTQyF8GcW6G(
zuza4+EaDGSJTk;%b@kL1_d~PNKC*}>rg&<IXQqhr^|8Ny?-qtr>7Fa&5$3G2lVjbi
z;)N+*8sblNHDlwk$EL5w#_-A%uMP2+Dc<<jNHCoXcTgt5H!S5pxJyy|y|G9)Try=+
zs3DVSTxvt#_KWwvw#ekfDTv(}dq90_Cs@kgmx?n(AXCCi)$>aDdifkiJ*k+)6Kcp$
zG(MW<_Qm8W+^jM+aT?;ZjMG7V>wUZ)SH>tk{8UZVDm<7nvCd<Q%)mq$p@z()v2W|l
z#bcJ-waCoGUc^}#XNA6-kMX%3z6m%rI@#c&D*3hI?ceLQ!Q0PH`y5b1=G3_G_A{wl
zRZMD?xrlQU=V6=|%8eBn9V>BVT=Kz5RkLry(kC~zdst<DrYHb4WI>Jdt?p7a_HcTu
zEJR$GxCrB-Q0@xxOVj=-?bMhQgM+H#VXc94@72VcE>7zbP(zl~I69(w)bM&J@>Akc
z#HAURf%5J+RN=~al!c3`q)3y~g_@jxW|7{sF9$Vbd5uqJ_dMx!5!0vwaYf=vj4MMO
z$HRqPQdWV3s$zbnlf9BHcwmt}w5|#@WHpV~W^A<l@HY=FvN~}M;+l*tP{;9barcx~
zxTs1NeS7n9jL#nyS&R0yp@yuZarZQVAs%6|7HK1{OI(j}eJFR;5AKXByQ*ve3suI3
zSkLvbo*4Ir^lk(-<YyWm`($ry<$?DtvN3TJ;--w7LAl#Hmf^|_X$~7zO38K6CDuhh
zvdGWrZ$J&%LgTTXvy#=T|C>d&ByL6AnsFN_cU#9&T;6Tt`)jJ6@ktxzjNZQEXW5oX
z+CdH3UgIbJTdy>1eWQ--K-`hI6JtLpciWHD<H{IyhM%e_N5c*;<HXQN>CZ%6poZ+K
zaooA3J|ipbwaIS80mR)I_kg~ezwx;fx3lzwi>kysGQ*&d^eb$#7wvmP4f%z}a@;2~
zx7<ErlYNN$5(hHw2jy;y(Q&NAm2v40CsobhtDa#YNw?diU<wH}<N%G!j1hC&dt9-}
zfy9G|2QwZ5<!a&rO4N2c6c(zCI;$7>1y@{ZlR@+z1~ufD8W(Zzls5a97?k0}BZx;b
z{tC*~<XDC)BQgp$s+8jG7wq1(YkZ^}P5&`aLypz>#@1ifSHHU7CdUzvCpH-eLlYR0
z__>Tv_f9>4Ccr|Kv3G65$fcicw#kX~o&+`I*BW2Ea>G66-m^A2nRp8ERL0Yw35-a5
z8Lo`Tbl9j;@-LqsHn{!FTJjtE&wv{8TaCwBcJCZhV{<JzlXw>KY{nr_->UfZ^x@5M
zY0I4h4^_vE4&&UX+*@vwb7?*gYRK<2PMz-bt<dymY;r#F0^)^?zlZwPOt=nL#$*wE
zR4pw^`Sxx51k)gt3BsU;T&!`jbxnhJM%=c^CB#dKmoZ)r^{ta|EiP}mD`2JyD!lti
z+b>>?iIgjuWfjzrt2KVrw)f&*p4i~l5U(X($9O%|xBkBr<jN>*fT1etNap%)(l%Ua
zlRq%iMyMe-Y3wui?1Jr$aK|<iZz0~wcpFqt;`ro=+jh6ZMwJr0weWGTM&Crr9rWJ`
zHRO*Pe{;_}U|ma$&rig=h<7s%hx*ofJ3fx3xH2*kuu|o$&hu<m?sn^Jau0Ltg&Oi_
zjUPS^PW{k!(k3H`_Yv=Bd;rR4Hdm3JF^SrM55h~;b2{+&h}6#x*yJH5ISe)A5sep~
zI4i4LZrbEg;$y_e8J~dinf;M^Tp6R2@KZI#&Hg2Gz1pj6@)Q%Dh8psW#u=`c?tkv;
z37b4ie2(}$;|tJ_jgc!`@<n*5ddzwccMe>>&n7Q1$z`Y^f6=&4Smk<CGTpMtUx}{}
zUuAp^`hLwj-ZPgr#3-1lf{s=AbK}!*Ln7sMW{HLx@`lEpf9hB>(EGGa-Xy+7e4Ftd
z==(MQ4+Xh$*J5C(it075<zLa^8*K77X1WVC<nJ1XF0Q!o&VpZU@*eSh;s=Z$LVX**
z+lc<5D1F)4M`|owRb{tFU+(mCOo&bX!E}$HhJ38?v_1!JWxe=|O+F!hO8ks*9MreD
zvz56rZqMPYs+;5fV~rf{m|ZWJ@+H)ee`@UheQcrMmtVKZSH!Q0|6=?G>bL^qt4Q3Y
znFPO{tD0(d9W|&&bL<LkxP(3q6nz|xXGd30QF1e8d~)Ix#O{nepuUalN6fJ%SH>zO
zJXKxCMqa;u!HTg;#blmP^m8<x8rWu5sgu~PQWK{kPRlqQ)bWS)gg={k#}A)Agdo%7
zr7Hb}0x!OP*=@Z|W}s(AC|WlfA9*}8&!o?yY%(*k7jYKGS)q<UxW}h|I}mo~AnZ!W
zhL@`no=?t@xyv4`vh4KD0Y%S7<DB((-L85Gt1K6BZsI(Q^Fkd*;O&n1@$~udQkCAC
zZ)ZU3d6*da=~)1ZCXL368l4{!7ln^Mg@_9i7hzl!>No;_`*8a45{lvFs)W+ZnszMJ
zcCt+tr*8=;Iy4%mDD!6FvT@gJ@>Akc#HAURfjWH@!R`)}#cNgm^2|TnCcSA|4vM~v
z#wtIaP8EnN5?5ke8S2sz1-lxm;PtA8+o@+&a_@vsEj~1^3Po2&;|bBF2UI(U^;w;`
z260Ws7O3k-7wihL!bBC~)iz~MubnF*Wi7hbhN3B>ammwN{R&sSV3RiDy2SMu*M~YD
z0B~wSHo!|&`Wa(aB_EP$txYzhXCo+@F&cL>zPqt*+i{z0Ox%RHDdT2PSB^T^jX-m}
zT$QkC@w90<jYT&3IeiT%nlKutj~ja{A`oAsTN1Y-Zq2w2)NuryT9EPQoK*VEqf(2{
z8!fcSw)AWVMbAa!uG5b8uAK~@Cp!>#B<{r659;*M2)no68Lw6Ozbn|#ufxJaHtA2(
zE>QGWG%n|}(=&SN9rRa-1Bkmb?g4e_$b?-DJ@I-~!)A{!7nHsqj?M~=dqdG#(Rj(a
zUE{mH#<tvtxG!-a<9<-rk5bqb(jO+OkkpOmS4ulz51J};mryiSG;VaRz|DOJu`CA?
z4<a7ScnCCs;|NYIhoN|_%CDbKK{Oo(MK?ub{d^iuJc4*6<FB9z98+-m0W}J*S2e6J
z9vN{w&wQI4P2(|8v{5u3cJi~^Wmn_F);Qwv#3tilXaZy4)Pk6R*Q)#}UVeAB;L5N_
zIgzH5py;1yTs~^hp-j)tqklp?g?K9CY0w15!0AWSbi7{GaH@Q*OciQ<8!o@0@eC*$
zCmQ!}z4FufP4ZjiOyXI@vl)j#oj<~1HxcLH#j1e6+)pRT-W9#_xpbWeMaM+r{n?VQ
zimK#mmGg-g5HDo>J=C?M9d<=5f`KaHTzF7}!`E6x$WS_mLD4GFI5f9^hZajst6W07
zlz18A<xsX>`Ta<L!~O7!rsEIic9pDvi>f5a=P||Jl(}e;D`~$9iXMr^0R@jeOWz0g
zV-4|I;&qJILqB#%!l?zi0Vb-DYO5AkUA6dbxcq_c8=>fnXngjy_tOWmm{o2j-a@>U
z@iu7Uj)>Te%61s3Vhn4Fmev$!!{rWU*a<~vMB_ChN2c$!uYgtlM7)c5H{)>V$414e
zB^v<~RY<DlZD)Pqdp%t4q5EDadLkOvJC!|m^U$_d8A-g4ct7I<(DxHXe?|Oo#{BC<
zIS3b3$@C2Md-wLaY>|g(e;A5xh{nl$PSo2RfQfRH_!#kV#wVbOJZfThgHFOpRTFzW
zbb#BEj8=JyDNaMt2hrGl!u5{b0?JtBS>kiV=NVss{+A;tb|qbeohs?|kI_w%6pgmX
zOU!c_idKlmKeetrr|FV>R{1OO72>OmuR$G;ZoFMTPA#J-IH)QnZ=d+x_K8O<@;a@f
zq3C~T-1$<MCV9u=Hr*t?MSPp_9VjPEd`3M@;{WBNUr6o7BL*(2k~@Q=-Ta1>u*%<P
ze;10ThsOK=>}GrF_L)`QBfd}kfbm19<9NJXIZlm7EF4r7Jtr>hGrva$tNer3kDzF9
zXgs}wpYd($HdgtB_$l!-#&J-`@%Y;#&#6kD!$noncvH7wgTpRa<O|xrgrb?D@id<z
zdoRtvgXb0TYvR8czk#}X^u_MBBuVzJj24gTM3!mWAVRv~68aZV^e;4CmA=sZ&PRt>
zWpd&a#O{nepzJ??FhTg_ab<?2gpC@JGUr|n_<BaY2$_oho=~(bH2%Ky?G?MHpp?|a
zX^7J@P6zd^jaG_dDSD^-$7Yz_(4>c#swdymqc`qu!TFL5Op+0b9)`wWZ|R=A{7tOj
z%*0;ASr})9{-+}`b~R;#pQ`Cz>yo>C2l+<G>`ascil&CfvFAz+E?X=Z2T_P~6X#)^
z7y54g#^0Y0*R->vlMgPclJNto1P`c!pYQY2z5o>c4UNlmtsge%Bu<AEA}&l^gmF=5
zB9Fw_jY}~&scH;2ujX!E5#h2pQ<Q+B)uHj`j4w|;^)86RD8!|ROEWG5bvy#{b}>7(
zrpv-XRk3BwOKa+)55lE4t;<2t@X$E<%gUuErYLWf6^JVmS7KZl%DWT4p(J{@tpXQS
zNude%#{K;DO&ms{eN`yh9vTn2`XpC|Dfq-vowx>ZO~w|e<9N8T+gjnEsyJ1<iD%Uv
z*j#GSx;7L&4~<LKul7fai&)V%;=0837}tk7j)$weZ3DQdN^&fzg+CksX-NA<P_#cZ
zo_QrWWLsG*^~S_ah?_EQ26gpFjNLSC4vV)FBw)H<<8+&G4u#$Z6fF>q`!;J{f7Tz^
z^ji|QB5uvN4V1g>2NT5Q-PRX2s+98l=SH|}OaFFIv_mxZ2+Vroax`X02jY&zof!K;
zx!XFH;_`0W8D6TMHeZDNQEJKsi}YubE>N^bG;S~_?$6-v_@vT}IDoi2;~voebR@>^
zcJ+jxs%dbiTP2FlzipAdn5Z`t?GlZ<b(C?xcEhgHhqy0sAme_}ck?&#yKR5Cs7fjo
z-gWMIotG9VXfL7YmuT$OvEIVkw}A%|4<a7ScnCC+M`G;8Whk6fH6DY1YF&CYp4351
zF${|CiN*sKWh=OSCf4<E;t|9n8Gi*$-~fm#+wCY=s4{M3Uei0QX#EH|n%-leXrO4^
z`t;~KzjYmMmE(xV6Pt{Kq58M;#P7EgV53S2-E_TJ(p_~U<V5;Uf})qAajT?f?j>!H
z5t&Rpg?K9CY0v~l#FY(qIxJKf7IXDnuhK6p@*8^3fTEqE@r{Mor}S#}+#+WZ&mx}9
zI0Tx&h`74r&Vh|8Ws!gO+5SPrt#U5?=Rwg}(Ku{az$e@8G(uyAcmeT3#@|C-J`!U$
zR~NxU)lqc0EU{ef4VR%b4}+q&qVZ4V9^9Oj5o>q}@lxVtjF&?bbtJ~FmKE?(wNz;o
znz>OZw*Qq(unLOqipJlys(H9h7wmCsh}ROYW4s>fTj$-6h57@6L!ZZ~4=fvCrV84Z
zwP>!s!}nR_56rR=iY|-B^Rl+f6Ojdjvzd4c@m9v$pznVk|A&HH`5v$xhN`GXeNH^<
za{>oxcQDgVD7q~g=kt8JsQ$it7WotLF5=yc!=ZW-Cw|+FfQ>38^QeqIVO<(V$UXGm
z3q`+0<NGJlhc?JE6#W+BeZ>12AAlzINQ~Y5IS4CNPR#gD_=`f*g*gsG(R9(c%dHKY
zPFQf{`Y7=+;^T}@K>5u6aK`BS=E??q5?-pFpy~$(R6p=@xID!qr=e)OXzbxTRc`db
zd_GHjj`%#|3sA=&<P*OWUxc5k>G_s@d&bPzioOdIU529XqH)U<=d88b;B(Ed#8-%~
zGQI}=*ciF8B}c(a)#FiOruFKpBvyHyNur_Xz-Zj>b((2k<a9#^hWHloZN_(?@7KKk
zXr=ENZ>6(e++tv+3d*(U_*S2uuPpL6X1NPRBSzyNi)KyNEDfF!_lWNkKVbY2`hLy-
zLqV>r`B)gLqK;JPxy8R?3iM@|=@Art8IAK+&rq~(f6VMB#7~KzF^+@&ACAP>t-0rL
zRh7j}$=Kn^P<(TE!E`U7=+kKYsCm$ozTS5%@)hxG;=dTbf&QP4#Mo7rB>B7QV)CuX
z+42{B@N>f@v~Qqj-)MYw)VICUe*Xmj84+;`Vt2+KP{$RR_)Rk<{M3j&vb3-BJP0+V
zVj@o{`ZyYIu73W<-CloLWNP9x#Az9)gZ}3uF?M5>9-gYMyb*4>BHS<-8JH|16#X2H
z56P9{%W-(@WG40^&cZk=)bT(_!q3`r@tfHDBQe?VQk8zGd-BUZmGPf+Wv6EjC|Wlf
zd+z$8XR@$3i_Arwn>Y{SyimsjA@S+oE;hRZA$BF?!^>3(K_`AIws|yi<fm@|D0(&;
z+gda^ux2s_s1R{s;v$TTLLEoo?T+~I^u_Q}mA+86*SFFX!B$wDo+Y4Y(rEnV_mLF`
z^ufgVl(-aeX~t!sjwA5552qh5p)6jmN*GwaQ|6|}l3ArUeak`7q0zY4lhC|5&S4v>
zKwOcy664BHr;o(g-GM52t;(PJVBE@xmC3Erho)7b=*wtaph&gazGbn`RVS`NT$8Z{
z>e7)IyBe%`y{e)8&@ZF9Hu=OVYtgti6kQpO2lNWvo7E>1x-!IdiR&@04|V-Wj9noO
zV4@0XQaQPM>xrqYvLW3YLD7`a_{pk)Gc&zHA&rTf5I1Gq4C;6w#Hj_@94}SrJLJq&
zET*TYRenxS1Bzyh#%=>2PS0==zbUmOZbjUhaT};BM`G+oz!xu9B`ls@zE|-~D4{KV
z+d<KU(YSNh8m)?VLkS&-I}&$d><4um0jCyZXS`IU-}Q6jE4Ln`vPyq?c7dYjqVa&9
zH<F(TM*42V0mR)I_kcQmB*yOT_rz;e{(D;kf8QF2{iqjBdqdG*(KxNg&gPHe@aXMB
z+?P0zaX+X_M`G-1=#ST{8us1JlD+z;Sn`6#5{k}>#@CzGFCX(AR^&k9LBxX@4}rRV
zB*w0gp)gT}1f5&Zc-9;IXPZHE9|lEJMdQ33A|Fqfl^snL;t|9n8Gi*$;5dj=%V88=
ztMV_7tyL}Nk(X7Drs)_cx+xkT9g#O%hzCA6k0TyWY%&gpCU6|Y=?ByVyk6B{?%14h
z!7<FZi8P)BMH@xqg;9$Nb&JZ4HVW|+;;D?MK@%7QrxwI?yjJC(IP1Z!Jw31^eM8e3
zQ1nkUE;fJbmf-4{aU6ws7V&JxA<zWI!0AWS9K2rD;NR{3jg2W$!(1BAgQ9VwabV#u
zL)^o$E6yigK)jIg_fY4L#Mn*5MR>6)AZ71EkA8GR0ikpagQ8=i@$sK0|2Xmi3RptC
zlz18A<xtm-#Ml+F0tTvx&V6sJns5YL(@Hw8f}&NT@yKH@KP#FW6J-tYTH<w#*F)KQ
z<@cixzb)zSERH7~>?+v+7gb5mORvf=JA^MpKhS<76g?7+&m0-Kui%!a7P*;t3-MOQ
z+n^si{NdCB-42ttLlT>5(<jyOu-HNOolx{eH2$LQ<c7JbV@Q4?-bK8daX2(_M`G+o
zB?3mOm>f}c!+IXa{n^6|d!guzXq<G5W#sB>_?<nHcpve8#s{Du8x^OP>_M2QLLR<4
zjz2s@4$=KE6g?4*zs(o9bm((DLyi(3BR<af1oZtx(Np8Y8S}3b<s@8GCHtp;_vQM|
z>2L^z_NSrfhG<-??6B+J*R!G<LVS++JmU+{L>`H;yFnM>q^fbt9$KJU9emin#1xmI
z=!0lHFGJ;(+qUD|$gjj#h_5of2K_HbV(dzaf}JWUIKbBoxQGdSoq3|6XoYC}a(p4T
zB0DgFZxY`kzRma!)bR+&+x6qrGKztNs^ZZ%>sD{rga`g_w7v^P|3l;Iul%C?Q=!Ov
z#P^9GFn$Q-go)3nr%C+3e6;CdHy*KYQI#AFntvduLwwVN_K%=wdT4xY(z+k7w8iK2
zC&W*QpD~VuI*!NNmE+WSJcom-Vp?>usnNx-zrCRKODGx~8V~vTOxmFA_&-;8Mf{rh
zFUD`6j^pvSN1juaBuVkElBtIRig$g3FK2GJgk}a5%?yo$lQ!+J<`}*^B_~cn?9SK&
z>gtggyW5fy7HUAw?|3w-+X5_&RP^?QqJN?B@@dI;l)Z=cMrz_T#Az9)gR=kp!35!R
z$dwtA9yY3!J6%fO?ot}LGSELG6fKMQIOfW#ArjA?%*0;ASr})9Ci+N>-Oyx%m#SxF
z?+M+C*f3+WGf568dKelv@kuqb+xPA`enOm^I1l5z(EoHK#;&G(@KZG%h+X=;;3dqO
z{7h5;il&Cf`OQgpJd2>@Ld1oMi!d$<eK&tyXnfgKQVcGtlH!w&Wd3z*QuH@yUjmB$
zhQ{9-5hFK^MWLS(mm)6BxC}IrM`G-%DGMi6&6!e#E9|<1C$u+Hl!Kzxp>f##zz&DH
z;%QZZxFT^S#+9LtM?l^#W~bJ46*#CW?!BzmCb}|yk@TT;RVW%B8b2I7c%c6Qw4ACF
z*C4LR*aGF<iQiBXz1v#hqAE!d7uERUFZd=`i}tmlXnSZpVs`t^qXc$a8*yFYdW`Es
z9mm6!-L?T7?5b!;>qb!YJT%r-G$w9B+>~)MsN;CJy4yB~i>f3jXPyQzcQGA5r@aA1
z`$OZdi`=VqIEUS~C2=d_){NUgT|E+GH%)zEp~^V2a{l3!^U?KdOYe42v_LctOzZbo
zk1zkU$PUCEi90d&gL1e1V1l^3+jfSHDkUU*b=yfz@Feu7e-|j)AsS~&6H#bWFMO2j
zMjSxgopBFnqL0Mb4NXsYsd|>%9<-c%0(Ynvlk|q7J)&{Ch-+baqi~1%5ceexWZVz>
zpN_=X)zlw;s-}u-Ji;qX$N#C1U?K@cyF}xsLv~#_UG8@rL?IqTJecti=)3uw_}z9W
zTvR2tHR~IXJ%iB+qWv%^`Xw5FWr?-^F%0|uaN-ffBN=}MP2`anyKxx>C%bz!nkmLW
z(LK>v->Y%N<B3hi!O#Q_fVi^VPJo3fBmL9n>7F*noR~=ONl-LUH14}T<<y`f7?jDx
zQ;4TBo(9#wohN?3oempSN)s=?gT>Pz*EjT^0YxuG<Bk#0FQ#X}XN8%>vxsLi4uK{x
zBCc$>b6}y$xa8h8`pR&WF_+%+plGLP?ACwamO<Vr(M};=K)jIg_s|4J#MK>l5o}Z`
z6~l&JYg`apT`2v-plGaUEao=p(`GP!m|a4=lz18A<xrQ8#MsT%74T4X6w7iZFm4LI
zoUf$$Dkyp@8W##F-qIF>PU9NlwZ!WfuZJe;NQ_-A8{ngAX?4G1@3wJhHvPZ^8=>f~
zXq@THzN;D5qT{xicnk4X#@nFpe;(H#5V-&AFZ2KS^SE6>+hL{(@;KXJ=C)ZVXa}?G
zgrdu$@#@W4J<^uWf-Vd3F5=yc!=dkg9{-1eT=^al0Yg>P*AHT*K8V5hfIZB#7m99+
z#?zjc@{4+b9!MndKH~k14?y)KPW-le5H_k5-<Lm3c(BsjDi6{BFcke3ji;A5=v}x=
zJ)A)yK1O_;@d;>RkHpyBu9L7*<wX7#8q}y1x{;@t<1`da7mcr_PIbETP;`vX5}zYJ
z&-eoLW5+#Q*?=#?OVu;F_=~yiDi%cBg-I?$(RR_e#qYW9x5`!p$4`i_5MO0{4eI!V
zeByWFDEO(G1}#b9-|HOC;aq2;XejzF8uz-Kbnm>`<<NH_zD0bS@g3;L#>kZ|IR;*;
zo?r5|2tNE8U$B2;lDklJU^E`<ZG^XPfPL^D@qOY4j2}YZuX(-7KU{0huK8G)se%r6
zHj|glfnDYgW_bifBSzy4!-wS0_9zb;F~m=apD~VuzF+hIP>?HY{y7X)QRjA*2ppdc
zKe)VLrk7CkWi;N}y5b3=2iD;$;@8A~F@6L6KOBj%TXRX=-&J;DcaCw9gYebS4VTcT
zfuc{Naptmxulzn4TV!(L6vXa~J)r-mBQbW>rG&E@w`-9B%b!%k2A+y3J)vmdXk25;
zXMap7fP0;qI1O=H#_6DrD=_h!W_tLknnvCkg1`7a4ijaBqK~8T@Uz8AuBnRsJ2SBt
zaTdl|q5t_vjNMpegQu$N!0NP}@;1Y7j@g+k2NeArjr&E<^znR{6a5_G+{Aep=Y<X`
F{XfJrHJAVZ

literal 0
HcmV?d00001

diff --git a/config/unique_features.txt b/config/unique_features.txt
new file mode 100644
index 0000000000000000000000000000000000000000..98cf316f0d45a64c1fb67db201cd772b86525923
GIT binary patch
literal 24330
zcmds;ca&5`6U7%n#Wi5S95G_TS(w=c#l&D-MQ8;vAnpJPN~!`>jF{S-bIv*EoKaCR
zqoSgsqGC>{n7>;!ZNIng>^Emm51x7BAMY;Q+F9rRy1JNs{hZWx5Y==ZGJ3+Ou@k!t
z8N<W6jG8cV{D>yzrir!VhBS?A;#z7`tk(`5KXL4^TAFWQ+nSo1{@EVX_Jre)qjrYo
z@7&mSU>le{X@Nd{`ZP{%Y}eR+JS|wrPaX$%0<KZG2ICrmYqb0GSbQCWYb36Txa51~
zdy=n_@7c%IhT`imT>Ii;_h<S0Kd+5{?*Z_e-1o`P&EQJD2YFxe8hKChRsJsTQC=tS
zOMWi3x3rL<+Tm@6yX?7cw6J7f#L%M1K3r2zE2dtoke`-J5RzJchP+Oa{`2lCN}+?L
z#SJYHQ9uVQDHN76)X`ILYrk~h+6#YSe-JKNtN40WWbK!+w5*}!qSRRX<t6nBhF0{c
z-P*4dxc14^sayM%Ev;f`)fj~gttJ#Y8Cu;_m{QyUYZUTRLUw?xyX@J2_IE1Qe@#nk
z8CpA*JWK0H^3I0V^~t9fldo6EPoG!GQ`ZCQTiU?Th7k$u|1LseBSRTa!tMV$?Ehp}
zhfKkW@Bglrx*5twsj>falDghdgHP@De|PNvd67DGYv04t#)dYDC}8b-3WZG#ZRRPs
zwck8&?UUpxzV=&K+R{+3D0MDFc}d;d&{jURn|fPg>LnAjrsGpN^|rCJt)cB=$+NV*
zByTjdgHP_J-j0}h^D24jI=_#loecGjk;qU#Az=*d>`AyD*abb%(t5V050d|GRJ{B9
zTN+?!*I4o_4V2`&8QR?^cRjENdSG59PhAh}X=#w5y<#LXG+0RNZK%nUa6M2cqX&|^
zsNy{^#L`eh!(z#^w2vg;*U)gE-1WeSGI}7HJas*=pQZf`jf|0~qftU)w4pJc#MI*F
zz_Eq=)X?3~((5YT2V{v2jf<tv(RfKe!O#Id{fuJz0}J^XEv0D96m02rsq2M<EKM|Y
zaEwMh9U?RiHFTJ#F|$bH@IroOa<;dIMDjK99w=3-$ZyF<Sej($$Yw;25+X+%Iwncv
z*gzu58Ifut*3xl?j*k&(pc911iH1({L}nFx<m5trR&q^S(<3eImQ+(Y#nP#UPK&72
z*U{-h<qSh-dMa~@RL&~o=gccA@^ge}OLx<f|BX1oitMJdEuCZN+=x=Hp3W0W=Nr1f
zQ*!g=LhPpG&S*{VluBKyRuLi>S-RNJCC!LjDnu?bba|4<6@f&O6ytr6IwDtEy2{Yi
zF(M6gjS#uk&~=`On=jX6z9iGNrbnu7zT9BxMngA6R4`v|7Am(Gy46#0^W`?omw81+
z`lD**%k7r#Fmz``Dc3-E38lLY-Qy{_-nkdO(^4O_rhiK9no_lj%$WNu-EZiDW>g*&
zDi0ZYI7#J^GN>ebF4c49QA>{*dOSv@J3S#(o;387r!u?vFZSd@es*ZDwDh`ElX=?G
zGlrgx$kcbGDMIEsL(h9MbBknNDCFn1l(03ssHN9c)x4Q%=|w{?MWk@|_+=sWilJ9M
zDR=kywZN0Ze`}u9VX_CE8ozF7nxQwM)HpeKQ&PWWXu41BP7dA<JUL9JF4Y(1Ox0it
z?^t@*(2R%z*8V-A@V=oBJO#J*GXvMY)I_aF>JKe_Wa#54HP(KXr2fRvr#`h?`_BT`
zKAAdoYd_o4=Z3zBQOMAjLg6bzUwaDfzUen9JT(sP`fn|LXXyJ_@+|!z$$vC7$0v99
zO@FF_Q{!L~KU@06(A<aw_W!R!;x|LTdlGK{{}Fg{n4E&~&kYsX|9@Kg%h2CZ>RdOj
zX;V{!;M@jZ4bKPl@r#3i+rmrv336y3a64qPJilgN02-mm_TU9!2%7d<UI^;Z6gz`!
z;RQBFa!gjbIe1}YvAl?8T@)Ij$Yppj7=ogMmKTS56vaWwOTbIvS#xk_EQvgpm(si)
zp)nj;UK)nrSVqgsLOqV+^yKB>RlxytFrMX+&+-bIe?@2vPli{5A$V5S@+we|$92o9
z@X9!mOxtAT)sV+>C(XM$G=?L~Yrqg3YifBdsK?>DWo>w698)H7r0pXYuY-J+J8S-R
zp)oueUJr)gSzpT=Ks_GUEgQlsqgzrpYP%qh<&89N1{%YW<vJLGqpOy?K|K!FEm?SF
zbW0LP>bfO|e3t7qe*-jzr;fYB5IjA!yfM_{DIRn4Ch$^v(j7c*dm@wNO*Qjo&=`^&
zZw^C{Y@y{Xp&m)`?3;VRtCHjIU_^OjwA@=6Yz2)Ws^_g?2%>GYye-rtDjrzzcJKmE
zfRp1l{!y+}trEWj@b<`QxluXn0Bwe8M;L;skCu0WCNcGe7l<i2cT$b1A97kY%3)_{
z3{wN|0z)wM*YW_U$23cCtn#k#s_gVUc;m_cV`F(YWwARnLRDYKd%zG>dun+Q)T1h%
zcky2Es{BYj7~NoGx4gHqX@W-Ra`jw*A?Su^c_`GQb2DogyuefCQgf+Pts*mPALO*W
zuW}d;ZH8$C48gRYmiLDyF^z;5h^eY()+pq(JX$%7fyOX3@K_jviL}g6kIBufaqz0_
zL_T=qjYn3?6O_dP&<GV~)`2ht)j?XG2=%Dk%sLoel^@dwqdNrIEg!0E4ueMMat(Yq
z3_*8<mM1|yI@e`K!YkvHy3}kcRjbI{Itp1WAFV8ofi^>REDS+qwR{{jiRyTGWuU66
z*>wW4T0T)(oCJ-b>dq&_5LBmV`BbP!HM{tE>oj;(c*-BV2~S5}%V#K$GocZ#`mTHy
z48e7_md}BDTyu-K&V~0MIQkF9cOLRvK41A<0FChBw*Q4N1m8tkz8LE9x!eAizzaMR
z{<mgS*TCli_)=uCe3@pw92%j(;m{Q@1jUtFz6$D5xWl2V;RPNPCsD}X|KG!E<&5uO
zG}j=T<!d$jb<hY6y5xEog60M--w5?+T$kJgFR)8WjqZw|xEWb2-=bM>g+?gQCAYy4
z6t`>n4yZ@ry5vrHfnAbBk-9Fq3)w8+t=aE^#?WN=UKoPrJ}uu5^=RC^?FZnc@EL>P
zP4gh~Sbj+JJ`9cF$nqmF1jnOVehlhyxO>}=!>fV^4}$SLfqa&q)cj9DBRrTXlVJ#+
zr?vbH)Z=k8<ym-v2hPcH8^8Tlk(n|DSu8)NS)YeSC@@oAfFUTRYWYQ|N8x75OYl<u
zSVC}@yo_v?U(xKZLL)TjlGk7en%A{F4eHUjE_nl9V3#DvZN<CfO=PkBmS&v}jZomR
zgtuV`ig&d9F4UuN<8=nS6h4*^+!^m7kLC9@?+4Hrjx5iFAviwN@<&jQ!;ROE;Z?z7
z3Bh<~A)n<>H2<g27@iD&21D@7*7E02kH>Y(7x2nBXinXT{StXBf2Dc9hQ@GY`5PF5
z<6A9%2lY5yw|oz;jDzMRj?{g0`vLhZ|ET%rKx23^{1Xhp^Rt$JfqFcyTjs(mqgzrp
zYJWu@%fD&f-=Q%aS^fit;P_L^e?dJC*DZg;E2CSII8xUwHS-CcHc&h#360^Y<F+sa
zPdhEo5A}H5V+jkuOX*_?!Q*y8WU|~|GcN><A<1zq3_-H6mKT9~B<`_<Md4M+V+p~C
z7DGnM9hAZ1&={h6UIK<7T2jkPK|LaO#McpC;CXv;{Kh}Zm8w<bmw}~`)ABOPVOeN1
zOv}L#Ov`I|1!xk}itqw4CFf46F|CB0mRD8|t3YFz8hBM0f@w7^cY=CMvx@h9SBF<+
zk0k_eyfu*3@|wzGEog)aM|^9;5LD}Exii$Gaz}jY!mIMf5`xjKhwPTuS2i0!BXoEy
zVM7>#u8Wp8f_ijrW@X?7p0}5pOQmWRnOSwnX}PO%=mu?uDGNg|<+NN6O=4<*7l^5<
zW>$CPwA@2EYz&QIYT!*^2&SG|-W2LFxtX;YyefMvA$a3$j;xlqP!?N4BUG4Ky<iBc
zyq0@IJt{Y|wt`pXk0k`7+Zx#|Z=-Csg+}P`Si*KN1l{&pZiIStuFH0SSH@X;so7Mj
zR*|{2BeGiVqbzoUHbd1HhM?-FWdlv3+8JIMsH$pq?Sib9`zwn9&={)jyekYrHBigD
zK|QM3#m`&2!>hu_5`s739>{BXPvtQP8sWlY346g1T!Xc|H`L>rTg24_??3QZLNLAp
O@>?FFe1<}Yb@?A>D>Hon

literal 0
HcmV?d00001

diff --git a/config/unique_names.txt b/config/unique_names.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c3faa5341dd8a5ffed925cbd446d14c77c1ff3f0
GIT binary patch
literal 13100
zcmb_g_nTBj5In`4bIuVHa);y$0*a`Z$AIf9%Xxac%iY2Wm@wy@bIv*E{ExZQ-wXSy
z=gsTxz27*#?dqE9nm04GeagDAfvIkAU|^uLxmg=&)i$<Aw{~j&kM@Sz`o{2hqtWsI
zoT!i2ru!c>+pTtUq(0gi+riBY)pbUOTa~pt@}AB5mg=5Ucu!v^>ba8}LcaBh#&C7h
zo!zWpp{VOFZho-1)!tOw));SBx8Iet^2^lCXE)M{)rnZ|&U=dHvj=Hh=qb~9Ptuqd
zirDT&8uMbg#(NWQqN)>lAL7jmMZEV7bQQ_GU!bcm6m{L-&FDI^NLe<d1KjLzrKs<L
zZb7(OKBj|c&_p&X(#`8&w>TvcMi4FKkQfiq1P{%{;5=m0ILs|6UkX8p)^fO8Q2~<?
zto*DW;pTL)LPv?{L^+Z~Vdcp(L=Z=D2FW}`<wtV{J^M-oag3Xb8l>|S)gS8?2J1B{
z9Osq=F?uH{B6GZ383)p^Iw2L;7qP=k#OFlveD|juLc`=Fa*3ZTemz7iPNs#hat(u1
zI0KDOPvs1>KAlQFEi6Li)6>YOyk4Wi>Eu(6q4wz+<kJX{hSiy=xW35dkh93AT|OK_
z!(<xGh{j?v>e)0SUa#RWJ;1>W-8~FMn`JP-!Pjdz47qvT&roq4DznaTi^2dJ7U#I-
zVGy-lXS!7tNE%+VGKGDW&9JlG(u5Jm&~TYUJDO&bsbaG3T-wnQAPuW|F;*Hg&(AHu
zm#1>%g4_ZnNSXyMbZb&Wm7rz+E#0?^+*&E5hUsEHS6^;(?Gm>dIdU)!yQMsr2!G@T
zJ>fhHS;lh-UzfCo90h8Z^PY(%<8|lqo;}~yc<l;t76N2fs<IF$UZu}M0O35IONi!k
zz9tKSo~wCJ(R?ltXCcsVjVcR);tTaz2q0V(NF_ufUmQp!#JgZ^psPscO9EZR``}V}
z76K|=rprR0`f|Er(t(kkj>WT%zqJA4idY6An%9-KEChI572_eApv%R`PN||Qm110N
z%tBx-*YuNx0M@lUiAbg*8qRejivMXQh5sXZm;r-zoIx@V5rgYFgPwgQf~aY;5Lm$t
zbh9mpK)XbvLfxE&0GS*6%0d9_rc_+Nl;Vg>FK7U<-k5~|OoJy8$!tX<-arfS#xVPI
zm^0A$^k&XL>(dc!76KaHLOv~sp!Vsl<}3urjP{j<09Z2>*Y4AnF$)1E?LZEpG3v(b
zm27wFSb&4Zs^b9;TCaB0SqKQZ$&`fv$maYZob7vdff0Q`Ch~`H36kb(e_N)o-LPA%
zSqNyfHI_PPth<fBne86FJ;q97<~wo=lwaFK7PvFFKnaq@0(VV976OyJdy=vcfZfjL
zYIp5DeP<!S?p~ftgr_;=&6sB)_wii9*Ciu_TmowE=RFfk#_Jy7J$t^Z@!AK)SqPAQ
zNR@>^@x%Ho1P~tKxrAswk7}|I==m7$DVopY;w%IjKB3A&p!i9B76J%Q1yTu-$WI4S
z3Gps?CeT$R^Rt1j;(hR(JPQGpp4Vj|Q2hd3G3oM9aslAae}H%~mO+T-^^z?M0Uj^M
zc!(zWN-jppQCKO)tHvw@*790ESqNag&Xb5_Dx%@ML8ADdW(M(pL@x!v;7!gTnTLqM
zTbx19z7j#at<6GU1@F+!wje_F8xt_zHD@6J^j=?C2!OqximSN%0K^BzECgUa<Vi#_
zThWL=qJ?;4n0@*&XQ1)vC!B%Sr=M!G5YX^5@@YW?wNF1cXCXl5i@vfD0Q)i(*Y4A=
zj9CaU`8tq8XpH(z_DZ%p_1gdkja9!3aL{`7dvz89LjGXNLIC8){2`p}dtnv=NI&Hd
z;SwaxnfG(1u-&k~ShEmV*{`wGL1W$D_?y}8;ooDdG-m!Iw?O%|O>~C*nOmR)Nn?S(
fCLs%fN&Y=aSqQ-X!{=&u?Z16zA;9jx#<c$dAK=(T

literal 0
HcmV?d00001

diff --git a/main_reinforcement.py b/main_reinforcement.py
new file mode 100644
index 0000000..daa928e
--- /dev/null
+++ b/main_reinforcement.py
@@ -0,0 +1,134 @@
+import math
+import pickle
+import random
+
+from config.ml_models import all_models
+from find_filename import find_dataset_filename
+from find_filename import find_model_filename
+from find_filename import find_other_filename
+import numpy as np
+# from sklearn import metrics
+from itertools import combinations
+from replicating_Dorians_features import compute_features_for_var
+from test_models import compute_metrics
+
+
+def train_reinforcement_model(model_name, method='Normal'):
+    train_data_filename = find_dataset_filename('Train', method=method)
+    with open(train_data_filename, 'rb') as train_data_file:
+        train_dataset = pickle.load(train_data_file)
+    # hyperparams_file = find_hyperparams_filename(method, model_name)
+    # hyperparams = read_yaml_from_file(hyperparams_file)
+    current_model = all_models[model_name]
+    # model = current_model(**hyperparams)
+    model = current_model()
+    first_polys = train_dataset['projections'][0][0][0]
+    first_features = get_vars_features(first_polys)
+    first_labels = [random.random() for _ in range(len(first_features))]
+    model.fit(first_features, first_labels)
+    training_features, training_labels = [], []
+    for i in range(30):
+        for projections, timings \
+                in zip(train_dataset['projections'], train_dataset['timings']):
+            new_training_features, new_training_labels = \
+                training_instances_reinforcement(model, projections, timings)
+            training_features += new_training_features
+            training_labels += new_training_labels
+        model.fit(training_features, training_labels)
+        print(test_reinforcement_model(model))
+    trained_model_filename = find_model_filename('reinforcement', model_name)
+    with open(trained_model_filename, 'wb') as trained_model_file:
+        pickle.dump(model, trained_model_file)
+
+
+def training_instances_reinforcement(model, projections, timings):
+    original_polynomials = projections[0][0]
+    nvar = len(original_polynomials[0][0]) - 1
+    vars_features = get_vars_features(original_polynomials)
+    evaluations = [model.predict([var_features])[0]
+                   for var_features in vars_features]
+    timing = []
+    for var in range(nvar):
+        # retruns the polynomials after projection wrt var
+        projected_polynomials = projections[var * math.factorial(nvar-1)][1]
+        new_var = var_choice_reinforcement(model, projected_polynomials)
+        ordering_chosen = new_var + var * math.factorial(nvar-1)
+        timing.append(timings[ordering_chosen])
+    # now compute which part of the difference between
+    # evaluations[i]/evaluations[j] and timing[i]/timing[j]
+    # corresponds to each evaluation
+    instances_features = []
+    instances_labels = []
+    pairs = list(combinations(range(nvar), 2))
+    for i, j in pairs:
+        correction_coefficient = \
+            math.sqrt((timing[i]/timing[j])/(evaluations[i]/evaluations[j]))
+        instances_features += [vars_features[i], vars_features[j]]
+        instances_labels += [evaluations[i]*correction_coefficient,
+                             evaluations[j]/correction_coefficient]
+    return instances_features, instances_labels
+
+
+def get_vars_features(polynomials):
+    '''Will return the features of each variable
+    in the given set of polynomials'''
+    vars_features = []
+    nvar = len(polynomials[0][0]) - 1
+    unique_features_filename = find_other_filename("unique_features")
+    with open(unique_features_filename, 'rb') as unique_features_file:
+        unique_names = pickle.load(unique_features_file)
+    for var in range(nvar):
+        var_features, var_names = \
+            compute_features_for_var(polynomials, var)
+        var_features = [feature for feature, name
+                        in zip(var_features, var_names)
+                        if name in unique_names]
+        vars_features.append(var_features)
+    return vars_features
+
+
+def var_choice_reinforcement(model, polynomials):
+    '''This function will return the next variable to project
+    chosen by the model trained using reinforcement'''
+    vars_features = get_vars_features(polynomials)
+    evaluations = model.predict(vars_features)
+    min_value = np.min(evaluations)
+    min_indices = np.where(evaluations == min_value)[0]
+    # Randomly select one of the minimal indices
+    return np.random.choice(min_indices)
+
+
+def ordering_choice_reinforcement(model, projections):
+    '''This function will return the ordering chosen by the RL model'''
+    nvar = len(projections[0])
+    ordering = 0
+    for level in range(nvar-1):
+        polynomials = projections[ordering][level]
+        next_var = var_choice_reinforcement(model, polynomials)
+        ordering += next_var * math.factorial(nvar-1-level)
+    return ordering
+
+
+def test_reinforcement_model(model_name, method='Normal', nvar=3):
+    train_data_filename = find_dataset_filename('Test', method=method)
+    with open(train_data_filename, 'rb') as train_data_file:
+        testing_dataset = pickle.load(train_data_file)
+    # trained_model_filename = find_model_filename('reinforcement', model_name)
+    # with open(trained_model_filename, 'rb') as trained_model_file:
+    #     model = pickle.load(trained_model_file)
+    model = model_name
+    chosen_indices = [ordering_choice_reinforcement(model, projections)
+                      for projections in testing_dataset['projections']]
+    metrics = compute_metrics(chosen_indices,
+                              testing_dataset['labels'],
+                              testing_dataset['timings'],
+                              testing_dataset['cells'],
+                              'reinfocement')
+    augmented_metrics = {key: metrics[key] if key in ['Accuracy', 'Markup']
+                         else math.factorial(nvar)*metrics[key]
+                         for key in metrics}
+    return augmented_metrics
+
+
+train_reinforcement_model('RF-Regression')
+# print(test_reinforcement_model('RFR'))