From 1196a43d961a95abc18d3c8e777e9a4e8233e562 Mon Sep 17 00:00:00 2001
From: Benjamin Auder <benjamin.auder@somewhere>
Date: Wed, 11 Mar 2020 13:20:33 +0100
Subject: [PATCH] Pass R CMD check --as-cran

---
 pkg/DESCRIPTION                    |  10 ++++----
 pkg/R/EMGLLF.R                     |   9 ++------
 pkg/R/EMGrank.R                    |  10 +++-----
 pkg/R/computeGridLambda.R          |   1 +
 pkg/R/generateXY.R                 |  10 ++++----
 pkg/R/initSmallEM.R                |   2 +-
 pkg/R/main.R                       |   1 +
 pkg/R/plot_valse.R                 |  29 ++++++++++++-----------
 pkg/R/selectVariables.R            |   1 +
 pkg/data/data.RData                | Bin 1010 -> 0 bytes
 pkg/data/data2.RData               | Bin 18385 -> 0 bytes
 pkg/src/{sources => }/EMGLLF.c     |  36 ++++++++++++++---------------
 pkg/src/{sources => }/EMGLLF.h     |   0
 pkg/src/{sources => }/EMGrank.c    |  18 +++++++--------
 pkg/src/{sources => }/EMGrank.h    |   0
 pkg/src/Makevars                   |  10 --------
 pkg/src/{adapters => }/a.EMGLLF.c  |   0
 pkg/src/{adapters => }/a.EMGrank.c |   0
 pkg/src/{sources => }/utils.h      |   0
 pkg/src/valse_init.c               |  19 +++++++++++++++
 20 files changed, 81 insertions(+), 75 deletions(-)
 delete mode 100644 pkg/data/data.RData
 delete mode 100644 pkg/data/data2.RData
 rename pkg/src/{sources => }/EMGLLF.c (91%)
 rename pkg/src/{sources => }/EMGLLF.h (100%)
 rename pkg/src/{sources => }/EMGrank.c (93%)
 rename pkg/src/{sources => }/EMGrank.h (100%)
 rename pkg/src/{adapters => }/a.EMGLLF.c (100%)
 rename pkg/src/{adapters => }/a.EMGrank.c (100%)
 rename pkg/src/{sources => }/utils.h (100%)
 create mode 100644 pkg/src/valse_init.c

diff --git a/pkg/DESCRIPTION b/pkg/DESCRIPTION
index 8dd0fcb..77812ed 100644
--- a/pkg/DESCRIPTION
+++ b/pkg/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: valse
-Title: Variable Selection With Mixture Of Models
-Date: 2020-01-11
+Title: Variable Selection with Mixture of Models
+Date: 2020-03-11
 Version: 0.1-0
 Description: Two methods are implemented to cluster data with finite mixture
     regression models. Those procedures deal with high-dimensional covariates and
@@ -19,10 +19,12 @@ Depends:
     R (>= 3.5.0)
 Imports:
     MASS,
-    parallel
+    parallel,
+    ggplot2,
+    cowplot,
+    reshape2
 Suggests:
     capushe,
-    methods,
     roxygen2
 URL: http://git.auder.net/?p=valse.git
 License: MIT + file LICENSE
diff --git a/pkg/R/EMGLLF.R b/pkg/R/EMGLLF.R
index 93012fb..dada0ef 100644
--- a/pkg/R/EMGLLF.R
+++ b/pkg/R/EMGLLF.R
@@ -16,6 +16,7 @@
 #' @param X matrix of covariates (of size n*p)
 #' @param Y matrix of responses (of size n*m)
 #' @param eps real, threshold to say the EM algorithm converges, by default = 1e-4
+#' @param fast boolean to enable or not the C function call
 #'
 #' @return A list (corresponding to the model collection) defined by (phi,rho,pi,LLF,S,affec):
 #'   phi : regression mean for each cluster
@@ -37,14 +38,8 @@ EMGLLF <- function(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda,
   }
 
   # Function in C
-  n <- nrow(X)  #nombre d'echantillons
-  p <- ncol(X)  #nombre de covariables
-  m <- ncol(Y)  #taille de Y (multivarie)
-  k <- length(piInit)  #nombre de composantes dans le melange
   .Call("EMGLLF", phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda,
-    X, Y, eps, phi = double(p * m * k), rho = double(m * m * k), pi = double(k),
-    llh = double(1), S = double(p * m * k), affec = integer(n), n, p, m, k,
-    PACKAGE = "valse")
+    X, Y, eps, PACKAGE = "valse")
 }
 
 # R version - slow but easy to read
diff --git a/pkg/R/EMGrank.R b/pkg/R/EMGrank.R
index 2dc6c37..fa66b3d 100644
--- a/pkg/R/EMGrank.R
+++ b/pkg/R/EMGrank.R
@@ -13,13 +13,14 @@
 #' @param Y matrix of responses (of size n*m)
 #' @param eps real, threshold to say the EM algorithm converges, by default = 1e-4
 #' @param rank vector of possible ranks
+#' @param fast boolean to enable or not the C function call
 #'
 #' @return A list (corresponding to the model collection) defined by (phi,LLF):
 #'   phi : regression mean for each cluster
 #'   LLF : log likelihood with respect to the training set
 #'
 #' @export
-EMGrank <- function(Pi, Rho, mini, maxi, X, Y, eps, rank, fast = TRUE)
+EMGrank <- function(Pi, Rho, mini, maxi, X, Y, eps, rank, fast)
 {
   if (!fast)
   {
@@ -28,12 +29,7 @@ EMGrank <- function(Pi, Rho, mini, maxi, X, Y, eps, rank, fast = TRUE)
   }
 
   # Function in C
-  n <- nrow(X)  #nombre d'echantillons
-  p <- ncol(X)  #nombre de covariables
-  m <- ncol(Y)  #taille de Y (multivarie)
-  k <- length(Pi)  #nombre de composantes dans le melange
-  .Call("EMGrank", Pi, Rho, mini, maxi, X, Y, eps, as.integer(rank), phi = double(p * m * k), 
-    LLF = double(1), n, p, m, k, PACKAGE = "valse")
+  .Call("EMGrank", Pi, Rho, mini, maxi, X, Y, eps, as.integer(rank), PACKAGE = "valse")
 }
 
 # helper to always have matrices as arg (TODO: put this elsewhere? improve?)  -->
diff --git a/pkg/R/computeGridLambda.R b/pkg/R/computeGridLambda.R
index f087ba7..3dae84c 100644
--- a/pkg/R/computeGridLambda.R
+++ b/pkg/R/computeGridLambda.R
@@ -12,6 +12,7 @@
 #' @param mini minimum number of iterations in EM algorithm
 #' @param maxi maximum number of iterations in EM algorithm
 #' @param eps threshold to stop EM algorithm
+#' @param fast boolean to enable or not the C function call
 #'
 #' @return the grid of regularization parameters
 #'
diff --git a/pkg/R/generateXY.R b/pkg/R/generateXY.R
index f13598a..d2e00ef 100644
--- a/pkg/R/generateXY.R
+++ b/pkg/R/generateXY.R
@@ -3,16 +3,16 @@
 #' Generate a sample of (X,Y) of size n
 #'
 #' @param n sample size
-#' @param π proportion for each cluster
+#' @param p proportion for each cluster
 #' @param meanX matrix of group means for covariates (of size p)
 #' @param covX covariance for covariates (of size p*p)
-#' @param β regression matrix, of size p*m*k
+#' @param beta regression matrix, of size p*m*k
 #' @param covY covariance for the response vector (of size m*m*K)
 #'
 #' @return list with X and Y
 #'
 #' @export
-generateXY <- function(n, π, meanX, β, covX, covY)
+generateXY <- function(n, p, meanX, beta, covX, covY)
 {
   p <- dim(covX)[1]
   m <- dim(covY)[1]
@@ -22,7 +22,7 @@ generateXY <- function(n, π, meanX, β, covX, covY)
   Y <- matrix(nrow = 0, ncol = m)
 
   # random generation of the size of each population in X~Y (unordered)
-  sizePop <- rmultinom(1, n, π)
+  sizePop <- stats::rmultinom(1, n, p)
   class <- c() #map i in 1:n --> index of class in 1:k
 
   for (i in 1:k)
@@ -31,7 +31,7 @@ generateXY <- function(n, π, meanX, β, covX, covY)
     newBlockX <- MASS::mvrnorm(sizePop[i], meanX, covX)
     X <- rbind(X, newBlockX)
     Y <- rbind(Y, t(apply(newBlockX, 1, function(row) MASS::mvrnorm(1, row %*%
-      β[, , i], covY[, , i]))))
+      beta[, , i], covY[, , i]))))
   }
 
   shuffle <- sample(n)
diff --git a/pkg/R/initSmallEM.R b/pkg/R/initSmallEM.R
index fccd51d..487a4e1 100644
--- a/pkg/R/initSmallEM.R
+++ b/pkg/R/initSmallEM.R
@@ -3,10 +3,10 @@
 #' @param k number of components
 #' @param X matrix of covariates (of size n*p)
 #' @param Y matrix of responses (of size n*m)
+#' @param fast boolean to enable or not the C function call
 #'
 #' @return a list with phiInit, rhoInit, piInit, gamInit
 #'
-#' @importFrom methods new
 #' @importFrom stats cutree dist hclust runif
 #' @export
 initSmallEM <- function(k, X, Y, fast)
diff --git a/pkg/R/main.R b/pkg/R/main.R
index 85a41b7..d750fec 100644
--- a/pkg/R/main.R
+++ b/pkg/R/main.R
@@ -21,6 +21,7 @@
 #' @param size_coll_mod (Maximum) size of a collection of models
 #' @param fast TRUE to use compiled C code, FALSE for R code only
 #' @param verbose TRUE to show some execution traces
+#' @param plot TRUE to plot the selected models after run
 #'
 #' @return a list with estimators of parameters
 #'
diff --git a/pkg/R/plot_valse.R b/pkg/R/plot_valse.R
index 3160067..73188d2 100644
--- a/pkg/R/plot_valse.R
+++ b/pkg/R/plot_valse.R
@@ -6,23 +6,24 @@
 #' @param Y matrix of responses (of size n*m)
 #' @param model the model constructed by valse procedure
 #' @param n sample size
-#' @return several plots
+#' @param comp TRUE to enable pairwise clusters comparison
+#' @param k1 index of the first cluster to be compared
+#' @param k2 index of the second cluster to be compared
+#'
+#' @importFrom ggplot2 ggplot aes ggtitle geom_tile geom_line geom_point scale_fill_gradient2 geom_boxplot theme
+#' @importFrom cowplot background_grid
+#' @importFrom reshape2 melt
 #'
 #' @export
 plot_valse <- function(X, Y, model, n, comp = FALSE, k1 = NA, k2 = NA)
 {
-  require("gridExtra")
-  require("ggplot2")
-  require("reshape2")
-  require("cowplot")
-
   K <- length(model$pi)
   ## regression matrices
   gReg <- list()
   for (r in 1:K)
   {
     Melt <- melt(t((model$phi[, , r])))
-    gReg[[r]] <- ggplot(data = Melt, aes(x = Var1, y = Var2, fill = value)) +
+    gReg[[r]] <- ggplot(data = Melt, aes(x = "Var1", y = "Var2", fill = "value")) +
       geom_tile() + scale_fill_gradient2(low = "blue", high = "red", mid = "white",
       midpoint = 0, space = "Lab") + ggtitle(paste("Regression matrices in cluster", r))
   }
@@ -31,10 +32,10 @@ plot_valse <- function(X, Y, model, n, comp = FALSE, k1 = NA, k2 = NA)
   ## Differences between two clusters
   if (comp)
   {
-    if (is.na(k1) || is.na(k))
+    if (is.na(k1) || is.na(k2))
       print("k1 and k2 must be integers, representing the clusters you want to compare")
     Melt <- melt(t(model$phi[, , k1] - model$phi[, , k2]))
-    gDiff <- ggplot(data = Melt, aes(x = Var1, y = Var2, fill = value))
+    gDiff <- ggplot(data = Melt, aes(x = "Var1", y = "Var2", fill = "value"))
       + geom_tile()
       + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
         space = "Lab")
@@ -48,7 +49,7 @@ plot_valse <- function(X, Y, model, n, comp = FALSE, k1 = NA, k2 = NA)
   for (r in 1:K)
     matCov[, r] <- diag(model$rho[, , r])
   MeltCov <- melt(matCov)
-  gCov <- ggplot(data = MeltCov, aes(x = Var1, y = Var2, fill = value)) + geom_tile()
+  gCov <- ggplot(data = MeltCov, aes(x = "Var1", y = "Var2", fill = "value")) + geom_tile()
     + scale_fill_gradient2(low = "blue", high = "red", mid = "white", midpoint = 0,
       space = "Lab")
     + ggtitle("Covariance matrices")
@@ -59,7 +60,7 @@ plot_valse <- function(X, Y, model, n, comp = FALSE, k1 = NA, k2 = NA)
   for (i in 1:n)
     gam2[i, ] <- c(model$proba[i, model$affec[i]], model$affec[i])
 
-  bp <- ggplot(data.frame(gam2), aes(x = X2, y = X1, color = X2, group = X2))
+  bp <- ggplot(data.frame(gam2), aes(x = "X2", y = "X1", color = "X2", group = "X2"))
     + geom_boxplot()
     + theme(legend.position = "none")
     + background_grid(major = "xy", minor = "none")
@@ -80,7 +81,7 @@ plot_valse <- function(X, Y, model, n, comp = FALSE, k1 = NA, k2 = NA)
   }
   data <- data.frame(mean = as.vector(meanPerClass),
     cluster = as.character(rep(1:K, each = dim(XY)[2])), time = rep(1:dim(XY)[2], K))
-  g <- ggplot(data, aes(x = time, y = mean, group = cluster, color = cluster))
-  print(g + geom_line(aes(linetype = cluster, color = cluster))
-    + geom_point(aes(color = cluster)) + ggtitle("Mean per cluster"))
+  g <- ggplot(data, aes(x = "time", y = "mean", group = "cluster", color = "cluster"))
+  print(g + geom_line(aes(linetype = "cluster", color = "cluster"))
+    + geom_point(aes(color = "cluster")) + ggtitle("Mean per cluster"))
 }
diff --git a/pkg/R/selectVariables.R b/pkg/R/selectVariables.R
index 0c18c67..e08a941 100644
--- a/pkg/R/selectVariables.R
+++ b/pkg/R/selectVariables.R
@@ -15,6 +15,7 @@
 #' @param thresh real, threshold to say a variable is relevant, by default = 1e-8
 #' @param eps   threshold to say that EM algorithm has converged
 #' @param ncores Number or cores for parallel execution (1 to disable)
+#' @param fast boolean to enable or not the C function call
 #'
 #' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
 #'
diff --git a/pkg/data/data.RData b/pkg/data/data.RData
deleted file mode 100644
index a9f09e143adfa04f595a40b993efa688ebd05a4b..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

literal 1010
zcmV<O0}cEiiwFP!0000016`77P}Bt&#{atu>p&WZl>sV;MkEktY=rRsmk}pa$Ymf|
zh%+!j5MfYaWQj0NjSw<W#7KlV8WM{`0pF!YkSkzVt}S3$Smbiq1BGQdTC-1lc;4rk
zc|Se#d%TYL+G_f05(GgdXf!H8rKzGCRdpzY8lmyheO15LRlyd-i{9N%Pn7s<BPHir
zem067C<~@1^<ag?u=m+|z$J>Z8tauaP}k|=7GfR?3xiC$wy8cy^2&Ku+%x#Sd9>t$
zLmDm^dp4WeYeFCEnoB`wICgw3@@~y4gPhV+@xcK*P%!AO`$5DRkTD)oXS7Ic^{*??
zW@d4z1<kq#IHzGbCRwVCN{8;*VXGFU9OwLO*iN3=Ft>MdXuj-ykhk3R&r1y<X;)(S
zSN+Se);sX?v^X)2eCzM?DE}Aa2O1Phg}q!#gS%{0ZbK6NQB5Kt8-%5Q2@<^9peO2!
zh6v+}IObGktlhW=$M^k_mdn$?nY!Z|J`#7FNFDD@Pp-u==N|UL4~6*8;e;ORI6aW;
zw~I^aECTsi!A(c|HB``J?r)^;hqdmqub6&q_~MQFjF3~R-i%A4wzus_y45W`UtudO
zd79nLuxNvtgNf`W?QvK+B6o{fKaPr&Z;lyfKgX5T56KgIf<O@Tyf0Xw11qsEvSerO
zHc+&%h-j7V`i~_+ykx4b(&l!a?EiTl#+HauVPU|>Frc`xn~9sSvAlM@y(*Vfi)3U6
z6_Z?=CI9l)hCa+Y{C)q>;4LnlH&A!>UOY(J`%@WB*Kw+7R_I|=538Xe^IaxaV6LQE
z${Gm5C2JFkVyl*<7&)30u6P0er*eaKb_bUdxM{YW--RQw)~7G!8eyO2PzAB0kEF)t
z?XHy_!ZphSLN<FAq&ssSewxlgv7s5$Cbb8KlAU<0{!~)UHaLjEv4o|7Xs0Hz7RqXl
z@g3~}r&+6t6xUi@zY%TWb?#kqSLQqFItEFotc*6R{4p8C#Wq6$Z+d`e5cXEN{)y7_
zTCR682T>wX1fD4Q6{c8^!k<;Mak*tgWMAQeqci5;=}*!@7W0`L#=>CsH@lls&U?r!
zc@iF6c@hNYlSY*_w~^;y75Te$4sIR|=P-7f!9+gWnOy2Zp&>Z7CWgV{3%AEc$_DH_
zI>bpVy9f&=2Rmjjlt7nvW^AOd048cSvZ`JygnrlCayPGi$Zr}>`8kaSB7KiJ-K~$X
zKP>8Li?SOh8ynTuGYsIVqt0dNolu+}p1ZeL@fJ*RK52ejSBxS*_1**vLzoeFJ*W;i
g2h$j?5gPyHEAZ5<ZKI&S8U?ZWFExW2g!}^l0QK<asQ>@~

diff --git a/pkg/data/data2.RData b/pkg/data/data2.RData
deleted file mode 100644
index 80003e3c090402d85e308401bb23159ebe1d53ca..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

literal 18385
zcmV(vK<d9AiwFP!000001MR#AP*p**E=tZIAOfNYh$7j9hy;5B0xF6GML`T8ASy`|
zL=XfeDS{#(K}E?(Qb2+r^d{$=bIv(uc${<Yd3DcU_kXwEdv#ycyY+X~+S7aWnr~)S
zubJ*%y=pYi-8eyagN}rRgp7oooQ#Bwe21kV+xa0Sp&+6Cw?F6fpX%?3ckl2!LNcbE
zVg!oZ`d;fjG$D|>9w!<qlw$0@3dI*Pxj0JFy_n*D5BmA#6HaMP!EkCxMI{?O)`TP&
zPcwv|4YN=|hR11WsrLU&mhcKEd<6Wn1KvS@=%di;_XZFb*X<a6ivkKny;ncg`=iU)
z``e~J>7o5D=RJ-5M3~85y5TpT4>flw+^-(2AySBs3Udj4#=a}%qfT$rVfI8z-ra~%
zB1xchqLg+qfo#aw;oL|PtlrVP(vazZfxnE>z8k!Q1sa;lxS#eg*2mVMqI4QZjXz&$
z=U5<+SF6AIny?qAF1q<2=_SRMapSSLsP{Nd^Vu_(`zA~~Uv8{9l?Y3(FE5@^|A`~{
zL(C#dNjMO5<Z|hkheXPltxuXhS71(qw|0rk1Zz&FZJqsd5mJrQ5>t(z;!yk5<;1I0
zutCP|XY;iM#;nxnGzG@6+1fjqucrg1pE)!fN`JD`?%oNV%hWhG)M(%sVFdj=jqw9w
z!7ywawBTE2kALO!Xt#}pVa`?XTlryEEWcu=okqul?e3d{GULy1{9yZ@yciW|Y4vqa
zmKem*^iulLv)<UQo@0D_ARp#NXV+x){NV3zVJ6=r95A96-JC6^ip2)^jSd^g!7%Ua
zQk3)t^xgMRG!9sYS@$W&qKSB%ZS$&pb+--Xdm=SL8Q9?O;j~BbZ0<Oxe{T03_5uQl
z!|zum`oXv&k`iuuqZ|5pc~~t}t8wK{nE0j%4fMsonK>V^2m^v&+WQ)ka82~-)A`af
z(D?nb*GUz62xqo6C-*YM^j(F{Jyl)U+KaLd*X3ZVBQof(Jr|lK|LA1VC&6vai8fs|
zQtT6nW%E+!z_EY}F3wtZVC(yM@seFH^oyk&u=j1n>2bkJw!RWrC;US?EJYYLfAS6$
z*@Z!>$)Q_n3kEn}@g*R3ngW}&9A}`40*1m;64f=%!CW5yletb(Y_Q%M3DkRzjeEFH
zf2JD2!7JR~u6`DT7QPSe-&Q7ZrY}cxZTT)Vi(J-QKV5`#N^Cq$1ztoFyw_lw!GX4k
zKW-ZaghM{*_;b&`0%*<p70BAX7w1H}C<1i{V3c0}ZR%Gq?7!$H+ZPlH!y>NtW}D1m
zm0ersEqe<t&srxG+>6C^CgIOvRvNI;u3Jn>Y6nGq64c7Fe_>kH@A2NvT3n1J(Ykos
z3-H*Go5~y&wk%x+)`MqpINpL~m*YKHYdm6+?P!aG(=OxnSsFOUSoZZ#`XShOF#q}&
z-5F?lzCSy!<1O@4X>DAdUWe8WPhp*03LHDT_40gGDGW3kIlId}g}Jrm*HdP(P_rlF
z!F`+C*vGN?_V9;aSaFk{g>sh$Haxybmc(F-bJ6jF)zKoj_WZHHG(j7N&gxt4K23!^
z)*VEPgg_Yckf{1Y9Rf2ql=sO|X=24Bt%EVc64bHF=kecrid*t2Pt(Ki!`#tm;a0m{
z*prof=bXnkBB{f1+0$BHm@iLrj`CI;u4r5TD(g{zNwX7%Q1=D<!<ZB{;-6v9v%YwN
zOY7Kta{tQ2Rs-~%y|0{)9{4MOb?#yD6&Q;wDPHq`4y)lwc=<pM=Eq-Y+#HvNf+kf9
zY6(T?R@6PdsGp9@wr0`s8XVX`(#D&#o<SgCkb8MS?=JKd^c*3SFW{_T+^!9y6<jvB
zNdIO^2I?Eiz0O8D!yt~=hW;_YF}||vipLl5$F3RCpleTXfiKOFN%a%d4b~P8I@Lpv
zh~u61+%!n$JYL!%`yBiv=-azSMj`!4g~slAYMlT4EC6;TA~90<o=o;4wpOV|Er(vm
zxwK4K*;y}G(A=|lURx4J9lM3tCv~7^^>$1Eixgx#*#xN`XM{DKzLT;im!Vf~{Ro#@
z437LQ=2z0b0bR2BF$GEGIGJ!slYW&JN5omfnmuQsC8+bbQ_?Zqc;ULNKU4x8MA7v#
z-s(7S;2dMw+XaKPo*g##f523_!nOE2{y4BO_04rI3Tnyihc-T0Le||6-DeMU;Exra
z6I*){phd^;o);|x7H7z5^raR+bd2FXGtV!udWurS!g2{4Z)I`$7q~!{74d4Oof=NA
zFj~~wT4B4VyQJf<Dd<%@rC_H17~2SP>v6ko!Fu$Mf;v-fSc_*FeaawBBwg$!2<dQQ
zSA{}7EA4%#vZL~-REUS=uacjJl@G&A<mEHFr0?L2*}Gj~J{h=VTE>62rU^RSS5ChT
zb|sRZ5xC^e_ZgcmD}TPOk%nV~+_(0a?7<c<;~=ZNFW92w{QMB}Md-f4(iOBhgxz!*
za`Ms)Fd2Lyt(S8M7t-vM4;gO3HifOI{UKWLoLhLeT-pLtVaJacH6Dkx?NmdCxoylg
z3nVht9)baliFdwb`M4yR@J5OM4}p~Kp58@`WJq@NJYoO(1ddq0VBDXmg;5Dt@9X3U
zWB7j8W*W=01X5pP7sJV8*mU2c-^aWUGYnooo2_+%D)RV>=Qn$>hw^lJxONI)R<+4$
z+a>7iScuwi-s%55No7RN7PQ5R<k7fPV8w}z+}xEH_|+U;1d=PDI5F<*X7f1C{Cs}o
zSHd4$u+Mp4bu|=cC<E?)+ux6?L5`&jgKw}&W#Wad?Q2-Bjq!L{JO}CaWgjXu9B`3j
z=yCHU3M^`5J>Z{m0ctoK!#-=O!FWi(Oc{e5PG1kW%4%DN^Wg?UxfV${70~-fUG@je
z-@<!GM|hC<jHYFVd=h4_oha<w?F(UI#dQ^dx1nhM)1$iw8=yhub$rS808BZFOQq9k
z<Kn8J)t7@+Fe`V8<6y!?ocZOmORtLuacc9y8M1Q(l6ifZL7`k&c_5IKXVwf0@%`Mg
zAO;J)(k?{aZfF|Sqt>i{i^F~@&$5I?U|7K`g8nog4mNlFR3J0JMe&wHMVu$Fqctqp
z<%l<|UR=#OJspA*$33o7ktjpq!-EeE2E}pPSn0v75_T928n)FG*aLH)q>hOOtYItr
zu#&-YD$ch*j+Lg##MzF!JU+cXP#~@vV!cQQB~OIo6gXONPMRf$YK9sXZ%}KD1yw_O
zPIu5piX<GjTs*fdw~3SN^CRzvSFtdN?ZVO01Xx|J8$2D8iX*-y&rGOvaLYxZgE&ir
z!`43nuGcF;<7c5m+cv+jmDA!{%ljhi@ewVl6imQzb@IB8k2j#RwwAD2$&I-g3H!w}
z6L7F_UuPkO6OmG}x`=D<O^m0PJ!Cm+h4X#eF_y{X(4ofbhnjZq^N-=feKt1<B$2P?
z<ii*VBo|0#gBKrR=hR&8La7gAIi^uj7)Zg))e23X?;l{)`_|d_t<x~PJ|?7PM1~VH
zXI=(by@66C!{CF91K4|t{n68K5(uiTpLuax7pBT`nN3OzAwNM-%wp9I+gxd8>{Yfg
zb3{St)TJc&mMB8`MMVv4hR!idwz3jQQq-kQVi0GyFL#6)mEiajN?X^;EnFpC7ae5X
zfT`g#BX{P;p~3jqXw8-$F8r=nepfGvi#e(TIV7tDiU3mo!6scCHr_A9lqL@I*>zdF
zM*cuul=#*aZdPcCQE-qbz7E4`95?GZdazTn|BlZ#J4Qd+Jmy+y05%7-?f6;SaA|bc
zne6Y~FkI2znX6fVGc>>SJ>AaXNZf0SJZ4##J7YoQqge*x-L>2$pIn$fyTmR*@PeKj
z?#nW>uV918?qtP$6pkh8gfYBJf$8*oiO%*Om}5U`T5GM0MN|^Hsd+;%SWa#zLqd+-
z)1^oM@QPuZ@xU8xOI4U@`dTw_?IDg_(B@hU7J??BM~-PCAvjrM?CtzV3|8%&+MA~6
zq1Mrz>S&WV3}2VA{m{@&pzA(rWUg9+`6ZjA&U*0#GEbGygjZS6nz^Unq?sRjnce%6
z$#&u7ZL7NT?b$HE>=`y*-U{gj#5`&3PdKgDO)6+fg-s>RE9)zixV+DI;f1>-E-jvY
z!zU__4L)C`DBV9{ky=Olr1c1_z0JQo`s*n4$joW-O=QE*mx@|n9-bhQFh3)n|9Jvu
zk!fnwH3b@1@7!j|JdO)ri+y&HRl(wV|6c#PqcHQnE9F+YF6L6zOk24(!eFd#7RNRp
z3{%T#{W)|BMsz#kzE3_SP#F39+NOFyW#?ozOQ9;Ho`1pcLt6y?Ud*yOyzeWN%GmO<
zR#w3zv!i3M7!^#_{|KQupNJc+y`guX-iDC{KUN9_UKpkjV{eOn39CM&cQefFaqv}L
zjd!0i&LnG*YrVPzlNw_#=XG`w$i+-2o#;}DWI^OV1(^zAL8SA3|NVZ*eYP|-yLJd8
zE$o(3e}9Djrl(gQe6NMRJF8~b;(1_I%|GY&Yi$^aYH)g8QjSyf#cTJYcb<djTfw!-
zMfhanCsVD}7R>lk4hEly#ZQLBs+4YVoUD&H9&vx2K&g1?)3(?$L?4@27YaCpL#{Gy
zUdxxD>M+$vuEasCWLnX_oZ$w&`$J>+lxDFmLS*xX%OZ?P?qlC4p$dt^K0cp3F5^;Z
zR%V3kH(a9ZAg$I?0^;j#*Rhf|-01oArlR~ZWRUC~wih2G(y*&>*-+-;bj;ee)k!Cq
zprw*9s6GcvKaC$|?K=UbwY@|)b61=qEI*iHD}xbnz7lumAOh)4a>Ih`K$vLva#XdB
zfx!`T_c!jFFhPI$y3KQQ4E`izety#kW^DF9XS7nr*^vk0`v*i}@uB@ICL=3c+`jXn
z;l4GrRSpQ66$|4cQ{ATv4|n{46H6Qo{+95Elr#I%U?J4$gl}H3XCP3V@aQ%ELBL-p
z^YlVV#Gqk;`L3NKEmWZA&yVZRao~Pk=p8ph0_EEHNSkm64)AwRHeY)Ujg!9>KC-dH
zIJH8F_Tg_t%CCyoLY1{}BiJ-Q-|8~<A2c`_tI7)QwAc1d>Y8I#W3ny}bv&+cT58?7
zlminc?|(h+JBADNPPaDs?qkz{+-tLYj?k5D1-|hs&?*!gDAe^B`#et_VRUiBp55x{
zcKO#}CfwO_UrZ&Wlq<2nGbzCCqH~TOk!{dBPrm!FnLdmc$#I^~vx1oSGYxeoK42Q_
z(@*Sox?qHl!YEVuHl(z79Cx~+0X@z2y36;tfp~D2c;ihT*lH~%4?NWbU(}8<(ecYd
zd(X=gPmUGh=<9g3sK=(TC7{pv<k>3J7#K*5^*caM^^k(Z;fL6vU`<QI_zOBUxDQ8R
z1Fn#KY_I-m4E=?F6}Lm?p~i*o(2Fd2oY1taemE!qtp#i^i~FNt8h+hP`bdps9lN$D
z-sfUPNa=msNNOBudstX1GXyg}QD^!C-V;gJgv0iozl>}21;R8V?{TtFw~}$B8de`Y
zeD9)n3~Fi3wvQzmU{l$bR#8(kC|^!|PHa(y;=1oY_x6<GVqik&ZM+3N8NDwrcprty
zH`SUj(FbcaK~FM5MX_tG#p;lLAWZW74Zl`l1amxJ?qnKWgrer%EtE@z&?7hdy+&on
zzF()BoC|ypYYGELS~%iy^}&==pwSc#FFH7SDF)yKugdig`h{5e{cF8*3J0$6x!oSv
zYmIZSg(m2fN};bzEUI(iJx)^>=t&nA!}ur}*R2Q@>^Y#eQ5jHyQ<dY7xy2BdS*zQ<
zUw*~@Nh2wicfq*fk!B-XB8b!ERzrT-9MCwikM+UIQ<ym*&rdO9fO9iJ7~Ja*HRQeT
z&$8Ud(bma(n)6NA^foA~!m<N<{6G0$|MLZM&*!w4==)-KfELn8T*Z_W0Y>BAHf)(K
zG`PW_34^x;EAY@xT)6+^w#)moM9P<XHi2Zfq0yCbt+vk;$M!QniTRTSlOY28?dA1h
zJ(B+I*!Mh~dAWVWRq+C1>vY;sl{wBX$)#vV>*GMl=|{$=3~<Qp+%6SaKj?ltJP=}i
z9fth-4HEm}p<|$@iCtkCe+64#J~F}q#LLxUYL3a6&hp00(jpS(HnsX9e~&@wFna^T
z-DPO9Rd9XPzl<XeapYn`-Pl0k$}JSc0}UkQk4NOM<I<xK$G^oKCy)#${q}PHjbnw+
zGTX}+Az8QL>#1CE7+3ifa`a&hbQ!3}HrzY{#QhB2Eahdm!Ybusl3#%Rr}+=)c2nWn
zO)Fcuk{y3Bkn_y}1__+M)Ny4jwF_5OKc*j{s(}_sPfOCzMOadl!pb)ziRF*(ObXIu
z5=r>qEc7u6V`usFp9%UpoMxs;Q2Fx>=i+@oXIPwo5sJ6<GY;#xd|#$F>3|iqFe!?E
zJD~y11!ouSh*=o5H%;C(M-p0U6eLTvIk2Gru<xC!U~JuT4t=&q3KrDf7rm2S#<Il=
zKW<DP#u2*x`WjRX1hN<VA6U{fVN7>d?U$7SY>@RVaw78MP@rA-c5(^!DQ1{Qc+|j1
zl;l<iUm^bO9-6W*a>Fr~`#1b!`!J*|SSpX~59C5L$#03r@H<K{G)pZ4Q{R|M<+@*n
zev)h?CY{5Ul`Cs?Rst|&qP=8fl@H^Rt#k%_WSBd($R@n#4#mu#e4fNnSgm%7tRmCG
zF+qp@?5~q|;vB!1k%#|4?|AGHX6t7-L#$p}F1v&8eb(#Khs<CyD`3N8&t+Jj6AP()
zO^WkAu||@&cILNBERTb$JCSV6>%f_IKAe2$wC9mCD{9zYN#&w6zzqUv=jvuOPH(hs
zu{G2|pL|E-`;HYH_!Ppc(H4&jPro0J^tg>Rk1VX7KbM06{R;JwiE(J;i+rEoWruzI
zKVvvjL~&Tx{wY51!kV(Xw|;z$$Myr|S;K?-G5vnT{Ft@@3^6q|K6M|1*jDE7+BSVG
z^41Vx3?adiOBV4Ar<HJ&-{cTkNhXY)u$cSM%Yx<iZmy`EI01OCDBvO=GxnCAqb8ca
z!Kthk7mqy}7<{9nchiO$+6RxyS*eS{+TmaRCgY8;!pncq^V0-OUfa&$|4j`eGR)OQ
z`6jqrUUPXw?*h&!YWpuI1VW3dRnsB=n=reO#>s8<8m5j~9OHk(0VBmX6RY^5U`o6+
zRG?`RHtv18c{4X23t~J;=cl=FWZKW`p7|z@R4cx?!@-W5e)jJke>n#2u44-FOC2!e
zzVx|#C=oYx7K#*p3POhF8TE+blAU;n_9_`k8w?M-Q2bUkfibPa$F6fJU^6+j$QR~x
zOz*h#uB@I876b|_%#1=IrM~&qCmI&$A-<B6ODDsb6REzeW(7F-K)=$5CjojGV>S%W
zD?qCw5BFCyVFIaeR-@CNSJ?ON#IumA(zq#=YyF4i0k+<@l9;hEB9J&9*{Y2>gPR-i
z9&|zS*p$n*Aar&c=ga!XNN;vx+y0m)Qj&YHY!N_N#cv1gRXGuFv3;k#=V`~h8KK!T
zN9^~dA*>Ph7HZhF4+@W)ujxpK;`U@Ar<b|~E*=bbPTH~4m0A~WC$Gh0<u_A>g8q{*
zRm&x7A8`)bA{fqX?wN$9iUPgCuKU<CYV#mS=LIev{eFf=;u{o7%HQx&qJ=qzf($B0
zN+Ow4bmz&d^*FM~MXJb43X6Vh2R6>0gw}yEZ^9q0op>y~WrP1S&aOQ3lDkib^D2AD
z4W|jv!ug=m<nlZ;J-mHF_MH~ABvnkkFCE1pKN9Qin>V4W(Cwice<jR)4{Hl}6bmyg
zrBST@0Z_yBmz=r%5_VjbmU%iE2X&iF?R{m^u+SLd8|f1Qv-{0ODH9WL*|f_jhxY)C
zJm%H);k1BdtE=H#Qr~dY?dIR<zh5vvb>ofE_1!o)pR6WLAq<<vZ?}##a^mvCh@TH)
zbs^O!r%b8f1&pX#sb2n`4Rhz-Bp%i7g4Nz?)#%y3INx-ZAai^TMl!-|lH2HEwYb4B
zn>q-xXf`~Wdp_WVNlof$p*Ju^y{pKj>e!Bb<otV;Tm^`(?jd;x-a^Bc(mDOZBe2!G
z*N^SNAXb0fEPd8}85SZsljO(rv0Xb=_P`TPY!r99C~S5K8=~tezns{Kn-qME_lPnQ
zN!3tJj1QpAf9Z<w+c(f_?W4U=BLUH|g05dqy~4krCGw?CU&W!q9_em=DXhB^MYBJv
z0OoB=DSjTfhpmcDTb@teLxByWpJ@DD{Bv%!$$MHF->Q$=yV>Z%kpBKtZig0dAxGr>
z?e|<TQ6|JV)olsAKLt9<cwRvtYun_6`y?z+btN*eD&nB|)_mo_M;IuoFQWbS3fm60
zuXeHvVdvwli+p^JSmRdYc_^=R$L~m%s!244MaEtH*KS<JnUfi*Rz7N2j@(HxT-ms`
z{gk$;)e>fGE!`9!L_&YU1ztJMi#WmRRBp=i0GDZPXwoMSV+%)M{A*J~=yx&q(G+dL
z{9VY9DY-->**||T&{PW&EwAtz#V+Dsl40$!-gi(M>)ZP&<Rp$9TCp}c^b*@1j<TBa
z%i^>{KTn>E8#Ggg3{J_^LE+QbE&kUXI2+j~P&y<5-POD6UV}WAc=|`~=}dw~zvV-`
z(Xr5RigLro*BiEF$&)glr$Bq$)HBP+Dp2`Xe)QaXY68X5m-%1pv)E(adXjUz0hWC7
z<UdoDLVrz^)vU)RY#WjY$7wj@oJ|L>w0r{0T~)HVUJ?ug7fdykdGcUdTfpm~r9Y8m
z`D>48MJd*ERm8<I7{JP)|2NIg-@vV^t%%rr9;(Mz8&Y1m;gs1Q|J5;Vn7-qe_i4BV
z=H%I#HHV%NXyWW|nWjxaZfB(N4aGRv?nz>`vR!~hvA2R9g#9>Qy<6~L>r?EB56aJp
zB!PhuI_WUqzdQD8d)JFQRyaSuoV!MH4C<(ijtZO@!rb}Sq;Ir>U@^LuaLPg!R=-%$
zE=6SFIF(9aU%wYNaFShCevyQ;CkLZy!Y@J3)brruSurrDsdU%ya4arACJ~OQ2!XEL
z)}*}J*95YRXPgANW$a;!p%2X%#LklfBrH{PFuRJ=x#pjtujBB@r!0M3y}16Fb1NDa
zt`WRdt3P0s^a_z=^)qxHu*r=){tOq4eNT%g`a|zS4%f&iTUdMIePC?E7#6t1*6N>|
z;XnjWw8=skt|<(?W=PM1&GT!a?E1V=^1%J*qxW>se?{5On#T#}Is}>)E_}sadW(@W
zi8rCAW|8v5Vlr;>&k2m03}eHC*3(udmk1;o@`Q$cG#K4%Z8Gbig;Vv!mZGQD&?}I6
z=d+9kOwl)^l<^#_+$xxws@s`&%*-AFrVn@GszXJzG{<pN+xLd`iBmAU<ma)d2RO@i
zuIL-{j$MtBPArTTgC5!QE<=9WL@EjUN9Ef67<=e$amK|V#Oe@T9{;y6UnI!?oA)^+
zT)S&}ZQC6ymzb_)21H`t<M$8Km)=0#?Df}f8;782xBaIaHz}A>UpuIzaCgVgzpf)K
zXpSxGBUiW^%pi3(=uuUfG4|By9^#*C#U28sPLXFmd}moIzH2iF9m`a@!x!SPwKaO-
zxTqI&%df<}j%>#%X7%MjRwi7K)l6Mt-SNY9hlQm-sN>{>ZPTqrLs-32o-0=115M^n
zt;03wu;!rF;pYLVILVpJ&#Uqari$8h_n&+U?RsuMeMl>?|4TTtLzOJL|9QmdN4*T?
zyjzcD?t4S)-$aIQ!A3Y5s)~KR-*8Ha`JMd4I?O42z3g&%6jM}qjxitS!r2>RD_`~q
z!PxS19{V^gSeKp4_B8awzUEbZ<Jbo<@kO`RJ#RM-t$ggCcFu>yxdn*~L1WmS6i#C7
zSi|ACO&vpNXKWrc8hQcyVf~?4r}2h1ft(p7oA_5?-9bmG_3bovQrvnHw`jKGuXuO=
z<#fR2k`)TEsgLl7MojI;CI`;51Tft;a)zxK>kigO89VE>dRb^|1dN1d6ZaPCV_tk@
zlw`w4taaG3=2tw0y*(PGUP(6Csqkze^Dqti`z>1v(OiNW3io1Lt!bEx*=j%YqzmVd
zo&KTt$O>!f6i0^7+r!+1mZQ9fE%g4Pe$VU63maF74xIZZV03!grk89Q`f9kYM)r5&
z(8+Owl#27v{-&AUzf%p?{HNl2MHH~g?(px_>}{+s3{#zITf<fAY;Van5A020`$c{u
z4~NJoSZ<jSVP@YGvI|!du!v8^@yUH!Xe!*Jb6A)Tram*b4F}4?;0Z<ZeJ597p(yCL
z04F;P9J|6udPERc$GI8|m?$Av;mVocfr?NoWjN1%$r<}Km}d`*1>lIwr;P)YB{=rp
z;6SN@6gExW%U!m~!zRkPuiR<_Fx~3O!qC_84>@*n!v|(N1>?V`;YmmgcaDEc$#4Ci
z>GlczRtuG|k3_~(`Q62@gb7soGFPfUZxNX(`~quLpF?NFTEy$_yF`j3X%V%Qo>)6}
z{ARukAI@GI(dhIxg~b?mG1KWz0_h8(->P&CFqlOC@=N~)I?`QnIu-B>nk|-+i`@-j
z{*vOU$VfT@$>+#RKk7?}BznQOD}xLn5m^kK*hmPh>}`=`!c{OM+C8(shYVNNE)jqC
zDG>LQL`8d4ED%}Nf9pK9NFuN@s~?$Rvw-KbM#l4A-wDiImG(BzMTq1ZdlS62QwWrG
z4TE~iY{cE!!W=b1H*n)g>4yvwAtDuzq5GuoPWx-U_dYQFC6Jc2vuBVo6Y12yCMn*1
ziJJqT{lfwe5J-~>*bJ{w6S-bY?{%UUAuwHS8N93^fos1%KiMm&4+GCrrw+xRA(HH!
zzrU`vm%ui6G(BN>96J=l#qLE&VC{wV){(&&0`ra7zP_OYM4HpqPi&^8h}4$noqs|q
zOjDxEcddF{l`~`<I9Q3(*Fqk6DNe!Km(A2vOHmxN>gLN?&4Gn`*m7Rflt{-c`};x9
z!JX;U@JCKJiAb7u<T&F|GnhX2ZG|D;oJhiv#SwRk1_y758OPAaz_x2pzQy?uFvEY_
zR@qVx=GkZMzAh%>z?^^{+cXK0WGnx`L$5#r8RMRV@m0SG<f}GKyq6kaeyA$NS@jIe
zZoZ`Pe*TxR|E(Ch*2fUpU$x%3qs)p^eXPnf3`K<9dzP22q}E`p&?}xg_!5yMLsnwy
zFguY_C*_?5xd(xSR*lundTGae6}+`}Ho%6x)&WIbCD8Y>E=C~W7J-wgPhiz(H_irG
zTl!!5Kwu73e{pl~CnB|6lzdav0&cl|AbX2UIHW+bJs@?GK$@^D6soZZi%yTj8yyN@
zgTH?E)3<iQe)p{C@joxH)->!%o1#8};#eYs{;mj^xwol%Jm?gT$QbK{5%v-(Yzz{+
zLMot5<1(9{_!sD<3*{eM=7sT@sNallA~52OXms4%FCwd2VFAZE2iR_#lp4rLBGUbK
zHjkjxBXYj|9e(GI49p8!KRy=52@}fSp9|tEoI&Q~YqsG;8mqjb-+eoJxO7S2z!)VC
z@_5^*c&ihrmP!<gAH5~8zSG+pTYo}eKACf{`^`N9Gb2l|k$N0%d1_kH9w~$2de=dt
zTkg1_o4h)cagazxy|qA{T!5YO&Sb;Uc{p$9dc63I41xTG8qA$^BQjFfdpggbh82fP
z8cZr9xHb2q(nB+t$VBhjsXXHVYnRo&NWTw*`Ih(J`J*1f=31BV!N4`xGT9k)mI;xB
zKICuxa1oJ)T-}}j+s^%zlhn>VL4oxGKac8OS%6jg)+ym9Pl(hy*Pe&8M#I(;L-W^y
z1tMFee05z>A}%iZk+uqy0g>s@-?!v}1nPk^%4ctk5NJPYqg1#y%&X;pcqEt&^Cb+C
z_t=?;+@B_=uT>L?<b&E4&eAVnk@jwS*LW9k-y2uQSdEjomVd%*Id?yibl(XETe}Yg
zru3h=dD>*qml-yYEEETG8FLNP#XIhW_WbB3=woMWKBut|0sqLKPn@|)N1#1(rd#e1
zFJUjkfa^+6EzFXS*?vE-2Fp1ro40N1aW?I+rsB;F;_iFfA`)s(A?1RK_8zNW#NEN%
zA=3wF2^5XZ=^5r*uxh`z?78<6f#UX==&9hB7_RZ+OXWKP%+?=EKCpNQ7irwh==zUB
zy@;n_L1hb(nx7%klXDfutXOwnnj6O6$R<Kr^(UB#*%K)I@-z;b)b|l-m2s8Pa6^!N
z1s5*(6Xma&!YtP!6<w4wbgt5tu}RkxSv}ZAIWB(3B~BIFh2};gWl#uz#k2`5dU*8G
z$SdQtBZCfUECqqJmA>-ow=|qsTIAOYDS^$EG}-i%YOthIz++PQ3udRe7j9KPCXi=*
z<8BB(Ngz|b@7ulFMqqj@Xn%=w50PHaxzfoXhQR1@@ms@@leiwIT^JK1L!{FG9xu7?
zBh-&SrA~ED#3r`p=A$bTILmQdh2{A#7*#ueNa-*YfwXJ*x|ZiYTy4M5Z+=Y>`lzG2
zpXu)=uzi{eZKdUcuC9$4DGeKFYl~e~5S1aaK#;9gfG>1Esr;4RDoZ3MWOI=Ox8S@!
z+2gyvDhVtD`V9f%L;^eaD^YP-VZ!e7Nh!>?4#MKFn(jk|Hk`2V_7wj37B+o8-uz=M
zh)WBjDKXuF#9j7BJtf|}B`{<diOFX$z?2yWYr?(-!tQS>Mw;Tm1d{7#JR<X&U}65N
zvspzM&PF|}Nl82eGv(iz6rKBFTsqll<ESJ0@V=V3(nSJW!r>y84{HeI!98L*;<ChD
z8LtAk`Bbo9Vfl8*rQ-xfy_7_Mx7`F*?jfyc9Whu>3Lu(AO~5)!h`>!9Is!F)bb<I=
zb^=!y{k7{a9zgNNVA2-V&OG+`8?|^z3wlpvT)6YdAKM`>OZ?MIB75@>&-YizF>_o`
zUo_ztZlpZvUN;-tx!)QTFCQI*xs@?bgTkB89BFvpQ~M)MR4I2fB)lTh=iR5(rt^cv
z69xwzcI#o|q(f4U_W^7~49^=mhxPeeZA)IiaC_*<&nl)M0tFe(3ty2EB8B9Hrd?(@
zku_ppYf5Mo&L;46>tA*xQtI(ar8Nd%`pxn0SH>!dtdHs6w`NlAgf-)O%+At8ved(F
z@BdiAO3K%}cO}CKWMzhqyzlPAc2M{^Z#hbs=|0>_zDt+D@+MS5?1~Z$?BUN<A27tR
zEsY;bC0$UFDSso<_b#l?*l+enDd3QSqeaF$N$i<?x{$XeL8Q$$k_)Cjk4q&|_XO-b
ziDX-Ug+A_bge5Q5yJ0Qwi6s2Cu9@~f3CzN)T6|1-I2ZOT(xmDOfijPaD}ebTE__V2
zjnAAXkhgGYBouDI=GTF)KM6_LcU!27TZN0Tr-Im&?nWfiNqX5NuQw4%bamTW&)$Xk
zxo)A%J(;kgZu!?cg_*#qTdbve^%%|^j=MZU%Z^JCyUuRheusk(_I`QzcOQW)H8w+5
zs1oK31HKw=c;if!qAB683RZU9w)O7ehpo^%G>Kjj1iHYm7U_<7=(~R*<ipXoL>Bdz
z@w+cI5$WY7wO4jGz$W+g9?QEXM1~TZ_(X9(B1K`_+an})L>9@DyDpPlg_VHIPq>V>
zU{>iCn_kc~E*|I4HAq<?lAp4p|9XyzKygP^*f{<y&h}m!&|6T4m0DIl6RrdzO~8~&
z-`igV&WKlbG!GbXT+fMose~0aO-gf|X8mC$IaTs%k3Z&D(GkrSZHT)P<;dpi_Yj$a
zewe?DmB;m>IBRA8GuU%gES$%{k3iu}eLZOPAc6MV8JiP9%>;^hhL9g$dSLbVfyqea
zPF!z)*_6Gz61G1T#@Bf$!qPPclFS311eU8LS>fl&aJg4w?;n$gkig^AVkzx}F)wJp
zUoBg}Y*G&Ow?TC<{H@9?-`<<ZZtOfe^^$`~-%2E1<Xt5)rW~`^wiO|eXa;Ht22>Gt
zZ{Cr*M{7VJDUf}Y^wf$#vhZwAeFO=CIjSYV!+ef#P~>yC%XM#D5<2#jtWuLe?G@E1
zclb5V@Rb<Ui5B3ZvJC$`*Imq$dO*%Y(?X<i5DnH+qQGWZuG8-weDPz#*}M?-P9ptT
zhr;d0;;`KKXy}j7cOuQZ>Z^H%yK$g|m*vKzV?+kJj*0xCE}WTWzHb%sg1~%Sv2}ue
z2FK*Qsw@61684CzMUI@-B#=dYd6HnxKqRLFgO|mLL~>>W-q(FRxbdv*SbR+wfsXm&
z*K?1!VMD>vsBtL=$Aj9=U&sz7FxQYMFp-rLXi|U4-0Pbol4Y%rj3)IES#&>f`15n&
zs*rN48rx-<bST(%ljR{WRo-6TdXPgr@Lol$!h0SY3S!hmU+NIa$GJ3?@5n;uf<Niu
zbvE2IwES6oFpxmSS|99XyGCG2_`7bHq7IWseqZ1Zj3rR#n|;0SaR9om`GLW>C@eAc
zjhLbVVOQU9QFJ;NxOtnINM<?V&>QKu><<Eoq^!qdYPb7vtvp!doc=yots8U>!6^cD
zPRt{4pM(|K4eoU7H6j)Lr3-Dc{X6rNBeeZt368e2cgatA5NO9&7EO;dVO1pYMY-mC
z0(oZjn=)%z*k--*@Ss2khG?4%7u)6HsJX7!htyywzpBQvuSO24wNHxM+x~*J6ZeG#
z{T^Z`uN>EfnJ8Q$NWCP~M?)Rcdi^ykL+lx`bEuB~j>CK+RRbc&p~+`OP4k{KjyNtq
z9xG_WF@|uqvP@=3&HJeGyfg}CN#j~kgbPQx9jAD9{Gi#VF}Z4cbFg*urM{CJInMtO
zy!%y34VMm6QOPGqz?Q}1v+lu{cJ$!Zad#sarnGM}?+;7C(bzGnMwuumsP3{J&Ao%$
zjAw_=%jV)>L1u-b4I8$~9Xk8)9xwC-UFbC`@`VBF`x)AqLa<@(lhz>M3Tp>*ocRS}
zaXOP?JD%egtYi*+);m*-L$h_J>brFa)K4fPt+MDK|8GOtC~-G5?3KLU|5FSnCr&Es
zniye;!@b90gN3+gLYWkFy$7}*WJ$V3G+^5ows2<8_#MBLg6yyN3^si-%8b3V8^*W!
z1j=+TLh$Mfj?Bm7xYTdLsp;N?YsUw2Lm7`@d+lfKo02<z7n2wr4<|zP2{$jQn-?I3
z#!2`?<4r7hq@|t2g)qj;oM96&1e5Gx+Q+{s!Zz8y`$8p0vGLWN`3ChAj4^LKE@N>J
zdihd9T>^f<(%M;?Eh8!T+oncF>9>jz4naDmVi#d4e2>tO8z(lAkDs?0F(i<^ziq4g
z<_T1$)Cn8Ec@D!V9&JYgmvMRK@P)BOUaYy~V`ZpdhchoUJwJ_Dqo-(@v{FzAq#sQ1
zes^3A=Y>_vGxhIb{ro8n*RKlDZ*+X4WY2yW4GJxj&x^!v7SqY(>MpFR+uNTpy@V|y
zE58T(9kK4__GiEHEtn2Cob)nGddKeGl!z3u!6g|(FZzR7IC5S2;j4(35F=*tIaBW-
z4n1Iu_*Hg}NYdh|eocN4zVPx$@4u6dlMUZ$Itxx?JEQEwFy&eJ`SkgGaTOi*ov;`C
z!5xmp78iajQ##?y{F><=!73Q!8!^@R%!$25(ld;YgRy#e*XZ}hMX+oh!u)e~duM&4
zQP^J~gEPhU7jjyTLz&>CBeKp#FtSfJtacv}d&We(eomV~YP_P?Zgn!~JYALGGWQOb
zf3efo86U;LAS!$l8-!!-{$wq113G#&UdQeCCy)+W4%Isp!vOO~SILGTm?_HIo}Q$D
zf@T+m@RHroWxbTgqp1e%WuI;4PNx#dxt(8S4pk6Hbkf<lpK@T+U(4U#EDvEi=)llB
zzW|(eK1)<FD}hlhw|)1bE<z=Dsw_i0D|W|}s+k0BV*lQx!sb99ED+36UA?Q0L-zN%
z<)(IHSDoqCPS#}X{}g@y4fQP;|Hygwv62kL7MHH1npHz^>Pvxp@kgLWnDSZ52R#BA
z!OqdN<{FWtpW#Zf1T!>q%=U-;Y=*Wa%G;Z5Q!uc=D4PAC0)M^xU2se{8`r|R0@%U|
zp!)H3Pp|Pj=*lMJNU!XIV2`CZ$qRfi=|?ZuIGc#b!I0oN@E50Q?@BH>b7Swxh`KeY
zqZpLnK1K2FJg%|Sbwu0OLuG<TMxB>CX4QP<VcKlL>Ae?HZ9I5zKABe3+4=@P?2A9w
z_eBH7NSIYls^-EvulvV?yBJ~aR>fhLS6(o8B`>K>=rm5rvp9K5+CxKUB>8>SAzV3l
zjgT8~0)|HGM#o-WhtS{VzA=KKSQlKk&3fw?E`0MyIhy$ZMiV<KBKY4x%f0ht_i}#V
z?D#XA3A!zu_{<~XAV~^+mL5YDhPz;-cu6+o*k0VsS%~<czz8G3r#Py+__2SQ<7k{4
zANE<?E+~+`gRAa~4O7RC<Lq|N(Y-H!;$&$T!vnsnFjgR{IjNKi{hZ9dpE`y>-pfhx
zvrH^lC932k=H-P|GnA%8irp~J5)v}SbO73f0@vr9)FJSEi+!+uBUDzKcb|&*2s6RK
zYBR*WFzwVf-}IscW<-B~e?8lbOQ{boTQ4f(xT||8BlkSE3~mMx0;Vumb%x^**BO}k
zD!)~C?GDb>#Kyeb>w!HaXG5$l$8p5^L5sKOHjK3&4v`xAjWut@3FnSlz?4R-c8YE{
zPAGTzDq5{V9{B|0uD4}7<LfFo*ZT;z_OSP}==Q;+y)&f&$qA@XmzLwMRl`|PM!r+$
zg<-B?yNc1f3~J`&%+^O)afx>hbSUI;L0Vjbo$@S<ZDkG~Qsjmynde%nqvo)vT_R%B
zGK~|z|H|at=YiF{><2YJq@maCgF=az2lmZxoDToPzO$ZWoR1^M!q}UQgA`xuU@5-D
zsqb4pO!CV1kZ29yP_f}OnOO`>8(7F5+vkkMhFirlRjSzUAhXQs`wjatc;&p4+hHYJ
z#XscF5Y%{S3{&dlW9&KPq?ww6deMN77i8pc{NA!r?7^$p7+626<Z}&LRhUEt1i4{k
ze0xjsWEI3lI8?HrDUPTs1#g9qqRZ!P?R5Dk&~xiUBJ22mSm+=-|1x3(7fDKg(~1b=
z(y-I(W2drV2HsiZXR%@jedWWic^Xi|y{rGxT0Hj2Q>K+`Z)5LFpLAyaB&PjD7d7u*
zSSC!Xd1mE9kEl$>?TlWS_MTzCvG*3vzjj0OXH?kqdcBeSLJ%Yunq(iz6vwi<)!Fiv
zeX#I2+U&!WAI#WayQuS_3Yye2I-WEK;ov=m4ws6Z=WO2rM&|e{xcqYeUH<QLFd1H;
zDBQsST`pObUI*QA*5K-~r-7v~o5f0LM#+uK_iCwAzcpjM%SgF-b|y?@UOlMrX$jin
zUG|%E1VikLBKf~`0kF>A;vj=zIH>xdZ8QEhw8q_0OS|d}wTq$icJ+^8>Bd%tS3?V|
zopG486F&-_kExgr)y?4a%e5}yOle$lc@*C@aU7@2s<MhJD{)!RCi+U10*pr2?K#kX
z5^EF>`nF!%gt`LH3dys_VPNje(O9u_u-=gudn>mBXPpnLNJ(D8C2e+t(76$8HEJ~?
zJ>QCxaji-P(ac0riky+7mkVI&&U;n4tG}@3>ZSe4d%a<6ygRmEpABZJTvoqWT4R3U
zDZWI3GB98pP`v3J4|Nx1Ma#t#A&<K1H{<?7>_4kYcA4@a^w8gEQ)jykgN0kizIrO-
zdbU@vS1=upT^<vqw!RM4WTHOo%K11$8xk<?NsX>7kNDYN@?%azobg?beAsMyn&<Vd
z9A^(+SNE}{!l_-M#U-B2uzr-!_RMQHSYpnpR$i{dWwE^;7s-pT|KxP(dWAczxJ4D-
zc(NB~Sy~?~&6GlMVN7J3@&?2g7~V<Qr-jo?L#OE5&)`~hpSR?r6zq~nDt!970hiy#
z4!S5$V`I<zfM?Hwh!k?a>78TfG3)9ed6eNY_8lM<+FU*jgWp&8<T`QVklN}`bA^w%
zFyPS<-hB+)Xb-xE-8lkniWa%nYF0S@)K;Q%!~(|+GngdZO97wne^8vah07T?zeky{
z!bTp+fYkkFY#vEWKSCXbVZRqXCS16J(_I$K-E3SiLCvAtMtBAji4xj-(*$AARaD~O
zm&dR*vM3c~N(ueCe0z1u?XYLIk0i;jpGbki8sU;gFgLu^={aTsBQHYkL>|$^S^Wj6
zVLfu}edEHQJ7A2J!v}U1NGoC!jf20g2p5d$Y}aw})x%V#QX|(NJLu!^vTeQY3#07T
zy5yH{z=+H92><WCI7WN3Kh~rG9@k0FG+wm9){x1i!?*vy()p$*d?md|%srM}BJ7T%
z^p@snlPfT*Aa!)4LlNhn*E3KIu0Zlgo1E02Ef_ppdMr>!AC@qvjjpQ$hfJowj~YM3
z>HEIF<$~YihE;~0?BQ3~Ql0s@)#N*F-Z$ep<spTArHzx1?M+}bd(iso%O33SFJSYc
zal|>Z4cfyFDcEkseN^I26wIg}p?sJ77mH&Kzhbo2#qf(=j^9envDRPHDJ+K+x4T1U
z8J8~r@yGtEkku;a9n;H2Ra0zP@f@~wl)>8A$sc(vmvLF5Eiy_a633fNsJYy4@5E^e
zN!8syp-)ld#xJ9t>s6ObwGyZS4P&<N8SUsn)-?B{>^3e=I(FsMRpQ*1`J+R@JL4~X
zSe+ikjROiHjmh8c!CZ}0fDg|HZ2H`*mOXtLW~7{MGrSDN{^WogF)XUM7@L^5#&{I^
zqi;M~ytM*-Mcab5SFCYNf6zutZ3ssB-7XQBePFeqGRG?5CC)uFAd*(-;ozCh=Fm?e
z@KK|0>6Ex44vg5Oeqd6=vCUhXq*_QMl_Swmxjl)we!s3=I=+O<jbAFwgR*d<@vT=_
z+;f~aNNF*9yc;Hbe^zJZN8!AZSx3^vSsZ-yLHTf}C@wGPlea2bK##K1<pdEK9FVx{
zU6F7c>vZcK8h0hZ$j0}gJ~CFE`1($jPSz2c66bF$edopnYl<T8t7l=`>NT&f|6#1_
zEf<OaOPqf0^K3HkFZN7TD19TT#3_NXIxX{c%=K-rDC0E8p@xL_*VSo=ls!Htz2wuN
z=7-o(8YNfkHu5hprKtsb6YRto*PVE5+|6w^eW#zCyB-I+L+?eWmt)z<5V~R^&%?Hh
zKr;WKz^E%97Im_;M#U9y&f&@Vm-o2fFVzgA^AjqFOf*RR`}!*MOg@de<M0D#G=Erg
z_xnI&#qn<Wm;TtT^w}$*lN)>dJC}8z^57gz#RY*2ZMb<{t-3}r3i~<E+m-rALQTcB
zG!*85iJzY}xNcWt?eA>PyMg4m?5t-$v->KJY)?KJO%}vyU&AD^<$E|dnMCsZ<0woy
zC&?}L8Q}Eo4V7!P;jmyV!1*=V99NUxI?Ab&;PCe|cf`~0VafKnAn%twP{EVGJ>V?`
zje;|*u4n29q)Y*<bT27!o>_!Khh7yH3XW!p>FmYMVj0<+X9lt1&Pe}~1vO0WJ^Yj2
zE*pAfkEOKnDr1LT=)e*+H{^Y5Vwb(IhP~x4Iae-=5$P29t807rK|gP%qLY#bfo!r{
zCp}po+vPtLWNMV*%;eIWG%HuEUJO2SJl`0$WY%u#+n<B^Bfp0tzYajXx$<=}x(OUR
z&1%2L@*plW=jZ>86vSb{2N_=kbD_v!BDV9fHVl0jv7NsWiwlmvexlxXxMDF@Z5bU5
zV-`J6RBN?i>lE#;xQ~0WR4g%Z%%cWpaGo%6BNAE!hHJuZ+<;z_pPrB6f_C&Yx7q1#
z2Wzhr#P8=&Lf2ZLZrgVnY@|s3b7QFrM!(~}h-7XkJsJ~Ao+t$is=Uh!qwJ7&j7|OP
zco1$Jo4=a2=z=o^5tZ=@*P!jwt+b&R^RU@zEu-;H4o5BX4cD2iprJ(Al-xNVJ9Q4G
z*L~S(pD*+b&jCGH+UPvfdiE3KB;0T4jTgb5bKkdQ-0gAUSy1j4$r-3KxjXpG^cl`p
zTx(_9eGz(lIfqrh-NeOHcO~}K=tA2={?A)!J}`gy)^Bp2M63>BquV`44dXG_)&(ZN
z;&zCVvAfa-9GXtGYwwanyU%xg_g0qSLZP&N!+a7pF$XZcj$y;T_zD6Y=YAM`Pstl<
z{Q)*<6mE|n>4ZM6wvSp-e6aY_!=BUmJ(0FkaNUBr9I8Iw+*{)eFjlR~X;b|a#?Fj9
zbt(=;;v&!~KH7(UQytmVQg2|CB;+a2^9<;zDm+2s6$kyU%g!G5uQ2OPY)t4XId=c7
z=DTuyFE$<f>bg&c7s~6$&T%>x!RSik>5*khBAH9IOnJlr_F775+|RxNON>G(c4sdV
zX#eC2pH8fRh2tOp^7T!@vP)pBh}&Tt^!uDrw8sbsv&9_rzu$%Kz(2pN9zDmJ@ofvi
zGnKfpZ|I0dk`N{}wDGA;R6|2(%O@qaoptc{bAf|GmbkiW#Jg@@2bNc&m4@a|;Y@?g
z=iPtoVRk{*VD`&2_D-c<dEt_X^^+O#i64hx=oif~?a#&Fds;$Qn13$}h2&d!h5KT`
z*-+z7*H$74vsBLyQ*#2@tEw}XRSw`p$$n4D7*T8rS@?A%SQA%TT*(Zx`>|k)?y?M@
zC4r<ODCUGuCr%Arc->4z!~r438S*$UY-aL~6b?VPv#x8s3Q2khGs+|VmnRmm)8J%$
zi0T1YILj+3yQzo)shW)fj@20VbD#Tw`aYOAHy`)Tu;M?`?PS~k;~e|HpELaTbo_tF
z$o?Bo`VahnFDLs4Iobb2{?F?FGmL+%^N;mO{|WB@tl$5mHvg~c{<E?CvvL13{C{lg
zpB?{Qpa07z5|rlpW=2nT80LT9hu}X>lHT}FM&~~-yJxEZ<jH^N^}p0-5ZBZ<H?%Ml
ze_~{0_#Zkav)U2+?(nu!v*Ho^V}sKq)ZO@z%sVjpX|DWHjza!t11s@+lWZ$L#~-Pe
z>Ql)3qGjplKIC*^-&Vo;-=)%@N*)R4FGjqh<Y$@T$=;J$4eKeq;#Nj~4I~a6VS3SG
zd|Ua*A-?Uxw@TOa#G))e2D&|Cneh9(n0hgNmDpdbCZ3~XQ@(#gqU3?c<d_U}OxUmo
zERa6DHuHchNUJvVG@H))Q7g95yDKicB0ZHJop5)29XNF9{2@vPRgM!<MD>uuvk8{O
z9MhJHj^GasbL1Mqso!Fw3AEC-%!$kIIRexQ)>353*rO|!<6V;Lb(~H2SC2%gUaEL!
zXr*FMF4LhkzbiWGwJ@8bb~|&KnxJH!-_JCma5%JWmRv%uCVe_);_uYcTZbEH&LNvb
zGM_rtqK0A=dyB6_Z;MOLZsn>2NBwO^Zmxe@>28$!sHFcY?Y^subzhCcfjXMM)HjW?
zQsm!9u`L@G+@dB^G94{frV~p)?m-L_rIvQiTc>s%Pi-F3Os7(|4|z^x$t>aeV{<%h
zp_<~`>j>^QQJrNu%c87;V@!-M?OJ2v&W>$-KfO};YN08aH<&<fwqjD_A4_he-|1j!
z>z3uJNm<)t_Un*+mEKWW|EA{p4_y%qCGqAoyE!hsNs`F-k*_<u%T4N+THyMTW8x8M
zL8^99rFIHKGt+gAvA$v^D~mPx+Kmg#O?RDX_(wvIZ|skaOSHLP#4XifH@j>XGLXUD
zm<Wbb4|GIc*|X@W36ZaGdAG0mU1Kk4Q)ft<&Y&u(J#VEII4Bpy<C|;Wx5gr*OzZ7*
z@GeKNyao3NQ+dtcsbHoRho>UtRj%@notT@iKZshFp4_CmKezZdee9-3hm<EXdF?B9
zyUC*`ujCPD#u_FsO5Tfzr>n4b{8=jh{E4YW)2#3l0lWu8_|ns5@O|?%F<|RgvGo;W
zg?HI6oAy%pO@EqNHS`%jFdM77Rolq<C6`AuM#{l4aGUlf1&i6AuRke9bEEU@AF1}J
zJZ)!l-jka^^ZlB%74@PO+nb02<F{2&&90AlbgVPg9EWPsl<AM~Qxj_p`h4GPPWg$R
z`NCQ@8KY!-_Vxx)lQ4*kXCwsl3To^QA;z{_Tae`8mck_iy|FUCUCs{-E{am{tS+Vx
z&bX)Pewc82y??OgRJJD%DW&P#<m;@;nH&c`bX~4_ak2W8RGfW@@5|85=9P82i@_C@
zCvU!`dL%<7bH3tJz|m&ERcoz*U!Gro?>X1~IwW64M3wJkPs}r$7CPCmcdu>wJ_aVA
zdus0`Fpzg^LSOEa$ZoyQrQ^mVlzckXA0KlLy*(YnQ)9QfJH6BRmd_)GnsN!RZ`|$O
zhA(&&%x}bnP~POCsX2Gu)mSfaWsLrUm!{1r-JGzkDXsB@kNFu7I_C#?;giz${Tawr
zqC=si5nGWy>vu=MLgd!TFP7nVdUfgH+i7`0Ub4ef7JD@3FHk&K<R4OEemE4C@<eE@
z^{xCAZ)knL(Gf2_{oZ-wPpoc&pMF<T#BN+@O0qkzR{kh-{?fzwJ-gp{f60-H8$0GE
zKvSlw;phD9lMNZ2Bya7Xo&y{XBjcIIie9nDX~OTB`tk;~9pR^Nkzg^S3{UG5DZibc
z<J~kqN(`rL=P>a7k(I+vQue3jL79yx6@>iM%+){tp*qujmw8gL+SSl)(-G~cwLf}3
z2F;INd^xoITkk`~#6_x{b7HQyZsZ|-%eU$IBZ+27PnzG-a{J#`<a5+5b~-I1A*D1!
z&v=xY{U&upcmv1#YlHQ<gt?2|N@CG`FBw1V6<8NzGvtpGzBkzWn_K6t;SlcIziAY~
z>q`-CNNQ43C$=D(P`T+l>r{DnXqMOF$Y~MvRB@y8F5l{R7aqD~7SHgNYm79WXVTZk
z_VL+)7`j&{s!vew&(+;+<RkE5p#8kO?e&|7)xNw|rd>It6Y<wN;j-*nixDG8rYL`K
zi2fi~wx&`1LRC(ASx(<Nf<B0=>^$cW6SbAg+zSPrsyxHxgR}?OY4=j?7ury{%y^dM
zrj%ddbW*?tJ)x@2zF52Oiz+U4TT2HGBQ&+M3>?#{_WU-dNj)|3=ek^#rG)VrfvmnO
z)bY*lLV7iv=#Or~6Y+HF$(Oc?*)){N7kMT=tNR`?_DbstW9A^gpKDZU^nzzx_)Jh7
zduW-*>AXq*G~MxYuXd@-iT6|K#jAWTf0L_yhUDFnWEf9!*~sdx$XYvtM^PU#e@ZaT
zyN76o*&62G5LEpheD$sJtuuMcQhG99JO*Ma`Hp=Y<0E~SmNT<0zA%19@k-J~RTsMl
zOW9^bjieyk{Ak6Rkwz)0!)DG>Uv8w7TG(Aoc*-0n#P?Y7NW_gB>mx<1F68a4LlrOY
zc>gsmSNP5KQNl^EeBlmb_oIuW18j7Av*;bZn^_%lB;BK9$7nr%L!5<bQIuBe0nfv-
z>V6Z7#~)>Q)+^>-gw57n5Ib(qtDY2{<l9#v-k}y8)SdcH!H8m0G9)~+sw~V{kL!r0
zNc_aD!|jqr<EabJ%5(QHbmYI|z3B2@akN%|okf7HDmnbaiLXcR{%Q3hLeLxD9xHjH
zsnzMpX6z<VjGyJ-$6D#_5GxqyJUU%)bamS}Rv<%L;(1lu7R@hpmzl)uGn)^?T2_Qi
zuM)$w2<Fr}Ri<4wu2Scs;+Ajm2`_fj*i%OF&QrO4ykZkVf8dGdw}jqz?1d3mo-*IW
z(DDJ3E#dRh3W8&!tb|Fv!g?v6gZ;F>Z>QanKPdPiFf+T!>ot?yvyY#CEcL!yn*4L{
z>aPglMV_gKsl&|ySL9T_jh=Ql3auXMy?AY=_d-S?^X<51iwB{;H|2Gu>Du40=QoH%
z5%Y=CYGctE96iydn_|Z#OGKS-DgP$;oeiP*s^@OzM?QDXfhP!EQ_|PX9+CMS+%=@q
zn^Y~V6;eGdBmREFQ?0=Eb%J7d@39=B5P@ufn*SsX%NyfKdv)<a>ae%NCKZe4V~Xk;
zt`USu=u<s6&-ENV70OkVtNEw-%qzO+v<%LsjVnLsYGW|Q`}M5nyaUG{(^u@;9mHMT
zb2TKp;?B1~fz<Bq@_dS}seaY3(Zz2beUdmg>mq&aqR+g_4N><vzK`WC(UEN3zlGHY
zJ<aq3ycynq+rLiu<}ROVU#rv~Xt(WnDP(ov_VRf4EqPwHwyCQ>BxTuy_KC(xjz8V|
zX+UJesWqVdO85;XBcO<QbHn`V7goNgilES4s+ZDcMVhvjSM;uGE#12v_~~Ln)lOh)
z`S28t2mhA5vfZ8`uc3JcZpIH%`xOtRZ@jYg;zPFdJvo8*=eno9Rh@V5_c+=T-Ei^O
zxF_@XC*Nrnp0VW%^qv{FbXN3ZAp6HHs}zj>eakAQ9lnG>L-N0b{)PK5`rm<w|E+ZT
zC*}WL`p<g*4EO&j-ao_re~b5zxc{Pm(SN1?^6u#0_D7`qZ^yscoPT`JKylB)M(00m
s56t|p>CwM%|AqU%1MdG{`~5H6f8qXrgZn?TJtSNI2e2Gl*uqx;0L*yv5C8xG

diff --git a/pkg/src/sources/EMGLLF.c b/pkg/src/EMGLLF.c
similarity index 91%
rename from pkg/src/sources/EMGLLF.c
rename to pkg/src/EMGLLF.c
index b77f24a..978f253 100644
--- a/pkg/src/sources/EMGLLF.c
+++ b/pkg/src/EMGLLF.c
@@ -6,30 +6,30 @@
 // TODO: don't recompute indexes ai(...) and mi(...) when possible
 void EMGLLF_core(
 	// IN parameters
-	const Real* phiInit, // parametre initial de moyenne renormalisé
-	const Real* rhoInit, // parametre initial de variance renormalisé
+	const Real* phiInit, // parametre initial de moyenne renormalise
+	const Real* rhoInit, // parametre initial de variance renormalise
 	const Real* piInit,	 // parametre initial des proportions
-	const Real* gamInit, // paramètre initial des probabilités a posteriori de chaque échantillon
-	int mini, // nombre minimal d'itérations dans l'algorithme EM
-	int maxi, // nombre maximal d'itérations dans l'algorithme EM
-	Real gamma, // puissance des proportions dans la pénalisation pour un Lasso adaptatif
-	Real lambda, // valeur du paramètre de régularisation du Lasso
-	const Real* X, // régresseurs
-	const Real* Y, // réponse
+	const Real* gamInit, // parametre initial des probabilites a posteriori de chaque echantillon
+	int mini, // nombre minimal d'iterations dans l'algorithme EM
+	int maxi, // nombre maximal d'iterations dans l'algorithme EM
+	Real gamma, // puissance des proportions dans la penalisation pour un Lasso adaptatif
+	Real lambda, // valeur du parametre de regularisation du Lasso
+	const Real* X, // regresseurs
+	const Real* Y, // reponse
 	Real eps, // seuil pour accepter la convergence
 	// OUT parameters (all pointers, to be modified)
-	Real* phi, // parametre de moyenne renormalisé, calculé par l'EM
-	Real* rho, // parametre de variance renormalisé, calculé par l'EM
-	Real* pi, // parametre des proportions renormalisé, calculé par l'EM
-	Real* llh, // (derniere) log vraisemblance associée à cet échantillon,
-	           // pour les valeurs estimées des paramètres
+	Real* phi, // parametre de moyenne renormalise, calcule par l'EM
+	Real* rho, // parametre de variance renormalise, calcule par l'EM
+	Real* pi, // parametre des proportions renormalise, calcule par l'EM
+	Real* llh, // (derniere) log vraisemblance associee a cet echantillon,
+	           // pour les valeurs estimees des parametres
 	Real* S,
 	int* affec,
 	// additional size parameters
 	int n, // nombre d'echantillons
 	int p, // nombre de covariables
-	int m, // taille de Y (multivarié)
-	int k) // nombre de composantes dans le mélange
+	int m, // taille de Y (multivarie)
+	int k) // nombre de composantes dans le melange
 {
 	//Initialize outputs
 	copyArray(phiInit, phi, p*m*k);
@@ -67,7 +67,7 @@ void EMGLLF_core(
 		copyArray(rho, Rho, m*m*k);
 		copyArray(pi, Pi, k);
 
-		// Calculs associés a Y et X
+		// Calculs associes a Y et X
 		for (int r=0; r<k; r++)
 		{
 			for (int mm=0; mm<m; mm++)
@@ -174,7 +174,7 @@ void EMGLLF_core(
 		for (int v=0; v<k; v++)
 			gam2DotLogPi2 += gam2[v] * log(pi2[v]);
 
-		//t(m) la plus grande valeur dans la grille O.1^k tel que ce soit décroissante ou constante
+		//t(m) la plus grande valeur dans la grille O.1^k tel que ce soit decroissante ou constante
 		while (-invN*a + lambda*piPowGammaDotB < -invN*gam2DotLogPi2 + lambda*pi2PowGammaDotB
 			&& kk<1000)
 		{
diff --git a/pkg/src/sources/EMGLLF.h b/pkg/src/EMGLLF.h
similarity index 100%
rename from pkg/src/sources/EMGLLF.h
rename to pkg/src/EMGLLF.h
diff --git a/pkg/src/sources/EMGrank.c b/pkg/src/EMGrank.c
similarity index 93%
rename from pkg/src/sources/EMGrank.c
rename to pkg/src/EMGrank.c
index 3a9bf94..a98ff91 100644
--- a/pkg/src/sources/EMGrank.c
+++ b/pkg/src/EMGrank.c
@@ -41,20 +41,20 @@ static Real* pinv(const Real* matrix, int dim)
 void EMGrank_core(
 	// IN parameters
 	const Real* Pi, // parametre de proportion
-	const Real* Rho, // parametre initial de variance renormalisé
-	int mini, // nombre minimal d'itérations dans l'algorithme EM
-	int maxi, // nombre maximal d'itérations dans l'algorithme EM
-	const Real* X, // régresseurs
-	const Real* Y, // réponse
+	const Real* Rho, // parametre initial de variance renormalise
+	int mini, // nombre minimal d'iterations dans l'algorithme EM
+	int maxi, // nombre maximal d'iterations dans l'algorithme EM
+	const Real* X, // regresseurs
+	const Real* Y, // reponse
 	Real tau, // seuil pour accepter la convergence
 	const int* rank, // vecteur des rangs possibles
 	// OUT parameters
-	Real* phi, // parametre de moyenne renormalisé, calculé par l'EM
-	Real* LLF, // log vraisemblance associé à cet échantillon, pour les valeurs estimées des paramètres
+	Real* phi, // parametre de moyenne renormalise, calcule par l'EM
+	Real* LLF, // log vraisemblance associe a cet echantillon, pour les valeurs estimees des parametres
 	// additional size parameters
 	int n, // taille de l'echantillon
 	int p, // nombre de covariables
-	int m, // taille de Y (multivarié)
+	int m, // taille de Y (multivarie)
 	int k) // nombre de composantes
 {
 	// Allocations, initializations
@@ -91,7 +91,7 @@ void EMGrank_core(
 		// Etape M //
 		/////////////
 		
-		//M step: Mise à jour de Beta (et donc phi)
+		//M step: Mise a jour de Beta (et donc phi)
 		for (int r=0; r<k; r++)
 		{
 			//Compute Xr = X(Z==r,:) and Yr = Y(Z==r,:)
diff --git a/pkg/src/sources/EMGrank.h b/pkg/src/EMGrank.h
similarity index 100%
rename from pkg/src/sources/EMGrank.h
rename to pkg/src/EMGrank.h
diff --git a/pkg/src/Makevars b/pkg/src/Makevars
index 50b7fb6..6a25e63 100644
--- a/pkg/src/Makevars
+++ b/pkg/src/Makevars
@@ -1,11 +1 @@
-#Debug flags
-PKG_CFLAGS=-g -I./sources
-
-#Prod flags:
-#PKG_CFLAGS=-O2 -I./sources
-
 PKG_LIBS=-lm -lgsl -lcblas
-
-SOURCES = $(wildcard adapters/*.c sources/*.c)
-
-OBJECTS = $(SOURCES:.c=.o)
diff --git a/pkg/src/adapters/a.EMGLLF.c b/pkg/src/a.EMGLLF.c
similarity index 100%
rename from pkg/src/adapters/a.EMGLLF.c
rename to pkg/src/a.EMGLLF.c
diff --git a/pkg/src/adapters/a.EMGrank.c b/pkg/src/a.EMGrank.c
similarity index 100%
rename from pkg/src/adapters/a.EMGrank.c
rename to pkg/src/a.EMGrank.c
diff --git a/pkg/src/sources/utils.h b/pkg/src/utils.h
similarity index 100%
rename from pkg/src/sources/utils.h
rename to pkg/src/utils.h
diff --git a/pkg/src/valse_init.c b/pkg/src/valse_init.c
new file mode 100644
index 0000000..b8ce9dd
--- /dev/null
+++ b/pkg/src/valse_init.c
@@ -0,0 +1,19 @@
+#include <stdlib.h> // for NULL
+#include <R_ext/Rdynload.h>
+#include <Rdefines.h>
+
+/* .Call calls */
+extern SEXP EMGLLF(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
+extern SEXP EMGrank(SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP, SEXP);
+
+static const R_CallMethodDef CEntries[] = {
+  { "EMGLLF",  (DL_FUNC) &EMGLLF,  11 },
+  { "EMGrank", (DL_FUNC) &EMGrank, 8  },
+  { NULL,      NULL,               0  }
+};
+
+void R_init_valse(DllInfo *dll)
+{
+  R_registerRoutines(dll, NULL, CEntries, NULL, NULL);
+  R_useDynamicSymbols(dll, FALSE);
+}
-- 
2.44.0