--- title: "Dyadic expansion with R" date: "2016-08-08" output: html_document --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE, collapse=TRUE, fig.path="./assets/fig/dyadic-", fig.align="center") fscale <- 1 # scale for figures ``` We provide a function that computes the dyadic representation of a real number in the interval $[0,1]$. Then we give an implementation of two transformations of the set ${\{0,1\}}^\mathbb{N}$ which are well-known in ergodic theory: the dyadic odometer and the Pascal transformation. For each of these transformations, we plot the graph of the conjugate transformation of $[0,1]$ obtained by the dyadic representation. ## Dyadic expansion Every real number $u \in [0,1]$ has a *dyadic expansion* (or *binary expansion*): $$ u = \frac{\epsilon_1}{2} + \frac{\epsilon_2}{2^2} + \frac{\epsilon_3}{2^3} + \ldots $$ where $\epsilon_i=0$ or $1$. We say that the sequence $(\epsilon_1, \epsilon_2, \ldots)$ is the *dyadic representation* of $u$. The `num2dyadic` function below returns the dyadic representation of $u \in [0,1]$. ```{r} num2dyadic <- function(u, nmax=1024L){ out <- integer(nmax) i <- j <- 0L while(u>0 && i<nmax){ j <- 1L + max(0L,floor(-log2(u*(1+.Machine$double.eps^.5)))) if(i+j <= nmax){ i <- i + j out[i] <- 1L u <- 2L^j*u - 1L }else{ i <- nmax } } return(out[1:i]) } ``` The `dyadic2num` function below does the reverse action: ```{r} dyadic2num <- function(d) sum(d/2L^(seq_along(d))) ``` Let us check that the dyadic representation of $0.75 = \frac{1}{2}+\frac{1}{4}$ is $(1,1)$: ```{r} num2dyadic(1/2+1/4) ``` The real number $u=0.2$ has the infinite periodic dyadic representation $(0, 0, 1, 1, 0, 0, 1, 1, \ldots)$. The `num2dyadic` function applied to $0.2$ returns only the first $54$ digits of its dyadic representation: ```{r} ( d <- num2dyadic(0.2) ) length(d) ``` But it makes no difference for R: ```{r} dyadic2num(d) == 0.2 ``` ## The dyadic odometer The dyadic odometer is the transformation $O$ of the set ${\{0,1\}}^{\mathbb{N}}$ defined by $O(d) = d + (1, 0, 0, \ldots)$, where "$+$" is the addition $\bmod\, 2$ with carry to the right. The `odometer` function below is an implementation of the dyadic odometer and its inverse (option `image="backward"`). ```{r odometer} odometer <- function(d, image=c("forward", "backward")){ image <- match.arg(image) if(image=="forward"){ if(all(d==1L)){ d <- c(rep(0L, length(d)), 1L) }else{ k <- which.min(d) d[1:k] <- 1L-d[1:k] } } if(image=="backward"){ if(all(d==0L)){ d <- c(rep(1L, length(d)), 0L) }else{ k <- which.max(d) d[1:k] <- 1L-d[1:k] } } return(d) } ``` Using the dyadic representation, the odometer also defines a map from the interval $[0,1]$ to itself. We plot its graph below: ```{r plot_odometer, fig.width=fscale*4, fig.height=fscale*4} par(mar=c(4,4,2,2)) u <- seq(0, 0.995, by=0.005) Ou <- sapply(u, function(u) dyadic2num(odometer(num2dyadic(u)))) plot(u, Ou, xlab="u", ylab="O(u)", xlim=c(0,1), ylim=c(0,1), pch=19, cex=.25, pty="s", xaxs="i", yaxs="i") grid(nx=10) ``` ## The Pascal transformation The Pascal transformation $P$ is defined for every $d \in {\{0,1\}}^{\mathbb{N}}$ except when $d=000\ldots$ or when $d$ has the form $d=0^i111\ldots$ ($i\geq 0$). Such a $d$ has the form $d= 0^m1^k10x$ where $m,k \geq 0$ and $x \in {\{0,1\}}^{\mathbb{N}}$, and then the image of $d$ by the Pascal transformation is $$ P(0^m1^k10x) = 1^k0^m01x. $$ The case when $d=0^i111\ldots$ does not occur for us since we deal with finite sequences only. One naturally extends the Pascal transformation to include the case $d=000\ldots$ by setting $P(000\ldots) = 000\ldots$. ```{r pascal} pascal <- function(d){ if(all(d==0L)) return(0L) i <- which.max(d) m1 <- i-1L d0 <- c(d, 0L) k1 <- which.min(d0[-(1:i)])-1L begin <- c(rep(1L, k1), rep(0L, m1+1L), 1L) if(length(d)==m1+k1+1L) d <- begin else d[1L:(m1+k1+2L)] <- begin return(d) } ``` By the dyadic representation, the Pascal transformation also defines a map from the interval $[0,1)$ to itself, whose graph is plotted below: ```{r plot_pascal, fig.width=fscale*4, fig.height=fscale*4} par(mar=c(4,4,2,2)) u <- seq(0, 1-1/2^10, by=1/2^10) Pu <- sapply(u, function(u) dyadic2num(pascal(num2dyadic(u)))) plot(u, Pu, xlab="u", ylab="P(u)", xlim=c(0,1), ylim=c(0,1), pch=19, cex=.25, pty="s", xaxs="i", yaxs="i") grid(nx=10) ```