From 58be677576c79770ba63b91240ec9ed991f4fc49 Mon Sep 17 00:00:00 2001 From: Tobias-Brock Date: Sat, 16 Dec 2023 17:08:03 +0100 Subject: [PATCH] add correlation and mi to correlation plots --- .../figure/correlation_plot.png | Bin 97142 -> 467034 bytes .../rsrc/make_correlation_plot.R | 26 ++++++++++++++++-- 2 files changed, 24 insertions(+), 2 deletions(-) diff --git a/slides/information-theory/figure/correlation_plot.png b/slides/information-theory/figure/correlation_plot.png index 216b33879eeebe9ef2e5e8e4e65156713b4e3905..3302cc47166e9fda990783ce5895a8cebd553af6 100644 GIT binary patch literal 467034 zcmdqJcRba9A3rQF=2yk$42<2ZshvMK6k>KFq>fF2z zej-e&q=JKkM`SG{qiQQ7Cu9G{-ckLXiJ66*g`I_?wHZ`S8V5%xEKJkzHMQnliR9V} z4#s}pk(``pqKl`o-`+rf`u$qDu&8)D%^CCN+q1~-jhR$yX8whEopojMwt4)7I>*$Qn-l z_*o`gPO4%q^zeK|=Tcjnh;uVykPtD*#StFI9>;v;!9q*ZuT2bH$L#n)_2H$}daAY)lh z*8I?mwyB^S%M1s4csHE>OofX*{aVEKs8_aIpx~1-!*HYTsdts^jBVSLuS!G(FXArh zYRy3cyJP%ZAW6FB;htLxU8&2#s`J7Ek8cv+zMIPA=S#2Xw%M1OOQS{=BmEi!6Y7Flycj-i`V6B z|HM^0HRc7g&C7@b)ow1VrI^$^c_Xetk?f3$xTEpg|YklP> zuXN5O!=J(Y7R+l+hKAc-?yn162JtQ5F^urZ^T&ap&!mfH=~g!nHUB9B zA$r;w|H#RFxAy0V`xORgx?o5{$O`OP$Ay)7;_q(*?T~aql8J$d0o$IqaXTXsgq?Os z{R^%1`Z1?fXGSY38!qRrUn8lG1D7qv%j2cS%Yu5hFK&2U^_!+hrKw6TDSU}R@e2<77x26qiwqnqaQMRFU&4V%=J5^ zJEl9J-gg=P=5{o8G!UJ~|EFcS`Fs#4cS!!=yfGB)Vk>|8wS6DGNC#mrw{yK|i&H{%2sDw<{Tx>>1@T`cJ{?ZmZ^W*ddK!B^k+>__^3InM6@paT*dB3QE$=0o54BGH zR{3e|V{7-~f+<1CWA=Nu(ceF_uGg*9Q~%5%s!Vu|#wqo9EYxBze{oJR<(_Tflzv_4 zj79WNuS%Hscj48+)7QNM@2wUZF*t=1Ic^6~Hx*3e`Zt!}WcAH#??T zoC(iHqs!BCIAZte2nwg>^X1h`CbwJdW@EizKnPjr$XhBY;jn|pH*u~6TI1k>M_0fX z75D;k?w{0u%CSz=zwoqt~e8gyB= z|6MU+?^C4I6?PJ4UUgxnf8QrxrCw70+g>A)qVvJkpi_L6;|Tfp6`<-9`S{;AtrYIH zuTqKM716Q(z5+hu(p&uNj>Yl8BT)6>^-1bsqyN_*4-BN9f8VkH{~kzEE;r{HN-cj- zRlaJ*-Txto`Z`*mUEsR;E3fM9RKAkHB%=h&GYIK_ir?q{Es}_Kq1~4v|LJmba=MOg zNGtAtTa1q9%6vh?#Kg`2&Lv*x`-%RpH}q=%DS1`-E2b$B+;ZW6o`4Sw`;56H0gr<> z`@emO^E)4UPZx_NLb5&CinWS9*-Vya|MI{zj#?xb=2T5uK0rA#LwNr5@-%$~Kh;K@ zZFk!ArwFf2**9s1Q9Xqg=~Y6{PxjS2X*~*UCQ367{MM8^_3az8jojw0J+&Rv zUzrr*j|3>6ypF6pnh!zjrUbW#P!t$7!i8h<5vK=hlUC_2xeJfK)KkB3a66oVjf!F# zG9``|$xcx_=-#*5-BV`a!Y}r>W<-0obSSRi-QkoHyLZ|5boC^Yfy=BjTr=bzR}V+# zbz<7WwUNA-@v8P;U9pLrY}<*8$>ENPD(;b}>KJAvC^R5fG3iU2+i1RKKKQkKr{#Vd z@N(KLsm{>ZCWcw>OT_+KLCLSC*2U_Hv*TUO;T)w+L@y?`*swm|mq>&)J*$EcH<*O3 zBiLKu(++|=T4eakDO@c-`V}OUVL3fkNX|;QPfK~M#JFUuVYmNH2*ZHn*`HR;^|2xb zdqJlq#Z$`Whu&uy+;uCDTt+puWoK_ZpnETcz7|x%Zm+W@9y_lWy_w>YML@qNSbEcgXdd>y-Mh)+w@0(nAA3I!(QDLtoX2!5U8|I_Du!% zEsa;#|0wbq`mHkFB3WP*hWQTsh{ZU`Ta*n)`&qH(vOx?(4H7f0w zX$TkY?z>?nK_%U|=apAhl{*uRy^_j}-r$SLv2|+6j>qn+%1*hjO*nv?^*C)jOmJ2w zuT_^v&T1NSyquoy(xf$ziF{i%<2qHi{;5U^CLHS6uQixZZuI=n-SVV(#yU3@%F}e_ z7;9L;4Ys`EdpFJtN}Hj5IV-(F0yW_h+oWQb$M$nA{vB4|*!Xm(7x=ngr=odno_&%) z!1ML1?Sy-aHKTa~O-2Sdd0b#`l@LB_;07 z*Ccevq4#==hVeUk(O&s=!_uB{+-V-4mf@2q?ZNXDeaBplf&D^=FY>;^d{qhZgdOH% zLWoBa)QD4NxKY82AseI#^jAvUa%Mah=iw7Tr|C~)s)Mt)%2_*a@}FItV%Q4G3N?Ow zdOCAzym~ldUI*?#p7+_pL$=_B79uhA+Z^q1c~Hdi(%efhq8!h3g*An!d%~7?(lQe7 zEWDKH5btM`6~0@o=({x`)_wSa-~BO9%6o!pDqC{(-(&jrO1k2e*Dii{?=f^GY1g}M zjls;9kd->BcJJYY*?9r;Wh=dJ|t(RDc2T@lfx25GjK+%~I`hT1W$i>ZwiE z7I>(7YQ=;%&n*>7c1S%P>1F63DW@S_mJFvf) zRORH=&q98af0@jQ^kp=-UD1yGC$%e~tzWWUScybmq$LO?I}U^`e^i4Y4qUu1j+bMf z2&}c4nMlA;h{KVdIF1U;p0|QqPGU?D`5i{7(3sDCeG3}S9rx5?)IWY>L{olb;|pJO zpI%6T#C&(~coL4{b;DAr7ek)U)f+ka8hP{j7*Jk3uRpltESzGRsy)c}E_g9R*&zr!s2Sqo?AR6amL=ug z2Mo2vxmxB6@;xz^O-}vqOv`k~i36ox=O-GwOFuXgyCi&Ri`#{N59tzRF8ahyg1tFy z#lur<{I2<0o>iJVGZUBaON@ZFk-G&%PjNqfv*~=(UX7@|?j{|H*_HXS`&LGJLrS$5 zFUy^CWQz@FZM8fwxfDw1eDQ)8)B6M2|FXf%u_>*l3C13XN{%~^QT%-9lU#lp^q;hZ#U{4HX}97;jB%!S z{X&G~EJY0Vt-8#(j89^Ic%5!myRtmkNz*>5=mc+LswwjuTN+!A4{wqVKoD(~Z&%2M zDfRu7+b*>@W%Z)>ZnwwYmn-M*cTi^QG0ABnpDA+}p1#$;_&?Y_hkD;`IKU)3^4 z@-+({7g4#VZ8`6)4tHwLX2k^nOku8=`)z_jyjGZ4mrCHx{rv3oP*IL~Mf>keJb#2% z69yjGH}I9jzQlZh;@yCaZ17xz`m|_^tXC<^6S7ychj<1|%=V zdgicW!;~FhgyB#Hg(~^+hcnhukgfiGh(tDhV75X+z(q9}iBH6LnU#XO=RL22g1N14 zvskSRZ*Sx%u6eYuWIJB0WaxE_M(#9jR!vzNXj}H2KuLd|9?~_bd7bZ%hfclJ>lej{ zp-uoia#^cJdG*#v@RJ7B0kGkXKDu5R&kzcc?C?W9!Tub zlrC(0zCBO;V4{^GWE!-71~CWW?Su94f$B!G8)`nhPZ&5Jsj>kq2-&8rC}SJHbLHnh zrQ&~{Ijl?6n$xUX0(OK}p-z+y3W?|t3L)@Q-ue?PwSyP58J&=;*54Jop1$QA+v;Hy zjR8m?WE~)Zk-tbFfF;eXg(9Z%&E(^!u&wFP^)Qq9bpB7 z4`xQSjcHaVpmVb9mcl#)UAcRXovH>`teZQMZ$NALUq_}fHLgcc3qO9nKiKP>BcnIB zo#P%z(nOnNcOr6VSnt^XsEL}Cg;9IUYsNYEqu5ro$UUZWrf{Bjo z5=M|?;LRvpH|)4k)>${s?#>$B)(o&>vEcWQYDBH^_3I@~vs@*2E_>|#3|c`OEl<7h zI<%x(ge4pvcG%T##`kDG(}Lf?OjhLDi&`)GU-8Mp2at(H&ZU!FEep(}<^4xJ!fQt3 z;GXyM7dwRaJAM_tEU8;#H@@w7vYHzxvDkF6U!nnUHe$+SfsUOdAje!5Z|5EzvM0H} zhES<4ens)tb{u5efM+^A9gGF;YY)cQ(N2x(%EC;xDYDmESZllLZnnw2pWv2o&*sR^ zF}QTj$uyYVjecy}BVJuIYfmPVYN2-U&{YVG?wOiGNF00KxUskRyJ4$z#F(M+R$RB! 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------------------------------------------------------------------------- n <- 400 @@ -36,16 +39,35 @@ df6 <- data.frame(x = xy6[,1], y = xy6[,2]) # PLOTS ------------------------------------------------------------------------ make_plot <- function(df, xlimit = NULL) { + + df <- na.omit(df) + # Calculate Pearson correlation + corr <- cor(df$x, df$y, method = "pearson") + + # Discretize for mutual information calculation + df_discrete <- df + num_bins <- ceiling(sqrt(nrow(df_discrete))) # Using the square root heuristic + df_discrete$x <- cut(df_discrete$x, breaks = num_bins, labels = FALSE) + df_discrete$y <- cut(df_discrete$y, breaks = num_bins, labels = FALSE) + mi <- mutinformation(df_discrete$x, df_discrete$y) + + # Create the plot p <- ggplot(df, aes(x = x, y = y)) + geom_point(shape = 1, size = 2, stroke = 1) + theme_bw() + - theme(axis.title = element_blank()) + ggtitle(paste("Corr: ", round(corr, 2), + ", MI: ", round(mi, 2))) + + theme(axis.title = element_blank(), plot.title = element_text(size = 10)) + + # Set x limits if specified if (!is.null(xlimit)) { p <- p + xlim(xlimit[1], xlimit[2]) } + p } + p1 <- make_plot(df1) p2 <- make_plot(df2, xlimit = c(-1, 1)) p3 <- make_plot(df3) @@ -54,4 +76,4 @@ p5 <- make_plot(df5) p6 <- make_plot(df6) p <- grid.arrange(grobs = list(p1, p2, p3, p4, p5, p6), nrow = 1, ncol = 6) -ggsave(filename = "../figure/correlation_plot.png", plot = p, width = 12, height = 2) \ No newline at end of file +ggsave(filename = "../figure/correlation_plot.png", plot = p, width = 12, height = 2)