更改默认拆分布局

时间:2018-06-06 14:48:49

标签: visual-studio-code

我知道我可以使用decodeFloat()快捷键来更改分割布局,但我希望它默认为水平分割。我找不到这个设置。有人知道VS Code中是否可以这样做吗?

1 个答案:

答案 0 :(得分:1)

1.25 版本开始,有4个方向分割编辑器的命令。示例 `#Data #Population counts (from years 1 to 10) y <- c(45, 48, 44, 59, 62, 62, 55, 51, 46, 42) #Capture-recapture data (in m-array format, from years 1 to 10) m <- matrix(c(11, 0, 0, 0, 0, 0, 0, 0, 0, 70, 0, 12, 0, 1, 0, 0, 0, 0, 0, 52, 0, 0, 15, 5, 1, 0, 0, 0, 0, 42, 0, 0, 0, 8, 3, 0, 0, 0, 0, 51, 0, 0, 0, 0, 4, 3, 0, 0, 0, 61, 0, 0, 0, 0, 0, 12, 2, 3, 0, 66, 0, 0, 0, 0, 0, 0, 16, 5, 0, 44, 0, 0, 0, 0, 0, 0, 0, 12, 0, 46, 0, 0, 0, 0, 0, 0, 0, 0, 11, 71, 10, 2, 0, 0, 0, 0, 0, 0, 0, 13, 0, 7, 0, 1, 0, 0, 0, 0, 0, 27, 0, 0, 13, 2, 1, 1, 0, 0, 0, 14, 0, 0, 0, 12, 2, 0, 0, 0, 0, 20, 0, 0, 0, 0, 10, 2, 0, 0, 0, 21, 0, 0, 0, 0, 0, 11, 2, 1, 1, 14, 0, 0, 0, 0, 0, 0, 12, 0, 0, 18, 0, 0, 0, 0, 0, 0, 0, 11, 1, 21, 0, 0, 0, 0, 0, 0, 0, 0, 10, 26), ncol = 10, byrow = TRUE) #Productivity data (from years 1 to 9) J <- c(64,132,86,154,156,134,116,106,110)# number R <- c(21, 28, 26, 38, 35, 33, 31, 30, 33)#surveyed broods #Specify model in JAGs sink("ipm.jags") cat(" model { # Integrated population model # - Age structured model with 2 age classes: # 1-year old and adults (at least 2 years old) # - Age at first breeding = 1 year # - Prebreeding census, female-based # - All vital rates assumed to be constant # 1. Define the priors for the parameters # Observation error tauy <- pow(sigma.y, −2) sigma.y ~ dunif(0, 50) sigma2.y <- pow(sigma.y, 2) # Initial population sizes N1[1]~ dnorm(100, 0.0001)I(0,) # 1-year Nad[1]~ dnorm(100, 0.0001)I(0,) # Adults # Survival and recapture probabilities, as well as productivity for (t in 1:(nyears-1)){ sjuv[t] <- mean.sjuv sad[t] <- mean.sad p[t] <- mean.p f[t] <- mean.fec } mean.sjuv ~ dunif(0, 1) mean.sad ~ dunif(0, 1) mean.p ~ dunif(0, 1) mean.fec ~ dunif(0, 20) # 2. Derived parameters # Population growth rate for (t in 1:(nyears−1)){ lambda[t] <- Ntot[t+1] / Ntot[t] } # 3. The likelihoods of the single data sets # 3.1. Likelihood for population population count data (state-space model) # 3.1.1 System process for (t in 2:nyears){ mean1[t] <- f[t−1] / 2 * sjuv[t−1] * Ntot[t−1] N1[t] ~ dpois(mean1[t]) Nad[t] ~ dbin(sad[t-1],Ntot[t-1])# problem here I think } for (t in 1:nyears){ Ntot[t] <- Nad[t] + N1[t] } # 3.1.2 Observation process for (t in 1:nyears){ y[t] ~ dnorm(Ntot[t], tauy) } # 3.2 Likelihood for capture-recapture data: CJS model (2 age classes) # Multinomial likelihood for (t in 1:2*(nyears−1)){ m[t,1:nyears] ~ dmulti(pr[t,], r[t]) } # Calculate the number of released individuals for (t in 1:2*(nyears−1)){ r[t] <- sum(m[t,]) } # m-array cell probabilities for juveniles for (t in 1:(nyears−1)){ # Main diagonal q[t] <- 1−p[t] pr[t,t] <- sjuv[t] * p[t] # Above main diagonal for (j in (t+1):(nyears−1)){ pr[t,j] <- sjuv[t]*prod(sad[(t+1):j])*prod(q[t:(j−1)])*p[j] } #j # Below main diagonal for (j in 1:(t−1)){ pr[t,j] <- 0 } #j # Last column: probability of non-recapture pr[t,nyears] <- 1-sum(pr[t,1:(nyears-1)]) } #t # m-array cell probabilities for adults for (t in 1:(nyears-1)){ # Main diagonal pr[t+nyears−1,t] <- sad[t] * p[t] # Above main diagonal for (j in (t+1):(nyears−1)){ pr[t+nyears−1,j] <- prod(sad[t:j])*prod(q[t:(j-1)])*p[j] } #j # Below main diagonal for (j in 1:(t−1)){ pr[t+nyears−1,j] <- 0 } #j # Last column pr[t+nyears−1,nyears] <- 1 − sum(pr[t+nyears−1,1:(nyears−1)]) } #t # 3.3. Likelihood for productivity data: Poisson regression for (t in 1:(nyears−1)){ J[t] ~ dpois(rho[t]) rho[t] <- R[t]*f[t] } } ",fill = TRUE) sink() #Bundle data jags.data <- list(m = m, y = y, J = J, R = R, nyears = dim(m)[2]) #Initial values inits <- function(){list(mean.sjuv = runif(1, 0, 1), mean.sad = runif(1, 0, 1), mean.p = runif(1, 0, 1), mean.fec = runif(1, 0, 10), N1 = rpois(dim(m)[2], 30), Nad = rpois(dim(m)[2], 30), sigma.y = runif(1, 0, 10))} #Parameters monitored parameters <- c("mean.sjuv", "mean.sad", "mean.p", "mean.fec", "N1", "Nad", "Ntot", "lambda", "sigma2.y") #MCMC settings ni <- 20000 nt <- 6 nb <- 5000 nc <- 3 ipm <- jags(data=jags.data, inits=inits, parameters.to.save=parameters, n.chains = nc, n.thin = nt, n.iter = ni, n.burnin =nb, model.file = "ipm.jags")

keybindings.json

{ "key": "ctrl+\\", "command": "workbench.action.splitEditorDown", },

workbench.action.splitEditorUp

workbench.action.splitEditorDown

workbench.action.splitEditorLeft