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import os | |
import shutil | |
import synapseclient | |
from synapseclient import Project, Folder, Entity, File | |
syn = synapseclient.login() | |
def download(entity, directory=None, verbose=False, indent=0): | |
""" |
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// Predict from Gaussian Process | |
// All data parameters must be passed as a list to the Stan call | |
// Based on original file from https://code.google.com/p/stan/source/browse/src/models/misc/gaussian-process/ | |
data { | |
int<lower=1> N1; | |
vector[N1] x1; | |
vector[N1] y1; | |
int<lower=1> N2; | |
vector[N2] x2; |
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vioplot2 <- function (x, ..., range = 1.5, h = NULL, ylim = NULL, names = NULL, | |
horizontal = FALSE, col = "magenta", border = "black", lty = 1, | |
lwd = 1, rectCol = "black", colMed = "white", pchMed = 19, | |
at, add = FALSE, wex = 1, drawRect = TRUE, side="both") | |
{ | |
datas <- list(x, ...) | |
n <- length(datas) | |
if (missing(at)) | |
at <- 1:n | |
upper <- vector(mode = "numeric", length = n) |