tompaton

#!/usr/bin/env python

# kd-tree index and nearest neighbour search
# includes doctests, run with: python -m doctest kdtree.py

class KDTree(object):
    """
    kd-tree spatial index and nearest neighbour search
    http://en.wikipedia.org/wiki/Kd-tree
    """

aaugustin

from django.contrib import admin


class ReadOnlyModelAdmin(admin.ModelAdmin):
    """
    ModelAdmin class that prevents modifications through the admin.

    The changelist and the detail view work, but a 403 is returned
    if one actually tries to edit an object.

xccds

\documentclass[UTF8,10pt]{ctexart}
\usepackage[a4paper,%%textwidth=129mm,textheight=185mm,  %%193-8
text={160mm,260mm},centering]{geometry}
\pagestyle{empty}
\begin{document}
\title{用散点图示范ggplot2的核心概念}
\author{肖凯}
\maketitle
\abstract{
本文稿是第五届R语言会议演讲内容的一部分，试图用散点图示例来说明ggplot2包的核心概念，以方便初学者快速上手。同时这也是笔者应用knitr包的一个练习。该示例所用数据是ggplot2包内带的mpg数据集。}

suziewong

github的多人协作

1. github上你可以用别人的现成的代码 直接 git clone 即可了

2. 然后你也想改代码或者贡献代码咋办？

Fork

gsee

set.seed(42)
dat <- rnorm(1)
shinyServer(function(input, output) {  
  fetchData <- reactive(function() {
    invalidateLater(1000)
    qt <- rnorm(1)
    dat <<- c(dat, qt)
    dat
  })
  output$plot_dat <- reactivePlot(function() { plot(fetchData(), type='l') })

jrnold

library(KFAS)
library(rstan)
data(GlobalTemp)

model_dlm1a <- stan_model("../stan/dlm1a.stan")

y <- as.matrix(GlobalTemp)
data <-
    within(list(),
       {

ramnathv

---
title: Slidify Playground
subtitle: Adapted from OpenCPU MarkdownApp
author: Ramnath Vaidyanathan
framework: io2012
widgets: [mathjax]
---

## Normal Distribution

withr

library(shiny)
library(datasets)
Logged = FALSE;
PASSWORD <- data.frame(Brukernavn = "withr", Passord = "25d55ad283aa400af464c76d713c07ad")
# Define server logic required to summarize and view the selected dataset
shinyServer(function(input, output) {
  source("www/Login.R",  local = TRUE)
  
  observe({
    if (USER$Logged == TRUE) {

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

thertrader

This Shiny application is designed to help analysing trading strategies. It is an ongoing project that I improve when time allows. Feel free to get in touch should you have any suggestion.

*How to use the App as it is?
The App uses as input several csv files (one for each strategy). Each file has two columns: date and daily return. There is an example of such a file in the Github repository. The code is essentially made of 3 files.
-ui.R: controls the layout and appearance of the app
-server.R: contains the instructions needed to build the app. You can load as much strategies as you want as long as the corresponding csv file has the right format (see below).
-shinyStrategyGeneral.R: loads the required packages and launches the app
put ui.R and server.R file in a separate directory

In the server.R file change the inputPath, inputFile and keepColumns parameters to match your setting. The first two are self explanatory the third one is a list of column names within the csv file. Keep only date and daily return