我的文件www夹中有一个静态PDF文件,我想链接到UI downloadButton().似乎服务器端downloadHandler需要content填充选项,并且用于反应性生成的输出.
我知道我可以tags$a('Download file.', href = 'foo.pdf')在UI端使用HTML标签链接到静态内容.
关于如何将两者放在一起的任何建议都会有所帮助.
我是Outlook VBA(Office 365版)的新手,我想要实现的是循环浏览文件夹中的所有电子邮件("收件箱"中的"abc@outlook.com")并移动主题与特定主题相匹配的电子邮件RegEx到另一个文件夹.
由于这是我第一次使用Outlook VBA,并且不熟悉其对象模型,因此我一直在努力拼凑出一个解决方案.
这是我到目前为止(我通过编写组件步骤的简单示例,然后构建最终的复合函数)来学习:
Sub RegExpMoveEmailToFolderSO()
Dim MyFolder As Outlook.Folder
Dim MyNS As NameSpace
Dim MyEmail As Outlook.MailItem
Dim MyItems As Outlook.Items
Dim CountMatches As Integer
Dim MySubject As String
Dim MyRegExp As RegExp
Dim MyDestinationFolder As Outlook.Folder
Set MyNS = Application.GetNamespace("MAPI")
Set MyFolder = MyNS.Folders("xyz@abc.com").Folders("Inbox")
Set MyDestinationFolder = MyNS.Folders("uvw@def.com").Folders("Inbox")
Set MyItems = MyFolder.Items
Set MyRegExp = New RegExp
CountMatches = 1
MyRegExp.Pattern = "(Reg).*(Exp)"
For Each Item In MyItems
MySubject = Item.Subject
If MyRegExp.Test(MySubject) Then
Item.Move MyDestinationFolder …我试图在我的facet_wrap情节中的前三个面板上得到一个阴影矩形.但是,当我geom_rect用于作业时,它会在每个面板上生成矩形.有没有办法只在前三个面板上选择性地获取矩形？
这是一些代码
dfTemp = data.frame(value = rnorm(100*4), variable = sort(rep(1:4, 100)),
date = rep(seq.Date(
from = as.Date('2011-01-01', format = '%Y-%m-%d'),
length.out = 100,
by = 'day'), 4))
ggplot(dfTemp) +
geom_rect(aes(xmin = as.Date('2011-02-01', format = '%Y-%m-%d'),
xmax = as.Date('2011-03-01', format = '%Y-%m-%d'),
ymin = -Inf,
ymax = Inf), alpha = 0.2, fill = 'grey') +
geom_line(aes(x = date, y = value, group = variable, color = factor(variable))) +
facet_wrap(~variable , scale = 'free', ncol = 1)
我正在尝试使用RMySQL,并且意外地创建了一个没有句柄的连接.
dbConnect(MySQL(), user = "foo", password = "bar")
connLocalDB = dbConnect(MySQL(), user = "foo", password = "bar")
请注意,第一次调用的返回不会分配给任何内容.现在,当我做一个时,dbListConnections(MySQL())我看到两个连接:
> dbListConnections(MySQL())
[[1]]
<MySQLConnection:0,0>
[[2]]
<MySQLConnection:0,1>
然后我尝试了这个:
> dbDisconnect(dbListConnections(MySQL())[[1]])
[1] TRUE
但是,我得到了这个:
> dbListConnections(MySQL())
[[1]]
Error in .local(dbObj, ...) :
internal error in RS_DBI_getConnection: corrupt connection handle
如何安全地终止未分配句柄的连接？
我想在调用中使用匿名函数summarize_each:
# how to use an anonymous function in dplyr
df_foo = data_frame(x = rnorm(100),
y = rnorm(100))
df_foo %>%
summarize_each(funs(function(bar) sum(bar/10)))
我将如何实现这一目标？显然,在使用它之前命名该函数是有效的.
在实施的数据科学(TM)整洁模型中modelr,使用列表列组织重采样数据:
library(modelr)
library(tidyverse)
# create the k-folds
df_heights_resampled = heights %>%
crossv_kfold(k = 10, id = "Resample ID")
可以为map列表列中的每个训练数据集建立模型,train并通过mapping到列表列来计算性能指标test.
如果需要使用多个模型,则需要对每个模型重复此操作.
# create a list of formulas
formulas_heights = formulas(
.response = ~ income,
model1 = ~ height + weight + marital + sex,
model2 = ~ height + weight + marital + sex + education
)
# fit each of the models in the list of …我正在尝试使用SciPy fmin_bfgs函数在Python中编写逻辑回归,但遇到了一些问题.我编写了逻辑(sigmoid)转换函数和成本函数的函数,并且这些函数工作正常(我使用了通过罐装软件找到的参数向量的优化值来测试函数,并且这些函数匹配).我不太确定我的渐变函数的实现,但它看起来很合理.
这是代码:
# purpose: logistic regression
import numpy as np
import scipy.optimize
# prepare the data
data = np.loadtxt('data.csv', delimiter=',', skiprows=1)
vY = data[:, 0]
mX = data[:, 1:]
intercept = np.ones(mX.shape[0]).reshape(mX.shape[0], 1)
mX = np.concatenate((intercept, mX), axis = 1)
iK = mX.shape[1]
iN = mX.shape[0]
# logistic transformation
def logit(mX, vBeta):
return((1/(1.0 + np.exp(-np.dot(mX, vBeta)))))
# test function call
vBeta0 = np.array([-.10296645, -.0332327, -.01209484, .44626211, .92554137, .53973828,
1.7993371, .7148045 ])
logit(mX, vBeta0)
# cost function
def logLikelihoodLogit(vBeta, …我将如何使用mutate(我的假设是我在我的情况下寻找标准评估,因此mutate_,但我对这一点并不完全有信心)当使用接受变量名称列表的函数时,例如:
createSum = function(data, variableNames) {
data %>%
mutate_(sumvar = interp(~ sum(var, na.rm = TRUE),
var = as.name(paste(as.character(variableNames), collapse =","))))
}
这是一个MWE,它将函数剥离到其核心逻辑并演示我想要实现的目标:
library(dplyr)
library(lazyeval)
# function to make random table with given column names
makeTable = function(colNames, sampleSize) {
liSample = lapply(colNames, function(week) {
sample = rnorm(sampleSize)
})
names(liSample) = as.character(colNames)
return(tbl_df(data.frame(liSample, check.names = FALSE)))
}
# create some sample data with the column name patterns required
weekDates = seq.Date(from = as.Date("2014-01-01"),
to = …我试图在我的R Markdown文档中排版引文,并且在某些情况下似乎没有正确解析引文,特别是当引文出现时带有a :,例如[@ref1]:跟随它的一些文本.
这是一个MWE:
---
title: Citations Parsing
references:
- id: fenner2012a
title: One-click science marketing
author:
- family: Fenner
given: Martin
container-title: Nature Materials
volume: 11
URL: 'http://dx.doi.org/10.1038/nmat3283'
DOI: 10.1038/nmat3283
issue: 4
publisher: Nature Publishing Group
page: 261-263
type: article-journal
issued:
year: 2012
month: 3
---
1. [@fenner2012a]: Here is some text. **This does not work.**
2. [@fenner2012a]:
3. [@fenner2012a] : Here is some text. **This works.**
我是rmarkdownCRAN(0.8.1)的最新版本.请注意,在上面的示例中,#2也可以.当你追逐:文本时,引文会停止渲染.
这也可能是一个knitr问题.我是来自CRAN(1.11)的最新版knitr.
我试图将一些actionButtons放在shinydashboard侧边栏中,并且需要将它们设置为在侧边栏中居中并在分配给它们的空间内水平分布.
这是一个MWE:
library(shiny)
library(shinydashboard)
foo_body = dashboardBody()
foo_header = dashboardHeader()
foo_sidebar = dashboardSidebar(
sidebarMenu(
menuItem(
"A Dashboard",
tabName = "tab_overview",
icon = icon("gamepad")
)
),
# add some buttons
actionButton(inputId = "button1", label = "B 1", icon = icon("paper-plane")),
actionButton(inputId = "button2", label = "B 2", icon = icon("paper-plane")),
actionButton(inputId = "button3", label = "B 3", icon = icon("paper-plane"))
)
foo_page = dashboardPage(
header = foo_header,
sidebar = foo_sidebar,
body = foo_body,
title = "A Dashboard" …