janeshdev

jd1 <- read.csv("datetime.csv")
## Then a new variable called timestamp will be added to the dataframe jd1. 
jd1 <- transform(jd1, timestamp=as.POSIXct(paste(Date,Time),format="%Y/%m/%d %H:%M"))

janeshdev

# GET EQUATION AND R-SQUARED AS STRING
# SOURCE: http://goo.gl/K4yh

lm_eqn = function(df){
    m = lm(y ~ x, df);
    eq <- substitute(italic(y) == a + b %.% italic(x)*","~~italic(r)^2~"="~r2, 
         list(a = format(coef(m)[1], digits = 2), 
              b = format(coef(m)[2], digits = 2), 
             r2 = format(summary(m)$r.squared, digits = 3)))
    as.character(as.expression(eq));                 

janeshdev

library(ggplot2)
library(grid)

# A viewport taking up a fraction of the plot area
vp <- viewport(width = 0.4, height = 0.4, x = 0.1, y = 0.9,just=c("left","top"))

b_plot <- ggplot(cars,aes(speed,dist))+geom_line()+xlim(10,15)
b_plot

janeshdev

 ## Let us assign a sample date as first with hours, minutes and seconds.
 ## It is also recommended to use the time zone
 
> date <- as.POSIXct("2013-06-14 16:34:26",tz="GMT")
 
## Convert to Julian date using the following function
> jddd <- julian(date, origin = as.POSIXct("2013-01-01 00:00:00",tz="GMT"))
> jddd
Time difference of 164.6906 days
 

janeshdev

\documentclass{beamer}
\usetheme{CambridgeUS}
\setbeamertemplate{items}[ball]
\usefonttheme[onlylarge]{structurebold}
\usecolortheme[RGB={205,173,0}]{structure} 
\setbeamerfont*{frametitle}{size=\normalsize,series=\bfseries}
\useoutertheme{infolines} 

%Pacakges
\usepackage{xcolor}

janeshdev

# Multiple plot function
#
# ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects)
# - cols:   Number of columns in layout
# - layout: A matrix specifying the layout. If present, 'cols' is ignored.
#
# If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
# then plot 1 will go in the upper left, 2 will go in the upper right, and
# 3 will go all the way across the bottom.
#

janeshdev

function [y,coef,window,Cx,Ff] = lanczosfilter(x,varargin)
%LANCZOSFILTER   Filters a time series via Lanczos method (cosine filter).  
%   [Y,coef,window,Cx,Ff] = LANCZOSFILTER(X,dT,Cf,M,pass) Filters the time
%   series via the Lanczos filter in the frequency space (FFT), where
%
%   INPUTS:
%      X    - Time series
%      dT   - Sampling interval       (default: 1)
%      Cf   - Cut-off frequency       (default: half Nyquist)
%      M    - Number of coefficients  (default: 100)

janeshdev

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

janeshdev

# A function to convert velocity xy EFDC file to velocity component file 
velxy_convert <- function(file){
    process_pp_template <- function(path) {
        # Read data using quicktoolsr function
        dat <- readts_EE(path)
        # Reshape the data from long format to wide format
        dat_mod <- dcast(dat, time ~ id)
        return(dat_mod)
    }
    # Read the file 

janeshdev

# Import files under folder name fawn 
# It is very important to include the option (full.names=TRUE). It it is not included 
# then you will get the error something like 
# "Error in file(file, "rt") : cannot open the connection In addition: Warning message:
#In file(file, "rt") : cannot open file 'FAWN_2002.csv': No such file or directory
 
mydata=ldply(list.files(path="data/fawn/",pattern="csv",full.names=TRUE),function(filename) {
    dum=read.csv(filename)
    dum$filename=filename
    return(dum)