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Tomorrows Solar Eclipse from Beirut

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I have stumbled upon several posts and discussions on social networks, and some have contacted me about whether the eclipse is visible from Lebanon or not and about the timing.
I am writing this post to address some of your confusions. Here’s a general video from NASA’s Jet Propulsion Lab to start with:

Following is a visualization of the eclipse. The greatest eclipse (totality) occurs above the Faroe Islands, halfway between Norway and Iceland, around 1200 hours Beirut time.
In the visualization below, the strip formed by the two blue curves within which the greatest eclipse occurs is the path of totality. This is the path the shadow due to the moon blocking the Sun’s light from us follows. The further on Earth the observer is from this path the smaller the percentage of the eclipse is observed. Read on for more details.

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Rscript to customize the R environment

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A while ago I published a post on how to install some basic packages in R. This post goes further by sharing with you an Rscript (as part of another Ubuntu customization script) to install many popular R packages.

I’ve written the Rscript to be run after a fresh installation of Ubuntu. The Rscript is called by the Ubuntu customization script (yet to be published) and should install some basic and popular R packages.

Below is a Gist. For the repo click here.


####################################
## R environment customization script
# to automate package installation
# repo is maintained at http://bit.ly/r-customize-script
####################################
## To run execute in a terminal:
# Rscript r-customize.R # depends on R being installed
####################################
## Some relevant links
# Rstudio's Quick list of useful R packages: http://bit.ly/useful_R_packages
####################################
## Basic packages
#################
install.packages("devtools")
library(devtools) # to install from source (eg; github)
install.packages("downloader")
install.packages("checkpoint")
install.packages("rJava")
install.packages("xlsxjars")
install.packages("xlsx")
install.packages("data.table")
install.packages(c("Hmisc", "jpeg"))
install.packages("RJSONIO") # also required for "WDI"
# DataTables see: https://rstudio.github.io/DT/
# installs an R interface to the Js DataTables
# will ask to select a server
if (!requireNamespace('htmlwidgets') || packageVersion('htmlwidgets') <= '0.3.2')
install_github('ramnathv/htmlwidgets')
install_github('rstudio/DT')
install.packages("xtable")
# Web scraping
##############
install.packages("XML") # read & create XML docs
install.packages("rvest") # XML & httr wrappers to make it easy to download & manipulate html & xml.
install.packages(c("httr", "rjson")) # required for "Rfacebook"
install.packages("jsonlite")
install.packages("RCurl")
## Data Wrangling
#################
install.packages(c("dplyr", "reshape2"))
install.packages("tidyr")
install.packages("sqldf") # Manipulate R data frames using SQ
## Swirl
# Learn R, in R. http://swirlstats.com
install.packages("swirl")
# install_github("swirldev/swirl") # latest development version
# Visualization
###############
install.packages("ggplot2")
install.packages("ggvis")
install.packages("gridExtra")
# R interface to dygraphs
if (!requireNamespace('htmlwidgets'))
install_github('ramnathv/htmlwidgets')
install_github('rstudio/dygraphs')
# Shiny Apps
install_github('rstudio/shinyapps')
# download("https://github.com/rstudio/shinyapps/archive/master.tar.gz&quot;, "shinyapps.tar.gz")
# install.packages("shinyapps.tar.gz", repos = NULL, type = "source")
# Plotly
install_github("ropensci/plotly")
# download("https://github.com/ropensci/plotly/archive/master.tar.gz&quot;, "plotly.tar.gz")
# install.packages("plotly.tar.gz", repos = NULL, type = "source")
install.packages("maptools") # for shapefiles
# install.packages("rgeos") # required by maptools
# rMaps (still under development) # https://rmaps.github.io/
# rCharts required for some (experimental) features
if (!requireNamespace('rCharts'))
install_github('ramnathv/rCharts@dev')
install_github('ramnathv/rMaps')
# Google Vis
install.packages("googleVis")
## Leaftlet
# R package to create interactive web-maps based on the Leaflet JavaScript library
install.packages("leafletR")
# install_github("chgrl/leafletR")
install_github("rstudio/leaflet") # by Rstudio
# Documents
###########
# for Knitr
install.packages("yaml"); install.packages("htmltools"); install.packages("rmarkdown")
# Slidify & Libraries
install_github('ramnathv/slidify')
install_github('ramnathv/slidifyLibraries')
# Spatial & GIS
###############
install.packages("sp") # classes and methods for spatial data
install.packages("maptools") # Tools for Reading and Handling Spatial Objects
install.packages("maps") # Draw Geographical Maps
install.packages("ggmap") # Spatial Visualization with Google Maps and OpenStreetMap
install.packages("raster")
install.packages("mapdata")
install.packages("mapproj")
install.packages("gpclib")
install.packages("rdgal")
install.packages("Rgooglemaps")
install.packages("rgeos")
install.packages("rasterVis")
# Connections
#############
# API's
install.packages("streamR") # Access to Twitter Streaming API via R # github: https://github.com/pablobarbera/streamR
install.packages("Rfacebook") # provides an interface to the Facebook API
# Connect to Databases
install.packages("DBI") # database interface (DBI) definition for communication between R and relational database management systems
install.packages("RMySQL") # DBI-compliant Interface to MySQL and MariaDB Databases
install.packages("dbConnect") # Provides a graphical user interface to connect with databases that use MySQL
# Data scources
install.packages("Quandl")
install.packages("WDI") #github.com/vincentarelbundock/WDI
# Big Data
##########
# Packages to deal with datasets larger than RAM
install.packages("bigmemory") # Manage massive matrices with shared memory and memory-mapped files
# Medical packages
install.packages("oro.dicom")
# Machine Learning & Predictive Modeling
########################################
## caret – Classification And REgression Training
install.packages("caret")
install.packages("e1071") # needed when fitting a model in caret

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r-customize.R

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Banque du Liban (BDL) Accelerate 2014 – First Startup Conference in Lebanon

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Banque du Liban (BDL), or the Central Bank Of Lebanon, is organizing the first international startup conference in Beirut, Lebanon. The conference is known by “Banque du Liban Accelerate 2014”. Accelerate 2014 will be a melting point for entrepreneurs, startup companies, investors, and a select of highly prolific and successful people including ambassadors, ministers, industry leaders and professionals. And there will be fifty speakers (see below) who are mostly successful entrepreneurs and startup founders.

It is an invitation-only conference whose theme was chosen to be Blueprints for Success. BDL is aiming that the conference be a building block that supports current and new startups in Lebanon and help to accelerate their development and success, hence the “Accelerate” name and the theme “Blueprints for Success”.

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Lebanese start to face unprecedented water problems

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Water shortages due to low precipitation levels and lack of nation-wide water management

Lebanon has long been a country abundant in water and as such most Lebanese have taken water for granted thinking that they will never have a shortage in or problems with it.

It was apparent that this year has had very little rain [1,2]. Indeed the numbers indicate that the precipitation levels have not even reached half the average annual of 900 ml. This, of course, has led to a huge deficiency in water reserves [3,4]. But the main problem does not lie in the low precipitation levels this year rather it lies in the incompetence of the Lebanese authorities “and most Lebanese” to manage and conserve water.

On one hand, the authorities have not been doing their job of investing in the main source of life by managing the water (and sewage as a matter of fact; see below on this) in order to effectively exploit it and not waste it. They have not been working on conserving this abundance in water by preventing leakage, building dams, replenishing underground reservoirs, introducing artificial ponds, or dealing with the r
andom wells being dug and un-licensed water suppliers.

This is demonstrated in what Claude Tabbal, an expert on the water resources in Lebanon, said to Azza el-Masri and Raed Khalil of the Al-Akhbar newspaper [4] on June 26:

”We get 800 cubic meters of water per year, but up to 65 percent of it is lost each year”

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Quantum Harmonic Oscillator: Power series method in Maple

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In the previous blog post What is Computational Physics (Science)?, I ended the post with the following figure

Graph of the probability distribution of the 100th state of the quantum
harmonic oscillator (generated using the power series method).

and stated that I might write a post on how to solve the Quantum harmonic oscillator numerically using the power series method (the other method being the ladder operator method [1]) and generate that figure. This post is just about that.

Ok. First I need to clear the cache with the restart command, import the PDEtools (to solve the pde SE) and Maplets[Elements] (necessary if you want to generate a maplet with a slider) packages.

restart;
with(PDEtools): #we need to use the dchange command later in the solution
with(Maplets[Elements]):