Archive for the Running Category

incredible India

Posted in Kids, Mountains, pictures, Running, Travel with tags , , , , , , , , , , , , , , on January 15, 2017 by xi'an

[The following is a long and fairly naïve rant about India and its contradiction, without pretence at anything else than writing down some impressions from my last trip. JATP: Just another tourist post!]

Incredible India (or Incredible !ndia) is the slogan chosen by the Indian Ministry of Tourism to promote India. And it is indeed an incredible country, from its incredibly diverse landscapes [and not only the Himalayas!] and eco-systems, to its incredibly huge range of languages [although I found out during this trip that the differences between Urdu and Hindi are more communitarian and religious than linguistic, as they both derive from Hindustani, although the alphabets completely differ] and religions [a mixed blessing], to its incredibly rich history and culture, to its incredibly wide offer of local cuisines [as shown by the Bengali sample below, where the mustard seed fish cooked in banana leaves and the fried banana flowers are not visible!] and even wines [like Sula Vineyards, which offers a pretty nice Viognier]. Not to mention incredibly savoury teas from Darjeeling and Assam. Continue reading

Great North Road [book review]

Posted in Books, Running, Travel with tags , , , , , , , , , , , , , , , on January 6, 2017 by xi'an

As I was unsure of the Internet connections and of the more than likely delays I would face during my trip to India, I went fishing for a massive novel on Amazon and eventually ordered Peter Hamilton’s Great North Road, a 1088 pages behemoth! I fear the book qualifies as space opera, with the conventional load of planet invasions, incomprehensible and infinitely wise aliens, gateways for instantaneous space travels, and sentient biospheres. But the core of the story is very, very, Earth-bound, with a detective story taking place in a future Newcastle that is not so distant from now in many ways. (Or even from the past as the 2012 book did not forecast Brexit…) With an occurrence of the town moor where I went running a few years ago.

The book is mostly well-designed, with a plot gripping enough to keep me hooked for Indian evenings in Kolkata and most of the flight back. I actually finished it just before landing in Paris. There is no true depth in the story, though, and the science fiction part is rather lame: a very long part of the detective plot is spent on the hunt for a taxi by an army of detectives, a task one would think should be delegated to a machine-learning algorithm and solved in a nano-second or so. The themes heavily borrow from those of classics like Avatar, Speaker for the Dead, Hyperion [very much Hyperion!], Alien… And from The Girl with the Dragon Tattoo for an hardcore heroin who is perfect at anything she undertakes.  Furthermore, the Earth at the centre of this extended universe is very close to its present version, with English style taxis, pub culture, and a geopolitic structure of the World pretty much unchanged. Plus main brands identical to currents ones (Apple, BMW, &tc), to the point it sounds like sponsored links! And no clue of a major climate change despite the continued use of fuel engines. Nonetheless, an easy read when stuck in an airport or a plane seat for several hours.

more street art [jatp]

Posted in pictures, Running, Travel with tags , , , , , on December 31, 2016 by xi'an

wading thru fog [jatp]

Posted in pictures, Running, Travel with tags , , , , , , , , on December 30, 2016 by xi'an

বড়দিনের শুভেচ্ছা

Posted in Mountains, pictures, Running, Travel with tags , , , , , , , on December 25, 2016 by xi'an

বড়দিনের শুভেচ্ছা

கிறிஸ்துமஸ் வாழ்த்துக்கள்

क्रिसमस की बधाई

క్రిస్మస్ శుభాకాంక్షలు

ਕ੍ਰਿਸਮਸ ਸਲਾਮ

ક્રિસમસ શુભેચ્છાઓ

ക്രിസ്മസ് ആശംസകൾ

crossing the Seine

Posted in pictures, Running, Travel with tags , , , , , , , on December 16, 2016 by xi'an

puzzled by harmony [not!]

Posted in Books, Kids, Mountains, pictures, R, Running, Statistics, Travel with tags , , , , , on December 13, 2016 by xi'an

In answering yet another question on X validated about the numerical approximation of the marginal likelihood, I suggested using an harmonic mean estimate as a simple but worthless solution based on an MCMC posterior sample. This was on a toy example with a uniform prior on (0,π) and a “likelihood” equal to sin(θ) [really a toy problem!]. Simulating an MCMC chain by a random walk Metropolis-Hastings algorithm is straightforward, as is returning the harmonic mean of the sin(θ)’s.

f <- function(x){
    if ((0<x)&(x<pi)){
        return(sin(x))}else{
        return(0)}}

n = 2000 #number of iterations
sigma = 0.5
x = runif(1,0,pi) #initial x value
chain = fx = f(x)   
#generates an array of random x values from norm distribution
rands = rnorm(n,0, sigma) 
#Metropolis - Hastings algorithm
for (i in 2:n){
    can = x + rands[i]  #candidate for jump
    fcan=f(can)
    aprob = fcan/fx #acceptance probability
    if (runif(1) < aprob){
        x = can
        fx = fcan}
    chain=c(chain,fx)}
I = pi*length(chain)/sum(1/chain) #integral harmonic approximation

However, the outcome looks remarkably stable and close to the expected value 2/π, despite 1/sin(θ) having an infinite integral on (0,π). Meaning that the average of the 1/sin(θ)’s has no variance. Hence I wonder why this specific example does not lead to an unreliable output… But re-running the chain with a smaller scale σ starts producing values of sin(θ) regularly closer to zero, which leads to an estimate of I both farther away from 2 and much more variable. No miracle, in the end!