Saturday, May 1, 2021

Dash cam landscapes - 2

I was surprised when I discovered the dashboard camera pictures. I could not believe that these fleeting moments were recorded. I could not believe that these moments of tragedy had been fixed and then shared in public.
It is terrifying that I will never know the aftermath of these accidents. I don't know if they were deadly, if people were wounded or if they just caused material damage. We see the moving life before and a still life after. We are shocked by the difference.
This can happen to all of us. It need not be a car accident, it can be any act of fate. We see speed and then we see the end of speed. We see the tumbling, we see the rolling, we see how it comes to rest and then we see the sky. Do we look through living or through dead eyes? Is this the final picture or just a cliffhanger? Why don't we see big letters spelling out: "T H E   E N D" ?
We see a normal situation. Was this normal situation restored or was it been destroyed forever?
We look at a road, somewhere far away, somewhere nowhere. We see the dry giant hogweed and then we see the stalks being mowed down.
Normally we would not care about this place, but now it is special. The place is transformed by spectacle. Would it be worth to come here and investigate? To sit in silence and awe.
Impossible to tell, but in the meantime we can admire the poetry of the situation like a surrealist painting. We stare, think and puzzle.
There is that one tree. It is worth looking at. 
It is like a modern artwork. (Wolfgang Tillmans, Lighter 33, 2007)
The road runs through the landscape and there are strange objects along the route. (SoiL Thornton, So Warm Out, That's A Lot Of Sea Weed Chips, 2014)

Tuesday, April 27, 2021

From a strange planet - 33

There are traffic cams in the Netherlands too. But there are only 26 of them and they are much less interesting than the Norwegian traffic cams. But during snowfall they present a nice, gray, flat landscape. At night they present a futuristic cityscape. The cameras are not fixed, so you almost never get the same landscape twice.

In the night they present a futuristic cityscape that escaped from a cyberpunk movie. Only if the cars could fly!
Sometimes you even catch a detailed view of somewhere:

Friday, April 9, 2021

Dash cam landscapes

There was a time when I watched Russian dash cam videos.
Many of them ending in horrible accidents.
The tumbling car would come to rest and I would see a small place in great detail.
In silence.

That I - in the Netherlands - would see that one tree, that specific blade of grass, that lonely roadside weed. They were recorded, they will not be forgotten.

I feel the earth move - I feel the tumbling down - the tumbling down.
(Philip Glass - Einstein on the beach)

I searched the internet at random for other fitting comments. 
I have no talent for good texts, but I can search for them. This is what I found:

We drove approximately 400 km by automobile from Chelyabinsk through Stepnoie to the Arkaim and recorded vegetation structure at random by visual observation along major traffic roads running with automobile approximately 10 km in distance.
The types of vegetation depended mainly on physiognomy with relatively smaller scale approximately some hundreds square meters: Pinus forest, Betula forest, cultivated land and pasture.
Plots along the major roads were randomly selected to cover representative vegetation pattern. Further, around the Arkaim, major vegetation types ware described. Field observations were carried out during early summer season, middle June in 2008.
This theory is contradicted by the 12 hours I spent yesterday watching Russian car dash-cams on YouTube. The russian car inventory must turnover at least every 6 months. Literally and figuratively. (3 stars or bust)
There’s a deeper point here: if your view of Russian life is conditioned by what is available on YouTube, you’e asking for a pretty skewed view of the country. The people who post dash-cam videos are, by definition, those who have cars, dash-cams, and internet connections. Faberge eggs are very pretty, but they say relatively little about per capita wealth in Russia on the eve of the revolution. (Ckb)
As we approached the city, we saw:
  • a billboard advertising a concert,
  • large signs on top of the buildings near the railway,
  • the cathedral on the hill,
  • the towers rising from the horizon gleaming in the sun,
  • the skyscrapers thrusting, soaring, sitting above the rest,
  • a crowd in front of the showroom near the highway,
  • more and more people along the way,
  • very ominous dark clouds in the sky,
  • orchards and orchards,
  • the high and snow capped peaks.
She proposes that the brains of all six species have gotten bigger because humans have radically changed the landscape. Where there were once pristine forests and prairies, there are now cities and farms. In this disrupted environment, animals better at learning new things were more likely to survive and have offspring.

The video:
Dash cams:
Landscape flora and fauna:
Vegetation landscape around the Arkaim eco-preserve, southeastern Ural, Russia
NYtimes - as-humans-change-landscape-brains-of-some-animals-change-too
Dash-cam comments:
Found poetry:
Bing search for "as we approached the city"

Sunday, April 4, 2021

Beta distribution - learning statistics with Python


So I'm reading this nice book on Bayesian statistics:

I'm in the chapter on the Beta distribution, and things start to get new and difficult for me:

So I follow the advice of Nassim Taleb and start playing around with some Python code. I'm not a rich guy like Taleb, so I don't have Mathematica. And this is too complex to do for free in Wolfram Alpha.

I copy and paste a crappy Python program and things become wonderfully intuitive.

Sampling and the beta function

I make an urn with 1000 good balls and 9000 bad balls.
I draw 5 samples from the urn.
I make a histogram and the corresponding probability distribution.
Then I plot the beta function for each draw. This shows the distributions that were most likely to produce this draw.
With increasing sample size both the histograms and the beta functions converge to 0.1. (Duh!)

Sample size 10:
Sample size 100:
Sample size 400:

Is 400 enough?

Many years ago I read this excellent book:

It says that a sample of 400 is sufficient in most situations. For the hypergeometric distribution that we draw from this seems to be the case. Going to 1000 samples does not seem to add that much certainty anymore.
The crappy Python code

import numpy
import matplotlib.pyplot
from matplotlib.pyplot import hist
import seaborn
from scipy.stats import beta

ngood, nbad, sample, runs = 1000, 9000, 1000, 5
samples = numpy.random.hypergeometric(ngood, nbad, sample, runs)


# Generate the value between 
x = numpy.linspace(0,1, num=400)

# Plot the beta distribution

matplotlib.pyplot.xlim(0, 1)
for s in samples:
    matplotlib.pyplot.plot(x, beta.pdf(x, s, sample-s), 'r-')

matplotlib.pyplot.title("Beta: " + str(sample) +
                        " samples from " + str(ngood) +
                        " good " + str(nbad) + " bad" +
                        "\n" + str(samples))
matplotlib.pyplot.xlabel('Values of Beta Dist.')

Friday, April 2, 2021

From a strange planet - 22

This time we don't take a road trip along many webcams. Instead we take a detailed look at  Fv296 Filefjell v/Varden and its surroundings. We use many open sources but mainly Google Street View.
We see three objects: 1) an electricity pylon, 2) a container and 3) a sign with a ladder. It's a mountainous terrain with sparse bushes. The rest is hidden in white mist. It looks empty and far away from everything.
But it's not that deserted if we look at a topographical map. There are many clusters of houses, inhabited and accessible by road.
On the satellite picture it doesn't look neglected. But it does look inhospitable to vegetation. Bushes, grass, nothing has an easy foothold here.
Winter is always present, 
even in summer the landscape looks sparse and transparent.
Snow remains in the background.
And very deserted and mountainous. Google Streetview
This is the kind of landscape I dream about.
A small hut with a porch, from where I can see the mountain every day.
Far away and in solitude.
But there is no real solitude here.
The garbage container is a sign of life.
Local people make pilgrimages to it.
They don't make pilgrimages to the sign.
I've never seen someone climb that ladder.
I've never seen anyone just looking at the sign.
But it's beautiful, like a modern Stonehenge sigil.
People do walk here.
And they walk their dogs.
But they don't notice the sign.
At night mysterious lights appear.
Sleeping houses come awake.
I sit on the porch of my simple hut,
and wait for the lights to come on.
For just 134.231 Euro I could buy an appartment in the neighborhood.
It would be far from the shopping centre.