denis-bz

Introduction to Netherlands wind data with xarray

Keywords: Netherlands, wind, wind speed, KNMI, python, xarray, data-carpentry

Purpose: introduce Netherlands wind data from KNMI, the Royal Netherlands$ Meteorological Institute, with the steps:

download 2 \.nc files by hand, one day and one gridpoint
look at them in xarray

Windspeeds and windfarms in Bayern

Keywords: wind power, Germany, Bayern, globalwindatlas, GWA

Purpose: I'm trying to show my neighbors around Munich that windfarms make more sense where there's more wind. To this end, here's a map of GWA windspeeds at 150m, together with the sites of 202 windfarms in Bayern:

Poisson2 - 4 I: nice test matrices for linear solvers and eigensolvers

Purpose: a simple generator of test matrices for linear solvers and eigensolvers

Keywords: sparse-matrix, linear-solver, eigensolver, arpack, nullspace, python

poisson2( n ) below generates sparse $n^2 \ x \ n^2$ matrices $A$ with $A$ symmetric (aka Hermitian) and positive-definite; solving $A \ x = b$ is then relatively easy. $A_4 = A - 4 I$ is more interesting: there are $n$ vectors $z_i$

HUSL rgb_to_lch is for CIELuv, not CIELab

Keywords: color-space HUSL HSLuv CIELCh CIELuv CIELab max-chroma everyone-knows

_{Whenever something can be done in two ways, someone will be confused.}

There are two quite different color spaces: \

Windfarms in Germany from de.wikipedia

Keywords: wind power, Germany, python, globalwindatlas

Purpose: collect data on wind farms in Germany in a single .csv file, from https://de.wikipedia.org/wiki/Liste_von_Windkraftanlagen_in_Bayern etc.

The file windfarms-in-Germany.csv looks like this:

MW MW/Rad Nrad Year N E Land Lkr Typ Ort

Warping maps or images

Keywords: image raster resize rescale reproject Manhattan-grid regular-grid

We have a picture (image, raster) A, an array of colored pixels, and want to warp it to a new picture O of a different size or shape. Examples: Map projection, flat maps <-> globe; Image scaling.
There are hundreds of cases of these, and zillions of programs

rioxarray reproject UTM -> 4326 widens NaNs at the sides

Keywords: rioxarray, rasterio, reproject, geotiff, testcase

This plot shows that rioxarray reproject UTM -> 4326, middle -> right, widens NaNs at the sides:

Electricity in Germany from coal, wind etc.

Keywords: electricity, Germany, renewable, wind, python, pandas

Purpose: summarize data on electricity sources in Germany from the electricity market site smard.de:

total 502489 GWh  365 days, 2020-07-01 .. 2021-06-30:
                 GWh    %   GW

Braunkohle 96253.2 19.2 11.0

	#!/usr/bin/env python3
	""" Usage:
	python3 ssquery.py '(posdef == 1) & (1000 <= rows <= 20000)' posdef.csv
	reads http://sparse.tamu.edu/files/ssstats.csv
	queries it
	writes "posdef.csv" like

	# SuiteSparse posdef & (1000 <= rows <= 20000)
	id,group,name,rows,cols,nnz,real,bool,is2d3d,posdef,symm,nsymm,kind
	29156,Boeing,msc01050,1050,1050,26198,1,0,1,1,1.0,1.0,structural

	#!/usr/bin/env python3
	""" https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Daten/Fallzahlen_Kum_Tab.html .xlsx
	-> python pandas read_excel
	"""
	# sheets, from openpyxl --
	# 0 Erlaeuterungen 20 rows 1 cols
	# 1 Fälle-Todesfälle-gesamt 509 rows 16384 cols ?!
	# 2 BL_7-Tage-Fallzahlen (fixiert) 39 rows 396 cols
	# 3 BL_7-Tage-Inzidenz (fixiert) 21 rows 396 cols
	# 4 LK_7-Tage-Fallzahlen (fixiert) 419 rows 207 cols