Ignacio Borlaf-Mena

pytest pytest is an alternative to Python’s Unittest module that simplifies testing even further. pytest automatically recognises tests based on filenames and functions that start with test_, while unitte...

We have updated the section on pytest with many exciting use cases
* on command line options
* on generating markers
* and on parameterising exceptions
python-basics-tutorial.readthedocs.io/en/latest/te...
#Python #Testing #pytest

Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring - Scientific Data Scientific Data - Natural forests of the world – a 2020 baseline for deforestation and degradation monitoring

We can map the world's existing forests with incredible accuracy now, but clearly we cannot (or will not) stop them from disappearing at rapid rates almost everywhere. www.nature.com/articles/s41... 🌎

A table showing profit margins of major publishers. A snippet of text related to this table is below. 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.

A figure detailing the drain on researcher time. 1. The four-fold drain 1.2 Time The number of papers published each year is growing faster than the scientific workforce, with the number of papers per researcher almost doubling between 1996 and 2022 (Figure 1A). This reflects the fact that publishers’ commercial desire to publish (sell) more material has aligned well with the competitive prestige culture in which publications help secure jobs, grants, promotions, and awards. To the extent that this growth is driven by a pressure for profit, rather than scholarly imperatives, it distorts the way researchers spend their time. The publishing system depends on unpaid reviewer labour, estimated to be over 130 million unpaid hours annually in 2020 alone (9). Researchers have complained about the demands of peer-review for decades, but the scale of the problem is now worse, with editors reporting widespread difficulties recruiting reviewers. The growth in publications involves not only the authors’ time, but that of academic editors and reviewers who are dealing with so many review demands. Even more seriously, the imperative to produce ever more articles reshapes the nature of scientific inquiry. Evidence across multiple fields shows that more papers result in ‘ossification’, not new ideas (10). It may seem paradoxical that more papers can slow progress until one considers how it affects researchers’ time. While rewards remain tied to volume, prestige, and impact of publications, researchers will be nudged away from riskier, local, interdisciplinary, and long-term work. The result is a treadmill of constant activity with limited progress whereas core scholarly practices – such as reading, reflecting and engaging with others’ contributions – is de-prioritized. What looks like productivity often masks intellectual exhaustion built on a demoralizing, narrowing scientific vision.

A table of profit margins across industries. The section of text related to this table is below: 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.

The costs of inaction are plain: wasted public funds, lost researcher time, compromised scientific integrity and eroded public trust. Today, the system rewards commercial publishers first, and science second. Without bold action from the funders we risk continuing to pour resources into a system that prioritizes profit over the advancement of scientific knowledge.

We wrote the Strain on scientific publishing to highlight the problems of time & trust. With a fantastic group of co-authors, we present The Drain of Scientific Publishing:

a 🧵 1/n

Drain: arxiv.org/abs/2511.04820
Strain: direct.mit.edu/qss/article/...
Oligopoly: direct.mit.edu/qss/article/...

What is the most profitable industry in the world, this side of the law? Not oil, not IT, not pharma.

It's *scientific publishing*.

We call this the Drain of Scientific Publishing.

Paper: arxiv.org/abs/2511.04820
Background: doi.org/10.1162/qss_...

Thread @markhanson.fediscience.org.ap.brid.gy 👇

Slides for my @foss4gna.bsky.social NA talk, "Cloud-Native Geospatial Metadata with stac-geoparquet" are at www.gadom.ski/presentation...

I subtitled the talk "Practical STAC", because #stac-geoparquet was motivated by real-world problems found while managing large @stacspec.bsky.social systems

Tree size, neighbourhood composition and structure affect individual tree vitality of European beech following extreme drought The severe drought of 2018/19 caused widespread early discoloration, defoliation and tree mortality in European beech (Fagus sylvatica L.), although l…

Happy to see my second PhD paper published in Forest Ecology and Management 🎉
#lidar #Europeanbeech #forestry #treemortality
check it out: www.sciencedirect.com/science/arti...

We created an #OpenSource automated workflow for multi-temporal #lidar processing to map forest change at scale. Generate canopy height, cover & change products critical for monitoring #wildfire impacts and ecosystem dynamics. Code and example from #Kaibab forest #AZ at github.com/OpenForest4D...

Global, multi-scale standing deadwood segmentation in centimeter-scale aerial images. Important work by J. Möhring, @cmosig.bsky.social, T. Kattenborn et al. in detecting dead trees across biomes from high resolution aerial images. doi.org/10.1016/j.op...

marimo looks good, some kind of a targets in a python notebook

github.com/marimo-team/...

When publishing a paper about an R package, how do you ensure the source code is permanently stored? CRAN or GitHub does not grant long-term persistence. Is issuing a DOI via linking GitHub with Zenodo a good idea for R packages? Or are there better ways? Maybe @ropensci.org knows.

SNAP 13 is out
Improve SAR geolocation accuracy.
Support for the BIOMASS commissioning phase products and ECOSTRESS Collection 2, improved ICEYE reader, S3 reader and OLCI O2A harmonization. Plus: Naive-Bayes, new Spectral Indices and LERC support.
t.co/mOOnQ6obws

Conda ≠ PyPI: Why Conda Is More Than a Package Manager | conda.org Part 1 of the 'Conda Is Not PyPI' series—why conda is a multi-language user-space distribution, not just a Python package manager.

Conda ≠ PyPI

Conda isn’t just another Python package manager-it’s a multi-language, user-space distribution system.

In this 3-part series, we explore the fundamental differences between conda and PyPI.

Part 1 is live now 👇
conda.org/blog/conda-i...
#conda #packaging #python

Your first Python project in Positron - Posit This walkthrough guides users through setting up a Python project in the Positron data science IDE, detailing the creation of a virtual environment, use of Quarto for analysis, and final deployment to...

Python users: Get started with Positron, the next-gen data science IDE, using our new video by @sara-altman.bsky.social.

See how to: ✅ Set up virtual environments ✅ Run code in Quarto ✅ Use the Variables Pane ✅ Integrate Git & Posit Connect

Start your #Python workflow: posit.co/blog/first-p...

A photograph of two apes (mother holds her child) and three recolored versions of the same phtograph using three palettes of different quality.

🦧📉 Why are there colorful apes in my #dataviz workshops?

📸 The photo taken years ago by my friend Richard Strozynski has become a tradition in my client projects and courses.

I like to recolor it with different palettes to show how palette design affects perception.

Thread 👇

PHOREAU v1.0: a new process-based model to predict forest functioning, from tree ecophysiology to forest dynamics and biogeography Abstract. Climate change impacts forest functioning and dynamics, but large uncertainties remain regarding the interactions between species composition, demographic processes and environmental drivers...

📣So happy to share the PhorEau model, combining models of forest dynamics, plant water relations, and process-based SDM = linking ecophysiology, ecology & biogeography 🌳📈💻
gmd.copernicus.org/articles/18/...
➡️ from Tanguy Postic's PhD, with many perspectives to simulate forests under CC

🏆 Congrats to @ruxizotta.bsky.social for the Best Paper Award 2024 from the Faculty of Mathematics and Geoinformation!

🛰️Her VODCA v2 paper advances global vegetation monitoring using multi-sensor microwave data. 🌿
🔗 doi.org/10.5194/essd...

👏 A well-deserved recognition of this impactful work

Our paper on drought & riparian phenology is out in @globalchangebio.bsky.social, skillfully led by PhD candidate Rose Mohammadi! Upshot: #Drought pushes down water tables & shortens tree growing seasons by intermittent streams - and that response is visible from space #timeseries

A lidar point cloud along central California’s Big Sur coast displaying elevation, classification, return number, and intensity. The airborne lidar point cloud was collected in 2022 has a point density of 85 points/m2.

Ever wondered what #lidar point clouds reveal about forests? OpenForest4D’s new guide breaks down how elevation, return number, intensity, and classification describe forest structure.
openforest4d.org/lidar-point-...
#pointcloud #laserscanning #forestry #geospatial

uv is the best thing to happen to the Python ecosystem in a decade - Blog - Dr. Emily L. Hunt Released in 2024, uv is hands-down the best tool for managing Python installations and dependencies. Here's why.

uv makes installing and using Python *so* easy! It works on pretty much any computer and it's lightning fast. 🔭☄️ #astrocode

If you're still using conda, pyenv, or... basically any other tool, then I can *highly* recommend switching:

The recording of my presentation at the UTK Open Access Week is available on YouTube now: youtu.be/nBFAvvHiBmc

Title: Open Publishing in Action: Creating Interactive Books with Jupyter Book and MyST Markdown

GitHub Repo: lnkd.in/eR3NEYrx

#openaccess #jupyter #opensource

I’m seeing some misinformation about pseudo-random number generator best practices going around the internets. Let’s talk about why the pseudo-random number generator seed you use shouldn’t actually have any impact on your results and, consequently, you can choose whatever seed you damn well please.

Screenshot of the CRAN Task View "Anomaly Detection" at https://CRAN.R-project.org/view=AnomalyDetection

🚨 New CRAN Task View: Anomaly Detection
#rstats #anomalydetection

By Priyanga Dilini Talagala, Rob J. Hyndman @robjhyndman.com, Gaetano Romano

URL: cran.r-project.org/view=Anomaly...

A map of the southern United States, with pixels colored according to family mineralogy class from the detailed soil survey.

I needed something outside of politics for a few hours.

Adding family mineralogy classes (from Soil Taxonomy) to SoilWeb/STE in the next release. These are very broad groupings of soil minerals that can have profound effects on use/management.

kaolinitic (R), siliceous (G), smectitic (B):

just added the MEGA TERMINAL CHEAT SHEET from "The Secret Rules of the Terminal" to our list of posters at https://wizardzines.com/#posters

just added the MEGA TERMINAL CHEAT SHEET from "The Secret Rules of the Terminal" to our list of posters at wizardzines.com#posters

finally got some legs on this #GDAL #xarray backend:

github.com/mdsumner/gdx

in combination with the upcoming 'gdal mdim mosaic' this should be pretty fun

Qualpal: Qualitative Color Palettes for Everyone Larsson, J., (2025). Qualpal: Qualitative Color Palettes for Everyone. Journal of Open Source Software, 10(114), 8936, https://doi.org/10.21105/joss.08936

💡 Came across this nice tool today:

🎨 qualpal for algorithmically choosing maximally distinct colors under certain restrictions #dataviz

JOSS paper, online tool, R package #rstats

joss.theoj.org/papers/10.21...

📢 NEWS: Our data stores turn ARCO! #ECMWF has launched an #ARCO Data Lake for #CopernicusClimate and #CopernicusAtmosphere, optimised for cloud & AI, enabling faster, and more efficient access to key datasets. Read our article to learn more: climate.copernicus.eu/work-progres...

Amazon Mining Watch | Earth Genome digital product Amazon Mining Watch uses machine learning to map the scars of mining activities in the Amazonian countries.

Earth Index: Find Anything, Anywhere by Kwin Keuter @earthgenome.org

Near-real-time detection of ‘artisanal‘ gold mining in the Amazon: www.earthgenome.org/work/amazon-...

#NACIS2025

Creating Shaded Relief in Blender Welcome! This is the long-awaited text version of my Blender relief tutorial, following on the video series I did a few years back. If you’ve already seen the videos and are returning for a r…

Rosemary is the second presenter to reference tutorials by @danielhuffman.bsky.social

somethingaboutmaps.wordpress.com/2017/11/16/c...