#scipy — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #scipy, aggregated by home.social.
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The call for proposals for the SciPy India 2026 Conference is open!
We are looking for 30-minute talks, 3-hour hands-on workshops, and posters on scientific computing and research software, across eight exciting tracks. First-time speakers are warmly welcomed.
Conference: 19th–20th December 2026, IIT Madras, Chennai
CFP closes: 19th October 2026, 23:59 IST -
The passagemath-10.10.x series follows the #SciPy toolchain roadmap in dropping support for GCC 9, requiring GCC 10.3 or newer.
github.com/passagemath/...
#Python #SageMath #OpenSource #Mathematics
RE: https://bsky.app/profile/did:plc:htd5nd5zj62hey7e7lm3a6ky/post/3ms2hl5dxg22d
Release passagemath-10.10.1.al... -
Все, что нужно знать про построение точечных оценок
Что происходит под капотом, когда вы вызываете scipy.stats.norm.fit() ? В статье рассматриваются два классических подхода точечного оценивания параметров — метод моментов и метод максимального правдоподобия — с математическими выводами, экспериментами на Python и визуализацией. Читать статью
https://habr.com/ru/articles/1061846/
#точечные_оценки #метод_моментов #метод_максимального_правдоподобия #математическая_статистика #MLE #python #scipy #data_science
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Scipy: "Fundamental algorithms for scientific computing in Python".
scipy.orgI do not know how to use it but who has will.
(It is open source)
#scipy #opensource #usefulweb #algorithm #python #py #programming #tool
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Ускоряем и оптимизируем numpy, pandas, scipy и sklearn
С момента публикации статьи на Хабре « Импортозамещаем numpy, pandas, scipy и sklearn » прошло почти три года. В течение этого времени я приостановил работу над проектом из-за нехватки времени, ресурсов и сил. К тому же, меня расстроило, что не смог выполнить просьбу пользователя @N-Cube , который активно интересовался моей библиотекой и хотел ускорить работу своего Jupyter Notebook. В самый критический момент на помощь пришел волшебный AI, который, хоть и иногда проявлял недостаток гибкости, с готовностью исполнял все пожелания своего хозяина. Благодаря этому проект начал продвигаться вперед. За это время в библиотеки были добавлены поддержка CUDA, множество ручных SIMD-оптимизаций с динамическим выбором SIMD, несколько реализаций линейной регрессии и многое другое. Давайте рассмотрим, что на сегодняшний день позволяет сделать моя библиотека. Я представлю несколько тестовых примеров в двух вариантах: с использованием AVX-2 на процессоре Intel® Core™ i7-4790K и AVX-512 на Intel® Xeon. Также покажу результаты замеров для каждого из них. Все тесты проводились без использования GPU, исключительно на процессоре. Это позволяет сравнивать производительность Python и моей библиотеки на равных условиях. Операционная система – Ubuntu 24.04, компилятор – GNU 13.3.0.
https://habr.com/ru/articles/1039866/
#C++ #numpy #pandas #scipy #sklearn #opensource #datascience #data_analysis
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- statistical distributions in #scipy are great too. I even used a scaled-shifted beta-prime distribution a few weeks ago! (???) (Still #julialang :julia: Distributions.jl is my fave)
- #cmdstanpy works exactly as expected (which is great) but the post-processing of mcmc draws is a bit more cumbersome in Python than in R in my opinion (arviz in Python vs posterior in R) although this might again be matplotlib vs ggplot (did I mention I am not a matplotlib fan?)4/n
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That's a wrap, #PyConUS! I loved all the conversational talks, documentation writing, and PRS this week. Looking forward to following up with many of you and more collaborations in the future!
If you missed the #python dashboarding tutorial using Shiny, I have all my materials here: https://chendaniely.github.io/pycon-2026-shiny/
If you missed it, hopefully I'll catch you at #SciPy in July!
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#scipy minimal spanning tree
The sketch-a-day archives and tip jar are at: https://abav.lugaralgum.com/sketch-a-day Code for this: https://github.com/villares/sketch-a-day/tree/main/2026/sketch_2026_03_20 #Processing #Python #py5 #CreativeCoding -
@rzeta0 my friend, what do you think about the code using np.roll() (in the linked sketch)?
I'm afraid it would be a bit hard to explain on a short class. So I'll use the simpler inefficient function...
The next big step in efficiency would be using #scipy I think:
def count_live_neighbors(status):
"""Counts the number of neighboring live cells"""
kernel = np.array([
[1, 1, 1],
[1, 0, 1],
[1, 1, 1]
])
return scipy.signal.convolve2d(status, kernel, mode='same', boundary="wrap") -
I love this logo for the upcoming #SciPy (#Scientific #Python) conference coming up this summer in #Minneapolis #Minnesota
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Hi all,
Hope you're fine and safe
An important #announcement about #tyssue , a Python modeling library :
https://github.com/DamCB/tyssue/blob/main/README.md
Please 🔁 this message to reach the few and far apart people that might be impacted :pray:
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#scipy #TSP #genuary #genuary20 @genuary2026
Find the sketch-a-day archives and tip jar at: https://abav.lugaralgum.com/sketch-a-day
Code for this sketch at: https://github.com/villares/sketch-a-day/tree/main/2026/sketch_2026_01_20 #Processing #Python #py5 #CreativeCoding -
CW: Advent of Code 2025 Day 10 Spoilers
Today I "cheated" and used scipy's MILP solver for Part 2. Discretion is the better part of valor, as they say, and writing a constraint solver by hand is not what I had planned for this Wednesday morning. The existence of `uv` to deal with all the dependencies makes reaching for scipy for even little scripts like this an easy choice.
Part 1 was trivial. Treat the lights and the buttons as bitmasks and recognize that buttons XOR themselves so they're pressed at most 1 time each. Generate the smallest combination of buttons that XOR to the target.
Part 2 is probably solvable via something like DFS before the heat death of the universe, but it would take way too long. Instead, I used scipy's integer linear programming solver, defined the constraints, objective, and bounds, and let it do its thing.
https://github.com/biesnecker/aoc-anyhow/blob/main/202510.py
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Книга «Python для инженерных задач»
Приветствуем, коллеги. Расскажем вам о нашей долгожданной новинке – «
https://habr.com/ru/companies/bhv_publishing/articles/973246/
#Python #самоучитель #математика #инженерия #matplotlib #numpy #scipy #pandas #книги_по_программированию
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The #Volcanic Isles . A brief history of volcanism across The British Isles.
Quite pleased with how this one turned out.
Location of volcanoes taken from wikipedia (spotted a mistake and got to make an edit to wikipedia in the process); fault lines from the #BGS 625k bedrock dataset and the IE GSI 500k Bedrock Geology for Ireland. Font: League-Spartan by the League of Moveable Type.
#requests, #pandas and #geopandas for scraping and wrangling.#scipy for making the proximity surface (that's the colour scheme), #matplotlib for plotting. With all labeling done manually in #inkscape.
EDIT: I've been kindly and helpfully informed that (a) Ben Nevis' age is closer to 399 Ma; (b) some are missing; (c) others perhaps shouldn't be there; (d) it's complicated. So, maybe don't use this map to make any strategic decisions.
#volcanism #volcano #imNotExtinctImDormant #magma #geology #faultlines
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Все об устройстве Q65 с примерами на Python (часть 1)
Q65 — цифровой протокол, разработанный Джо Тейлором (K1JT) и его командой в 2021 году для проведения минимальных связей в условиях сложных трасс прохождения радиосигнала, в том числе для проведения связи через отражение сигнала от Луны, где сигналы не только очень сильно ослабевают, но и имеют Доплеровский разброс. В этой статье будут рассмотрены подробности работы протокола. Статья может быть интересна радиолюбителям, как знакомым, так и не знакомым с Q65, а также тем, кто хочет понять устройство этого протокола.
https://habr.com/ru/articles/965862/
#ham #hamradio #numpy #scipy #python #python3 #LDPC #QRA #GF #Q65
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Making Math Less Stressful with a Python Super-Calculator https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #WolframMathematica #datavisualization #SoftwareHacks #matplotlib #Seaborn #Pandas #python #maple #numpy #scipy #SymPy
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Making Math Less Stressful with a Python Super-Calculator - In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-l... - https://hackaday.com/2025/10/26/making-math-less-stressful-with-a-python-super-calculator/ #wolframmathematica #datavisualization #softwarehacks #matplotlib #seaborn #pandas #python #maple #numpy #scipy #sympy
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@hisold Citing a plain website or GitHub repo is kinda unprofessional. Many widespead software packages have a publication that is well citable, e.g. #sympy has this one with a proper DOI: https://doi.org/10.7717/peerj-cs.103, same for #numpy, #scipy, #matplotlib, etc. Some have at least a #Zenodo entry (with a DOI) to be properly citable. #PlatformIO apparently has none of those.
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I like to do math, small prototypes and other experimenting with Python in Jupyter notebooks. NumPy, SciPy, SymPy and Matplotlib have been very handy.
But recently Python was too slow for what I was doing and I had trouble juggling Numpy arrays like I often have (it is required for speed). I know some #Rust so I decided to give #evcxr a go because it has a Jupyter kernel. And omg, I wasn't disappointed! It was mindbogglingly fast compared to what I'm used to and it also made the hard part of my code way easier to get right.
However, I only needed math functions provided by std this time. Now I'm trying to figure out if there are science Rust libs that are convenient enough to replace most Python in my notebooks. I know it's a fragmented space, but maybe one could already gather a comprehensive collection of crates manually.
Any recommendations?
