#mpfr
Live, measured metrics for the hashtag #mpfr from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #mpfr
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-07-27 11:15 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-07-27 11:15 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-07-27 11:15 UTCEverything below is measured over the latest 6 public posts (spanning ~22087 hours).
Posting hours (UTC)
Languages: English (3) · German (2) · French (1)
Avg boosts / post: 5.8
Top of the latest posts
RE: https://social.numerique.gouv.fr/@ouvrirlascience/115649636066049327 We (the #MPFR team) are very proud to share the fact that GNU MPFR received a French open science award for free research software (Prix science ouverte du logiciel li
Does anyone know of a way to import a very high precision CSV file into R or another numerical language? I have some plain text data with floating points sometimes exceeding quad-precision decimal (34+ digits) which I'd like to work on usin
Recently found out about libraries like #mpfr and gmp. Going to have some fun implementing an arbitrary precision #FFT algorithm to help quantify the numerical error. Here is the absolute error (bad metric I know) between FFTW and a #dft al
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/mpfr