My SSH key-based authorization kept failing on a private GitHub repo on a remote machine, even though my SSH keys for that machine were properly registered on the GitHub account. The solution was to force the “git” protocol instead of “http”. That is, instead of: url = https://github.com/accountname/reponame.git use: url = email@example.com:accountname/reponame.git in your “.git/config: [core] repositoryformatversion = 0 filemode = true bare = false logallrefupdates = true [remote "origin"] url = git@github.
This one’s simple. Just disable the GUI and solve two problems at once. ./configure --without-tcltk \ --prefix=$HOME/Environment/local \ && make && make install
In contrast to the simple single-line nicely-behaved “git submodule add” command, removing a submodule requires you to: $ git submodule deinit -- path/to/submodule $ rm -rf .git/modules/path/to/submodule $ git rm -f path/to/submodule $ git commit -a -m "Remove submodule" Apart from the multiple steps with “rm -rf freely being tossed around willy-nilly, note the second command where you manually fiddle with the guts of the repository structure. That does not get propagated up to any remotes in a push or any repos that pull from you or a shared remote.
TL;DR: Just look at the Gist. Summary: Act I, in which I try and fail. Act II, in which I think I succeed but actually failed without knowing it till I tried to use it. Act III, in which I return to my beginning, ponder the universe, dive deep into the depths of the abyss, and come back with the magic bean that makes everything work.
Whales are all large by any measure, but one group of them in particular, the baleen whales (Mysticeti), are especially large, and, interestingly, this group only became really big relatively recently. Why did they get so big? Ed Yong (on Twitter) writes about the rise of these majestic giants in a series of great articles here and here, based on two separate yet related studies by Slater et al. and Gearty et al.
For the sake of future me, I am recording this here, the coolest shell trick I’ve learned this year: (Linux): tar cf - /folder-with-big-files -P | pv -s $(du -sb /folder-with-big-files | awk '') | gzip > big-files.tar.gz (OSX): tar cf - /folder-with-big-files -P | pv -s $(($(du -sk /folder-with-big-files | awk '') * 1024)) | gzip > big-files.tar.gz with output looking like: 4.69GB 0:04:50 [16.3MB/s] [==========================> ] 78% ETA 0:01:21 Requires ‘pv’: https://github.
I. "Have Any of These People Ever Been to a Chinese Restaurant?" The Dirichlet process is a stochastic process that can be used to partition a set of elements into a set of subsets. In biological modeling, it is commonly used to assign elements into groups, such as molecular sequence sites into distinct rate categories. Very often, an intuitive explanation as to how it works invokes the "Chinese Restaurant Process"
R doing what R does really, really, really, really, really, really, *R*eally well: visualization. Folks, this might be THE plot to use to visualize distributions of discrete/categorical variables or simultaneous distributions of multiple continuous variables, replacing or at least taking up a seat alongside the violin plots as the current best approach IMHO. Source code repository: ggjoy Example of use (EDIT: This plot style is named after the “Joy Division”, due to a similar graphic on one of their album covers.
When, in 1994, definitive evidence of tuberculosis in humans was reported from pre-Columbian America, it was a startling. Conventional understanding had pegged tuberculosis as part of the new, exotic, and (to immunologically-naive populaces) deadly menagerie of pathogens brought by Europeans over to the Americas. While there were suggestions of pre-Columbian tuberculosis in the Americans, these were based on lesions on bones, which were ambiguous. Unlike previous cases, however, the Chiribaya mummy from 1000-1300 CE in Peru was shown beyond doubt to have been exposed to tuberculosis:
A new fossil provides some insight into the critical K-PG boundary around which most modern bird lineages radiated: doi: 10.1073/pnas.1700188114