Youtbe tutorial simply fortran install#
Youtbe tutorial simply fortran software#

Do folks see Anaconda Navigator somewhere among their applications? Okay, so go ahead and fire up Anaconda Navigator, and you should see a pretty look like this.

Youtbe tutorial simply fortran install#

So you will want to install Anaconda Navigator, which I think is what Anaconda does when you download it. Those of you who are still installing, don’t worry, we’ll try to go slow so you get a chance to catch up. For your system, okay? I’m going to move forward a little bit because some of you, about maybe half of you, are kind of done. And it should download and install it for your system. It’s smart enough to know what OS you’re using, so go ahead and download it. So you’ll want to go to the Anaconda website, which is, and I think that’ll take you immediately to the download page.

There are ways to run things online without installing Python, but I think it’ll be easier just to install Python. I think that might be the easiest way to do this. So is it set up?Īnd the first thing we want to do is to install Python. So visit the URL, and you’re going to want to scroll down to where you see the setup. Oh, that doesn’t make the URL any bigger. So the first thing you’re going to want to do is go to the website here.

Youtbe tutorial simply fortran software#

All these software carpentry workshops, almost all of them, the tutorials are kind of focused around a kind of real-world problem example so that you can apply what you’re learning as you go along, and so it provides some data files and things like that. This is the software carpentry Python tutorial, and it uses as an example some sort of fake data having to do with inflammation. It’s just Jason’s in the room, and Randy is Randy in the room? No? Okay, great. State and I’ll be helping out with this workshop.īrain: Does anyone online want to introduce themselves? See, we have someone named Randy and someone named Jason. I’m an HPC engineer with research computing services here at Boise. Michael: I’m Michael from the University of Idaho State. Joe: I’m Joe with the University of Idaho. I’m helping out today as a Zoom moderator as well. Jason: Hi, I’m Jason Watt, and I’m with OIT research computing. I’m doing my Master’s with Ellen Enderlin in the geosciences department. I’m a busy student in the biomolecular sciences program in Charles’ lab.Īman: Hi, I’m Aman. I’m a Material Science PhD student with Eric Jankowski’s lab.Īndrea: Hi, Andrea, a PhD student at the University of Idaho. Is this connected to the Zoom? Can you hear us? Okay, yes. I work in the genetics and infectious disease lab on campus, so if you ever get a COVID test, I’m the one running that for you. Why doesn’t everyone just introduce themselves? At least give us your name, and that way, we can kind of get to know each other a little better. Before we dive in though, let’s have introductions. They’re very well constructed, and they’ve been tested and kind of vetted by a variety of folks, so they’re pretty strong, solid instructional materials. How many of you have already done software carpentry tutorials? Anyone done one? A couple of you? Yeah, they’re really good. Python tutorial because it’s really great. So let’s bring up the software carpentry. I didn’t make them for anyone except for me, honestly, but we put notes there that’ll be useful.

So this is just a link to a couple of the notebooks and stuff that I started for this thing, but they’re not probably sort of generally useful. I did post a few notes and things at this tiny URL: /RCdays 2023 Python. If someone posted one, I didn’t put it in myself, so no, okay. I put up, I didn’t put any Jupiter notebooks. Is anyone on Zoom that wants to be on Zoom we’ll probably post links and things to Zoom as well as the Ether pad. Okay, I’m just trying to clear some stuff out here. I think it’s one of those kinds of languages that it’s easy to interpret what you’re seeing without even necessarily knowing a lot of coding, so this is a tremendous advantage in that sense. Python is a particularly readable language. In computing, so it’s, you know, it’s useful. And as those of you who have done any kind of coding before know, once you learn one language, you can kind of learn, you kind of learn all languages. In astronomy right now, almost all the kind of simple data science-type things are being done in Python, so Python, I think, is a really good language for Sonic, particularly, but I think for a lot of scientific fields. I’m an astronomer by training, and so I have some experience with data science and with Python, frankly.

I’m a professor in the physics department. Brian: Great, yes, well again, thanks to everyone for coming.