Cocalc Tutorial Intro Ipynb

After completing this week's lecture and tutorial work, you will be able to: use a Jupyter notebook to execute provided R code edit code and markdown cells in a Jupyter notebook create new code and markdown cells in a Jupyter notebook create new variables and objects in R using the assignment symbol ...

stands for 'Collaboritive Calculation in the Cloud'. Their platform allows you to: You can set up an account and do all this for free without installing any software on your own computer, other than a web browser. (Acknowledgment: This web page is a revision of one originally authored by Paul Meyer-Reimer.) A project is like a folder for your work. But you have to create one before you can do anything else.

After you Create an account on CoCalc, or after you sign in, you'll land on the Projects page. Your new notebook will open. Let's get oriented... NOTHING ABOVE THIS LINE IS VISIBLE IN EDX First of all, greetings from the TOPOCMx team! We are very happy that you chose to follow our course.

Through TOPOCMx we want to provide an introduction to the new topics on topology in condensed matter. We want it to be simple, and we want it to be useful for people with very different background and motivation. We want the course to be useful to you if you are a master student, and you want to get an understanding of what topology is all about. Or you could be a PhD student or a postdoc doing experiments, and you want to get a better theoretical understanding of what you should expect in your investigations. This tutorial should take at most 3-4 hours to fully work through. You can read it in HTML or PDF versions, or from the Sage notebook click Help, then click Tutorial to interactively work through the tutorial from within Sage.

Though much of Sage is implemented using Python, no Python background is needed to read this tutorial. You will want to learn Python (a very fun language!) at some point, and there are many excellent free resources for doing so: the Python Beginner’s Guide lists many options. If you just want to quickly try out Sage, this tutorial is the place to start. For example: This IPython / Jupyter notebook is an interactive tutorial in the use of Python for data analysis. First of all, the interface.

The text you see in boxes like this is editable and is written in a format called Markdown similar to the syntax used to edit Wikipedia. If you double-click on this text you will convert it to the raw Markdown for editing. If you want to go back to the nicely-rendered form, click on the editable text and press shift-enter. Second, code to execute appears in editable textboxes, nicely syntax-highlighted for Python: When you evaluate the cell above (click on it and press shift-enter), output should appear below the cell. Yay.

Python is telling you 1+1=2. Not exactly earth-shattering, but that's the basic mode of interaction at work here: Edit the snippet or write another and repeat You can use NetworkX to construct and draw graphs that are undirected or directed, with weighted or unweighted edges. An array of functions to analyze graphs is available. This tutorial takes you through a few basic examples and exercises.

Note that many exercises are followed by a block with some assert statements. These assertions may be preceded by some setup code. They are provided to give you feedback that you are on the right path -- receiving an AssertionError probably means you've done something wrong. https://networkx.github.io/documentation/networkx-2.2/ https://networkx.github.io/documentation/networkx-2.2/tutorial.html Recall that import statements go at the top of your code, telling Python to load an external module.

In this case we want to load NetworkX, but give it a short alias nx since we'll have to type it repeatedly, hence the as statement. ... stands for 'Collaboritive Calculation in the Cloud'. Built with open source tools, it's a platform that has been shepherded by the mathematician William Stein, first as SageMath, since about 2007. The CoCalc platform supports Jupyter notebooks. When you see familiar terms spelled with py instead of pi, it's because developers using the python computing language have been involved!

A notebook (files end in .ipynb) mixes computer math calculations, graphics, data visualizations and documentation including publication-quality math typesetting. Within a single Jupyter notebook you can include all these things: [(*) These are the ones you'll be using in Calculus I & III. ] You can set up an account and do all this for free without installing any software on your own computer, other than a web browser. (Right now, the GC Math Department is picking up the tab for improved performance for your class projects. Watch this Video introduction (10 minutes) to CoCalc (below).

It was prepared for a programming (Python) class. We'll be doing slightly different things. Python code is usually stored in text files with the file ending ".py": Every line in a Python program file is assumed to be a Python statement, or part thereof. The only exception is comment lines, which start with the character # (optionally preceded by an arbitrary number of white-space characters, i.e., tabs or spaces). Comment lines are usually ignored by the Python interpreter.

To run our Python program from the command line we use: On UNIX systems it is common to define the path to the interpreter on the first line of the program (note that this is a comment line as far as the Python interpreter is... In this notebook we will deal mainly with syntax and semantics in Python we explore some basic expressions in Python we introduce some of the most important control flow statements This is a Jupyter notebook.

It is an interface allowing us to combine code (in this case Python) and formatted text in a unified way. The basic unit in a notebook is a cell. You are right now reading the content of a "Markdown" cell, designed to input formatted text. There are also 'Code' cells, designed to input executable code. This tutorial should take at most 3-4 hours to fully work through. You can read it in HTML or PDF versions, or from the Sage notebook click "Help", then click "Tutorial" to interactively work through the tutorial from within Sage.

Though much of Sage is implemented using Python, no Python background is needed to read this tutorial. You will want to learn Python (a very fun language!) at some point, and there are many excellent free resources for doing so including [PyT] and [Dive]. If you just want to quickly try out Sage, this tutorial is the place to start. For example: If you do not have Sage installed on a computer and just want to try some commands, use it online at http://sagecell.sagemath.org. See the Sage Installation Guide in the documentation section of the main Sage webpage [SA] for instructions on installing Sage on your computer.

Here we merely make a few comments. The Sage download file comes with “batteries included”. In other words, although Sage uses Python, IPython, PARI, GAP, Singular, Maxima, NTL, GMP, and so on, you do not need to install them separately as they are included with the Sage distribution. However, to use certain Sage features, e.g., Macaulay or KASH, you must install the relevant optional package or at least have the relevant programs installed on your computer already. Macaulay and KASH are Sage packages (for a list of available optional packages, type "sage -optional", or browse the “Download” page on the Sage website).

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