Algebra to solve logic puzzles Convert boolean polynomials to probability

YouTube Tutorial: https://youtu.be/P92boGjCnPA

What You'll Learn: Discover how to create a log-log plot using SageMath within a Jupyter notebook on the CoCalc platform. Learn to visualize functions with both standard and logarithmic scales.

Transcription:

Hello everyone, my name is Blaec Bejarano. Today, I'll show you how to create a log-log plot using SageMath in a Jupyter notebook within the CoCalc platform.

The log-log plot displays both the x and y axes on logarithmic scales, which can help visualize certain characteristics of the function.

YouTube Tutorial: https://youtu.be/t7x3iUJDJyc

Transcription: Hello everyone, my name is Blaec Bejarano. Today, I'll demonstrate how to plot the gradient of a function alongside its contour plot using SageMath in a Jupyter notebook on CoCalc. This example is inspired by Gregory Bard's textbook "Sage for Undergraduates" and attributed to Augustin O'Keefe.

1. Define the multivariate function $f(x,y) = \cos(x) - 2\sin(y)$.

The gradient of this function can be written in angle bracket notation as:

2. In the Jupyter notebook, define the function and compute its gradient: f(x,y)=cos(x)-2*sin(y) gradient = derivative(f)

3. Create the vector field plot of the gradient: plot1 = plot_vector_field(gradient, (x, -5, 5), (y, -5, 5))

4. Create the contour plot of the function: plot2 = contour_plot(f, (x, -5, 5), (y, -5, 5), fill=True)

5. Display both plots together: show(plot1 + plot2)

This tutorial showcases CoCalc's ability to perform mathematical computations and visualizations seamlessly within a collaborative environment. Please like, subscribe, and follow for more content. See you next time. Thanks again!

#SageMath #Jupyter #Gradient #ContourPlot #CoCalc

YouTube Tutorial: https://youtu.be/TRbWjocJ2ZI

What You'll Learn: How to create visually appealing plots with grid lines using SageMath in a Jupyter notebook on the CoCalc platform. Learn to specify functions, define domains, and customize your plots with a few simple lines of code.

Transcription:

Hello everyone, my name is Blaec Bejarano. Today, I'll show you how to create plots with grid lines using SageMath in a Jupyter notebook on the CoCalc platform.

1. Log in to your account at cocalc.com and open your desired project.

2. Create a new Jupyter notebook by clicking on the "+New" button and selecting "Jupyter Notebook". Name your notebook and choose the SageMath kernel.

3. In a code cell, use the plot() function to define your desired function. In this example, we'll plot $x^5$:

   • Specify the function you want to plot, e.g., x^5.

   • Define the domain using tuple notation (x, start, end), e.g., (x, 1, 16).

   • Add the gridlines parameter and set it to 'minor' to display grid lines on the plot.

4. Click the run button or press Shift+Enter to execute the code cell and view your plot with grid lines.

Propagação de incertezas

Lista-2

Palestra de divulgação de matemática

CoCalc at AISTATS & ICLR: Connect with us at two leading machine learning conferences! Discover how CoCalc empowers AI and deep learning researchers with collaborative tools, scalable GPUs, and a unified environment for Python, TensorFlow, PyTorch, and more.

SIAM Optimization 2023 Insights: CoCalc shares highlights from the SIAM OP23 conference in Seattle, including real-world applications of optimization at Amazon, smarter algorithms, and unifying theories. See how CoCalc supports this cutting-edge work.

CoCalc at SIAM Dynamical Systems 2023: Read our reflections on the SIAM DS23 conference in Portland, highlighting key presentations on dynamical systems research relevant to computational science. Learn how CoCalc supports cutting-edge work in areas like collective motion, stability analysis, and more.

Worksheets related to Applied Discrete Structures

Math 208 Interactive Notebooks © 2024 by Soham Bhosale, Sara Billey, Herman Chau, Zihan Chen, Isaac Hartin Pasco, Jennifer Huang, Snigdha Mahankali, Clare Minerath, and Anna Willis is licensed under CC BY-ND 4.0

test

Jupyter notebook ED0101 Conceptos Básicos.ipynb

Jupyter notebook Bronson Solved 16.5.ipynb

Proměnné a jejich vyhodnocování v programu Sage

Excellence in Capstone Prize

"Guiding Future STEM Leaders through Innovative Research Training" ~ thinkingbeyond.education

If you love fast-paced arcade games that challenge your reflexes, strategy, and problem-solving skills, then Block Breaker is the perfect game for you!

M2142 - zápisník pro první přednášku

Research done and presented in relation to "Cubulated Holonomy", our chosen direction of research at the IU Bloomington 2024 REU. Mentor: Seppo Niemi Colvin Collaborator: Josue Molina

Example showing two interpretations of Mx = b.

Calculo II, grados TIC, Universidad de Alcalá

German notebook on linear approximation in order to evaluate usability of Jupyter notebooks in German HE Math education

Example implementations of algorithms to search for representations of an integer as a sum of three cubes in the computer algebra systems Pari/GP, Magma, Oscar, and SageMath prepared as part of the PCMI/IAS summer program on Number Theory Informed by Computation.

Life, the Universe, and Everything

Jupyter notebook 2017-01-10-TestFIle.ipynb

compile a figure to a separate small PDF, crop and optimize that small PDF, and then include it in a larger doument

Física Experimental IFC

doughmortician

Polyhedral Omega Demo

How To Copy a Course in CoCalc.

To copy a course to a new project in CoCalc, follow these steps:

Slope

Peeling at an infinity obtained from a generic spherically symmetric degenerate horizon through an extended Couch-Torrence inversion

Effectively manage and adjust the CoCalc licenses applied to your academic and professional projects. This post offers a straightforward guide on navigating CoCalc's flexible licensing system, allowing users to tailor resources according to their evolving needs. Whether you're switching between projects or ensuring seamless collaboration, learn how CoCalc's intuitive tools can enhance your experience. Perfect for both new and seasoned users, this guide ensures you can focus on your work without unnecessary distractions due to licensing.

Enhance your organization's collaborative scientific computing capabilities with CoCalc OnPrem, a robust enterprise-grade alternative to JupyterHub. Experience real-time collaboration with features like TimeTravel version control, IPyWidgets support, and AI-assisted code improvements. CoCalc OnPrem is designed for customizable projects, secure infrastructure deployment, and scalability, running on Kubernetes and integrating seamlessly with LaTeX, Jupyter, R Studio, VS Code, X11 Desktop, and more. Tailored for research, teaching, and publishing, CoCalc OnPrem seamlessly combines the power of shared workspaces with the enhanced security and data privacy of on-premise solutions. Contact help@cocalc.com for advice on how to ensure collaborative computing within your organization is more effective.

This notebook details some computations in the extremal Reissner-Nordström spacetime.