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Showing 11 open source projects for "so"
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Swift Numerics
Advanced mathematical types and functions for Swift
Swift Numerics is a foundational library that extends the Swift standard library with essential numerical protocols, types, and functions needed for scientific and systems programming. It defines generic abstractions over real and complex numbers so algorithms can be written once and work across concrete floating-point types. The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics in Swift. API design follows Swift’s emphasis on value semantics and protocol-oriented programming, enabling compiler optimizations and predictable performance. ... -
2
JAX
Composable transformations of Python+NumPy programs
...But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python. -
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Napkin
An Infinitely Large Napkin
Napkin (also titled “An Infinitely Large Napkin”) is a lightweight, semi-formal introduction to higher mathematics, aimed at giving readers a bird’s-eye view over various mathematical fields. It is not a polished textbook full of full proofs; rather it offers clean definitions, theorem statements, intuitive motivations, and informal sketches of why things work, with the goal of building conceptual understanding. The coverage spans undergraduate and early graduate topics, designed to show how... -
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NZMATH
Python Calculator on Number Theory, three-birds-one learning material
NZMATH is a Python calculator on number theory. It is freely available and distributed under the BSD license. All programs are written only by Python so that you can easily see their algorithmic number theory. You can get NZMATH with a single command: % python -m pip install -U nzmath Here % is the command line prompt of Windows or Unix/macOS. This release contains several program corrections and additions obtained by writing a programming "notebook" of the book 'Lectures on Elementary Number Theory' (TAKAGI, Teiji) in Python-NZMATH language. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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5
3d Linear Transformation Visualization
Visualize 3d linear transformations.
...For visualizing this we can transform a vector, but it has an obvious problem, because the linear transformation transform the whole space, not just the vector, in other words it transforms the basis vectors thus every vector in the space gets transformed too. That's why i created this app so everyone can see how a transformation matrix change the whole space. -
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Awesome Math
This is the Curriculum for "How to Learn Mathematics Fast"
...The materials emphasize short, high-leverage resources—video lectures, concise notes, and hands-on exercises—that help you build momentum quickly. It also suggests checkpoints and practice ideas so you can test comprehension and move forward with confidence. The structure is useful both for newcomers who want a starting plan and for practitioners filling specific gaps before tackling ML or deep learning. Overall, it acts as a compact study plan that turns “learn math” from a vague goal into a concrete, achievable path. -
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Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.
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wmtsa-python
Discrete wavelet methods for time series analysis using python
...This library aims at filling this gap, in particular considering discrete wavelet transform as described by Percival and Walden. This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices. The code uses a mix of python and cython for improved performance. The code reflects my needs and preferences, but contributions from others are welcome. The code has to some extent been tested, but bugs are to be expected. -
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DeDAY
MLE survival analysis: Gompertz, Weibull, Logistic and mixed morality.
...Mixed mortality models, such as in Gompertz-Makeham distribution, consider a more general case where mortality is consist of both age-dependent and in-dependent mortality. Mixed models partition mortality into exogenous and endogenous components, so that the intrinsic survivorship can be estimated without the interference from extrinsic noise. DeDAY supports both interval-censored data and exact event-time data. Using MLE (Maximum Likelihood Estimate), DeDAY fits statistic model to the data. DeDAY also calculates the variances and the multi-dimensional confidence limits of model parameters. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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10
Noisy Channel Simulator
Demonstrate errors in transmission of a file over a noisy channel.
...It takes an input file, the probability of a bit being flipped, and, if specified, the size of the header of the file. The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any input file. -
11
This is a slide rule emulator based on the classic Pickett slide rule design. It is written in Python, so the name "pyckett" is appropriate. It is suitable as an example of object-oriented Python software construction, including multiple inheritance.
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