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This was my final project for MIT's Junction computer science class. It is written in Python, and can always be updated with more words! Its just code, so it needs to be run with Python(2.7 recommended).
A spread sheet engine running over python. Any formula is pure python! You can do Macro in python and include any python package like NumPy. There is bult-in functions like D([list]) which automatically extend the list in cells.
Python standard library + numpy + scipy + matplotlib + ipython + mercurial distribution that can be built from source on most Linux machines. SAGE-PyRuntime is based on customized and stripped version of SAGE (http://www.sagemath.org).
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Moving 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.
Earth is fallen, humanity is near extinguish, commander, our warship is trapped in a sub space, we need escape before the androids found us. pygame and numpy are needed for running this game!
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
A simple project which attempts to emulate real life in the launching of a trebuchet. Requires a python compiler, and the python modules for math, gtk, pygame, random, and numpy. Please note: this is an early version and is in alpha.
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Moving 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.
The scikits.timeseries python module provides classes and functions for manipulating, reporting, and plotting time series of various frequencies. The focus is on convenient data access while leveraging the existing functionality in numpy.
pyIDL is a bridge from Python to ITT's IDL. It allows easy access to functions, procedures and variables in the IDL context. pyIDL directly links to IDL's internal API using Cyton and Numpy.
Set of python scripts that can be used for the calculations of equilibrium fractionation factors from experiments and from statistical mechanics theory. python scripts use Scipy/Numpy/Matplotlib/WxPython for calculations, plotting and the GUI
PyMaTi is a simple and easy to use GUI for numerical and scientific computing in Python. It surrounds well know packages NumPy and Matplotlib and provides possibility to immediately play with numerical python from intuitive user interface.
PyPlotSuite aims to provide immediate, easy-to-use, GUI tools to display, analyze and create publication-quality 2D plots of 1D data series, images, 2D arrays. This project is based on (and would not exist without) pygtk, matplotlib and numpy.
Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.
QME-DEV Workbench (wxScipy) is a data analysis workbench based on Python, SciPy, Numpy and MatPlotLib(PyLab) and uses wxPython for the GUI. It can be used for non-linear analysis with a large set of experimental or generated data. Load/Acquire / Save/ Gr
pynpvm is a Python interface to Parallel Virtual Machine (PVM), a portable heterogeneous message-passing system. It requires NumPy as a pre-requisite because the datatype numpy.array is used for message passing.
Lightweight Python 2D table object with column headers
For 2D data objects in Python, you have 3 main options:
- Numpy Array
- Pandas DataFrame (built on np.array)
- SQL table
Numpy and Pandas are great for working with a complete set of data, but not very efficient for building up row by row.
SQL is good for building up the object row by row, but you have to write SQL and leave the world of Python objects.
Python feature engineering using NumPy, SciPy, pandas, scikit-learn, Featuretools and Feature-engine. Identifying and extracting features to develop optimized machine learning models.
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A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset.
https://makeweb.ai
https://eazyseo.co
Simple Python class for managing tables of data in memory using NumPy. It allows to give names to views of array. The package contains few classes built on top of the basic one to be used as post processing tools for particle optics computations.
...Not working yet! The first release comming soon...
Requirements
numpy
matplotlib
PyAstronomy
pymc
Installation is possible from source code or using build installation binary file (only for OS
Windows). The following procedure is only for installation from the source code. Extract
files and go to new-created folder. Running script setup.py the installation will be done:
python setup.py install
* This project is under development, not fit for end users *
The project consists of the infrastructure to remotely control apliances (eg. turn the cofee maker on from a web page)
Needed parts:
- an arduino uno board (www.arduino.cc).
- a circuit board for the relays.
- a PC connected to the arduino.
- python2.7 to run the server.
- port forwarding to the PC for remote access.