Projects tagged ‘numpy’

NumPy adds a flexible multi-dimensional array to Python along with mathematical and structural manipulation routines to allow Python to be used for high-level scientific and engineering code development.

matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python ... [More] scripts, the python and ipython shell (ala matlab or mathematica), web application servers, and six graphical user interface toolkits [Less]

Reinteract is a system for interactive experimentation with python.

Trading & Charting system written in Python including Quotes Management, Historic Data, Live Data, Import/Export, Charting, candlestick and Technical analysis, automated alerts, portfolio management, risk management, and much much more

DeVIDE, or the Delft Visualisation and Image processing Development Environment, is a cross-platform software framework for the rapid prototyping, testing and deployment of visualisation and image ... [More] processing algorithms. The software was developed within the Visualisation group. DeVIDE's primary (and currently only) front-end is a data-flow boxes-and-lines network editor. In this regard, it is very similar to AVS, OpenDX, Khoros or VISSION. DeVIDE integrates functionality from libraries such as VTK, ITK, GDCM, DCMTK, numpy and matplotlib. It is being very actively developed. [Less]

Pyprop is a farily general framework for solving TDSE-like initial value problems, and related problems. The aim is to have a standard framework taking care of parallelization, loading and saving the ... [More] wavefunction, etc. Discretization schemes and propagation methods are implemented following a standard interface, which enables users to test different methods without requiring detailed knowledge about the implementation. Propagators for N-dimensional Cartesian coordinates, as well as 3D spherical coordinates are included in the standard package. In addition representations can be combined to create more exotic systems, such as including radial nuclear motion in a diatomic molecule (3D + 1D), combining 3 radial dimensions to simulate a 1D model for a 3-electron atom (1D + 1D + 1D). Pyprop is written in Python (depending heavily on the numpy module), while all the computationally intensive routines have been developed in C++ (using the blitz++ array library) [Less]

Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modelling techniques. It can be used through a nice and intuitive user ... [More] interface or, for more advanced users, as a module for Python programming language. [Less]

Imagine the situation where you need to pass of a series of numbers contained in a file through a series of transformations like absolute, logarithm, square power, cubic power and so on. Well, you ... [More] think: - Wow, I need to open my editor write a program to read a file, put its content into a numeric array structure, take the series of functions and write the results. If your file has some tabular format you still need to split each line and coerce the fields into a numeric matrix data structure. This task becomes a pain when you have to do a lot of transformations to generate graphics or more data for analysis and you appear with a set of ten small files to maintain. It usually happens for those that work with scientific modeling and data processing, analyzing and generating data through simulations. Ok, you can use awk and solve this with an one line command. awk will split the rows in fields and has a small set of mathematical functions. But, if you need a more complex function like Fourier transform, forget. Further, its very common for those that work with data processing to use gnuplot to create graphics. I will show to you a situation that happens to me very frequently. I study time series and use gnuplot to watch the data I am working. When I look at a time series I like to see its logarithm and take the first difference, it's a very usual transformation known as logarithmic return. gnuplot> plot "< awk 'BEGIN{a = \"S\"} { if (a == \"S\") a = log($1); else print log($1) - a; }' timeseries.txt" w lOk, awk solves my problem, but I don't like awk, I can't control the way the text is converted to number and I don't trust in its precision. Awk has not scientific purposes. I can write a program using my preferred language to read the time series file and send the results to standard output, it also solves my problem, but it is also usual to me to take the first difference of the data after the log, and what do I do now ? I can write another program, actually I can write many programs is possible to fulfill my requirements. I can write programs in C, C++, Python ... I will have dozens programs and all my issues will be closed. But, from my experience, I know that many programs are very hard to maintain, specially in my case where I have small and specific programs, imagine the situation where I need to handle a new data format, wow, it will be a pain to update, not all, the most used programs to handle it. It's enough, I write pypus to have time to worry with interesting problems and in my case the interesting problems are those related with data modeling. I create pypus having in mind that: it must be simple and straight forward it must to use existing APIs (I don't want to write another fft implementation) it must be quickly extensible Pypus is a tool to execute one-liners commands for data handling and you can use the well established scientific APIs developed for the Python language: scipy numpy matplotlib Oh, pypus is also developed in Python, just to mention. ExamplesExponential of a time seriesusing awk $ awk '{print exp($1)}' dataseries.txtusing pypus $ pypus '@numpy.exp' dataseries.txtLogarithmic returns of a time seriesusing python $ python logreturn.py dataseries.txtusing pypus $ pypus '@numpy.log @numpy.diff' dataseries.txtGenerating random numbersusing awk $ awk 'BEGIN{ for (i=0 ; i [Less]

Pyspread is a cross-platform Python spreadsheet application. Instead of spreadsheet formulas, Python expressions are entered into the spreadsheet cells. Each expression returns a Python object that ... [More] can be accessed from other cells. These objects can represent anything including lists or matrices. Pyspread works on * Linux, BSD, Unix,... (with GTK+) * Windows * (OS/X is unsupported) [Less]

PyAMG is a library of Algebraic Multigrid (AMG) solvers with a convenient Python interface. AMG is a multilevel technique for solving large-scale linear systems with optimal or near-optimal ... [More] efficiency. Unlike geometric multigrid, AMG requires little or no geometric information about the underlying problem and develops a sequence of coarser grids directly from the input matrix. This feature is especially important for problems discretized on unstructured meshes and irregular grids. PyAMG features implementations of several popular AMG methods: Ruge-Stuben (RS) or Classical AMG, AMG based on Smoothed Aggregation (SA), and Adaptive Smoothed Aggregation (aSA). [Less]