Search Results for "function point analysis"
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Showing 32 open source projects for "function point analysis"
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IntervalRootFinding.jl
Find all roots of a function in a guaranteed way with Julia
This package provides guaranteed methods for finding roots of functions, i.e. solutions to the equation f(x) == 0 for a function f. To do so, it uses methods from interval analysis, using interval arithmetic from the IntervalArithmetic.jl package by the same authors. The basic function is roots. A standard Julia function and an interval is provided and the roots function return a list of intervals containing all roots of the function located in the starting interval. -
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HomotopyContinuation.jl
A Julia package for solving systems of polynomials
...Many models in the sciences and engineering are expressed as sets of real solutions to systems of polynomial equations. We can optimize any objective whose gradient is an algebraic function using homotopy methods by computing all critical points of the objective function. An important special case is when the objective function is the euclidean distance to a given point. An example of an non-algebraic objective function whose derivative is algebraic is the Kullback–Leibler divergence. Homotopy continuation methods allow us to study the conformation space of molecules as for example cyclooctane (CH₂)₈. ... -
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Roots.jl
Root finding functions for Julia
This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known (one where f(a) and f(b) have alternate signs), a bracketing method, like Bisection, can be specified. ... -
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Infiltrator.jl
No-overhead breakpoints in Julia
This package provides the @infiltrate macro, which acts as a breakpoint with negligible runtime performance overhead. Note that you cannot access other function scopes or step into further calls. Use an actual debugger if you need that level of flexibility. Running code that ends up triggering the @infiltrate REPL mode via inline evaluation in VS Code or Juno can cause issues, so it's recommended to always use the REPL directly. When the infiltration point is hit, it will drop you into an interactive REPL session that lets you inspect local variables and the call stack as well as execute arbitrary statements in the context of the current local and global scope. -
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CausalInference.jl
Causal inference, graphical models and structure learning in Julia
Julia package for causal inference and analysis, graphical models and structure learning. This package contains code for the PC algorithm and the extended FCI algorithm, the score based greedy equivalence search (GES) algorithm, the Bayesian Causal Zig-Zag sampler and a function suite for adjustment set search. -
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ydata-profiling
Create HTML profiling reports from pandas DataFrame objects
ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json. -
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SPX
A simple & straight-to-the-point PHP profiling extension
SPX, which stands for Simple Profiling eXtension, is just another profiling extension for PHP. It differentiates itself from other similar extensions as being totally free and confined to your infrastructure (i.e. no data leaks to a SaaS). Very simple to use: just set an environment variable (command line) or switch on a radio button (web request) to profile your script. Thus, you are free of manually instrumenting your code (Ctrl-C a long running command line script is even supported).... -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations of f. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). -
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Foxglove Studio
Robotics visualization and debugging
...Use Foxglove Studio's rich interactive visualizations to analyze live connections and pre-recorded data. Experience the world as your robot does. Visualize images and point clouds, overlay bounding boxes, add classification labels and planned movements, and drill down into your data with plots or raw message views. Upload recordings to your private data lake for easy storage, searching, and analysis. Stream recorded data directly into Foxglove Studio to get insights into your robots' behavior. We're long-time fans and beneficiaries of open source software. ... -
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Tokenize.jl
Tokenization for Julia source code
Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens. -
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). More detailed description as well as documentation can be found at webpage http://xrayutilities.sourceforge.io/. ... -
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DataMelt
Computation and Visualization environment
DataMelt (or "DMelt") is an environment for numeric computation, data analysis, computational statistics, and data visualization. This Java multiplatform program is integrated with several scripting languages such as Jython (Python), Groovy, JRuby, BeanShell. DMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. ... -
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3Depict
atom probe software : visualisation and data analysis
This software is designed to help users visualize and analyze 3D point clouds with an associated real value, in a fast and flexible fashion. The primary use is in Atom Probe Tomography, which is an atomic imaging technique. However the program may also be useful in other areas, such as geospatial data, lidar, etc. -
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
...The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible. -
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OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
OzGIS is an extensive mapping system for the analysis and display of geographically referenced data. Map data are downloaded from Census bureaux and map agencies or extracted from your own databases. The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research. Systems for Windows, Mac and Ubuntu, source code, sample data files and manuals are included. DOWNLOAD to... -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
...A tensor can be thought of as an n-dimensional matrix. In the CNN above, tensors will be 3-dimensional with the exception of the output layer. A neuron can be thought of as a function that takes in multiple inputs and yields a single output. The outputs of neurons are represented above as the red → blue activation maps. -
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Facets
Visualizations for machine learning datasets
The power of machine learning comes from its ability to learn patterns from large amounts of data. Understanding your data is critical to building a powerful machine learning system. Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive. Explore Facets Overview and Facets Dive on the UCI Census Income... -
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GEOMS2
Geostatistics and geosciences modeling software
GEOMS2 is a geostatistics and geosciences modeling software. Provides interface for grid (mesh), point, surface and data (non-spatial) objects. It has a 3D viewer and 2D plots using the well known Python engines Mayavi and Matplotlib. It has several functions to manipulate your data as well as provide univariate and multivariate analysis. NOTE: The software is still an early beta. Please tell us if you found a bug. Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?... -
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OpenUnderwriter (Insurance Distribution)
Feature rich insurance quote & buy system for underwriters and brokers
OpenUnderwriter is an open source software house specialising in the development of IT solutions for the insurance market. Specialists in the areas of eBusiness and component based development, the team has developed technology for a number of major insurance companies. The OpenUnderwriter platform has been collaboratively developed by some of the best technical brains in the Insurance Industry and offers a viable alternative to traditional solutions. To date, OpenUnderwriter has been... -
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SIVIC is an open-source, standards-based software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.
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GeoJAGS
JAGS module with covariance functions and the CAR model.
A module for JAGS containing several covariance functions for point-referenced data analysis and a function that creates the precision matrix for the proper CAR model for areal data analysis. -
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Calculation of camshafts - allows to define a camshaft profile on the set trajectory which should provide the given mechanism. The trajectory can be set graphically, co-ordinates or function.
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Random Bits Regression
Random Bits Regression is a strong general predictor.
...For example, natural disaster prediction, stock price prediction, personal/population disease prediction. The fast-speed nature of our method not only allows big data analysis but also enables real-time recognition and predictions. The RBR framework also hints the mechanism of brain function and leads to a "wide learning" hypothesis. We believe that this method will make a great impact and enable many downstream applications. -
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Savuka-VirtualBox
Virtual Box VDI of SliTaz Linux with Savuka installed and configured
Savuka global analysis software (www.osmanbilsel.net) is installed and configured in a light version of SliTaz linux (www.SliTaz.org). root name: root root password: root username: tux password: root Instructions: -Download and install 7zip (www.7-zip.org) -Extract files to HDD -Install included VirtualBox (not tested on other versions, but shouldn't matter) -Within VirtualBox make a new machine ----Machine/New --------Name: Savuka / Type: Linux / Version: Other Linux (32-bit) --------1024MB RAM -------- Use Existing virtual drive (point to extracted Savuka.vdi) ---- Machine/Settigns/Display: set video memory to 50 MB, enable 2D and 3D acceleration ---- Machine/Settings/Shared Folders: Create new machine folder. ...
