### All Submissions In Order Of Most Views

• #### Basic linear regression

Expected result: See the official Scipy documentation for details about linregress. A more complete regression model can be obtained with the OLS function in the statsmodels library.

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• revision 5
• by jeremy
• on 07 February 2016

• #### Building a simple interactive 2d-data viewer with Matplotlib

This is a very simple, but practical 2d-data viewer, which uses only matplotlib widgets. Click: on the image or the plots to get a cross section - x or y depending ...

The code considers the case of finding the intersection of a polynomial, $$y=x^2$$ and a line, $$y=x+1$$. Write these functions in the form $$\mathbf{f(x ... • #### Fitting a Gaussian to noisy data-points This script reproduces the plots from Guo, A Simple Algorithm for Fitting a Gaussian Function, IEEE Signal Processing Magazine, September 2011, pp. 134–137. The paper describes how to fit ... • 0 • revision 2 • by stefan • on 23 September 2011 • #### Using Prony's method to fit a sum of exponentials This a basic implementation of Prony’s method. In this form, it is very susceptible to noise. Added by Jose: I had some problems using “lstsq” from scipy.linalg that ... • 0 • revision 4 • by joseA • on 17 September 2013 • #### Principal components analysis (PCA) using a sequential method The singular value decomposition is usually presented as the way to calculate the PCA decomposition of a data matrix. The NIPALS algorithm is a very computationally tractable way of calculating ... • #### Simple interactive Matplotlib plots Interactive graphs with Matplotlib have haunted me. So here I have collected a number of tricks that should make interactive use of plots simpler. The functions below show how to ... • #### pymls - solving bounded linear least squares problems Based on mls_alloc from the matlab toolbox Qcat by Ola Harkegard, this package allows to solve bounded least squares problems. It is also possible to put weights on your columns ... • #### Plot an ellipse The code will plot any ellipse where you specify the major and minor axis distances, optional translation by \(x, y$$ units, and an optional rotation. This revision deploys numpy broadcasting ...

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• revision 2
• by woiski
• on 03 September 2011

• #### 100 Numpy exercices

A collection of 100 numpy exercices gathered from the numpy mailing list, stack overflow and other places.

• #### finds the solitary and clustered pixels in a 2D array of pixels

Upgraded on Wed Sep 14 10:55:30 2016 - Version 2 - Improved algorithm: the first version can fail for some specific shapes of clusters (worm-like shapes). For example with Pos ...

• #### SciPy Lectures Notes

These are a consistent set of materials to learn the core aspects of the scientific Python ecosystem, from beginner to expert. They are written and maintained by a set of ...

• #### Integrating an initial value problem (single ODE)

We want to integrate a single equation $$\displaystyle \frac{dy(t)}{dt} = f(t, y)$$ with a given initial condition $$y(t=0)=y_0$$. There are several integrators available in ...

• #### Learning Scipy

This repository contains source code programs and some notes to complement the book about the scientific Python module SciPy entitle [Learning SciPy for Numerical and Scientific Computing - Second Edition (2015 ...

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• by sr
• on 14 August 2015

• #### Python tools for oceanographic analysis

A collaborative effort to organize Python tools for the Oceanographic Community.

• #### NumPy / SciPy Recipes for Data Science: Eigenvalues/Eigenvectors of Covariance Matrices

In this note, we discuss a potential pitfall in using NumPy or SciPy methods to compute eigen decompositions of covariance matrices and show how to avoid it. In short, we ...

• #### Pure python first- and second-order automatic differentiation

The ad python package was designed to make the calculation of first and second derivatives (i.e., the gradient/jacobian and hessian) as transparent as possible for all the base ...

• #### Matplotlib tutorial

Matplotlib is probably the single most used Python package for 2D-graphics. It provides both a very quick way to visualize data from Python and publication-quality figures in many formats. We ...

• #### NumPy / SciPy Recipes for Data Science: Computing Nearest Neighbors

In this note, we discuss efficient NumPy recipes for Euclidean nearest neighbor and k-nearest neighbor searches in data sets of moderate size. Our code snippets are basically one-liners and orders ...

• #### Ten simple rules for better figures

This link to the sources of the figures of the article “Ten Simple Rules for better figures”, Nicolas P. Rougier, Michael Droettboom, Philip E. Bourne, PLOS Computational Biology, 2014. Article ...

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