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Numpy and Scipy Documentation. This is the documentation for Numpy and Scipy. Numpy (development version) Reference Guide. Numpy (development version) User Guide. Numpy 1.14.0 Reference Guide. Numpy 1.14.0 User Guide. Numpy 1.13.0 Reference Guide. Numpy 1.13.0 User Guide. Numpy 1.12.0 Reference Guide. Numpy 1.12.0 User Guide. Numpy 1.11.0 Reference Guide. Numpy 1.11.0 User Guide. Numpy 1.10.4 Reference Guide. Numpy 1.10.4 User Guide. Numpy 1.10.1 Reference Guide. Numpy 1.10.1 User Guide. Scipy 0.14&#...

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Numpy and Scipy Documentation. This is the documentation for Numpy and Scipy. Numpy (development version) Reference Guide. Numpy (development version) User Guide. Numpy 1.14.0 Reference Guide. Numpy 1.14.0 User Guide. Numpy 1.13.0 Reference Guide. Numpy 1.13.0 User Guide. Numpy 1.12.0 Reference Guide. Numpy 1.12.0 User Guide. Numpy 1.11.0 Reference Guide. Numpy 1.11.0 User Guide. Numpy 1.10.4 Reference Guide. Numpy 1.10.4 User Guide. Numpy 1.10.1 Reference Guide. Numpy 1.10.1 User Guide. Scipy 0.14&#...

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Weave (scipy.weave) — SciPy v0.18.0 Reference Guide

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SciPy v0.18.0 Reference Guide. NumPy – cast/copy/transpose. A quick look at the code. Passing Variables in/out of the C/C code. String, List, Tuple, and Dictionary Conversion. Callable, Instance, and Module Conversion. Catalog search paths and the PYTHONCOMPILED variable. NumPy efficiency issues: What compilation buys you. Type definitions and coercion. Creating the Extension Module. Customizing Type Conversions – Type Factories. There are three basic ways to use. Was the original reason. Fits in this sp...

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scipy.interpolate.interp1d — SciPy v0.18.0 Reference Guide

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SciPy v0.18.0 Reference Guide. Interpolate a 1-D function. Are arrays of values used to approximate some function f:. This class returns a function whose call method uses interpolation to find the value of new points. N,) array like. A 1-D array of real values. N,) array like. A N-D array of real values. The length of. Along the interpolation axis must be equal to the length of. Str or int, optional. Specifies the axis of. Along which to interpolate. Interpolation defaults to the last axis of. If a two-e...

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scipy.cluster.vq.whiten — SciPy v0.14.0 Reference Guide

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SciPy v0.14.0 Reference Guide. K-means clustering and vector quantization (. Normalize a group of observations on a per feature basis. Before running k-means, it is beneficial to rescale each feature dimension of the observation set with whitening. Each feature is divided by its standard deviation across all observations to give it unit variance. Each row of the array is an observation. The columns are the features seen during each observation. Contains the values in. Last updated on May 11, 2014.

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numpy.loadtxt — NumPy v1.11 Manual

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NumPy v1.11 Manual. Load data from a text file. Each row in the text file must have the same number of values. File, filename, or generator to read. If the filename extension is. The file is first decompressed. Note that generators should return byte strings for Python 3k. Str or sequence, optional. The characters or list of characters used to indicate the start of a comment; default: ‘#’. The string used to separate values. By default, this is any whitespace. Lines; default: 0. Data read from the text f...

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Statistical functions (scipy.stats) — SciPy v0.18.0 Reference Guide

https://docs.scipy.org/doc/scipy/reference/stats.html

SciPy v0.18.0 Reference Guide. This module contains a large number of probability distributions as well as a growing library of statistical functions. Each univariate distribution is an instance of a subclass of. Momtype, a, b, xtol, .]). A generic continuous random variable class meant for subclassing. A, b, name, badvalue, .]). A generic discrete random variable class meant for subclassing. An alpha continuous random variable. An anglit continuous random variable. An arcsine continuous random variable.

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A curious mind...: February 2011

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Friday, February 25, 2011. A scientific Python starter. As requested by some, here is a list of important websites, doc-sites and modules for a successful start in Python. If there's one problem with Python, it is how some of the available modules depend on other modules to be the right version. Therefore I recommend wholeheartedly to install big packages that include all the modules you need as one big chunk. I personally made good experiences with http:/ www.enthought.com. 3 A warning for IDL switchers:.

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A curious mind...: A scientific Python starter

http://michaelaye.blogspot.com/2011/02/scientific-python-starter.html

Friday, February 25, 2011. A scientific Python starter. As requested by some, here is a list of important websites, doc-sites and modules for a successful start in Python. If there's one problem with Python, it is how some of the available modules depend on other modules to be the right version. Therefore I recommend wholeheartedly to install big packages that include all the modules you need as one big chunk. I personally made good experiences with http:/ www.enthought.com. 3 A warning for IDL switchers:.

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pandas: powerful Python data analysis toolkit — pandas 0.18.1 documentation

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Pandas 0.18.1 documentation. Frequently Asked Questions (FAQ). 10 Minutes to pandas. Intro to Data Structures. Working with Text Data. Indexing and Selecting Data. MultiIndex / Advanced Indexing. Working with missing data. Merge, join, and concatenate. Reshaping and Pivot Tables. Time Series / Date functionality. IO Tools (Text, CSV, HDF5, .). Rpy2 / R interface. Comparison with R / R libraries. Enter search terms or a module, class or function name. Pandas: powerful Python data analysis toolkit. Any oth...

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1.3.1. The NumPy array object — Scipy lecture notes

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1 Getting started with Python for science. 13 NumPy: creating and manipulating numerical data. Collapse document to compact view. Edit Improve this page:. Edit it on Github. 131 The NumPy array object. What are NumPy and NumPy arrays? 1311 What are NumPy and NumPy arrays? High-level number objects: integers, floating point. Containers: lists (costless insertion and append), dictionaries (fast lookup). Extension package to Python for multi-dimensional arrays. Closer to hardware (efficiency). 2 x 3 array.

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Numerical Analysis and Statistics: MATLAB, R, NumPy, Julia. A side-by-side reference sheet. Matlab -nojvm -nodisplay -r 'exit'. Import sys, os, re, math. Import numpy as np. Import scipy as sp. Import scipy.stats as stats. Import pandas as pd. Import matplotlib as mpl. Import matplotlib.pyplot as plt. Matlab -nojvm -nodisplay -r "run('foo.m')". R -f foo.r. Matlab -nojvm -nodisplay -r 'disp(1 1); exit'. If elseif else end. Newlines not separators after three dots:. Newline or ;. 1 1 % addition. Uint8 uint...

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5. Systèmes dynamiques : utilisation de SciPy — Python scientifique - ENS Paris

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Python scientifique - ENS Paris. 5 Systèmes dynamiques : utilisation de SciPy. Présentation du module SciPy. Réalisation de traitements de données avancés avec SciPy. Génération de figures avancées avec Matplotlib. Ecrire la documentation d’une fonction. On a déjà vu qu’il existe beaucoup d’opérations permettant par exemple de. Générer des tableaux particuliers :. Faire des opérations à partir des valeurs du tableau :. Est la boîte à outils. Numérique pour les tableaux NumPy. On trouve dans SciPy. On peu...

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SciPy library — SciPy.org

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The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Source code (on Github).

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