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Scipy Lecture Notes — Scipy lecture notes

Collapse document to compact view. Edit Improve this page:. Edit it on Github. One document to learn numerics, science, and data with Python. PDF, 2 pages per side. PDF, 1 page per side. HTML and example files. Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. About the scipy lecture notes. 1 Getting started with Python for science.

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Scipy Lecture Notes — Scipy lecture notes | scipy-lectures.org Reviews

https://scipy-lectures.org

Collapse document to compact view. Edit Improve this page:. Edit it on Github. One document to learn numerics, science, and data with Python. PDF, 2 pages per side. PDF, 1 page per side. HTML and example files. Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. About the scipy lecture notes. 1 Getting started with Python for science.

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1.3.3. More elaborate arrays — Scipy lecture notes

http://www.scipy-lectures.org/intro/numpy/elaborate_arrays.html

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. 133 More elaborate arrays. Dealing with (propagation of) missing data. 1331 More data types. 8220;Bigger” type wins in mixed-type operations:. Array([ 2.5, 3.5, 4.5]). Assignment never changes the type! Float is truncated to integer. Array([1, 2, 3]). Array([1, 1, 1]). Array([ 1., 2., 2., 2., 4., 4.]). Array([1, 2, 2, 2, 4, 4]).

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1.2. The Python language — Scipy lecture notes

http://www.scipy-lectures.org/intro/language/python_language.html

1 Getting started with Python for science. Collapse document to compact view. Edit Improve this page:. Edit it on Github. 12 The Python language. Chris Burns, Christophe Combelles, Emmanuelle Gouillart, Gaël Varoquaux. Python for scientific computing. Dedicated books are also available, such as http:/ www.diveintopython.net/. Python is a programming language. As are C, Fortran, BASIC, PHP, etc. Some specific features of Python are as follows:. A free software released under an open-source. Some other fea...

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1.3.2. Numerical operations on arrays — Scipy lecture notes

http://www.scipy-lectures.org/intro/numpy/operations.html

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. 132 Numerical operations on arrays. Array([2, 3, 4, 5]). Array([ 2, 4, 8, 16]). All arithmetic operates elementwise:. Array([-1., 0., 1., 2.]). Array([ 2., 4., 6., 8.]). Array([ 2, 3, 6, 13, 28]). These operations are of course much faster than if you did them in pure python:. 10000 loops, best of 3: 24.3 us per loop. 1, 1, 1.] ).

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1.2.6. Input and Output — Scipy lecture notes

http://www.scipy-lectures.org/intro/language/io.html

1 Getting started with Python for science. 12 The Python language. Collapse document to compact view. Edit Improve this page:. Edit it on Github. 126 Input and Output. To be exhaustive, here are some information about input and output in Python. Since we will use the Numpy methods to read and write files, you may skip this chapter at first reading. We write or read strings. To/from files (other types must be converted to strings). To write in a file:. Opens the workfile file. This is a test.

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1.2.5. Reusing code: scripts and modules — Scipy lecture notes

http://www.scipy-lectures.org/intro/language/reusing_code.html

1 Getting started with Python for science. 12 The Python language. Collapse document to compact view. Edit Improve this page:. Edit it on Github. 125 Reusing code: scripts and modules. For now, we have typed all instructions in the interpreter. For longer sets of instructions we need to change track and write the code in text files (using a text editor), that we will call either. Let us first write a. The extension for Python files is. Write or copy-and-paste the following lines in a file called. By exec...

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pydy.org

Examples — PyDy Website

http://www.pydy.org/examples/examples.html

Some general help and examples for using PyDy. Please add your own! If you are familiar with scientific computing. With Python you should start with the SymPy vector/mechanics documentation and the PyDy documentation:. Symbolic Vectors [SymPy Docs]. Symbolic Dynamics [SymPy Docs]. If you aren’t familiar with scientific computing with Python there are many sources to learn. You can start with the Python programming language itself, with the canonical source being the Python Documentation.

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python_basics

http://musicinformationretrieval.com/python_basics.html

Larr; Back to Index. Python Basics ¶. Is a general-purpose programming language that is popular and easy to use. For new programmers, it is a great choice as a first programming language. In fact, more and more university CS departments are centering their introductory courses around Python. For a summary of reasons to move from Matlab to Python, please read this post. This page on Udacity. Provides some more great reasons to use Python, along with resources for getting started. Section 5: Data Structures.

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Python | I Love Symposia!

https://ilovesymposia.com/tag/python

Science and Tech for the Small Fry. The cost of a Python function call. December 10, 2015. I’ve read in various places that the Python function call overhead is very high. As I was parroting this “fact” to Ed Schofield. Recently, he asked me what the cost of a function actually was. I had no idea. This prompted us to do a few quick benchmarks. The short version is that it takes about 150ns to call a function in Python (on my laptop). This doesn’t sound like a lot, but it means that you can make. Lose two...

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python – thoughts…

https://irrlab.com/tag/python

ArangoDB is designed as a native multi-model database. August 26, 2016. Text summarization with TensorFlow. August 24, 2016. Neural Networks and Deep Learning. August 17, 2016. Neural Networks and Deep Learning is a free online book. The book will teach you about: Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data Deep learning, a powerful set of techniques for learning in neural networks Neural networks and deep learning ...

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conference | I Love Symposia!

https://ilovesymposia.com/category/conference

Science and Tech for the Small Fry. October 9, 2015. The videos from EuroSciPy 2015 are up. This marks a good time to write up my thoughts on the conference. That the yearly SciPy conference is stunningly useful. This year I couldn’t make it to Austin, but I did attend EuroSciPy. The European version of the same conference, in Cambridge, UK. It was spectacular. The talk of the conference, for me, goes to Robin Wilson for recipy. I also enjoyed Nicolas Rougier’s talk. A new journal dedicated to replicated...

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Planet SciPy | I Love Symposia!

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Science and Tech for the Small Fry. Tag Archives: Planet SciPy. Why scientists should code in the open. December 26, 2015. All too often, I encounter. In which the code is “available upon request”, or “available in the supplementary materials” (as a zip file). This is not just poor form. It also hurts your software’s future. (And, in my opinion, when results depend on software, it is inexcusable.). In this piece, I’ll go even further: put your code there. Put your code there. But here’s the secret:.

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programming | I Love Symposia!

https://ilovesymposia.com/category/programming

Science and Tech for the Small Fry. Why scientists should code in the open. December 26, 2015. All too often, I encounter. In which the code is “available upon request”, or “available in the supplementary materials” (as a zip file). This is not just poor form. It also hurts your software’s future. (And, in my opinion, when results depend on software, it is inexcusable.). In this piece, I’ll go even further: put your code there. Put your code there. As soon as you finish reading this article. When it come...

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Juan Nunez-Iglesias | I Love Symposia!

https://ilovesymposia.com/author/jnuneziglesias

Science and Tech for the Small Fry. All posts by Juan Nunez-Iglesias. Review: Sony Digital Paper. May 2, 2016. Three years ago I excitedly posted. About Sony’s then-new writeable e-paper tablet, called Sony Digital Paper System (DPS-1). Now it is finally mine and I love it. Here’s what I wrote about it when Sony announced it:. Having had it for about a month, I can confidently say that it. Here’s a zoomed-in shot of a paper on the DPS-1:. I can barely tell that it’s not just a slightly low-res print.

nightlylibrary.wordpress.com

Online Courses – NightlyArt Vault

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Online courses are cool. They really are. An Elementary Introduction to the Wolfram Language. This is basically a free, online book version of Stephen Wolfram’s book on learning the Wolfram Language. Yes it is free. Just like any other online learning platform to learn how to code. This is an online book for learning (primarily) Python programming language. This course was developed at Harvey Mudd College. 8220;Learn the ways of Linux-fu, for free”. Little Book of R for Bioinformatics. Offered by Massach...

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Interfacing With Other Languages. This is the “SciPy Cookbook” — a collection of various user-contributed recipes, which once lived under. If you have a nice notebook you’d like to add here, or you’d like to make some other edits, please see the SciPy-CookBook repository. Data Acquisition with NIDAQmx. Data acquisition with PyUL. Reading SPE file from CCD camera. Interfacing With Other Languages. C Extensions for Using NumPy Arrays. Compiling Extension Modules on Windows using mingw. Scripting Mayavi 2: ...

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Python Scientific Lecture Notes — Scipy lecture notes

Collapse document to compact view. Edit Improve this page:. Edit it on Github. Python Scientific Lecture Notes. PDF, 2 pages per side. PDF, 1 page per side. HTML and example files. Tutorial material on the scientific Python ecosystem, a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. 1 Getting started with Python for science. 11 Scientific computing with tools and workflow.

scipy-lectures.org

Scipy Lecture Notes — Scipy lecture notes

Collapse document to compact view. Edit Improve this page:. Edit it on Github. One document to learn numerics, science, and data with Python. PDF, 2 pages per side. PDF, 1 page per side. HTML and example files. Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. About the scipy lecture notes. 1 Getting started with Python for science.

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SciPy India 2015

DECEMBER 18, 19 and 20. CFP for the conference is now open! Registrations will open soon! Python for Scientific Computing. SciPy India Conferences down the lane. Few snaps from SciPy India 2014. Lecture Hall Complex, IIT Bombay. Project undertaken by IIT Bombay is funded by Ministry of Human Resource Development. We are open for sponsorships. Kindly write to us at scipy[at]fossee[dot]in. Feel free to send us an email if you have any questions.

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SciPy.org — SciPy.org

SciPy (pronounced Sigh Pie ) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. In particular, these are some of the core packages:. Base N-dimensional array package. Fundamental library for scientific computing. Data structures and analysis. SciPy 0.15.0 released 2015-01-11. Obtaining NumPy and SciPy libraries. SciPy 0.14.1 released 2014-12-30. Obtaining NumPy and SciPy libraries. NumPy 1.9.1 released 2014-11-02. Obtaining NumPy and SciPy libraries.

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SciPy 2010

Scientific Computing with Python Conference Austin, TX June 28-July 3. Friday, July 16, 2010. Download the video from enthought.com. Posted by Amenity Applewhite. Thursday, July 1, 2010. Reposted from the Enthought blog. Travis Oliphant, President of Enthought, Inc. Last, but not least, Travis closed his talk with rather large announcement: Enthought has undertaken the extension of NumPy and SciPy to the .NET framework. For details on the project refer to the official release. Posted by Amenity Applewhite.