scipy scienti c toolkit scipy
play

SciPy: Scientic Toolkit SciPy SciPy is a collection of mathematical - PowerPoint PPT Presentation

Sep 27, 2023 •447 likes •526 views

SciPy: Scientic Toolkit SciPy SciPy is a collection of mathematical algorithms and convience functions built on Numpy data structures Organized into subpackages covering dierent scientic computing areas A data-processing and

  1. SciPy: Scienti�c Toolkit

  2. SciPy SciPy is a collection of mathematical algorithms and convience functions built on Numpy data structures Organized into subpackages covering di�erent scienti�c computing areas A data-processing and prototyping environment rivaling MATLAB

  3. SciPy Submodules Special functions ( scipy.special ) Integration ( scipy.integrate ) Optimization ( scipy.optimize ) Interpolation ( scipy.interpolate ) Fourier Transforms ( scipy.fftpack ) Signal Processing ( scipy.signal ) Linear Algebra ( scipy.linalg ) Sparse Eigenvalue Problems with ARPACK Compressed Sparse Graph Routines ( scipy.sparse.csgraph ) Statistics ( scipy.stats ) Multi-dimensional image processing ( scipy.ndimage ) File IO ( scipy.io ) Weave ( scipy.weave ) And more. . .

  4. Common submodules: scipy.integrate Integrate the function: 4 x 2 f ( x ) = d x ∫ 0 import scipy.integrate ans, err = scipy.integrate.quad( lambda x: x ** 2, 0., 4) ans 21.333333333333336 See also: dblquad , tplquad , fixed_quad , trapz , simps

  5. Common submodules: scipy.linalg Matrix Inverse import numpy as np import scipy.linalg a = np.random.rand(3,3) scipy.linalg.inv(a) array([[ 2.09386567, 0.18794291, -2.33891785], [ 4.50278126, -2.39788758, -1.04738682], [-6.0432121 , 2.88320448, 3.46459537]]) Eigenvalues scipy.linalg.eigvals(a) array([ 2.08083995+0.j, 0.16847753+0.j, -0.30717139+0.j])

  6. Common submodules: scipy.interpolate Interpolate a function import numpy as np from scipy import interpolate, integrate x = np.arange(-1,11) y = np.exp(-x/3.0) f = interpolate.interp1d(x,y); f <scipy.interpolate.interpolate.interp1d at 0x1127a2728> Integrate the interpolated function ans, err = integrate.quad(f,0,10); ans 2.9197153790964223 Integrate the data integrate.simps(y[1:-1],x[1:-1]) 2.8550038226912573

  7. Why Python/Numpy/SciPy? A free alternative to MATLAB The power of the full Python language Object-oriented Procedural Functional (almost) More reasons come: MATLAB-like plotting Call C/C++/Fortran code directly MPI-style parallel programming (take my graduate course!)

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

iPython Data Analytics in Python 1 / 13 The SciPy Stack SciPy is a Python-based ecosystem of

iPython Data Analytics in Python 1 / 13 The SciPy Stack SciPy is a Python-based ecosystem of

iPython Data Analytics in Python 1 / 13 The SciPy Stack SciPy is a Python-based ecosystem of libraries and tools for scientific computing and data analytics iPython Jupyter notebooks Numpy Pandas Matplotlib iPython is the

608 views • 13 slides
Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler

Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler

Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler https://github.com/scw/scipy-devsummit-2016-talk Handout PDF High Quality PDF (5MB) Resources Section Scientific Computing Scientific Computing The application of

661 views • 19 slides
Data structures for statistical computing in Python Wes McKinney SciPy 2010 McKinney ()

Data structures for statistical computing in Python Wes McKinney SciPy 2010 McKinney ()

Data structures for statistical computing in Python Wes McKinney SciPy 2010 McKinney () Statistical Data Structures in Python SciPy 2010 1 / 31 Environments for statistics and data analysis The usual suspects: R / S+, MATLAB, Stata, SAS,

615 views • 36 slides
SciPy Neelofer Banglawala nbanglaw@epcc.ed.ac.uk Kevin Stratford

SciPy Neelofer Banglawala nbanglaw@epcc.ed.ac.uk Kevin Stratford

L04_Student_SciPy http://localhost:8889/nbconvert/html/L04_SciPy/L04_Studen... SciPy Neelofer Banglawala nbanglaw@epcc.ed.ac.uk Kevin Stratford kevin@epcc.ed.ac.uk Original course authors: Andy Turner Arno Proeme 1 of 13

297 views • 13 slides
Modelling correlations with Python and SciPy Eric Marsden

Modelling correlations with Python and SciPy Eric Marsden

Modelling correlations with Python and SciPy Eric Marsden &lt;eric.marsden@risk-engineering.org&gt; Process safety engineer: To what extent does increased process temperature and pressure increase the level of corrosion of my

599 views • 33 slides
A trainers journey Asokan Pichai SciPy November 2019 TalentSprint 1 What do I do/have done?

A trainers journey Asokan Pichai SciPy November 2019 TalentSprint 1 What do I do/have done?

A trainers journey Asokan Pichai SciPy November 2019 TalentSprint 1 What do I do/have done? Write code Design courses/training programs Train mostly fresh grads in programming Coach fjrst time tech managers Coach

273 views • 16 slides
SciPy &amp; other packages Arno Proeme, ARCHER CSE Team aproeme@epcc.ed.ac.uk Attributed to

SciPy &amp; other packages Arno Proeme, ARCHER CSE Team aproeme@epcc.ed.ac.uk Attributed to

SciPy &amp; other packages Arno Proeme, ARCHER CSE Team aproeme@epcc.ed.ac.uk Attributed to Jussi Enkovaara &amp; Martti Louhivuori, CSC Helsinki Reusing this material This work is licensed under a Creative Commons Attribution-

368 views • 9 slides
Vis isualization and and optimizatio ion Jupyter Matplotlib scipy.optimize.minimize

Vis isualization and and optimizatio ion Jupyter Matplotlib scipy.optimize.minimize

Vis isualization and and optimizatio ion Jupyter Matplotlib scipy.optimize.minimize The Jupyter Notebook The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code,

735 views • 28 slides
Numerical Calculations Ali Taheri Sharif University of Technology Fall 2018 Some slides have

Numerical Calculations Ali Taheri Sharif University of Technology Fall 2018 Some slides have

Fu Fundamentals of Pr Programming (Py Python) Numerical Calculations Ali Taheri Sharif University of Technology Fall 2018 Some slides have been adapted from Scipy Lecture Notes at http://www.scipy-lectures.org/ Outline 1. NumPy and

625 views • 36 slides
Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler

Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler

Scientific Programming with the SciPy Stack Shaun Walbridge Kevin Butler https://github.com/scw/sc ipy-devsummit-2017-talk High Quality PDF (5MB) Resources Section Scientific Computing Scientific Computing The application of computational

923 views • 61 slides
StarCluster - NumPy/SciPy Computing on Amazons Elastic Compute Cloud (EC2) Justin Riley

StarCluster - NumPy/SciPy Computing on Amazons Elastic Compute Cloud (EC2) Justin Riley

Outline Introduction Amazon EC2 Basics StarCluster Overview Conclusions StarCluster - NumPy/SciPy Computing on Amazons Elastic Compute Cloud (EC2) Justin Riley Software Tools for Academics and Researchers Office of Educational Innovation

941 views • 74 slides
Google App Engine - Python Douglas Starnes SciPy 2011 Austin, Texas Agenda Lightning

Google App Engine - Python Douglas Starnes SciPy 2011 Austin, Texas Agenda Lightning

Google App Engine - Python Douglas Starnes SciPy 2011 Austin, Texas Agenda Lightning Round of GAE features Overview Data storage (datastore, blobstore, memcache) Task management (queues, backends) Development and

291 views • 15 slides
Lin inear programming Example Numpy: PageRank scipy.optimize.linprog Example linear

Lin inear programming Example Numpy: PageRank scipy.optimize.linprog Example linear

Lin inear programming Example Numpy: PageRank scipy.optimize.linprog Example linear programming: Maximum flow PageRank PageRank - A A NumPy / / Jupyter / / matplotlib example Central to Google's original search engine was the

461 views • 22 slides
SciPy Conference 2012 A talk on SBHS Virtual labs using Python Team SBHS led by Prof. Kannan

SciPy Conference 2012 A talk on SBHS Virtual labs using Python Team SBHS led by Prof. Kannan

SciPy Conference 2012 A talk on SBHS Virtual labs using Python Team SBHS led by Prof. Kannan Moudgalya Speaker Rupak Rokade Indian Institute of Technology Bombay Project funded by National Mission on Education through ICT,MHRD. December

891 views • 62 slides
Analysis of Electronic Circuits using PySpice and Scipy Raghuttam Hombal and N. S. Ashokkumar

Analysis of Electronic Circuits using PySpice and Scipy Raghuttam Hombal and N. S. Ashokkumar

Analysis of Electronic Circuits using PySpice and Scipy Raghuttam Hombal and N. S. Ashokkumar Automation and Simulation PySpice Simulate electronic circuit using Python and the Ngspice / Xyce simulators PySpice is a Python module PySpice

267 views • 14 slides
http://eric.univ-lyon2.fr/~ricco/cours/cours_programmation_python.html 1 R.R. Universit Lyon

http://eric.univ-lyon2.fr/~ricco/cours/cours_programmation_python.html 1 R.R. Universit Lyon

Ricco Rakotomalala http://eric.univ-lyon2.fr/~ricco/cours/cours_programmation_python.html 1 R.R. Universit Lyon 2 Scipy ? SciPy is a library for scientific computing in Python. It incorporates, among others, modules for data

440 views • 25 slides
Session 3 : Scientific Python Exercises 2 1) Create an array x = [-3.00, -2.99, -2.98, ,

Session 3 : Scientific Python Exercises 2 1) Create an array x = [-3.00, -2.99, -2.98, ,

An introduction to scientific programming with Session 3 : Scientific Python Exercises 2 1) Create an array x = [-3.00, -2.99, -2.98, , 2.98, 2.99, 3.00] 2 e x 2 / 2 1 2) Create a corresponding array for the Gaussian function y =

502 views • 27 slides
Interfacing Python and C using Ctypes Giuseppe Piero Brandino and Jimmy Aguilar Mena March 9,

Interfacing Python and C using Ctypes Giuseppe Piero Brandino and Jimmy Aguilar Mena March 9,

Interfacing Python and C using Ctypes Giuseppe Piero Brandino and Jimmy Aguilar Mena March 9, 2016 Giuseppe Piero Brandino and Jimmy Aguilar Mena Interfacing Python and C using Ctypes March 9, 2016 1 / 12 Motivation When do we want to

799 views • 30 slides
AMath 483/583 Lecture 6 Notes: This lecture: NumPy arrays and functions Python: main

AMath 483/583 Lecture 6 Notes: This lecture: NumPy arrays and functions Python: main

AMath 483/583 Lecture 6 Notes: This lecture: NumPy arrays and functions Python: main programs and private variables Timing Python execution Reading: class notes: Numerical Python Numpy and Scipy documentation R.J.

383 views • 6 slides
Introduction to important modules (libraries) Read (and write) netCDF Work with array Data

Introduction to important modules (libraries) Read (and write) netCDF Work with array Data

Introduction to important modules (libraries) Read (and write) netCDF Work with array Data analysis Plotting Read (and write netCDF) The netCDF4 module Read a netCDF In [3]: # import the module import netCDF4 In [4]: # open the netCDF

513 views • 24 slides
Healthcare Portal With Drupal Sergey Cheban Micah Forster Sergey Cheban Micah Forster

Healthcare Portal With Drupal Sergey Cheban Micah Forster Sergey Cheban Micah Forster

Healthcare Portal With Drupal Sergey Cheban Micah Forster Sergey Cheban Micah Forster Software Engineer/Consultant Software Engineer/Consultant Born and raised in Ukraine Loves implementing new technologies Who we are... Web &amp;

841 views • 34 slides
Proto-DUNE single-phase cold electronics Integration test Guang Yang (Stony Brook) for the DUNE

Proto-DUNE single-phase cold electronics Integration test Guang Yang (Stony Brook) for the DUNE

Proto-DUNE single-phase cold electronics Integration test Guang Yang (Stony Brook) for the DUNE collaboration July 2017 DPF 2017 - Guang Yang (SBU) 1 Neutrino Oscillation - Neutrino mixing can be parameterized by PMNS matrix. - PNMS

483 views • 44 slides
CS-184: Computer Graphics Lecture 16: Radiometry James OBrien University of California,

CS-184: Computer Graphics Lecture 16: Radiometry James OBrien University of California,

CS-184: Computer Graphics Lecture 16: Radiometry James OBrien University of California, Berkeley V2011-F-16-1.0 Today Radiometry: measuring light Local Illumination and Raytracing were discussed in an ad hoc fashion Proper

502 views • 12 slides
Superheterodyne Laser Metrology for the Very Large Telescope Interferometer (VLTI) Y. Salvad,

Superheterodyne Laser Metrology for the Very Large Telescope Interferometer (VLTI) Y. Salvad,

Superheterodyne Laser Metrology for the Very Large Telescope Interferometer (VLTI) Y. Salvad, R. Dndliker Institute of Microtechnology, University of Neuchtel, Switzerland S. Lvque European Southern Observatory, Garching bei

359 views • 16 slides

More recommend