diff -r 7167b896d8de -r 50770620ea7f project/templates/about/tutorial.html --- a/project/templates/about/tutorial.html Sat Nov 19 13:26:28 2011 +0530 +++ b/project/templates/about/tutorial.html Thu Nov 24 09:29:05 2011 +0530 @@ -1,6 +1,46 @@ {% extends "base.html" %} {% block content %} -

Tutorials

SciPy.in 2011 Tutorial Schedule

+ +

Day 3

+ + + + ++ + + + + + + + + + + +


Time	Speaker	Title
09:00-11:00	Jarror Millman	Gig/Github + NumPy/SciPy/MPL basics
11:00-13:00	Emmanuelle Gouillart	Image processing using NumPy, SciPy and scikits-image
13:00-14:00		Lunch
14:00-16:00	Gael Varoquaux	Machine learning with scikit-learn
16:00-18:00	Mateusz Paprocki	SymPy

+ +

Day 4

+ + + + ++ + + + + + + + + + + + +


Time	Speaker	Title
09:00-11:00	Ole Nielsen	Mapping and Geoprocessing with Python
11:00-13:00	Eric Jones	Traits + Traits UI
13:00-14:00		Lunch
14:00-16:00	Prabhu Ramachandran and Gael Varoquaux	Mayavi for 3D visualization
16:00-17:00	Puneeth Chaganti	Sage introduction/tutorial
17:00-18:00	Pankaj Pandey and Prabhu Ramachandran	An introduction to Cython

Intended audience

@@ -38,7 +78,7 @@ -

Jarrod Millman, Git/Github + NumPy/SciPy/MPL basics (2 hrs)

Git/Github
NumPy and SciPy basics along with the most important Matplotlib commands. @@ -48,7 +88,7 @@ -
Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)
+
Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)
- This tutorial will show a bag of basic recipes in order to efficiently manipulate and process images in the form of NumPy arrays. @@ -81,7 +121,7 @@
-
Gael Varoquaux, Machine learning with scikit-learn (2 hrs)
+
Gael Varoquaux, Machine learning with scikit-learn (2 hrs)
- Introduction to machine learning and statistical data processing with the @@ -112,115 +152,7 @@
-
Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)
-
- - Putting information on a map and analyzing spatial data are fundamental to a - wide range of areas such as navigation, working with climate or geological data, - disaster management, presentation of modelling results, demographics, social networking etc. -
- - This tutorial will give a practical introduction to tools and techniques - available for processing spatial information and, through a few hands-on - exercises, give the participants a sense of how to manipulate and visualise - spatial data using Python. Topics covered include reading and writing - of important data formats for both raster and vector data, looking at the layers, - awareness of issues with datums and projections, calculating centroids of polygons, - calculation of distance between points on the surface of Earth, interpolation from raster - grids to points etc. The tutorial has been developed for Ubuntu Linux and will provide source code, - tests and data for this platform. However, the content and messages should be general and apply to any platform. -
- - I assume that participants know how to write and run - Python scripts and would suggest you install qgis as well as - the python dependencies numpy, matplotlib and gdal on your - laptop. I don't assume any previous knowledge of mapping or Geographic Information Systems (GIS). -
- - If you have some spatial data you want to manipulate in Python feel free to bring it along and grab me during a lunch break. -
- - -
Eric Jones/Puneeth/Pankaj: Traits + Traits UI (2 hrs)
-
- - Enthought’s traits package provides for a powerful object model which - provides a host of useful functionality with a clean and expressive syntax. - It is an open source library and forms the basis of the Enthought Tool Suite and many of - Enthought’s internal commercial projects. In this tutorial we will cover the basics of using - Traits along with the UI library TraitsUI which makes it very easy to build powerful and - interactive, user interfaces using Traits. -
- - -
Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)
-
- - At the end of this tutorial attendees will learn how to visualize numpy - arrays using Mayavi's mlab interface. They will also learn enough about - mayavi to be able to create their own simple datasets and visualize - them. If this tutorial follows one on traits, then attendees will learn - how easy it is to embed 3D visualization in their own application UIs - (provided they are written in wxPython or PyQt). -
- - In this tutorial, we first provide a rapid overview of Mayavi_ and its - features. We then move on to using Mayavi via IPython_ and mlab. This - is done in a hands-on fashion and introduces the audience to visualizing - numpy arrays and the basic mayavi visualization pipeline. We then - introduce the audience to the basic objects and data sources used in - Mayavi. We end with an example of creating custom dialogs using Traits - and embedding 3D visualization in these dialogs with Mayavi. -
- - Packages required -
  - Mayavi
  - IPython
  - Traits
  - numpy, scipy
  -
- -
Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)
-
- - At some level, Cython (http://www.cython.org) can be thought of a Python to C compiler. - It allows someone to write extension modules in a language very similar to Python and - therefore makes it rather easy to write C-extensions. In this tutorial we will cover - the basics of building extension modules with Cython. -
- - Package requirements: You will require to have Cython, the - Python development headers and a working C-compiler to run the hands-on exercises. -
- -
Puneeth Chaganti, Sage introduction/tutorial: (1 hr)
-
- This tutorial will feature a demonstration and a brief review of some of the capabilities of the Sage notebook.
- A rough schedule of the talk would be as follows: -
  - Introduction
  - Starting the server
  - The UI
  - Getting Help
  - Overview of what's available in Sage -
    - Basic Algebra
    - Basic Calculus
    - Basic Plotting
    -
  -
- - -
Mateusz Paprocki, SymPy (2 hrs)
+
Mateusz Paprocki, SymPy (2 hrs)
- SymPy is a pure Python library for symbolic mathematics. It aims to become a @@ -263,4 +195,112 @@
+
Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)
+
- + Putting information on a map and analyzing spatial data are fundamental to a + wide range of areas such as navigation, working with climate or geological data, + disaster management, presentation of modelling results, demographics, social networking etc. +
- + This tutorial will give a practical introduction to tools and techniques + available for processing spatial information and, through a few hands-on + exercises, give the participants a sense of how to manipulate and visualise + spatial data using Python. Topics covered include reading and writing + of important data formats for both raster and vector data, looking at the layers, + awareness of issues with datums and projections, calculating centroids of polygons, + calculation of distance between points on the surface of Earth, interpolation from raster + grids to points etc. The tutorial has been developed for Ubuntu Linux and will provide source code, + tests and data for this platform. However, the content and messages should be general and apply to any platform. +
- + I assume that participants know how to write and run + Python scripts and would suggest you install qgis as well as + the python dependencies numpy, matplotlib and gdal on your + laptop. I don't assume any previous knowledge of mapping or Geographic Information Systems (GIS). +
- + If you have some spatial data you want to manipulate in Python feel free to bring it along and grab me during a lunch break. +
+ + +
Eric Jones: Traits + Traits UI (2 hrs)
+
- + Enthought’s traits package provides for a powerful object model which + provides a host of useful functionality with a clean and expressive syntax. + It is an open source library and forms the basis of the Enthought Tool Suite and many of + Enthought’s internal commercial projects. In this tutorial we will cover the basics of using + Traits along with the UI library TraitsUI which makes it very easy to build powerful and + interactive, user interfaces using Traits. +
+ + +
Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)
+
- + At the end of this tutorial attendees will learn how to visualize numpy + arrays using Mayavi's mlab interface. They will also learn enough about + mayavi to be able to create their own simple datasets and visualize + them. If this tutorial follows one on traits, then attendees will learn + how easy it is to embed 3D visualization in their own application UIs + (provided they are written in wxPython or PyQt). +
- + In this tutorial, we first provide a rapid overview of Mayavi_ and its + features. We then move on to using Mayavi via IPython_ and mlab. This + is done in a hands-on fashion and introduces the audience to visualizing + numpy arrays and the basic mayavi visualization pipeline. We then + introduce the audience to the basic objects and data sources used in + Mayavi. We end with an example of creating custom dialogs using Traits + and embedding 3D visualization in these dialogs with Mayavi. +
- + Packages required +
  - Mayavi
  - IPython
  - Traits
  - numpy, scipy
  +
+ +
Puneeth Chaganti, Sage introduction/tutorial: (1 hr)
+
- This tutorial will feature a demonstration and a brief review of some of the capabilities of the Sage notebook.
- A rough schedule of the talk would be as follows: +
  - Introduction
  - Starting the server
  - The UI
  - Getting Help
  - Overview of what's available in Sage +
    - Basic Algebra
    - Basic Calculus
    - Basic Plotting
    +
  +
+ +
Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)
+
- + At some level, Cython (http://www.cython.org) can be thought of a Python to C compiler. + It allows someone to write extension modules in a language very similar to Python and + therefore makes it rather easy to write C-extensions. In this tutorial we will cover + the basics of building extension modules with Cython. +
- + Package requirements: You will require to have Cython, the + Python development headers and a working C-compiler to run the hands-on exercises. +
+ + {% endblock content %}

Tutorials

SciPy.in 2011 Tutorial Schedule

Day 3

Day 4

Intended audience

Jarrod Millman, Git/Github + NumPy/SciPy/MPL basics (2 hrs)

Jarrod Millman, Git/Github + NumPy/SciPy/MPL basics (2 hrs)

Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)

Emmanuelle Gouillart, Image processing using NumPy, SciPy and scikits-image (2 hrs)

Gael Varoquaux, Machine learning with scikit-learn (2 hrs)

Gael Varoquaux, Machine learning with scikit-learn (2 hrs)

Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)

Eric Jones/Puneeth/Pankaj: Traits + Traits UI (2 hrs)

Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)

Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)

Puneeth Chaganti, Sage introduction/tutorial: (1 hr)

Mateusz Paprocki, SymPy (2 hrs)

Mateusz Paprocki, SymPy (2 hrs)

Ole Nielsen: Mapping and Geoprocessing with Python (2 hrs)

Eric Jones: Traits + Traits UI (2 hrs)

Prabhu Ramachandran and Gael Varoquaux, Mayavi for 3D visualization (2 hrs)

Puneeth Chaganti, Sage introduction/tutorial: (1 hr)

Pankaj Pandey and Prabhu Ramachandran, An introduction to Cython (1 hrs)