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Part 11c: Finer Control for Parallel Computing in IPython
Category: Languages > Python      Posted: 22 Jun 09

In this segment, we discuss the push, pull, and push_function, features of IPython that allow finer control over individual namespaces of remote nodes and over the computations that run on them.

Part 11b: Distributing Parallel Computations Using IPython
Category: Languages > Python      Posted: 22 Jun 09

In this segment, we discuss the map feature to distribute computations across the available nodes, how to use targets to specify which nodes to use, and how to use blocking to avoid waiting for long computations to finish.

Part 11a: Basic Parallel Computing Using IPython
Category: Languages > Python      Posted: 22 Jun 09

In this segment, we discuss cover importing modules for the remote nodes and how to distribute data (i.e. scatter, gather) to and from these nodes.

Part 11: Getting Started with Parallel IPython
Category: Languages > Python      Posted: 22 Jun 09

IPython provides excellent interactive parallel computing tools. In this segment, we discuss how to set up remote computational engines using ipcluster and how to use special magic commands in IPython to use these remote engines.

Here we show how to run the IPython interpreter on the Wind...

Part 10: Getting started with Matplotlib
Category: Languages > Python      Posted: 21 Jun 09

Matplotlib is one of the best, if not the best, plotting package for scientific Python. In this segment, we discuss how to best use the Matplotlib website to get started with plotting with Matplotlib.

Part 9: Introducing Sympy -- symbolic computing in Python
Category: Languages > Python      Posted: 21 Jun 09

Introducing Sympy
-- manipulating expressions
-- defining functions
-- lambdify

Part 8: Profiling in IPython
Category: Languages > Python      Posted: 21 Jun 09

We discuss the following profiling methods:
using %time
using %prun

Part 7: Debugging using IPython
Category: Languages > Python      Posted: 21 Jun 09

We discuss the following debugging methods: , using %run -d -b , using %pdb to catch errors, using pdb.set_trace() in source code

Part 6: Python Language Features for Large Data Sets
Category: Languages > Python      Posted: 21 Jun 09

Here we discuss how generators can be used to process large data sets, which may be too resource-consuming to pull into memory all at once. We further introduce the itertools module as a way of extending the functionality of generators

Part 5: Using doctest and docstrings in customized classes
Category: Languages > Python      Posted: 21 Jun 09

In this segment, we continue with our example of subclassing objects from the scipy module and we discuss how to set up and use docstrings and doctests to provide documentation and testing

Part 4: Subclassing and using the Python language for scientific computing
Category: Languages > Python      Posted: 21 Jun 09

In this segment, we discuss how to subclass an existing object from the scipy module, how to use an external editor with IPython, and how to add customized functions to an existing object

Part 3: Using on-line documentation for a short case study on computing integrals
Category: Languages > Python      Posted: 21 Jun 09

Scipy and numpy are too vast to discuss their constituent components. Instead, we take a simple case study where we want to compute the integral of sampled data and illustrate how to use the on-line documentation effectively.