Monthly Archives: September 2009

Upcoming EPD webinar: How do I… process signals with EPD?

One of the useful tools in the the Enthought Python Distribution (EPD) is the signal processing module of SciPy. In this webinar we will demonstrate how to analyze and process signals using the Fast Fourier Transform (FFT), and the tools in scipy.signal. Topics to be covered include designing and applying time-domain and frequency-domain filters, down-sampling data, and dealing with data streams by processing chunks at a time while handling edge-effects.

As usual, all EPD subscribers at a basic level or above will be emailed the registration link and guaranteed a seat at the webinar. Non-subscribers will be granted access on a first-come, first-served basis by adding their names to the waiting listhere.

This has been a favorite topic in our private training courses, so we’re excited to present it to a wider audience. Hope to see you there!

Enthought Python Distribution Webinar

How do I process signals with EPD?

October 2, 2009
1pm CDT(6pm UTC)

waiting list

Next Webinar: Regression analysis in NumPy/SciPy

September is well upon us and it looks like it’s already time for another Scientific Computing with Python webinar. Next week, Travis Oliphant will be hosting a presentation on regression analysis in NumPy and SciPy. As you are probably aware, Travis was the primary developer of NumPy, so we’re fortunate to have him presenting these tools. Here’s a word on what to expect Friday:

A common scientific and engineering need is to find the parameters to a model that best fit a particular data set. A large number of techniques and tools have been created for assisting with this general problem. They vary based on the model (e.g. linear or nonlinear), the characteristics of the errors on the data (e.g. weighted or un-weighted), and the error metric selected (e.g. least-squares, or absolute difference).

This webinar will provide an overview of the tools that SciPy and NumPy provide for regression analysis including linear and non-linear least-squares and a brief look at handling other error metrics. We will also demonstrate simple GUI tools that can make some problems easier and provide a quick overview of the new Scikits package statsmodels whose API is maturing in a separate package but should be incorporated into SciPy in the future.

Here’s the registration information:

Scientific Computing with Python Webinar: Regression analysis in NumPy

Friday, September 18

1pm CDT/6pm UTC

Register at GoToMeeting

Hope to see you there!