Linear regression is often used to estimate the relationship between two variables – basically by drawing the ‘line of best fit’ on a graph. The mathematical method that is used for this is known as Least Squares, and aims to minimise the sum of the squared error for each point. The key question here is how do […]
I bought a new laptop recently, and just realised that I hadn’t installed two great IPython extensions that I always try to install whenever I set up a new IPython environment – so I thought I’d blog about them to let the world (well, my half-a-dozen readers) know. They’re both written by MinRK – one […]
(This is really Part 2 of IPython tips, tricks & notes – Part 1, but I thought I’d give it a more self-explanatory title) IPython (sorry, Jupyter!) notebooks are really great for interactively exploring data, and then turning your analyses into something which can easily be sent to a non-technical colleague (by adding some Markdown and […]
By time this blog post is published, I will have finished my presentation about recipy at EuroSciPy (see the abstract for my talk), and so I thought it would be a good time to introduce recipy to the wider world. I’ve been looking for something like recipy for ages – and I suggested the idea […]
During the last week, I attended the Next Generation Computational Modelling (NGCM) Summer Academy at the University of Southampton. Three days were spent on a detailed IPython course, run by MinRK, one of the core IPython developers, and two days on a Pandas course taught by Skipper Seaborn and Chris Fonnesbeck. The course was very […]
At the end of my last post I left you with a taster of what Part 2 would provide: a way of producing automatically-updating graphs of power usage over time. Part 1 was based purely on Python code that would run on any system (Windows, Linux or OS X) but this part will require a […]
After borrowing a CurrentCost electricity usage meter from my local library (if you’re in the area, then Eastleigh library will loan you one for free!), I decided to buy one, as I’d found it very useful in trying to reduce my electricity usage. The benefit of buying one as opposed to borrowing one was that […]
Summary: Fascinating book covering the whole breadth of high performance Python. It starts with detailed discussion of various profiling methods, continues with chapters on performance in standard Python, then focuses on high performance using arrays, compiling to C and various approaches to parallel programming. I learnt a lot from the book, and have already started improving […]
The last few months have seen a flurry of activity in Py6S – probably caused by procrastinating from working on my PhD thesis! Anyway, I thought it was about time that I summarised the various updates and new features which have been released, and gave a few more details on how to use them. These […]
As part of my PhD I’ve developed a number of algorithms which are implemented as a class in Python code. An example would be something like this: class Algorithm: def __init__(self, input_filename, output_basename, thresh, n_iter=10): self.input_filename = input_filename self.output_basename = output_basename self.thresh = thresh self.n_iter = n_iter def run(self): self.preprocess() self.do_iterations() self.postprocess() def preprocess(self): # […]