Authors / CoAuthors
Newey, V. | Gray, D.
Abstract
Geoscience Australia has developed a number of open source risk models to estimate hazard, damage or financial loss to residential communities from natural hazards and is used to underpin disaster risk reduction activities. Two of these models will be discussed here: the Earthquake Risk Model (EQRM) and a hydrodynamic model call ANUGA, developed in collaboratoin with the ANU. Both models have been developed in Python using scientific and GIS packages such as Shapely, Numeric and SciPy. This presentation will outline key lessons learnt in developing scientific software in Python. Methods of maintaining and accessing code quality will be discussed (1) what makes a good unit test (2) how defects in the code were discovered quickly by being able to visualise the output data; and (3) how characterisation tests, which describe the actual behaviour of a system, are useful for finding unintended system changes. The challenges involved in optimising and parallelising Python code will also be presented. This is particularly important in scientific simulations as they use considerable computational resources and involve large data sets. This will be focus on: profiling; NumPyl using C code; and parallelisation of applications to run on clusters. Reduction of memory use by using a class to represent a group of items instead of a single item will also be discussed.
Product Type
nonGeographicDataset
eCat Id
73749
Contact for the resource
Custodian
Point of contact
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Keywords
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- External Publication
- ( Theme )
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- numerical modelling
- Australian and New Zealand Standard Research Classification (ANZSRC)
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- Earth Sciences
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- Published_Internal
Publication Date
2012-03-01T00:00:00
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geoscientificInformation
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