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Geophysical data analysis using Python
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DOI：10.1016/S0098-3004(01)00086-3.png)
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Abstract
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A set of routines designed for geophysical data analysis that make extensive use of the numerical extensions to the computer language Python are presented. The routines perform some typical tasks during multivariate analysis of geophysical fields, such as principal component analysis and related tasks (truncation rules by means of analytical and Monte Carlo techniques). Other functions perform singular value decomposition of covariance matrices and canonical correlation analysis for coupled variability of geophysical fields. Other parts of the package allow access to a library of statistical distribution functions, multivariate digital filters, time-handling routines, kernel-based probability density function estimation and differential operators over the sphere for gridded data sets. As they rely on the numerical extensions to the Python language. they are fast for numerical analysis. The programs make the analysis of geophysical data sets both easier and faster. (C) 2002 Elsevier Science Ltd. All rights reserved.
Keywords:
principal component analysis
digital filter
probability density function
differential operator
python
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