You are viewing a plain text version of this content. The canonical link for it is here.
Posted to dev@climate.apache.org by "Alex Goodman (JIRA)" <ji...@apache.org> on 2013/06/18 18:42:19 UTC
[jira] [Updated] (CLIMATE-117) updates to regridding
[ https://issues.apache.org/jira/browse/CLIMATE-117?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Alex Goodman updated CLIMATE-117:
---------------------------------
Description:
Paul Loikith and I had a meeting this morning and we thought that our current regridding function could use a few improvements. Right now it only supports two interpolation schemes for uniformly spaced data: bilinear and cubic spline. Quick ways to improve it now are:
-Use mpl_toolkits.basemap.interp to do the actual interpolation instead of using our own code. This keeps our own code cleaner and also adds support for one other interpolation scheme (nearest neighbor)
-Add support for irregularly spaced grids. Thankfully this is also not too difficult to do since both matplotlib and scipy have functions that do this (scipy.interpolate.griddata and matplotlib.mlab.griddata).
was:
Paul Loikith and I had a meeting this morning and we thought that our current regridding function could use a few improvements. Right now it only supports two interpolation schemes for uniformly spaced data: bilinear and cubic spline. Ways to improve it are:
-Use mpl_toolkits.basemap.interp to do the actual interpolation instead of using our own code. This keeps our own code cleaner and also adds support for one other interpolation scheme (nearest neighbor)
-Add support for irregularly spaced grids. Thankfully this is also not too difficult to do since both matplotlib and scipy have functions that do this (scipy.interpolate.griddata and matplotlib.mlab.griddata).
-Seth McGinnis at NCAR suggests that more advanced interpolation schemes, such as Kriging, are needed for certain cases. Something like this would likely have to be coded from scratch since there are no well known python packages that have this built-in.
> updates to regridding
> ---------------------
>
> Key: CLIMATE-117
> URL: https://issues.apache.org/jira/browse/CLIMATE-117
> Project: Apache Open Climate Workbench
> Issue Type: Improvement
> Components: regridding
> Affects Versions: 0.1-incubating
> Reporter: Alex Goodman
> Assignee: Chris A. Mattmann
> Fix For: 0.1-incubating
>
>
> Paul Loikith and I had a meeting this morning and we thought that our current regridding function could use a few improvements. Right now it only supports two interpolation schemes for uniformly spaced data: bilinear and cubic spline. Quick ways to improve it now are:
> -Use mpl_toolkits.basemap.interp to do the actual interpolation instead of using our own code. This keeps our own code cleaner and also adds support for one other interpolation scheme (nearest neighbor)
> -Add support for irregularly spaced grids. Thankfully this is also not too difficult to do since both matplotlib and scipy have functions that do this (scipy.interpolate.griddata and matplotlib.mlab.griddata).
--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira