Cameron Goodale created CLIMATE-236:
---------------------------------------
Summary: Add Dataset Ensemble Support to the ocw.dataset_processor
module
Key: CLIMATE-236
URL: https://issues.apache.org/jira/browse/CLIMATE-236
Project: Apache Open Climate Workbench
Issue Type: Sub-task
Components: rcmet
Affects Versions: 0.1-incubating
Environment: *nix
Reporter: Cameron Goodale
Assignee: Cameron Goodale
Currently within the rcmes code base there is an ability to take in multiple
datasets and return an 'ensemble' dataset. This ensemble is just the mean of
all the input datasets.
The plan is to grab this code block (around line 250) from do_data_prep:
{code}
# TODO: Refactor this into a function within the toolkit module
# compute the simple multi-obs ensemble if multiple obs are used
if numOBSs > 1:
print 'numOBSs = ', numOBSs
oData = obsData
print 'oData shape = ', oData.shape
obsData = ma.zeros((numOBSs + 1, nT, ngrdY, ngrdX))
print 'obsData shape = ', obsData.shape
avg = ma.zeros((nT, ngrdY, ngrdX))
for i in np.arange(numOBSs):
obsData[i, :, :, :] = oData[i, :, :, :]
avg[:, :, :] = avg[:, :, :] + oData[i, :, :, :]
avg = avg / float(numOBSs)
obsData[numOBSs, :, :, :] = avg[:, :, :] # store the model-ensemble
data
numOBSs = numOBSs + 1 # update the number of obs
data to include the model ensemble
obsList.append('ENS-OBS')
{code}
Port all of that into a private function in dataset_processor called
_rcmes_make_dataset_ensemble() and setup the dataset_processor.ensemble()
function use it initially.
Once the code move, documentation, unit tests are all complete, then I will
resolve this issue.
--
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
