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seadatanet-connector
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git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/data-analysis/SeaDataNetConnector@120158 82a268e6-3cf1-43bd-a215-b396298e98cf

This commit is contained in:
Gianpaolo Coro 2015-11-02 10:28:55 +00:00
parent bfad8e562a
commit 05c7b0a0c8
2 changed files with 4 additions and 4 deletions
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2
src/org/gcube/dataanalysis/seadatanet/DivaHTTPClient.java
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@ -211,7 +211,7 @@ public class DivaHTTPClient {
try{ try{
obs_count=Integer.parseInt(root.getChildNodes().item(1).getTextContent()); obs_count=Integer.parseInt(root.getChildNodes().item(1).getTextContent());
}catch(NullPointerException pe ){ }catch(NullPointerException pe ){
throw new Exception("Error in uploading file to DIVA!"); throw new Exception("Error in uploading file to DIVA - Possibly non uniformly filled table!");
} }
Double obs_x0=Double.parseDouble(root.getChildNodes().item(3).getTextContent()); Double obs_x0=Double.parseDouble(root.getChildNodes().item(3).getTextContent());
Double obs_x1=Double.parseDouble(root.getChildNodes().item(5).getTextContent()); Double obs_x1=Double.parseDouble(root.getChildNodes().item(5).getTextContent());

6
src/org/gcube/dataanalysis/seadatanet/SeaDataNetConnector.java
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@ -42,7 +42,7 @@ public class SeaDataNetConnector extends StandardLocalExternalAlgorithm {
//->adjusted description with proper citation //->adjusted description with proper citation
return "A connector for the SeaDataNet infrastructure. This algorithms invokes the Data-Interpolating Variational Analysis (DIVA) SeaDataNet service to interpolate spatial data. " + return "A connector for the SeaDataNet infrastructure. This algorithms invokes the Data-Interpolating Variational Analysis (DIVA) SeaDataNet service to interpolate spatial data. " +
"The model uses GEBCO bathymetry data and requires an estimate of the maximum spatial span of the correlation between points and the signal-to-noise ratio, among the other parameters. " + "The model uses GEBCO bathymetry data and requires an estimate of the maximum spatial span of the correlation between points and the signal-to-noise ratio, among the other parameters. " +
"It can interpolate up to 100,000 points randomly taken from the input table. " + "It can interpolate up to 10,000 points randomly taken from the input table. " +
"As output, it produces a NetCDF file with a uniform grid of values. " + "As output, it produces a NetCDF file with a uniform grid of values. " +
"This powerful interpolation model is described in Troupin et al. 2012, 'Generation of analysis and consistent error fields using the Data Interpolating Variational Analysis (Diva)', Ocean Modelling, 52-53, 90-101."; "This powerful interpolation model is described in Troupin et al. 2012, 'Generation of analysis and consistent error fields using the Data Interpolating Variational Analysis (Diva)', Ocean Modelling, 52-53, 90-101.";
} }
@ -128,7 +128,7 @@ public class SeaDataNetConnector extends StandardLocalExternalAlgorithm {
//->set limit to 100 000 - maximum allowed by DIVA //->set limit to 100 000 - maximum allowed by DIVA
String query = "select " String query = "select "
+ config.getParam("Longitude") + "," + config.getParam("Latitude") + "," + config.getParam("Quantity") + " From " + getInputParameter("InputTable") + + config.getParam("Longitude") + "," + config.getParam("Latitude") + "," + config.getParam("Quantity") + " From " + getInputParameter("InputTable") +
" ORDER BY RANDOM() limit 100000"; " ORDER BY RANDOM() limit 10000";
//->indicate the status of the computation //->indicate the status of the computation
status = 10; status = 10;
AnalysisLogger.getLogger().debug("Query for extracting data from the DB: " + query); AnalysisLogger.getLogger().debug("Query for extracting data from the DB: " + query);
@ -192,7 +192,7 @@ public class SeaDataNetConnector extends StandardLocalExternalAlgorithm {
List<TableTemplates> templates = new ArrayList<TableTemplates>(); List<TableTemplates> templates = new ArrayList<TableTemplates>();
templates.add(TableTemplates.GENERIC); templates.add(TableTemplates.GENERIC);
InputTable tinput = new InputTable(templates, "InputTable", "Input tabular resource. Up to 100,000 points will be randomly taken from this table."); InputTable tinput = new InputTable(templates, "InputTable", "Input tabular resource. Up to 10,000 points will be randomly taken from this table.");
inputs.add(tinput); inputs.add(tinput);