ref 17252: Enable DEA Analysis

https://support.d4science.org/issues/17252

Updated DEA Analysis

git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/portlets/user/performfish-analytics-portlet@182246 82a268e6-3cf1-43bd-a215-b396298e98cf
This commit is contained in:
Giancarlo Panichi 2019-11-11 16:46:54 +00:00
parent e5251afac0
commit 85606139e8
6 changed files with 29 additions and 15 deletions

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@ -1 +1,4 @@
The correlation matrix is a table displaying the correlation between pairs of KPIs. Correlation coefficients are calculated using the Person parametric correlation test and coloured according to the value in red (significant positive correlation), yellow (significant negative correlation), and in light blue (non-significant correlation). The Student t-test is used to determine the ranges of correlation for Pearson coefficients.
The correlation matrix is a table displaying the correlation between pairs of KPIs.
Correlation coefficients are calculated using the Person parametric correlation test and coloured according to the value in red (significant positive correlation), yellow (significant negative correlation), and in light blue (non-significant correlation).
The Student t-test is used to determine the ranges of correlation for Pearson coefficients.
The analysis is performed on all batches data.

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@ -2,4 +2,5 @@ DEA is an analytical non-parametric technique used to benchmark the performance
1) A TE chart displaying the efficiency curve, which shows the KPIs performance (outputs) given the inputs. If there is more than one input or output, summed values are displayed;
2) TE statistics for all batches data in the VRE, reporting the number of batches in several TE ranges;
3) Measurements of TE per user's batch.
The analysis is performed on all batches data.
Reference: Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.

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@ -1 +1,4 @@
The correlation matrix is a table displaying the correlation between pairs of KPIs. Correlation coefficients are calculated using the Person parametric correlation test and coloured according to the value in red (significant positive correlation), yellow (significant negative correlation), and in light blue (non-significant correlation). The Student t-test is used to determine the ranges of correlation for Pearson coefficients.
The correlation matrix is a table displaying the correlation between pairs of KPIs.
Correlation coefficients are calculated using the Person parametric correlation test and coloured according to the value in red (significant positive correlation), yellow (significant negative correlation), and in light blue (non-significant correlation).
The Student t-test is used to determine the ranges of correlation for Pearson coefficients.
The analysis is performed on all farm data.

View File

@ -2,4 +2,5 @@ DEA is an analytical non-parametric technique used to benchmark the performance
1) A TE chart displaying the efficiency curve, which shows the KPIs performance (outputs) given the inputs. If there is more than one input or output, summed values are displayed;
2) TE statistics for all farm data in the VRE, reporting the number of farms in several TE ranges;
3) Measurements of TE for the user's farm.
The analysis is performed on all farm data.
Reference: Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.

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@ -636,9 +636,9 @@ public class DeaAnnualPanelResult extends Composite {
/////
flexTable.setWidget(0, 0, new HTML("Selected Input KPI:"));
flexTable.setWidget(0, 0, new HTML("Selected Input KPIs:"));
flexTable.setWidget(0, 1, new HTML(stringInputKPINamesBuilder.toString()));
flexTable.setWidget(1, 0, new HTML("Selected Output KPI:"));
flexTable.setWidget(1, 0, new HTML("Selected Output KPIs:"));
flexTable.setWidget(1, 1, new HTML(stringOutputKPINamesBuilder.toString()));
flexTable.addStyleName("the_margin_top_bottom");
@ -676,8 +676,11 @@ public class DeaAnnualPanelResult extends Composite {
List<KPI> inputKPIs, List<KPI> outputKPIs, final String focusID, final Panel container,
boolean displayError) {
String title = displayError ? "No results " : "";
title += chartType.getTitle();
//title += chartType.getTitle();
/*
title += inputKPIs.size() > 1 ? " [Input KPIs: " : " [Input KPI: ";
for (KPI kpi : inputKPIs) {
@ -692,7 +695,7 @@ public class DeaAnnualPanelResult extends Composite {
title += " " + kpi.getName() + ",";
}
title = title.substring(0, title.length() - 1) + "]";
}
}*/
if (displayError) {
Alert alert = new Alert(title);
@ -771,10 +774,10 @@ public class DeaAnnualPanelResult extends Composite {
if (outputName.contains("dea")) {
flexTable.setWidget(0, 0, showResult);
} else {
if (outputName.contains("efficiency_aggregated")) {
if (outputName.contains("efficiency_legend")) {
flexTable.setWidget(1, 0, showResult);
} else {
if (outputName.contains("efficiency_legend")) {
if (outputName.contains("efficiency_aggregated")) {
flexTable.setWidget(2, 0, showResult);
} else {
if (outputName.contains("efficiency_per_id")) {

View File

@ -639,9 +639,9 @@ public class DeaPanelResult extends Composite {
/////
flexTable.setWidget(0, 0, new HTML("Selected Input KPI:"));
flexTable.setWidget(0, 0, new HTML("Selected Input KPIs:"));
flexTable.setWidget(0, 1, new HTML(stringInputKPINamesBuilder.toString()));
flexTable.setWidget(1, 0, new HTML("Selected Output KPI:"));
flexTable.setWidget(1, 0, new HTML("Selected Output KPIs:"));
flexTable.setWidget(1, 1, new HTML(stringOutputKPINamesBuilder.toString()));
flexTable.addStyleName("the_margin_top_bottom");
@ -678,8 +678,11 @@ public class DeaPanelResult extends Composite {
boolean displayError) {
String title = displayError ? "No results " : "";
title += chartType.getTitle();
title += inputKPIs.size() > 1 ? " [Input KPIs: " : " [Input KPI: ";
//title += chartType.getTitle();
/*
title += inputKPIs.size() > 1 ? " [Input KPIs: " : " [Input KPI: ";
for (KPI kpi : inputKPIs) {
title += " " + kpi.getName() + ",";
@ -693,7 +696,7 @@ public class DeaPanelResult extends Composite {
title += " " + kpi.getName() + ",";
}
title = title.substring(0, title.length() - 1) + "]";
}
}*/
if (displayError) {
Alert alert = new Alert(title);
@ -771,10 +774,10 @@ public class DeaPanelResult extends Composite {
if (outputName.contains("dea")) {
flexTable.setWidget(0, 0, showResult);
} else {
if (outputName.contains("efficiency_aggregated")) {
if (outputName.contains("efficiency_legend")) {
flexTable.setWidget(1, 0, showResult);
} else {
if (outputName.contains("efficiency_legend")) {
if (outputName.contains("efficiency_aggregated")) {
flexTable.setWidget(2, 0, showResult);
} else {
if (outputName.contains("efficiency_per_id")) {