diff --git a/api/src/engine/connectors/datashield/datashield.connector.ts b/api/src/engine/connectors/datashield/datashield.connector.ts
index 244c56621dd6d018f73655df9fec142416934e21..62249ee5dadccdae77ab9c07d9a6e6ab15fdd8e5 100644
--- a/api/src/engine/connectors/datashield/datashield.connector.ts
+++ b/api/src/engine/connectors/datashield/datashield.connector.ts
@@ -1,5 +1,5 @@
import { HttpService } from '@nestjs/axios';
-import { Inject, InternalServerErrorException, Logger } from '@nestjs/common';
+import { InternalServerErrorException, Logger } from '@nestjs/common';
import { Request } from 'express';
import { catchError, firstValueFrom } from 'rxjs';
import {
@@ -7,7 +7,6 @@ import {
MIME_TYPES,
} from 'src/common/interfaces/utilities.interface';
import { errorAxiosHandler } from 'src/common/utils/shared.utils';
-import { ENGINE_MODULE_OPTIONS } from 'src/engine/engine.constants';
import EngineService from 'src/engine/engine.service';
import ConnectorConfiguration from 'src/engine/interfaces/connector-configuration.interface';
import Connector from 'src/engine/interfaces/connector.interface';
@@ -38,7 +37,7 @@ export default class DataShieldConnector implements Connector {
private static readonly logger = new Logger(DataShieldConnector.name);
headers = {};
constructor(
- @Inject(ENGINE_MODULE_OPTIONS) private readonly options: EngineOptions,
+ private readonly options: EngineOptions,
private readonly httpService: HttpService,
private readonly engineService: EngineService,
) {}
diff --git a/api/src/engine/connectors/exareme/converters.ts b/api/src/engine/connectors/exareme/converters.ts
index 86b58070bbca5bfcada6303b2ec4806b6df9ced8..a9a165184c4cd7c11103b1e1ab156354e91bddd3 100644
--- a/api/src/engine/connectors/exareme/converters.ts
+++ b/api/src/engine/connectors/exareme/converters.ts
@@ -1,31 +1,28 @@
+import { Logger } from '@nestjs/common';
import { MIME_TYPES } from 'src/common/interfaces/utilities.interface';
import { Category } from 'src/engine/models/category.model';
import { Dataset } from 'src/engine/models/dataset.model';
+import { Domain } from 'src/engine/models/domain.model';
import {
Experiment,
ExperimentStatus,
} from 'src/engine/models/experiment/experiment.model';
import { Group } from 'src/engine/models/group.model';
-import { ResultUnion } from 'src/engine/models/result/common/result-union.model';
import {
GroupResult,
GroupsResult,
} from 'src/engine/models/result/groups-result.model';
-import { HeatMapResult } from 'src/engine/models/result/heat-map-result.model';
-import { LineChartResult } from 'src/engine/models/result/line-chart-result.model';
import { RawResult } from 'src/engine/models/result/raw-result.model';
import { Variable } from 'src/engine/models/variable.model';
import { AlgorithmParamInput } from 'src/experiments/models/input/algorithm-parameter.input';
import { ExperimentCreateInput } from 'src/experiments/models/input/experiment-create.input';
+import handlers from './handlers';
import { Entity } from './interfaces/entity.interface';
import { ExperimentData } from './interfaces/experiment/experiment.interface';
-import { ResultChartExperiment } from './interfaces/experiment/result-chart-experiment.interface';
import { ResultExperiment } from './interfaces/experiment/result-experiment.interface';
import { Hierarchy } from './interfaces/hierarchy.interface';
import { VariableEntity } from './interfaces/variable-entity.interface';
import {
- dataROCToLineResult,
- dataToHeatmap,
descriptiveModelToTables,
descriptiveSingleToTables,
transformToExperiment,
@@ -80,7 +77,10 @@ const algoParamInputToData = (param: AlgorithmParamInput) => {
};
};
-export const experimentInputToData = (data: ExperimentCreateInput) => {
+export const experimentInputToData = (
+ data: ExperimentCreateInput,
+ domains?: Domain[],
+) => {
const formula =
((data.transformations?.length > 0 || data.interactions?.length > 0) && {
single:
@@ -95,6 +95,8 @@ export const experimentInputToData = (data: ExperimentCreateInput) => {
}) ||
null;
+ const domain = domains?.find((d) => d.id === data.domain);
+
const params = {
algorithm: {
parameters: [
@@ -106,12 +108,14 @@ export const experimentInputToData = (data: ExperimentCreateInput) => {
{
name: 'filter',
label: 'filter',
- value: data.filter,
+ value: data.filter ?? '',
},
{
name: 'pathology',
label: 'pathology',
- value: data.domain,
+ value: domain.version
+ ? `${data.domain}:${domain.version}`
+ : data.domain,
},
...(formula
? [
@@ -205,6 +209,8 @@ export const descriptiveDataToTableResult = (
export const dataToExperiment = (
data: ExperimentData,
+ logger: Logger,
+ domains?: Domain[],
): Experiment | undefined => {
try {
const expTransform = transformToExperiment.evaluate(data);
@@ -214,12 +220,10 @@ export const dataToExperiment = (
results: [],
};
- exp.results = data.result
- ? data.result
- .map((result) => dataToResult(result, exp.algorithm.name))
- .filter((r) => r.length > 0)
- .flat()
- : [];
+ const domain = domains?.find((d) => d.id === exp.domain);
+
+ if (data && data.result && data.result.length)
+ handlers(exp, data.result, domain);
const allVariables = exp.filterVariables || [];
@@ -242,6 +246,8 @@ export const dataToExperiment = (
return exp;
} catch (e) {
+ logger.error('Error parsing experiment', data.uuid);
+ logger.debug(e);
return {
id: data.uuid,
name: data.name,
@@ -280,46 +286,3 @@ export const dataToRaw = (
},
];
};
-
-export const dataToResult = (
- result: ResultExperiment,
- algo: string,
-): Array<typeof ResultUnion> => {
- switch (result.type.toLowerCase()) {
- case 'application/json':
- return dataJSONtoResult(result, algo);
- case 'application/vnd.highcharts+json':
- return dataHighchartToResult(result as ResultChartExperiment, algo);
- default:
- return dataToRaw(algo, result);
- }
-};
-
-export const dataJSONtoResult = (
- result: ResultExperiment,
- algo: string,
-): Array<typeof ResultUnion> => {
- switch (algo.toLowerCase()) {
- case 'cart':
- case 'id3':
- return dataToRaw(algo, result);
- case 'descriptive_stats':
- return descriptiveDataToTableResult(result);
- default:
- return [];
- }
-};
-
-export const dataHighchartToResult = (
- result: ResultChartExperiment,
- algo: string,
-): Array<typeof ResultUnion> => {
- switch (result.data.chart.type) {
- case 'heatmap':
- return [dataToHeatmap.evaluate(result) as HeatMapResult];
- case 'area':
- return [dataROCToLineResult.evaluate(result) as LineChartResult];
- default:
- return dataToRaw(algo, result);
- }
-};
diff --git a/api/src/engine/connectors/exareme/exareme.connector.ts b/api/src/engine/connectors/exareme/exareme.connector.ts
index 8fd464d61c773e7061bee76e8c1271fad324cfa6..51b4c3f77417689c32ee879c5d1c63ae9c9001c8 100644
--- a/api/src/engine/connectors/exareme/exareme.connector.ts
+++ b/api/src/engine/connectors/exareme/exareme.connector.ts
@@ -3,14 +3,14 @@ import {
BadRequestException,
HttpException,
HttpStatus,
- Inject,
Injectable,
InternalServerErrorException,
+ Logger,
} from '@nestjs/common';
import { AxiosRequestConfig } from 'axios';
import { Request } from 'express';
import { firstValueFrom, map, Observable } from 'rxjs';
-import { ENGINE_MODULE_OPTIONS } from 'src/engine/engine.constants';
+import EngineService from 'src/engine/engine.service';
import ConnectorConfiguration from 'src/engine/interfaces/connector-configuration.interface';
import Connector from 'src/engine/interfaces/connector.interface';
import EngineOptions from 'src/engine/interfaces/engine-options.interface';
@@ -46,9 +46,12 @@ type Headers = Record<string, string>;
@Injectable()
export default class ExaremeConnector implements Connector {
+ private static readonly logger = new Logger(ExaremeConnector.name);
+
constructor(
- @Inject(ENGINE_MODULE_OPTIONS) private readonly options: EngineOptions,
+ private readonly options: EngineOptions,
private readonly httpService: HttpService,
+ private readonly engineService: EngineService,
) {}
async getFormulaConfiguration(): Promise<FormulaOperation[]> {
@@ -82,7 +85,9 @@ export default class ExaremeConnector implements Connector {
isTransient = false,
request: Request,
): Promise<Experiment> {
- const form = experimentInputToData(data);
+ const domains = await this.engineService.getDomains(request);
+
+ const form = experimentInputToData(data, domains);
const path =
this.options.baseurl + `experiments${isTransient ? '/transient' : ''}`;
@@ -91,7 +96,7 @@ export default class ExaremeConnector implements Connector {
this.post<ExperimentData>(request, path, form),
);
- return dataToExperiment(resultAPI.data);
+ return dataToExperiment(resultAPI.data, ExaremeConnector.logger, domains);
}
async listExperiments(
@@ -109,7 +114,10 @@ export default class ExaremeConnector implements Connector {
return {
...resultAPI.data,
- experiments: resultAPI.data.experiments?.map(dataToExperiment) ?? [],
+ experiments:
+ resultAPI.data.experiments?.map((exp) =>
+ dataToExperiment(exp, ExaremeConnector.logger),
+ ) ?? [],
};
}
@@ -120,6 +128,7 @@ export default class ExaremeConnector implements Connector {
return transformToAlgorithms.evaluate(resultAPI.data);
}
+
async getExperiment(id: string, request: Request): Promise<Experiment> {
const path = this.options.baseurl + `experiments/${id}`;
@@ -127,7 +136,9 @@ export default class ExaremeConnector implements Connector {
this.get<ExperimentData>(request, path),
);
- return dataToExperiment(resultAPI.data);
+ const domains = await this.engineService.getDomains(request);
+
+ return dataToExperiment(resultAPI.data, ExaremeConnector.logger, domains);
}
async editExperiment(
@@ -141,7 +152,9 @@ export default class ExaremeConnector implements Connector {
this.patch<ExperimentData>(request, path, expriment),
);
- return dataToExperiment(resultAPI.data);
+ const domains = await this.engineService.getDomains(request);
+
+ return dataToExperiment(resultAPI.data, ExaremeConnector.logger, domains);
}
async removeExperiment(
@@ -173,6 +186,7 @@ export default class ExaremeConnector implements Connector {
return {
id: d.code,
label: d.label,
+ version: d.version,
groups: groups,
rootGroup: dataToGroup(d.metadataHierarchy),
datasets: d.datasets ? d.datasets.map(dataToDataset) : [],
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.spec.ts b/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.spec.ts
index d2a299b68ae5de8399e3c4116548d2303a04e971..fd0a46d6d38f19e9dfac67bf3ec798431ff503a8 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.spec.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.spec.ts
@@ -24,15 +24,15 @@ const createExperiment = (): Experiment => ({
results: [],
});
-describe('PCA result handler', () => {
- const data = {
+const data = [
+ {
n_obs: 920,
- eigen_vals: [
+ eigenvalues: [
4.355128575368841, 1.0450017532423244, 0.7421875389691931,
0.5621334410413102, 0.4449774285333259, 0.3926006044635884,
0.24709792171717856, 0.2195778509188677,
],
- eigen_vecs: [
+ eigenvectors: [
[
-0.39801260415007417, -0.408618968170694, -0.005388160172392957,
-0.39520225162483835, -0.34101372698341037, -0.3857891852309699,
@@ -74,27 +74,27 @@ describe('PCA result handler', () => {
0.29263999750747904, -0.009909769193655195,
],
],
- };
+ },
+];
+describe('PCA result handler', () => {
it('Test PCA handler with regular data (no edge cases)', () => {
const exp = createExperiment();
handlers(exp, data, null);
expect(exp.results.length).toBeGreaterThanOrEqual(2);
- exp.results.forEach((it) => {
- if (it['matrix']) {
- const heatmap = it as HeatMapResult;
- const matrix = data.eigen_vecs[0].map(
- (_, i) => data.eigen_vecs.map((row) => row[i]), // reverse matrix as we want row-major order
+ exp.results.forEach((result) => {
+ if (result['matrix']) {
+ const heatmap = result as HeatMapResult;
+ const matrix = data[0].eigenvectors[0].map(
+ (_, i) => data[0].eigenvectors.map((row) => row[i]), // reverse matrix as we want row-major order
);
expect(heatmap.matrix).toEqual(matrix);
expect(heatmap.yAxis.categories).toEqual(exp.variables);
}
- });
- exp.results.forEach((it) => {
- if (it['barValues']) {
- const barchart = it as BarChartResult;
- expect(barchart.barValues).toEqual(data.eigen_vals);
+ if (result['barValues']) {
+ const barchart = result as BarChartResult;
+ expect(barchart.barValues).toEqual(data[0].eigenvalues);
}
});
});
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.ts
index 61f82be6593f6165326387e228971236679e1d84..32f08a02deb817ca2078c07774e39ac06a26f041 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/PCA.handler.ts
@@ -1,20 +1,32 @@
+import { Domain } from 'src/engine/models/domain.model';
import { Experiment } from '../../../../models/experiment/experiment.model';
import { BarChartResult } from '../../../../models/result/bar-chart-result.model';
-import { HeatMapResult } from '../../../../models/result/heat-map-result.model';
+import {
+ HeatMapResult,
+ HeatMapStyle,
+} from '../../../../models/result/heat-map-result.model';
import BaseHandler from '../base.handler';
export default class PCAHandler extends BaseHandler {
- canHandle(algorithm: string): boolean {
- return algorithm.toLocaleLowerCase() === 'pca';
+ canHandle(algorithm: string, data: any): boolean {
+ return (
+ algorithm.toLowerCase() === 'pca' &&
+ data &&
+ data[0] &&
+ data[0]['eigenvalues'] &&
+ data[0]['eigenvectors']
+ );
}
- handle(exp: Experiment, data: unknown): void {
- if (!this.canHandle(exp.algorithm.name))
- return this.next?.handle(exp, data);
+ handle(exp: Experiment, data: any, domain?: Domain): void {
+ if (!this.canHandle(exp.algorithm.name, data))
+ return this.next?.handle(exp, data, domain);
+
+ const extractedData = data[0];
const barChar: BarChartResult = {
name: 'Eigen values',
- barValues: data['eigen_vals'],
+ barValues: extractedData['eigenvalues'],
xAxis: {
label: 'Dimensions',
categories: exp.variables.map((_, i) => i + 1).map(String),
@@ -28,11 +40,12 @@ export default class PCAHandler extends BaseHandler {
if (barChar.barValues && barChar.barValues.length > 0)
exp.results.push(barChar);
- const matrix = data['eigen_vecs'] as number[][];
+ const matrix = extractedData['eigenvectors'] as number[][];
const heatMapChart: HeatMapResult = {
name: 'Eigen vectors',
matrix,
+ heatMapStyle: HeatMapStyle.BUBBLE,
yAxis: {
categories: exp.variables,
},
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.spec.ts b/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.spec.ts
index 0de41ca99cd43c14bfb389c58ee28934dcb49f78..a251a54ec784afdb775ac0e7f8073bd96d2763d2 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.spec.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.spec.ts
@@ -6,7 +6,7 @@ const createExperiment = (): Experiment => ({
id: 'dummy-id',
name: 'Testing purpose',
algorithm: {
- name: 'Anova_OnEway',
+ name: 'one_way_ANOVA',
},
datasets: ['desd-synthdata'],
domain: 'dementia',
@@ -15,19 +15,20 @@ const createExperiment = (): Experiment => ({
results: [],
});
-describe('Anova oneway result handler', () => {
- const anovaHandler = new AnovaOneWayHandler();
- const data = {
- x_label: 'Variable X',
- y_label: 'Variable Y',
- df_residual: 1424.0,
- df_explained: 3.0,
- ss_residual: 1941.1517872154072,
- ss_explained: 23.52938815624377,
- ms_residual: 1.3631683898984601,
- ms_explained: 7.843129385414589,
- p_value: 0.0006542139533101455,
- f_stat: 5.753602741623733,
+const data = [
+ {
+ anova_table: {
+ x_label: 'Variable X',
+ y_label: 'Variable Y',
+ df_residual: 1424.0,
+ df_explained: 3.0,
+ ss_residual: 1941.1517872154072,
+ ss_explained: 23.52938815624377,
+ ms_residual: 1.3631683898984601,
+ ms_explained: 7.843129385414589,
+ p_value: 0.0006542139533101455,
+ f_stat: 5.753602741623733,
+ },
tuckey_test: [
{
groupA: 'GENPD',
@@ -90,22 +91,11 @@ describe('Anova oneway result handler', () => {
p_tuckey: 0.02355122851783331,
},
],
- min_per_group: [
- {
- GENPD: 7.2276,
- HC: 7.2107,
- PD: 7.0258,
- PRODROMA: 6.3771,
- },
- ],
- max_per_group: [
- {
- GENPD: 13.7312,
- HC: 14.52,
- PD: 14.4812,
- PRODROMA: 12.3572,
- },
- ],
+ min_max_per_group: {
+ categories: ['GENPD', 'HC, PD', 'PRODROMA'],
+ min: [2.6377, 8.4133, 2.6377, 8.4133],
+ max: [61.1428, 66.8592, 2.6377, 8.4133],
+ },
ci_info: {
sample_stds: {
GENPD: 1.2338388511229372,
@@ -132,13 +122,17 @@ describe('Anova oneway result handler', () => {
PRODROMA: 11.35849951898973,
},
},
- };
+ },
+];
+
+describe('Anova oneway result handler', () => {
+ const anovaHandler = new AnovaOneWayHandler();
it('Test anova 1 way handler', () => {
const exp = createExperiment();
- const table1 = anovaHandler.getSummaryTable(data, exp.coVariables[0]);
- const table2 = anovaHandler.getTuckeyTable(data);
- const meanPlot = anovaHandler.getMeanPlot(data);
+ const table1 = anovaHandler.getSummaryTable(data[0], exp.coVariables[0]);
+ const table2 = anovaHandler.getTuckeyTable(data[0]);
+ const meanPlot = anovaHandler.getMeanPlot(data[0]);
handlers(exp, data, null);
@@ -153,7 +147,7 @@ describe('Anova oneway result handler', () => {
expect(meanPlot.pointCIs.length).toBeGreaterThan(1);
expect(meanPlot.name).toEqual(
- `Mean Plot: ${data.y_label} ~ ${data.x_label}`,
+ `Mean Plot: ${data[0].anova_table.y_label} ~ ${data[0].anova_table.x_label}`,
);
});
});
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.ts
index d52d088f9234d00d5aa06329b9d7d49e71a002a8..97880671b9bd5e1cacf3d86494ae1dc7df82a4a3 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/anova-one-way.handler.ts
@@ -8,6 +8,8 @@ import {
} from '../../../../models/result/table-result.model';
import BaseHandler from '../base.handler';
+const ALGO_NAME = 'one_way_anova';
+
export default class AnovaOneWayHandler extends BaseHandler {
private static readonly tuckeyTransform = jsonata(`
{
@@ -22,7 +24,7 @@ export default class AnovaOneWayHandler extends BaseHandler {
{"name": 'T value', "type": 'string'},
{"name": 'P value', "type": 'string'}
],
- "data": tuckey_test.[$.groupA, $.groupB, $.meanA, $.meanB, $.diff, $.se, $.t_stat, $.p_tuckey]
+ "data": tuckey_test.[$.groupA, $.groupB, $.meanA, $.meanB, $.diff, $.se, $.t_stat, $.p_tuckey][]
}
`);
@@ -30,24 +32,24 @@ export default class AnovaOneWayHandler extends BaseHandler {
(
$cats:= $keys(ci_info.means);
{
- "name": "Mean Plot: " & y_label & ' ~ ' & x_label,
+ "name": "Mean Plot: " & anova_table.y_label & ' ~ ' & anova_table.x_label,
"xAxis": {
- "label": x_label,
+ "label": anova_table.x_label,
"categories": $cats
},
"yAxis": {
- "label": '95% CI: ' & y_label
+ "label": '95% CI: ' & anova_table.y_label
},
- "pointCIs": $cats.[{
+ "pointCIs": $cats.{
"min": $lookup($$.ci_info.'m-s', $),
"mean": $lookup($$.ci_info.means, $),
"max": $lookup($$.ci_info.'m+s', $)
- }]
+ }[]
})
`);
canHandle(algorithm: string): boolean {
- return algorithm.toLocaleLowerCase() === 'anova_oneway';
+ return algorithm.toLocaleLowerCase() === ALGO_NAME;
}
getTuckeyTable(data: unknown): TableResult | undefined {
@@ -57,7 +59,7 @@ export default class AnovaOneWayHandler extends BaseHandler {
const tableResult: TableResult = {
...tableData,
- tableStyle: TableStyle.NORMAL,
+ tableStyle: TableStyle.DEFAULT,
} as unknown as TableResult;
return tableResult;
@@ -65,8 +67,8 @@ export default class AnovaOneWayHandler extends BaseHandler {
getSummaryTable(data: unknown, varname: string): TableResult | undefined {
const tableSummary: TableResult = {
- name: 'Annova summary',
- tableStyle: TableStyle.NORMAL,
+ name: 'Anova summary',
+ tableStyle: TableStyle.DEFAULT,
headers: ['', 'DF', 'SS', 'MS', 'F ratio', 'P value'].map((name) => ({
name,
type: 'string',
@@ -74,17 +76,17 @@ export default class AnovaOneWayHandler extends BaseHandler {
data: [
[
varname,
- data['df_explained'],
- data['ss_explained'],
- data['ms_explained'],
- data['p_value'],
- data['f_stat'],
+ data['anova_table']['df_explained'],
+ data['anova_table']['ss_explained'],
+ data['anova_table']['ms_explained'],
+ data['anova_table']['p_value'],
+ data['anova_table']['f_stat'],
],
[
'Residual',
- data['df_residual'],
- data['ss_residual'],
- data['ms_residual'],
+ data['anova_table']['df_residual'],
+ data['anova_table']['ss_residual'],
+ data['anova_table']['ms_residual'],
'',
'',
],
@@ -94,23 +96,25 @@ export default class AnovaOneWayHandler extends BaseHandler {
return tableSummary;
}
- getMeanPlot(data: unknown): MeanChartResult {
+ getMeanPlot(data: any): MeanChartResult {
return AnovaOneWayHandler.meanPlotTransform.evaluate(data);
}
- handle(exp: Experiment, data: unknown, domain: Domain): void {
+ handle(exp: Experiment, data: any, domain: Domain): void {
+ if (!data || data.length === 0) return super.handle(exp, data, domain);
+
if (!this.canHandle(exp.algorithm.name))
return super.handle(exp, data, domain);
- const summaryTable = this.getSummaryTable(data, exp.coVariables[0]);
+ const result = data[0];
+
+ const summaryTable = this.getSummaryTable(result, exp.coVariables[0]);
if (summaryTable) exp.results.push(summaryTable);
- const tuckeyTable = this.getTuckeyTable(data);
+ const tuckeyTable = this.getTuckeyTable(result);
if (tuckeyTable) exp.results.push(tuckeyTable);
- const meanPlot = this.getMeanPlot(data);
+ const meanPlot = this.getMeanPlot(result);
if (meanPlot && meanPlot.pointCIs) exp.results.push(meanPlot);
-
- return super.handle(exp, data, domain); // continue request
}
}
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/descriptive.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/descriptive.handler.ts
index 56396522d7a5504f218f586962d44cf81ac461b3..4e51ff16e39f652caa51c743ba08cfddd46c5ce3 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/descriptive.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/descriptive.handler.ts
@@ -1,4 +1,5 @@
import * as jsonata from 'jsonata'; // old import style needed due to 'export = jsonata'
+import { Domain } from '../../../../models/domain.model';
import { Experiment } from '../../../../models/experiment/experiment.model';
import {
GroupResult,
@@ -37,6 +38,7 @@ $fn := function($o, $prefix) {
$ks := $keys($model.*.data.*[$i][$type($) = 'object']);
{
'name': $varName,
+ 'tableStyle': 1,
'headers': $append("", $keys($$.data.model)).{
'name': $,
'type': 'string'
@@ -66,6 +68,7 @@ $fn := function($o, $prefix) {
$ks := $keys($p.*.data[$type($) = 'object']);
{
'name': $keys(%)[$i],
+ 'tableStyle': 1,
'headers': $append("", $keys(*)).{
'name': $,
'type': 'string'
@@ -110,24 +113,17 @@ $fn := function($o, $prefix) {
return result;
}
- handle(exp: Experiment, data: unknown): void {
- let req = data;
+ handle(exp: Experiment, data: unknown, domain?: Domain): void {
+ if (exp.algorithm.name.toLowerCase() !== 'descriptive_stats')
+ return super.handle(exp, data, domain);
- if (exp.algorithm.name.toLowerCase() === 'descriptive_stats') {
- const inputs = data as ResultExperiment[];
+ const inputs = data as ResultExperiment[];
- if (inputs && Array.isArray(inputs)) {
- inputs
- .filter((input) => input.type === 'application/json')
- .map((input) => this.descriptiveDataToTableResult(input))
- .forEach((input) => exp.results.push(input));
-
- req = JSON.stringify(
- inputs.filter((input) => input.type !== 'application/json'),
- );
- }
+ if (inputs && Array.isArray(inputs)) {
+ inputs
+ .filter((input) => input.type === 'application/json')
+ .map((input) => this.descriptiveDataToTableResult(input))
+ .forEach((input) => exp.results.push(input));
}
-
- this.next?.handle(exp, req);
}
}
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.spec.ts b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.spec.ts
index f1a404cd7941f69101f2e59e641baedceefc6760..a2388797da8531010fbbd958421719dcdb8a87e1 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.spec.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.spec.ts
@@ -3,19 +3,21 @@ import { TableResult } from 'src/engine/models/result/table-result.model';
import { Experiment } from '../../../../models/experiment/experiment.model';
import LinearRegressionCVHandler from './linear-regression-cv.handler';
-const data = {
- dependent_var: 'leftocpoccipitalpole',
- indep_vars: [
- 'Intercept',
- 'righthippocampus',
- 'rightsogsuperioroccipitalgyrus',
- 'leftppplanumpolare',
- ],
- n_obs: [497, 498, 498, 499],
- mean_sq_error: [0.3296455054532643, 0.02930654997949175],
- r_squared: [0.5886631959286948, 0.04365853383949705],
- mean_abs_error: [0.2585157369288272, 0.019919123005319055],
-};
+const data = [
+ {
+ dependent_var: 'leftocpoccipitalpole',
+ indep_vars: [
+ 'Intercept',
+ 'righthippocampus',
+ 'rightsogsuperioroccipitalgyrus',
+ 'leftppplanumpolare',
+ ],
+ n_obs: [497, 498, 498, 499],
+ mean_sq_error: [0.3296455054532643, 0.02930654997949175],
+ r_squared: [0.5886631959286948, 0.04365853383949705],
+ mean_abs_error: [0.2585157369288272, 0.019919123005319055],
+ },
+];
const domain: Domain = {
id: 'dummy-id',
@@ -36,7 +38,7 @@ const createExperiment = (): Experiment => ({
id: 'dummy-id',
name: 'Testing purpose',
algorithm: {
- name: 'LINEAR_REGRESSION_CROSS_VALIDATION',
+ name: 'LINEAR_REGRESSION_CV',
},
datasets: ['desd-synthdata'],
domain: 'dementia',
@@ -76,14 +78,18 @@ describe('Linear regression CV result handler', () => {
const json = JSON.stringify(experiment.results);
+ expect(experiment.results.length).toEqual(2);
+
const dataPoints = experiment.results[0] as TableResult;
const scoresData = experiment.results[1] as TableResult;
+ console.log(JSON.stringify(dataPoints));
+ console.log(JSON.stringify(scoresData));
+
expect(dataPoints.data).toStrictEqual(expectedDataPoints);
expect(scoresData.data).toStrictEqual(expectedScoresData);
expect(json.includes(domain.variables[0].label)).toBeTruthy();
- expect(experiment.results.length === 2);
});
it('Should be empty with another algo', () => {
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.ts
index 89f46631872eb16e193e5fdd14c1d0371d4a5d96..4518157f624d6d2354fdb8189fb39c351dc614e8 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression-cv.handler.ts
@@ -9,7 +9,7 @@ import {
import BaseHandler from '../base.handler';
const NUMBER_PRECISION = 4;
-const ALGO_NAME = 'linear_regression_cross_validation';
+const ALGO_NAME = 'linear_regression_cv';
const lookupDict = {
dependent_var: 'Dependent variable',
indep_vars: 'Independent variables',
@@ -23,7 +23,7 @@ export default class LinearRegressionCVHandler extends BaseHandler {
private getModel(data: any): TableResult | undefined {
return {
name: 'Data points',
- tableStyle: TableStyle.NORMAL,
+ tableStyle: TableStyle.DEFAULT,
headers: ['', `${lookupDict['n_obs']} (${data['dependent_var']})`].map(
(name) => ({ name, type: 'string' }),
),
@@ -37,7 +37,7 @@ export default class LinearRegressionCVHandler extends BaseHandler {
private getScores(data: any): TableResult | undefined {
return {
name: 'Scores',
- tableStyle: TableStyle.NORMAL,
+ tableStyle: TableStyle.DEFAULT,
headers: ['', 'Mean', 'Standard deviation'].map((name) => ({
name: name,
type: 'string',
@@ -56,14 +56,26 @@ export default class LinearRegressionCVHandler extends BaseHandler {
return varible.label ?? id;
}
+ canHandle(exp: Experiment, data: any): boolean {
+ return (
+ exp.algorithm.name.toLowerCase() === ALGO_NAME &&
+ data &&
+ data[0] &&
+ data[0].mean_sq_error &&
+ data[0].r_squared
+ );
+ }
+
handle(experiment: Experiment, data: any, domain: Domain): void {
- if (experiment.algorithm.name.toLowerCase() !== ALGO_NAME)
+ if (!this.canHandle(experiment, data))
return super.handle(experiment, data, domain);
+ const extractedData = data[0];
+
const varIds = [...experiment.variables, ...(experiment.coVariables ?? [])];
const variables = domain.variables.filter((v) => varIds.includes(v.id));
- let jsonData = JSON.stringify(data);
+ let jsonData = JSON.stringify(extractedData);
variables.forEach((v) => {
const regEx = new RegExp(v.id, 'gi');
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.spec.ts b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.spec.ts
index c2d6561e6268d278e3da3eed70a8264c67033ac0..04e9c0f20e4f16a0b2d571de4e991ece91101099 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.spec.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.spec.ts
@@ -2,26 +2,28 @@ import { Domain } from 'src/engine/models/domain.model';
import { Experiment } from '../../../../models/experiment/experiment.model';
import LinearRegressionHandler from './linear-regression.handler';
-const data = {
- dependent_var: 'lefthippocampus',
- n_obs: 15431,
- df_resid: 1540.0,
- df_model: 2.0,
- rse: 0.1270107560405171,
- r_squared: 0.8772983534917347,
- r_squared_adjusted: 0.8771390007040616,
- f_stat: 5505.38441342865,
- f_pvalue: 0.0,
- indep_vars: ['Intercept', 'righthippocampus', 'leftamygdala'],
- coefficients: [0.2185676251985193, 0.611894589820809, 1.0305204881766319],
- std_err: [0.029052606790014847, 0.016978263425746872, 0.05180007458246667],
- t_stats: [7.523167431352125, 36.03988078621131, 19.894189274496593],
- pvalues: [
- 9.04278019740564e-14, 8.833386164556705e-207, 1.4580450464941301e-78,
- ],
- lower_ci: [0.16158077395909892, 0.5785916308422961, 0.9289143512210847],
- upper_ci: [0.2755544764379397, 0.6451975487993219, 1.132126625132179],
-};
+const data = [
+ {
+ dependent_var: 'lefthippocampus',
+ n_obs: 15431,
+ df_resid: 1540.0,
+ df_model: 2.0,
+ rse: 0.1270107560405171,
+ r_squared: 0.8772983534917347,
+ r_squared_adjusted: 0.8771390007040616,
+ f_stat: 5505.38441342865,
+ f_pvalue: 0.0,
+ indep_vars: ['Intercept', 'righthippocampus', 'leftamygdala'],
+ coefficients: [0.2185676251985193, 0.611894589820809, 1.0305204881766319],
+ std_err: [0.029052606790014847, 0.016978263425746872, 0.05180007458246667],
+ t_stats: [7.523167431352125, 36.03988078621131, 19.894189274496593],
+ pvalues: [
+ 9.04278019740564e-14, 8.833386164556705e-207, 1.4580450464941301e-78,
+ ],
+ lower_ci: [0.16158077395909892, 0.5785916308422961, 0.9289143512210847],
+ upper_ci: [0.2755544764379397, 0.6451975487993219, 1.132126625132179],
+ },
+];
const domain: Domain = {
id: 'dummy-id',
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.ts
index b3b2801d9fa0d9fa88409786c7cd5dbfc2cef820..b58526d32447c3040571da65a6f6f138156efc00 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/linear-regression.handler.ts
@@ -34,8 +34,8 @@ export default class LinearRegressionHandler extends BaseHandler {
const excepts = ['n_obs'];
const tableModel: TableResult = {
name: 'Model',
- tableStyle: TableStyle.NORMAL,
- headers: ['', 'name', 'value'].map((name) => ({ name, type: 'string' })),
+ tableStyle: TableStyle.DEFAULT,
+ headers: ['name', 'value'].map((name) => ({ name, type: 'string' })),
data: [
'dependent_var',
'n_obs',
@@ -71,8 +71,8 @@ export default class LinearRegressionHandler extends BaseHandler {
const tableCoef: TableResult = {
name: 'Coefficients',
- tableStyle: TableStyle.NORMAL,
- headers: ['', ...keys].map((name) => ({
+ tableStyle: TableStyle.DEFAULT,
+ headers: keys.map((name) => ({
name: lookupDict[name],
type: 'string',
})),
@@ -95,18 +95,32 @@ export default class LinearRegressionHandler extends BaseHandler {
return varible.label ?? id;
}
+ canHandle(exp: Experiment, data: any): boolean {
+ return (
+ exp.algorithm.name.toLowerCase() === ALGO_NAME &&
+ data &&
+ data[0] &&
+ data[0].rse &&
+ data[0].f_stat
+ );
+ }
+
handle(experiment: Experiment, data: any, domain: Domain): void {
- if (experiment.algorithm.name.toLowerCase() !== ALGO_NAME)
+ if (!this.canHandle(experiment, data))
return super.handle(experiment, data, domain);
+ const extractedData = data[0];
+
const varIds = [...experiment.variables, ...(experiment.coVariables ?? [])];
const variables = domain.variables.filter((v) => varIds.includes(v.id));
- let jsonData = JSON.stringify(data);
+ let jsonData = JSON.stringify(extractedData);
+
variables.forEach((v) => {
const regEx = new RegExp(v.id, 'gi');
jsonData = jsonData.replaceAll(regEx, v.label);
});
+
const improvedData = JSON.parse(jsonData);
const model = this.getModel(improvedData);
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.spec.ts b/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.spec.ts
index 17abd4315ce007d48502d9924416720d50b2ba91..950298bc95046e11e80737d733b135125be63ddb 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.spec.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.spec.ts
@@ -136,7 +136,7 @@ describe('Pearson result handler', () => {
0.47221482855748664, 0.5181316725208311,
],
},
- 'p-values': {
+ p_values: {
variables: [
'leftputamen',
'leftttgtransversetemporalgyrus',
@@ -228,7 +228,7 @@ describe('Pearson result handler', () => {
7.914506269450685e-103, 6.154408322606963e-127,
],
},
- low_confidence_intervals: {
+ ci_lo: {
variables: [
'leftputamen',
'leftttgtransversetemporalgyrus',
@@ -320,7 +320,7 @@ describe('Pearson result handler', () => {
0.4329922438384865, 0.48111874424540896,
],
},
- high_confidence_intervals: {
+ ci_hi: {
variables: [
'leftputamen',
'leftttgtransversetemporalgyrus',
@@ -418,7 +418,7 @@ describe('Pearson result handler', () => {
const exp = createExperiment();
const names = [
'correlations',
- 'p-values',
+ 'p_values',
'low_confidence_intervals',
'high_confidence_intervals',
];
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.ts
index 40248088dcbb5aeff0a6b9b822d093743ed0607c..75d6610fd3434866d6d3d09c6526350c9269698e 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/pearson.handler.ts
@@ -1,5 +1,6 @@
import * as jsonata from 'jsonata'; // old import style needed due to 'export = jsonata'
import { Expression } from 'jsonata';
+import { Domain } from 'src/engine/models/domain.model';
import { Experiment } from '../../../../models/experiment/experiment.model';
import { HeatMapResult } from '../../../../models/result/heat-map-result.model';
import BaseHandler from '../base.handler';
@@ -7,16 +8,22 @@ import BaseHandler from '../base.handler';
export default class PearsonHandler extends BaseHandler {
private static readonly transform: Expression = jsonata(`
(
- $params := ['correlations', 'p-values', 'low_confidence_intervals', 'high_confidence_intervals'];
+ $params := ['correlations', 'p_values', 'ci_lo', 'ci_hi'];
+ $dictName := {
+ "correlations": "Correlations",
+ "p_values": "P values",
+ "ci_lo": 'Low confidence intervals',
+ "ci_hi": 'High confidence intervals'
+ };
$.$sift(function($v, $k) {$k in $params}).$each(function($v, $k) {
{
- 'name': $k,
+ 'name': $lookup($dictName, $k),
'xAxis': {
'categories': $v.variables
},
'yAxis': {
- 'categories': $keys($v.$sift(function($val, $key) {$key ~> /^(?!variables$)/}))
+ 'categories': $reverse($v.variables)
},
'matrix': $v.$sift(function($val, $key) {$key ~> /^(?!variables$)/}).$each(function($val, $key) {$val})[]
}
@@ -28,34 +35,28 @@ export default class PearsonHandler extends BaseHandler {
* @param {string} algorithm - The name of the algorithm to use.
* @returns a boolean value.
*/
- canHandle(algorithm: string): boolean {
- return algorithm.toLocaleLowerCase() === 'pearson';
+ canHandle(algorithm: string, data: any): boolean {
+ return (
+ algorithm.toLocaleLowerCase() === 'pearson' &&
+ data &&
+ data[0] &&
+ data[0]['correlations'] &&
+ data[0]['p_values']
+ );
}
- /**
- * If the algorithm is Pearson, then transform the data into a HeatMapResult and push it into the
- * results array
- * @param {string} algorithm - The name of the algorithm.
- * @param {unknown} data - The data that is passed to the algorithm.
- * @param {AlgoResults} res - list of possible results
- * @returns
- */
- handle(exp: Experiment, data: unknown): void {
- if (this.canHandle(exp.algorithm.name)) {
- try {
- const results = PearsonHandler.transform.evaluate(
- data,
- ) as HeatMapResult[];
- results
- .filter((heatMap) => heatMap.matrix.length > 0 && heatMap.name)
- .forEach((heatMap) => exp.results.push(heatMap));
- } catch (e) {
- PearsonHandler.logger.warn(
- 'An error occur when converting result from Pearson',
- );
- PearsonHandler.logger.verbose(JSON.stringify(data));
- }
- }
+ handle(exp: Experiment, data: any, domain?: Domain): void {
+ if (!this.canHandle(exp.algorithm.name, data))
+ return super.handle(exp, data, domain);
+
+ const extData = data[0];
+
+ const results = PearsonHandler.transform.evaluate(
+ extData,
+ ) as HeatMapResult[];
+ results
+ .filter((heatMap) => heatMap.matrix.length > 0 && heatMap.name)
+ .forEach((heatMap) => exp.results.push(heatMap));
this.next?.handle(exp, data);
}
diff --git a/api/src/engine/connectors/exareme/handlers/algorithms/raw.handler.ts b/api/src/engine/connectors/exareme/handlers/algorithms/raw.handler.ts
index 08cdac953300a1a06dee98568e37268a1999298c..c6d2f3268da9632421b9c8d692380d14e3cc0c65 100644
--- a/api/src/engine/connectors/exareme/handlers/algorithms/raw.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/algorithms/raw.handler.ts
@@ -1,29 +1,37 @@
+import { Domain } from '../../../../models/domain.model';
import { MIME_TYPES } from '../../../../../common/interfaces/utilities.interface';
import { Experiment } from '../../../../models/experiment/experiment.model';
import { RawResult } from '../../../../models/result/raw-result.model';
import { ResultExperiment } from '../../interfaces/experiment/result-experiment.interface';
import BaseHandler from '../base.handler';
+const JSON_ALGO_LIST = ['cart', 'id3'];
+
export default class RawHandler extends BaseHandler {
dataToRaw = (algo: string, result: ResultExperiment): RawResult => {
let data = result;
- if (algo === 'CART') {
+ if (algo === 'cart') {
data = { ...data, type: MIME_TYPES.JSONBTREE };
}
return { rawdata: data };
};
- handle(exp: Experiment, data: unknown): void {
+ handle(exp: Experiment, data: unknown, domain: Domain): void {
const inputs = data as ResultExperiment[];
+ const algoName = exp.algorithm.name.toLowerCase();
if (inputs && Array.isArray(inputs))
inputs
.filter((input) => !!input.data && !!input.type)
- .map((input) => this.dataToRaw(exp.algorithm.name, input))
+ .filter(
+ (input) =>
+ input.type !== MIME_TYPES.JSON || JSON_ALGO_LIST.includes(algoName),
+ )
+ .map((input) => this.dataToRaw(algoName, input))
.forEach((input) => exp.results.push(input));
- this.next?.handle(exp, data);
+ super.handle(exp, data, domain);
}
}
diff --git a/api/src/engine/connectors/exareme/handlers/base.handler.ts b/api/src/engine/connectors/exareme/handlers/base.handler.ts
index 1aa3d2f6391922b10e1d9b29bf9c9a74fef0d575..6ab3074a48df252eb39b00fbdc0c1edd07106afb 100644
--- a/api/src/engine/connectors/exareme/handlers/base.handler.ts
+++ b/api/src/engine/connectors/exareme/handlers/base.handler.ts
@@ -13,7 +13,7 @@ export default abstract class BaseHandler implements ResultHandler {
return h;
}
- handle(experiment: Experiment, data: unknown, domain: Domain): void {
+ handle(experiment: Experiment, data: unknown, domain?: Domain): void {
this.next?.handle(experiment, data, domain);
}
}
diff --git a/api/src/engine/connectors/exareme/interfaces/pathology.interface.ts b/api/src/engine/connectors/exareme/interfaces/pathology.interface.ts
index e71e3a0251af2e03aa7e7995e6129609a9140cd0..7da8b77b983fd1e1489b23f7548ac2584604c658 100644
--- a/api/src/engine/connectors/exareme/interfaces/pathology.interface.ts
+++ b/api/src/engine/connectors/exareme/interfaces/pathology.interface.ts
@@ -4,6 +4,7 @@ import { VariableEntity } from './variable-entity.interface';
export interface Pathology {
code: string;
label: string;
+ version: string;
datasets: VariableEntity[];
metadataHierarchy: Hierarchy;
}
diff --git a/api/src/engine/connectors/exareme/transformations.ts b/api/src/engine/connectors/exareme/transformations.ts
index 60f6a78a7b9e9598eb5495e42493787f6c28ae96..70d2989c2ef4d4668287f56d92607b3ef3fb55be 100644
--- a/api/src/engine/connectors/exareme/transformations.ts
+++ b/api/src/engine/connectors/exareme/transformations.ts
@@ -22,7 +22,7 @@ export const transformToExperiment = jsonata(`
"finishedAt": $convDate(finished),
"shared": shared,
"updateAt": $convDate(updated),
- "domain": algorithm.parameters[name = "pathology"][0].value,
+ "domain": $split(algorithm.parameters[name = "pathology"][0].value, ':')[0],
"datasets": $split(algorithm.parameters[name = "dataset"][0].value, ','),
"variables": $split($rp(algorithm.parameters[name = "y"][0].value), ','),
"coVariables": $toArray($split($rp(algorithm.parameters[name = "x"][0].value), ',')),
diff --git a/api/src/engine/connectors/exareme/transformations/algorithms/index.ts b/api/src/engine/connectors/exareme/transformations/algorithms/index.ts
index f177cbfdee60baf64000ad170a520fb097560b0f..b3626f3499aee15f47487f2704fd4f6226a03b1e 100644
--- a/api/src/engine/connectors/exareme/transformations/algorithms/index.ts
+++ b/api/src/engine/connectors/exareme/transformations/algorithms/index.ts
@@ -10,9 +10,9 @@ const transformToAlgorithms = jsonata(`
$excludedParams:= ['centers', 'formula'];
$includes:= ['ANOVA_ONEWAY','ANOVA','LINEAR_REGRESSION',
'LOGISTIC_REGRESSION','TTEST_INDEPENDENT','TTEST_PAIRED',
- 'PEARSON_CORRELATION','ID3','KMEANS','NAIVE_BAYES',
+ 'PEARSON','ID3','KMEANS','NAIVE_BAYES',
'TTEST_ONESAMPLE','PCA','CALIBRATION_BELT','CART',
- 'KAPLAN_MEIER','THREE_C'];
+ 'KAPLAN_MEIER','THREE_C', 'ONE_WAY_ANOVA', 'PEARSON', 'LINEAR_REGRESSION_CV'];
$linkedVars:= ['positive_level', 'negative_level', 'outcome_neg', 'outcome_pos'];
$linkedCoVars:= ['referencevalues', 'xlevels'];
$truthy:= function($val) {(
@@ -40,7 +40,7 @@ const transformToAlgorithms = jsonata(`
"coVariable": parameters[(type='column' or type='formula') and name='x'] ~> $extract,
"hasFormula": $boolean(parameters[(type='formula_description')]),
"parameters": parameters[type='other' and $not(name in $excludedParams)].{
- "__typename": $lookup($dict, valueType),
+ "__typename": $lookup($dict, (valueType ? valueType : 'null')),
"name": name,
"label": label,
"hint": $checkVal(desc),
diff --git a/api/src/engine/engine.service.ts b/api/src/engine/engine.service.ts
index 97ff0b4687613a9e8eb7863ab0e4814aa19d1ce6..70a7180033d724421c44589f206cca935130f9c4 100644
--- a/api/src/engine/engine.service.ts
+++ b/api/src/engine/engine.service.ts
@@ -221,18 +221,30 @@ export default class EngineService implements Connector {
return this.connector.getFilterConfiguration(req);
}
- async logout?(req?: Request): Promise<void> {
- const user = req?.user as User;
-
- if (user && user.id)
- CACHE_KEYS.map((key) => `${key}-${user.id}`).forEach((key) =>
- this.cacheManager.del(key),
- );
+ async logout?(req: Request): Promise<void> {
+ await this.clearCache(req);
if (!this.connector.logout) throw new NotImplementedException();
return this.connector.logout(req);
}
+ /**
+ * It deletes all the cache keys for the current user
+ * @param {Request} req - Request - The request object.
+ * @returns A promise that resolves to an array of promises that resolve to undefined.
+ */
+ async clearCache(req: Request): Promise<void> {
+ const user = req?.user as User;
+
+ if (!user || !user.id) return;
+
+ await Promise.all(
+ CACHE_KEYS.map((key) => `${key}-${user.id}`).map((key) =>
+ this.cacheManager.del(key),
+ ),
+ );
+ }
+
async login?(username: string, password: string): Promise<User> {
if (!this.connector.login) throw new NotImplementedException();
return this.connector.login(username, password);
diff --git a/api/src/engine/interceptors/errors.interceptor.ts b/api/src/engine/interceptors/errors.interceptor.ts
index fa68a283ca34b0dee868c9c09e143d3c01a0109d..fee41f5e65e54c6f6f3f41d7da432dc7d207d41b 100644
--- a/api/src/engine/interceptors/errors.interceptor.ts
+++ b/api/src/engine/interceptors/errors.interceptor.ts
@@ -23,7 +23,7 @@ export class ErrorsInterceptor implements NestInterceptor {
this.logger = new Logger(options.type);
}
- intercept(context: GqlExecutionContext, next: CallHandler): Observable<any> {
+ intercept(_context: GqlExecutionContext, next: CallHandler): Observable<any> {
return next.handle().pipe(
catchError((e) => {
if (!e.response || !e.response.data || !e.response.status) throw e;
diff --git a/api/src/engine/models/domain.model.ts b/api/src/engine/models/domain.model.ts
index 9fe826291a9f0932a30c6125e73a5f80d3c15981..35c27fe60e97dfc6743e0a589ce1da19c659502a 100644
--- a/api/src/engine/models/domain.model.ts
+++ b/api/src/engine/models/domain.model.ts
@@ -9,6 +9,9 @@ export class Domain extends BaseModel {
@Field({ nullable: true })
description?: string;
+ @Field({ nullable: true })
+ version?: string;
+
@Field(() => [Group])
groups: Group[];
diff --git a/api/src/schema.gql b/api/src/schema.gql
index 417733367410fc6764fb214f008800cefafa4c4e..3720e78944a93b077e3e7458d088bf4c562dda53 100644
--- a/api/src/schema.gql
+++ b/api/src/schema.gql
@@ -86,6 +86,7 @@ type Domain {
id: String!
label: String
description: String
+ version: String
groups: [Group!]!
variables: [Variable!]!
datasets: [Dataset!]!