GENERATE_CLASSIFIERSET Operation

This operation is used to add classes and properties to points in Datapools. This point classification can be done 100% online using the point classifier interface of the Web-UI to create a classifier set and subsequently apply it to a Datapool. However some onboarding teams may prefer to generate the classifier sets offline. This is supported by the model generation tooling through the GENERATE_CLASSIFIERSET operation. Once a classifier set is created it can be uploaded via REST API, and applied to Datapool(s) either using the Web-UI or via REST API.

Note that multiple point_class.csv files can be supplied to the manifest and that field is a list with square brackets.

manifest.json

{
  "manifest_version": "1.0.0",
  "id_mapping": {
    "bld": "dch:org/myOrg/site/mySite/building/myBuilding#",
    "myDatapool": "dch:org/myOrg/datapool/managed_datapool_MyDataPool_12345678-9abc-def0-1234-56789abcdef0#"
  },
  "operations": [{
      "operation_type": "CREATE",
      "config": {
        "object_file": "objects.csv"
      }
    }, {
      "operation_type": "RELATE",
      "config": {
        "skeleton_file": "skeleton.csv"
      }
    }, {
      "operation_type": "POINT_CREATE_LINK_PATTERN_MATCH",
      "config": {
        "point_linkage_file": "point_linkage.csv",
        "point_list_files": ["point_list.csv"]
      }
    }, {
      "operation_type": "GENERATE_CLASSIFIERSET",
      "config": {
        "organisation": "myOrg",
        "point_class_files": ["point_class.csv"]
      }
    }]
}

All other CSVs in this example are from POINT_CREATE_LINK_PATTERN_MATCH example 4, but now we add a new point_class.csv. This CSV assigns classes to Points based on a pattern match on the end of the Point ID string.

For example, for classifying a Point with the ID mySite.myBuilding.AHU_1.Enb, the pattern Enb is matched to the class Enable_Status.

The CSV has 2 primary columns:

1. Point_Expression: the field where you put the pattern you would like to match.

2. Brick Class: the BRICK class you would like to assign to any Point that has matched the value in Point_Expression.

Entity Properties can also be declared in other columns to assign units, scale, offset and any other metadata as defined in BRICK. For this example, the point_class.csv looks like below:

Order of rows in the CSV is important as application of latter rules in a file can overwrite changes from earlier rows. In scenarios where similar patterns share an expression, the top level should be done first. E.g. Points with pattern "*AHU1" are classed as brick:Enable and Points with "*AHU1.Filter" are classed as brick:Status. "*AHU1" should be declared at a higher row in the CSV:

AHU1,Enable

AHU1.Filter,Status

In contrast, by doing "AHU1.Filter" first, when the pattern "AHU1" is processed, the class for "AHU1.Filter" is overwritten to be brick:Enable, instead of brick:Status.

Example

Inputs

Point_Expression	Brick Class	brick:hasUnit	brick:scaleFactor [brick:scale, brick:offset]
bom_gov_au.94870.air.air_temp	Outside_Air_Temperature_Sensor	DEG_C
5.DefVal	Temperature_Setpoint	DEG_C
AhrPbAct.In	Mode_Command
AhrPbAct.Out	Mode_Command
AhrPbAct.Reset	Reset_Command
Alm	Alarm
ClgVlv	Valve_Position_Sensor	PERCENT	[100,0]
EcoEnb	Operating_Mode_Status
Enb	Enable_Status
FilDpStp	Differential_Pressure_Setpoint	KiloPA
FiltDpr	Filter_Differential_Pressure_Sensor	KiloPA
HtgVlv	Valve_Position_Sensor	PERCENT	[100,0]
MaSatStp	Max_Discharge_Air_Temperature_Setpoint_Limit	DEG_C
MaxDmdEn	Operating_Mode_Status
MinSatStp	Min_Discharge_Air_Temperature_Setpoint_Limit	DEG_C
OaDmp	Damper_Position_Sensor	PERCENT
OatMaxSp	Outside_Air_Lockout_Temperature_Setpoint	DEG_C
OatMinSp	Low_Outside_Air_Temperature_Enable_Setpoint	DEG_C
OccClgSp	Cooling_Temperature_Setpoint	DEG_C
OccDb	Air_Temperature_Sensor	DEG_C
OccHtgSp	Heating_Temperature_Setpoint	DEG_C
Pb	Mode_Command
PosMinOa	Min_Position_Setpoint_Limit	PERCENT
RaDmp	Damper_Position_Sensor	PERCENT
RmSp	Room_Air_Temperature_Setpoint	DEG_C
Sat	Discharge_Air_Temperature_Sensor	DEG_C
Sts	System_Status
Tmp	Air_Temperature_Sensor	DEG_C
vOAT	Intake_Air_Temperature_Sensor	DEG_C

3KB

Classify_Eg1.zip

archive

Open

CLASSIFY Example 1: Full input archive

---

Outputs

Partial view of the output:

{
    "name": "point_class_mgtool_2.0",
    "classifiers": [
        {
            "id": "a1b2c3d4-1234-1234-abcd-123456789abc",
            "enabled": true,
            "comment": "",
            "filterBy": {
                "id": {
                    "enabled": true,
                    "value": "*Pb"
                },
                "timeseriesId": {
                    "enabled": false
                },
                "class": {
                    "enabled": false,
                    "includeChildren": false
                },
                "label": {
                    "enabled": false
                },
                "entityProperties": {
                    "enabled": false
                },
                "entity": {
                    "enabled": false
                },
                "unit": {
                    "enabled": false
                }
            },
            "executeRules": {
                "class": {
                    "enabled": true,
                    "value": "brick:Mode_Command"
                },
                "entityProperties": {
                    "enabled": false,
                    "value": null
                },
                "label": {
                    "enabled": false
                },
                "entity": {
                    "enabled": false
                },
                "unit": {
                    "enabled": false,
                    "value": null
                }
            }
        },
        ...

This set can then be uploaded to DCH via this endpoint. You either continue the rest of the classification with the UI, or by using REST API.

4KB

generated-Classify_Eg1.zip

archive

Open

CLASSIFY Example 1: Full output archive

Using swagger API docs to finish point classification

Classification can be finished by using our API docs.

Step 1: authenticate

1. Generate an API key from DCH.

2. On the API docs page, press Authorize.

3. Paste your API key in the ApiKeyAuth (apiKey) field.

4. Press Authorize.

If you refresh the API docs page, your auth resets and you have to repeat this step again.

Step 2: POST the generated classifier set

Classifier Sets cannot be uploaded (unmodified) to DCH twice because the UUIDs of the individual classifiers need to be unique in DCH. If you wish to edit a Classifier Set and re-upload it you must update all the used UUIDs before reuploading it. Uploading a classifier set via the UI automatically updates UUIDs for you.

1. Scroll down to the Classifier Set section of the docs.

2. Press on "POST/classifiersets".

3. Click on Try it out.

4. Copy and Paste the contents of your classifier set JSON in the Request Body.

5. Press Execute.

6. A response of 201 means this step was successfully executed. Copy the id field of the response (your set ID).

Step 3: POST classification plan

At this stage, you can move to the UI for steps 3 and 4, or you can continue with the API docs.

1. Scroll up to the Classification Plan section.

2. Press on POST/classificationplans.

3. Click on Try it out.

4. Fill-in the request body

   1. Plan Scope is a list of datapools that are the target of this plan

   2. organisationId is the organisation where the datapool exists

   3. classifierSetId is the classifier set ID from step 2

5. Press Execute.

6. A response of 201 means this step was successfully executed. Copy the id field of the response again (your plan ID).

{
  "planScope": [
    "my_datapool_id"
  ],
  "organisationId": "my_organisation_id",
  "classifierSetId": "my_classifier_set_id_from_step_2"
}

Step 4: POST classification plan apply

1. In the same section as step 3 (Classification Plan), press on POST/classificationplans/{classification_plan_id}/apply

2. Click on Try it out.

3. Paste your plan ID from step 3

4. Press Execute.