Numeric

Temperature	23.45	°C	`20<x<25`	Pass
Output Voltage	4.50	V	`4.8<x<5.2`	Fail
Current	0.15	A	`x!=0`	Pass

You can create a numeric measurement with measurements:

measurements:
  - name: Output Voltage
    unit: V
    validators: 
      - operator: ">="
        expected_value: 4.8
      - operator: "<="
        expected_value: 5.2

You can set the measurement value in your Python phase:

def measure_voltage(run, measurements, multimeter):
    voltage = multimeter.read_voltage()
    measurements.output_voltage = voltage

Definition

You can configure the measurement name and metadata.

Property	Type	Required	Description
`key`	`string`	No	Unique identifier for the measurement within the phase
`name`	`string`	Yes	Display name (1-100 characters)
`unit`	`string`	No	Measurement unit (e.g., `"V"`, `"A"`, `"°C"`, max 50 characters)
`description`	`string`	No	Detailed description (max 50,000 characters)

TofuPilot auto-generates the key from name (snake_case) if not specified, and uses it for Python access (e.g., measurements.output_voltage). The unit and description display in the web interface and reports.

Validators

You can add one or several validators to your measurement using the following properties:

Property	Type	Required	Description
`operator`	`string`	Yes	Comparison operator
`expected_value`	`number` or `array`	Yes	Expected value(s) for comparison

You can use the following operators for numeric measurements:

Operator	Expected Value	Description	Example
`==`	Number	Value must equal expected	`expected_value: 5.0`
`!=`	Number	Value must not equal expected	`expected_value: 0.0`
`>`	Number	Value must be greater than	`expected_value: 4.8`
`>=`	Number	Value must be greater than or equal	`expected_value: 4.8`
`<`	Number	Value must be less than	`expected_value: 5.2`
`<=`	Number	Value must be less than or equal	`expected_value: 5.2`
`in`	Array of numbers	Value must be in the array	`expected_value: [5.0, 12.0, 24.0]`
`not in`	Array of numbers	Value must not be in the array	`expected_value: [0.0, -1.0]`

TofuPilot evaluates validators and sets the outcome to Pass if met, Fail if not, or Unset if no value provided.

You can use Aggregations for statistical validation on numeric arrays.

Examples

Voltage Measurement

We will measure output voltage with min/max limits:

phases:
  - name: Power Supply Test
    python:
      module: measure_voltage
    measurements:
      - name: Output Voltage
        unit: V
        description: Main power supply output voltage
        validators:
          - operator: ">="
            expected_value: 4.8
          - operator: "<="
            expected_value: 5.2

def measure_voltage(run, multimeter):
    log.info("Measuring output voltage")

    voltage = multimeter.read_voltage()
    measurements.output_voltage = voltage

    if voltage < 4.8 or voltage > 5.2:
        log.warning(f"Voltage out of spec: {voltage} V")

Set Point Validation

We will validate voltage is one of the allowed setpoints:

phases:
  - name: Voltage Check
    python:
      module: check_voltage
    measurements:
      - name: Output Voltage
        unit: V
        description: Verify output matches one of the valid setpoints
        validators:
          - operator: in
            expected_value: [5.0, 12.0, 24.0]

def check_voltage(run, multimeter):
    log.info("Checking voltage setpoint")

    voltage = multimeter.read_voltage()
    measurements.output_voltage = voltage

    if voltage not in [5.0, 12.0, 24.0]:
        log.warning(f"Unexpected voltage: {voltage} V")

How is this guide?