Neuron validation

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Validator

The validator class template in the key component to validate a reconstruction. The validator works at neuron level, that is, it validates a neuron or its sub-components. To create a new validator you just need a Measure that takes a single element (Neuron, Neurite, Branch or Node) as input and a Check function that accepts the measure output value.

template <typename M, typename C>
class Validator {
  Validator(M measure, C check){}
}

The measure is applied to every Neurite/Branch/Node in the Neuron or to the neuron itself, and then the output value is given to the check function, that determines whether the value pass the check (returning a true boolean value) or not. This is stored in a ValidatorItem structure within the validator.

template <typename M, typename C>
void Validator<M,C>::validate(const Neuron& n)

The ValidatorItem is basically a container with:

• element: A reference to the validated element
• value: The measure value
• valid: The check function evaluated over value

There are a bunch of prebuilt check functions and validators included in the library. All validations described in the Prebuilt validations sections are included in the Validator tool bundled with the library. Details about the validator class template and the ValidatorItem are available in the validator namespace documentation.

The Validator class and the ValidatorItem class as well have a toJSON method that writes the validation results in a easily readable JSON format (the Validator tool output uses this function). The output specifications are detailed at the end of this section.

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Checks

Any function that takes a single value as input and outputs a boolean qualifies as check. The only restriction is that the check function input must match the measure function output. There are a couple of simple check functions already implemented in the library:

public const auto is_true

Checks that a given boolean is true

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public const auto is_false

Checks that a given boolean is false

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public const auto empty_string

Checks that a given string is empty

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public template<typename T>
inline auto range_check_factory(T min,T max)

Range check factory. Checks that a given value is in the range [min, max)

Parameters

• min Range minimum

• max Range maximum

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JSON Output

The toJSON method in the validator class template writes the results into an output stream as a JSON Object with the following fields:

• name: The name given to the validator. Usually a short test name. e.g. "Planar neurite validation"
• description: Test description. e.g. "Fails if the non-axis aligned box volume of the neurite is lower than prebuilt threshold"
• neuron_id: The validated neuron ID
• pass: Boolean. True if the neuron (or all its sub-elements) passed the test
• results: An array of Validation Items

{
        "description": "Fails when the branch tortuosity falls below 1.010000",
        "name": "Linear branch validator",
        "neuron_id": "simple_tree",
        "pass": false,
        "results": [ ]
}

In turn, a Validation Item is also written as a JSON Objects with:

• id: A JSON object that identifies the tested element.
• type: A string that identifies the type of the tested element. It can be "Neuron", "Neurite", "Branch" or "Node"
• value: The measure value.
• pass: The result of the check function over the measure value.

And the ID object has:

• neuron: The Neuron name string.
• neurite: The Neurite ID (int). Present when the element type is Node, Branch or Neurite.
• branch: The Branch ID as a string. Present when the element type is Node or Branch.
• node: The Node ID (int). Present only if the element type is Node

{
                "id": {
                    "branch": "1-2",
                    "neurite": 1,
                    "neuron": "simple_tree"
                },
                "pass": false,
                "type": "Branch",
                "value": 1.0
}