# Load Objectives

Loads optimization objectives for a trial in globalMOO.

## Endpoint

`POST /models/{model_id}/projects/{project_id}/trials/{trial_id}/objectives`

## Path Parameters

| Parameter   | Type    | Required | Description       |
| ----------- | ------- | -------- | ----------------- |
| model\_id   | integer | Yes      | ID of the model   |
| project\_id | integer | Yes      | ID of the project |
| trial\_id   | integer | Yes      | ID of the trial   |

## Request Parameters

| Parameter      | Type           | Required    | Description                                           |
| -------------- | -------------- | ----------- | ----------------------------------------------------- |
| objectives     | array\[float]  | Yes         | Target values for each objective                      |
| objectiveTypes | array\[string] | Yes         | Type for each objective (see below)                   |
| initialInput   | array\[float]  | Yes         | Initial input values (must match project input count) |
| initialOutput  | array\[float]  | Yes         | Initial output values (must match objectives count)   |
| desiredL1Norm  | float          | Yes         | Desired L1 norm for objectives (default: 0.0)         |
| minimumBounds  | array\[float]  | Conditional | Lower bounds (required for percent/value types)       |
| maximumBounds  | array\[float]  | Conditional | Upper bounds (required for percent/value types)       |

### Objective Types

Valid objective types are:

* `exact` - Match target value exactly within L1 norm
* `percent` - Within a percentage range of target value (requires bounds)
* `value` - Within an absolute range of target value (requires bounds)
* `lessthan` - Less than target value
* `lessthan_equal` - Less than or equal to target value
* `greaterthan` - Greater than target value
* `greaterthan_equal` - Greater than or equal to target value
* `minimize` - Find minimum possible value
* `maximize` - Find maximum possible value

## Request Format

```json
{
    "objectives": [100.0, 50.0, 25.0],
    "objectiveTypes": ["percent", "value", "percent"],
    "initialInput": [1.0, 2.0, 3.0],
    "initialOutput": [90.0, 45.0, 20.0],
    "desiredL1Norm": 0.0,
    "minimumBounds": [-5.0, -2.0, -1.0],
    "maximumBounds": [5.0, 2.0, 1.0]
}
```

## Response Format

```json
{
    "id": 123,
    "trialId": 456,
    "objectives": [100.0, 50.0, 25.0],
    "objectiveTypes": ["percent", "value", "percent"],
    "initialInput": [1.0, 2.0, 3.0],
    "initialOutput": [90.0, 45.0, 20.0],
    "l1Norm": 0.0,
    "minimumBounds": [-5.0, -2.0, -1.0],
    "maximumBounds": [5.0, 2.0, 1.0],
    "createdAt": "2025-01-31T10:00:00.000Z",
    "updatedAt": "2025-01-31T10:00:00.000Z",
    "results": [
        {
            "number": 0,
            "type": "percent",
            "objective": 100.0,
            "minimumBound": null,
            "maximumBound": null,
            "output": 90.0,
            "error": 10.0,
            "detail": "Error exceeds L1 norm threshold",
            "satisfied": false
        },
        {
            "number": 1,
            "type": "value",
            "objective": 50.0,
            "minimumBound": -2.0,
            "maximumBound": 2.0,
            "output": 45.0,
            "error": -5.0,
            "detail": "Output within absolute bounds",
            "satisfied": true
        }
    ]
}
```

## Examples

{% tabs %}
{% tab title="Python" %}

```python
from globalmoo import Client, ObjectiveType

client = Client(api_key="your-api-key")
objectives = client.load_objectives(
    model_id=123,
    project_id=456,
    trial_id=789,
    objectives=[100.0, 50.0, 25.0],
    objective_types=[
        ObjectiveType.PERCENT,
        ObjectiveType.VALUE,
        ObjectiveType.PERCENT
    ],
    initial_input=[1.0, 2.0, 3.0],
    initial_output=[90.0, 45.0, 20.0],
    minimum_bounds=[-5.0, -2.0, -1.0],
    maximum_bounds=[5.0, 2.0, 1.0]
)

# Checking detailed results
for result in objectives.results:
    print(f"Objective {result.number}:")
    print(f"  Type: {result.type}")
    print(f"  Target: {result.objective}")
    print(f"  Output: {result.output}")
    print(f"  Error: {result.error}")
    print(f"  Satisfied: {'✓' if result.satisfied else '✗'}")
    print(f"  Detail: {result.detail}")
```

{% endtab %}

{% tab title="Node.js" %}

```javascript
const { Client } = require('globalmoo');

const client = new Client('your-api-key');
const objectives = await client.loadObjectives({
    modelId: 123,
    projectId: 456,
    trialId: 789,
    objectives: [100.0, 50.0, 25.0],
    objectiveTypes: ["exact", "value", "percent"],
    initialInput: [1.0, 2.0, 3.0],
    initialOutput: [90.0, 45.0, 20.0],
    minimumBounds: [-5.0, -2.0, -1.0],
    maximumBounds: [5.0, 2.0, 1.0]
});
```

{% endtab %}

{% tab title="PHP" %}

```php
$client = new Client("your-api-key");

$objectives = $client->loadObjectives([
    "modelId" => 123,
    "projectId" => 456,
    "trialId" => 789,
    "objectives" => [100.0, 50.0, 25.0],
    "objectiveTypes" => ["exact", "value", "percent"],
    "initialInput" => [1.0, 2.0, 3.0],
    "initialOutput" => [90.0, 45.0, 20.0],
    "minimumBounds" => [-5.0, -2.0, -1.0],
    "maximumBounds" => [5.0, 2.0, 1.0]
]);
```

{% endtab %}
{% endtabs %}

## Error Responses

| Status Code | Description                                                                     |
| ----------- | ------------------------------------------------------------------------------- |
| 400         | Invalid request - Missing required fields, invalid format, or validation errors |
| 401         | Unauthorized - Invalid API key                                                  |
| 404         | Model, project, or trial not found                                              |
| 429         | Too many requests - Rate limit exceeded                                         |
| 500         | Internal server error                                                           |

## Server-Side Validation

The API performs the following validations:

* Model, project, and trial IDs must be positive integers
* Array lengths must be consistent:
  * objectives and objectiveTypes must have the same length
  * initialInput length must match the project's input count
  * initialOutput length must match objectives length
  * minimumBounds/maximumBounds must match objectives length when required
* All numeric values must be valid floating point numbers
* Objective types must be valid types as listed above
* For percent and value objectives:
  * minimumBounds and maximumBounds are required
  * maximumBounds values must be greater than minimumBounds
* desiredL1Norm must be provided and non-negative (defaults to 0.0)
* Trial must exist and be in an active state


---

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