InitialRepositoryConfig (Market Risk Accelerator 1.9.1-jdk11 API)

java.lang.Object
- com.activeviam.risk.ref.cfg.impl.InitialRepositoryConfig

```
@Configuration
public class InitialRepositoryConfig
extends Object
```
The initial repository configuration.
This is the base file configuring the repository module.
For a given set of parameters, it creates or sets some point values.
The parameters set here are thighly linked to the monitor defined inside the cube.

Author:

ActiveViam

Field Summary

Fields
Modifier and Type	Field	Description
`protected org.springframework.core.env.Environment`	`env`
`static String`	`LOADING_PROPERTY`	Parameter controlling initial loading
`protected com.qfs.repository.cfg.impl.RepositoryServiceConfiguration`	`repositoryServices`	The repository service.

Constructor Summary

Constructors
Constructor Description

InitialRepositoryConfig()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`Void`	`addToRepositoryService()`	[Optional] Initial Load of Parameters.
`protected boolean`	`loadData()`	Decides if initial data must be loaded.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - LOADING_PROPERTY
```
public static final String LOADING_PROPERTY
```
    Parameter controlling initial loading
    
    See Also:
    
    Constant Field Values
  - repositoryServices
```
@Autowired
protected com.qfs.repository.cfg.impl.RepositoryServiceConfiguration repositoryServices
```
    The repository service. It can be remote or local. This is transparent at this point.
  - env
```
@Autowired
protected org.springframework.core.env.Environment env
```
- Constructor Detail
  - InitialRepositoryConfig
```
public InitialRepositoryConfig()
```
- Method Detail
  - addToRepositoryService
```
@Bean
public Void addToRepositoryService()
```
    [Optional] Initial Load of Parameters.
    In this method, we create or update the parameters that are important to the application. For PL Attribution we declare three parameters : mean_ratio_lower_range (-0.1), mean_ratio_upper_range (0.1) and variance_ratio_goal (0.2) For Backtesting we need two parameters : nb_exceptions_99_var (12) and nb_exceptions_97_5_var (30)
    
    Returns:
    
    Void
  - loadData
```
protected boolean loadData()
```
    Decides if initial data must be loaded.
    
    Returns:
    
    true to perform initial data loading