![](https://cdn.steemitimages.com/DQmVLEQz4R6TLspWojh1uHaiMhZ2w8125zWdBp1YeodBrzM/image.png)

Each scot has now two new parameters:
* `post_reward_curve` - can be `default`, `convergent_linear`
* `post_reward_curve_parameter` - can be None or a float number

Default setting is `post_reward_curve=default` and `post_reward_curve_parameter=None`, which means that the post reward is calculated by 
```
weight_rshares = rshares ^ config[token]["author_curve_exponent"]
```


When `post_reward_curve` is set to `convergent_linear`, the post reward is calculated by:
```
s = config[token]["post_reward_curve_parameter"]
weight_rshares = ( rshares  *  rshares ) / ( rshares + s )
```

and config[token]["author_curve_exponent"] is not used for calculation.



## Comparison
Lets assume there is a pool of 2 TOKEN and there are three posts with 500, 1500 and 10000 rshares

#### default settings

 | author curve exponent| rshares | weight_rshares | payout |
 | --- | --- | --- | --- |
 | 1.0 |500  | 500 | 0.08 |
 | 1.0 | 1500  | 1500 | 0.25 |
 | 1.0 | 10000  | 10000  | 1.67 |
 | 1.05 | 500 | 682  | 0.07 |
 | 1.05 | 1500 | 2162 |0.23 |
 | 1.05 | 10000  | 15848| 1.7 |
 | 1.1 | 500 | 930| 0.06 |
 | 1.1 | 1500 | 3116| 0.21 |
 | 1.1 | 10000  | 25118| 1.72 |
 | 1.3 | 500 | 3225| 0.04|
 | 1.3 | 1500 | 13456| 0.15|
 | 1.3 | 10000  | 158489| 1.81 |
 | 1.5 | 500 | 11180| 0.02| 
 | 1.5 | 1500 | 58094| 0.11|
 | 1.5 | 10000  | 1000000| 1.87 |

## convergent_linear

|  post reward curve parameter| rshares | weight_rshares | payout |
 | --- | --- | --- | --- |
 | 10 |500  | 490| 0.08 |
 | 10 | 1500  | 1490| 0.25 |
 | 10 | 10000  | 9990| 1.67 |
 | 100 | 500 | 416| 0.07 |
 | 100 | 1500 | 1406|0.24 |
 | 100 | 10000  | 9900| 1.69 |
 | 1000 | 500 | 166| 0.03 |
 | 1000 | 1500 | 900| 0.18 |
 | 1000 | 10000  | 9090| 1.79 |
 | 10000 | 500 | 23| 0.01|
 | 10000  | 1500 | 195| 0.07|
 | 10000  | 10000  | 5000| 1.92 |

## Conclusion
When using the convergent_linear cuve, the parameter can be used to decide from which reward to should convert to a linear curve. For `post_reward_curve_parameter=10`, the payout is the same as for exponent = 1.

For post_reward_curve_parameter = 1000, the rshares for the post with 500 rshares are weighted with 0.33, the post with 1500 rshares is weighted with 0.6 and the post with 10000 rshares is weighted with 0.909.

Thus, `convergent_linear ` with a parameter of 1000 can be used to reduce the payout of post with less than 1000 rshares.

___

Let me know when you want to change the configuration for your SCOT.