Jump Controller in Pele++ control file¶

This page documents what is also known as the jumping or spawning functionality of Pele++.

The jump controller is the responsible to change the explorer coordinates if some conditions are met in the task. Thus, the block is defined at Task level.

If you use the jumping functionality, you may want to enable the controller log file through the PELE_Output controllerEventsLogPath option.

Example¶

"jumpIf":
[
     "diff_rmsd1 > 1.1",
     "diff_rmsd2 > 0.5"
],

"jumpController":{
    "strategyToChooseBestExplorer":{
        "type": "bestHasMinimumValueForOneSensor",
        "sensorTag": "rmsd1"
    },

    "jumpStrategy": {
        "type": "jumpToBestExplorerCoordinates"
    }
}

jumpIf section¶

The jumpIf clause contains the jumping conditions. If any condition is met, the system’s state will change.

There are two kinds of conditions:

Absolute condition. We compare the value of the sensor to a certain value. The sensor is specified with a tag.
Relative condition. We compare the sensor’s current value to the best one so far in the whole simulation. We write it: “diff_” + tag.

Note

For a relative condition, comparing to the best one so far in the whole simulation implies that a given explorer (or the single explorer, in the serial version of PELE++) may compare its current value to a value already generated by that explorer in the past. It also means that an explorer does not necessarily compare its current value to the best value of the current state of any other explorer, but to the best value in the whole simulation.

Note

In the current version it is not possible to mix absolute and relative conditions:

"jumpIf":
[
    "rmsdSelection > 1.1 and diff_rmsd1 > 0.5"
]

Example1¶

"jumpIf":[ "rmsdSelection > 1.1" ]

Example2¶

"jumpIf":[ "diff_rmsd1 > 0.5" ]

jumpController section¶

The jumpController section is comprised of two configuration blocks:

strategyToChooseBestExplorer: the way we choose the best explorer/step in the simulation.
jumpStrategy: the way we jump after the jumpIf condition is met.

Example¶

"jumpController":{
    "strategyToChooseBestExplorer":{
        "type": "bestHasMinimumValueForOneSensor",
         "sensorTag": "rmsd1"
    },
    "jumpStrategy": {
        "type": "jumpToBestExplorerCoordinates"
    }
}

Types of strategyToChooseBestExplorer¶

bestHasMinimumValueForOneSensor: The best explorer will have the smaller value for one sensor. The sensor is specified with “sensorTag”.
```
"strategyToChooseBestExplorer":{
    "type": "bestHasMinimumValueForOneSensor",
    "sensorTag": "rmsd1"
}
```
bestHasMinimumValueForWeightedSensors: The best explorer is calculated using more than one sensor, each one with a certain weight associated to it. It is specified with a block named “sensorWeights” that consists of the pairs tag:weight.
```
"strategyToChooseBestExplorer":{
    "type":"bestHasMinimumValueForWeightedSensors",
    "sensorWeights":{
        "rmsd1": 1,
        "rmsd2": 2,
        "rmsd3": 4
    }
}
```
We compare the current explorer with the best one by assigning a score. For all the sensors, we subtract “weight” to the score of the explorer with the minimum value for that sensor. The explorer with the smallest score is the best one. Ex: Using the weights of the previous example. Explorer1: rmsd1 = 1.12, rmsd2 = 0.024, rmsd3 = 1.10. Explorer2: rmsd1 = 1.14, rmsd2 = 0.015, rmsd3 = 1.10. Explorer1 score = -1 - 0 - 0 = -1. Explorer2 score = -0 - 2 - 0= -2. Hence, Explorer2 is better than Explorer1.

Types of jumpStrategy¶

jumpToBestExplorerCoordinates: In case of jump, it will jump to the coordinates of the best explorer.
```
<pre>
"jumpStrategy": {
    "type": "jumpToBestExplorerCoordinates"
}
```

MPI vs Serial execution¶

The “strategyToChooseBestExplorer” in MPI chooses the best result so far of all the explorers. In Serial version, the best explorer is the best step of the serial execution.

Who takes the decisions¶

A jump can be caused by two factors:

The explorer decides to jump: After evaluating its own sensors, an explorer decides that it has gone too far, so it asks the explorer for jumping.
The controller forces a jump: The controller compares the values of the sensors for a given explorer against the values of the best one. If the difference is too big, the controller will make the given explorer jump.

This can also be said as the following: although all the jump conditions are listed in the “jumpIf” sections, the conditions which not involves a comparison between the best one’s values will be evaluated by the explorer, who will be who takes the decision of either jumping or not. Those are the conditions not prefixed by “diff_”. The conditions which actually have a “diff_” prefix will be the ones that the controller, and only the controller, will evaluate in order to decide if an explorer has to jump.

Jumping (Spawning)¶

With the previous tools we can make explorers spawn closer or further to a certain point.

Example: Bringing the ligand close to a point.¶

We need to define the distance of the ligand to the point of interest. In the metrics block of the same task we add:

"metrics": [
    {
        "type": "distanceToPoint",
        "point": [ 0.3, 0.1, 0.5 ],
        "atoms": {
        "links": {
            "ids": [
            "L:571"
            ]
        }
        },
        "tag": "distance"
    },
    ...
]

In the same task, we add the “jumpIf” block:

"jumpIf": [
    "diff_distance > 10"
],
"jumpController": {
    "strategyToChooseBestExplorer": {
        "type": "bestHasMinimumValueForOneSensor",
        "sensorTag": "distance"
    },
    "jumpStrategy": {
        "type": "jumpToBestExplorerCoordinates"
    }
}

This way, when a explorer is \(10 \AA{}\) further to the point than the closest explorer (i.e. \(| \Delta \text{distance}| > 10 \AA{}\), where \(\Delta \text{distance} = \text{CurrentExplorer_distance} - \text{BestExplorer_distance}\)), it jumps to the best explorer coordinates. It is worth emphazising that diff_distance is NOT the distance between the two explorers.

Example: Moving the ligand away from a point.¶

The example is essentialy the same as the previous example. The only difference is that now the best explorer is the one that is the furthest away.The jump controller is now:

"jumpIf": [
    "diff_distance > 10"
],
"jumpController": {
    "strategyToChooseBestExplorer": {
        "type": "bestHasMaximumValueForOneSensor",
        "sensorTag": "distance"
    },
    "jumpStrategy": {
        "type": "jumpToBestExplorerCoordinates"
    }
}

Jump Controller in Pele++ control file¶

Example¶

jumpIf section¶

Example1¶

Example2¶

jumpController section¶

Example¶

Types of strategyToChooseBestExplorer¶

Types of jumpStrategy¶

MPI vs Serial execution¶

Who takes the decisions¶

Jumping (Spawning)¶

Example: Bringing the ligand close to a point.¶

Example: Moving the ligand away from a point.¶

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