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linear_scale_range.json
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linear_scale_range.json
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{
"id": "linear_scale_range",
"summary": "Linear transformation between two ranges",
"description": "Performs a linear transformation between the input and output range.\n\nThe given number in `x` is clipped to the bounds specified in `inputMin` and `inputMax` so that the underlying formula *`((x - inputMin) / (inputMax - inputMin)) * (outputMax - outputMin) + outputMin`* never returns any value lower than `outputMin` or greater than `outputMax`.\n\nPotential use case include\n\n* scaling values to the 8-bit range (0 - 255) often used for numeric representation of values in one of the channels of the [RGB colour model](https://en.wikipedia.org/wiki/RGB_color_model#Numeric_representations) or\n* calculating percentages (0 - 100).\n\nThe no-data value `null` is passed through and therefore gets propagated.",
"categories": [
"math"
],
"parameters": [
{
"name": "x",
"description": "A number to transform. The number gets clipped to the bounds specified in `inputMin` and `inputMax`.",
"schema": {
"type": [
"number",
"null"
]
}
},
{
"name": "inputMin",
"description": "Minimum value the input can obtain.",
"schema": {
"type": "number"
}
},
{
"name": "inputMax",
"description": "Maximum value the input can obtain.",
"schema": {
"type": "number"
}
},
{
"name": "outputMin",
"description": "Minimum value of the desired output range.",
"schema": {
"type": "number"
},
"default": 0,
"optional": true
},
{
"name": "outputMax",
"description": "Maximum value of the desired output range.",
"schema": {
"type": "number"
},
"default": 1,
"optional": true
}
],
"returns": {
"description": "The transformed number.",
"schema": {
"type": [
"number",
"null"
]
}
},
"examples": [
{
"arguments": {
"x": 0.3,
"inputMin": -1,
"inputMax": 1,
"outputMin": 0,
"outputMax": 255
},
"returns": 165.75
},
{
"arguments": {
"x": 25.5,
"inputMin": 0,
"inputMax": 255
},
"returns": 0.1
},
{
"arguments": {
"x": null,
"inputMin": 0,
"inputMax": 100
},
"returns": null
},
{
"description": "Shows that the input data is clipped.",
"arguments": {
"x": 1.12,
"inputMin": 0,
"inputMax": 1,
"outputMin": 0,
"outputMax": 255
},
"returns": 255
}
],
"process_graph": {
"subtract1": {
"process_id": "subtract",
"arguments": {
"x": {
"from_parameter": "x"
},
"y": {
"from_parameter": "inputMin"
}
}
},
"subtract2": {
"process_id": "subtract",
"arguments": {
"x": {
"from_parameter": "inputMax"
},
"y": {
"from_parameter": "inputMin"
}
}
},
"subtract3": {
"process_id": "subtract",
"arguments": {
"x": {
"from_parameter": "outputMax"
},
"y": {
"from_parameter": "outputMin"
}
}
},
"divide": {
"process_id": "divide",
"arguments": {
"x": {
"from_node": "subtract1"
},
"y": {
"from_node": "subtract2"
}
}
},
"multiply": {
"process_id": "multiply",
"arguments": {
"x": {
"from_node": "divide"
},
"y": {
"from_node": "subtract3"
}
}
},
"add": {
"process_id": "add",
"arguments": {
"x": {
"from_node": "multiply"
},
"y": {
"from_parameter": "outputMin"
}
},
"result": true
}
}
}