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Documented 8 functions across 1 file #16

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Documented 8 functions across 1 file #16

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3a8b3be
Added comments to 8 functions across 1 file
komment-ai[bot] Jul 3, 2024
369542c
Added comments to 79 items across 10 files
komment-ai[bot] Sep 7, 2024
9605c83
Added comments to 82 items across 9 files
komment-ai[bot] Sep 8, 2024
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217 changes: 217 additions & 0 deletions .komment/00000.json
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[
{
"name": "filters.py",
"path": "pyFRI/tools/filters.py",
"content": {
"structured": {
"description": "Three classes: StateFilter, ExponentialStateFilter, and MovingAverageFilter, which are subclasses of ABC's abstract class StateFilter. These filters are used to smooth or average a sequence of values, such as time series data, to reduce noise and highlight trends. The classes use different methods to filter the data, including exponential smoothing with a parameter for controlling the smoothing level, and moving average filtering.",
"items": [
{
"id": "4fc5d738-da39-15b1-b944-b54021738842",
"ancestors": [],
"description": "Initializes a window of fixed size and appends elements to it using the `append()` method. It then filters the elements in the window using an abstract method.",
"attributes": [
{
"name": "_window_size",
"type_name": "int",
"description": "Used to control the size of the sliding window used for filtering."
},
{
"name": "reset",
"type_name": "instance",
"description": "Used to reset the internal buffer of the object to its initial state by clearing it of all elements."
}
],
"name": "StateFilter",
"location": {
"start": 6,
"insert": 7,
"offset": " ",
"indent": 4,
"comment": null
},
"item_type": "class",
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},
{
"id": "fb222aeb-9c23-64b1-464c-1432b304bcbf",
"ancestors": [
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],
"description": "Sets the `window_size` attribute of an instance of `StateFilter`, which is used to control the size of the moving window for filtering states. The `reset()` method is also defined within the function, which resets the internal state of the filter.",
"params": [
{
"name": "window_size",
"type_name": "int",
"description": "Used to set the size of the sliding window used for computing moving averages."
}
],
"returns": null,
"name": "__init__",
"location": {
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"offset": " ",
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},
"item_type": "method",
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{
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"ancestors": [
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],
"description": "In the `StateFilter` class inherited from `abc.ABC`, does not perform any operation as it is marked as `@abc.abstractmethod`.",
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"type_name": "abcobject",
"description": "Used to represent any object that can be passed through an abstraction method."
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"name": "filter",
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},
{
"id": "980780df-53ca-01a5-ad45-f91cc65929a8",
"ancestors": [],
"description": "Filters time-series data by taking an exponentially smoothed average of the previous values, with a smoothing parameter to control the degree of smoothing.",
"attributes": [
{
"name": "_smooth",
"type_name": "float",
"description": "Set to a value of 0.02 during initialization, which represents the smoothing parameter used to blend the input values with the previous values in the window."
}
],
"name": "ExponentialStateFilter",
"location": {
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},
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"ancestors": [
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"description": "Sets up an instance of the `ExponentialStateFilter` class by initializing its internal variable `smooth` to a value passed as an argument, and then calls the parent class's `__init__` method to initialize the filter with a default value of 1.",
"params": [
{
"name": "smooth",
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"description": "Set to `0.02`. Its value influences the initial position of the random walk."
}
],
"returns": null,
"name": "__init__",
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{
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],
"description": "Takes an input `x` and applies an exponential smoothing filter to it, appending the smoothed value to a internal list. The filter uses a parameter `smooth` to control the degree of smoothing.",
"params": [
{
"name": "x",
"type_name": "object",
"description": "Used to represent an input value that is to be filtered using a smoothing window."
}
],
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"type_name": "nparray",
"description": "A smoothed version of the input value `x`, created by multiplying it with a smoothing factor and adding the initial value of the window array."
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"name": "filter",
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{
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"description": "Computes and returns the moving average of a sequence of values using the provided window size.",
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],
"description": "Appends an input value to a internal buffer and calculates the mean of the buffer along the axis 0.",
"params": [
{
"name": "x",
"type_name": "object",
"description": "Passed to the method for filtering."
}
],
"returns": {
"type_name": "npmean",
"description": "A measure of central tendency of a set of numbers."
},
"name": "filter",
"location": {
"start": 37,
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},
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}
]
}
}
}
]
15 changes: 15 additions & 0 deletions .komment/komment.json
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{
"meta": {
"version": "1",
"updated_at": "2024-07-03T15:56:10.941Z",
"created_at": "2024-07-03T15:56:11.430Z",
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}
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