filters
LATFilter
Bases: ScalarFilter
Extract LATs (local activation times) from the input scalars using a threshold.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
threshold |
float
|
Voltage threshold for activation. Defaults to -50. |
-50.0
|
dtime |
float
|
Time between samples (ms). Defaults to 1. |
1.0
|
dtime: float = dtime
instance-attribute
threshold: float = threshold
instance-attribute
__init__(threshold=-50.0, dtime=1.0)
Initialize the LATFilter with a voltage threshold and sample interval.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
threshold |
float
|
Voltage threshold for activation. Defaults to -50.0. |
-50.0
|
dtime |
float
|
Time between samples in milliseconds. Defaults to 1.0. |
1.0
|
apply(scalars)
Compute the local activation times (LATs) for each point.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
scalars |
ndarray
|
Input scalar array with shape (points, timepoints). |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
np.ndarray: LAT array with shape (n_points, n_lats), NaN where no LAT detected. |
MovingAverage
Bases: ScalarFilter
Apply a moving average filter to the input signal(s).
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
window_length |
int
|
Length of the moving average window. Defaults to 5. |
5
|
mode |
str
|
Convolution mode. Defaults to "same". |
'same'
|
mode: str = mode
instance-attribute
window_length: int = window_length
instance-attribute
__init__(window_length=5, mode='same')
Initializes MovingAverage filter with a windowlenght and convolution mode.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
window_length |
int
|
Length of the moving average window. Defaults to 5. |
5
|
mode |
str
|
Convolution mode. Defaults to "same". |
'same'
|
apply(scalars)
Smooth the signal using a moving average.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
scalars |
ndarray
|
Input scalar array with shape (points, timepoints). |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
np.ndarray: Filtered scalar array with the same shape. |
Normalize
Bases: ScalarFilter
Normalize input scalar signal(s) to range [0, 1].
apply(scalars)
Normalize the scalar array to [0, 1].
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
scalars |
ndarray
|
Input scalar array. |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
np.ndarray: Normalized scalar array. |
ScalarFilter
Bases: ABC
Abstract base class for scalar signal filters.
apply(scalars)
abstractmethod
Apply the filter to the input scalars.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
scalars |
ndarray
|
Input scalar array of shape (n_points, n_timepoints). |
required |
Returns:
| Type | Description |
|---|---|
ndarray
|
np.ndarray: Filtered scalar array of the same shape. |