ReferenceVisualization
Visualization
Lorem ipsum dolor sit amet, consectetur adipiscing elit. This module visualizes individual files or batches.
Automated mode
def plot_dashboard(path_names: dict, column_name: str, sampling_rate: float = 1000.0, units: str = 'mV', auto_run: bool = True)| Name | Type | Description |
|---|---|---|
path_names | dict | Lorem ipsum dolor sit amet. |
column_name | str | Consectetur adipiscing elit. |
sampling_rate | float | Sed do eiusmod tempor. Default is 1000.0. |
units | str | Ut labore et dolore. Default is mV. |
Manual mode
path_names = ability.make_paths()
ability.make_sample_data(path_names)
ability.clean_signals(path_names, sampling_rate=2000)
ability.plot_dashboard(path_names, 'channel_a', units='mV')Clean and plot
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To run some of the samples below, you may also want:
- matplotlib
Clean a folder of files
import ability as ab
paths = ab.make_paths()
ab.plot_dashboard(paths, "channel_a", "mV")Plot a dashboard
import ability as ab
data = ab.read_file("trial.csv")
ab.plot_trace(data, sampling_rate=250, channel=0)Features and windows
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Extract features
import ability as ab
paths = ab.make_paths()
ab.plot_dashboard(paths, "channel_a", "mV", save_as="dashboard.png")