waveform_editor.tendencies.piecewise.PiecewiseLinearTendency¶

class waveform_editor.tendencies.piecewise.PiecewiseLinearTendency(user_time=None, user_value=None, **kwargs)¶

Bases: BaseTendency

A tendency representing a piecewise linear function.

__init__(user_time=None, user_value=None, **kwargs)¶

Methods

__init__([user_time, user_value])
get_derivative(time)	Get the values of the derivatives at the provided time array.
get_value([time])	Get the tendency values at the provided time array.
set_next_tendency(next_tendency)	Sets the next tendency as a param.
set_previous_tendency(prev_tendency)	Sets the previous tendency as a param.

Attributes

allow_zero_duration
annotations
duration
end
end_derivative
end_value
is_first_repeated
line_number
name
next_tendency
param
prev_tendency
start
start_derivative
start_value
start_value_set
time
times_changed
user_duration
user_end
user_start
value
values_changed

get_derivative(time: ndarray) → ndarray¶

Get the values of the derivatives at the provided time array.

Parameters:

time: ndarray¶

The time array on which to generate points.

Returns:

numpy array containing the derivatives

get_value(time: ndarray | None = None) → tuple[numpy.ndarray, numpy.ndarray]¶

Get the tendency values at the provided time array. If a time array is provided, the values will be linearly interpolated between the piecewise linear points.

Parameters:

time: ndarray | None = None¶

The time array on which to generate points.

Returns:

Tuple containing the time and its tendency values.

set_next_tendency(next_tendency)¶

Sets the next tendency as a param.

Parameters:

next_tendency¶

The tendency follows the current tendency.

set_previous_tendency(prev_tendency)¶

Sets the previous tendency as a param.

Parameters:

prev_tendency¶

The tendency precedes the current tendency.

time = array([0, 1, 2])¶

value = array([0, 1, 2])¶