RampTimeSeries

RampTimeSeries(tStart: float = 0.0, tRamp: float = 1.0, smoothness: float = 0.0, offset: float = 0.0, cFactor: float = 1.0)

Bases: TimeSeries

Ramp load-factor time series with optional smoothing.

This time series defines a ramped load-factor history starting at tStart and transitioning over tRamp with optional smoothing, offset, and scale controls.

Tcl form

timeSeries Ramp <tag> <tStart> <tRamp> -smooth <smoothness> -offset <offset> -factor <cFactor>

Attributes:

Name	Type	Description
`tStart`		Start time of the ramp.
`tRamp`		Duration of the ramp.
`smoothness`		Smoothness parameter in the inclusive range `[0, 1]`.
`offset`		Vertical offset applied to the ramp.
`cFactor`		Scale factor applied to the ramp amplitude.

Example

from femora.core.model import Model

model = Model()
ts = model.time_series.ramp(
    tStart=0.0,
    tRamp=2.0,
    smoothness=0.1,
    cFactor=1.0,
)
pattern = model.pattern.plain(time_series=ts)
print(ts.tag)

Create a ramp time series with validated numeric parameters.

Parameters:

Name	Type	Description	Default
`tStart`	`float`	Start time of the ramp.	`0.0`
`tRamp`	`float`	Duration of the ramp.	`1.0`
`smoothness`	`float`	Smoothness parameter in the inclusive range `[0, 1]`.	`0.0`
`offset`	`float`	Vertical offset.	`0.0`
`cFactor`	`float`	Scale factor.	`1.0`

Raises:

Type	Description
`ValueError`	If numeric arguments are invalid or `smoothness` is outside `[0, 1]`.