LinBurst {OscillatorGenerator}

Generation of a Burst Signal with Linear Rise and Decline

Description

This function takes in numeric arguments for a customizable, burst shape with linear rise and decline. Each oscillation cycle is separated into four phases: the growth phase, in which the oscillator rises from the baseline to the peak concentration, a first drop phase, in which the oscillator declines from the peak to the secondary peak concentration, a second drop phase, in which the oscillator declines from the secondary peak to the baseline concentration and an inactive phase, in which the oscillator stays at baseline concentration. A discretized time course is returned.

Usage

LinBurst(baseline, peak, period, duty_cycle, sec_duty_cycle, sec_peak, trend,
  peak_pos, duration, resolution)

Arguments

baseline

minimal oscillation value

peak

maximal oscillation value

period

oscillation period of the oscillating species (reciprocal of the frequency)

duty_cycle

ratio of the active phase (oscillator above baseline) to the total oscillation period

sec_duty_cycle

ratio of the primary active phase (time interval from cycle start till reaching of the secondary peak) to the total active phase

sec_peak

intermediary value reached after the end of the primary active phase

trend

percental decrease or increase in the peak and secondary peak values for the successive oscillation cycles; if set to 1, values remain unchanged

peak_pos

position of the peak value in the primary active phase (example: peak_pos = 0.5, peak position is in the middle of the primary active phase)

duration

duration of the generated time course

resolution

temporal resolution of the generated time course

Details

Standards:

• peak and sec_peak must be larger than baseline

• duration must be larger than resolution

• duration must be a multiple of resolution

• period must be a multiple of resolution

• duration, resolution, peak, sec_peak and period must be larger than 0

• baseline must be larger or equal to 0

• duty_cycle must be larger than 0 and smaller or equal to 1

• sec_duty_cycle must be larger than 0 and smaller or equal to 1

• trend must be larger than 0

• peak_pos must be larger or equal to 0 and smaller than 1

Value

Returns a matrix with two columns: first column time vector, second column oscillator abundance vector.

Examples

# test effect of changes in period
m1 = LinBurst(baseline = 200, peak = 1000, period = 50, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m2 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m3 = LinBurst(baseline = 200, peak = 1000, period = 200, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)

par(mfrow = c(3,1))
plot(m1, type = "l", xlab = "time", ylab = "abundance")
plot(m2, type = "l", xlab = "time", ylab = "abundance")
plot(m3, type = "l", xlab = "time", ylab = "abundance")

# test effect of changes in duty_cycle
m1 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.3,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m2 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m3 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.9,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)

par(mfrow = c(3,1))
plot(m1, type = "l", xlab = "time", ylab = "abundance")
plot(m2, type = "l", xlab = "time", ylab = "abundance")
plot(m3, type = "l", xlab = "time", ylab = "abundance")

# test effect of changes in sec_duty_cycle
m1 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.3, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m2 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.6, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m3 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.9, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)

par(mfrow = c(3,1))
plot(m1, type = "l", xlab = "time", ylab = "abundance")
plot(m2, type = "l", xlab = "time", ylab = "abundance")
plot(m3, type = "l", xlab = "time", ylab = "abundance")

# test effect of changes in trend
m1 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 0.7, peak_pos = 0.3, duration = 500, resolution = 0.1)
m2 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m3 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1.3, peak_pos = 0.3, duration = 500, resolution = 0.1)

par(mfrow = c(3,1))
plot(m1, type = "l", xlab = "time", ylab = "abundance")
plot(m2, type = "l", xlab = "time", ylab = "abundance")
plot(m3, type = "l", xlab = "time", ylab = "abundance")

# test effect of changes in peak_pos
m1 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.3, duration = 500, resolution = 0.1)
m2 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.6, duration = 500, resolution = 0.1)
m3 = LinBurst(baseline = 200, peak = 1000, period = 100, duty_cycle = 0.6,
sec_duty_cycle = 0.5, sec_peak = 850, trend = 1, peak_pos = 0.9, duration = 500, resolution = 0.1)

par(mfrow = c(3,1))
plot(m1, type = "l", xlab = "time", ylab = "abundance")
plot(m2, type = "l", xlab = "time", ylab = "abundance")
plot(m3, type = "l", xlab = "time", ylab = "abundance")