89 lines
3.8 KiB
Python
89 lines
3.8 KiB
Python
from stimuli.AbstractStimulus import AbstractStimulus
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import numpy as np
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from numba import jit, njit
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class SinusAmplitudeModulationStimulus(AbstractStimulus):
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def __init__(self, carrier_frequency, contrast, modulation_frequency, start_time=0, duration=np.inf, amplitude=1):
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self.contrast = contrast
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self.modulation_frequency = modulation_frequency
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self.amplitude = amplitude
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self.carrier_frequency = carrier_frequency
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self.start_time = start_time
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self.duration = duration
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def value_at_time_in_s(self, time_point):
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carrier = np.sin(2 * np.pi * self.carrier_frequency * time_point)
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if time_point < self.start_time or time_point > self.start_time + self.duration:
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return self.amplitude * carrier
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am = (1 + self.contrast * np.sin(2*np.pi*self.modulation_frequency * time_point))
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return self.amplitude * am * carrier
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def get_stimulus_start_s(self):
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return self.start_time
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def get_stimulus_duration_s(self):
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return self.duration
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def get_amplitude(self):
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return self.contrast
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def as_array(self, time_start, total_time, step_size):
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carrier = self.carrier_frequency
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amp = self.amplitude
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mod_freq = self.modulation_frequency
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contrast = self.contrast
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start_time = self.start_time
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duration = self.duration
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values = convert_to_array(carrier, amp, mod_freq, contrast, start_time, duration, time_start, total_time, step_size)
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return values
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# @jit(nopython=True) # makes it slower?
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def convert_to_array(carrier_freq, amplitude, modulation_freq, contrast, start_time, duration, time_start, total_time, step_size_s):
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# if the whole stimulus time has the amplitude modulation just built it at once;
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if time_start >= start_time and start_time+duration < time_start+total_time:
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carrier = np.sin(2 * np.pi * carrier_freq * np.arange(start_time, total_time - start_time, step_size_s))
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modulation = 1 + contrast * np.sin(2 * np.pi * modulation_freq * np.arange(start_time, total_time - start_time, step_size_s))
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values = amplitude * carrier * modulation
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return values
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# if it is split into parts with and without amplitude modulation built it in parts:
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values = np.array([], dtype='float32')
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if time_start < start_time:
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carrier_before_am = np.sin(2 * np.pi * carrier_freq * np.arange(time_start, start_time, step_size_s))
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values = np.concatenate((values, amplitude * carrier_before_am))
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# there is at least a second part of the stimulus that contains the amplitude:
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# time starts before the end of the am and ends after it was started
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if time_start < start_time+duration and time_start+total_time > start_time:
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if duration is np.inf:
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carrier_during_am = np.sin(
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2 * np.pi * carrier_freq * np.arange(start_time, time_start + total_time, step_size_s))
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am = 1 + contrast * np.sin(
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2 * np.pi * modulation_freq * np.arange(start_time, time_start + total_time, step_size_s))
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else:
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carrier_during_am = np.sin(
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2 * np.pi * carrier_freq * np.arange(start_time, start_time + duration, step_size_s))
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am = 1 + contrast * np.sin(
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2 * np.pi * modulation_freq * np.arange(start_time, start_time + duration, step_size_s))
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values = np.concatenate((values, amplitude * am * carrier_during_am))
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else:
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if contrast != 0:
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print("Given stimulus time parameters (start, total) result in no part of it containing the amplitude modulation!")
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if time_start+total_time > start_time+duration:
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carrier_after_am = np.sin(2 * np.pi * carrier_freq * np.arange(start_time + duration, time_start + total_time, step_size_s))
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values = np.concatenate((values, amplitude*carrier_after_am))
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return values
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