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ssa_tone_5.py
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# import numpy as np
# import sounddevice as sd
# from math import pi
# import random
####################
d = 0.05 # duration of the tone (seconds , when the sampling rate is defined by you, the device will understand what 3 seconds means !)
sr = 48000 # sampling rate
rpt = 100 # If you change the repeatition to 10000, the program crashes.
# frequency of a tone.
f = 600
###################
# increment factor
a = (600/11)**(1/7)
soi_1 = 0.11
soi_2 = soi_1 * a
soi_3 = soi_1 * (a**2)
soi_4 = soi_1 * (a**3)
soi_5 = soi_1 * (a**4)
soi_6 = soi_1 * (a**5)
soi_7 = soi_1 * (a**6)
soi_8 = 6
# itl = interval
itl_1 = soi_1 - d
itl_2 = soi_2 - d
itl_3 = soi_3 - d
itl_4 = soi_4 - d
itl_5 = soi_5 - d
itl_6 = soi_6 - d
itl_7 = soi_7 - d
itl_8 = soi_8 - d
####################
# duration of the tone is 'd' here.
# if 'int' would not be inserted, this error would emerge :
# TypeError: 'float' object cannot be interpreted as an integer
# sound may be either noise or tone.
##sound = np.random.uniform( low=-1 , high=1 , size=int(d*sr) )
# tone
dots = np.arange(0,d,1/sr)
sound = np.sin(2*pi*f*dots)
# noise , I (old) = sound (current)
# noise.shape , I.shape = (1600,)
######################################
######################################
# ramp
# rpr = ramp__plateu__ramp
rpr = np.ones(int(d*sr))
# ascending ramp.
# 1st 7ms.
rpr[0: int(0.007 * sr) ] = np.linspace(0,1,int(0.007 * sr))
# descending ramp.
# last 7ms.
rpr[ -int(0.007 * sr ) : ] = np.linspace(1,0,int(0.007 * sr))
#####################
#####################
# ramped sound
r_s = sound * rpr
#############
#############
# if not mentioning 'int', this error would result :
# TypeError: 'float' object cannot be interpreted as an integer
silence_1 = np.zeros(int(itl_1*sr))
silence_2 = np.zeros(int(itl_2*sr))
silence_3 = np.zeros(int(itl_3*sr))
silence_4 = np.zeros(int(itl_4*sr))
silence_5 = np.zeros(int(itl_5*sr))
silence_6 = np.zeros(int(itl_6*sr))
silence_7 = np.zeros(int(itl_7*sr))
silence_8 = np.zeros(int(itl_8*sr))
####################
# not necessarily all the tone-noise period should be on trigger.
# only the START is important.
# list(range(10))
# Out[40]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
# 2 ms.
trig = np.zeros(int(d*sr))
for i in range (96) :
trig[i] = 1
# flat period of trigger (corresponding to the silence of the tone).
zeros_1 = np.zeros(int(itl_1*sr))
zeros_2 = np.zeros(int(itl_2*sr))
zeros_3 = np.zeros(int(itl_3*sr))
zeros_4 = np.zeros(int(itl_4*sr))
zeros_5 = np.zeros(int(itl_5*sr))
zeros_6 = np.zeros(int(itl_6*sr))
zeros_7 = np.zeros(int(itl_7*sr))
zeros_8 = np.zeros(int(itl_8*sr))
#####################
# ss = sound + silence. vectoral concatenation.
ss_1 = np.concatenate((r_s,silence_1) , axis=None)
ss_2 = np.concatenate((r_s,silence_2) , axis=None)
ss_3 = np.concatenate((r_s,silence_3) , axis=None)
ss_4 = np.concatenate((r_s,silence_4) , axis=None)
ss_5 = np.concatenate((r_s,silence_5) , axis=None)
ss_6 = np.concatenate((r_s,silence_6) , axis=None)
ss_7 = np.concatenate((r_s,silence_7) , axis=None)
ss_8 = np.concatenate((r_s,silence_8) , axis=None)
# sound channel containing the total number of repeatitions.
sound_channel_1 = np.tile(ss_1 , rpt)
sound_channel_2 = np.tile(ss_2 , rpt)
sound_channel_3 = np.tile(ss_3 , rpt)
sound_channel_4 = np.tile(ss_4 , rpt)
sound_channel_5 = np.tile(ss_5 , rpt)
sound_channel_6 = np.tile(ss_6 , rpt)
sound_channel_7 = np.tile(ss_7 , rpt)
sound_channel_8 = np.tile(ss_8 , rpt)
#############
# tz = trigger + zeros . vectoral concatenation.
tz_1 = np.concatenate((trig,zeros_1) , axis=None)
tz_2 = np.concatenate((trig,zeros_2) , axis=None)
tz_3 = np.concatenate((trig,zeros_3) , axis=None)
tz_4 = np.concatenate((trig,zeros_4) , axis=None)
tz_5 = np.concatenate((trig,zeros_5) , axis=None)
tz_6 = np.concatenate((trig,zeros_6) , axis=None)
tz_7 = np.concatenate((trig,zeros_7) , axis=None)
tz_8 = np.concatenate((trig,zeros_8) , axis=None)
# trigger channel containing the total number of repeatitions.
trigger_channel_1 = np.tile(tz_1 , rpt)
trigger_channel_2 = np.tile(tz_2 , rpt)
trigger_channel_3 = np.tile(tz_3 , rpt)
trigger_channel_4 = np.tile(tz_4 , rpt)
trigger_channel_5 = np.tile(tz_5 , rpt)
trigger_channel_6 = np.tile(tz_6 , rpt)
trigger_channel_7 = np.tile(tz_7 , rpt)
trigger_channel_8 = np.tile(tz_8 , rpt)
#############
# st = 2 channels : sound & trigger : Axial channel concatenation :
st_1 = np.concatenate(([sound_channel_1],[trigger_channel_1]) , axis=0)
st_2 = np.concatenate(([sound_channel_2],[trigger_channel_2]) , axis=0)
st_3 = np.concatenate(([sound_channel_3],[trigger_channel_3]) , axis=0)
st_4 = np.concatenate(([sound_channel_4],[trigger_channel_4]) , axis=0)
st_5 = np.concatenate(([sound_channel_5],[trigger_channel_5]) , axis=0)
st_6 = np.concatenate(([sound_channel_6],[trigger_channel_6]) , axis=0)
st_7 = np.concatenate(([sound_channel_7],[trigger_channel_7]) , axis=0)
st_8 = np.concatenate(([sound_channel_8],[trigger_channel_8]) , axis=0)
###############
# randomizing the soi.s .
st_all = [ st_1 ,st_2, st_3, st_4, st_5, st_6, st_7, st_8 ]
random.shuffle(st_all)
###########
# putting a bracket arround I or trig, is for changing them from a vector with 1 dimenstion, to an array with 2 dimensions. Remember: a 1 column or 1 row array, has 2 dimensions, unlike a vector.
# Otherwise concatenation can not be done correctly.
##########
# iti = inter-train interval
# here : 60 s
iti = np.zeros((2 , int(60*sr)))
# iti.shape : (2, 960000)
###########
total = np.concatenate((st_all[0] , iti , st_all[1] , iti , st_all[2] , iti , st_all[3] , iti , st_all[4] , iti , st_all[5] , iti , st_all[6] , iti , st_all[7]) , axis=1)
##################
# the above 'total' array is of the shape (2,n). i.e. having 2 rows.
# sounddevice splits channels into columns. Hence this array should be transposed to get in the shape (n,2).
total_T = total.T
###################
# initial silence.
# here : 4s.
# this is to prevent initial glitch at the loudspeaker to disturb the adaptation while starting the paradigm.
insl = np.zeros((4*sr , 2))
# initial silence added to the whole sequence.
insl_total_T = np.concatenate((insl , total_T) , axis=0)
#################
sd.play(insl_total_T,sr)
# to check the plot :
# plt.plot(tt_T)
'''
White socket (from the USB audio interface) is sound.
In total the experiment lasts for 30 minutes.
stg software : download & start the program.
turn your volume to max.
change the pitch.
for test reasons you can use this :
sd.play(st_4.T , sr )
####################
the trigger length must put to 4000 (with a sampling rate of 48000 instead of 16000), for the triggers to be shown in oscilloscope !!
trig = np.zeros(int(d*sr))
for i in range (4000) :
trig[i] = 1
plot :
plt.plot(insl_total_T[192000: 336000 , :])
'''