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TISC_sim.py
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TISC_sim.py
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#!/usr/bin/env python
# A very simple impulsive signal + noise generator to get the
import random
#from array import array
import numpy as np
from impulse import impulse_gen
from anita_filter import butter_bandpass, butter_bandpass_filter
from noise import generate_noise
from digitizer import digitize
from sum_correlator import sum_correlate
from cw import generate_cw
from datetime import datetime
def TISC_sim(SNR,threshold,
b_input_delay,c_input_delay,num_bits=3,
noise_sigma=32.0,
sample_freq=2600000000.0,TISC_sample_length=16,
num_samples=74,upsample=10,cw_flag=0,
cw_rms=25.0,carrier_frequency=260000000.0,modulation_frequency=1.0,
seed=5522684,draw_flag=0,digitization_factor=32.0,
delay_type_flag=1,
output_dir="output/",average_subtract_flag=0,correlation_mean=np.zeros(44),trial_run_number=1):
#print b_input_delay
# Setup
save_output_flag = 0
#if(save_output_flag):
#outfile = str(output_dir+"/test.root")
trigger_flag = 0
#num_bits = 3 # Number of bits available to the digitizer
filter_flag = False
#print SNR
# Fill numpy arrays with zeros
a_input_noise = np.zeros(num_samples)
b_input_noise = np.zeros(num_samples)
c_input_noise = np.zeros(num_samples)
a_input_noise_test = np.zeros(num_samples)
b_input_noise_test = np.zeros(num_samples)
c_input_noise_test = np.zeros(num_samples)
a_input_signal = np.zeros(num_samples)
b_input_signal = np.zeros(num_samples)
c_input_signal = np.zeros(num_samples)
a_dig_waveform = np.zeros(num_samples)
b_dig_waveform = np.zeros(num_samples)
c_dig_waveform = np.zeros(num_samples)
cw_noise = np.zeros(num_samples)
empty_list = np.zeros(num_samples)
###################################
# Generate Thermal Noise
a_input_noise = generate_noise(num_samples,noise_sigma,filter_flag)
b_input_noise = generate_noise(num_samples,noise_sigma,filter_flag)
c_input_noise = generate_noise(num_samples,noise_sigma,filter_flag)
#a_input_noise_test = a_input_noise
#b_input_noise_test = b_input_noise
#c_input_noise_test = c_input_noise
###################################
#print a_input_noise[0]
#print b_input_noise[0]
#print c_input_noise[0]
#####################################
# Determine signal amplitude
signal_amp = SNR*2*noise_sigma
#####################################
#################################
#Generate CW & thermal noise
if cw_flag:
cw_noise = generate_cw(num_samples,upsample,sample_freq,carrier_frequency,modulation_frequency,cw_rms,filter_flag)
a_input_noise = np.add(a_input_noise,cw_noise)
#cw_noise = generate_cw(num_samples,sample_freq,carrier_frequency,modulation_frequency,peak_amplitude,filter_flag)
b_input_noise = np.add(b_input_noise,cw_noise)
#cw_noise = generate_cw(num_samples,sample_freq,carrier_frequency,modulation_frequency,peak_amplitude,filter_flag)
c_input_noise = np.add(c_input_noise,cw_noise)
#####################################
# Filter the noise
a_input_noise = butter_bandpass_filter(a_input_noise)
b_input_noise = butter_bandpass_filter(b_input_noise)
c_input_noise = butter_bandpass_filter(c_input_noise)
#print "Filter Took: " +str(datetime.now()-start_filter)
#start_signal = datetime.now()
#####################################
# Generate impulse
if (SNR != 0):
# Generate Signal and Amplify
a_input_signal = impulse_gen(num_samples,upsample,draw_flag=draw_flag,output_dir=output_dir)
difference=np.amax(a_input_signal)-np.amin(a_input_signal) # Get peak to peak voltage
a_input_signal *= (1/difference) # Normalize input
a_input_signal *= signal_amp # Amplify
b_input_signal = np.concatenate([a_input_signal[:num_samples+b_input_delay],empty_list[:(-1)*b_input_delay]])
c_input_signal = np.concatenate([a_input_signal[:num_samples+c_input_delay],empty_list[:(-1)*c_input_delay]])
# Add the signal to the noise
a_input_signal = np.add(a_input_noise, a_input_signal)
b_input_signal = np.add(b_input_noise, b_input_signal)
c_input_signal = np.add(c_input_noise, c_input_signal)
else:
a_input_signal = a_input_noise
b_input_signal = b_input_noise
c_input_signal = c_input_noise
##########################################
##########################################
# Digitized the incoming signal and noise (RITC)
a_dig_waveform = digitize(a_input_signal,num_samples,num_bits,digitization_factor)
b_dig_waveform = digitize(b_input_signal,num_samples,num_bits,digitization_factor)
c_dig_waveform = digitize(c_input_signal,num_samples,num_bits,digitization_factor)
##########################################
#print a_dig_waveform
##########################################
# Run the signal through the GLITC module to get trigger
if (average_subtract_flag):
trigger_flag, max_sum, as_max_sum, correlation_mean, test_sum, as_test_sum = sum_correlate(num_samples,a_dig_waveform,b_dig_waveform,c_dig_waveform,
threshold,TISC_sample_length,delay_type_flag=delay_type_flag,
average_subtract_flag=average_subtract_flag,correlation_mean=correlation_mean,trial_run_number=trial_run_number)
else:
trigger_flag, max_sum, test_sum = sum_correlate(num_samples,a_dig_waveform,b_dig_waveform,c_dig_waveform,
threshold,TISC_sample_length,delay_type_flag=delay_type_flag,
average_subtract_flag=average_subtract_flag,correlation_mean=correlation_mean)
"""
if (max_sum>800):
import matplotlib.pyplot as plt
#print a_dig_waveform
#print b_dig_waveform
#print c_dig_waveform
#print np.add(np.add(a_dig_waveform,b_dig_waveform),c_dig_waveform)
#print (np.add(np.add(a_dig_waveform,b_dig_waveform),c_dig_waveform))**2
#print np.sum((np.add(np.add(a_dig_waveform,b_dig_waveform),c_dig_waveform))**2)
time = np.linspace(0.0,((num_samples*(10**9))/sample_freq), num_samples)
plt.figure(1)
plt.clf()
plt.plot(time,a_dig_waveform)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch A")
plt.savefig(output_dir+"/ch_A_large_correlation.png")
plt.figure(2)
plt.clf()
plt.plot(time,b_dig_waveform)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch B")
plt.savefig(output_dir+"/ch_B_large_correlation.png")
plt.figure(3)
plt.clf()
plt.plot(time,c_dig_waveform)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch C")
plt.savefig(output_dir+"/ch_C_large_correlation.png")
plt.figure(4)
plt.clf()
plt.plot(time,np.add(np.add(a_dig_waveform,b_dig_waveform),c_dig_waveform))
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("ABC Added")
plt.savefig(output_dir+"/ABC_large_correlation.png")
plt.figure(5)
plt.clf()
plt.plot(time,(np.add(np.add(a_dig_waveform,b_dig_waveform),c_dig_waveform))**2)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("ABC Square Added")
plt.savefig(output_dir+"/ABC_square_large_correlation.png")
plt.figure(6)
plt.clf()
plt.plot(time,a_input_noise_test)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch A Thermal Noise")
plt.savefig(output_dir+"/ch_A_thermal_large_correlation.png")
plt.figure(7)
plt.clf()
plt.plot(time,b_input_noise_test)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch B Thermal Noise")
plt.savefig(output_dir+"/ch_B_thermal_large_correlation.png")
plt.figure(8)
plt.clf()
plt.plot(time,c_input_noise_test)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("Ch C Thermal Noise")
plt.savefig(output_dir+"/ch_C_thermal_large_correlation.png")
plt.figure(9)
plt.clf()
plt.plot(time,cw_noise)
plt.xlabel("Time [ns]")
plt.ylabel("Amplitude [unitless]")
plt.title("CW Noise")
plt.savefig(output_dir+"/cw_large_correlation.png")
plt.show()
"""
#########################################
#########################################
# Output data
#if(save_output_flag):
# Now to more ROOT stuff
#rf_tree.Fill()
#f.Write()
#f.Close()
if draw_flag:
dummy = raw_input('Press any key to close')
#print "Everything took: " +str(datetime.now()-start_time)
if (average_subtract_flag):
return trigger_flag, max_sum, as_max_sum, correlation_mean, test_sum, as_test_sum
else:
return trigger_flag, max_sum
if __name__ == '__main__':
#import ROOT
import time
num_samples = 80
impulse_position = 0
num_bits = 3
#signal_amp = 10.0
draw_flag = False
# These delays should be negative, since A is the top antenna
# and we expect an upgoing signal
b_input_delay = -8
c_input_delay = -7
SNR = 5
threshold = 100
noise_sigma = 20
#num_runs = 100
upsample = 1
cw_flag = True
cw_rms = 1.0*noise_sigma
cw_frequency = 260000000.0
modulation_frequency = 1.0
delay_type_flag = 1
digitization_factor=20.0
average_subtract_flag = 1
#global correlation_mean
correlation_mean = np.zeros(44)
correlation_mean.fill(100)
#print correlation_mean
print "SNR: "+str(SNR)
print "Threshold: "+str(threshold)
# Get impulse signal
#a_input_signal = np.zeros(num_samples*upsample)
#a_input_signal = impulse_gen(num_samples,impulse_position,upsample=upsample,draw_flag=draw_flag)
for i in range(0,10):
passedFlag, max_sum, as_max_sum, correlation_mean, d1, d2 = TISC_sim(SNR,threshold,b_input_delay,c_input_delay,num_bits=num_bits,
upsample=upsample,num_samples=num_samples,noise_sigma=noise_sigma,
cw_flag=cw_flag,cw_rms=cw_rms,carrier_frequency=cw_frequency,modulation_frequency=modulation_frequency,
draw_flag=draw_flag,digitization_factor=digitization_factor,output_dir="output/",delay_type_flag=delay_type_flag,
average_subtract_flag=average_subtract_flag,correlation_mean=correlation_mean,trial_run_number=(i+1))
print max_sum
print as_max_sum