data_storage.py

"""
Created by : Team Unique Tech for ITSP, IIT Bombay

The below code is for storing the signal data coming from the electrical circuit through the RaspberryPi. 
The code creates arrays for data collected from the RaspberryPi. 

"""

import numpy as np
import time
from math import pi
from read_adc import read_val

# some fundamental definitions and variables

T = 0.0 # initialize time interval (in s) for which the input was taken
n = 400000 # number of samples or number of data points (will represent sound intensity in 10-bits)
dt = T/n # average time interval (in s) between two readings
df = 0.0 # initialize fundamental frequency of the fft
dw = 2*pi*df # initialize fundamental angular frequency of the fft
ny = df*n/2 # initialize nyquist frequency (or the top frequency)
freq = 2000 # frequency of the sound-source 

def data():
	
	mic_data_0 = np.array([]) # used to store data from mic1 for 'n' sample points
	mic_data_1 = np.array([]) # ----------""----------- mic2 ---------""----------
	mic_data_2 = np.array([]) # ----------""----------- mic3 ---------""----------
	mic_data_3 = np.array([]) # ----------""----------- mic4 ---------""----------

	t_axis = np.array([]) # used to create the time axis for data obtained through mic

	temp = n
	t_start = time.time()

	while(temp>0):

		temp -= 1
		# take the input from the mics through read_val and store it in the array
		mic_temp_0, mic_temp_1, mic_temp_2, mic_temp_3 = read_val()
		t_now = time.time()
		mic_data_0 = np.append(mic_data_0, mic_temp_0)
		mic_data_1 = np.append(mic_data_1, mic_temp_1)
		mic_data_2 = np.append(mic_data_2, mic_temp_2)
		mic_data_3 = np.append(mic_data_3, mic_temp_3)
		t_delay = t_now - t_start # calculating the delay from the start of loop (/the point after which readings were taken)
		t_axis = np.append(t_axis, t_delay) # update the t_axis array
		
	t_end = time.time()
	
	T = t_end - t_start # update time interval (in s) for which the input was taken
	dt = T/n # update average time interval (in s) between two readings
	df = 1/T # update fundamental frequency of the fft
	dw = 2*pi*df # update fundamental angular frequency of the fft
	ny = df*n/2 # update nyquist frequency (or the top frequency)

	return mic_data_0, mic_data_1, mic_data_2, mic_data_3