#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Control a CW Doppler radar based on the Innosent IVS-162. 

Daniel Sjoberg, 2018-02-04
"""

# Import libraries
from __future__ import print_function
from pylab import *   # Loads many 'matlab-like' commands
from ADCDACPi import ADCDACPi
import RPi.GPIO as GPIO

# Settings for using the ADCDACPi 
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BOARD)
GPIO.setup(22, GPIO.OUT)
GPIO.output(22, False)
adcdac = ADCDACPi(1)

# Radar and signal processing parameters
adcdac.set_dac_voltage(2, 0.0) # Enable the radar module
adcdac.set_dac_voltage(1, 0.0) # Set tuning voltage to zero
N = 128                        # Number of samples 
a = zeros(N, dtype=complex)    # Storage for the analytic signal
PlotMode = 'LivePlot'          # Choose between 'LivePlot', 'Capture', 'Text'

if PlotMode == 'LivePlot':     # Some settings are necessary to enable 
    ion()                      # a plot that is updated as the measurements
    fig = figure()             # proceed. Note that this takes significant
    ax = fig.add_subplot(111)  # processing resources and slows the radar down.
    line1, = ax.plot(np.real(a))
    xlabel('Doppler frequency (Hz)')
    ylabel('Amplitude spectrum')
    xlim(-2000, 2000)
    ylim(0, 1)

# Infinite measurement loop, break by ctrl-c or set PlotMode='Capture'
while True:
    starttime = datetime.datetime.now()       # Start time
    for n in range(0, N):                     # Sample N values
        I = adcdac.read_adc_voltage(1, 0)     # Read I signal from pin 1
        Q = adcdac.read_adc_voltage(2, 0)     # Read Q signal from pin 2
        a[n] = I + 1j*Q                       # Save as analytic signal
    endtime = datetime.datetime.now()         # Stop time
    T = (endtime - starttime).total_seconds() # Compute total time
    m = mean(a)                               # Estimate the mean
    a_f = fftshift(fft(a - m))                # Compute Fourier transform for zero mean
    fvec = fftshift(fftfreq(N, d=T/N))        # Compute frequencies
    f = fvec[abs(a_f) == max(abs(a_f))][0]    # Find frequency of maximum signal
    if PlotMode == 'LivePlot':                # Update plot 
        line1.set_xdata(fvec)
        line1.set_ydata(abs(a_f))
        fig.canvas.draw()
    elif PlotMode == 'Capture':               # Make some plots and exit
        figure()                              # Plots can be saved using GUI
        plot(linspace(0, T, len(a)), real(a), 'b-')
        plot(linspace(0, T, len(a)), imag(a), 'r--')
        xlabel('Time (s)')
        ylabel('Raw analytic signal')
        figure()
        plot(linspace(0, T, len(a)), real(a-m), 'b-')
        plot(linspace(0, T, len(a)), imag(a-m), 'r--')
        xlabel('Times (s)')
        ylabel('Zero mean analytic signal')
        figure()
        plot(fvec, abs(a_f))
        xlabel('Doppler frequency (Hz)')
        ylabel('Amplitude spectrum')
        show()
        exit()
    print('Doppler frequency = {0:10.2f} Hz'.format(f))  # Print Doppler frequency of maximum signal