import streamlit as st
import pyttsx3
from scipy.io import wavfile
from scipy import signal
from scipy.spatial import distance
import plotly.graph_objs as go
import numpy as np
from scipy.interpolate import interp2d


def similarity(file1, file2):
    fs1, data1 = wavfile.read(file1)
    fs2, data2 = wavfile.read(file2)

    f1, t1, Sxx1 = signal.spectrogram(data1, fs=fs1)
    f2, t2, Sxx2 = signal.spectrogram(data2, fs=fs2)

    interp1 = interp2d(t1, f1, Sxx1)
    interp2 = interp2d(t2, f2, Sxx2)

    tmin = max(t1.min(), t2.min())
    tmax = min(t1.max(), t2.max())
    fmin = max(f1.min(), f2.min())
    fmax = min(f1.max(), f2.max())

    tnew = np.linspace(tmin, tmax, num=max(len(t1), len(t2)))
    fnew = np.linspace(fmin, fmax, num=max(len(f1), len(f2)))

    Sxx1new = interp1(tnew, fnew)
    Sxx2new = interp2(tnew, fnew)

    d = distance.euclidean(Sxx1new.flatten(), Sxx2new.flatten())
    max_d = max(Sxx1new.max(), Sxx2new.max()) * len(Sxx1new.flatten())

    return 100 * (1 - d / max_d)

st.title('Text to Sound Comparing')

texto1 = st.text_input('First text','hi')
texto2 = st.text_input('Second text','five')

intercambiar = st.selectbox('Interchange texts', [False, True])

if intercambiar:
    texto1, texto2 = texto2, texto1

if texto1=="":
        texto1="hi"

if texto2=="":
        texto2="five"

if 1:
        engine = pyttsx3.init()
        engine.setProperty('voice', 'english')
        engine.save_to_file(texto1, 'texto1.wav')
        engine.save_to_file(texto2, 'texto2.wav')
        engine.runAndWait()

        fs1, data1 = wavfile.read('texto1.wav')
        fs2, data2 = wavfile.read('texto2.wav')

        inicio1 = st.slider('Start 1: '+str(texto1), 0, len(data1), 0)
        inicio2 = st.slider('Start 2: '+str(texto2), 0, len(data2), 0)

        f1, t1, Sxx1 = signal.spectrogram(data1[inicio1:], fs=fs1)
        f2, t2, Sxx2 = signal.spectrogram(data2[inicio2:], fs=fs2)

        fig1 = go.Figure()
        fig1.add_trace(go.Scatter(y=data1[inicio1:], mode='lines', name='Text 1: '+str(texto1)))
        fig1.add_trace(go.Scatter(y=data2[inicio2:], mode='lines', name='Text 2: '+str(texto2)))
        st.header('Waves')
        st.plotly_chart(fig1)

        fig2 = go.Figure()
        fig2.add_trace(go.Heatmap(x=t1, y=f1, z=Sxx1, name='Spectrogram 1', xaxis='x2', yaxis='y2'))
        st.header('Spectrogram '+str(texto1))
        st.plotly_chart(fig2)

        fig3 = go.Figure()
        fig3.add_trace(go.Heatmap(x=t2, y=f2, z=Sxx2, name='Spectrogram 2', xaxis='x3', yaxis='y3'))
        st.header('Spectrogram '+str(texto2))
        st.plotly_chart(fig3)

        #sim = similarity('texto1.wav', 'texto2.wav')
        #print(f'Similarity: {sim:.2f}%')
        #st.header('Similarity: '+str(sim))

        N = len(data1[inicio1:])
        T = 1.0 / fs1
        yf = np.fft.fft(data1[inicio1:])
        xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
        fig4 = go.Figure()
        fig4.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 1: '+str(texto1)))
        st.header('Fourier '+str(texto1))
        st.plotly_chart(fig4)

        N = len(data2[inicio2:])
        T = 1.0 / fs2
        yf = np.fft.fft(data2[inicio2:])
        xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
        fig5 = go.Figure()
        fig5.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 2: '+str(texto2)))
        st.header('Fourier '+str(texto2))
        st.plotly_chart(fig5)


        N = len(data1[inicio1:])
        T = 1.0 / fs1
        yf = np.fft.fft(data1[inicio1:])
        xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
        fig6 = go.Figure()
        fig6.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 1: '+str(texto1)))

        N = len(data2[inicio2:])
        T = 1.0 / fs2
        yf = np.fft.fft(data2[inicio2:])
        xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
        fig6.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 2: '+str(texto2)))

        st.header('Fourier Mix')
        st.plotly_chart(fig6)