import marimo

__generated_with = "0.25.1"
app = marimo.App()


@app.cell
def _():
    import marimo as mo

    return (mo,)


@app.cell(hide_code=True)
def _(mo):
    mo.md(r"""
    # Spectrum example
    """)
    return


@app.cell
def _():
    import numpy as np
    import matplotlib.pyplot as pl
    from matplotlib import rcParams
    rcParams.update({'figure.figsize': (10, 8)})
    rcParams.update({'font.size': 14})
    return np, pl


@app.cell
def _(np):
    fs = 100 # Hz
    y = np.loadtxt('data/FFT_Example_data_with_window.txt')
    t = np.linspace(0,len(y)/fs,len(y))
    return fs, t, y


@app.cell
def _(pl, t, y):
    pl.plot(t,y)
    pl.xlabel('$t$ [sec]',fontsize=16)
    pl.ylabel('$y$ [V]',fontsize=16)
    return


@app.cell
def _(np, y):
    # subtract the DC:
    yf = y - np.mean(y)
    return (yf,)


@app.cell
def _(pl, t, yf):
    pl.plot(t,yf)
    pl.xlabel('$t$ [sec]',fontsize=16)
    pl.ylabel('$y - DC(y) $ [V]',fontsize=16)
    return


@app.cell
def _(np, pl):
    def spectrum(y,Fs):
        """
        Plots a Single-Sided Amplitude Spectrum of a sampled
        signal y(t), sampling frequency Fs (lenght of a signal 
        provides the number of samples recorded)
    
        Following: http://goo.gl/wRoUn
        """
        n = len(y) # length of the signal
        k = np.arange(n)
        T = n/Fs
        frq = k/T # two sides frequency range
        frq = frq[range(int(n/2))] # one side frequency range
        Y = 2*np.fft.fft(y)/n # fft computing and normalization
        Y = Y[range(int(n/2))]
        return frq, Y

    def plotSignal(t,y,frq,Y):
        """ plots the time signal Y(t) and the 
        frequency spectrum Y(fs)
        Inputs:
            t - time 
            y - signal
        Outputs:
            t - time signal, [sec]
            Y - values, [Volt]
        Usage:
            plotSignal(t,y,fs)
        """

        # Plot
        pl.figure()
        pl.subplot(2,1,1)
        pl.plot(t,y,'b-')
        pl.xlabel('$t$ [s]',fontsize=16)
        pl.ylabel('$Y$ [V]',fontsize=16)
        # axes().set_aspect(0.2)
        # title('sampled signal')
        pl.subplot(2,1,2)
        pl.plot(frq,abs(Y),'r') # plotting the spectrum
        pl.xlabel('$f$ (Hz)',fontsize=16)
        pl.ylabel('$|Y(f)|$',fontsize=16)

    return plotSignal, spectrum


@app.cell
def _(fs, plotSignal, spectrum, t, yf):
    frq,Y = spectrum(yf,fs) 
    plotSignal(t,yf,frq,Y)
    return


if __name__ == "__main__":
    app.run()