Python function that draws a plot with matplotlib slider

Matplotlib plot using slider widget

I am currently working on demodulating digitally modulated signals for a practical assignement and wish to make some of my code reuseable. I would like to create a function in a seperate file that I can call that will draw me a graph of some sort that has a slider like the one above.

I have tried just using the code I used to generate the plot above in said external function but then the slider does not work and therefore I can't live update teh figure. Is there any way I can achive what I wish to achive or is it not possible?

Here is my current set of code. defined in a external file.

#functions.py
    
def Find_Sampling_indexes(phase_shift:float,period:float, sample_rate:int):
    Clk = np.cos(2*np.pi*sample_rate*period-phase_shift)

    indexes = signal.find_peaks(Clk)
    index = indexes[0]

    return index

fig, ax = plt.subplots()



def update(complex_data,period,symbol_rate,val):
        index = Find_Sampling_indexes(val,period,symbol_rate)
        ax.clear()
        ax.plot(np.real(complex_data[index]),np.imag(complex_data[index]), 'g o')
        plt.draw()

def slider_phase_shift(complex_data,period,symbol_rate):
    
    index = Find_Sampling_indexes(0,period,symbol_rate)
    ax.plot(np.real(complex_data[index]),np.imag(complex_data[index]), 'g o')
    plt.xlim(-1,1)
    plt.xlim(-1,1)
    
    plt.subplots_adjust(bottom=0.25, left =0.25)
    ax_Slider = plt.axes([0.25, 0.1, 0.65, 0.03])
    sliders = Slider(ax_Slider, ' Phase', -2, 2,0)

    sliders.on_changed(update(complex_data,period,symbol_rate,sliders.val))
    show()
    return

it is then imported into my main file and called as such.

#main.py
esc.slider_phase_shift(OOK_Complex,t1,93696)

I have been able to find a way to fix my issue. I need to return my sliders to my main program and then use the on_change function to call the update functions that are also in my external function. I also had to make use of global variables to make the information from my initial function available to the update function.

def Update_Shifting(val):
    ax1.clear()
    frequency = freq.val
    phase_shift = phase.val
    comp = Frequency_Shift(comp_data,frequency,t_a)
    p = Phase_Shift(comp, phase_shift)
    ax1.plot(np.real(p), np.imag(p), ' o')
    draw()
    return

def Slider_Shifting(complex_data, t, freq_low_lim:int,freq_high_lim:int,phase_low_lim:int,phase_high_lim:int,Modulation_type:str):
    global comp_data, freq, phase, t_a,ax1
    t_a = t
    comp_data = complex_data
    fig, ax1 = plt.subplots()
    plt.subplots_adjust(bottom=0.35)
    plt.plot(np.real(complex_data), np.imag(complex_data), ' o')
    plt.xlim(-1,1)
    plt.ylim(-1,1)
    plt.xlabel('Real (I)')
    plt.ylabel('Imaginary (Q)')
    plt.title(f'{Modulation_type} Frequncy and phase shifting')

    axfreq = plt.axes([0.25, 0.15, 0.65, 0.03])
    axphase = plt.axes([0.25, 0.1, 0.65, 0.03])

    freq = Slider(axfreq, 'Frequency Shift', freq_low_lim, freq_high_lim, 0)
    phase = Slider(axphase, 'Phase Shift', phase_low_lim, phase_high_lim, (phase_low_lim +phase_high_lim)/2)

    return freq,phase

Then when I call the function I do the following:

fig, ax = esc.Slider_Shifting(OOK_Complex, tOOK,-50,50,-3,-2,'OOK')

fig.on_changed(esc.Update_Shifting)
ax.on_changed(esc.Update_Shifting)
plt.show()

This allows me to do what I wanted.