New Matplotlib using Image Element demo - shows a Spectrogram
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import PySimpleGUI as sg
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import numpy as np
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from matplotlib.backends.backend_tkagg import FigureCanvasAgg
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import matplotlib.pyplot as plt
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import io
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"""
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Demo_Matplotlib_Image_Elem Demo
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Demo to show
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* How to use an Image element to show a Matplotlib figure
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* How to draw a Spectrogram
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* Hide the Image when a figure isn't present (shrinks the window automatically)
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The example graph can be found in the matplotlib gallery:
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https://matplotlib.org/stable/gallery/images_contours_and_fields/specgram_demo.html
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Copyright 2021 PySimpleGUI
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"""
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# .d88888b dP dP
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# 88. "' 88 88
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# `Y88888b. d8888P .d8888b. 88d888b. d8888P
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# `8b 88 88' `88 88' `88 88
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# d8' .8P 88 88. .88 88 88
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# Y88888P dP `88888P8 dP dP
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# oooooooooooooooooooooooooooooooooooooooooo of your Matplotlib code
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def your_matplotlib_code():
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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dt = 0.0005
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t = np.arange(0.0, 20.0, dt)
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s1 = np.sin(2 * np.pi * 100 * t)
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s2 = 2 * np.sin(2 * np.pi * 400 * t)
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# create a transient "chirp"
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s2[t <= 10] = s2[12 <= t] = 0
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# add some noise into the mix
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nse = 0.01 * np.random.random(size=len(t))
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x = s1 + s2 + nse # the signal
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NFFT = 1024 # the length of the windowing segments
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Fs = int(1.0 / dt) # the sampling frequency
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fig, (ax1, ax2) = plt.subplots(nrows=2)
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ax1.plot(t, x)
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Pxx, freqs, bins, im = ax2.specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900)
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return fig
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# 88888888b dP
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# 88 88
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# 88aaaa 88d888b. .d888b88
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# 88 88' `88 88' `88
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# 88 88 88 88. .88
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# 88888888P dP dP `88888P8
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# ooooooooooooooooooooooooooooo of your Matplotlib code
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# dP dP dP
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# 88 88 88
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# 88aaaaa88a .d8888b. 88 88d888b. .d8888b. 88d888b.
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# 88 88 88ooood8 88 88' `88 88ooood8 88' `88
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# 88 88 88. ... 88 88. .88 88. ... 88
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# dP dP `88888P' dP 88Y888P' `88888P' dP
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# ooooooooooooooooooooooo~88~oooooooooooooooooooooooo function
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# dP
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def draw_figure(element, figure):
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"""
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Draws the previously created "figure" in the supplied Image Element
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:param element: an Image Element
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:param figure: a Matplotlib figure
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:return: The figure canvas
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"""
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plt.close('all') # erases previously drawn plots
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canv = FigureCanvasAgg(figure)
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buf = io.BytesIO()
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canv.print_figure(buf, format='png')
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if buf is None:
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return None
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buf.seek(0)
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element.update(data=buf.read(), visible=True)
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return canv
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# .88888. dP dP dP
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# d8' `88 88 88 88
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# 88 88 88 88
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# 88 YP88 88 88 88
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# Y8. .88 Y8. .8P 88
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# `88888' `Y88888P' dP
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# ooooooooooooooooooooooo
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def main():
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# define the window layout
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layout = [[sg.Text('Spectrogram test')],
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[sg.pin(sg.Image(key='-IMAGE-'))],
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[sg.Button('Ok'), sg.B('Clear')]]
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# create the form and show it without the plot
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window = sg.Window('Spectrogram', layout, element_justification='c', font='Helvetica 14')
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while True:
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# add the plot to the window
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event, values = window.read()
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if event == sg.WIN_CLOSED:
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break
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elif event == 'Ok':
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draw_figure(window['-IMAGE-'], your_matplotlib_code())
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elif event == 'Clear':
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plt.close('all') # close all plots
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window['-IMAGE-'].update() # clears the image
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window['-IMAGE-'].update(visible=False) # hides the blank image
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window.close()
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if __name__ == '__main__':
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main()
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