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debugging_mod contains the various functions used to interface with the debugging data, while vid_read has examples of how to use them. I'm still in the process of trying to fix the g2 correlation function.
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
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import numpy as np
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from matplotlib import pyplot as plt
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import imageio
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from PIL import Image, ImageSequence
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from debugging_mod import ImageSeries
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vid = Image.open('data_10_4/kiara_20fps_redlaser_vid.tif')
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vidarray = []
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for i, page in enumerate(ImageSequence.Iterator(vid)):
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pg = np.array(page)
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vidarray.append(pg)
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vidarray = np.array(vidarray)
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RedLaserExp = ImageSeries(vidarray, (430,606,590,766),fps=20) #cropping x1:x2, y1:y2
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#with np.load('data_9_28/kiara_data_300sec_green') as data:
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# GreenLaserExp = ImageSeries(data['arr_0'], (500,676,580,756), fps=5)
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#crop to: x1=500, x2=676, y1=580, y2=756
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#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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#Note: human eye can see at c. 150 fps
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#inner top right corner of disk (120,70)
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#inner top left corner of disk (66,63)
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#inner bottom left corner of disk (66,107)
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#inner bottom (87,118)
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#inner right (125, 86)
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#pixel intensity plot: ---------------------------------------
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#RedLaserExp.plot_Ipixel((125,86),description="inner right")
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#RedLaserExp.plot_Ipixel((87,118),description="inner bottom")
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#RedLaserExp.plot_Ipixel((66,63),description="inner top left")
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#pixel fft plot: --------------------------------------------
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#RedLaserExp.plot_fftIpixel((125,86))
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#RedLaserExp.plot_fftIpixel((87,118))
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#RedLaserExp.plot_fftIpixel((66,63))
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#waterfall plot for row: -------------------------------------
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#RedLaserExp.plot_waterfall(None,118,tint=1)
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#waterfall plot for col: -------------------------------------
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#RedLaserExp.plot_waterfall(66,None,tint=1)
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#save a video: -----------------------------------------------
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#RedLaserExp.save_vid("redlaser_10-4_20fps_1x.mp4",1)
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