140 lines
4.8 KiB
Python
140 lines
4.8 KiB
Python
#!/usr/bin/env python3
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import sys
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import numpy as np
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import numpy.ma as ma
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from strf.rfio import Spectrogram
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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from matplotlib.backend_bases import MouseButton
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from matplotlib.widgets import RectangleSelector
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import matplotlib as mpl
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import imageio
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from skimage.morphology import binary_dilation, remove_small_objects
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from skimage.filters import gaussian
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from modest import imshow
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mpl.rcParams['keymap.save'].remove('s')
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mpl.rcParams['keymap.fullscreen'].remove('f')
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if __name__ == "__main__":
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# Settings
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path = "D:\\New folder\\2022-06-13T22%3A56%3A48+02%3A00_401000000"
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prefix = "2022-06-13T20%3A56%3A48"
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ifile = 0
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nsub = 3600*12
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# Read spectrogram
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s = Spectrogram(path, prefix, ifile, nsub, 4171)
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# Create plot
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vmin, vmax = np.percentile(s.z, (5, 99.95))
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# Time limits
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tmin, tmax = mdates.date2num(s.t[0]), mdates.date2num(s.t[-1])
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# Frequency limits
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fcen = np.mean(s.freq)
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fmin, fmax = (s.freq[0] - fcen) * 1e-6, (s.freq[-1] - fcen) * 1e-6
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fig, ax = plt.subplots(figsize=(10, 6))
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print("hey")
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mark = ax.scatter([], [],c="white",s=5)
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line_fitting = ax.scatter([], [], edgecolors="yellow",s=10, facecolors='none')
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# imshow(ax, s.z, vmin=vmin, vmax=vmax)
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imshow(ax, s.z, origin="lower", aspect="auto", interpolation="None",
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vmin=vmin, vmax=vmax,
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extent=[tmin, tmax, fmin, fmax])
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mode = {
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"current_mode" : None
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}
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def line_select_callback(eclick, erelease):
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x1, y1 = eclick.xdata, eclick.ydata
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x2, y2 = erelease.xdata, erelease.ydata
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if mode["current_mode"] =="fit":
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t1_ind = round(len(s.t) * (x1 - tmin) / (tmax - tmin))
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t2_ind = round(len(s.t) * (x2 - tmin) / (tmax - tmin))
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f1_ind = round(len(s.freq) * (y1 - fmin) / (fmax - fmin))
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f2_ind = round(len(s.freq) * (y2 - fmin) / (fmax - fmin))
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submat = gaussian(s.z[f1_ind:f2_ind,t1_ind:t2_ind])
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data = submat - np.mean(submat, axis=0)
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mask = data > 3 * np.std(data, axis=0)
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data1 = ma.array(submat, mask=mask)
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data1 -= ma.mean(data1)
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mask = data1 > 3 * ma.std(data1, axis=0)
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mask = binary_dilation(mask,np.ones((7,1)))
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mask = np.flipud(remove_small_objects(mask, 50))
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imageio.imwrite(f'test3.png', 255 * mask.astype(np.uint8))
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print(s.z[f1_ind:f2_ind,t1_ind:t2_ind].shape)
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elif mode["current_mode"] == "delete":
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array = mark.get_offsets()
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maskx = np.logical_and(array[:,0] >= min(x1,x2), array[:,0] <= max(x1,x2))
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masky = np.logical_and(array[:,1] >= min(y1,y2), array[:,1] <= max(y1,y2))
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mask = np.logical_and(maskx, masky)
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mark.set_offsets(array[np.logical_not(mask),:])
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fig.canvas.draw()
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print(f"select over {x1},{y1},{x2},{y2}")
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selector = RectangleSelector(ax, line_select_callback, useblit=True, button=[1], minspanx=5, minspany=5, spancoords='pixels',props={'edgecolor':'white', 'fill': False})
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selector.active = False
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ax.xaxis_date()
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date_format = mdates.DateFormatter("%F\n%H:%M:%S")
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ax.xaxis.set_major_formatter(date_format)
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fig.autofmt_xdate(rotation=0, ha="center")
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ax.set_xlabel("Time (UTC)")
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ax.set_ylabel(f"Frequency (MHz) - {fcen * 1e-6:g} MHz")
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def add_point(scatter, point):
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array = scatter.get_offsets()
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print(array)
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array = np.vstack([array, point])
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scatter.set_offsets(array)
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fig.canvas.draw()
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def handle(key, x, y):
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print(f"pressed {key} over x={x} y={y}")
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if key == "d":
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selector.active = True
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mode["current_mode"] = "delete"
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elif key == "s":
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point = (x, y)
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add_point(line_fitting, point)
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elif key == "f":
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print("performing fitting on")
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mode["current_mode"] = "fit"
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selector.active = True
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print(line_fitting.get_offsets())
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elif key == "r":
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print("performing reset")
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mode["current_mode"] = None
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selector.active = False
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mark.set_offsets(np.empty((0, 2), float))
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line_fitting.set_offsets(np.empty((0, 2), float))
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fig.canvas.draw()
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sys.stdout.flush()
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def on_press(event):
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handle(event.key, event.xdata, event.ydata)
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sys.stdout.flush()
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def on_click(event):
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if event.button is MouseButton.MIDDLE:
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point = (event.xdata, event.ydata)
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add_point(mark, point)
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print(f"{event.xdata} {fcen + event.ydata}")
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sys.stdout.flush()
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fig.canvas.mpl_connect('key_press_event', on_press)
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fig.canvas.mpl_connect('button_press_event', on_click)
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plt.show()
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