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Update rfplot.py

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Michał Drzał 2022-06-20 19:36:03 +02:00 committed by GitHub
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commit 4c15a40a5f
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1 changed files with 42 additions and 42 deletions
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rfplot.py
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@ -1,6 +1,7 @@
#!/usr/bin/env python3
import sys
import numpy as np
import numpy.ma as ma
from strf.rfio import Spectrogram
import matplotlib.pyplot as plt
@ -8,19 +9,20 @@ import matplotlib.dates as mdates
from matplotlib.backend_bases import MouseButton
from matplotlib.widgets import RectangleSelector
import matplotlib as mpl
from astropy.visualization import (ZScaleInterval, ImageNormalize,SqrtStretch)
import imageio
from skimage.morphology import binary_dilation, remove_small_objects
from skimage.filters import gaussian
from modest import imshow
mpl.rcParams['keymap.save'].remove('s')
mpl.rcParams['keymap.fullscreen'].remove('f')
if __name__ == "__main__":
# Settings
path = "data"
prefix = "2021-08-04T20_48_35"
ifile = 50
nsub = 1800
path = "D:\\New folder\\2022-06-13T22%3A56%3A48+02%3A00_401000000"
prefix = "2022-06-13T20%3A56%3A48"
ifile = 0
nsub = 3600*12
# Read spectrogram
s = Spectrogram(path, prefix, ifile, nsub, 4171)
@ -36,59 +38,52 @@ if __name__ == "__main__":
fmin, fmax = (s.freq[0] - fcen) * 1e-6, (s.freq[-1] - fcen) * 1e-6
fig, ax = plt.subplots(figsize=(10, 6))
print("hey")
mark = ax.scatter([], [],c="white",s=5)
line_fitting = ax.scatter([], [], edgecolors="yellow",s=10, facecolors='none')
ax.imshow(s.z, origin="lower", aspect="auto", interpolation="None",
# imshow(ax, s.z, vmin=vmin, vmax=vmax)
imshow(ax, s.z, origin="lower", aspect="auto", interpolation="None",
vmin=vmin, vmax=vmax,
extent=[tmin, tmax, fmin, fmax])
mode = {
"current_mode" : None
}
def line_select_callback(eclick, erelease):
x1, y1 = eclick.xdata, eclick.ydata
x2, y2 = erelease.xdata, erelease.ydata
if mode["current_mode"] =="fit":
t1_ind = round(len(s.t) * (x1 - tmin) / (tmax - tmin))
t2_ind = round(len(s.t) * (x2 - tmin) / (tmax - tmin))
f1_ind = round(len(s.freq) * (y1 - fmin) / (fmax - fmin))
f2_ind = round(len(s.freq) * (y2 - fmin) / (fmax - fmin))
submat = gaussian(s.z[f1_ind:f2_ind,t1_ind:t2_ind])
data = submat - np.mean(submat, axis=0)
mask = data > 3 * np.std(data, axis=0)
t1_ind = round(len(s.t) * (x1 - tmin) / (tmax - tmin))
t2_ind = round(len(s.t) * (x2 - tmin) / (tmax - tmin))
f1_ind = round(len(s.freq) * (y1 - fmin) / (fmax - fmin))
f2_ind = round(len(s.freq) * (y2 - fmin) / (fmax - fmin))
submat = s.z[f1_ind:f2_ind,t1_ind:t2_ind]
signal = submat - np.median(submat, axis=0)
background = np.copy(signal)
filter = np.ones(50)/50
for i in range(signal.shape[1]):
background[:,i] = np.convolve(signal[:,i], filter, mode="same")
data1 = ma.array(submat, mask=mask)
data1 -= ma.mean(data1)
mask = data1 > 3 * ma.std(data1, axis=0)
mask = binary_dilation(mask,np.ones((7,1)))
mask = np.flipud(remove_small_objects(mask, 50))
imageio.imwrite(f'test3.png', 255 * mask.astype(np.uint8))
sig_without_background = signal - background
mask = sig_without_background > 3 * np.std(sig_without_background, axis=0)
sig_without_background[mask] = background[mask]
sig_without_background[np.logical_not(mask)] = signal[np.logical_not(mask)]
print(s.z[f1_ind:f2_ind,t1_ind:t2_ind].shape)
elif mode["current_mode"] == "delete":
array = mark.get_offsets()
maskx = np.logical_and(array[:,0] >= min(x1,x2), array[:,0] <= max(x1,x2))
masky = np.logical_and(array[:,1] >= min(y1,y2), array[:,1] <= max(y1,y2))
mask = np.logical_and(maskx, masky)
mark.set_offsets(array[np.logical_not(mask),:])
for i in range(signal.shape[1]):
background[:,i] = np.convolve(sig_without_background[:,i], filter, mode="same")
sig_without_background = signal - background
mask = (sig_without_background > 3 * np.std(sig_without_background, axis=0)).astype(np.uint8)
mask = binary_dilation(mask)
remove_small_objects(mask, min_size=16, in_place=True)
mask = np.flipud(mask)
imageio.imwrite(f'test3.png', 255 * mask)
print(s.z[f1_ind:f2_ind,t1_ind:t2_ind].shape)
# array = mark.get_offsets()
# maskx = np.logical_and(array[:,0] >= min(x1,x2), array[:,0] <= max(x1,x2))
# masky = np.logical_and(array[:,1] >= min(y1,y2), array[:,1] <= max(y1,y2))
# mask = np.logical_and(maskx, masky)
# mark.set_offsets(array[np.logical_not(mask),:])
fig.canvas.draw()
print(f"select over {x1},{y1},{x2},{y2}")
selector = RectangleSelector(ax, line_select_callback, useblit=True, button=[1], minspanx=5, minspany=5, spancoords='pixels',props={'edgecolor':'white', 'fill': False})
selector.active = False
ax.xaxis_date()
date_format = mdates.DateFormatter("%F\n%H:%M:%S")
ax.xaxis.set_major_formatter(date_format)
@ -108,14 +103,19 @@ if __name__ == "__main__":
print(f"pressed {key} over x={x} y={y}")
if key == "d":
selector.active = True
mode["current_mode"] = "delete"
elif key == "s":
point = (x, y)
add_point(line_fitting, point)
elif key == "f":
print("performing fitting on")
mode["current_mode"] = "fit"
selector.active = True
print(line_fitting.get_offsets())
elif key == "r":
print("performing reset")
mode["current_mode"] = None
selector.active = False
mark.set_offsets(np.empty((0, 2), float))
line_fitting.set_offsets(np.empty((0, 2), float))
fig.canvas.draw()