80 lines
2.0 KiB
Python
80 lines
2.0 KiB
Python
import os
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import re
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from qdx import Bind
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from qdx.utils import get_hist, file_filter
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from tqdm import tqdm
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from matplotlib import pyplot as plt
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path = 'result/bind'
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file_list = os.listdir(path)
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reg = re.compile(r'(([0-9]{4})-([0-9])-([0-9])).txt')
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n, m = 5, 8
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binds = [[j for j in range(m)] for i in range(n)]
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for i in range(n):
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for j in range(m):
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binds[i][j] = Bind(i, j)
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pbar = tqdm(desc="Gaussian Mixture Filter", total=len(file_list))
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for file in file_list:
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bind = binds[int(i)][int(j)]
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name, E, i, j = reg.match(file).groups()
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file = os.path.join(path, file)
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_, data = file_filter(file)
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# bind.draw_filter('result/GMM/' + name + '.png')
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# np.savetxt('result/bind-GMM/' + name + '.txt', data, fmt='%d')
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bind.add_data(int(E) / 100, data)
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pbar.update(1)
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pbar.close()
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split_n = [8, 7, 7, 8, 8]
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pbar = tqdm(desc="Bind Process", total=n * m)
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for i in range(n):
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for j in range(m):
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bind: Bind = binds[i][j]
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bind.filter()
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bind.fit1()
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bind.solve()
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bind.split(n=split_n[i])
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bind.fit2()
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bind.draw_fit1('result/FIT1/' + bind.name + '.png')
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bind.draw_fit2('result/FIT2/' + bind.name + '.png')
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pbar.update(1)
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pbar.close()
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y = [
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[620, 610, 600, 590, 580, 570, 560, 550],
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[485, 475, 465, 455, 445, 435, 425],
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[360, 350, 340, 330, 320, 310, 300],
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[235, 225, 215, 205, 195, 185, 175, 165],
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[100, 90, 80, 70, 60, 50, 40, 30]
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]
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for i in range(n):
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k = 1
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fig = plt.figure(figsize=(14, 6))
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for j in range(m):
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ax = fig.add_subplot(int(m / 2), 2, k)
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bind = binds[i][j]
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bind.fit3(y[i])
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ny = bind.reg3.predict(bind.x1)
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c, e = get_hist(ny, delta=0.5)
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ax.scatter(e, c, s=0.5)
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k += 1
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fig.savefig('./Figure-' + str(i) + '.png', facecolor='w', transparent=False)
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plt.tight_layout()
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plt.close()
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f = open('cal.txt', 'w')
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for i in range(n):
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for j in range(m):
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bind = binds[i][j]
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f.writelines('{:d} {:d} {:.5f} {:.5f} {:.5f}\n'.format(i, j, bind.k1, bind.k2, bind.b))
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