2019-10-24 21:22:25 +05:00
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import json
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import sys
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import subprocess
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import statistics
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def readData(a, files):
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amin=[]
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amax=[]
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amin1=[]
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amax1=[]
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bad=[]
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ne1d=[]
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ne2d=[]
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ne3d=[]
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2021-06-10 13:55:28 +05:00
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file=[]
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2019-10-24 21:22:25 +05:00
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for f in files:
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2024-03-12 01:10:56 +05:00
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if f == 'cylinder.geo':
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continue
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2019-10-24 21:22:25 +05:00
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for t in a[f]:
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if t['ne1d']>0:
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ne1d.append(t['ne1d'])
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if t['ne2d']>0:
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ne2d.append(t['ne2d'])
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if t['ne3d']>0:
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ne3d.append(t['ne3d'])
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if t['total_badness']>0.0:
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bad.append(t['total_badness'])
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2021-07-19 17:59:12 +05:00
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file.append(f)
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2019-10-24 21:22:25 +05:00
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if 'angles_tet' in t:
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amin.append(t['angles_tet'][0])
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amax.append(t['angles_tet'][1])
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if 'angles_trig' in t:
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amin1.append(t['angles_trig'][0])
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amax1.append(t['angles_trig'][1])
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return {
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"min tet angle":amin,
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"max tet angle" : amax,
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"min trig angle":amin1,
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"max trig angle" : amax1,
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"badness" : bad,
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"#edges" : ne1d,
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"#trigs" : ne2d,
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"#tets" : ne3d,
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2021-06-10 13:55:28 +05:00
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"file" : file,
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2019-10-24 21:22:25 +05:00
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}
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import matplotlib.pyplot as plt
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ref = 'master'
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if len(sys.argv)>1:
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ref = sys.argv[1]
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res = subprocess.run(['git','show','{}:./results.json'.format(ref)], capture_output=True)
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s = json.loads(res.stdout.decode())
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if len(sys.argv) > 2:
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ref2 = sys.argv[2]
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res = subprocess.run(['git','show','{}:./results.json'.format(ref2)], capture_output=True)
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s2 = res.stdout.decode()
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else:
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ref2 = 'current'
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s2 = open('results.json','r').read()
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s2 = json.loads(s2)
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filenames = [f for f in s if f in s2]
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data = readData(s, filenames)
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data2 = readData(s2, filenames)
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2021-06-10 13:55:28 +05:00
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assert(len(data) == len(data2))
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2022-04-13 15:44:45 +05:00
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w = 90
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GREEN = '\033[92m'
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RED = '\033[91m'
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RESET = '\033[0m'
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2021-06-10 13:55:28 +05:00
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for bad1,bad2, f1, f2 in zip(data['badness'], data2['badness'], data['file'], data2['file']):
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assert f1==f2
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2022-04-13 15:44:45 +05:00
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diff = f"{100*(bad2-bad1)/bad1:+.2f}%"
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if bad2>0 and bad2>1.2*bad1:
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print(f"{RED}badness {f1} got worse: {bad1} -> {bad2}".ljust(w) + diff + RESET)
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if bad2>0 and bad2<0.8*bad1:
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print(f"{GREEN}badness {f1} got better: {bad1} -> {bad2}".ljust(w) + diff + RESET)
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2021-11-30 23:43:32 +05:00
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for bad1,bad2, f1, f2 in zip(data['#trigs'], data2['#trigs'], data['file'], data2['file']):
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assert f1==f2
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2022-04-13 15:44:45 +05:00
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diff = f"{100*(bad2-bad1)/bad1:+.2f}%"
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if bad2>0 and bad2>1.2*bad1:
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print(f"{RED}ntrigs {f1} got worse: {bad1} -> {bad2}".ljust(w) + diff + RESET)
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if bad2>0 and bad2<0.8*bad1:
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print(f"{GREEN}ntrigs {f1} got better: {bad1} -> {bad2}".ljust(w) + diff + RESET)
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2021-06-10 13:55:28 +05:00
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2024-02-24 00:32:39 +05:00
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n = len(data) + 1
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fig, ax = plt.subplots(figsize=(15, 7)) # Adjust figsize as needed
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plt.xticks([])
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plt.yticks([])
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ax.yaxis.grid(False)
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ax.xaxis.grid(False)
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for i, d in enumerate(['min trig angle', 'min tet angle', 'max trig angle', 'max tet angle']):
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plt.subplot(2, 4, i + 1) # Remove ax =
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2019-10-24 21:22:25 +05:00
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plt.title(d)
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2024-02-24 00:32:39 +05:00
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# plt.xticks([1, 2])
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if len(data[d]) == 0 or len(data2[d]) == 0:
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2019-10-24 21:22:25 +05:00
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continue
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2024-02-24 00:32:39 +05:00
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plt.violinplot([data[d], data2[d]], showmedians=True)
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2019-10-24 21:22:25 +05:00
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med = statistics.median(data[d])
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2024-02-24 00:32:39 +05:00
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plt.hlines(med, 1, 2, linestyle='dotted')
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if d == 'badness':
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plt.yscale('log')
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plt.xticks([1, 2], [ref, ref2])
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for i, d in enumerate(['badness', '#edges', '#trigs', '#tets']):
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plt.xticks([])
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plt.subplot(2, 4, 5 + i)
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plt.title('difference ' + d + ' (in %)')
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plt.boxplot([100.0 * (y - x) / x for x, y in zip(data[d], data2[d])])
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plt.hlines(0.0, 0.5, 1.5, linestyle='dotted')
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plt.tight_layout() # Adjust layout
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2019-10-24 21:22:25 +05:00
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# plt.savefig('comparison.png', dpi=100)
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plt.show()
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