Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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46 lines
1.4 KiB
46 lines
1.4 KiB
import sys
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import re
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from numpy.testing import jiffies, memusage
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def cmdline():
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m = re.compile(r'\A\d+\Z')
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args = []
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repeat = 1
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for a in sys.argv[1:]:
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if m.match(a):
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repeat = eval(a)
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else:
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args.append(a)
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f2py_opts = ' '.join(args)
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return repeat, f2py_opts
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def run(runtest, test_functions, repeat=1):
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l = [(t, repr(t.__doc__.split('\n')[1].strip())) for t in test_functions]
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start_memusage = memusage()
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diff_memusage = None
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start_jiffies = jiffies()
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i = 0
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while i < repeat:
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i += 1
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for t, fname in l:
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runtest(t)
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if start_memusage is None:
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continue
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if diff_memusage is None:
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diff_memusage = memusage() - start_memusage
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else:
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diff_memusage2 = memusage() - start_memusage
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if diff_memusage2 != diff_memusage:
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print('memory usage change at step %i:' % i,
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diff_memusage2 - diff_memusage,
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fname)
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diff_memusage = diff_memusage2
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current_memusage = memusage()
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print('run', repeat * len(test_functions), 'tests',
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'in %.2f seconds' % ((jiffies() - start_jiffies) / 100.0))
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if start_memusage:
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print('initial virtual memory size:', start_memusage, 'bytes')
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print('current virtual memory size:', current_memusage, 'bytes')
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