Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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56 lines
1.6 KiB
56 lines
1.6 KiB
import numpy as np
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class _MockFunction:
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def __init__(self, return_value = None):
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self.number_calls = 0
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self.return_value = return_value
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self.last_args = ([], {})
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def __call__(self, *args, **kwargs):
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self.number_calls += 1
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self.last_args = (args, kwargs)
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return self.return_value
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fft = _MockFunction(np.random.random(10))
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fft2 = _MockFunction(np.random.random(10))
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fftn = _MockFunction(np.random.random(10))
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ifft = _MockFunction(np.random.random(10))
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ifft2 = _MockFunction(np.random.random(10))
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ifftn = _MockFunction(np.random.random(10))
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rfft = _MockFunction(np.random.random(10))
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rfft2 = _MockFunction(np.random.random(10))
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rfftn = _MockFunction(np.random.random(10))
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irfft = _MockFunction(np.random.random(10))
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irfft2 = _MockFunction(np.random.random(10))
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irfftn = _MockFunction(np.random.random(10))
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hfft = _MockFunction(np.random.random(10))
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hfft2 = _MockFunction(np.random.random(10))
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hfftn = _MockFunction(np.random.random(10))
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ihfft = _MockFunction(np.random.random(10))
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ihfft2 = _MockFunction(np.random.random(10))
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ihfftn = _MockFunction(np.random.random(10))
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dct = _MockFunction(np.random.random(10))
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idct = _MockFunction(np.random.random(10))
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dctn = _MockFunction(np.random.random(10))
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idctn = _MockFunction(np.random.random(10))
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dst = _MockFunction(np.random.random(10))
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idst = _MockFunction(np.random.random(10))
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dstn = _MockFunction(np.random.random(10))
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idstn = _MockFunction(np.random.random(10))
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__ua_domain__ = "numpy.scipy.fft"
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def __ua_function__(method, args, kwargs):
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fn = globals().get(method.__name__)
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return (fn(*args, **kwargs) if fn is not None
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else NotImplemented)
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