Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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438 lines
15 KiB
438 lines
15 KiB
4 years ago
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import timeit
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from functools import reduce
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import numpy as np
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from numpy import float_
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import numpy.core.fromnumeric as fromnumeric
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from numpy.testing import build_err_msg
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# Fixme: this does not look right.
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np.seterr(all='ignore')
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pi = np.pi
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class ModuleTester:
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def __init__(self, module):
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self.module = module
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self.allequal = module.allequal
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self.arange = module.arange
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self.array = module.array
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self.concatenate = module.concatenate
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self.count = module.count
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self.equal = module.equal
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self.filled = module.filled
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self.getmask = module.getmask
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self.getmaskarray = module.getmaskarray
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self.id = id
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self.inner = module.inner
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self.make_mask = module.make_mask
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self.masked = module.masked
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self.masked_array = module.masked_array
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self.masked_values = module.masked_values
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self.mask_or = module.mask_or
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self.nomask = module.nomask
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self.ones = module.ones
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self.outer = module.outer
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self.repeat = module.repeat
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self.resize = module.resize
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self.sort = module.sort
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self.take = module.take
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self.transpose = module.transpose
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self.zeros = module.zeros
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self.MaskType = module.MaskType
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try:
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self.umath = module.umath
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except AttributeError:
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self.umath = module.core.umath
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self.testnames = []
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def assert_array_compare(self, comparison, x, y, err_msg='', header='',
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fill_value=True):
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"""
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Assert that a comparison of two masked arrays is satisfied elementwise.
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"""
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xf = self.filled(x)
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yf = self.filled(y)
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m = self.mask_or(self.getmask(x), self.getmask(y))
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x = self.filled(self.masked_array(xf, mask=m), fill_value)
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y = self.filled(self.masked_array(yf, mask=m), fill_value)
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if (x.dtype.char != "O"):
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x = x.astype(float_)
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if isinstance(x, np.ndarray) and x.size > 1:
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x[np.isnan(x)] = 0
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elif np.isnan(x):
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x = 0
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if (y.dtype.char != "O"):
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y = y.astype(float_)
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if isinstance(y, np.ndarray) and y.size > 1:
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y[np.isnan(y)] = 0
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elif np.isnan(y):
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y = 0
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try:
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cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
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if not cond:
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msg = build_err_msg([x, y],
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err_msg
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+ '\n(shapes %s, %s mismatch)' % (x.shape,
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y.shape),
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header=header,
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names=('x', 'y'))
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assert cond, msg
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val = comparison(x, y)
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if m is not self.nomask and fill_value:
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val = self.masked_array(val, mask=m)
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if isinstance(val, bool):
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cond = val
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reduced = [0]
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else:
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reduced = val.ravel()
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cond = reduced.all()
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reduced = reduced.tolist()
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if not cond:
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match = 100-100.0*reduced.count(1)/len(reduced)
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msg = build_err_msg([x, y],
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err_msg
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+ '\n(mismatch %s%%)' % (match,),
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header=header,
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names=('x', 'y'))
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assert cond, msg
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except ValueError:
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msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
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raise ValueError(msg)
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def assert_array_equal(self, x, y, err_msg=''):
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"""
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Checks the elementwise equality of two masked arrays.
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"""
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self.assert_array_compare(self.equal, x, y, err_msg=err_msg,
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header='Arrays are not equal')
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def test_0(self):
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"""
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Tests creation
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"""
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x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
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m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
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xm = self.masked_array(x, mask=m)
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xm[0]
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def test_1(self):
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"""
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Tests creation
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"""
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x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
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y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
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m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
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m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
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xm = self.masked_array(x, mask=m1)
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ym = self.masked_array(y, mask=m2)
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xf = np.where(m1, 1.e+20, x)
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xm.set_fill_value(1.e+20)
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assert((xm-ym).filled(0).any())
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s = x.shape
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assert(xm.size == reduce(lambda x, y:x*y, s))
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assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1))
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for s in [(4, 3), (6, 2)]:
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x.shape = s
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y.shape = s
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xm.shape = s
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ym.shape = s
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xf.shape = s
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assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1))
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def test_2(self):
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"""
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Tests conversions and indexing.
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"""
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x1 = np.array([1, 2, 4, 3])
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x2 = self.array(x1, mask=[1, 0, 0, 0])
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x3 = self.array(x1, mask=[0, 1, 0, 1])
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x4 = self.array(x1)
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# test conversion to strings, no errors
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str(x2)
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repr(x2)
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# tests of indexing
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assert type(x2[1]) is type(x1[1])
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assert x1[1] == x2[1]
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x1[2] = 9
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x2[2] = 9
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self.assert_array_equal(x1, x2)
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x1[1:3] = 99
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x2[1:3] = 99
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x2[1] = self.masked
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x2[1:3] = self.masked
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x2[:] = x1
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x2[1] = self.masked
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x3[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0])
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x4[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0])
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x1 = np.arange(5)*1.0
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x2 = self.masked_values(x1, 3.0)
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x1 = self.array([1, 'hello', 2, 3], object)
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x2 = np.array([1, 'hello', 2, 3], object)
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# check that no error occurs.
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x1[1]
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x2[1]
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assert x1[1:1].shape == (0,)
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# Tests copy-size
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n = [0, 0, 1, 0, 0]
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m = self.make_mask(n)
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m2 = self.make_mask(m)
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assert(m is m2)
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m3 = self.make_mask(m, copy=1)
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assert(m is not m3)
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def test_3(self):
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"""
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Tests resize/repeat
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"""
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x4 = self.arange(4)
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x4[2] = self.masked
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y4 = self.resize(x4, (8,))
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assert self.allequal(self.concatenate([x4, x4]), y4)
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assert self.allequal(self.getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0])
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y5 = self.repeat(x4, (2, 2, 2, 2), axis=0)
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self.assert_array_equal(y5, [0, 0, 1, 1, 2, 2, 3, 3])
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y6 = self.repeat(x4, 2, axis=0)
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assert self.allequal(y5, y6)
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y7 = x4.repeat((2, 2, 2, 2), axis=0)
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assert self.allequal(y5, y7)
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y8 = x4.repeat(2, 0)
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assert self.allequal(y5, y8)
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def test_4(self):
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"""
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Test of take, transpose, inner, outer products.
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"""
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x = self.arange(24)
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y = np.arange(24)
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x[5:6] = self.masked
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x = x.reshape(2, 3, 4)
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y = y.reshape(2, 3, 4)
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assert self.allequal(np.transpose(y, (2, 0, 1)), self.transpose(x, (2, 0, 1)))
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assert self.allequal(np.take(y, (2, 0, 1), 1), self.take(x, (2, 0, 1), 1))
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assert self.allequal(np.inner(self.filled(x, 0), self.filled(y, 0)),
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self.inner(x, y))
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assert self.allequal(np.outer(self.filled(x, 0), self.filled(y, 0)),
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self.outer(x, y))
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y = self.array(['abc', 1, 'def', 2, 3], object)
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y[2] = self.masked
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t = self.take(y, [0, 3, 4])
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assert t[0] == 'abc'
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assert t[1] == 2
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assert t[2] == 3
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def test_5(self):
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"""
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Tests inplace w/ scalar
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"""
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x = self.arange(10)
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y = self.arange(10)
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xm = self.arange(10)
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xm[2] = self.masked
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x += 1
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assert self.allequal(x, y+1)
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xm += 1
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assert self.allequal(xm, y+1)
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x = self.arange(10)
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xm = self.arange(10)
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xm[2] = self.masked
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x -= 1
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assert self.allequal(x, y-1)
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xm -= 1
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assert self.allequal(xm, y-1)
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x = self.arange(10)*1.0
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xm = self.arange(10)*1.0
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xm[2] = self.masked
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x *= 2.0
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assert self.allequal(x, y*2)
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xm *= 2.0
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assert self.allequal(xm, y*2)
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x = self.arange(10)*2
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xm = self.arange(10)*2
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xm[2] = self.masked
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x /= 2
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assert self.allequal(x, y)
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xm /= 2
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assert self.allequal(xm, y)
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x = self.arange(10)*1.0
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xm = self.arange(10)*1.0
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xm[2] = self.masked
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x /= 2.0
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assert self.allequal(x, y/2.0)
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xm /= self.arange(10)
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self.assert_array_equal(xm, self.ones((10,)))
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x = self.arange(10).astype(float_)
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xm = self.arange(10)
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xm[2] = self.masked
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x += 1.
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assert self.allequal(x, y + 1.)
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def test_6(self):
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"""
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Tests inplace w/ array
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"""
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x = self.arange(10, dtype=float_)
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y = self.arange(10)
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xm = self.arange(10, dtype=float_)
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xm[2] = self.masked
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m = xm.mask
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a = self.arange(10, dtype=float_)
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a[-1] = self.masked
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x += a
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xm += a
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assert self.allequal(x, y+a)
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assert self.allequal(xm, y+a)
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assert self.allequal(xm.mask, self.mask_or(m, a.mask))
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x = self.arange(10, dtype=float_)
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xm = self.arange(10, dtype=float_)
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xm[2] = self.masked
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m = xm.mask
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a = self.arange(10, dtype=float_)
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a[-1] = self.masked
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x -= a
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xm -= a
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assert self.allequal(x, y-a)
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assert self.allequal(xm, y-a)
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assert self.allequal(xm.mask, self.mask_or(m, a.mask))
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x = self.arange(10, dtype=float_)
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xm = self.arange(10, dtype=float_)
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xm[2] = self.masked
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m = xm.mask
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a = self.arange(10, dtype=float_)
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a[-1] = self.masked
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x *= a
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xm *= a
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assert self.allequal(x, y*a)
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assert self.allequal(xm, y*a)
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assert self.allequal(xm.mask, self.mask_or(m, a.mask))
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x = self.arange(10, dtype=float_)
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xm = self.arange(10, dtype=float_)
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xm[2] = self.masked
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m = xm.mask
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a = self.arange(10, dtype=float_)
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a[-1] = self.masked
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x /= a
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xm /= a
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def test_7(self):
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"Tests ufunc"
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d = (self.array([1.0, 0, -1, pi/2]*2, mask=[0, 1]+[0]*6),
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self.array([1.0, 0, -1, pi/2]*2, mask=[1, 0]+[0]*6),)
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for f in ['sqrt', 'log', 'log10', 'exp', 'conjugate',
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# 'sin', 'cos', 'tan',
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# 'arcsin', 'arccos', 'arctan',
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# 'sinh', 'cosh', 'tanh',
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# 'arcsinh',
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||
|
|
# 'arccosh',
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||
|
|
# 'arctanh',
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||
|
|
# 'absolute', 'fabs', 'negative',
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||
|
|
# # 'nonzero', 'around',
|
||
|
|
# 'floor', 'ceil',
|
||
|
|
# # 'sometrue', 'alltrue',
|
||
|
|
# 'logical_not',
|
||
|
|
# 'add', 'subtract', 'multiply',
|
||
|
|
# 'divide', 'true_divide', 'floor_divide',
|
||
|
|
# 'remainder', 'fmod', 'hypot', 'arctan2',
|
||
|
|
# 'equal', 'not_equal', 'less_equal', 'greater_equal',
|
||
|
|
# 'less', 'greater',
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||
|
|
# 'logical_and', 'logical_or', 'logical_xor',
|
||
|
|
]:
|
||
|
|
try:
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||
|
|
uf = getattr(self.umath, f)
|
||
|
|
except AttributeError:
|
||
|
|
uf = getattr(fromnumeric, f)
|
||
|
|
mf = getattr(self.module, f)
|
||
|
|
args = d[:uf.nin]
|
||
|
|
ur = uf(*args)
|
||
|
|
mr = mf(*args)
|
||
|
|
self.assert_array_equal(ur.filled(0), mr.filled(0), f)
|
||
|
|
self.assert_array_equal(ur._mask, mr._mask)
|
||
|
|
|
||
|
|
def test_99(self):
|
||
|
|
# test average
|
||
|
|
ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
|
||
|
|
self.assert_array_equal(2.0, self.average(ott, axis=0))
|
||
|
|
self.assert_array_equal(2.0, self.average(ott, weights=[1., 1., 2., 1.]))
|
||
|
|
result, wts = self.average(ott, weights=[1., 1., 2., 1.], returned=1)
|
||
|
|
self.assert_array_equal(2.0, result)
|
||
|
|
assert(wts == 4.0)
|
||
|
|
ott[:] = self.masked
|
||
|
|
assert(self.average(ott, axis=0) is self.masked)
|
||
|
|
ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
|
||
|
|
ott = ott.reshape(2, 2)
|
||
|
|
ott[:, 1] = self.masked
|
||
|
|
self.assert_array_equal(self.average(ott, axis=0), [2.0, 0.0])
|
||
|
|
assert(self.average(ott, axis=1)[0] is self.masked)
|
||
|
|
self.assert_array_equal([2., 0.], self.average(ott, axis=0))
|
||
|
|
result, wts = self.average(ott, axis=0, returned=1)
|
||
|
|
self.assert_array_equal(wts, [1., 0.])
|
||
|
|
w1 = [0, 1, 1, 1, 1, 0]
|
||
|
|
w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
|
||
|
|
x = self.arange(6)
|
||
|
|
self.assert_array_equal(self.average(x, axis=0), 2.5)
|
||
|
|
self.assert_array_equal(self.average(x, axis=0, weights=w1), 2.5)
|
||
|
|
y = self.array([self.arange(6), 2.0*self.arange(6)])
|
||
|
|
self.assert_array_equal(self.average(y, None), np.add.reduce(np.arange(6))*3./12.)
|
||
|
|
self.assert_array_equal(self.average(y, axis=0), np.arange(6) * 3./2.)
|
||
|
|
self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0])
|
||
|
|
self.assert_array_equal(self.average(y, None, weights=w2), 20./6.)
|
||
|
|
self.assert_array_equal(self.average(y, axis=0, weights=w2), [0., 1., 2., 3., 4., 10.])
|
||
|
|
self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0])
|
||
|
|
m1 = self.zeros(6)
|
||
|
|
m2 = [0, 0, 1, 1, 0, 0]
|
||
|
|
m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
|
||
|
|
m4 = self.ones(6)
|
||
|
|
m5 = [0, 1, 1, 1, 1, 1]
|
||
|
|
self.assert_array_equal(self.average(self.masked_array(x, m1), axis=0), 2.5)
|
||
|
|
self.assert_array_equal(self.average(self.masked_array(x, m2), axis=0), 2.5)
|
||
|
|
self.assert_array_equal(self.average(self.masked_array(x, m5), axis=0), 0.0)
|
||
|
|
self.assert_array_equal(self.count(self.average(self.masked_array(x, m4), axis=0)), 0)
|
||
|
|
z = self.masked_array(y, m3)
|
||
|
|
self.assert_array_equal(self.average(z, None), 20./6.)
|
||
|
|
self.assert_array_equal(self.average(z, axis=0), [0., 1., 99., 99., 4.0, 7.5])
|
||
|
|
self.assert_array_equal(self.average(z, axis=1), [2.5, 5.0])
|
||
|
|
self.assert_array_equal(self.average(z, axis=0, weights=w2), [0., 1., 99., 99., 4.0, 10.0])
|
||
|
|
|
||
|
|
def test_A(self):
|
||
|
|
x = self.arange(24)
|
||
|
|
x[5:6] = self.masked
|
||
|
|
x = x.reshape(2, 3, 4)
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
setup_base = ("from __main__ import ModuleTester \n"
|
||
|
|
"import numpy\n"
|
||
|
|
"tester = ModuleTester(module)\n")
|
||
|
|
setup_cur = "import numpy.ma.core as module\n" + setup_base
|
||
|
|
(nrepeat, nloop) = (10, 10)
|
||
|
|
|
||
|
|
for i in range(1, 8):
|
||
|
|
func = 'tester.test_%i()' % i
|
||
|
|
cur = timeit.Timer(func, setup_cur).repeat(nrepeat, nloop*10)
|
||
|
|
cur = np.sort(cur)
|
||
|
|
print("#%i" % i + 50*'.')
|
||
|
|
print(eval("ModuleTester.test_%i.__doc__" % i))
|
||
|
|
print("core_current : %.3f - %.3f" % (cur[0], cur[1]))
|