Exemplo n.º 1
0
    def test_linear(self):
        N = 3000.
        x = arange(N)
        y = arange(N)
        new_x = arange(N)+0.5
        new_y = linear(x, y, new_x)

        self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
Exemplo n.º 2
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    def test_linear(self):
        N = 3000.
        x = arange(N)
        y = arange(N)
        new_x = arange(N)+0.5
        with suppress_warnings() as sup:
            sup.filter(DeprecationWarning, "`linear` is deprecated")
            new_y = linear(x, y, new_x)

        assert_allclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
Exemplo n.º 3
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def test_linear_interp():
    n = 10
    x = np.arange(n, dtype=np.float)
    y = np.arange(n, dtype=np.float)
    new_x = np.arange(n, dtype=np.float) + 0.5
    scipy_new_y = linear(x, y, new_x)
    np.testing.assert_almost_equal(scipy_new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
    for i in range(n - 1):
        assert vic_lib.linear_interp(new_x[i], x[i], x[i + 1],
                                     y[i], y[i + 1]) == scipy_new_y[i]
Exemplo n.º 4
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    def test_linear(self):
        N = 3000.
        x = arange(N)
        y = arange(N)
        new_x = arange(N)+0.5
        with warnings.catch_warnings():
            warnings.simplefilter("ignore", DeprecationWarning)
            new_y = linear(x, y, new_x)

        self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
 def test_linear(self):
     N = 3000.
     x = arange(N)
     y = arange(N)
     new_x = arange(N)+0.5
     t1 = time.clock()
     new_y = linear(x, y, new_x)
     t2 = time.clock()
     #print "time for linear interpolation with N = %i:" % N, t2 - t1
     
     self.assertAllclose(new_y[:5], [0.5, 1.5, 2.5, 3.5, 4.5])
Exemplo n.º 6
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 def test_linear2(self):
     N = 3000
     x = arange(N, dtype=np.float)
     y = ones((100,N)) * arange(N)
     new_x = arange(N) + 0.5
     new_y = linear(x, y, new_x)
     self.assertAllclose(new_y[:5,:5],
                         [[0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5]])
Exemplo n.º 7
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 def test_linear2(self):
     N = 3000
     x = arange(N, dtype=float)
     y = ones((100,N)) * arange(N)
     new_x = arange(N) + 0.5
     with suppress_warnings() as sup:
         sup.filter(DeprecationWarning, "`linear` is deprecated")
         new_y = linear(x, y, new_x)
     assert_allclose(new_y[:5,:5],
                         [[0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5]])
Exemplo n.º 8
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 def test_linear2(self):
     N = 3000
     x = arange(N, dtype=float)
     y = ones((100,N)) * arange(N)
     new_x = arange(N) + 0.5
     with suppress_warnings() as sup:
         sup.filter(DeprecationWarning, "`linear` is deprecated")
         new_y = linear(x, y, new_x)
     assert_allclose(new_y[:5,:5],
                         [[0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5]])
Exemplo n.º 9
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 def test_linear2(self):
     N = 3000
     x = arange(N, dtype=float)
     y = ones((100,N)) * arange(N)
     new_x = arange(N) + 0.5
     with warnings.catch_warnings():
         warnings.simplefilter("ignore", DeprecationWarning)
         new_y = linear(x, y, new_x)
     self.assertAllclose(new_y[:5,:5],
                         [[0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5],
                          [0.5, 1.5, 2.5, 3.5, 4.5]])
Exemplo n.º 10
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 def test_linear2(self):
     N = 3000.
     x = arange(N)
     y = ones((100, N)) * arange(N)
     new_x = arange(N) + 0.5
     t1 = time.clock()
     new_y = linear(x, y, new_x)
     t2 = time.clock()
     #print "time for 2D linear interpolation with N = %i:" % N, t2 - t1
     self.assertAllclose(
         new_y[:5, :5],
         [[0.5, 1.5, 2.5, 3.5, 4.5], [0.5, 1.5, 2.5, 3.5, 4.5],
          [0.5, 1.5, 2.5, 3.5, 4.5], [0.5, 1.5, 2.5, 3.5, 4.5],
          [0.5, 1.5, 2.5, 3.5, 4.5]])