Python core.arange方法代碼示例

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def _assert_valid_refcount(op):
    """
    Check that ufuncs don't mishandle refcount of object `1`.
    Used in a few regression tests.
    """
    import numpy as np

    b = np.arange(100*100).reshape(100, 100)
    c = b
    i = 1

    rc = sys.getrefcount(i)
    for j in range(15):
        d = op(b, c)
    assert_(sys.getrefcount(i) >= rc)
    del d  # for pyflakes 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def _assert_valid_refcount(op):
    """
    Check that ufuncs don't mishandle refcount of object `1`.
    Used in a few regression tests.
    """
    import numpy as np
    a = np.arange(100 * 100)
    b = np.arange(100*100).reshape(100, 100)
    c = b

    i = 1

    rc = sys.getrefcount(i)
    for j in range(15):
        d = op(b, c)

    assert_(sys.getrefcount(i) >= rc) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def test_byte_bounds(self):
        # pointer difference matches size * itemsize
        # due to contiguity
        a = arange(12).reshape(3, 4)
        low, high = utils.byte_bounds(a)
        assert_equal(high - low, a.size * a.itemsize) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def test_unusual_order_positive_stride(self):
        a = arange(12).reshape(3, 4)
        b = a.T
        low, high = utils.byte_bounds(b)
        assert_equal(high - low, b.size * b.itemsize) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def test_strided(self):
        a = arange(12)
        b = a[::2]
        low, high = utils.byte_bounds(b)
        # the largest pointer address is lost (even numbers only in the
        # stride), and compensate addresses for striding by 2
        assert_equal(high - low, b.size * 2 * b.itemsize - b.itemsize) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def test_byte_bounds():
    a = arange(12).reshape(3, 4)
    low, high = utils.byte_bounds(a)
    assert_equal(high - low, a.size * a.itemsize) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def test_equal_to_original(self):
        """ Test that the new (>=v1.15) implementation (see #10073) is equal to the original (<=v1.14) """
        from numpy.compat import integer_types
        from numpy.core import asarray, concatenate, arange, take

        def original_fftshift(x, axes=None):
            """ How fftshift was implemented in v1.14"""
            tmp = asarray(x)
            ndim = tmp.ndim
            if axes is None:
                axes = list(range(ndim))
            elif isinstance(axes, integer_types):
                axes = (axes,)
            y = tmp
            for k in axes:
                n = tmp.shape[k]
                p2 = (n + 1) // 2
                mylist = concatenate((arange(p2, n), arange(p2)))
                y = take(y, mylist, k)
            return y

        def original_ifftshift(x, axes=None):
            """ How ifftshift was implemented in v1.14 """
            tmp = asarray(x)
            ndim = tmp.ndim
            if axes is None:
                axes = list(range(ndim))
            elif isinstance(axes, integer_types):
                axes = (axes,)
            y = tmp
            for k in axes:
                n = tmp.shape[k]
                p2 = n - (n + 1) // 2
                mylist = concatenate((arange(p2, n), arange(p2)))
                y = take(y, mylist, k)
            return y

        # create possible 2d array combinations and try all possible keywords
        # compare output to original functions
        for i in range(16):
            for j in range(16):
                for axes_keyword in [0, 1, None, (0,), (0, 1)]:
                    inp = np.random.rand(i, j)

                    assert_array_almost_equal(fft.fftshift(inp, axes_keyword),
                                              original_fftshift(inp, axes_keyword))

                    assert_array_almost_equal(fft.ifftshift(inp, axes_keyword),
                                              original_ifftshift(inp, axes_keyword)) 

# 需要導入模塊: from numpy import core [as 別名]
# 或者: from numpy.core import arange [as 別名]
def fftfreq(n, d=1.0):
    """
    Return the Discrete Fourier Transform sample frequencies.

    The returned float array `f` contains the frequency bin centers in cycles
    per unit of the sample spacing (with zero at the start).  For instance, if
    the sample spacing is in seconds, then the frequency unit is cycles/second.

    Given a window length `n` and a sample spacing `d`::

      f = [0, 1, ...,   n/2-1,     -n/2, ..., -1] / (d*n)   if n is even
      f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (d*n)   if n is odd

    Parameters
    ----------
    n : int
        Window length.
    d : scalar, optional
        Sample spacing (inverse of the sampling rate). Defaults to 1.

    Returns
    -------
    f : ndarray
        Array of length `n` containing the sample frequencies.

    Examples
    --------
    >>> signal = np.array([-2, 8, 6, 4, 1, 0, 3, 5], dtype=float)
    >>> fourier = np.fft.fft(signal)
    >>> n = signal.size
    >>> timestep = 0.1
    >>> freq = np.fft.fftfreq(n, d=timestep)
    >>> freq
    array([ 0.  ,  1.25,  2.5 ,  3.75, -5.  , -3.75, -2.5 , -1.25])

    """
    if not isinstance(n, integer_types):
        raise ValueError("n should be an integer")
    val = 1.0 / (n * d)
    results = empty(n, int)
    N = (n-1)//2 + 1
    p1 = arange(0, N, dtype=int)
    results[:N] = p1
    p2 = arange(-(n//2), 0, dtype=int)
    results[N:] = p2
    return results * val