Python LinearTimeSpectrogram.join_many示例

示例#1

文件： test_spectrogram.py 项目： tyagi-prashant/sunpy

def test_join_gap():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image,
        np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(
            2010,
            10,
            11,
            0,
            15,
        ),
        85500,
        0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image,
        np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15, 1),
        datetime(2010, 10, 11, 1, 15),
        901,
        1,
    )
    with pytest.raises(ValueError) as excinfo:
        LinearTimeSpectrogram.join_many([one, other],
                                        nonlinear=False,
                                        maxgap=0)

    assert excinfo.value.message == "Too large gap."

示例#2

def test_join_diff_freq():
    image = np.random.rand(5, 3600)
    spec = LinearTimeSpectrogram(
        image, np.linspace(0, 0.25 * (image.shape[1] - 1), image.shape[1]),
        np.array([8, 6, 4, 2, 0]), datetime(2010, 1, 1, 0, 15),
        datetime(2010, 1, 1, 0, 30), 900, 0.25)
    image = np.random.rand(5, 3600)
    spec2 = LinearTimeSpectrogram(
        image, np.linspace(0, 0.25 * (image.shape[1] - 1), image.shape[1]),
        np.array([9, 7, 5, 3, 1]), datetime(2010, 1, 1, 0, 15),
        datetime(2010, 1, 1, 0, 30), 1800, 0.25)

    with pytest.raises(ValueError) as excinfo:
        LinearTimeSpectrogram.join_many([spec, spec2])
    assert excinfo.value.message == "Frequency channels do not match."

示例#3

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_nonlinear():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15),
        datetime(2010, 10, 11, 1, 15), 901, 1,
    )

    oz = other.resample_time(0.5)

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=True, maxgap=2
    )

    # The - 1 is because resampling other produces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)
    assert np.array_equal(z.time_axis[:3600], one.time_axis)
    assert np.array_equal(z.time_axis[3600:], oz.time_axis + 1801)
    assert isinstance(z, Spectrogram)

示例#4

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_with_gap_fill():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15), datetime(2010, 10, 11, 1, 15), 901, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=2, fill=np.NaN
    )
    # The - 1 is because resampling other produces an image of size
    # 2 * 3600 - 1
    # The + 2 is because there is one second without data inserted.
    assert z.shape == (200, 3 * 3600 + 2 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)

    print(type(z.data))

    # Second data to unpack masked array
    assert np.isnan(z.data.data[:, 3600:3602]).all()
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#5

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_year():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2012, 12, 31, 23, 30),
        datetime(2013, 1, 1, 0, 0, 0), 84600, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2013, 1, 1), datetime(2013, 1, 1, 1), 0, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    # The - 1 is because resampling other produces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#6

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10), datetime(2010, 10, 10, 0, 30), 0, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 0, 29),
        datetime(2010, 10, 10, 1, 29), 1799, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    # The - 1 is because resampling other produces an image of size
    # 2 * 3600 - 1
    # The - 2 is because there is one second overlap.
    assert z.shape == (200, 3 * 3600 - 2 - 1)

    assert np.array_equal(z.data[:, :3598], one.data[:, :-2])
    # assert np.array_equal(z[:, 3598:], ndimage.zoom(other, (1, 2)))
    assert z.start == one.start
    assert z.end == other.end
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#7

文件： test_spectrogram.py 项目： saemideluxe/sunpy

def test_join_nonlinear():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15),
        datetime(2010, 10, 11, 1, 15), 901, 1,
    )

    oz = other.resample_time(0.5)

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=True, maxgap=2
    )

    # The - 1 is because resampling other procuces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)
    assert np.array_equal(z.time_axis[:3600], one.time_axis)
    assert np.array_equal(z.time_axis[3600:], oz.time_axis + 1801)
    assert isinstance(z, Spectrogram)

示例#8

文件： test_spectrogram.py 项目： saemideluxe/sunpy

def test_join_with_gap_fill():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15), datetime(2010, 10, 11, 1, 15), 901, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=2, fill=np.NaN
    )
    # The - 1 is because resampling other procuces an image of size
    # 2 * 3600 - 1
    # The + 2 is because there is one second without data inserted.
    assert z.shape == (200, 3 * 3600 + 2 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)

    print type(z.data)

    # Second data to unpack masked array
    assert np.isnan(z.data.data[:, 3600:3602]).all()
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#9

文件： test_spectrogram.py 项目： saemideluxe/sunpy

def test_join_year():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2012, 12, 31, 23, 30),
        datetime(2013, 1, 1, 0, 0, 0), 84600, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2013, 1, 1), datetime(2013, 1, 1, 1), 0, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    # The - 1 is because resampling other procuces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#10

文件： test_spectrogram.py 项目： saemideluxe/sunpy

def test_join():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10), datetime(2010, 10, 10, 0, 30), 0, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 0, 29),
        datetime(2010, 10, 10, 1, 29), 1799, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    # The - 1 is because resampling other procuces an image of size
    # 2 * 3600 - 1
    # The - 2 is because there is one second overlap.
    assert z.shape == (200, 3 * 3600 - 2 - 1)

    assert np.array_equal(z.data[:, :3598], one.data[:, :-2])
    # assert np.array_equal(z[:, 3598:], ndimage.zoom(other, (1, 2)))
    assert z.start == one.start
    assert z.end == other.end
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#11

文件： test_spectrogram.py 项目： ToyDragon/sunpy

def test_join_over_midnight():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )
    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15), datetime(2010, 10, 11, 1, 15), 900, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    oz = other.resample_time(0.5)

    # The - 1 is because resampling other procuces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z[:, :3600], one)
    assert np.array_equal(z.time_axis[:3600], one.time_axis)
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#12

def test_join_different_dtype():
    image = np.random.rand(200, 3600).astype(np.uint16)
    one = LinearTimeSpectrogram(
        image,
        np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10),
        datetime(2010, 10, 10, 0, 30),
        0,
        0.5,
    )

    image = np.random.rand(200, 3600).astype(np.uint8)
    other = LinearTimeSpectrogram(
        image,
        np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 0, 29),
        datetime(2010, 10, 10, 1, 29),
        1799,
        1,
    )

    z = LinearTimeSpectrogram.join_many([one, other],
                                        nonlinear=False,
                                        maxgap=0)
    assert z.dtype == np.dtype('uint16')

示例#13

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_gap():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(2010, 10, 11, 0, 15,), 85500, 0.5,
    )

    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15, 1),
        datetime(2010, 10, 11, 1, 15), 901, 1,
    )
    with pytest.raises(ValueError) as excinfo:
        LinearTimeSpectrogram.join_many(
            [one, other], nonlinear=False, maxgap=0
        )
        assert excinfo.value.message == "Too large gap."

示例#14

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_diff_freq():
    image = np.random.rand(5, 3600)
    spec = LinearTimeSpectrogram(image,
        np.linspace(0, 0.25 * (image.shape[1] - 1), image.shape[1]),
        np.array([8, 6, 4, 2, 0]),
        datetime(2010, 1, 1, 0, 15),
        datetime(2010, 1, 1, 0, 30),
        900,
        0.25
    )
    image = np.random.rand(5, 3600)
    spec2 = LinearTimeSpectrogram(image,
        np.linspace(0, 0.25 * (image.shape[1] - 1), image.shape[1]),
        np.array([9, 7, 5, 3, 1]),
        datetime(2010, 1, 1, 0, 15),
        datetime(2010, 1, 1, 0, 30),
        1800,
        0.25
    )

    with pytest.raises(ValueError) as excinfo:
        LinearTimeSpectrogram.join_many([spec, spec2])
        assert excinfo.value.message == "Frequency channels do not match."

示例#15

文件： test_spectrogram.py 项目： tyagi-prashant/sunpy

def test_join_over_midnight():
    image = np.random.rand(200, 3600)
    one = LinearTimeSpectrogram(
        image,
        np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 23, 45),
        datetime(
            2010,
            10,
            11,
            0,
            15,
        ),
        85500,
        0.5,
    )
    image = np.random.rand(200, 3600)
    other = LinearTimeSpectrogram(
        image,
        np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 11, 0, 15),
        datetime(2010, 10, 11, 1, 15),
        900,
        1,
    )

    z = LinearTimeSpectrogram.join_many([one, other],
                                        nonlinear=False,
                                        maxgap=0)
    # FIXME: not used?!
    oz = other.resample_time(0.5)

    # The - 1 is because resampling other produces an image of size
    # 2 * 3600 - 1
    assert z.shape == (200, 3 * 3600 - 1)

    assert np.array_equal(z.data[:, :3600], one.data)
    assert np.array_equal(z.time_axis[:3600], one.time_axis)
    assert is_linear(z.time_axis)
    assert isinstance(z, LinearTimeSpectrogram)

示例#16

文件： test_spectrogram.py 项目： derdon/sunpy

def test_join_different_dtype():
    image = np.random.rand(200, 3600).astype(np.uint16)
    one = LinearTimeSpectrogram(
        image, np.linspace(0, 0.5 * (image.shape[1] - 1), image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10), datetime(2010, 10, 10, 0, 30), 0, 0.5,
    )

    image = np.random.rand(200, 3600).astype(np.uint8)
    other = LinearTimeSpectrogram(
        image, np.linspace(0, image.shape[1] - 1, image.shape[1]),
        np.linspace(0, image.shape[0] - 1, image.shape[0]),
        datetime(2010, 10, 10, 0, 29),
        datetime(2010, 10, 10, 1, 29), 1799, 1,
    )

    z = LinearTimeSpectrogram.join_many(
        [one, other], nonlinear=False, maxgap=0
    )
    assert z.dtype == np.dtype('uint16')