Python matplotlib.mlab.apply_window() Examples

The following are 30 code examples of matplotlib.mlab.apply_window(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module matplotlib.mlab , or try the search function .
Example #1
Source File: test_mlab.py    From neural-network-animation with MIT License 6 votes vote down vote up 
def test_apply_window_hanning_2D_stack_windows_axis1_unflatten(self):
        n = 32
        ydata = np.arange(n)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        ydata = ydata.flatten()
        ydata1 = mlab.stride_windows(ydata, 32, noverlap=0, axis=0)
        result = mlab.apply_window(ydata1, mlab.window_hanning, axis=0,
                                   return_window=False)
        assert_allclose(ycontrol.T, result, atol=1e-08)
Example #2
Source File: test_mlab.py    From ImageFusion with MIT License 6 votes vote down vote up 
def test_apply_window_hanning_2D_stack_windows_axis1_unflatten(self):
        n = 32
        ydata = np.arange(n)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        ydata = ydata.flatten()
        ydata1 = mlab.stride_windows(ydata, 32, noverlap=0, axis=0)
        result = mlab.apply_window(ydata1, mlab.window_hanning, axis=0,
                                   return_window=False)
        assert_allclose(ycontrol.T, result, atol=1e-08)
Example #3
Source File: test_mlab.py    From python3_ios with BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up 
def test_apply_window_hanning_2D_stack_windows_axis1_unflatten(self):
        n = 32
        ydata = np.arange(n)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        ydata = ydata.flatten()
        ydata1 = mlab.stride_windows(ydata, 32, noverlap=0, axis=0)
        result = mlab.apply_window(ydata1, mlab.window_hanning, axis=0,
                                   return_window=False)
        assert_allclose(ycontrol.T, result, atol=1e-08)
Example #4
Source File: test_mlab.py    From coffeegrindsize with MIT License 6 votes vote down vote up 
def test_apply_window_hanning_2D_stack_windows_axis1_unflatten(self):
        n = 32
        ydata = np.arange(n)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        ydata = ydata.flatten()
        ydata1 = mlab.stride_windows(ydata, 32, noverlap=0, axis=0)
        result = mlab.apply_window(ydata1, mlab.window_hanning, axis=0,
                                   return_window=False)
        assert_allclose(ycontrol.T, result, atol=1e-08)
Example #5
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_1D_els_wrongsize_ValueError(self):
        x = self.sig_rand
        window = mlab.window_hanning(np.ones(x.shape[0]-1))
        with pytest.raises(ValueError):
            mlab.apply_window(x, window)
Example #6
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_0D_ValueError(self):
        x = np.array(0)
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #7
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_3D_ValueError(self):
        x = self.sig_rand[np.newaxis][np.newaxis]
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #8
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_1D(self):
        x = self.sig_rand
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[0]))
        y, window2 = mlab.apply_window(x, window, return_window=True)
        yt = window(x)
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
        assert_array_equal(window1, window2)
Example #9
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_1D(self):
        x = self.sig_rand
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[0]))
        y, window2 = mlab.apply_window(x, window, return_window=True)
        yt = window(x)
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
        assert_array_equal(window1, window2)
Example #10
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_1D_axis1_ValueError(self):
        x = self.sig_rand
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #11
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els_1D_axis0(self):
        x = self.sig_rand
        window = mlab.window_hanning(np.ones(x.shape[0]))
        window1 = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = window1(x)
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
Example #12
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_0D_ValueError(self):
        x = np.array(0)
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #13
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_3D_ValueError(self):
        x = self.sig_rand[np.newaxis][np.newaxis]
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #14
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window(x[:, i])
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
Example #15
Source File: test_mlab.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els1_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning(np.ones(x.shape[0]))
        window1 = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window1(x[:, i])
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
Example #16
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_stack_axis1(self):
        ydata = np.arange(32)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        result = mlab.apply_window(ydata, mlab.window_hanning, axis=1,
                                   return_window=False)
        assert_allclose(ycontrol, result, atol=1e-08)
Example #17
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window(x[:, i])
        assert yt.shape == y.shape
        assert x.shape == y.shape
        assert_allclose(yt, y, atol=1e-06)
Example #18
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_1D_els_wrongsize_ValueError(self):
        x = self.sig_rand
        window = mlab.window_hanning(np.ones(x.shape[0]-1))
        with pytest.raises(ValueError):
            mlab.apply_window(x, window)
Example #19
Source File: test_mlab.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_apply_window_1D_axis1_ValueError(self):
        x = self.sig_rand
        window = mlab.window_hanning
        with pytest.raises(ValueError):
            mlab.apply_window(x, window, axis=1, return_window=False)
Example #20
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_stack_axis1(self):
        ydata = np.arange(32)
        ydata1 = ydata+5
        ydata2 = ydata+3.3
        ycontrol1 = mlab.apply_window(ydata1, mlab.window_hanning)
        ycontrol2 = mlab.window_hanning(ydata2)
        ydata = np.vstack([ydata1, ydata2])
        ycontrol = np.vstack([ycontrol1, ycontrol2])
        ydata = np.tile(ydata, (20, 1))
        ycontrol = np.tile(ycontrol, (20, 1))
        result = mlab.apply_window(ydata, mlab.window_hanning, axis=1,
                                   return_window=False)
        assert_allclose(ycontrol, result, atol=1e-08)
Example #21
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_stride_windows_hanning_2D_n13_noverlapn3_axis0(self):
        x = self.sig_rand
        window = mlab.window_hanning
        yi = mlab.stride_windows(x, n=13, noverlap=2, axis=0)
        y = mlab.apply_window(yi, window, axis=0, return_window=False)
        yt = self.check_window_apply_repeat(x, window, 13, 2)
        assert_equal(yt.shape, y.shape)
        assert_not_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #22
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_els3_axis1(self):
        x = np.random.standard_normal([10, 1000]) + 100.
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[1]))
        y = mlab.apply_window(x, window, axis=1, return_window=False)
        yt = mlab.apply_window(x, window1, axis=1, return_window=False)
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #23
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_els2_axis1(self):
        x = np.random.standard_normal([10, 1000]) + 100.
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[1]))
        y, window2 = mlab.apply_window(x, window, axis=1, return_window=True)
        yt = np.zeros_like(x)
        for i in range(x.shape[0]):
            yt[i, :] = window1 * x[i, :]
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
        assert_array_equal(window1, window2)
Example #24
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D__els1_axis1(self):
        x = np.random.standard_normal([10, 1000]) + 100.
        window = mlab.window_hanning(np.ones(x.shape[1]))
        window1 = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=1, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[0]):
            yt[i, :] = window1(x[i, :])
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #25
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els3_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[0]))
        y, window2 = mlab.apply_window(x, window, axis=0, return_window=True)
        yt = mlab.apply_window(x, window1, axis=0, return_window=False)
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
        assert_array_equal(window1, window2)
Example #26
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els2_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning
        window1 = mlab.window_hanning(np.ones(x.shape[0]))
        y, window2 = mlab.apply_window(x, window, axis=0, return_window=True)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window1*x[:, i]
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
        assert_array_equal(window1, window2)
Example #27
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els1_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning(np.ones(x.shape[0]))
        window1 = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window1(x[:, i])
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #28
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_2D_axis0(self):
        x = np.random.standard_normal([1000, 10]) + 100.
        window = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = np.zeros_like(x)
        for i in range(x.shape[1]):
            yt[:, i] = window(x[:, i])
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #29
Source File: test_mlab.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_apply_window_hanning_els_1D_axis0(self):
        x = self.sig_rand
        window = mlab.window_hanning(np.ones(x.shape[0]))
        window1 = mlab.window_hanning
        y = mlab.apply_window(x, window, axis=0, return_window=False)
        yt = window1(x)
        assert_equal(yt.shape, y.shape)
        assert_equal(x.shape, y.shape)
        assert_allclose(yt, y, atol=1e-06)
Example #30
Source File: test_mlab.py    From neural-network-animation with MIT License 5 votes vote down vote up 
def test_apply_window_1D_axis1_ValueError(self):
        x = self.sig_rand
        window = mlab.window_hanning
        assert_raises(ValueError, mlab.apply_window, x, window, axis=1,
                      return_window=False)