Python highpass_filter Examples

Example #1

File: test_preprocess.py Project: misanthropealoupe/burst_search_ring

    def test_ramp(self):

        ntime = 1000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)

        data_filt = preprocess.highpass_filter(data, 100)
        self.assertTrue(np.allclose(data_filt, 0))

Example #2

File: test_preprocess.py Project: kiyo-masui/burst_search

    def test_ramp(self):

        ntime = 1000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)

        data_filt = preprocess.highpass_filter(data, 100)
        self.assertTrue(np.allclose(data_filt, 0))

Example #3

File: test_preprocess.py Project: misanthropealoupe/burst_search_ring

    def test_low(self):
        ntime = 1000000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)
        data = np.cos(data / 200000.)

        data_filt = preprocess.highpass_filter(data, 100)
        nlost = ntime - data_filt.shape[-1]

        self.assertTrue(np.allclose(data_filt, 0, atol=1e-5))

Example #4

File: test_preprocess.py Project: misanthropealoupe/burst_search_ring

    def test_high(self):
        ntime = 10000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)
        data = np.cos(data)

        data_filt = preprocess.highpass_filter(data, 1000)
        nlost = ntime - data_filt.shape[-1]

        self.assertTrue(
            np.allclose(data_filt, data[:, nlost // 2:-nlost // 2], atol=1e-5))

Example #5

File: test_preprocess.py Project: kiyo-masui/burst_search

    def test_low(self):
        ntime = 1000000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)
        data = np.cos(data / 200000.)

        data_filt = preprocess.highpass_filter(data, 100)
        nlost = ntime - data_filt.shape[-1]

        self.assertTrue(np.allclose(data_filt, 0,
                atol=1e-5))

Example #6

File: test_preprocess.py Project: kiyo-masui/burst_search

    def test_high(self):
        ntime = 10000
        data = np.arange(5 * ntime)
        data.shape = (5, ntime)
        data = np.cos(data)

        data_filt = preprocess.highpass_filter(data, 1000)
        nlost = ntime - data_filt.shape[-1]

        self.assertTrue(np.allclose(data_filt, data[:,nlost//2:-nlost//2],
                atol=1e-5))