python类geterr()的实例源码

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def with_error_settings(**new_settings):
    """
    TODO.

    Arguments:
      **new_settings: TODO

    Returns:
    """
    @decorator.decorator
    def dec(f, *args, **kwargs):
        old_settings = np.geterr()

        np.seterr(**new_settings)
        ret = f(*args, **kwargs)

        np.seterr(**old_settings)

        return ret

    return dec

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def transform(value, left_scale, right_scale, scale=0):
    if left_scale is None or right_scale is None:
        raise Exception('Left or Right scales cannot be None.')
    if scale not in [0, 1]:
        raise Exception('Scale must be 0 or 1.')
    invalid_err = np.geterr().get('invalid')
    invalid_err = np.geterr().get('invalid')
    np.seterr(invalid='ignore')    
    if scale == 0:
        range_ = np.absolute(right_scale - left_scale)
        translated_value = np.abs(value - left_scale)    
        ret_val =  (translated_value / range_)
    else:
        if left_scale <= 0.0:
            raise Exception()
        ls = np.log10(left_scale)    
        rs = np.log10(right_scale)
        range_ = rs - ls
        translated_value = np.log10(value) - ls
        ret_val =  (translated_value / range_)
    np.seterr(invalid=invalid_err)
    return ret_val

def setUp(self):
        # Base data definition.
        x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
        y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
        a10 = 10.
        m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
        m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
        xm = masked_array(x, mask=m1)
        ym = masked_array(y, mask=m2)
        z = np.array([-.5, 0., .5, .8])
        zm = masked_array(z, mask=[0, 1, 0, 0])
        xf = np.where(m1, 1e+20, x)
        xm.set_fill_value(1e+20)
        self.d = (x, y, a10, m1, m2, xm, ym, z, zm, xf)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def setUp(self):
        # Base data definition.
        self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
                  array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def __enter__(self):
        self.err = numpy.geterr()
        numpy.seterr(**self.kw)

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def setUp(self):
        # Base data definition.
        self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
                  array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def index(self):
        if self._instantiated_index is None:
            if self._index_class is None:
                raise RuntimeError("You should not instantiate Dataset.")
            self._instantiated_index = self._index_class(
                self, dataset_type=self.dataset_type)
            # Now we do things that we need an instantiated index for
            # ...first off, we create our field_info now.
            oldsettings = np.geterr()
            np.seterr(all='ignore')
            self.create_field_info()
            np.seterr(**oldsettings)
        return self._instantiated_index

def __enter__(self):
        self.err = numpy.geterr()
        numpy.seterr(**self.kw)

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def setUp(self):
        # Base data definition.
        self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
                  array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def setUp(self):
        # Base data definition.
        self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
                  array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def setUp(self):
        # Base data definition.
        self.d = (array([1.0, 0, -1, pi / 2] * 2, mask=[0, 1] + [0] * 6),
                  array([1.0, 0, -1, pi / 2] * 2, mask=[1, 0] + [0] * 6),)
        self.err_status = np.geterr()
        np.seterr(divide='ignore', invalid='ignore')

def test_default(self):
        err = np.geterr()
        self.assertEqual(err, dict(
            divide='warn',
            invalid='warn',
            over='warn',
            under='ignore',
        ))

def test_set(self):
        with np.errstate():
            err = np.seterr()
            old = np.seterr(divide='print')
            self.assertTrue(err == old)
            new = np.seterr()
            self.assertTrue(new['divide'] == 'print')
            np.seterr(over='raise')
            self.assertTrue(np.geterr()['over'] == 'raise')
            self.assertTrue(new['divide'] == 'print')
            np.seterr(**old)
            self.assertTrue(np.geterr() == old)

def _sample(self):
        super()._sample()

        self._fft_values[:] = numpy.abs(numpy.fft.rfft(self._window_function * self.buffer))

        if self._output == 'fft':
            pass
        elif self._output == 'psd':
            # Reminder for future-self:
            # Our Input signal is clamped between -1.0 and +1.0 yet if we convert the values above ^ into dB
            # we get values way beyond 0dB which makes no sense. Turns out we have to normalize the resulting
            # vector.
            # Thank you my hero: https://dsp.stackexchange.com/a/32080
            # TODO: This can be pre-calculated!
            self._fft_values[:] = numpy.power(self._fft_values * 2.0, 2) \
                / numpy.power(self._window_function_sum * self._reference_value, 2)
        else:
            raise PulsevizException('This should not happen.')

        if self._scaling == 'lin':
            pass
        elif self._scaling == 'log':
            numpy.seterr(divide='ignore')
            self._fft_values[:] = 10.0 * numpy.log10(self._fft_values)
            numpy.seterr(all='raise')  # TODO: Use result of numpy.geterr instead?
        else:
            raise PulsevizException('This should not happen.')

        if self._scaling == 'log':
            self._fft_values[:] += self._fft_weights
        else:
            self._fft_values[:] *= numpy.power(10, self._fft_weights / 20)  # TODO: Test this.