Python numpy.floor_divide() Examples

The following are 30 code examples for showing how to use numpy.floor_divide(). These examples are extracted from open source projects. 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 check out the related API usage on the sidebar.

You may also want to check out all available functions/classes of the module numpy , or try the search function .

Example 1
def w(w_max, w_min, step):
    linspace_lower = (np.floor_divide(w_min, step)+1)*step
    N = np.floor_divide(w_max-w_min, step)
    linspace_upper = linspace_lower + N*step
    w = np.linspace(linspace_lower, linspace_upper, int(N)+1)
    
    if not np.isclose(w[0], w_min, atol=step/5.):
        w = np.concatenate((np.array([w_min]), w))
        
    if not np.isclose(w[-1], w_max, atol=step/5.):
        w = np.concatenate((w,np.array([w_max])))
    
    return w, len(w)

# Compute dielectric function using Lorentzian model.
# Units of w and ResFreq must match and must be directly proportional to angular frequency. All other parameters are unitless. 
Example 2
def w(w_max, w_min, step):
    linspace_lower = (np.floor_divide(w_min, step)+1)*step
    N = np.floor_divide(w_max-w_min, step)
    linspace_upper = linspace_lower + N*step
    w = np.linspace(linspace_lower, linspace_upper, int(N)+1)
    
    if not np.isclose(w[0], w_min, atol=step/5.):
        w = np.concatenate((np.array([w_min]), w))
        
    if not np.isclose(w[-1], w_max, atol=step/5.):
        w = np.concatenate((w,np.array([w_max])))
    
    return w, len(w)

# Compute dielectric function using Brendel-Bormann (aka Gaussian or Gaussian-convoluted Drude–Lorentz) model.
# Units of w and ResFreq must match and must be directly proportional to angular frequency. All other parameters are unitless. 
Example 3
def w(w_max, w_min, step):
    linspace_lower = (np.floor_divide(w_min, step)+1)*step
    N = np.floor_divide(w_max-w_min, step)
    linspace_upper = linspace_lower + N*step
    w = np.linspace(linspace_lower, linspace_upper, int(N)+1)
    
    if not np.isclose(w[0], w_min, atol=step/5.):
        w = np.concatenate((np.array([w_min]), w))
        
    if not np.isclose(w[-1], w_max, atol=step/5.):
        w = np.concatenate((w,np.array([w_max])))
    
    return w, len(w)

# Compute dielectric function using Lorentzian model.
# Units of w and ResFreq must match and must be directly proportional to angular frequency. All other parameters are unitless. 
Example 4
def w(w_max, w_min, step):
    linspace_lower = (np.floor_divide(w_min, step)+1)*step
    N = np.floor_divide(w_max-w_min, step)
    linspace_upper = linspace_lower + N*step
    w = np.linspace(linspace_lower, linspace_upper, int(N)+1)
    
    if not np.isclose(w[0], w_min, atol=step/5.):
        w = np.concatenate((np.array([w_min]), w))
        
    if not np.isclose(w[-1], w_max, atol=step/5.):
        w = np.concatenate((w,np.array([w_max])))
    
    return w, len(w)

# Compute dielectric function using Lorentzian model.
# Units of w and ResFreq must match and must be directly proportional to angular frequency. All other parameters are unitless. 
Example 5
def w(w_max, w_min, step):
    linspace_lower = (np.floor_divide(w_min, step)+1)*step
    N = np.floor_divide(w_max-w_min, step)
    linspace_upper = linspace_lower + N*step
    w = np.linspace(linspace_lower, linspace_upper, int(N)+1)
    
    if not np.isclose(w[0], w_min, atol=step/5.):
        w = np.concatenate((np.array([w_min]), w))
        
    if not np.isclose(w[-1], w_max, atol=step/5.):
        w = np.concatenate((w,np.array([w_max])))
    
    return w, len(w)

# Compute dielectric function using Lorentzian model.
# Units of w and ResFreq must match and must be directly proportional to angular frequency. All other parameters are unitless. 
Example 6
Project: recruit   Author: Frank-qlu   File: test_ufunc.py    License: Apache License 2.0 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod,
            np.greater, np.greater_equal, np.less, np.less_equal,
            np.equal, np.not_equal]

        a = np.array('1')
        b = 1
        c = np.array([1., 2.])
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b)
            assert_raises(TypeError, f, c, a) 
Example 7
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_ufunc.py    License: MIT License 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 8
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_umath.py    License: MIT License 6 votes vote down vote up
def test_remainder_basic(self):
        dt = np.typecodes['AllInteger'] + np.typecodes['Float']
        for dt1, dt2 in itertools.product(dt, dt):
            for sg1, sg2 in itertools.product((+1, -1), (+1, -1)):
                if sg1 == -1 and dt1 in np.typecodes['UnsignedInteger']:
                    continue
                if sg2 == -1 and dt2 in np.typecodes['UnsignedInteger']:
                    continue
                fmt = 'dt1: %s, dt2: %s, sg1: %s, sg2: %s'
                msg = fmt % (dt1, dt2, sg1, sg2)
                a = np.array(sg1*71, dtype=dt1)
                b = np.array(sg2*19, dtype=dt2)
                div = np.floor_divide(a, b)
                rem = np.remainder(a, b)
                assert_equal(div*b + rem, a, err_msg=msg)
                if sg2 == -1:
                    assert_(b < rem <= 0, msg)
                else:
                    assert_(b > rem >= 0, msg) 
Example 9
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_umath.py    License: MIT License 6 votes vote down vote up
def test_float_remainder_exact(self):
        # test that float results are exact for small integers. This also
        # holds for the same integers scaled by powers of two.
        nlst = list(range(-127, 0))
        plst = list(range(1, 128))
        dividend = nlst + [0] + plst
        divisor = nlst + plst
        arg = list(itertools.product(dividend, divisor))
        tgt = list(divmod(*t) for t in arg)

        a, b = np.array(arg, dtype=int).T
        # convert exact integer results from Python to float so that
        # signed zero can be used, it is checked.
        tgtdiv, tgtrem = np.array(tgt, dtype=float).T
        tgtdiv = np.where((tgtdiv == 0.0) & ((b < 0) ^ (a < 0)), -0.0, tgtdiv)
        tgtrem = np.where((tgtrem == 0.0) & (b < 0), -0.0, tgtrem)

        for dt in np.typecodes['Float']:
            msg = 'dtype: %s' % (dt,)
            fa = a.astype(dt)
            fb = b.astype(dt)
            div = np.floor_divide(fa, fb)
            rem = np.remainder(fa, fb)
            assert_equal(div, tgtdiv, err_msg=msg)
            assert_equal(rem, tgtrem, err_msg=msg) 
Example 10
Project: vnpy_crypto   Author: birforce   File: test_ufunc.py    License: MIT License 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 11
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: test_ufunc.py    License: MIT License 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod,
            np.greater, np.greater_equal, np.less, np.less_equal,
            np.equal, np.not_equal]

        a = np.array('1')
        b = 1
        c = np.array([1., 2.])
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b)
            assert_raises(TypeError, f, c, a) 
Example 12
Project: MONAI   Author: Project-MONAI   File: array.py    License: Apache License 2.0 6 votes vote down vote up
def __init__(self, roi_center=None, roi_size=None, roi_start=None, roi_end=None):
        """
        Args:
            roi_center (list or tuple): voxel coordinates for center of the crop ROI.
            roi_size (list or tuple): size of the crop ROI.
            roi_start (list or tuple): voxel coordinates for start of the crop ROI.
            roi_end (list or tuple): voxel coordinates for end of the crop ROI.
        """
        if roi_center is not None and roi_size is not None:
            roi_center = np.asarray(roi_center, dtype=np.uint16)
            roi_size = np.asarray(roi_size, dtype=np.uint16)
            self.roi_start = np.subtract(roi_center, np.floor_divide(roi_size, 2))
            self.roi_end = np.add(self.roi_start, roi_size)
        else:
            assert roi_start is not None and roi_end is not None, "roi_start and roi_end must be provided."
            self.roi_start = np.asarray(roi_start, dtype=np.uint16)
            self.roi_end = np.asarray(roi_end, dtype=np.uint16)

        assert np.all(self.roi_start >= 0), "all elements of roi_start must be greater than or equal to 0."
        assert np.all(self.roi_end > 0), "all elements of roi_end must be positive."
        assert np.all(self.roi_end >= self.roi_start), "invalid roi range." 
Example 13
Project: GraphicDesignPatternByPython   Author: Relph1119   File: test_ufunc.py    License: MIT License 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 14
Project: deep_image_model   Author: tobegit3hub   File: cwise_ops_test.py    License: Apache License 2.0 6 votes vote down vote up
def testFloatBasic(self):
    x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float32)
    y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float32)
    self._compareBoth(x, y, np.add, tf.add, also_compare_variables=True)
    self._compareBoth(x, y, np.subtract, tf.sub)
    self._compareBoth(x, y, np.multiply, tf.mul)
    self._compareBoth(x, y + 0.1, np.true_divide, tf.truediv)
    self._compareBoth(x, y + 0.1, np.floor_divide, tf.floordiv)
    self._compareBoth(x, y, np.add, _ADD)
    self._compareBoth(x, y, np.subtract, _SUB)
    self._compareBoth(x, y, np.multiply, _MUL)
    self._compareBoth(x, y + 0.1, np.true_divide, _TRUEDIV)
    self._compareBoth(x, y + 0.1, np.floor_divide, _FLOORDIV)
    try:
      from scipy import special  # pylint: disable=g-import-not-at-top
      a_pos_small = np.linspace(0.1, 2, 15).reshape(1, 3, 5).astype(np.float32)
      x_pos_small = np.linspace(0.1, 10, 15).reshape(1, 3, 5).astype(np.float32)
      self._compareBoth(a_pos_small, x_pos_small, special.gammainc, tf.igamma)
      self._compareBoth(a_pos_small, x_pos_small, special.gammaincc, tf.igammac)
      # Need x > 1
      self._compareBoth(x_pos_small + 1, a_pos_small, special.zeta, tf.zeta)
      n_small = np.arange(0, 15).reshape(1, 3, 5).astype(np.float32)
      self._compareBoth(n_small, x_pos_small, special.polygamma, tf.polygamma)
    except ImportError as e:
      tf.logging.warn("Cannot test special functions: %s" % str(e)) 
Example 15
Project: deep_image_model   Author: tobegit3hub   File: cwise_ops_test.py    License: Apache License 2.0 6 votes vote down vote up
def testDoubleBasic(self):
    x = np.linspace(-5, 20, 15).reshape(1, 3, 5).astype(np.float64)
    y = np.linspace(20, -5, 15).reshape(1, 3, 5).astype(np.float64)
    self._compareBoth(x, y, np.add, tf.add)
    self._compareBoth(x, y, np.subtract, tf.sub)
    self._compareBoth(x, y, np.multiply, tf.mul)
    self._compareBoth(x, y + 0.1, np.true_divide, tf.truediv)
    self._compareBoth(x, y + 0.1, np.floor_divide, tf.floordiv)
    self._compareBoth(x, y, np.add, _ADD)
    self._compareBoth(x, y, np.subtract, _SUB)
    self._compareBoth(x, y, np.multiply, _MUL)
    self._compareBoth(x, y + 0.1, np.true_divide, _TRUEDIV)
    self._compareBoth(x, y + 0.1, np.floor_divide, _FLOORDIV)
    try:
      from scipy import special  # pylint: disable=g-import-not-at-top
      a_pos_small = np.linspace(0.1, 2, 15).reshape(1, 3, 5).astype(np.float32)
      x_pos_small = np.linspace(0.1, 10, 15).reshape(1, 3, 5).astype(np.float32)
      self._compareBoth(a_pos_small, x_pos_small, special.gammainc, tf.igamma)
      self._compareBoth(a_pos_small, x_pos_small, special.gammaincc, tf.igammac)
    except ImportError as e:
      tf.logging.warn("Cannot test special functions: %s" % str(e)) 
Example 16
Project: deep_image_model   Author: tobegit3hub   File: cwise_ops_test.py    License: Apache License 2.0 6 votes vote down vote up
def testInt32Basic(self):
    x = np.arange(1, 13, 2).reshape(1, 3, 2).astype(np.int32)
    y = np.arange(1, 7, 1).reshape(1, 3, 2).astype(np.int32)
    self._compareBoth(x, y, np.add, tf.add)
    self._compareBoth(x, y, np.subtract, tf.sub)
    self._compareBoth(x, y, np.multiply, tf.mul)
    self._compareBoth(x, y, np.true_divide, tf.truediv)
    self._compareBoth(x, y, np.floor_divide, tf.floordiv)
    self._compareBoth(x, y, np.mod, tf.mod)
    self._compareBoth(x, y, np.add, _ADD)
    self._compareBoth(x, y, np.subtract, _SUB)
    self._compareBoth(x, y, np.multiply, _MUL)
    self._compareBoth(x, y, np.true_divide, _TRUEDIV)
    self._compareBoth(x, y, np.floor_divide, _FLOORDIV)
    self._compareBoth(x, y, np.mod, _MOD)
    # _compareBoth tests on GPU only for floating point types, so test
    # _MOD for int32 on GPU by calling _compareGpu
    self._compareGpu(x, y, np.mod, _MOD) 
Example 17
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod,
            np.greater, np.greater_equal, np.less, np.less_equal,
            np.equal, np.not_equal]

        a = np.array('1')
        b = 1
        c = np.array([1., 2.])
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b)
            assert_raises(TypeError, f, c, a) 
Example 18
Project: pySINDy   Author: luckystarufo   File: test_ufunc.py    License: MIT License 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 19
Project: mxnet-lambda   Author: awslabs   File: test_ufunc.py    License: Apache License 2.0 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 20
Project: lkpy   Author: lenskit   File: test_matrix_csr.py    License: MIT License 6 votes vote down vote up
def test_csr_from_coo_novals():
    for i in range(50):
        coords = np.random.choice(np.arange(50 * 100, dtype=np.int32), 1000, False)
        rows = np.mod(coords, 100, dtype=np.int32)
        cols = np.floor_divide(coords, 100, dtype=np.int32)

        csr = lm.CSR.from_coo(rows, cols, None, (100, 50))
        assert csr.nrows == 100
        assert csr.ncols == 50
        assert csr.nnz == 1000

        for i in range(100):
            sp = csr.rowptrs[i]
            ep = csr.rowptrs[i+1]
            assert ep - sp == np.sum(rows == i)
            points, = np.nonzero(rows == i)
            po = np.argsort(cols[points])
            points = points[po]
            assert all(np.sort(csr.colinds[sp:ep]) == cols[points])
            assert np.sum(csr.row(i)) == len(points) 
Example 21
Project: SpaceNet_Off_Nadir_Solutions   Author: SpaceNetChallenge   File: convert_test.py    License: Apache License 2.0 6 votes vote down vote up
def process_image(img_id):
    if 'Pan-Sharpen_' in img_id:
        img_id = img_id.split('Pan-Sharpen_')[1]
    img = io.imread(path.join(test_dir, '_'.join(img_id.split('_')[:4]), 'Pan-Sharpen', 'Pan-Sharpen_' + img_id+'.tif'))
    nir = img[:, :, 3:]
    img = img[:, :, :3]
    np.clip(img, None, threshold, out=img)
    img = np.floor_divide(img, threshold / 255).astype('uint8')
    cv2.imwrite(path.join(test_png, img_id + '.png'), img, [cv2.IMWRITE_PNG_COMPRESSION, 9])

    img2 = io.imread(path.join(test_dir, '_'.join(img_id.split('_')[:4]), 'MS', 'MS_' + img_id+'.tif'))
    img2 = np.rollaxis(img2, 0, 3)
    img2 = cv2.resize(img2, (900, 900), interpolation=cv2.INTER_LANCZOS4)
    
    img_0_3_5 = (np.clip(img2[..., [0, 3, 5]], None, (2000, 3000, 3000)) / (np.array([2000, 3000, 3000]) / 255)).astype('uint8')
    cv2.imwrite(path.join(test_png2, img_id + '.png'), img_0_3_5, [cv2.IMWRITE_PNG_COMPRESSION, 9])
    
    pan = io.imread(path.join(test_dir, '_'.join(img_id.split('_')[:4]), 'PAN', 'PAN_' + img_id+'.tif'))
    pan = pan[..., np.newaxis]
    img_pan_6_7 = np.concatenate([pan, img2[..., 7:], nir], axis=2)
    img_pan_6_7 = (np.clip(img_pan_6_7, None, (3000, 5000, 5000)) / (np.array([3000, 5000, 5000]) / 255)).astype('uint8')
    cv2.imwrite(path.join(test_png3, img_id + '.png'), img_pan_6_7, [cv2.IMWRITE_PNG_COMPRESSION, 9]) 
Example 22
Project: elasticintel   Author: securityclippy   File: test_ufunc.py    License: GNU General Public License v3.0 6 votes vote down vote up
def test_NotImplemented_not_returned(self):
        # See gh-5964 and gh-2091. Some of these functions are not operator
        # related and were fixed for other reasons in the past.
        binary_funcs = [
            np.power, np.add, np.subtract, np.multiply, np.divide,
            np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or,
            np.bitwise_xor, np.left_shift, np.right_shift, np.fmax,
            np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2,
            np.logical_and, np.logical_or, np.logical_xor, np.maximum,
            np.minimum, np.mod
            ]

        # These functions still return NotImplemented. Will be fixed in
        # future.
        # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal]

        a = np.array('1')
        b = 1
        for f in binary_funcs:
            assert_raises(TypeError, f, a, b) 
Example 23
Project: gnocchi   Author: gnocchixyz   File: carbonara.py    License: Apache License 2.0 5 votes vote down vote up
def median(self):
        ordered = numpy.lexsort((self._ts['values'], self.indexes))
        # TODO(gordc): can use np.divmod when centos supports numpy 1.13
        mid_diff = numpy.floor_divide(self.counts, 2)
        odd = numpy.mod(self.counts, 2)
        mid_floor = (numpy.cumsum(self.counts) - 1) - mid_diff
        mid_ceil = mid_floor + (odd + 1) % 2
        return make_timeseries(
            self.tstamps, (self._ts['values'][ordered][mid_floor] +
                           self._ts['values'][ordered][mid_ceil]) / 2.0) 
Example 24
Project: baseband   Author: mhvk   File: encoding.py    License: GNU General Public License v3.0 5 votes vote down vote up
def encode_2bit_base(values):
    """Generic encoder for data stored using two bits.

    This returns an unsigned integer array containing encoded sample
    values that range from 0 to 3.  The conversion from floating point
    sample value to unsigned int is given below, with
    ``lv = TWO_BIT_1_SIGMA = 2.1745``:

      ================= ======
      Input range       Output
      ================= ======
            value < -lv   0
      -lv < value <  0.   2
       0. < value <  lv   1
       lv < value         3
      ================= ======

    This does not pack the samples into bytes.
    """
    # Optimized for speed by doing calculations in-place, and ensuring that
    # the dtypes match.
    values = np.clip(values, clip_low, clip_high)
    values += two_bit_2_sigma
    bitvalues = np.empty(values.shape, np.uint8)
    return np.floor_divide(values, TWO_BIT_1_SIGMA, out=bitvalues,
                           casting='unsafe') 
Example 25
Project: recruit   Author: Frank-qlu   File: test_umath.py    License: Apache License 2.0 5 votes vote down vote up
def test_floor_division_complex(self):
        # check that implementation is correct
        msg = "Complex floor division implementation check"
        x = np.array([.9 + 1j, -.1 + 1j, .9 + .5*1j, .9 + 2.*1j], dtype=np.complex128)
        y = np.array([0., -1., 0., 0.], dtype=np.complex128)
        assert_equal(np.floor_divide(x**2, x), y, err_msg=msg)
        # check overflow, underflow
        msg = "Complex floor division overflow/underflow check"
        x = np.array([1.e+110, 1.e-110], dtype=np.complex128)
        y = np.floor_divide(x**2, x)
        assert_equal(y, [1.e+110, 0], err_msg=msg) 
Example 26
Project: recruit   Author: Frank-qlu   File: test_umath.py    License: Apache License 2.0 5 votes vote down vote up
def floor_divide_and_remainder(x, y):
    return (np.floor_divide(x, y), np.remainder(x, y)) 
Example 27
Project: recruit   Author: Frank-qlu   File: frequencies.py    License: Apache License 2.0 5 votes vote down vote up
def _is_business_daily(self):
        # quick check: cannot be business daily
        if self.day_deltas != [1, 3]:
            return False

        # probably business daily, but need to confirm
        first_weekday = self.index[0].weekday()
        shifts = np.diff(self.index.asi8)
        shifts = np.floor_divide(shifts, _ONE_DAY)
        weekdays = np.mod(first_weekday + np.cumsum(shifts), 7)
        return np.all(((weekdays == 0) & (shifts == 3)) |
                      ((weekdays > 0) & (weekdays <= 4) & (shifts == 1))) 
Example 28
Project: knmt   Author: fabiencro   File: utils.py    License: GNU General Public License v3.0 5 votes vote down vote up
def generate_pos_vectors(d_model, max_length):
    pos_component = np.arange(max_length, dtype = np.float32)
    dim_component = np.arange(d_model, dtype = np.float32)
    dim_component_even = np.floor_divide(dim_component, 2) * 2
    dim_factor = np.power(1e-4, dim_component_even / d_model)
    pos_dim = pos_component[:, None] * dim_factor[None, :]
    pos_dim[:, ::2] = np.sin(pos_dim[:, ::2])
    pos_dim[:, 1::2] = np.cos(pos_dim[:, 1::2])
    return pos_dim
    
########################################################################
# batch handling
# 
Example 29
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_umath.py    License: MIT License 5 votes vote down vote up
def test_floor_division_complex(self):
        # check that implementation is correct
        msg = "Complex floor division implementation check"
        x = np.array([.9 + 1j, -.1 + 1j, .9 + .5*1j, .9 + 2.*1j], dtype=np.complex128)
        y = np.array([0., -1., 0., 0.], dtype=np.complex128)
        assert_equal(np.floor_divide(x**2, x), y, err_msg=msg)
        # check overflow, underflow
        msg = "Complex floor division overflow/underflow check"
        x = np.array([1.e+110, 1.e-110], dtype=np.complex128)
        y = np.floor_divide(x**2, x)
        assert_equal(y, [1.e+110, 0], err_msg=msg) 
Example 30
Project: vnpy_crypto   Author: birforce   File: test_umath.py    License: MIT License 5 votes vote down vote up
def test_floor_division_complex(self):
        # check that implementation is correct
        msg = "Complex floor division implementation check"
        x = np.array([.9 + 1j, -.1 + 1j, .9 + .5*1j, .9 + 2.*1j], dtype=np.complex128)
        y = np.array([0., -1., 0., 0.], dtype=np.complex128)
        assert_equal(np.floor_divide(x**2, x), y, err_msg=msg)
        # check overflow, underflow
        msg = "Complex floor division overflow/underflow check"
        x = np.array([1.e+110, 1.e-110], dtype=np.complex128)
        y = np.floor_divide(x**2, x)
        assert_equal(y, [1.e+110, 0], err_msg=msg)