8000 ENH: Add the 'heaviside' ufunc. · numpy/numpy@bf83345 · GitHub
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ENH: Add the 'heaviside' ufunc.
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‎doc/release/1.13.0-notes.rst‎

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@@ -121,6 +121,16 @@ This means that, e.g., it is now possible to do the following:
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[array([[ 1. , 1. , -0.5], [ 1. , 1. , -0.5]]),
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array([[ 2. , 2. , 2. ], [ 2. , 1.7, 0.5]])]
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``np.heaviside`` computes the Heaviside function
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------------------------------------------------
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The new function ``np.heaviside(x, h0)`` (a ufunc) computes the Heaviside
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function::
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{ 0 if x < 0,
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heaviside(x, h0) = { h0 if x == 0,
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{ 1 if x > 0.
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Improvements
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============
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‎numpy/core/code_generators/generate_umath.py‎

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@@ -550,6 +550,12 @@ def english_upper(s):
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TD(ints, simd=[('avx2', ints)]),
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TD(O, f='PyNumber_Rshift'),
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),
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'heaviside':
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Ufunc(2, 1, None,
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docstrings.get('numpy.core.umath.heaviside'),
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None,
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TD(flts, f='heaviside', astype={'e':'f'}),
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),
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'degrees':
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Ufunc(1, 1, None,
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docstrings.get('numpy.core.umath.degrees'),

‎numpy/core/code_generators/ufunc_docstrings.py‎

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@@ -915,6 +915,50 @@ def add_newdoc(place, name, doc):
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""")
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add_newdoc('numpy.core.umath', 'heaviside',
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"""
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Compute the Heaviside step function.
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The Heaviside step function is defined as::
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0 if x < 0
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heaviside(x, h0) = h0 if x == 0
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1 if x > 0
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where `h0` is often taken to be 0.5, but 0 and 1 are also sometimes used.
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Parameters
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----------
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x : array_like
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Input values.
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h0 : array_like
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The value of the function at x = 0.
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out : ndarray, optional
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Array into which the output is placed. Its type is preserved and it
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must be of the right shape to hold the output. See doc.ufuncs.
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Returns
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-------
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out : ndarray
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The output array, element-wise Heaviside step function of `x`.
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Notes
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-----
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.. versionadded:: 1.13.0
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References
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----------
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.. Wikipedia, "Heaviside step function",
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https://en.wikipedia.org/wiki/Heaviside_step_function
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Examples
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--------
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>>> np.heaviside([-1.5, 0, 2.0], 0.5)
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array([ 0. , 0.5, 1. ])
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>>> np.heaviside([-1.5, 0, 2.0], 1)
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array([ 0., 1., 1.])
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""")
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add_newdoc('numpy.core.umath', 'divide',
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"""
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Divide arguments element-wise.

‎numpy/core/include/numpy/npy_math.h‎

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@@ -316,19 +316,22 @@ NPY_INPLACE double npy_rad2deg(double x);
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NPY_INPLACE double npy_logaddexp(double x, double y);
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NPY_INPLACE double npy_logaddexp2(double x, double y);
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NPY_INPLACE double npy_divmod(double x, double y, double *modulus);
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NPY_INPLACE double npy_heaviside(double x, double h0);
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NPY_INPLACE float npy_deg2radf(float x);
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NPY_INPLACE float npy_rad2degf(float x);
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NPY_INPLACE float npy_logaddexpf(float x, float y);
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NPY_INPLACE float npy_logaddexp2f(float x, float y);
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NPY_INPLACE float npy_divmodf(float x, float y, float *modulus);
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NPY_INPLACE float npy_heavisidef(float x, float h0);
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NPY_INPLACE npy_longdouble npy_deg2radl(npy_longdouble x);
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NPY_INPLACE npy_longdouble npy_rad2degl(npy_longdouble x);
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NPY_INPLACE npy_longdouble npy_logaddexpl(npy_longdouble x, npy_longdouble y);
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NPY_INPLACE npy_longdouble npy_logaddexp2l(npy_longdouble x, npy_longdouble y);
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NPY_INPLACE npy_longdouble npy_divmodl(npy_longdouble x, npy_longdouble y,
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npy_longdouble *modulus);
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NPY_INPLACE npy_longdouble npy_heavisidel(npy_longdouble x, npy_longdouble h0);
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#define npy_degrees npy_rad2deg
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#define npy_degreesf npy_rad2degf

‎numpy/core/src/npymath/npy_math_internal.h.src‎

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@@ -541,6 +541,22 @@ NPY_INPLACE @type@ npy_cbrt@c@(@type@ x)
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* #C = F, ,L#
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*/
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@type@ npy_heaviside@c@(@type@ x, @type@ h0)
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{
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if (npy_isnan(x)) {
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return (@type@) NPY_NAN;
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}
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else if (x == 0) {
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return h0;
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}
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else if (x < 0) {
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return (@type@) 0.0;
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}
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else {
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return (@type@) 1.0;
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}
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}
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#define LOGE2 NPY_LOGE2@c@
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#define LOG2E NPY_LOG2E@c@
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#define RAD2DEG (180.0@c@/NPY_PI@c@)

‎numpy/core/tests/test_umath.py‎

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@@ -1197,6 +1197,28 @@ def test_radians(self):
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assert_almost_equal(ncu.radians(-90.0), -0.5*np.pi)
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class TestHeavside(TestCase):
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def test_heaviside(self):
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x = np.array([[-30.0, -0.1, 0.0, 0.2], [7.5, np.nan, np.inf, -np.inf]])
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expectedhalf = np.array([[0.0, 0.0, 0.5, 1.0], [1.0, np.nan, 1.0, 0.0]])
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expected1 = expectedhalf.copy()
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expected1[0, 2] = 1
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h = ncu.heaviside(x, 0.5)
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assert_equal(h, expectedhalf)
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h = ncu.heaviside(x, 1.0)
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assert_equal(h, expected1)
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x = x.astype(np.float32)
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h = ncu.heaviside(x, np.float32(0.5))
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assert_equal(h, expectedhalf.astype(np.float32))
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h = ncu.heaviside(x, np.float32(1.0))
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assert_equal(h, expected1.astype(np.float32))
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class TestSign(TestCase):
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def test_sign(self):
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a = np.array([np.inf, -np.inf, np.nan, 0.0, 3.0, -3.0])

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