update docstring and change order

Author: vtavana

dpnp/dpnp_iface_window.py

@@ -81,15 +81,15 @@ def _call_window_kernel(
     return result
 
 
-def blackman(M, device=None, usm_type=None, sycl_queue=None):
+def bartlett(M, device=None, usm_type=None, sycl_queue=None):
     r"""
-    Return the Blackman window.
+    Return the Bartlett window.
 
-    The Blackman window is a taper formed by using the first three terms of a
-    summation of cosines. It was designed to have close to the minimal leakage
-    possible. It is close to optimal, only slightly worse than a Kaiser window.
+    The Bartlett window is very similar to a triangular window, except that the
+    end points are at zero. It is often used in signal processing for tapering
+    a signal, without generating too much ripple in the frequency domain.
 
-    For full documentation refer to :obj:`numpy.blackman`.
+    For full documentation refer to :obj:`numpy.bartlett`.
 
     Parameters
     ----------
@@ -120,69 +120,70 @@ def blackman(M, device=None, usm_type=None, sycl_queue=None):
     Returns
     -------
     out : dpnp.ndarray of shape (M,)
-        The window, with the maximum value normalized to one (the value one
-        appears only if the number of samples is odd).
+        The triangular window, with the maximum value normalized to one
+        (the value one appears only if the number of samples is odd), with the
+        first and last samples equal to zero.
 
     See Also
     --------
-    :obj:`dpnp.bartlett` : Return the Bartlett window.
+    :obj:`dpnp.blackman` : Return the Blackman window.
     :obj:`dpnp.hamming` : Return the Hamming window.
     :obj:`dpnp.hanning` : Return the Hanning window.
     :obj:`dpnp.kaiser` : Return the Kaiser window.
 
     Notes
     -----
-    The Blackman window is defined as
+    The Bartlett window is defined as
 
-    .. math::  w(n) = 0.42 - 0.5\cos\left(\frac{2\pi{n}}{M-1}\right)
-               + 0.08\cos\left(\frac{4\pi{n}}{M-1}\right)
+    .. math::  w(n) = \frac{2}{M-1} \left(\frac{M-1}{2} -
+               \left|n - \frac{M-1}{2}\right|\right)
                \qquad 0 \leq n \leq M-1
 
     Examples
     --------
     >>> import dpnp as np
-    >>> np.blackman(12)
-    array([-1.38777878e-17,  3.26064346e-02,  1.59903635e-01,  4.14397981e-01,
-            7.36045180e-01,  9.67046769e-01,  9.67046769e-01,  7.36045180e-01,
-            4.14397981e-01,  1.59903635e-01,  3.26064346e-02, -1.38777878e-17])
+    >>> np.bartlett(12)
+    array([0.        , 0.18181818, 0.36363636, 0.54545455, 0.72727273,
+        0.90909091, 0.90909091, 0.72727273, 0.54545455, 0.36363636,
+        0.18181818, 0.        ])
 
     Creating the output array on a different device or with a
     specified usm_type:
 
-    >>> x = np.blackman(3) # default case
+    >>> x = np.bartlett(4) # default case
     >>> x, x.device, x.usm_type
-    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
+    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
      Device(level_zero:gpu:0),
      'device')
 
-    >>> y = np.blackman(3, device="cpu")
+    >>> y = np.bartlett(4, device="cpu")
     >>> y, y.device, y.usm_type
-    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
+    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
      Device(opencl:cpu:0),
      'device')
 
-    >>> z = np.blackman(3, usm_type="host")
+    >>> z = np.bartlett(4, usm_type="host")
     >>> z, z.device, z.usm_type
-    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
+    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
      Device(level_zero:gpu:0),
      'host')
 
     """
 
     return _call_window_kernel(
-        M, wi._blackman, device=device, usm_type=usm_type, sycl_queue=sycl_queue
+        M, wi._bartlett, device=device, usm_type=usm_type, sycl_queue=sycl_queue
     )
 
 
-def bartlett(M, device=None, usm_type=None, sycl_queue=None):
+def blackman(M, device=None, usm_type=None, sycl_queue=None):
     r"""
-    Return the Bartlett window.
+    Return the Blackman window.
 
-    The Bartlett window is very similar to a triangular window, except that the
-    end points are at zero. It is often used in signal processing for tapering
-    a signal, without generating too much ripple in the frequency domain.
+    The Blackman window is a taper formed by using the first three terms of a
+    summation of cosines. It was designed to have close to the minimal leakage
+    possible. It is close to optimal, only slightly worse than a Kaiser window.
 
-    For full documentation refer to :obj:`numpy.bartlett`.
+    For full documentation refer to :obj:`numpy.blackman`.
 
     Parameters
     ----------
@@ -213,57 +214,57 @@ def bartlett(M, device=None, usm_type=None, sycl_queue=None):
     Returns
     -------
     out : dpnp.ndarray of shape (M,)
-        The triangular window, with the maximum value normalized to one
-        (the value one appears only if the number of samples is odd), with the
-        first and last samples equal to zero.
+        The window, with the maximum value normalized to one (the value one
+        appears only if the number of samples is odd).
 
     See Also
     --------
-    :obj:`dpnp.blackman` : Return the Blackman window.
+    :obj:`dpnp.bartlett` : Return the Bartlett window.
     :obj:`dpnp.hamming` : Return the Hamming window.
     :obj:`dpnp.hanning` : Return the Hanning window.
     :obj:`dpnp.kaiser` : Return the Kaiser window.
 
     Notes
     -----
-    The Bartlett window is defined as
+    The Blackman window is defined as
 
-    .. math::  w(n) = \frac{2}{M-1} \left(\frac{M-1}{2} -
-               \left|n - \frac{M-1}{2}\right|\right)
+    .. math::  w(n) = 0.42 - 0.5\cos\left(\frac{2\pi{n}}{M-1}\right)
+               + 0.08\cos\left(\frac{4\pi{n}}{M-1}\right)
+               \qquad 0 \leq n \leq M-1
 
     Examples
     --------
     >>> import dpnp as np
-    >>> np.bartlett(12)
-    array([0.        , 0.18181818, 0.36363636, 0.54545455, 0.72727273,
-        0.90909091, 0.90909091, 0.72727273, 0.54545455, 0.36363636,
-        0.18181818, 0.        ])
+    >>> np.blackman(12)
+    array([-1.38777878e-17,  3.26064346e-02,  1.59903635e-01,  4.14397981e-01,
+            7.36045180e-01,  9.67046769e-01,  9.67046769e-01,  7.36045180e-01,
+            4.14397981e-01,  1.59903635e-01,  3.26064346e-02, -1.38777878e-17])
 
     Creating the output array on a different device or with a
     specified usm_type:
 
-    >>> x = np.bartlett(4) # default case
+    >>> x = np.blackman(3) # default case
     >>> x, x.device, x.usm_type
-    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
+    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
      Device(level_zero:gpu:0),
      'device')
 
-    >>> y = np.bartlett(4, device="cpu")
+    >>> y = np.blackman(3, device="cpu")
     >>> y, y.device, y.usm_type
-    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
+    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
      Device(opencl:cpu:0),
      'device')
 
-    >>> z = np.bartlett(4, usm_type="host")
+    >>> z = np.blackman(3, usm_type="host")
     >>> z, z.device, z.usm_type
-    (array([0.        , 0.66666667, 0.66666667, 0.        ]),
+    (array([-1.38777878e-17,  1.00000000e+00, -1.38777878e-17]),
      Device(level_zero:gpu:0),
      'host')
 
     """
 
     return _call_window_kernel(
-        M, wi._bartlett, device=device, usm_type=usm_type, sycl_queue=sycl_queue
+        M, wi._blackman, device=device, usm_type=usm_type, sycl_queue=sycl_queue
     )