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-rw-r--r--numpy/lib/function_base.py71
1 files changed, 19 insertions, 52 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 95edb95fa..9a680dd55 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -27,6 +27,7 @@ from numpy.core.fromnumeric import (
ravel, nonzero, sort, partition, mean, any, sum
)
from numpy.core.numerictypes import typecodes, number
+from numpy.core.function_base import add_newdoc
from numpy.lib.twodim_base import diag
from .utils import deprecate
from numpy.core.multiarray import (
@@ -1649,7 +1650,7 @@ def disp(mesg, device=None, linefeed=True):
return
-# See http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html
+# See https://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html
_DIMENSION_NAME = r'\w+'
_CORE_DIMENSION_LIST = '(?:{0:}(?:,{0:})*)?'.format(_DIMENSION_NAME)
_ARGUMENT = r'\({}\)'.format(_CORE_DIMENSION_LIST)
@@ -1906,7 +1907,7 @@ class vectorize(object):
References
----------
.. [1] NumPy Reference, section `Generalized Universal Function API
- <http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html>`_.
+ <https://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html>`_.
"""
def __init__(self, pyfunc, otypes=None, doc=None, excluded=None,
@@ -2561,7 +2562,7 @@ def bartlett(M):
.. [3] A.V. Oppenheim and R.W. Schafer, "Discrete-Time Signal
Processing", Prentice-Hall, 1999, pp. 468-471.
.. [4] Wikipedia, "Window function",
- http://en.wikipedia.org/wiki/Window_function
+ https://en.wikipedia.org/wiki/Window_function
.. [5] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
"Numerical Recipes", Cambridge University Press, 1986, page 429.
@@ -2661,7 +2662,7 @@ def hanning(M):
.. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics",
The University of Alberta Press, 1975, pp. 106-108.
.. [3] Wikipedia, "Window function",
- http://en.wikipedia.org/wiki/Window_function
+ https://en.wikipedia.org/wiki/Window_function
.. [4] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
"Numerical Recipes", Cambridge University Press, 1986, page 425.
@@ -2759,7 +2760,7 @@ def hamming(M):
.. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The
University of Alberta Press, 1975, pp. 109-110.
.. [3] Wikipedia, "Window function",
- http://en.wikipedia.org/wiki/Window_function
+ https://en.wikipedia.org/wiki/Window_function
.. [4] W.H. Press, B.P. Flannery, S.A. Teukolsky, and W.T. Vetterling,
"Numerical Recipes", Cambridge University Press, 1986, page 425.
@@ -3036,7 +3037,7 @@ def kaiser(M, beta):
.. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The
University of Alberta Press, 1975, pp. 177-178.
.. [3] Wikipedia, "Window function",
- http://en.wikipedia.org/wiki/Window_function
+ https://en.wikipedia.org/wiki/Window_function
Examples
--------
@@ -3124,7 +3125,7 @@ def sinc(x):
.. [1] Weisstein, Eric W. "Sinc Function." From MathWorld--A Wolfram Web
Resource. http://mathworld.wolfram.com/SincFunction.html
.. [2] Wikipedia, "Sinc function",
- http://en.wikipedia.org/wiki/Sinc_function
+ https://en.wikipedia.org/wiki/Sinc_function
Examples
--------
@@ -3398,9 +3399,9 @@ def _median(a, axis=None, out=None, overwrite_input=False):
def percentile(a, q, axis=None, out=None,
overwrite_input=False, interpolation='linear', keepdims=False):
"""
- Compute the qth percentile of the data along the specified axis.
+ Compute the q-th percentile of the data along the specified axis.
- Returns the qth percentile(s) of the array elements.
+ Returns the q-th percentile(s) of the array elements.
Parameters
----------
@@ -3467,7 +3468,7 @@ def percentile(a, q, axis=None, out=None,
Notes
-----
- Given a vector ``V`` of length ``N``, the ``q``-th percentile of
+ Given a vector ``V`` of length ``N``, the q-th percentile of
``V`` is the value ``q/100`` of the way from the minimum to the
maximum in a sorted copy of ``V``. The values and distances of
the two nearest neighbors as well as the `interpolation` parameter
@@ -3543,7 +3544,7 @@ def percentile(a, q, axis=None, out=None,
def quantile(a, q, axis=None, out=None,
overwrite_input=False, interpolation='linear', keepdims=False):
"""
- Compute the `q`th quantile of the data along the specified axis.
+ Compute the q-th quantile of the data along the specified axis.
..versionadded:: 1.15.0
Parameters
@@ -3569,6 +3570,7 @@ def quantile(a, q, axis=None, out=None,
This optional parameter specifies the interpolation method to
use when the desired quantile lies between two data points
``i < j``:
+
* linear: ``i + (j - i) * fraction``, where ``fraction``
is the fractional part of the index surrounded by ``i``
and ``j``.
@@ -3602,7 +3604,7 @@ def quantile(a, q, axis=None, out=None,
Notes
-----
- Given a vector ``V`` of length ``N``, the ``q``-th quantile of
+ Given a vector ``V`` of length ``N``, the q-th quantile of
``V`` is the value ``q`` of the way from the minimum to the
maximum in a sorted copy of ``V``. The values and distances of
the two nearest neighbors as well as the `interpolation` parameter
@@ -3720,7 +3722,7 @@ def _quantile_ureduce_func(a, q, axis=None, out=None, overwrite_input=False,
indices = concatenate((indices, [-1]))
ap.partition(indices, axis=axis)
- # ensure axis with qth is first
+ # ensure axis with q-th is first
ap = np.moveaxis(ap, axis, 0)
axis = 0
@@ -3753,7 +3755,7 @@ def _quantile_ureduce_func(a, q, axis=None, out=None, overwrite_input=False,
ap.partition(concatenate((indices_below, indices_above)), axis=axis)
- # ensure axis with qth is first
+ # ensure axis with q-th is first
ap = np.moveaxis(ap, axis, 0)
weights_below = np.moveaxis(weights_below, axis, 0)
weights_above = np.moveaxis(weights_above, axis, 0)
@@ -3767,7 +3769,7 @@ def _quantile_ureduce_func(a, q, axis=None, out=None, overwrite_input=False,
x1 = take(ap, indices_below, axis=axis) * weights_below
x2 = take(ap, indices_above, axis=axis) * weights_above
- # ensure axis with qth is first
+ # ensure axis with q-th is first
x1 = np.moveaxis(x1, axis, 0)
x2 = np.moveaxis(x2, axis, 0)
@@ -3840,10 +3842,10 @@ def trapz(y, x=None, dx=1.0, axis=-1):
References
----------
- .. [1] Wikipedia page: http://en.wikipedia.org/wiki/Trapezoidal_rule
+ .. [1] Wikipedia page: https://en.wikipedia.org/wiki/Trapezoidal_rule
.. [2] Illustration image:
- http://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png
+ https://en.wikipedia.org/wiki/File:Composite_trapezoidal_rule_illustration.png
Examples
--------
@@ -3891,41 +3893,6 @@ def trapz(y, x=None, dx=1.0, axis=-1):
return ret
-#always succeed
-def add_newdoc(place, obj, doc):
- """
- Adds documentation to obj which is in module place.
-
- If doc is a string add it to obj as a docstring
-
- If doc is a tuple, then the first element is interpreted as
- an attribute of obj and the second as the docstring
- (method, docstring)
-
- If doc is a list, then each element of the list should be a
- sequence of length two --> [(method1, docstring1),
- (method2, docstring2), ...]
-
- This routine never raises an error.
-
- This routine cannot modify read-only docstrings, as appear
- in new-style classes or built-in functions. Because this
- routine never raises an error the caller must check manually
- that the docstrings were changed.
- """
- try:
- new = getattr(__import__(place, globals(), {}, [obj]), obj)
- if isinstance(doc, str):
- add_docstring(new, doc.strip())
- elif isinstance(doc, tuple):
- add_docstring(getattr(new, doc[0]), doc[1].strip())
- elif isinstance(doc, list):
- for val in doc:
- add_docstring(getattr(new, val[0]), val[1].strip())
- except Exception:
- pass
-
-
# Based on scitools meshgrid
def meshgrid(*xi, **kwargs):
"""