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DOC: More single to double backticks (#31524)
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Lines changed: 12 additions & 12 deletions

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numpy/__config__.py.in

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@@ -122,15 +122,15 @@ def show(mode=DisplayModes.stdout.value):
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Parameters
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----------
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mode : {`'stdout'`, `'dicts'`}, optional.
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mode : {'stdout', 'dicts'}, optional.
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Indicates how to display the config information.
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`'stdout'` prints to console, `'dicts'` returns a dictionary
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``'stdout'`` prints to console, ``'dicts'`` returns a dictionary
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of the configuration.
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Returns
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-------
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out : {`dict`, `None`}
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If mode is `'dicts'`, a dict is returned, else None
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out : {dict, None}
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If mode is ``'dicts'``, a dict is returned, else None
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See Also
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--------
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Notes
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-----
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1. The `'stdout'` mode will give more readable
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1. The ``'stdout'`` mode will give more readable
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output if ``pyyaml`` is installed
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"""

numpy/f2py/symbolic.py

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@@ -1319,10 +1319,10 @@ def process(self, s, context='expr'):
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"""Parse string within the given context.
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The context may define the result in case of ambiguous
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expressions. For instance, consider expressions `f(x, y)` and
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`(x, y) + (a, b)` where `f` is a function and pair `(x, y)`
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expressions. For instance, consider expressions ``f(x, y)`` and
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``(x, y) + (a, b)`` where ``f`` is a function and pair ``(x, y)``
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denotes complex number. Specifying context as "args" or
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"expr", the subexpression `(x, y)` will be parse to an
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"expr", the subexpression ``(x, y)`` will be parse to an
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argument list or to a complex number, respectively.
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"""
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if isinstance(s, (list, tuple)):

numpy/fft/_helper.py

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@@ -127,7 +127,7 @@ def fftfreq(n, d=1.0, device=None):
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"""
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Return the Discrete Fourier Transform sample frequencies.
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The returned float array `f` contains the frequency bin centers in cycles
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The returned float array ``f`` contains the frequency bin centers in cycles
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per unit of the sample spacing (with zero at the start). For instance, if
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the sample spacing is in seconds, then the frequency unit is cycles/second.
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@@ -183,7 +183,7 @@ def rfftfreq(n, d=1.0, device=None):
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Return the Discrete Fourier Transform sample frequencies
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(for usage with rfft, irfft).
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The returned float array `f` contains the frequency bin centers in cycles
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The returned float array ``f`` contains the frequency bin centers in cycles
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per unit of the sample spacing (with zero at the start). For instance, if
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the sample spacing is in seconds, then the frequency unit is cycles/second.
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numpy/fft/_pocketfft.py

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@@ -494,7 +494,7 @@ def irfft(a, n=None, axis=-1, norm=None, out=None):
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If you specify an `n` such that `a` must be zero-padded or truncated, the
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extra/removed values will be added/removed at high frequencies. One can
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thus resample a series to `m` points via Fourier interpolation by:
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thus resample a series to ``m`` points via Fourier interpolation by:
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``a_resamp = irfft(rfft(a), m)``.
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The correct interpretation of the hermitian input depends on the length of
@@ -1520,7 +1520,7 @@ def irfftn(a, s=None, axes=None, norm=None, out=None):
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axes : sequence of ints, optional
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Axes over which to compute the inverse FFT. If not given, the last
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`len(s)` axes are used, or all axes if `s` is also not specified.
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``len(s)`` axes are used, or all axes if `s` is also not specified.
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Repeated indices in `axes` means that the inverse transform over that
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axis is performed multiple times.
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