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Directly dedent the spectral parameter docs.
There's little point in sending them through inspect.cleandoc. Also list the defaults right next to the parameters.
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‎lib/matplotlib/mlab.py

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@@ -54,7 +54,6 @@
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"""
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import csv
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import inspect
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from numbers import Number
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import numpy as np
@@ -613,72 +612,62 @@ def _single_spectrum_helper(x, mode, Fs=None, window=None, pad_to=None,
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# Split out these keyword docs so that they can be used elsewhere
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docstring.interpd.update(Spectral=inspect.cleandoc("""
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Fs : scalar
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The sampling frequency (samples per time unit). It is used
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to calculate the Fourier frequencies, freqs, in cycles per time
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unit. The default value is 2.
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window : callable or ndarray
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A function or a vector of length *NFFT*. To create window vectors see
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`.window_hanning`, `.window_none`, `numpy.blackman`, `numpy.hamming`,
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`numpy.bartlett`, `scipy.signal`, `scipy.signal.get_window`, etc. The
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default is `.window_hanning`. If a function is passed as the argument,
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it must take a data segment as an argument and return the windowed
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version of the segment.
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sides : {'default', 'onesided', 'twosided'}
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Which sides of the spectrum to return. 'default' is one-sided for real
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data and two-sided for complex data. 'onesided' forces the return of a
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one-sided spectrum, while 'twosided' forces two-sided.
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"""))
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docstring.interpd.update(Single_Spectrum=inspect.cleandoc("""
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pad_to : int
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The number of points to which the data segment is padded when
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performing the FFT. While not increasing the actual resolution of
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the spectrum (the minimum distance between resolvable peaks),
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this can give more points in the plot, allowing for more
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detail. This corresponds to the *n* parameter in the call to fft().
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The default is None, which sets *pad_to* equal to the length of the
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input signal (i.e. no padding).
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"""))
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docstring.interpd.update(PSD=inspect.cleandoc("""
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pad_to : int
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The number of points to which the data segment is padded when
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performing the FFT. This can be different from *NFFT*, which
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specifies the number of data points used. While not increasing
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the actual resolution of the spectrum (the minimum distance between
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resolvable peaks), this can give more points in the plot,
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allowing for more detail. This corresponds to the *n* parameter
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in the call to fft(). The default is None, which sets *pad_to*
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equal to *NFFT*
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NFFT : int
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The number of data points used in each block for the FFT.
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A power 2 is most efficient. The default value is 256.
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This should *NOT* be used to get zero padding, or the scaling of the
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result will be incorrect. Use *pad_to* for this instead.
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detrend : {'none', 'mean', 'linear'} or callable, default 'none'
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The function applied to each segment before fft-ing, designed to
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remove the mean or linear trend. Unlike in MATLAB, where the
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*detrend* parameter is a vector, in Matplotlib is it a function.
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The :mod:`~matplotlib.mlab` module defines `.detrend_none`,
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`.detrend_mean`, and `.detrend_linear`, but you can use a custom
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function as well. You can also use a string to choose one of the
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functions: 'none' calls `.detrend_none`. 'mean' calls `.detrend_mean`.
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'linear' calls `.detrend_linear`.
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scale_by_freq : bool, optional
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Whether the resulting density values should be scaled by the scaling
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frequency, which gives density in units of Hz^-1. This allows for
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integration over the returned frequency values. The default is True
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for MATLAB compatibility.
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"""))
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docstring.interpd.update(
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Spectral="""\
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Fs : scalar, default: 2
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The sampling frequency (samples per time unit). It is used to calculate
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the Fourier frequencies, *freqs*, in cycles per time unit.
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window : callable or ndarray, default: `.window_hanning`
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A function or a vector of length *NFFT*. To create window vectors see
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`.window_hanning`, `.window_none`, `numpy.blackman`, `numpy.hamming`,
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`numpy.bartlett`, `scipy.signal`, `scipy.signal.get_window`, etc. If a
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function is passed as the argument, it must take a data segment as an
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argument and return the windowed version of the segment.
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sides : {'default', 'onesided', 'twosided'}, optional
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Which sides of the spectrum to return. 'default' is one-sided for real
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data and two-sided for complex data. 'onesided' forces the return of a
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one-sided spectrum, while 'twosided' forces two-sided.""",
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Single_Spectrum="""\
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pad_to : int, optional
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The number of points to which the data segment is padded when performing
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the FFT. While not increasing the actual resolution of the spectrum (the
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minimum distance between resolvable peaks), this can give more points in
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the plot, allowing for more detail. This corresponds to the *n* parameter
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in the call to fft(). The default is None, which sets *pad_to* equal to
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the length of the input signal (i.e. no padding).""",
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PSD="""\
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pad_to : int, optional
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The number of points to which the data segment is padded when performing
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the FFT. This can be different from *NFFT*, which specifies the number
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of data points used. While not increasing the actual resolution of the
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spectrum (the minimum distance between resolvable peaks), this can give
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more points in the plot, allowing for more detail. This corresponds to
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the *n* parameter in the call to fft(). The default is None, which sets
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*pad_to* equal to *NFFT*
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NFFT : int, default: 256
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The number of data points used in each block for the FFT. A power 2 is
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most efficient. This should *NOT* be used to get zero padding, or the
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scaling of the result will be incorrect; use *pad_to* for this instead.
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detrend : {'none', 'mean', 'linear'} or callable, default 'none'
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The function applied to each segment before fft-ing, designed to remove
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the mean or linear trend. Unlike in MATLAB, where the *detrend* parameter
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is a vector, in Matplotlib is it a function. The :mod:`~matplotlib.mlab`
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module defines `.detrend_none`, `.detrend_mean`, and `.detrend_linear`,
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but you can use a custom function as well. You can also use a string to
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choose one of the functions: 'none' calls `.detrend_none`. 'mean' calls
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`.detrend_mean`. 'linear' calls `.detrend_linear`.
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scale_by_freq : bool, optional, default: True
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Whether the resulting density values should be scaled by the scaling
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frequency, which gives density in units of Hz^-1. This allows for
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integration over the returned frequency values. The default is True for
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MATLAB compatibility.""")
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@docstring.dedent_interpd

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