Merge pull request matplotlib#15772 from anntzer/spectral-cleandocs

Directly dedent the spectral parameter docs.

Author: timhoffm

lib/matplotlib/mlab.py

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