matplotlib.axes.Axes.psd

Axes.psd(self, x, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, *, data=None, **kwargs) [source]

Plot the power spectral density.

The power spectral density \(P_{xx}\) by Welch's average periodogram method. The vector x is divided into NFFT length segments. Each segment is detrended by function detrend and windowed by function window. noverlap gives the length of the overlap between segments. The \(|\mathrm{fft}(i)|^2\) of each segment \(i\) are averaged to compute \(P_{xx}\), with a scaling to correct for power loss due to windowing.

If len(x) < NFFT, it will be zero padded to NFFT.

Parameters:	x : 1-D array or sequence Array or sequence containing the data 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'} Specifies which sides of the spectrum to return. Default gives the default behavior, which returns one-sided for real data and both for complex data. 'onesided' forces the return of a one-sided spectrum, while 'twosided' forces two-sided. 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 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 Specifies 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. noverlap : int The number of points of overlap between segments. The default value is 0 (no overlap). Fc : int The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband. return_line : bool Whether to include the line object plotted in the returned values. Default is False.
Returns:	Pxx : 1-D array The values for the power spectrum P_{xx} before scaling (real valued). freqs : 1-D array The frequencies corresponding to the elements in Pxx. line : a Line2D instance The line created by this function. Only returned if return_line is True.
Other Parameters:	**kwargs Keyword arguments control the Line2D properties: Property Description agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alpha float animated bool antialiased or aa bool clip_box Bbox clip_on bool clip_path [(Path, Transform) | Patch | None] color or c color contains callable dash_capstyle {'butt', 'round', 'projecting'} dash_joinstyle {'miter', 'round', 'bevel'} dashes sequence of floats (on/off ink in points) or (None, None) drawstyle or ds {'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figure Figure fillstyle {'full', 'left', 'right', 'bottom', 'top', 'none'} gid str in_layout bool label object linestyle or ls {'-', '--', '-.', ':', '', (offset, on-off-seq), ...} linewidth or lw float marker marker style markeredgecolor or mec color markeredgewidth or mew float markerfacecolor or mfc color markerfacecoloralt or mfcalt color markersize or ms float markevery None or int or (int, int) or slice or List[int] or float or (float, float) path_effects AbstractPathEffect picker float or callable[[Artist, Event], Tuple[bool, dict]] pickradius float rasterized bool or None sketch_params (scale: float, length: float, randomness: float) snap bool or None solid_capstyle {'butt', 'round', 'projecting'} solid_joinstyle {'miter', 'round', 'bevel'} transform matplotlib.transforms.Transform url str visible bool xdata 1D array ydata 1D array zorder float

See also

specgram()

specgram() differs in the default overlap; in not returning the mean of the segment periodograms; in returning the times of the segments; and in plotting a colormap instead of a line.

magnitude_spectrum()

magnitude_spectrum() plots the magnitude spectrum.

csd()

csd() plots the spectral density between two signals.

Notes

For plotting, the power is plotted as \(10\log_{10}(P_{xx})\) for decibels, though Pxx itself is returned.

References

Bendat & Piersol -- Random Data: Analysis and Measurement Procedures, John Wiley & Sons (1986)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All arguments with the following names: 'x'.

Objects passed as data must support item access (data[<arg>]) and membership test (<arg> in data).