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matplotlib.axes.Axes.csd
- Axes.- csd(x, y, 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 cross-spectral density. The cross spectral density \(P_{xy}\) by Welch's average periodogram method. The vectors x and y are 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 product of the direct FFTs of x and y are averaged over each segment to compute \(P_{xy}\), with a scaling to correct for power loss due to windowing. If len(x) < NFFT or len(y) < NFFT, they will be zero padded to NFFT. Parameters: - x, y1-D arrays or sequences
- 
           Arrays or sequences containing the data. 
- Fsfloat, default: 2
- 
           The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit. 
- 
           windowcallable 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. 
- pad_toint, 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 
- NFFTint, 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 mlabmodule definesdetrend_none,detrend_mean, anddetrend_linear, but you can use a custom function as well. You can also use a string to choose one of the functions: 'none' callsdetrend_none. 'mean' callsdetrend_mean. 'linear' callsdetrend_linear.
- scale_by_freqbool, 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. 
- noverlapint, default: 0 (no overlap)
- 
           The number of points of overlap between segments. 
- Fcint, default: 0
- 
           The center frequency of x, 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_linebool, default: False
- 
           Whether to include the line object plotted in the returned values. 
 Returns: - Pxy1-D array
- 
           The values for the cross spectrum \(P_{xy}\) before scaling (complex valued). 
- freqs1-D array
- 
           The frequencies corresponding to the elements in Pxy. 
- 
           lineLine2D
- 
           The line created by this function. Only returned if return_line is True. 
 Other Parameters: - **kwargs
- 
           Keyword arguments control the Line2Dproperties:Property Description agg_filtera filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array alphascalar or None animatedbool antialiasedor aabool clip_boxBboxclip_onbool clip_pathPatch or (Path, Transform) or None coloror ccolor containsunknown dash_capstyleCapStyleor {'butt', 'projecting', 'round'}dash_joinstyleJoinStyleor {'miter', 'round', 'bevel'}dashessequence of floats (on/off ink in points) or (None, None) data(2, N) array or two 1D arrays drawstyleor ds{'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}, default: 'default' figureFigurefillstyle{'full', 'left', 'right', 'bottom', 'top', 'none'} gidstr in_layoutbool labelobject linestyleor ls{'-', '--', '-.', ':', '', (offset, on-off-seq), ...} linewidthor lwfloat markermarker style string, PathorMarkerStylemarkeredgecoloror meccolor markeredgewidthor mewfloat markerfacecoloror mfccolor markerfacecoloraltor mfcaltcolor markersizeor msfloat markeveryNone or int or (int, int) or slice or list[int] or float or (float, float) or list[bool] path_effectsAbstractPathEffectpickerfloat or callable[[Artist, Event], tuple[bool, dict]] pickradiusfloat rasterizedbool sketch_params(scale: float, length: float, randomness: float) snapbool or None solid_capstyleCapStyleor {'butt', 'projecting', 'round'}solid_joinstyleJoinStyleor {'miter', 'round', 'bevel'}transformmatplotlib.transforms.Transformurlstr visiblebool xdata1D array ydata1D array zorderfloat 
 See also - 
       psd
- 
       is equivalent to setting y = x.
 NotesFor plotting, the power is plotted as \(10 \log_{10}(P_{xy})\) for decibels, though \(P_{xy}\) itself is returned. ReferencesBendat & 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 can also be string s, which is interpreted asdata[s](unless this raises an exception): x, y.Objects passed as data must support item access ( data[s]) and membership test (s in data).
Examples using matplotlib.axes.Axes.csd
  
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