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.
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.
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.
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
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.
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
.
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.
The number of points of overlap between blocks. The default value is 0 (no overlap).
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.
The coherence vector.
The frequencies for the elements in Cxy.
Keyword arguments control the Line2D
properties:
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
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