matplotlib.axes.Axes.phase_spectrum

Axes.phase_spectrum(x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, *, data=None, **kwargs) [source]

Plot the phase spectrum.

Call signature:

phase_spectrum(x, Fs=2, Fc=0,  window=mlab.window_hanning,
               pad_to=None, sides='default', **kwargs)

Compute the phase spectrum (unwrapped angle spectrum) of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.

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. 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).
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.

Returns:

spectrum : 1-D array: The values for the phase spectrum in radians (real valued).
freqs : 1-D array: The frequencies corresponding to the elements in spectrum.
line : a Line2D instance: The line created by this function.

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`	bool
`clip_box`	`Bbox`
`clip_on`	bool
`clip_path`	[(`Path`, `Transform`) \| `Patch` \| None]
`color`	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`	{'default', 'steps', 'steps-pre', 'steps-mid', 'steps-post'}
`figure`	`Figure`
`fillstyle`	{'full', 'left', 'right', 'bottom', 'top', 'none'}
`gid`	str
`in_layout`	bool
`label`	object
`linestyle`	{'-', '--', '-.', ':', '', (offset, on-off-seq), ...}
`linewidth`	float
`marker`	unknown
`markeredgecolor`	color
`markeredgewidth`	float
`markerfacecolor`	color
`markerfacecoloralt`	color
`markersize`	float
`markevery`	unknown
`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

Notes

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).