visbrain.objects.TimeFrequencyObj

class visbrain.objects.TimeFrequencyObj(name, data=None, sf=1.0, method='fourier', nperseg=256, f_min=1.0, f_max=160.0, f_step=1.0, baseline=None, norm=None, n_window=None, overlap=0.0, window=None, c_parameter=20, cmap='viridis', clim=None, vmin=None, under='gray', vmax=None, over='red', interpolation='nearest', max_pts=-1, parent=None, transform=None, verbose=None, **kw)

Compute the time-frequency map (or spectrogram).

The time-frequency decomposition can be assessed using :

• The fourier transform

• Morlet’s wavelet

• Multi-taper

Parameters

namestring | None

Name of the time-frequency object.

dataarray_like

Array of data of shape (N,)

sffloat | 1.

The sampling frequency.

method{‘fourier’, ‘wavelet’, ‘multitaper’}

The method to use to compute the time-frequency decomposition.

npersegint | 256

Length of each segment. Argument pass to the scipy.signal.spectrogram function (for ‘fourier’ and ‘multitaper’ method).

overlapfloat | 0.

Overlap between segments. Must be between 0. and 1.

f_minfloat | 1.

Minimum frequency (for ‘wavelet’ method).

f_maxfloat | 160.

Maximum frequency (for ‘wavelet’ method).

f_stepfloat | 2.

Frequency step between two consecutive frequencies (for ‘wavelet’ method).

baselinearray_like | None

Baseline period (for ‘wavelet’ method).

normint | None

The normalization type (for ‘wavelet’ method).. See the normalization function.

n_windowint | None

If this parameter is an integer, the time-frequency map is going to be averaged into smaller windows (for ‘wavelet’ method).

window{‘flat’, ‘hanning’, ‘hamming’, ‘bartlett’, ‘blackman’}

Windowing method for averaging. By default, ‘flat’ is used for Wavelet and ‘hamming’ for Fourier.

c_parameterint | 20

Parameter ‘c’ described in doi:10.1155/2011/980805 (for ‘multitaper’ method)

climtuple | None

Colorbar limits. If None, clim=(data.min(), data.max())

cmapstring | None

Colormap name.

vminfloat | None

Minimum threshold of the colorbar.

understring/tuple/array_like | None

Color for values under vmin.

vmaxfloat | None

Maximum threshold of the colorbar.

overstring/tuple/array_like | None

Color for values over vmax.

interpolationstring | ‘nearest’

Interpolation method for the image. See vispy.scene.visuals.Image for availables interpolation methods.

max_ptsint | -1

Maximum number of points of the image along the x or y axis. This parameter is essentially used to solve OpenGL issues with very large images.

transformVisPy.visuals.transforms | None

VisPy transformation to set to the parent node.

parentVisPy.parent | None

Markers object parent.

verbosestring

Verbosity level.

kwdict | {}

Optional arguments are used to control the colorbar (See ColorbarObj).

Notes

List of supported shortcuts :

• s : save the figure

• <delete> : reset camera

Examples

>>> import numpy as np
>>> from visbrain.objects import TimeFrequencyObj
>>> n, sf = 512, 256  # number of time-points and sampling frequency
>>> time = np.arange(n) / sf  # time vector
>>> data = np.sin(2 * np.pi * 25. * time) + np.random.rand(n)
>>> tf = TimeFrequencyObj('tf', data, sf)
>>> tf.preview(axis=True)

Methods

__init__(self, name[, data, sf, method, …])	Init.
animate(self[, step, interval, iterations])	Animate the object.
copy(self)	Get a copy of the object.
describe_tree(self)	Tree description.
preview(self[, bgcolor, axis, xyz, show, …])	Previsualize the result.
record_animation(self, name[, n_pic, bgcolor])	Record an animated object and save as a *.gif file.
render(self)	Render the canvas.
screenshot(self, saveas[, print_size, dpi, …])	Take a screeshot of the scene.
set_data(self, data[, sf, method, nperseg, …])	Compute TF and set data to the ImageObj.
set_shortcuts_to_canvas(self, canvas)	Set shortcuts to a VisbrainCanvas.
to_dict(self)	Return a dictionary of all colorbar args.
to_kwargs(self[, addisminmax])	Return a dictionary for input arguments.
update(self)	Fonction to run when an update is needed.
update_from_dict(self, kwargs)	Update attributes from a dictionary.

animate(self, step=1.0, interval='auto', iterations=-1)

Animate the object.

Note that this method can only be used with 3D objects.

Parameters

stepfloat | 1.

Rotation step.

intervalfloat | ‘auto’

Time between events in seconds. The default is ‘auto’, which attempts to find the interval that matches the refresh rate of the current monitor. Currently this is simply 1/60.

iterationsint | -1

Number of iterations. Can be -1 for infinite.

property clim

Get the clim value.

property cmap

Get the cmap value.

copy(self)

Get a copy of the object.

property data_folder

Get the data_folder value.

property interpolation

Get the interpolation value.

property name

Get the name value.

property over

Get the over value.

property parent

Get the parent value.

preview(self, bgcolor='black', axis=False, xyz=False, show=True, obj=None, size=(1200, 800), mpl=False, **kwargs)

Previsualize the result.

Parameters

bgcolorarray_like/string/tuple | ‘black’

Background color for the preview.

axisbool | False

Add x and y axis with ticks.

xyzbool | False

Add an (x, y, z) axis to the scene.

objVisbrainObj | None

Pass a Visbrain object if you want to use the camera of an other object.

sizetuple | (1200, 800)

Default size of the window.

mplbool | False

Use Matplotlib to display the object. This result in a non interactive figure.

kwargsdict | {}

Optional arguments are passed to the VisbrainCanvas class.

record_animation(self, name, n_pic=10, bgcolor=None)

Record an animated object and save as a *.gif file.

Note that this method :

• Can only be used with 3D objects.

• Requires the python package imageio

Parameters

namestring

Name of the gif file (e.g ‘myfile.gif’)

n_picint | 10

Number of pictures to use to render the gif.

bgcolorstring, tuple, list | None

Background color.

render(self)

Render the canvas.

Returns

imgarray_like

Array of shape (n_rows, n_columns, 4) where 4 describes the RGBA components.

screenshot(self, saveas, print_size=None, dpi=300.0, unit='centimeter', factor=None, region=None, autocrop=False, bgcolor=None, transparent=False, obj=None, line_width=1.0, **kwargs)

Take a screeshot of the scene.

By default, the rendered canvas will have the size of your screen. The screenshot() method provides two ways to increase to exported image resolution :

• Using print_size, unit and dpi inputs : specify the size of the image at a specific dpi level. For example, you might want to have an (10cm, 15cm) image at 300 dpi.

• Using the factor input : multiply the default image size by this factor. For example, if you have a (1920, 1080) monitor and if factor is 2, the exported image should have a shape of (3840, 2160) pixels.

Parameters

saveasstr

The name of the file to be saved. This file must contains a extension like .png, .tiff, .jpg…

print_sizetuple | None

The desired print size. This argument should be used in association with the dpi and unit inputs. print_size describe should be a tuple of two floats describing (width, height) of the exported image for a specific dpi level. The final image might not have the exact desired size but will try instead to find a compromize regarding to the proportion of width/height of the original image.

dpifloat | 300.

Dots per inch for printing the image.

unit{‘centimeter’, ‘millimeter’, ‘pixel’, ‘inch’}

Unit of the printed size.

factorfloat | None

If you don’t want to use the print_size input, factor simply multiply the resolution of your screen.

regiontuple | None

Select a specific region. Must be a tuple of four integers each one describing (x_start, y_start, width, height).

autocropbool | False

Automaticaly crop the figure in order to have the smallest space between the brain and the border of the picture.

bgcolorarray_like/string | None

The background color of the image.

transparentbool | False

Specify if the exported figure have to contains a transparent background.

objVisbrainObj | None

Pass a Visbrain object if you want to use the camera of an other object for the sceen rendering.

kwargsdict | {}

Optional arguments are passed to the VisbrainCanvas class.

set_data(self, data, sf=1.0, method='fourier', nperseg=256, f_min=1.0, f_max=160.0, f_step=1.0, baseline=None, norm=None, n_window=None, overlap=0.0, window=None, c_parameter=20, clim=None, cmap='viridis', vmin=None, under=None, vmax=None, over=None)

Compute TF and set data to the ImageObj.

property transform

Get the transform value.

property under

Get the under value.

property visible_obj

Get the visible_obj value.

property vmax

Get the vmax value.

property vmin

Get the vmin value.

Examples using visbrain.objects.TimeFrequencyObj

Image, time-frequency map and spectrogram objects