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)[source][source]¶

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)[source]¶

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.

clim¶: Get the clim value.

cmap¶: Get the cmap value.

copy(self)[source]¶: Get a copy of the object.

data_folder¶: Get the data_folder value.

interpolation¶: Get the interpolation value.

name¶: Get the name value.

over¶: Get the over value.

parent¶: Get the parent value.

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

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)[source]¶

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)[source]¶

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)[source]¶

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)[source][source]¶: Compute TF and set data to the ImageObj.

transform¶: Get the transform value.

under¶: Get the under value.

visible_obj¶: Get the visible_obj value.

vmax¶: Get the vmax value.

vmin¶: Get the vmin value.

Examples using `visbrain.objects.TimeFrequencyObj`¶

Image, time-frequency map and spectrogram objects¶

visbrain.objects.TimeFrequencyObj¶

Examples using visbrain.objects.TimeFrequencyObj¶

Examples using `visbrain.objects.TimeFrequencyObj`¶