visbrain.objects.TimeSeries3DObj¶

class visbrain.objects.TimeSeries3DObj(name, data, xyz, select=None, line_width=1.5, color='white', ts_amp=6.0, ts_width=20.0, alpha=1.0, antialias=False, translate=(0.0, 0.0, 1.0), transform=None, parent=None, verbose=None, _z=-10.0, **kw)[source][source]¶

Create a 3-D time-series object.

Parameters:

namestring: Name of the time-series object.
dataarray_like: Array of time-series of shape (n_sources, n_time_points)
xyzarray_like: The 3-D center location of each time-series of shape (n_sources, 3).
selectarray_like | None: Select the time-series to display. Should be a vector of bolean values of shape (n_sources,).
line_widthfloat | 1.5: Time-series’ line width.
colorarray_like/tuple/string | ‘white’: Time-series’ color.
ts_ampfloat | 6.: Graphical amplitude of the time-series.
ts_widthfloat | 20.: Graphical width of the time-series.
alphafloat | 1.: Time-series transparency.
antialiasbool | False: Use smooth lines.
translatetuple | (0., 0., 1.): Translate the time-series over the (x, y, z) axes.
transformVisPy.visuals.transforms | None: VisPy transformation to set to the parent node.
parentVisPy.parent | None: Line object parent.
verbosestring: Verbosity level.
_zfloat | 10.: In case of (n_sources, 2) use _z to specify the elevation.
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 TimeSeries3DObj
>>> n_pts, n_ts = 100, 5
>>> time = np.arange(n_pts)
>>> phy = np.random.uniform(2, 30, (n_ts))
>>> data = np.sin(2 * np.pi * time.reshape(1, -1) * phy.reshape(-1, 1))
>>> xyz = np.random.uniform(-20, 20, (n_ts, 3))
>>> ts = TimeSeries3DObj('Ts', data, xyz, antialias=True, color='red',
>>>                    line_width=3.)
>>> ts.preview(axis=True)

Methods

`__init__`(name, data, xyz[, select, ...])	Init.
`animate`([step, interval, iterations])	Animate the object.
`copy`()	Get a copy of the object.
`describe_tree`()	Tree description.
`preview`([bgcolor, axis, xyz, show, obj, ...])	Previsualize the result.
`record_animation`(name[, n_pic, bgcolor])	Record an animated object and save as a *.gif file.
`render`()	Render the canvas.
`screenshot`(saveas[, print_size, dpi, unit, ...])	Take a screeshot of the scene.
`set_shortcuts_to_canvas`(canvas)	Set shortcuts to a VisbrainCanvas.
`to_dict`()	Return a dictionary of all colorbar args.
`to_kwargs`([addisminmax])	Return a dictionary for input arguments.
`update`()	Update line.
`update_from_dict`(kwargs)	Update attributes from a dictionary.

Examples using `visbrain.objects.TimeSeries3DObj`¶

Combine multiple objects

Time-series and pictures 3D (TimeSeries3DObj & Picture3DObj): complete tutorial

Add time series

visbrain.objects.TimeSeries3DObj¶

Examples using visbrain.objects.TimeSeries3DObj¶

Examples using `visbrain.objects.TimeSeries3DObj`¶