visbrain.objects.HypnogramObj¶

class visbrain.objects.HypnogramObj(name, data=None, time=None, datafile=None, art=-1, wake=0, n1=1, n2=2, n3=3, rem=4, art_visual=1, wake_visual=0, rem_visual=-1, n1_visual=-2, n2_visual=-3, n3_visual=-4, art_color='#8bbf56', wake_color='#56bf8b', rem_color='#bf5656', n1_color='#aabcce', n2_color='#405c79', n3_color='#0b1c2c', line_width=2.0, antialias=False, unicolor=False, transform=None, parent=None, verbose=None, **kw)[source][source]¶

Hypnogram object.

Parameters

namestring: Name of the hypnogram object or path to a *.txt or *.csv file.
dataarray_like: Array of data of shape (n_pts,).
timearray_like | None: Array of time points of shape (n_pts,)
datafilestring | None: Path to the data file.
art, wake, rem, n1, n2, n3 :: Stage identification inside the data array.
art_visual, wake_visual, rem_visual, n1_visual, n2_visual, n3_visual :: Stage order when plotting.
art_color, wake_color, rem_color, n1_color, n2_color, n3_color :: Stage color.
line_widthfloat | 2.: Line with of the hypnogram.
antialiasbool | False: Use anti-aliasing line.
unicolorbool | False: Use a uni black color for the hypnogram.
transformVisPy.visuals.transforms | None: VisPy transformation to set to the parent node.
parentVisPy.parent | None: Hypnogram 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 HypnogramObj
>>> data = np.repeat(np.arange(6), 100) - 1.
>>> h_obj = HypnogramObj('hypno', data)
>>> h_obj.preview(axis=True)

Methods

`__init__`(self, name[, data, time, datafile, …])	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_shortcuts_to_canvas`(self, canvas)	Set shortcuts to a VisbrainCanvas.
`set_stage`(self, stage, idx_start, idx_end)	Set stage.
`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.

cmap¶: Get the cmap value.

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

data_folder¶: Get the data_folder value.

line_width¶: Get the line_width value.

name¶: Get the name 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_stage(self, stage, idx_start, idx_end)[source][source]¶

Set stage.

Parameters

stagestr, int: Stage to define. Should either be a string (e.g ‘art’, ‘rem’…) or an integer.
idx_startint: Index where the stage begin.
idx_endint: Index where the stage finish.

transform¶: Get the transform value.

unicolor¶: Get the unicolor value.

visible_obj¶: Get the visible_obj value.