visbrain.objects.ImageObj

class visbrain.objects.ImageObj(name, data=None, xaxis=None, yaxis=None, 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]

Create a single image object.

Parameters:
data : array_like

Array of data. If data.ndim in [1, 2] the color is inferred from the data. Otherwise, if data.ndim is 3, data is interpreted as color if the last dimension is either 3 (RGB) or 4 (RGBA).

xaxis : array_like | None

Vector to use for the x-axis (number of columns in the image). If None, xaxis is inferred from the second dimension of data.

yaxis : array_like | None

Vector to use for the y-axis (number of rows in the image). If None, yaxis is inferred from the first dimension of data.

clim : tuple | None

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

cmap : string | None

Colormap name.

vmin : float | None

Minimum threshold of the colorbar.

under : string/tuple/array_like | None

Color for values under vmin.

vmax : float | None

Maximum threshold of the colorbar.

under : string/tuple/array_like | None

Color for values over vmax.

interpolation : string | ‘nearest’

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

max_pts : int | -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.

transform : VisPy.visuals.transforms | None

VisPy transformation to set to the parent node.

parent : VisPy.parent | None

Markers object parent.

verbose : string

Verbosity level.

kw : dict | {}

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 ImageObj
>>> n = 100
>>> time = np.r_[np.arange(n - 1), np.arange(n)[::-1]]
>>> time = time.reshape(-1, 1) + time.reshape(1, -1)
>>> im = ImageObj('im', time, cmap='Spectral_r', interpolation='bicubic')
>>> im.preview(axis=True)

Methods

__init__(name[, data, xaxis, yaxis, cmap, …]) Init.
describe_tree() Tree description.
preview([bgcolor, axis, xyz, show, obj, size]) Previsualize the result.
screenshot(saveas[, print_size, dpi, unit, …]) Take a screeshot of the scene.
set_data(data[, xaxis, yaxis, clim, cmap, …]) Set data to the image.
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() Fonction to run when an update is needed.
update_from_dict(kwargs) Update attributes from a dictionary.
clim

Get the clim value.

cmap

Get the cmap value.

interpolation

Get the interpolation value.

name

Get the name value.

over

Get the over value.

parent

Get the parent value.

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

Previsualize the result.

Parameters:
bgcolor : array_like/string/tuple | ‘black’

Background color for the preview.

axis : bool | False

Add x and y axis with ticks.

xyz : bool | False

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

obj : VisbrainObj | None

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

size : tuple | (1200, 800)

Default size of the window.

kwargs : dict | {}

Optional arguments are passed to the VisbrainCanvas class.

screenshot(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:
saveas : str

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

print_size : tuple | 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.

dpi : float | 300.

Dots per inch for printing the image.

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

Unit of the printed size.

factor : float | None

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

region : tuple | None

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

autocrop : bool | False

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

bgcolor : array_like/string | None

The background color of the image.

transparent : bool | False

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

obj : VisbrainObj | None

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

kwargs : dict | {}

Optional arguments are passed to the VisbrainCanvas class.

set_data(data, xaxis=None, yaxis=None, clim=None, cmap=None, vmin=None, under=None, vmax=None, over=None)[source][source]

Set data to the image.

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.ImageObj