Module gonioanalysis.drosom.plotting.illustrate_experiments

Functions

def illustrate_experiments(manalyser, rel_rotation_time=1)

Create a visualizing video how the vectormap is built.

Arguments

rel_rotation_time : int or float
Relative time spend on incrimentally rotating the vectormap between the stimuli.
def moving_rois(manalyser, roi_color='red,blue', lw=3, e=50, rel_rotation_time=1, crop_factor=0.5)

Visualization video how the ROI boxes track the analyzed features, drawn on top of the original video frames.

Arguments

roi : string
A valid matplotlib color. If two comma separated colors given use the first for the left eye and the second for the right.
lw : int
ROI box line width, in pixels
e : int
Extended region for brightness normalization, in pixels
rel_rotation_time : int or float
Blend the last and the first next frame for "smooth" transition
crop_factor : int
If smaller than 1 then cropped in Y.

Returns

None
 
def moving_rois_mosaic(manalysers, common_threshold=7.5, **kwargs)

Uses moving_rois() to make a mosaic video of the experiments, in which the specimens move in sync.

The first specimen (manalyser[0]) determines the rotation order (in the order as it was recorded).

Arguments

common_threshold : int
In rotation stage steps, how close the recordings of different analysers have to be classified as the same.
kwargs : dict
Passed to moving_rois

Returns

None
 
def rotation_mosaic(manalyser, imsize=(512, 512), e=50, crop_factor=0.5)

A mosaic (matrix) of the taken images.

Arguments

manalyser : obj
Analyser object
n_vecticals : int
How many vertical rotations rows to show
n_horizontals : int
How many horizontal rotation columns to show
e, crop_factor