Python analysis module for AVATAR recording system.
pip install avatarpy
https://jeakwon.github.io/avatarpy
from avatarpy import Avatar
avatar = Avatar('<your_file>.csv')from avatarpy import Avatar, dataset
csv_path = dataset['freely_moving'] # dataset is dict of csv_path provided by avatarpy package
avatar = Avatar(csv_path)
print(avatar.data.head())Output>
0 1 2 3 4 5 6 7 8 ... 18 19 20 21 22 23 24 25 26
0.00 7.563278 6.401241 1.350410 7.052756 5.516540 1.751832 4.075222 -0.440819 1.087099 ... 5.473783 5.572334 -0.249568 5.601366 6.874110 -0.223811 7.233006 -3.937290 3.460134
0.05 7.575983 6.197442 1.385232 7.026716 5.480618 1.777821 4.027716 -0.442995 1.033222 ... 5.482899 5.572342 -0.246786 5.601272 6.864918 -0.220855 7.059306 -4.178260 3.297818
0.10 7.561103 5.993541 1.419173 7.000675 5.444695 1.803809 3.980210 -0.445171 0.979356 ... 5.492015 5.572350 -0.244004 5.601178 6.855827 -0.217890 6.885703 -4.419129 3.135606
0.15 7.531137 5.933699 1.574473 6.960131 5.260929 1.883197 3.941283 -0.480223 0.957676 ... 5.482900 5.581542 -0.246813 5.381383 6.855808 -0.227845 6.823680 -4.460647 3.094629
0.20 7.551146 5.873858 1.731368 6.919584 5.077264 1.962684 3.902356 -0.515285 0.936006 ... 5.492015 5.572350 -0.244004 5.601365 6.855810 -0.223757 6.761554 -4.502164 3.053748
[5 rows x 27 columns]
from avatarpy import Avatar
avatar = Avatar('<your_file>.csv')
avatar.helpOutput>
Functions:
get_angle:
Calcultes angle of T-series vector (Nx3)
get_axis_data:
Returns axis data of all nodes and vectors
get_distance:
Calculates euclidian distance of T-series vector (Nx3)
get_dot_product:
Calculates dot product of two T-series vectors (Nx3)
get_node:
Returns T-series node x, y, z coords by assigned index of columns
get_node_data:
Returns coords data with labels of provided nodes names
get_projection:
Project 3D coordinates on to axis or plane
get_rotation_matrix:
Returns rotation matrix require for rotation of vector a onto vector b
get_rotation_matrix_of_two_unit_vectors:
Rotates unit vector a onto unit vector b
get_unit_vector:
Returns numpy 2d array (N x 3) of given axis unit vector
get_vector:
Returns T-series vector x, y, z coords by assigned index of columns
get_vector_coords:
Retruns dataframe dicts of nodes given by vector name.
get_xaxis_rotation_matrix:
Returns rotation matrix for x axis rotation when angles are given
get_yaxis_rotation_matrix:
Returns rotation matrix for y axis rotation when angles are given
get_zaxis_rotation_matrix:
Returns rotation matrix for z axis rotation when angles are given
set_nodes:
Set node attributes in avatar with predefined node info in `cls._nodes`
set_vectors:
Set vector attributes in avatar with predefined vector info in `cls._nodes`
x_projection:
Project 3D coordinates on to x axis
xy_projection:
Project 3D coordinates on to xy plane
xz_projection:
Project 3D coordinates on to xz plane
y_projection:
Project 3D coordinates on to y axis
yz_projection:
Project 3D coordinates on to yz plane
z_projection:
Project 3D coordinates on to z axis
Attributes:
ID:
User provided ID for avatar instance. (default: csv_path)
acceleration:
Returns moment acceleration of all coords
angle:
Returns T-series angles between predefined two vectors
animate:
Animation module for coordinate change
csv_path:
Original coordinates file path
cummulative_distance:
Returns cumulative distance of all coords
data:
Raw data of repeated x, y, z coordinates of nodes
distance:
Returns inter-frame distances of all coords
frame_rate:
Number of frames recorded in 1 second. (a.k.a. data rate, sampling rate)
help:
Prints list of available functions and attributes of avatar
index:
Index of recording timecourse. If frame rate is provided, unit is second
node_data:
Coords data with labels of all nodes. [x, y, z, node]
nodes:
Dictionary of all nodes data
total_distance:
Returns total explored distance of all coords
transform:
Transform module for coordinate change
unit_vector_x:
Numpy 2d array (N x 3) of x unit vector [1,0,0]
unit_vector_y:
Numpy 2d array (N x 3) of y unit vector [0,1,0]
unit_vector_z:
Numpy 2d array (N x 3) of z unit vector. [0,0,1]
vector_length:
Returns length of all vectors
vector_length_zscore:
Returns zscores of vector length from all vectors
vectors:
Dictionary of all vectors data
velocity:
Returns moment velocity of all coords
x:
x coordindates of nodes and vectors
x_max:
Maximum x coord value among all nodes
x_min:
Minimum x coord value among all nodes
y:
y coordindates of nodes and vectors
y_max:
Maximum y coord value among all nodes
y_min:
Minimum y coord value among all nodes
z:
z coordindates of nodes and vectors
z_max:
Maximum z coord value among all nodes
z_min:
Minimum z coord value among all nodes
from avatarpy import Avatar, dataset
csv_path = dataset['freely_moving'] # dataset is dict of csv_path provided by avatarpy package
avatar = Avatar(csv_path)
avatar.animate(avatar.index[0:100]).save('freely_moving_0_to_100.html')
# avatar.animate(avatar.index[:100]).show()You can check sample avatar animation html file with link below created by plotly. https://jeakwon.github.io/avatarpy/animation/freely_moving_0_to_100.html