humo 1.5.1.40

A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer

humo

A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer

Description

A toolkit for non-programmer to wrangle the motion data measured by 3D motion analyzer

DEMO:

Features

• Intuitive operability
• Seamlessly from data shaping to analysis

For more information, see humo -HP.

Requirement

• numpy
• scipy
• pandas
• matplotlib

Usage

quick start

import humo

# loading data and making humo object
data = humo.dataIO.load_data() # open pkl file
cfg = humo.dataIO.load_cfg() # open cfg.json
obj = humo.motion.CoreMain(data, cfg) # make humo object

# get right shoulder angle
Rsho = obj.getJointAngle("Rshoulder")

# get multi data
shoulder = obj.getJointAngle(["Rshoulder","Lshoulder"])
shoulder.Lshoulder # getting Lshoulder angle
shoulder.Lshoulder.x # getting Lshoulder x axis angle

Installation

pip install humo

Anything Else

The pickle data needed to create a humo object is created from a csv file. By converting it to a pickle file, very fast data loading can be achieved.

import humo

# Procedure to convert csv file to pkl file
c2p = humo.Preprocess.convert2pkl() # opening csv file
c2p.datacleansing() # cleansing csv data
c2p.convert2pkl() # save csv file as pkl file

Author

akira6

License

MIT