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pyulgresample.

Project description

pyulgresample

Package that processes ulog-data from pyulog. It converts ulog-data into pandas dataframe through resampling and provides convenient functions to add and extract additional information from the ulog-data. To convert a .ulg file into ulog, please follow the pyulog instruction.

modules

ulogdataframe

ulogdataframe contains the following classes:

  • TopicMsgs
  • DfUlg

TopicMsgs

This class is a convenient class to specify a topic and messages of interest.

DfUlg

This class contains a ulog-structure, pandas dataframe-structure and list of topics as class-members. It also contains a factory-method for converting a .ulg-file into class-members.

ulogconv

This module contains a few helper-functions for converting a .ulg-file into pandas-dataframe. It is mainly used for DfUlg.

mathpandas

Contains time-series functions.

loginfo

Functions that provide info about the ulg-file.

Each dataframe column represents a message-field. For instance, the thrust-field of the topic vehicle_local_position_setpoint would be named as follow:

T_vehicle_local_position_setpoint_0__F_thrust

if thrust is a scalar or

T_vehicle_local_position_setpoint_0__F_thrust_2

if thrust is an array, where the 2 represents the index of the array.

The T stands for topic, which indicates the beginning of the topic. In this example, the topcic name is vehicle_local_position_setpoint. The topic name is followed by a number, which indicates the topic instance. If there is only one instance of a specific topic, then this number will be 0. The instance number is followed by two underlines and a capital letter F, which stands for field. In the example above, the field in question is thrust.

installation

To prevent any conflict with the system python version, it is suggested to use a virtual enrionment with python version 3.6 and higher. Otherwise, python 3.6 and higher must be the python system version. If you don't have 3.6 installed on your machinge, you can follow this tutorial.

virtualenvwrapper

First install virtualenv:

sudo apt install virtualenv

Install virtualenvrapper: this will install virtualenvwrapper.sh in ~/.local/bin

pip install virtualenvwrapper

Create a virtual environement directory

mkdir ~/.virtualenvs

Add virtual envrionment working-folder to bashrc and source virtualenvwrapper:

export WORKON_HOME=$HOME/.virtualenvs
source /usr/local/bin/virtualenvwrapper.sh

Open new terminal or source bashrc:

source ~/.bashrc

Create a virtual environment with python version 3 and no site packages included (python3 must be installed)

mkvirtualenv --python=python3 --no-site-packages [name-of-new-env]

You now created a new virtual environment with name [name-of-new-env].

To enter [name-of-new-env]:

workon [name-of-new-env]

To exit [name-of-new-env]:

deactivate

build setup

The build-system in use is flit

pip install flit

Now we can build the projct:

flit install -s

The -s stands for symlink which gives the option to test changes without reinstalling the package.

The projcet uses black for code-formatting and flake8 for style-guide enforcement. pre-commit-framework is used to ensure that each commit first gets adjusted through blake and then checked by flake8. PEP257 docstring style checker is used as well. We need to add pre-commit to our system:

pre-commit install

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