MAVdataflash 2.4.2

Read, analyze and visualize *.bin flight data logs recorded by ArduPilot

MAVdataflash

Read, analyze and visualize *.bin flight data logs recorded by ArduPilot

Installation

Installing via PyPI

Install the latest version with:

$ pip install MAVdataflash

Installing via GitHub

Install directly from the source code:

$ pip install https://github.com/generalaeronautics/MAVdataflash/archive/refs/heads/latest.zip

If you have git installed, you can also try:

$ pip install git+https://github.com/generalaeronautics/MAVdataflash.git

You can also install by cloning or downloading the repo:

$ git clone https://github.com/generalaeronautics/MAVdataflash
$ cd MAVdataflash
$ pip install .

If you get any installation or compilation errors, make sure you have the latest pip and setuptools::

$ pip install --upgrade pip setuptools

Usage

from MAVdataflash import DataFlash

# Create a new instance with DataFlash class
analysis = DataFlash("flight_data.bin")

# Return data in pandas dataframe
analysis.GetData('IMU')

# Return data of specific instance in pandas dataframe
analysis.GetData('IMU', instance=1)

# Return data in polars dataframe
analysis.GetData('IMU', in_polars=True)

# Plot any Parameter and Subparameter VS Time
analysis.Plot('GPS', 'Alt')

# Plot with instance, if parameter data type has more than 1 instance
analysis.Plot('IMU', 'GyrX', instance=1)

# Return the pandas dataframe of EV(Events) data type with Message
analysis.GetEvents()

# Return in polars dataframe
analysis.GetEvents(in_polars=True)

# Return the pandas dataframe of MODE(Modes) data type with Message
analysis.GetModes()

# Return in polars dataframe
analysis.GetModes(in_polars=True)

# Return the pandas dataframe of PARM(Commands) with Values
analysis.GetPARAMS()

# Return Params in dictionary data type
analysis.GetPARAMS(in_dict=True)

# Return in polars dataframe
analysis.GetPARAMS(in_polars=True)

# Return PARM(Command) with Value
analysis.GetPARAM('EK3_IMU_MASK')

# Return the list of Subparameter(Columns) of the Parameter data type
analysis.GetColumns('GPS')

# Return True if Parameter data type is plottable otherwise return as False
analysis.isPlotable('GPS')
analysis.isPlotable('GPS', column='Alt')