A Python interface for asynchronous MIDI data collection using PsychoPy
Project description
midi-psychopy - A Python interface for asynchronous MIDI data collection
The MIDI Interface is a Python package designed to interact with MIDI devices through the Mido library. It provides functionality to receive and transmit MIDI data asynchronously, which is useful for real-time data collection in PsychoPy experiments.
Installation
You can install the MIDI Interface package using pip:
pip install midi-psychopy
Usage
Basic Usage - Collecting MIDI Data
import time
import pandas as pd
from midi_controller import MidiController
# Create an instance of MidiController
controller = MidiController(device_name='UM-ONE')
# Start data collection
controller.start_data_collection()
# Let the program run for some time (e.g., 10 seconds)
time.sleep(10)
# Stop data collection
controller.stop_data_collection()
# Access the collected MIDI data
print(controller.sequence_out_full)
In PsychoPy
The setup for using the MidiController in a PsychoPy experiment is similar to the basic usage. Users can follow the steps below to integrate the MidiController into their experiment:
- Create a code component in the PsychoPy Builder interface inside the routine where you want to collect MIDI data.
- Import and instantiate the MidiController object in the "Begin Experiment" tab.
import os
import pandas as pd
from midi_controller import MidiController
# Create an instance of MidiController
# Note that globalClock is a standard PsychoPy variable that can be used to synchronize the MIDI data with the
# PsychoPy global timer.
midi_controller = MidiController(device_name='UM-ONE', psychopy_global_timer=globalClock)
# Initialize a DataFrame to store the collected MIDI data
keypress_data = pd.DataFrame()
# Also initialize a variable to keep track of the trial number
trial_count = 0
# Define the path to save the data
# expInfo is standard PsychoPy variable. make sure to check the name of the identifying variable in your experiment
# (i.e., participant is the default name for the participant ID defined in the "Experiment Info" section of the "Basic"
# tab in the PsychoPy GUI's "Properties" window).
par_id = expInfo['participant']
save_dir = os.path.abspath(f'./')
file_name = f'par_{par_id}.csv'
save_path = f'{save_dir}/{file_name}'
- Start data collection in the "Begin Routine" tab.
# Start data collection
midi_controller.start_data_collection()
- Stop data collection in the "End Routine" tab.
# Stop data collection
midi_controller.stop_data_collection()
Alternatively, a conditional statement can also be used in the "Each Frame" tab to terminate data collection based on certain conditions.
if some_condition:
midi_controller.stop_data_collection()
- Store the collected MIDI data in the "End Experiment" tab.
Because the start_data_collection() method would reset the collected data (sequence_out_full) each time it is called, the data should be stored locally as a csv file or in a Pandas DataFrame.
temp_out = midi_controller.sequence_out_full
# Add a column to store the trial number. If there are other variables to store, add them here.
temp_out['trial'] = trial_count
trial_count += 1
# Append the collected data to the keypress_data DataFrame
keypress_data = pd.concat([keypress_data, temp_out], ignore_index=True)
# Save the data to a csv file in case the experiment crashes
keypress_data.to_csv(save_path)
Requirements
- Python 3.x
- Mido
- Pandas
Contributing
Contributions are welcome! If you find any issues or have suggestions for improvement, please open an issue or submit a pull request on GitHub.
License
This project is licensed under the MIT License - see the LICENSE file for details.
MIDI Interface
For more details about the underlying MIDI interface used by the MidiController, refer to midi_interface.py.
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