A Python Module for Creating Experiments, Tasks and Questionnaires.
| Name | neuropsydia |
|---|---|
| Latest Version |  |
| Documentation | |
| Discussion |  |
| Questions |  |
| Authors |   |
| Support | Windows 7, 8, 10, MacOS |
To get the latest stable version (1.0.3), run the following in the command prompt (might take a few minutes):
pip install https://github.com/neuropsychology/Neuropsydia.py/zipball/masterTo get the latest development version (1.0.4), run the following:
pip install https://github.com/neuropsychology/Neuropsydia.py/zipball/devNOTE: We strongly recommend (for Windows users) the use of the WinPython bundle, that will allow you to have a ready-to-go scientific and portable Python setup.
To upgrade Neuropsydia, uninstall it and reinstall it 😉.
pip uninstall neuropsydia- You need some help? You found a bug? You would like to request a new feature?
Just open an issue
☺️ - Want to add yourself a feature? Correct a bug? You're more than welcome to contribute! Check this page to see how to submit your changes on github.
You can cite Neuropsydia with the following:
Makowski, D. & Dutriaux, L. (2016). Neuropsydia: A Python Module for Creating Experiments, Tasks and Questionnaires.
Memory and Cognition Lab' Day, 01 November, Paris, France
Note: The authors do not give any warranty. If this software causes your keyboard to blow up, your brain to liquefy, your toilet to clog or a zombie plague to leak, the authors CANNOT IN ANY WAY be held responsible.
Tutorials are currently under development. Check out this page to help us improve them.
- Novice
- 1.0 Getting Started
- 1.1 Computerize a questionnaire
- 1.2 Complexify this questionnaire
- [1.3 Include info about the participant] (http://ecole-de-neuropsychologie.readthedocs.io/en/latest/CreatingExperiments/Neuropsydia.py/Tutorials/Novice/#part-13-include-info-about-the-participant)
- 1.4 The novice's trial
- Apprentice
- 2.0 Basics of Python programming
- [2.1 Structuring your Code] (http://ecole-de-neuropsychologie.readthedocs.io/en/latest/CreatingExperiments/Neuropsydia.py/Tutorials/Apprentice/#part-21-structuring-your-code)
- 2.1 Create a Stroop task
- 2.2 The apprentice's trial
- Companion
- 3.0 Create a more complex experiment
- 3.1 The companion's trial
- Master
- 4.0 Improve timing and precision
- 4.1 Data manipulation and analysis
- 4.2 The master's trial
Try this!
import neuropsydia as n # Load neuropsydia
import random # Import the random module
import pandas as pd # To manipulate and save the data
import numpy as np # To do some maths
n.start() # Start neuropsydia
n.instructions("Goal: Hit SPACE whenever a GREEN circle appears. \nWhen it is RED, don't press anything.") # Display instructions and break line with \n
n.newpage("grey") # Fill the screen
n.countdown() # Display countdown
# Initialize the data storage with a dictionary containing empty lists
data = {"Trial": [],
"Stimulus": [],
"ISI":[],
"RT":[],
"Response":[]}
for trial in range(5): # Iterate over the number of trials
stimulus = random.choice(["green", "red"]) # Select a stimulus type
ISI = random.randrange(start=500, stop=2000, step=500) # Select the inter-stimuli interval (ISI)
n.newpage("grey") # Fill the screen
n.write("+") # Fixation cross
n.refresh() # Diplay it on screen
n.time.wait(ISI) # Wait
n.circle(size=2, fill_color=stimulus) # Display the stimulus (filled with the color selected above)
n.refresh() # Diplay it on screen
response, RT = n.response(time_max=1500) # Wait until 1.5s and collect the response and its time
# Categorize the response
if response == "SPACE" and stimulus == "green":
response_type = "HIT" # Hit
if response != "SPACE" and stimulus == "green":
response_type = "MISS" # Miss
if response == "SPACE" and stimulus == "red":
response_type = "FA" # False Alarm
if response != "SPACE" and stimulus == "red":
response_type = "CR" # Correct Rejection
# Store data by appending each item to its list
data["Trial"].append(trial)
data["Stimulus"].append(stimulus)
data["ISI"].append(ISI)
data["RT"].append(RT)
data["Response"].append(response_type)
# Data saving
df = pd.DataFrame.from_dict(data) # Transform the data dictionary into a proper and savable dataframe
df.to_csv("data.csv") # Save it
# Quick analysis
RTs = df.query('Response=="HIT"')["RT"] # Select the Hits' RTs
print(np.mean(RTs), np.std(RTs)) # Print the mean and the standard deviation
print(len(df.query('Response=="FA"'))) # Print the number of intrusions (false alarms)
n.close() # Close neuropsydia- Easily write, display images and interact with the user.
- Detailed control over the timing and latency: preload images and display them exactly whenever you want.
n.start()
n.write("Welcome", style="title") name = n.ask("What is your name?", y=5) n.write("Ok, " + name + ", here is a super cool cat.", y=3) n.image("cat.png", size=3, y=-3.5) n.refresh() n.time.wait(2000)
n.close()
---
## Scales and Questionnaires
- [x] Fully automated questionnaires.
- [x] Powerful scale creation.
<p align="left">
<a href="">
<img src="https://github.com/neuropsychology/Neuropsydia.py/blob/master/examples/Files/demo-scale.gif" height="500" alt="interactive scale psychology">
</a>
</p>
```python
import neuropsydia as n
n.start()
n.newpage()
n.scale(title="Is Python great?",
y=3.3,
anchors=["", ""],
style="blue",
analog=False,
edges=[1,5],
labels=["not at all", "not really", "maybe", "quite", "totally"],
labels_size=0.6
)
n.scale(title="How is neuropsydia?",
y=-3.3,
line_length=12,
edges=[0,100],
anchors=["atrocious", "brilliant"],
point_center=True,
separation_labels=["Bad","Good"],
style="purple",
show_result=True,
show_result_shape_line_color="blue"
)
n.close()
- Easily display clickable choices, useful in case of recognition tasks or so.
import neuropsydia as n
n.start()
n.newpage()
response = n.choice(["Yes", "No"], y=5, title="Isn't it easy?")
response = n.choice(["Hell no", "Nope", "Dunno", "Sure"],
y=-5,
title="Am I better looking?",
height=-2,
boxes_edge_size=0,
boxes_background=["red", "amber", "teal", "blue"],
help_list=["means not at all", "means no", "means you don't know", "means yes"])
n.close()