example.py

"""A simple example using a fake model, but data from neuroelectro.org"""

import os

from quantities import mV
import sciunit
from neuronunit import neuroelectro,tests,capabilities,models

# Specify reference data for this test.  
reference_data = neuroelectro.NeuroElectroSummary(
    neuron = {'name':'Cerebellum Purkinje Cell'}, # Neuron type.  
    ephysprop = {'name':'Resting Membrane Potential'}) # Electrophysiological property name.  

# Get and verify summary data for the combination above from neuroelectro.org. 
reference_data.get_values()  

# Initialize the test with summary statistics from the reference data
# and arguments for the model (model).    
test = tests.RestingPotentialTest(
    observation = {'mean':reference_data.mean*mV,
                      'std':reference_data.std*mV},
                )

# Initialize (parameterize) the model with some initialization parameters.
# Pretend model produces v_rest 1 s.d. from the reference data mean.  
model = models.SimpleModel(reference_data.mean + 1.0*reference_data.std)

# (1) Check capabilities,
# (2) take the test, 
# (3) generate a score and validate it,
# (4) bind the score to model/test combination. 
score = test.judge(model)

# Summarize the result.  
score.summarize()

# Get model output used for this test (optional).
vm = score.related_data['mean_vm']