def extract_somatic_spiking_features(self, traces, delay, duration):
# soma
trace = {}
traces_for_efel=[]
trace['T'] = traces['T']
trace['V'] = traces['v_stim']
trace['stim_start'] = [delay]
trace['stim_end'] = [delay + duration]
traces_for_efel.append(trace)
# trunk locations
'''
for key in traces['v_rec']:
for k in traces['v_rec'][key]:
trace = {}
trace['T'] = traces['T']
trace['V'] = traces['v_rec'][key][k]
trace['stim_start'] = [delay]
trace['stim_end'] = [delay + duration]
traces_for_efel.append(trace)
'''
efel.setDoubleSetting('interp_step', 0.025)
efel.setDoubleSetting('DerivativeThreshold', 40.0)
traces_results = efel.getFeatureValues(traces_for_efel, ['inv_first_ISI','AP_begin_time', 'doublet_ISI'])
return traces_results
def test_ohmic_input_resistance_vb_ssse():
"""basic: Test ohmic_input_resistance_vb_ssse"""
import efel
efel.reset()
stim_start = 500.0
stim_end = 900.0
time = efel.io.load_fragment('%s#col=1' % meanfrequency1_url)
voltage = efel.io.load_fragment('%s#col=2' % meanfrequency1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['ohmic_input_resistance_vb_ssse', 'voltage_deflection_vb_ssse']
stimulus_current = 10.0
efel.setDoubleSetting('stimulus_current', stimulus_current)
feature_values = \
efel.getFeatureValues(
[trace],
features)
voltage_deflection = feature_values[0]['voltage_deflection_vb_ssse'][0]
ohmic_input_resistance = \
feature_values[0]['ohmic_input_resistance_vb_ssse'][0]
nt.assert_equal(
ohmic_input_resistance,
voltage_deflection /
stimulus_current)
def test_ohmic_input_resistance_vb_ssse():
"""basic: Test ohmic_input_resistance_vb_ssse"""
import efel
efel.reset()
stim_start = 500.0
stim_end = 900.0
time = efel.io.load_fragment('%s#col=1' % meanfrequency1_url)
voltage = efel.io.load_fragment('%s#col=2' % meanfrequency1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['ohmic_input_resistance_vb_ssse', 'voltage_deflection_vb_ssse']
stimulus_current = 10.0
efel.setDoubleSetting('stimulus_current', stimulus_current)
feature_values = \
efel.getFeatureValues(
[trace],
features)
voltage_deflection = feature_values[0]['voltage_deflection_vb_ssse'][0]
ohmic_input_resistance = \
feature_values[0]['ohmic_input_resistance_vb_ssse'][0]
nt.assert_equal(
ohmic_input_resistance,
voltage_deflection /
stimulus_current)
def generate_prediction(self, model: sciunit.Model, verbose: bool = False) -> float:
efel.reset()
stim_start = 10.0 # ms
stim_dur = 50.0 # ms
stim_amp = -1.0 # nA
efel.setDoubleSetting('stimulus_current', stim_amp)
model.inject_soma_square_current(current={'delay':stim_start,
'duration':stim_dur,
'amplitude':stim_amp})
trace = model.get_soma_membrane_potential_eFEL_format(tstop=stim_start+stim_dur+stim_start,
start=stim_start,
stop =stim_start+stim_dur)
prediction = efel.getFeatureValues([trace], ['ohmic_input_resistance_vb_ssse'])[0]["ohmic_input_resistance_vb_ssse"][0]
return prediction
def test_derivwindow1():
"""basic: Test DerivativeWindow"""
import efel
efel.reset()
stim_start = 100.0
stim_end = 1000.0
time = efel.io.load_fragment('%s#col=1' % derivwindow1_url)
voltage = efel.io.load_fragment('%s#col=2' % derivwindow1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['AP_begin_voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)
AP_begin_voltage = feature_values[0]['AP_begin_voltage'][0]
nt.assert_almost_equal(AP_begin_voltage, -45.03627393790836)
efel.reset()
efel.setDoubleSetting('interp_step', 0.01)
feature_values = \
efel.getFeatureValues(
[trace],
features)
AP_begin_voltage = feature_values[0]['AP_begin_voltage'][0]
nt.assert_almost_equal(AP_begin_voltage, -83.57661997973835)
efel.reset()
efel.setDoubleSetting('interp_step', 0.01)
efel.setIntSetting('DerivativeWindow', 30)
feature_values = \
efel.getFeatureValues(
[trace],
features)
AP_begin_voltage = feature_values[0]['AP_begin_voltage'][0]
nt.assert_almost_equal(AP_begin_voltage, -45.505521563640386)
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.stimulus_current is not None:
efel.setDoubleSetting('stimulus_current', self.stimulus_current)
if not efel.FeatureNameExists(self.efel_feature_name):
raise ValueError("eFEL doesn't have a feature called %s" %
self.efel_feature_name)
def generate_prediction(self, model: sciunit.Model, verbose: bool = False) -> Optional[float]:
efel.reset()
stim_start = 10.0 # ms
stim_dur = 5.0 # ms
stim_amp = 15.0 # nA
efel.setDoubleSetting('stimulus_current', stim_amp)
model.inject_soma_square_current(current={'delay':stim_start,
'duration':stim_dur,
'amplitude':stim_amp})
trace = model.get_soma_membrane_potential_eFEL_format(tstop=stim_start+stim_dur+stim_start,
start=stim_start,
stop =stim_start+stim_dur)
output = efel.getFeatureValues([trace], ['AP_duration_half_width'])[0]["AP_duration_half_width"]
prediction = output[0] if output else None
return prediction
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.stimulus_current is not None:
efel.setDoubleSetting('stimulus_current', self.stimulus_current)
if not efel.FeatureNameExists(self.efel_feature_name):
raise ValueError("eFEL doesn't have a feature called %s" %
self.efel_feature_name)
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.interp_step is not None:
efel.setDoubleSetting("interp_step", self.interp_step)
if self.double_settings is not None:
for setting_name, setting_value in self.double_settings.items():
efel.setDoubleSetting(setting_name, setting_value)
if self.int_settings is not None:
for setting_name, setting_value in self.int_settings.items():
efel.setIntSetting(setting_name, setting_value)
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.stimulus_current is not None:
efel.setDoubleSetting('stimulus_current', self.stimulus_current)
if self.interp_step is not None:
efel.setDoubleSetting('interp_step', self.interp_step)
if self.double_settings is not None:
for setting_name, setting_value in self.double_settings.items():
efel.setDoubleSetting(setting_name, setting_value)
if self.int_settings is not None:
for setting_name, setting_value in self.int_settings.items():
efel.setIntSetting(setting_name, setting_value)
if self.string_settings is not None:
print(self.string_settings)
for setting_name, setting_value in self.string_settings.items():
efel.setStrSetting(setting_name, setting_value)
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.stimulus_current is not None:
efel.setDoubleSetting('stimulus_current', self.stimulus_current)
if self.interp_step is not None:
efel.setDoubleSetting('interp_step', self.interp_step)
if self.double_settings is not None:
for setting_name, setting_value in self.double_settings.items():
efel.setDoubleSetting(setting_name, setting_value)
if self.int_settings is not None:
for setting_name, setting_value in self.int_settings.items():
efel.setIntSetting(setting_name, setting_value)
def _setup_efel(self):
"""Set up efel before extracting the feature"""
import efel
efel.reset()
if self.threshold is not None:
efel.setThreshold(self.threshold)
if self.stimulus_current is not None:
efel.setDoubleSetting('stimulus_current', self.stimulus_current)
if self.interp_step is not None:
efel.setDoubleSetting('interp_step', self.interp_step)
if self.double_settings is not None:
for setting_name, setting_value in self.double_settings.items():
efel.setDoubleSetting(setting_name, setting_value)
if not efel.FeatureNameExists(self.efel_feature_name):
raise ValueError("eFEL doesn't have a feature called %s" %
self.efel_feature_name)
#*This script is designed to plot each sweep to visualize where errors in the main script (ABF_EFELv2) may be occurring
#The following libraries must be installed before being imported!
import efel
import numpy as np
import pyabf
from tkinter import filedialog
from matplotlib import pyplot as plt
#Opens a dialog box allowing the user to select the file and removes the extension from the file name
file_path = filedialog.askopenfilename()
file = file_path[:-4]
#Sets settings for derivative threshold, interpolation step, and calculation of RMP
efel.setDoubleSetting('interp_step',0.05) #Must be set to the sampling rate (20,000 Hz = 0.05)
efel.setDoubleSetting('voltage_base_start_perc',0.1) #Used for RMP calculation
efel.setDoubleSetting('voltage_base_end_perc',0.8) #Used for RMP calculation
efel.setDerivativeThreshold(15) #Normally set to 15
#Import ABF file and assign the corresponding data to Time and RawData variables
File = pyabf.ABF(file_path)
Time = (File.sweepX)*1000
RawData = File.data
#Identify the number of traces in the abf file (*Note: this is designed for a 20kHz recording lasting ~10s)
#Other differences in recording will need to change these values
RawData = np.transpose(RawData)
TraceNum = int((len(RawData) / 200000))
#Using the number of calulcated traces, split the first RawData column into equal arrays of 200000
