def test_mean_frequency1():
"""basic: Test mean_frequency 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = joinp(testdata_dir, 'basic', 'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['mean_frequency']
feature_values = \
efel.getFeatureValues(
[trace],
features)
nt.assert_almost_equal(feature_values[0]['mean_frequency'][0], 15.2858453)
def test_mean_frequency1():
"""basic: Test mean_frequency 1"""
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 = ['mean_frequency']
feature_values = \
efel.getFeatureValues(
[trace],
features)
nt.assert_almost_equal(feature_values[0]['mean_frequency'][0], 15.2858453)
def test_ISI_log_slope_skip():
"""basic: Test ISI_log_slope_skip"""
import efel
efel.reset()
import numpy
stim_start = 31.2
stim_end = 431.2
data = numpy.loadtxt(
'testdata/basic/zero_ISI_log_slope_skip95824004.abf.csv')
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['ISI_log_slope_skip']
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
feature_values = \
efel.getFeatureValues(
[trace],
features)
nt.assert_equal(feature_values[0]['ISI_log_slope_skip'], None)
def test_getDistance1():
"""basic: Test getDistance 1"""
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]
nt.assert_almost_equal(
3.09045815935,
efel.getDistance(
trace,
'AP_amplitude',
50,
10))
def test_APlast_amp():
"""basic: Test APlast_amp"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = joinp(testdata_dir, 'basic', 'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['AP_amplitude', 'APlast_amp']
feature_values = \
efel.getFeatureValues(
[trace],
features)
APlast_amp = feature_values[0]['APlast_amp'][0]
AP_amplitude = feature_values[0]['APlast_amp']
nt.assert_equal(APlast_amp, AP_amplitude[-1])
def test_min_AHP_indices():
"""basic: Test min_AHP_indices"""
import efel
efel.reset()
stim_start = 650.0
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 = ['min_AHP_indices']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
min_AHP_indices = feature_values[0]['min_AHP_indices']
nt.assert_equal(len(min_AHP_indices), 5)
def test_decay_time_constant_after_stim2():
"""basic: decay_time_constant_after_stim 2"""
import efel
efel.reset()
import numpy
stim_start = 100.0
stim_end = 1000.0
test_data_path = joinp(testdata_dir, 'basic', 'tau20.0.csv')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {
'T': time,
'V': voltage,
'stim_start': [stim_start],
'stim_end': [stim_end],
'decay_start_after_stim': [1.0],
'decay_end_after_stim': [10.0]
}
features = ['decay_time_constant_after_stim']
feature_values = efel.getFeatureValues([trace], features)[0]
nt.assert_almost_equal(
20.0,
feature_values['decay_time_constant_after_stim'][0], places=1)
def calculate_feature(self, responses, raise_warnings=False):
"""Calculate feature value"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
feature_value = None
else:
self._setup_efel()
import efel
values = efel.getMeanFeatureValues(
[efel_trace],
[self.efel_feature_name],
raise_warnings=raise_warnings)
feature_value = values[0][self.efel_feature_name]
efel.reset()
logger.debug(
'Calculated value for %s: %s',
self.name,
str(feature_value))
return feature_value
def test_spikecount_libv4peakindices():
"""basic: Test Spikecount in combination with LibV4 peak_indices"""
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 = ['peak_indices', 'Spikecount']
test_peak = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'DependencyV5_LibV4peakindices.txt')
efel.setDependencyFileLocation(test_peak)
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_indices = feature_values[0]['peak_indices']
spikecount = feature_values[0]['Spikecount'][0]
nt.assert_equal(len(peak_indices), 5)
nt.assert_equal(len(peak_indices), spikecount)
def test_version():
"""basic: Test if version number exists"""
import efel
efel.reset()
nt.assert_true(efel.version is not None)
def test_raise_warnings():
"""basic: Test raise_warnings"""
import efel
efel.reset()
import numpy
trace = {}
trace['T'] = numpy.arange(0, 100, 0.1)
trace['V'] = numpy.ones(len(trace['T'])) * -80.0
trace['stim_start'] = [25]
trace['stim_end'] = [75]
import warnings
with warnings.catch_warnings(record=True) as warning:
warnings.simplefilter("always")
feature_value = efel.getFeatureValues(
[trace],
['AP_amplitude'])[0]['AP_amplitude']
nt.assert_equal(feature_value, None)
nt.assert_equal(len(warning), 1)
nt.assert_true(
"Error while calculating feature AP_amplitude" in
str(warning[0].message))
with warnings.catch_warnings(record=True) as warning:
warnings.simplefilter("always")
feature_value = efel.getFeatureValues(
[trace],
['AP_amplitude'], raise_warnings=False)[0]['AP_amplitude']
nt.assert_equal(feature_value, None)
nt.assert_equal(len(warning), 0)
def test_getmeanfeaturevalues():
"""basic: Test getMeanFeatureValues"""
import efel
efel.reset()
import numpy
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]
feature_values = \
efel.getFeatureValues(
[trace],
['AP_amplitude', 'BPAPHeightLoc1'], raise_warnings=False)
mean_feature_values = efel.getMeanFeatureValues(
[trace], [
'AP_amplitude', 'BPAPHeightLoc1'], raise_warnings=False)
nt.assert_equal(numpy.mean(feature_values[0]['AP_amplitude']),
mean_feature_values[0]['AP_amplitude'])
def test_getDistance_error_dist():
"""basic: Test getDistance error_dist option"""
import efel
efel.reset()
stim_start = 400.0
stim_end = 500.0
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]
score_normal = efel.getDistance(
trace,
'AP_amplitude',
50,
10)
score_150 = efel.getDistance(
trace,
'AP_amplitude',
50,
10,
error_dist=150)
nt.assert_almost_equal(score_normal, 250)
nt.assert_almost_equal(score_150, 150)
def test_getFeatureNameExists():
"""basic: Test FeatureNameExists"""
import efel
efel.reset()
nt.assert_true(efel.FeatureNameExists('voltage_base'))
nt.assert_false(efel.FeatureNameExists('voltage_base_wrong'))
def test_mean_frequency1():
"""basic: Test mean_frequency 1"""
import efel
efel.reset()
trace, time, voltage, stim_start, stim_end = load_data(
'mean_frequency1', interp=True)
features = ['mean_frequency', 'peak_time']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_times = feature_values[0]['peak_time']
stim_spikes = peak_times[numpy.where((stim_start <= peak_times)
& (peak_times <= stim_end))]
n_of_spikes = len(stim_spikes)
mean_frequency = float(n_of_spikes) * 1000 / \
(stim_spikes[-1] - stim_start)
nt.assert_almost_equal(
feature_values[0]['mean_frequency'][0],
mean_frequency)
def test_strict_stiminterval():
"""basic: Test strict_stiminterval"""
import efel
for strict, n_of_spikes in [(False, 5), (True, 3)]:
efel.reset()
efel.setIntSetting("strict_stiminterval", strict)
stim_start = 600.0
stim_end = 750.0
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 = ['peak_indices', 'peak_time', 'Spikecount']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
peak_indices = feature_values[0]['peak_indices']
peak_time = feature_values[0]['peak_time']
spikecount = feature_values[0]['Spikecount']
nt.assert_equal(len(peak_indices), n_of_spikes)
nt.assert_equal(len(peak_time), n_of_spikes)
nt.assert_equal(spikecount, n_of_spikes)
def test_min_AHP_indices_strict():
"""basic: Test min_AHP_indices with strict_stiminterval"""
import efel
for strict, n_of_ahp in [(False, 17), (True, 16)]:
efel.reset()
efel.setIntSetting('strict_stiminterval', strict)
stim_start = 700.0
stim_end = 2700.0
time = efel.io.load_fragment('%s#col=1' % ahptest1_url)
voltage = efel.io.load_fragment('%s#col=2' % ahptest1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['min_AHP_indices', 'AHP_time_from_peak', 'peak_time']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
min_AHP_indices = feature_values[0]['min_AHP_indices']
AHP_time_from_peak = feature_values[0]['AHP_time_from_peak']
nt.assert_equal(len(min_AHP_indices), n_of_ahp)
nt.assert_equal(len(AHP_time_from_peak), n_of_ahp)
def test_APlast_amp():
"""basic: Test APlast_amp"""
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 = ['AP_amplitude', 'APlast_amp']
feature_values = \
efel.getFeatureValues(
[trace],
features)
APlast_amp = feature_values[0]['APlast_amp'][0]
AP_amplitude = feature_values[0]['APlast_amp']
nt.assert_equal(APlast_amp, AP_amplitude[-1])
def test_setDerivativeThreshold():
"""basic: Test setDerivativeThreshold"""
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 = ['AP_begin_voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)
AP_begin_voltage_orig = feature_values[0]['AP_begin_voltage'][1]
efel.setDerivativeThreshold(5)
feature_values = \
efel.getFeatureValues(
[trace],
features)
AP_begin_voltage = feature_values[0]['AP_begin_voltage'][1]
nt.assert_almost_equal(AP_begin_voltage, -51.6400489995987)
nt.assert_not_equal(AP_begin_voltage, AP_begin_voltage_orig)
def test_spikecount1():
"""basic: Test Spikecount 1"""
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 = ['peak_indices', 'Spikecount']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_indices = feature_values[0]['peak_indices']
spikecount = feature_values[0]['Spikecount'][0]
nt.assert_equal(len(peak_indices), spikecount)
def test_zero_ISI_log_slope_skip():
"""basic: Test zero ISI_log_slope_skip"""
import efel
efel.reset()
stim_start = 31.2
stim_end = 431.2
time = efel.io.load_fragment('%s#col=1' % zeroISIlog1_url)
voltage = efel.io.load_fragment('%s#col=2' % zeroISIlog1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['ISI_log_slope_skip']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
nt.assert_equal(feature_values[0]['ISI_log_slope_skip'], None)
def test_voltagebase1():
"""basic: Test voltagebase 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = joinp(testdata_dir, 'basic', 'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)
voltage_base = numpy.mean(voltage[numpy.where(
(time >= 0.9 * stim_start) & (time <= stim_start))])
nt.assert_almost_equal(voltage_base, feature_values[0]['voltage_base'][0])
def test_ISI_semilog_slope():
"""basic: Test ISI_semilog_slope"""
import numpy
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 = ['ISI_values', 'ISI_semilog_slope']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
isi_values = feature_values[0]['ISI_values']
x_values = numpy.arange(0, len(isi_values)) + 1.0
# fit
x_values = x_values
log_isi_values = numpy.log(isi_values)
slope, _ = numpy.polyfit(x_values, log_isi_values, 1)
nt.assert_almost_equal(feature_values[0]['ISI_semilog_slope'][0], slope)
def test_getDistance1():
"""basic: Test getDistance 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = joinp(testdata_dir, 'basic', 'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
nt.assert_almost_equal(
3.09045815935,
efel.getDistance(
trace,
'AP_amplitude',
50,
10))
def test_spikecount1():
"""basic: Test Spikecount 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = joinp(testdata_dir, 'basic', 'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['peak_indices', 'Spikecount']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_indices = feature_values[0]['peak_indices']
spikecount = feature_values[0]['Spikecount'][0]
nt.assert_equal(len(peak_indices), spikecount)
def test_spikecount2():
"""basic: Test Spikecount 2: test empty trace"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
time = numpy.arange(0, 1000.0, 0.1)
voltage = numpy.ones(len(time)) * -80.0
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['Spikecount']
feature_values = \
efel.getFeatureValues(
[trace],
features)
spikecount = feature_values[0]['Spikecount'][0]
nt.assert_equal(spikecount, 0)
def test_ap_amplitude_from_voltagebase1():
"""basic: Test AP_amplitude_from_voltagebase 1"""
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 = ['AP_amplitude_from_voltagebase',
'peak_voltage', 'voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)
voltage_base = feature_values[0]['voltage_base'][0]
for peak_voltage, ap_amplitude_from_voltagebase in zip(
feature_values[0]['peak_voltage'],
feature_values[0]['AP_amplitude_from_voltagebase']):
nt.assert_almost_equal(peak_voltage - voltage_base,
ap_amplitude_from_voltagebase)
def calculate_score(self, responses, trace_check=False):
"""Calculate the score"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
score = self.max_score
else:
self._setup_efel()
import efel
score = efel.getDistance(
efel_trace,
self.efel_feature_name,
self.exp_mean,
self.exp_std,
trace_check=trace_check,
error_dist=self.max_score
)
if self.force_max_score:
score = min(score, self.max_score)
efel.reset()
logger.debug('Calculated score for %s: %f', self.name, score)
return score
def test_voltagebase1():
"""basic: Test voltagebase 1"""
import numpy
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 = ['voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)
voltage_base = numpy.mean(voltage[numpy.where(
(time >= 0.9 * stim_start) & (time <= stim_start))])
nt.assert_almost_equal(voltage_base, feature_values[0]['voltage_base'][0],
places=5)
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_interpolate():
"""basic: Test interpolate"""
import efel
efel.reset()
trace, time, voltage, stim_start, stim_end = load_data('mean_frequency1',
interp=True)
features = ['voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features, raise_warnings=False)
interp_voltage = feature_values[0]['voltage']
nt.assert_equal(len(interp_voltage), len(voltage))
nt.assert_true(numpy.allclose(interp_voltage, voltage))
def test_failing_double_feature():
"""basic: Test failing double feature"""
import efel
efel.reset()
trace = {}
trace['T'] = numpy.arange(0, 100, 0.1)
trace['V'] = numpy.ones(len(trace['T'])) * -80.0
trace['stim_start'] = [25]
trace['stim_end'] = [75]
feature_value = efel.getFeatureValues(
[trace],
['AP_amplitude'], raise_warnings=False)[0]['AP_amplitude']
nt.assert_equal(feature_value, None)
def test_nonexisting_feature():
"""basic: Test nonexisting feature"""
import efel
efel.reset()
trace = {}
trace['T'] = numpy.arange(0, 100, 0.1)
trace['V'] = numpy.ones(len(trace['T'])) * -80.0
trace['stim_start'] = [25]
trace['stim_end'] = [75]
nt.assert_raises(
TypeError,
efel.getFeatureValues,
[trace],
['nonexisting_feature'])
def test_stimstart_stimend():
"""basic: Test exception when stimstart or stimend are wrong"""
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 = ['AP_begin_voltage']
nt.assert_raises(
Exception,
efel.getFeatureValues, [trace], features)
trace['stim_start'] = [stim_end]
trace['stim_end'] = [stim_start]
nt.assert_raises(
Exception,
efel.getFeatureValues, [trace], features)
trace['stim_start'] = [stim_start, stim_end]
trace['stim_end'] = [stim_end]
nt.assert_raises(
Exception,
efel.getFeatureValues, [trace], features)
del trace['stim_start']
nt.assert_raises(
Exception,
efel.getFeatureValues, [trace], features)
def test_decay_time_constant_after_stim1():
"""basic: decay_time_constant_after_stim 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = os.path.join(
testdata_dir,
'basic',
'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
time = efel.io.load_fragment('%s#col=1' % meanfrequency1_url)
voltage = efel.io.load_fragment('%s#col=2' % meanfrequency1_url)
trace = {
'T': time,
'V': voltage,
'stim_start': [stim_start],
'stim_end': [stim_end],
}
features = ['decay_time_constant_after_stim']
feature_values = efel.getFeatureValues([trace], features)[0]
expected = decay_time_constant_after_stim(
trace['T'],
trace['V'],
stim_end + 1.0,
stim_end + 10.0,
trace['stim_start'][0],
trace['stim_end'][0])
nt.assert_almost_equal(
expected,
feature_values['decay_time_constant_after_stim'][0])
def test_steady_state_voltage1():
"""basic: Test steady_state_voltage"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
test_data_path = os.path.join(
testdata_dir,
'basic',
'mean_frequency_1.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
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 = ['steady_state_voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)[0]
begin_time = stim_end
end_time = max(time)
steady_state_voltage = numpy.mean(voltage[numpy.where(
(time <= end_time) & (time > begin_time)
)])
nt.assert_almost_equal(steady_state_voltage,
feature_values['steady_state_voltage'][0])
def _get_peak_times(self, responses, raise_warnings=False):
efel_trace = self._construct_somatic_efel_trace(responses)
if efel_trace is None:
peak_times = None
else:
self._setup_efel()
import efel
peaks = efel.getFeatureValues(
[efel_trace], ["peak_time"], raise_warnings=raise_warnings
)
peak_times = peaks[0]["peak_time"]
efel.reset()
return peak_times
def test_decay_time_constant_after_stim1():
"""basic: Test decay_time_constant_after_stim 1"""
import efel
efel.reset()
trace, time, voltage, stim_start, stim_end = load_data('mean_frequency1',
interp=True)
features = ['decay_time_constant_after_stim']
feature_values = efel.getFeatureValues([trace], features)[0]
expected = decay_time_constant_after_stim(time, voltage, stim_end + 1.0,
stim_end + 10.0, stim_start,
stim_end)
nt.assert_almost_equal(expected,
feature_values['decay_time_constant_after_stim'][0])
def test_min_voltage_between_spikes1():
"""basic: Test min_voltage_between_spikes 1"""
import efel
efel.reset()
import numpy
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 = ['min_voltage_between_spikes', 'peak_indices', 'voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_indices = feature_values[0]['peak_indices']
min_voltage_between_spikes = feature_values[
0]['min_voltage_between_spikes']
fel_voltage = feature_values[0]['voltage']
for index, min_voltage_between_spikes_value in zip(
list(range(len(peak_indices[:-1]))),
min_voltage_between_spikes):
nt.assert_almost_equal(
numpy.min(
fel_voltage[
peak_indices[index]:peak_indices[
index +
1]]),
min_voltage_between_spikes_value)
def test_AP_begin_indices1():
"""basic: Test AP_begin_indices 1"""
import efel
efel.reset()
import numpy
stim_start = 31.2
stim_end = 431.2
voltage = numpy.loadtxt('testdata/basic/AP_begin_indices_95810005.abf.csv')
time = numpy.arange(len(voltage)) * 0.1
trace = {}
trace['V'] = voltage
trace['T'] = time
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = [
'AP_begin_indices', 'AP_amplitude', 'peak_time',
'AP_duration_half_width'
]
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
feature_values = \
efel.getFeatureValues(
[trace],
features)
# Make sure the amount of peak_times, AP_begin_indices and AP_amplitude is
# the same in this trace
# There was originally an issue in this case due to the 'width' value
# in AP_begin_indices, which caused a segmentation fault
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['AP_amplitude']))
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['peak_time']))
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['AP_duration_half_width']))
def test_AP_begin_indices1():
"""basic: Test AP_begin_indices 1"""
import efel
efel.reset()
import numpy
stim_start = 31.2
stim_end = 431.2
test_data_path = os.path.join(testdata_dir, 'basic',
'AP_begin_indices_95810005.abf.csv')
voltage = numpy.loadtxt(test_data_path)
time = numpy.arange(len(voltage)) * 0.1
trace = {}
trace['V'] = voltage
trace['T'] = time
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = [
'AP_begin_indices', 'AP_amplitude', 'peak_time',
'AP_duration_half_width'
]
feature_values = \
efel.getFeatureValues(
[trace],
features,
raise_warnings=False)
# Make sure the amount of peak_times, AP_begin_indices and AP_amplitude is
# the same in this trace
# There was originally an issue in this case due to the 'width' value
# in AP_begin_indices, which caused a segmentation fault
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['AP_amplitude']))
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['peak_time']))
nt.assert_equal(len(feature_values[0]['AP_begin_indices']),
len(feature_values[0]['AP_duration_half_width']))
def test_steady_state_voltage1():
"""basic: Test steady_state_voltage"""
import efel
efel.reset()
trace, time, voltage, stim_start, stim_end = load_data(
'mean_frequency1', interp=True)
features = ['steady_state_voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)[0]
steady_state_voltage = numpy.mean(voltage[numpy.where(time >= stim_end)])
nt.assert_almost_equal(steady_state_voltage,
feature_values['steady_state_voltage'][0])
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 calculate_feature(self, responses, raise_warnings=False):
"""Calculate feature value"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
feature_value = None
else:
import efel
efel.reset()
values = efel.getMeanFeatureValues([efel_trace],
[self.efel_feature_name],
raise_warnings=raise_warnings)
feature_value = values[0][self.efel_feature_name]
efel.reset()
return feature_value
def test_spikecount_stimint1():
"""basic: Test Spikecount_stimint 1"""
import numpy
import efel
efel.reset()
stim_start = 700.0
stim_end = 2700.0
time = efel.io.load_fragment('%s#col=1' % spikeoutsidestim_url)
voltage = efel.io.load_fragment('%s#col=2' % spikeoutsidestim_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['peak_time', 'Spikecount_stimint', 'Spikecount']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_times = feature_values[0]['peak_time']
spikecount = feature_values[0]['Spikecount'][0]
spikecount_stimint = feature_values[0]['Spikecount_stimint'][0]
interval_peaktimes, = \
numpy.where((peak_times >= stim_start) & (peak_times <= stim_end))
nt.assert_equal(
len(interval_peaktimes),
spikecount_stimint)
nt.assert_equal(
spikecount,
spikecount_stimint + 2)
def test_getDistance1():
"""basic: Test getDistance 1"""
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]
nt.assert_almost_equal(3.09045815935,
efel.getDistance(trace, 'AP_amplitude', 50, 10))
def generate_prediction(self, model: sciunit.Model) -> Dict[float, float]:
self.traces = []
self.run_times = {}
efel.reset()
stim_list = list(map(float, self.observation.keys()))
run_stim_ = functools.partial(self.run_stim, model)
# multiprocessing giving errors regards to [xcb] ?!
# npool = multiprocessing.cpu_count() - 1
# with Pool(npool, maxtasksperchild=1) as pool:
# results = pool.map(run_stim_, stim_list, chunksize=1)
results = []
for stim_inj in stim_list:
results.append(run_stim_(stim_inj))
# construct prediction with structure similar to observation
prediction = {}
for ind, stim_inj in enumerate(stim_list):
prediction[stim_inj] = results[ind]
return prediction
def test_min_voltage_between_spikes1():
"""basic: Test min_voltage_between_spikes 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
data = numpy.loadtxt('testdata/basic/mean_frequency_1.txt')
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['min_voltage_between_spikes', 'peak_indices', 'voltage']
feature_values = \
efel.getFeatureValues(
[trace],
features)
peak_indices = feature_values[0]['peak_indices']
min_voltage_between_spikes = feature_values[0][
'min_voltage_between_spikes']
fel_voltage = feature_values[0]['voltage']
for index, min_voltage_between_spikes_value in zip(
range(len(peak_indices[:-1])), min_voltage_between_spikes):
nt.assert_almost_equal(
numpy.min(fel_voltage[peak_indices[index]:peak_indices[index +
1]]),
min_voltage_between_spikes_value)
def test_ap_amplitude_outside_stim():
"""basic: Test AP amplitude with spike outside stim"""
import efel
efel.reset()
import numpy
stim_start = 700.0
stim_end = 2700.0
test_data_path = os.path.join(
testdata_dir,
'basic',
'spike_outside_stim.txt')
data = numpy.loadtxt(test_data_path)
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['AP_amplitude', 'peak_time']
feature_values = \
efel.getFeatureValues(
[trace],
features,
raise_warnings=False)
# Make sure AP_amplitude doesn't pick up the two spikes outside of
# the stimulus
# (which are present in peak_time)
nt.assert_equal(
len(feature_values[0]['AP_amplitude']) + 2,
len(feature_values[0]['peak_time']))
def test_getDistance_trace_check():
"""basic: Test getDistance trace_check option"""
import numpy
import efel
efel.reset()
dt = 0.1
# voltage trace at constant -70 mV
v = numpy.zeros(int(100 / dt)) - 70.0
# create 'spikes' at 20, 40 and 60 ms
v[int(20 / dt):int(25 / dt)] = 20.
v[int(40 / dt):int(45 / dt)] = 20.
v[int(60 / dt):int(65 / dt)] = 20.
traces = []
trace = {}
trace['T'] = numpy.arange(len(v)) * dt
trace['V'] = v
trace['stim_start'] = [10]
trace['stim_end'] = [70]
traces.append(trace)
nt.assert_almost_equal(efel.getDistance(trace, 'Spikecount', 0, 1), 3.0)
trace['stim_end'] = [50]
efel.reset()
nt.assert_almost_equal(
efel.getDistance(trace, 'Spikecount', 0, 1, trace_check=False), 3.0)
efel.reset()
nt.assert_almost_equal(efel.getDistance(trace, 'Spikecount', 0, 1), 250.0)
def calculate_score(self, responses):
"""Calculate the score"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
score = 250.0
else:
import efel
efel.reset()
if self.threshold:
efel.setThreshold(self.threshold)
score = efel.getDistance(efel_trace, self.efel_feature_name,
self.exp_mean, self.exp_std)
efel.reset()
logger.debug('Calculated score for %s: %f', self.name, score)
return score
def test_steady_state_voltage_stimend():
"""basic: steady_state_voltage_stimend 1"""
import efel
efel.reset()
import numpy
stim_start = 500.0
stim_end = 900.0
data = numpy.loadtxt('testdata/basic/mean_frequency_1.txt')
time = data[:, 0]
voltage = data[:, 1]
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = ['steady_state_voltage_stimend']
feature_values = \
efel.getFeatureValues(
[trace],
features)[0]
stim_duration = stim_end - stim_start
begin_time = stim_end - 0.1 * stim_duration
end_time = stim_end
steady_state_voltage_stimend = [
numpy.mean(voltage[numpy.where((time < end_time)
& (time >= begin_time))])
]
nt.assert_almost_equal(steady_state_voltage_stimend,
feature_values['steady_state_voltage_stimend'])
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)
def calculate_feature(self, responses, raise_warnings=False):
"""Calculate feature value"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
feature_value = None
else:
self._setup_efel()
import efel
values = efel.getMeanFeatureValues([efel_trace],
[self.efel_feature_name],
raise_warnings=raise_warnings)
feature_value = values[0][self.efel_feature_name]
efel.reset()
logger.debug('Calculated value for %s: %s', self.name,
str(feature_value))
return feature_value
def calculate_score(self, responses, trace_check=False):
"""Calculate the score"""
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
score = 250.0
else:
self._setup_efel()
import efel
score = efel.getDistance(efel_trace,
self.efel_feature_name,
self.exp_mean,
self.exp_std,
trace_check=trace_check)
efel.reset()
logger.debug('Calculated score for %s: %f', self.name, score)
return score
def test_empty_trace():
"""basic: Test results for empty trace"""
import efel
efel.reset()
import numpy
max_time = 3000.0
stim_start = 700.0
stim_end = 2700.0
dt = 0.02
time = numpy.arange(0.0, max_time, dt)
voltage = -80.0 * numpy.ones(len(time))
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = [
'time_to_last_spike',
'inv_time_to_first_spike',
'inv_first_ISI',
'inv_second_ISI',
'inv_third_ISI',
'inv_fourth_ISI',
'inv_fifth_ISI',
'inv_last_ISI']
# efel.getFeatureValues([trace], features)
for feature, value in \
efel.getFeatureValues([trace], features)[0].items():
nt.assert_equal(value[0], 0.0)
def test_sag_ratio2():
"""basic: Test sag_ratio2"""
import efel
efel.reset()
stim_start = 800.0
stim_end = 3800.0
time = efel.io.load_fragment('%s#col=1' % sagtrace1_url)
voltage = efel.io.load_fragment('%s#col=2' % sagtrace1_url)
trace = {}
trace['T'] = time
trace['V'] = voltage
trace['stim_start'] = [stim_start]
trace['stim_end'] = [stim_end]
features = [
'sag_ratio2',
'minimum_voltage',
'steady_state_voltage_stimend',
'voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)
steady_state_voltage_stimend = \
feature_values[0]['steady_state_voltage_stimend'][0]
minimum_voltage = feature_values[0]['minimum_voltage'][0]
voltage_base = feature_values[0]['voltage_base'][0]
sag_ratio2 = feature_values[0]['sag_ratio2'][0]
nt.assert_equal(
sag_ratio2,
(voltage_base - steady_state_voltage_stimend) /
(voltage_base - minimum_voltage))
def test_maximum_voltage_from_voltagebase():
"""basic: Test maximum_voltage_from_voltagebase"""
import efel
efel.reset()
import numpy
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 = ['maximum_voltage_from_voltagebase', 'voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)[0]
maximum_voltage = numpy.max(voltage[numpy.where(
(time <= stim_end) & (time >= stim_start)
)])
voltage_base = feature_values['voltage_base'][0]
maximum_voltage_from_voltagebase = maximum_voltage - voltage_base
nt.assert_almost_equal(
maximum_voltage_from_voltagebase,
feature_values['maximum_voltage_from_voltagebase'][0])
def test_voltagebase1():
"""basic: Test voltagebase 1"""
import efel
efel.reset()
trace, time, voltage, stim_start, stim_end = load_data(
'mean_frequency1', interp=True)
features = ['voltage_base']
feature_values = \
efel.getFeatureValues(
[trace],
features)
interp_time, interp_voltage = interpolate(time, voltage, 0.1)
voltage_base = numpy.mean(interp_voltage[numpy.where(
(interp_time >= 0.9 * stim_start) & (interp_time <= stim_start))])
nt.assert_almost_equal(voltage_base, feature_values[0]['voltage_base'][0],
places=5)
def calculate_score(self, responses, trace_check=False):
"""Calculate the score"""
if self.efel_feature_name.startswith(
"bpo_"): # check if internal feature
score = self.get_bpo_score(responses)
elif self.exp_mean is None:
score = 0
else:
efel_trace = self._construct_efel_trace(responses)
if efel_trace is None:
score = 250.0
else:
self._setup_efel()
import efel
score = efel.getDistance(
efel_trace,
self.efel_feature_name,
self.exp_mean,
self.exp_std,
trace_check=trace_check,
error_dist=self.max_score,
)
if self.force_max_score:
score = min(score, self.max_score)
efel.reset()
logger.debug("Calculated score for %s: %f", self.name, score)
return score
