def get_spike_times(data_file):
delimiter = '\t'
if os.path.isfile(data_file):
times, data = analysis.load_csv_data(data_file, delimiter=delimiter)
elif os.path.isfile('simulations/' + data_file):
times, data = analysis.load_csv_data('simulations/' + data_file,
delimiter=delimiter)
print("Loaded data with %i times & %i datapoints from %s" %
(len(times), len(data), data_file))
results = analysis.max_min(data, times)
Spike_time_array = np.asarray(results['maxima_times'])
Spike_time_aray = np.transpose(Spike_time_array)
print results['maxima_times']
np.savetxt('simulations/txt/Golgi_pop0_0_NEURON_V2010multi1_1c_1input.txt',
Spike_time_array,
fmt='%f',
newline=" ")
return results['maxima_times']
def get_real_data(self):
data_file = 'Gran_0.dat'
delimiter = '\t'
if os.path.isfile(data_file):
times, data = analysis.load_csv_data(data_file, delimiter=delimiter)
elif os.path.isfile('test/'+data_file):
times, data = analysis.load_csv_data('test/'+data_file, delimiter=delimiter)
print("Loaded data with %i times & %i datapoints from %s"%(len(times),len(data),data_file))
return times, data
def get_real_data(self):
data_file = 'Gran_0.dat'
delimiter = '\t'
if os.path.isfile(data_file):
times, data = analysis.load_csv_data(data_file,
delimiter=delimiter)
elif os.path.isfile('test/' + data_file):
times, data = analysis.load_csv_data('test/' + data_file,
delimiter=delimiter)
print("Loaded data with %i times & %i datapoints from %s" %
(len(times), len(data), data_file))
return times, data
def get_spike_times(data_file):
delimiter = '\t'
if os.path.isfile(data_file):
times, data = analysis.load_csv_data(data_file, delimiter=delimiter)
elif os.path.isfile('simulations/'+data_file):
times, data = analysis.load_csv_data('simulations/'+data_file, delimiter=delimiter)
print("Loaded data with %i times & %i datapoints from %s"%(len(times),len(data),data_file))
results = analysis.max_min(data, times)
Spike_time_array=np.asarray(results['maxima_times'])
Spike_time_aray=np.transpose(Spike_time_array)
print results['maxima_times']
np.savetxt('simulations/txt/Golgi_pop0_0_NEURON_V2010multi1_1c_1input.txt',Spike_time_array,fmt='%f',newline=" ")
return results['maxima_times']
def __init__(self,
analysis_start_time,
controller,
analysis_end_time,
target_data_path,
parameters,
analysis_var,
weights,
targets=None,
automatic=False):
super(IClampEvaluator, self).__init__(parameters,
weights,
targets,
controller)
self.analysis_start_time=analysis_start_time
self.analysis_end_time=analysis_end_time
self.target_data_path=target_data_path
self.analysis_var=analysis_var
print 'target data path in evaluator:'
print target_data_path
if automatic == True:
t , v_raw = analysis.load_csv_data(target_data_path)
v = numpy.array(v_raw)
v_smooth = list(analysis.smooth(v))
analysis = analysis.IClampAnalysis(v_smooth,
t,
analysis_var,
start_analysis=analysis_start_time,
end_analysis=analysis_end_time)
analysis.analyse()
self.targets = analysis.analysis_results
print('Obtained targets are:')
print(self.targets)
def __init__(self,
analysis_start_time,
controller,
analysis_end_time,
target_data_path,
parameters,
analysis_var,
weights,
targets=None,
automatic=False):
super(IClampEvaluator, self).__init__(parameters, weights, targets,
controller)
self.analysis_start_time = analysis_start_time
self.analysis_end_time = analysis_end_time
self.target_data_path = target_data_path
self.analysis_var = analysis_var
print('target data path in evaluator:' + target_data_path)
if automatic == True:
t, v_raw = analysis.load_csv_data(target_data_path)
v = numpy.array(v_raw)
v_smooth = list(analysis.smooth(v))
ic_analysis = analysis.IClampAnalysis(
v_smooth,
t,
analysis_var,
start_analysis=analysis_start_time,
end_analysis=analysis_end_time)
ic_analysis.analyse()
self.targets = ic_analysis.analysis_results
print('Obtained targets are:')
print(self.targets)
from pyelectro import analysis as pye_analysis
from matplotlib import pyplot
file_name = '100pA_1a.csv'
t, v = pye_analysis.load_csv_data(file_name)
analysis_var = {
'peak_delta': 0.1,
'baseline': 0,
'dvdt_threshold': 2,
'peak_threshold': 0
}
analysis = pye_analysis.IClampAnalysis(v,
t,
analysis_var,
start_analysis=150,
end_analysis=900)
res = analysis.analyse()
print res
pyplot.plot(t, v)
pyplot.suptitle('Data read in from: %s' % file_name)
pyplot.show()
from pyelectro import analysis as pye_analysis
from matplotlib import pyplot
file_name = '100pA_1a.csv'
t,v=pye_analysis.load_csv_data(file_name)
analysis_var={'peak_delta':0.1,'baseline':0,'dvdt_threshold':2,'peak_threshold':0}
analysis=pye_analysis.IClampAnalysis(v,
t,
analysis_var,
start_analysis=150,
end_analysis=900)
res = analysis.analyse()
print res
pyplot.plot(t,v)
pyplot.suptitle('Data read in from: %s'%file_name)
pyplot.show()
