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()