90 lines
3.3 KiB
Python
90 lines
3.3 KiB
Python
import unittest
|
|
import numpy as np
|
|
from my_util import helperFunctions as hF
|
|
from parser.CellData import icelldata_of_dir
|
|
from experiments.Baseline import BaselineCellData
|
|
import os
|
|
|
|
|
|
class HelperFunctionsTester(unittest.TestCase):
|
|
reference_base_spikes = {'2012-12-21-an-invivo-1': 39, '2012-07-12-ag-invivo-1': 21, '2012-12-13-ac-invivo-1': 19,
|
|
'2012-12-20-ac-invivo-1': 43, '2013-01-08-ad-invivo-1': 29, '2012-06-27-an-invivo-1': 19,
|
|
'2012-12-13-ah-invivo-1': 35, '2012-12-13-ag-invivo-1': 26, '2012-12-13-an-invivo-1': 29,
|
|
'2012-12-21-ai-invivo-1': 55, '2012-12-20-aa-invivo-1': 24, '2012-12-21-am-invivo-1': 26,
|
|
'2012-06-27-ah-invivo-1': 27, '2012-07-12-ap-invivo-1': 35, '2012-12-21-ak-invivo-1': 30}
|
|
|
|
noise_levels = [0, 0.05, 0.1, 0.2]
|
|
frequencies = [0, 1, 5, 30, 100, 500, 750, 1000]
|
|
|
|
def setUp(self):
|
|
pass
|
|
|
|
def tearDown(self):
|
|
pass
|
|
|
|
def test__vector_strength__is_1(self):
|
|
length = 2000
|
|
rel_spike_times = np.full(length, 0.3)
|
|
eod_durations = np.full(length, 0.14)
|
|
|
|
self.assertEqual(1, round(hF.__vector_strength__(rel_spike_times,eod_durations), 2))
|
|
|
|
def test__vector_strength__is_0(self):
|
|
length = 2000
|
|
period = 0.14
|
|
rel_spike_times = np.arange(0, period, period/length)
|
|
eod_durations = np.full(length, period)
|
|
|
|
self.assertEqual(0, round(hF.__vector_strength__(rel_spike_times, eod_durations), 5))
|
|
|
|
def test_detect_spiketimes(self):
|
|
count = 0
|
|
for cell_data in icelldata_of_dir("../data/"):
|
|
if os.path.basename(cell_data.get_data_path()) not in self.reference_base_spikes:
|
|
continue
|
|
|
|
print(cell_data.get_data_path())
|
|
# if "21-ai" not in cell_data.get_data_path() and "20-ac" not in cell_data.get_data_path():
|
|
# continue
|
|
|
|
spikes = np.array(cell_data.get_base_spikes()[0])
|
|
|
|
time_length = 0.2
|
|
time = cell_data.get_base_traces(cell_data.TIME)[0]
|
|
length_data_points = int(time_length / cell_data.get_sampling_interval())
|
|
|
|
start_idx = 0
|
|
end_idx = length_data_points + 1
|
|
end_idx = end_idx if end_idx <= len(time) else len(time)
|
|
|
|
bot_lim_spikes = spikes[spikes > time[start_idx]]
|
|
top_lim_spikes = bot_lim_spikes[bot_lim_spikes < time[end_idx]]
|
|
|
|
expected = self.reference_base_spikes[os.path.basename(cell_data.get_data_path())]
|
|
if len(top_lim_spikes) == expected:
|
|
print("yay")
|
|
else:
|
|
|
|
print("detected: {:}, reference: {:}".format(len(top_lim_spikes), expected))
|
|
print("nay")
|
|
baseline = BaselineCellData(cell_data)
|
|
baseline.plot_baseline(position=0, time_length=0.2)
|
|
|
|
count += 1
|
|
|
|
def test_automatic_splitting(self):
|
|
for cell_data in icelldata_of_dir("../data/"):
|
|
print(cell_data.get_data_path())
|
|
v1 = cell_data.get_base_traces(cell_data.V1)[0]
|
|
|
|
hF.detect_spike_indices_automatic_split(v1, 2.8)
|
|
|
|
# todo
|
|
# search_eod_start_and_end_times ? (not used anymore ?)
|
|
# eods_around_spikes
|
|
# calculate_phases
|
|
|
|
# def test(self):
|
|
# test_distribution()
|
|
|