def test_corr2():
t = [1, 2, 3, 4]
v = [40, 50, 60, 70]
t2 = [1, 2, 3, 4]
v2 = [40, 50, 60, 70]
row = {}
row['ts'] = ts.TimeSeries(t,v)
#Since its the same time series, the correlation here should be zero
assert(corr.proc_main(1, row, (t2, v2))[0] == 0)
def test_corr2():
t = [1, 2, 3, 4]
v = [40, 50, 60, 70]
t2 = [1, 2, 3, 4]
v2 = [40, 50, 60, 70]
row = {}
row['ts'] = ts.TimeSeries(t, v)
#Since its the same time series, the correlation here should be zero
assert (corr.proc_main(1, row, (t2, v2))[0] == 0)
def test_corr_small():
from procs.corr import proc_main
ts_l = [10, 22, 26, 4, 18]
ts_l_x = range(len(ts_l))
ts_ts = ts.TimeSeries(ts_l_x, ts_l).to_json()
# print (ts_ts)
res = proc_main(None, {'ts': ts_ts}, {'times': ts_l_x, 'values': ts_l})
# print (res)
assert np.abs(res) < EPS
def test_corr_small():
from procs.corr import proc_main
ts_l = [10, 22, 26, 4, 18]
ts_l_x = range(len(ts_l))
ts_ts = ts.TimeSeries(ts_l_x, ts_l).to_json()
# print (ts_ts)
res = proc_main(None, {'ts':ts_ts}, {'times':ts_l_x, 'values':ts_l})
# print (res)
assert np.abs(res) < EPS
