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import sys
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import os
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if not hasattr(sys, 'argv') or len(sys.argv)==0:
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sys.argv = ['']
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current_script_path = os.path.dirname(os.path.realpath(__file__))
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sys.path.append(current_script_path)
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import sciqlopqt
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import pysciqlopcore
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import numpy as np
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import pandas as pds
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import datetime
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import time
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import unittest
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import ddt
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def listify(obj):
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if hasattr(obj, "__getitem__"):
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return obj
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return [obj]
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@ddt.ddt
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class TimeSeriesCtors(unittest.TestCase):
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@ddt.data(
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(pysciqlopcore.ScalarTimeSerie,10),
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(pysciqlopcore.VectorTimeSerie,10),
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(pysciqlopcore.SpectrogramTimeSerie,[10,10])
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)
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def test_construct(self, case):
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ts = case[0](case[1])
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self.assertEqual(ts.shape,listify(case[1]))
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class TimeSeriesData(unittest.TestCase):
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def test_set_ScalarTimeSerie_values(self):
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ts = pysciqlopcore.ScalarTimeSerie(10)
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ts.t[0]=111.
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self.assertEqual(ts.t[0],111.)
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ts[0]=123.
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self.assertEqual(ts[0],123.)
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def test_build_ScalarTimeSerie_from_np_arrays(self):
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ts = pysciqlopcore.ScalarTimeSerie(np.arange(10), np.arange(10)*10)
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for i in range(len(ts)):
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self.assertEqual(ts[i],i*10.)
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def test_build_VectorTimeSerie_from_np_arrays(self):
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v=np.ones((3,10))
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for i in range(3):
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v[:][i] = np.arange(10)*10**i
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ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)
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for i in range(len(ts)):
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self.assertEqual(ts[i].x,i)
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self.assertEqual(ts[i].y,i*10.)
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self.assertEqual(ts[i].z,i*100.)
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def test_build_VectorTimeSerie_from_np_arrays_row(self):
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v=np.ones((10,3))
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for i in range(3):
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v.transpose()[:][i] = np.arange(10)*10**i
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ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)
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for i in range(len(ts)):
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self.assertEqual(ts[i].x,i)
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self.assertEqual(ts[i].y,i*10.)
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self.assertEqual(ts[i].z,i*100.)
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def test_build_VectorTimeSerie_from_np_dataframe(self):
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df = pds.DataFrame(data=np.zeros((10,3)),index=np.arange(10))
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for i in range(3):
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df[i] = np.arange(10)*10**i
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ts = pysciqlopcore.VectorTimeSerie(df.index.values, df.values)
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for i in range(len(ts)):
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self.assertEqual(ts[i].x,i)
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self.assertEqual(ts[i].y,i*10.)
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self.assertEqual(ts[i].z,i*100.)
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def test_build_SpectrogramTimeSerie_from_np_arrays(self):
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v=np.ones((4,10))
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for i in range(4):
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v[:][i] = np.arange(10)*10**i
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ts = pysciqlopcore.SpectrogramTimeSerie(np.arange(10), v)
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for i in range(len(ts)):
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for j in range(4):
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print(f"ts[{i}][{j}] = " + str(ts[i][j]))
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if __name__ == '__main__':
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unittest.main(exit=False)
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