HG_REPOSITORIES/LPP/INSTRUMENTATION/USERS/JEANDET/SciQLOPCore Files · tests/TestVariables.py

New TimeSeries classes mostly usable from Python...

New TimeSeries classes mostly usable from Python Signed-off-by: Alexis Jeandet <alexis.jeandet@member.fsf.org>

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             TestVariables.py
        
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        jeandet
    
More work on new Variable python bindings...

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      import sys

      import os

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      if not hasattr(sys, 'argv') or len(sys.argv)==0:

          sys.argv = ['']

      current_script_path = os.path.dirname(os.path.realpath(__file__))

      sys.path.append(current_script_path)

        jeandet
    
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      import sciqlopqt

      import pysciqlopcore

      import numpy as np

        jeandet
    
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      import pandas as pds

        jeandet
    
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      import datetime

      import time

      import unittest

      import ddt

      def listify(obj):

          if hasattr(obj, "__getitem__"):

              return obj

          return [obj]

      @ddt.ddt

      class TimeSeriesCtors(unittest.TestCase):

          @ddt.data(

                   (pysciqlopcore.ScalarTimeSerie,10),

                   (pysciqlopcore.VectorTimeSerie,10),

        jeandet
    
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                   (pysciqlopcore.SpectrogramTimeSerie,[10,10])

        jeandet
    
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          )

          def test_construct(self, case):

              ts = case[0](case[1])

              self.assertEqual(ts.shape,listify(case[1]))

      class TimeSeriesData(unittest.TestCase):

          def test_set_ScalarTimeSerie_values(self):

              ts = pysciqlopcore.ScalarTimeSerie(10)

              ts.t[0]=111.

              self.assertEqual(ts.t[0],111.)

              ts[0]=123.

              self.assertEqual(ts[0],123.)

          def test_build_ScalarTimeSerie_from_np_arrays(self):

        jeandet
    
New TimeSeries classes mostly usable from Python...

              r65
            
              ts = pysciqlopcore.ScalarTimeSerie(np.arange(10), np.arange(10)*10)

              for i in range(len(ts)):

                  self.assertEqual(ts[i],i*10.)

        jeandet
    
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              r63
            
        jeandet
    
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              r64
            
          def test_build_VectorTimeSerie_from_np_arrays(self):

        jeandet
    
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              v=np.ones((3,10))

              for i in range(3):

                  v[:][i] = np.arange(10)*10**i

              ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)

              for i in range(len(ts)):

                  self.assertEqual(ts[i].x,i)

                  self.assertEqual(ts[i].y,i*10.)

                  self.assertEqual(ts[i].z,i*100.)

          def test_build_VectorTimeSerie_from_np_arrays_row(self):

              v=np.ones((10,3))

              for i in range(3):

                  v.transpose()[:][i] = np.arange(10)*10**i

              ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)

              for i in range(len(ts)):

                  self.assertEqual(ts[i].x,i)

                  self.assertEqual(ts[i].y,i*10.)

                  self.assertEqual(ts[i].z,i*100.)

          def test_build_VectorTimeSerie_from_np_dataframe(self):

              df = pds.DataFrame(data=np.zeros((10,3)),index=np.arange(10))

              for i in range(3):

                  df[i] = np.arange(10)*10**i

              ts = pysciqlopcore.VectorTimeSerie(df.index.values, df.values)

              for i in range(len(ts)):

                  self.assertEqual(ts[i].x,i)

                  self.assertEqual(ts[i].y,i*10.)

                  self.assertEqual(ts[i].z,i*100.)

          def test_build_SpectrogramTimeSerie_from_np_arrays(self):

              v=np.ones((4,10))

              for i in range(4):

                  v[:][i] = np.arange(10)*10**i

              ts = pysciqlopcore.SpectrogramTimeSerie(np.arange(10), v)

              for i in range(len(ts)):

                  for j in range(4):

                      print(f"ts[{i}][{j}] = " + str(ts[i][j]))

        jeandet
    
Added vector build from numpy arrays...

              r64
            
        jeandet
    
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              r63
            
      if __name__ == '__main__':

        jeandet
    
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          unittest.main(exit=False)

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jeandet More work on new Variable python bindings...	r63	import sys
		import os
jeandet New TimeSeries classes mostly usable from Python...	r65	if not hasattr(sys, 'argv') or len(sys.argv)==0:
		sys.argv = ['']
		current_script_path = os.path.dirname(os.path.realpath(__file__))
		sys.path.append(current_script_path)
jeandet More work on new Variable python bindings...	r63
		import sciqlopqt
		import pysciqlopcore

		import numpy as np
jeandet New TimeSeries classes mostly usable from Python...	r65	import pandas as pds
jeandet More work on new Variable python bindings...	r63	import datetime
		import time
		import unittest
		import ddt

		def listify(obj):
		if hasattr(obj, "__getitem__"):
		return obj
		return [obj]

		@ddt.ddt
		class TimeSeriesCtors(unittest.TestCase):
		@ddt.data(
		(pysciqlopcore.ScalarTimeSerie,10),
		(pysciqlopcore.VectorTimeSerie,10),
jeandet New TimeSeries classes mostly usable from Python...	r65	(pysciqlopcore.SpectrogramTimeSerie,[10,10])
jeandet More work on new Variable python bindings...	r63	)
		def test_construct(self, case):
		ts = case[0](case[1])
		self.assertEqual(ts.shape,listify(case[1]))

		class TimeSeriesData(unittest.TestCase):
		def test_set_ScalarTimeSerie_values(self):
		ts = pysciqlopcore.ScalarTimeSerie(10)
		ts.t[0]=111.
		self.assertEqual(ts.t[0],111.)
		ts[0]=123.
		self.assertEqual(ts[0],123.)

		def test_build_ScalarTimeSerie_from_np_arrays(self):
jeandet New TimeSeries classes mostly usable from Python...	r65	ts = pysciqlopcore.ScalarTimeSerie(np.arange(10), np.arange(10)*10)
		for i in range(len(ts)):
		self.assertEqual(ts[i],i*10.)
jeandet More work on new Variable python bindings...	r63
jeandet Added vector build from numpy arrays...	r64	def test_build_VectorTimeSerie_from_np_arrays(self):
jeandet New TimeSeries classes mostly usable from Python...	r65	v=np.ones((3,10))
		for i in range(3):
		v[:][i] = np.arange(10)10*i
		ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)
		for i in range(len(ts)):
		self.assertEqual(ts[i].x,i)
		self.assertEqual(ts[i].y,i*10.)
		self.assertEqual(ts[i].z,i*100.)

		def test_build_VectorTimeSerie_from_np_arrays_row(self):
		v=np.ones((10,3))
		for i in range(3):
		v.transpose()[:][i] = np.arange(10)10*i
		ts = pysciqlopcore.VectorTimeSerie(np.arange(10), v)
		for i in range(len(ts)):
		self.assertEqual(ts[i].x,i)
		self.assertEqual(ts[i].y,i*10.)
		self.assertEqual(ts[i].z,i*100.)

		def test_build_VectorTimeSerie_from_np_dataframe(self):
		df = pds.DataFrame(data=np.zeros((10,3)),index=np.arange(10))
		for i in range(3):
		df[i] = np.arange(10)10*i
		ts = pysciqlopcore.VectorTimeSerie(df.index.values, df.values)
		for i in range(len(ts)):
		self.assertEqual(ts[i].x,i)
		self.assertEqual(ts[i].y,i*10.)
		self.assertEqual(ts[i].z,i*100.)

		def test_build_SpectrogramTimeSerie_from_np_arrays(self):
		v=np.ones((4,10))
		for i in range(4):
		v[:][i] = np.arange(10)10*i
		ts = pysciqlopcore.SpectrogramTimeSerie(np.arange(10), v)
		for i in range(len(ts)):
		for j in range(4):
		print(f"ts[{i}][{j}] = " + str(ts[i][j]))

jeandet Added vector build from numpy arrays...	r64
jeandet More work on new Variable python bindings...	r63	if __name__ == '__main__':
jeandet New TimeSeries classes mostly usable from Python...	r65	unittest.main(exit=False)