upstream/ipython Files · IPython/extensions/tests/test_rmagic.py

Backport PR : Fix: longest_substr([]) -> ''...

Backport PR : Fix: longest_substr([]) -> '' Previously the algorithm used to find the longest common starting substring unintentionally raised an error when it was called on an empty list. This should fix the issue of an error being raised when running %paste on an empty clipboard (#2252).

Jonathan Taylor - - Load All Authors

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             test_rmagic.py
        
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        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
      import numpy as np

      from IPython.core.interactiveshell import InteractiveShell

      from IPython.extensions import rmagic

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
      import nose.tools as nt

        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
        Jonathan Taylor
    
fixing InteractiveShell instantiation in test

              r7222
            
      ip = get_ipython()

      ip.magic('load_ext rmagic')

        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
      def test_push():

          rm = rmagic.RMagics(ip)

          ip.push({'X':np.arange(5), 'Y':np.array([3,5,4,6,7])})

          ip.run_line_magic('Rpush', 'X Y')

          np.testing.assert_almost_equal(np.asarray(rm.r('X')), ip.user_ns['X'])

          np.testing.assert_almost_equal(np.asarray(rm.r('Y')), ip.user_ns['Y'])

      def test_pull():

          rm = rmagic.RMagics(ip)

          rm.r('Z=c(11:20)')

          ip.run_line_magic('Rpull', 'Z')

          np.testing.assert_almost_equal(np.asarray(rm.r('Z')), ip.user_ns['Z'])

          np.testing.assert_almost_equal(ip.user_ns['Z'], np.arange(11,21))

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
      def test_Rconverter():

          datapy= np.array([(1, 2.9, 'a'), (2, 3.5, 'b'), (3, 2.1, 'c')], 

                dtype=[('x', '<i4'), ('y', '<f8'), ('z', '|S1')])

          ip.user_ns['datapy'] = datapy

          ip.run_line_magic('Rpush', 'datapy')

          # test to see if a copy is being made

        Jonathan Taylor
    
added Rget, and options to try to return strucutred array

              r7276
            
          v = ip.run_line_magic('Rget', '-d datapy')

          w = ip.run_line_magic('Rget', '-d datapy')

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
          np.testing.assert_almost_equal(w['x'], v['x'])

          np.testing.assert_almost_equal(w['y'], v['y'])

          nt.assert_true(np.all(w['z'] == v['z']))

          np.testing.assert_equal(id(w.data), id(v.data))

          nt.assert_equal(w.dtype, v.dtype)

        Jonathan Taylor
    
added Rget, and options to try to return strucutred array

              r7276
            
          ip.run_cell_magic('R', ' -d datar  datar=datapy', '')

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
        Jonathan Taylor
    
added Rget, and options to try to return strucutred array

              r7276
            
          u = ip.run_line_magic('Rget', ' -d datar')

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
          np.testing.assert_almost_equal(u['x'], v['x'])

          np.testing.assert_almost_equal(u['y'], v['y'])

          nt.assert_true(np.all(u['z'] == v['z']))

          np.testing.assert_equal(id(u.data), id(v.data))

          nt.assert_equal(u.dtype, v.dtype)

        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
      def test_cell_magic():

          ip.push({'x':np.arange(5), 'y':np.array([3,5,4,6,7])})

          snippet = '''

          print(summary(a))

        Jonathan Taylor
    
return vectors instead of structured arrays when 1d and no names

              r7268
            
          plot(x, y, pch=23, bg='orange', cex=2)

          plot(x, x)

          print(summary(x))

        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
          r = resid(a)

          xc = coef(a)

          '''

        Jonathan Taylor
    
removed %Rinline, %R has been converted to line_cell_magic

              r7217
            
          ip.run_cell_magic('R', '-i x,y -o r,xc a=lm(y~x)', snippet)

        Jonathan Taylor
    
added tests of R line and cell magics

              r7215
            
          np.testing.assert_almost_equal(ip.user_ns['xc'], [3.2, 0.9])

          np.testing.assert_almost_equal(ip.user_ns['r'], np.array([-0.2,  0.9, -1. ,  0.1,  0.2]))

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Jonathan Taylor added tests of R line and cell magics	r7215	import numpy as np
		from IPython.core.interactiveshell import InteractiveShell
		from IPython.extensions import rmagic
Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268	import nose.tools as nt
Jonathan Taylor added tests of R line and cell magics	r7215
Jonathan Taylor fixing InteractiveShell instantiation in test	r7222	ip = get_ipython()
		ip.magic('load_ext rmagic')

Jonathan Taylor added tests of R line and cell magics	r7215
		def test_push():
		rm = rmagic.RMagics(ip)
		ip.push({'X':np.arange(5), 'Y':np.array([3,5,4,6,7])})
		ip.run_line_magic('Rpush', 'X Y')
		np.testing.assert_almost_equal(np.asarray(rm.r('X')), ip.user_ns['X'])
		np.testing.assert_almost_equal(np.asarray(rm.r('Y')), ip.user_ns['Y'])

		def test_pull():
		rm = rmagic.RMagics(ip)
		rm.r('Z=c(11:20)')
		ip.run_line_magic('Rpull', 'Z')
		np.testing.assert_almost_equal(np.asarray(rm.r('Z')), ip.user_ns['Z'])
		np.testing.assert_almost_equal(ip.user_ns['Z'], np.arange(11,21))

Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268	def test_Rconverter():
		datapy= np.array([(1, 2.9, 'a'), (2, 3.5, 'b'), (3, 2.1, 'c')],
		dtype=[('x', '<i4'), ('y', '<f8'), ('z', '\|S1')])
		ip.user_ns['datapy'] = datapy
		ip.run_line_magic('Rpush', 'datapy')

		# test to see if a copy is being made
Jonathan Taylor added Rget, and options to try to return strucutred array	r7276	v = ip.run_line_magic('Rget', '-d datapy')
		w = ip.run_line_magic('Rget', '-d datapy')
Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268	np.testing.assert_almost_equal(w['x'], v['x'])
		np.testing.assert_almost_equal(w['y'], v['y'])
		nt.assert_true(np.all(w['z'] == v['z']))
		np.testing.assert_equal(id(w.data), id(v.data))
		nt.assert_equal(w.dtype, v.dtype)

Jonathan Taylor added Rget, and options to try to return strucutred array	r7276	ip.run_cell_magic('R', ' -d datar datar=datapy', '')
Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268
Jonathan Taylor added Rget, and options to try to return strucutred array	r7276	u = ip.run_line_magic('Rget', ' -d datar')
Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268	np.testing.assert_almost_equal(u['x'], v['x'])
		np.testing.assert_almost_equal(u['y'], v['y'])
		nt.assert_true(np.all(u['z'] == v['z']))
		np.testing.assert_equal(id(u.data), id(v.data))
		nt.assert_equal(u.dtype, v.dtype)

Jonathan Taylor added tests of R line and cell magics	r7215
		def test_cell_magic():

		ip.push({'x':np.arange(5), 'y':np.array([3,5,4,6,7])})
		snippet = '''
		print(summary(a))
Jonathan Taylor return vectors instead of structured arrays when 1d and no names	r7268	plot(x, y, pch=23, bg='orange', cex=2)
		plot(x, x)
		print(summary(x))
Jonathan Taylor added tests of R line and cell magics	r7215	r = resid(a)
		xc = coef(a)
		'''
Jonathan Taylor removed %Rinline, %R has been converted to line_cell_magic	r7217	ip.run_cell_magic('R', '-i x,y -o r,xc a=lm(y~x)', snippet)
Jonathan Taylor added tests of R line and cell magics	r7215	np.testing.assert_almost_equal(ip.user_ns['xc'], [3.2, 0.9])
		np.testing.assert_almost_equal(ip.user_ns['r'], np.array([-0.2, 0.9, -1. , 0.1, 0.2]))