diff options
Diffstat (limited to 'Examples/Tests/Langmuir/langmuir_analysis.py')
| -rwxr-xr-x | Examples/Tests/Langmuir/langmuir_analysis.py | 32 |
1 files changed, 13 insertions, 19 deletions
diff --git a/Examples/Tests/Langmuir/langmuir_analysis.py b/Examples/Tests/Langmuir/langmuir_analysis.py index 578ecc8b7..2ffb7f56b 100755 --- a/Examples/Tests/Langmuir/langmuir_analysis.py +++ b/Examples/Tests/Langmuir/langmuir_analysis.py @@ -48,33 +48,27 @@ E_predicted = m_e * wp * u * c / e * np.sin(wp*t) # at the edges of the plasma if direction == 'x': E = data[ 'Ex' ].to_ndarray() - # compute and print errors - max_rel_error_nonzero = np.max(np.abs((E[2:30,:,:]-E_predicted)/E_predicted)) - max_rel_error_zero = np.max(E[34:-2,:,:]) - print('relative error: %s' %max_rel_error_nonzero) - print('absolute field error (where field should be 0): %s' %max_rel_error_zero) - # assert small errors + # Print errors, and assert small error + print( "relative error: np.max( np.abs( ( E[2:30,:,:] - E_predicted ) / E_predicted ) ) = %s" \ + %np.max( np.abs( ( E[2:30,:,:] - E_predicted ) / E_predicted ) ) ) assert np.allclose( E[2:30,:,:], E_predicted, rtol=0.1 ) - assert np.allclose( E[34:-2,:,:], 0, atol=2.e-5 ) + print( "absolute error: np.max( np.abs( E[34:-2,:,:] ) ) = %s" %np.max( np.abs( E[34:-2,:,:] ) ) ) + assert np.allclose( E[34:-2,:,:], 0, atol=5.e-5 ) elif direction == 'y': E = data[ 'Ey' ].to_ndarray() - # compute and print errors - max_rel_error_nonzero = np.max(np.abs((E[:,2:30,:]-E_predicted)/E_predicted)) - max_rel_error_zero = np.max(E[:,34:-2,:]) - print('relative error: %s' %max_rel_error_nonzero) - print('absolute field error (where field should be 0): %s' %max_rel_error_zero) - # assert small errors + # Print errors, and assert small error + print( "relative error: np.max( np.abs( ( E[:,2:30,:] - E_predicted ) / E_predicted ) ) = %s" \ + %np.max( np.abs( ( E[:,2:30,:] - E_predicted ) / E_predicted ) ) ) assert np.allclose( E[:,2:30,:], E_predicted, rtol=0.1 ) + print( "absolute error: np.max( np.abs( E[:,34:-2,:] ) ) = %s" %np.max( np.abs( E[:,34:-2,:] ) ) ) assert np.allclose( E[:,34:-2,:], 0, atol=2.e-5 ) elif direction == 'z': E = data[ 'Ez' ].to_ndarray() - # compute and print errors - max_rel_error_nonzero = np.max(np.abs((E[:,:,2:30]-E_predicted)/E_predicted)) - max_rel_error_zero = np.max(E[:,:,34:-2]) - print('relative error: %s' %max_rel_error_nonzero) - print('absolute field error (where field should be 0): %s' %max_rel_error_zero) - # assert small errors + # Print errors, and assert small error + print( "relative error: np.max( np.abs( ( E[:,:,2:30] - E_predicted ) / E_predicted ) ) = %s" \ + %np.max( np.abs( ( E[:,:,2:30] - E_predicted ) / E_predicted ) ) ) assert np.allclose( E[:,:,2:30], E_predicted, rtol=0.1 ) + print( "absolute error: np.max( np.abs( E[:,:,34:-2] ) ) = %s" %np.max( np.abs( E[:,:,34:-2] ) ) ) assert np.allclose( E[:,:,34:-2], 0, atol=2.e-5 ) # Save an image to be displayed on the website |