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RTest: more verbose outputs for lin comparison and only abort at the end
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@ebranlard
ebranlard committed Aug 3, 2023
1 parent d4014b2 commit cc9a734
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Showing 2 changed files with 165 additions and 129 deletions.
278 changes: 157 additions & 121 deletions reg_tests/executeOpenfastLinearRegressionCase.py
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Original file line number Diff line number Diff line change
Expand Up @@ -178,128 +178,164 @@ def indent(msg, sindent='\t'):
exitWithError("An expected local solution file does not exist:")

### test for regression (compare lin files only)
try:
for i, f in enumerate(localOutFiles):
local_file = os.path.join(testBuildDirectory, f)
baseline_file = os.path.join(targetOutputDirectory, f)

def compareLin(f):
Errors = []
ElemErrors = []

local_file = os.path.join(testBuildDirectory, f)
baseline_file = os.path.join(targetOutputDirectory, f)
local_file2 = local_file # Ellude the long filename

# Set a prefix for all errors to identify where it comes from
basename = os.path.splitext(os.path.basename(local_file))[0]
ext2 = os.path.splitext(basename)[1][1:] +'.lin' # '.1' or '.AD' '.BD'
errPrefix = CasePrefix[:-1]+ext2+': '

if verbose:
print(errPrefix+'file_ref:', baseline_file)
print(errPrefix+'file_new:', local_file)

def newError(msg):
msg=errPrefix+msg
if verbose:
print(CasePrefix+'ref:', baseline_file)
print(CasePrefix+'new:', local_file)

# verify both files have the same number of lines
local_file_line_count = file_line_count(local_file)
baseline_file_line_count = file_line_count(baseline_file)
if local_file_line_count != baseline_file_line_count:
Err="Local and baseline solutions have different line counts in"
Err+="\n\tFile1:{}".format(local_file)
Err+="\n\tFile2:{}\n\n".format(baseline_file)
raise Exception(Err)

# open both files
floc = FASTLinearizationFile(local_file)
fbas = FASTLinearizationFile(baseline_file)

# --- Test that they have the same variables
kloc = floc.keys()
kbas = fbas.keys()
try:
np.testing.assert_equal(kloc, kbas)
except Exception as e:
Err = 'Different keys in local linfile.\n'
Err+= '\tNew:{}\n'.format(kloc)
Err+= '\tRef:{}\n'.format(kbas)
Err+= '\tin linfile: {}.\n'.format(local_file)
raise Exception(Err)

# --- Compare 10 first frequencies and damping ratios in 'A' matrix
if 'A' in fbas.keys():
Abas = fbas['A']
Aloc = floc['A']
# Note: we could potentially reorder states like MBC does, but no need for freq/damping
_, zeta_bas, _, freq_bas = eigA(Abas, nq=None, nq1=None, sort=True)
_, zeta_loc, _, freq_loc = eigA(Aloc, nq=None, nq1=None, sort=True)

if len(freq_bas)==0:
# We use complex eigenvalues instead of frequencies/damping
# If this fails often, we should discard this test.
_, Lambda = eig(Abas, sort=False)
v_bas = np.diag(Lambda)
_, Lambda = eig(Aloc, sort=False)
v_loc = np.diag(Lambda)

if verbose:
print(CasePrefix+'val_ref:', v_bas[:7])
print(CasePrefix+'val_new:', v_loc[:7])
try:
np.testing.assert_allclose(v_bas[:10], v_loc[:10], rtol=rtol_f, atol=atol_f)
except Exception as e:
raise Exception('Failed to compare A-matrix frequencies\n\tLinfile: {}.\n\tException: {}'.format(local_file, indent(e.args[0])))
else:

#if verbose:
print(CasePrefix+'freq_ref:', np.around(freq_bas[:8] ,5), '[Hz]')
print(CasePrefix+'freq_new:', np.around(freq_loc[:8] ,5),'[Hz]')
print(CasePrefix+'damp_ref:', np.around(zeta_bas[:8]*100,5), '[%]')
print(CasePrefix+'damp_new:', np.around(zeta_loc[:8]*100,5), '[%]')

try:
np.testing.assert_allclose(freq_loc[:10], freq_bas[:10], rtol=rtol_f, atol=atol_f)
except Exception as e:
raise Exception('Failed to compare A-matrix frequencies\n\tLinfile: {}.\n\tException: {}'.format(local_file, indent(e.args[0])))


if caseName=='Ideal_Beam_Free_Free_Linear':
# The free-free case is a bit weird, smae frequencies but dampings are +/- a value
zeta_loc=np.abs(zeta_loc)
zeta_bas=np.abs(zeta_bas)


try:
# Note: damping ratios in [%]
np.testing.assert_allclose(zeta_loc[:10]*100, zeta_bas[:10]*100, rtol=rtol_d, atol=atol_d)
except Exception as e:
raise Exception('Failed to compare A-matrix damping ratios\n\tLinfile: {}.\n\tException: {}'.format(local_file, indent(e.args[0])))



# --- Compare individual matrices/vectors
KEYS= ['A','B','C','D','dUdu','dUdy']
KEYS+=['x','y','u','xdot']
for k,v in fbas.items():
if k in KEYS and v is not None:
if verbose:
print(CasePrefix+'key:', k)
# Arrays
Mloc=np.atleast_2d(floc[k])
Mbas=np.atleast_2d(fbas[k])

# --- Compare dimensions
try:
np.testing.assert_equal(Mloc.shape, Mbas.shape)
except Exception as e:
Err = 'Different dimensions for variable `{}`.\n'.format(k)
Err+= '\tNew:{}\n'.format(Mloc.shape)
Err+= '\tRef:{}\n'.format(Mbas.shape)
Err+= '\tLinfile: {}.\n'.format(local_file)
raise Exception(Err)


# We for loop below to get the first element that mismatch
# Otherwise, do: np.testing.assert_allclose(floc[k], fbas[k], rtol=rtol, atol=atol)
for i in range(Mbas.shape[0]):
for j in range(Mbas.shape[1]):
# Old method:
#if not isclose(Mloc[i,j], Mbas[i,j], rtol=rtol, atol=atol):
# sElem = 'Element [{},{}], new : {}, baseline: {}'.format(i+1,j+1,Mloc[i,j], Mbas[i,j])
# raise Exception('Failed to compare variable `{}`, {} \n\tLinfile: {}.'.format(k, sElem, local_file)) #, e.args[0]))
try:
np.testing.assert_allclose(Mloc[i,j], Mbas[i,j], rtol=rtol, atol=atol)
except Exception as e:
sElem = 'Element [{},{}], new : {}, baseline: {}'.format(i+1,j+1,Mloc[i,j], Mbas[i,j])
raise Exception('Failed to compare variable `{}`, {} \n\tLinfile: {}.\n\tException: {}'.format(k, sElem, local_file, indent(e.args[0])))

except Exception as e:
exitWithError(e.args[0])
print(msg)
Errors.append(msg)




# verify both files have the same number of lines
local_file_line_count = file_line_count(local_file)
baseline_file_line_count = file_line_count(baseline_file)
if local_file_line_count != baseline_file_line_count:
Err="Local and baseline solutions have different line counts in"
Err+="\n\tFile1:{}".format(local_file)
Err+="\n\tFile2:{}\n\n".format(baseline_file)
newError(Err)
#raise Exception(Err)

# open both files
floc = FASTLinearizationFile(local_file)
fbas = FASTLinearizationFile(baseline_file)

# --- Test that they have the same variables
kloc = floc.keys()
kbas = fbas.keys()
try:
np.testing.assert_equal(kloc, kbas)
except Exception as e:
Err = 'Different keys in local linfile.\n'
Err+= '\tNew:{}\n'.format(kloc)
Err+= '\tRef:{}\n'.format(kbas)
Err+= '\tin linfile: {}.\n'.format(local_file2)
newError(Err)
#raise Exception(Err)

# --- Compare 10 first frequencies and damping ratios in 'A' matrix
if 'A' in fbas.keys():
Abas = fbas['A']
Aloc = floc['A']
# Note: we could potentially reorder states like MBC does, but no need for freq/damping
_, zeta_bas, _, freq_bas = eigA(Abas, nq=None, nq1=None, sort=True, fullEV=True)
_, zeta_loc, _, freq_loc = eigA(Aloc, nq=None, nq1=None, sort=True, fullEV=True)

if len(freq_bas)==0:
# We use complex eigenvalues instead of frequencies/damping
# If this fails often, we should discard this test.
_, Lambda = eig(Abas, sort=False)
v_bas = np.diag(Lambda)
_, Lambda = eig(Aloc, sort=False)
v_loc = np.diag(Lambda)

if verbose:
print(errPrefix+'val_ref:', v_bas[:7])
print(errPrefix+'val_new:', v_loc[:7])
try:
np.testing.assert_allclose(v_bas[:10], v_loc[:10], rtol=rtol_f, atol=atol_f)
except Exception as e:
Err='Failed to compare A-matrix frequencies\n\tLinfile: {}.\n\tException: {}'.format(local_file2, indent(e.args[0]))
newError(Err)
else:

#if verbose:
print(errPrefix+'freq_ref:', np.around(freq_bas[:8] ,5), '[Hz]')
print(errPrefix+'freq_new:', np.around(freq_loc[:8] ,5),'[Hz]')
print(errPrefix+'damp_ref:', np.around(zeta_bas[:8]*100,5), '[%]')
print(errPrefix+'damp_new:', np.around(zeta_loc[:8]*100,5), '[%]')

try:
np.testing.assert_allclose(freq_loc[:10], freq_bas[:10], rtol=rtol_f, atol=atol_f)
except Exception as e:
Err = 'Failed to compare A-matrix frequencies\n\tLinfile: {}.\n\tException: {}'.format(local_file2, indent(e.args[0]))
newError(Err)


if caseName=='Ideal_Beam_Free_Free_Linear':
# The free-free case is a bit weird, smae frequencies but dampings are +/- a value
zeta_loc=np.abs(zeta_loc)
zeta_bas=np.abs(zeta_bas)


try:
# Note: damping ratios in [%]
np.testing.assert_allclose(zeta_loc[:10]*100, zeta_bas[:10]*100, rtol=rtol_d, atol=atol_d)
except Exception as e:
Err = 'Failed to compare A-matrix damping ratios\n\tLinfile: {}.\n\tException: {}'.format(local_file2, indent(e.args[0]))
newError(Err)

# --- Compare individual matrices/vectors
KEYS= ['A','B','C','D','dUdu','dUdy']
KEYS+=['x','y','u','xdot']
for k,v in fbas.items():
if k in KEYS and v is not None:
if verbose:
print(errPrefix+'key:', k)
# Arrays
Mloc=np.atleast_2d(floc[k])
Mbas=np.atleast_2d(fbas[k])

# --- Compare dimensions
try:
np.testing.assert_equal(Mloc.shape, Mbas.shape)
dimEqual=True
except Exception as e:
Err = 'Different dimensions for variable `{}`.\n'.format(k)
Err+= '\tNew:{}\n'.format(Mloc.shape)
Err+= '\tRef:{}\n'.format(Mbas.shape)
Err+= '\tLinfile: {}.\n'.format(local_file2)
newError(Err)
dimEqual=False

if not dimEqual:
# We don't compare elements if shapes are different
continue

# We for loop below to get the first element that mismatch
# Otherwise, do: np.testing.assert_allclose(floc[k], fbas[k], rtol=rtol, atol=atol)
for i in range(Mbas.shape[0]):
for j in range(Mbas.shape[1]):
# Old method:
#if not isclose(Mloc[i,j], Mbas[i,j], rtol=rtol, atol=atol):
# sElem = 'Element [{},{}], new : {}, baseline: {}'.format(i+1,j+1,Mloc[i,j], Mbas[i,j])
# raise Exception('Failed to compare variable `{}`, {} \n\tLinfile: {}.'.format(k, sElem, local_file)) #, e.args[0]))
try:
np.testing.assert_allclose(Mloc[i,j], Mbas[i,j], rtol=rtol, atol=atol)
except Exception as e:
sElem = 'Element [{},{}], new : {}, baseline: {}'.format(i+1,j+1,Mloc[i,j], Mbas[i,j])
Err=errPrefix+'Failed to compare variable `{}`, {} \n\tLinfile: {}.\n\tException: {}'.format(k, sElem, local_file2, indent(e.args[0]))
ElemErrors.append(Err)
return Errors, ElemErrors

Errors=[]
for i, f in enumerate(localOutFiles):
ErrorsLoc, ElemErrorsLoc = compareLin(f)
Errors += ErrorsLoc
if len(ElemErrorsLoc)>0:
Errors += ElemErrorsLoc[:3] # Just a couple of them

if len(Errors)>0:
exitWithError('See errors below: \n'+'\n'.join(Errors))

# passing case
sys.exit(0)
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16 changes: 8 additions & 8 deletions reg_tests/lib/eva.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -158,18 +158,18 @@ def eigA(A, nq=None, nq1=None, fullEV=False, normQ=None, sort=True):

if m!=n:
raise Exception('Matrix needs to be squared')
if nq is None:
if nq1 is None:
nq1=0
nq = int((n-nq1)/2)
else:
nq1 = n-2*nq
if n!=2*nq+nq1 or nq1<0:
raise Exception('Number of 1st and second order dofs should match the matrix shape (n= 2*nq + nq1')
Q, Lambda = eig(A, sort=False)
v = np.diag(Lambda)

if not fullEV:
if nq is None:
if nq1 is None:
nq1=0
nq = int((n-nq1)/2)
else:
nq1 = n-2*nq
if n!=2*nq+nq1 or nq1<0:
raise Exception('Number of 1st and second order dofs should match the matrix shape (n= 2*nq + nq1')
Q=np.delete(Q, slice(nq,2*nq), axis=0)

# Selecting eigenvalues with positive imaginary part (frequency)
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