Author: tlinnet
Date: Wed May 21 20:36:39 2014
New Revision: 23318
URL: http://svn.gna.org/viewcvs/relax?rev=23318&view=rev
Log:
Code cleanup in systemtest Relax_disp.test_baldwin_synthetic_full.
bug #22021: (https://gna.org/bugs/?22021) Model B14 shows bad fitting to data.
The precision could also be increased with 1 digit.
Modified:
trunk/test_suite/system_tests/relax_disp.py
Modified: trunk/test_suite/system_tests/relax_disp.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/test_suite/system_tests/relax_disp.py?rev=23318&r1=23317&r2=23318&view=diff
==============================================================================
--- trunk/test_suite/system_tests/relax_disp.py (original)
+++ trunk/test_suite/system_tests/relax_disp.py Wed May 21 20:36:39 2014
@@ -593,11 +593,9 @@
# Generate the sequence.
# Generate both a 1H spin, and 15N spin.
self.interpreter.spin.create(res_name='Ala', res_num=1,
spin_name='H')
- self.interpreter.spin.create(res_name='Ala', res_num=2,
spin_name='N')
# Define the isotope.
self.interpreter.spin.isotope('1H', spin_id='@H')
- self.interpreter.spin.isotope('15N', spin_id='@N')
# Build the experiment IDs.
# Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay)
@@ -638,7 +636,6 @@
# Try reading the R2eff file.
self.interpreter.relax_disp.r2eff_read_spin(id="CPMG",
file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1,
data_col=2, error_col=3)
- self.interpreter.relax_disp.r2eff_read_spin(id="CPMG",
file="test_15N_w_error.out", dir=data_path, spin_id=':2@N', disp_point_col=1,
data_col=2, error_col=3)
# Check the global data.
data = [
@@ -686,10 +683,6 @@
## Now prepare for MODEL calculation.
MODEL = "B14 full"
- #MODEL = "CR72 full"
- #MODEL = "NS CPMG 2-site star full"
- #MODEL = "NS CPMG 2-site 3D full"
- #MODEL = "NS CPMG 2-site expanded"
# Change pipe.
pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL)
@@ -726,26 +719,26 @@
# Store result.
for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
- # Store grid results.
- if "r2a" in MODEL_PARAMS[MODEL]:
- grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
- else:
- grid_results.append([spin.r2[r20_key], spin.dw, spin.pA,
spin.kex, spin.chi2, spin_id, resi, resn])
-
+ grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
## Now do minimisation.
# Standard parameters are: func_tol=1e-25, grad_tol=None,
max_iter=10000000,
- set_func_tol = 1e-12
+ set_func_tol = 1e-11
set_max_iter = 10000
self.interpreter.minimise(min_algor='simplex',
func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True,
verbosity=1)
# Store result.
for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
- # Store minimisation results.
- if "r2a" in MODEL_PARAMS[MODEL]:
- mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
- else:
- mini_results.append([spin.r2[r20_key], spin.dw, spin.pA,
spin.kex, spin.chi2, spin_id, resi, resn])
+ mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
+
+ print("\n# Now print before and after minimisation-\n")
+
+ # Print results.
+ for i in range(len(grid_results)):
+ g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi,
g_resn = grid_results[i]
+ m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi,
m_resn = mini_results[i]
+ print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f
chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA,
g_kex, g_chi2, g_spin_id, g_resi, g_resn))
+ print("MIN %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f
chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA,
m_kex, m_chi2, m_spin_id, m_resi, m_resn))
# Reference values from Baldwin.py.
# Exchange rate = k+ + k- (s-1)
@@ -761,89 +754,12 @@
# Test the parameters which created the data.
# This is for the 1H spin.
- if "r2a" in MODEL_PARAMS[MODEL]:
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key],
R2g, 3)
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key],
R2e, 1)
- else:
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key],
R2g, 4)
+ self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g,
4)
+ self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key], R2e,
2)
self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6)
self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6)
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 1)
-
- ## Since the Rex is 5 times as small for N15, it have hard times
finding the values.
- ## So we can try to cluster. But it won't work.
-
- # Change pipe.
- pipe_name_MODEL_CLUSTER = "%s_%s_CLUSTER"%(pipe_name, MODEL)
- self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff,
pipe_to=pipe_name_MODEL_CLUSTER)
- self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER)
-
- # Then select model.
- self.interpreter.relax_disp.select_model(model=MODEL)
-
- # Skip the clustering analysis, since it won't work. !!!
- #self.interpreter.relax_disp.cluster('model_cluster', ":1-2")
-
- # Copy the parameters from before.
-
self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL,
pipe_to=pipe_name_MODEL_CLUSTER)
-
- # Skip the clustering analysis, since it won't work. !!!
- self.interpreter.minimise(min_algor='simplex',
func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True,
verbosity=1)
-
- # Store result.
- for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
- # Store minimisation results.
- if "r2a" in MODEL_PARAMS[MODEL]:
- clust_results.append([spin.r2a[r20_key], spin.r2b[r20_key],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
- else:
- clust_results.append([spin.r2[r20_key], spin.dw, spin.pA,
spin.kex, spin.chi2, spin_id, resi, resn])
-
- print("\n# Now print before and after minimisation-\n")
-
- # Print results.
- for i in range(len(grid_results)):
- # Get values.
- if "r2a" in MODEL_PARAMS[MODEL]:
- g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi,
g_resn = grid_results[i]
- m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi,
m_resn = mini_results[i]
- c_r2a, c_r2b, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi,
c_resn = clust_results[i]
- print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f
kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b,
g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn))
- print("MIN %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f
kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b,
m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn))
- print("CLUS %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f
kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s\n"%(c_spin_id, c_r2a, c_r2b,
c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn))
- else:
- g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn =
grid_results[i]
- m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn =
mini_results[i]
- c_r2, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn =
clust_results[i]
- print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f
chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex,
g_chi2, g_spin_id, g_resi, g_resn))
- print("MIN %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f
chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex,
m_chi2, m_spin_id, m_resi, m_resn))
- print("CLUS %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f
chi2=%3.4f spin_id=%s resi=%i resn=%s\n"%(c_spin_id, c_r2, c_dw, c_pA, c_kex,
c_chi2, c_spin_id, c_resi, c_resn))
-
- # Test the parameters which created the data.
- # This is for the 1H spin.
- if "r2a" in MODEL_PARAMS[MODEL]:
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key],
R2g, 3)
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key],
R2e, 1)
- else:
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key],
R2g, 4)
-
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6)
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6)
- self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 1)
-
- # This is for the 15N spin. The data won't fit, since r2b is making
trouble.
- #if "r2a" in MODEL_PARAMS[MODEL]:
- # self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].r2a[r20_key],
R2g, 4)
- # self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].r2b[r20_key],
R2e, 2)
- #else:
- # self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].r2[r20_key],
R2g, 4)
-
- #self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].dw, dw_ppm, 6)
- #self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].pA, 1-pb, 6)
- #self.assertAlmostEqual(cdp.mol[0].res[1].spin[0].kex, kex, 2)
-
- # Save graphs
-
#self.interpreter.relax_disp.plot_disp_curves(dir=path.join(getcwd()),
num_points=100, extend=0.0, force=True)
+ self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 2)
def test_bug_21081_disp_cluster_fail(self):
r23318 - /trunk/test_suite/system_tests/relax_disp.py