Author: tlinnet
Date: Tue Apr 29 19:56:14 2014
New Revision: 22884
URL: http://svn.gna.org/viewcvs/relax?rev=22884&view=rev
Log:
Modified systemtest Relax_disp.test_sod1wt_t25_to_cr72.
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=22884&r1=22883&r2=22884&view=diff
==============================================================================
--- trunk/test_suite/system_tests/relax_disp.py (original)
+++ trunk/test_suite/system_tests/relax_disp.py Tue Apr 29 19:56:14 2014
@@ -23,6 +23,7 @@
# Python module imports.
from os import F_OK, access, sep
+from numpy import median
import re, math
from tempfile import mkdtemp
@@ -3635,7 +3636,7 @@
select_spin_index = range(0,2)
self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type,
pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index)
- # Generate r20 keu.
+ # Generate r20 key.
r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ,
frq=599.8908617*1E6)
r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ,
frq=499.862139*1E6)
@@ -3651,53 +3652,136 @@
self.interpreter.relax_disp.select_model(model=MODEL)
# GRID inc of 7 was found to be appropriate not to find pA=0.5.
- GRID_INCS = [7]
- #GRID_INCS = [3, 5, 7, 9, 11, 13, 19, 21]
+ GRID_INC = 7
# Store grid and minimisations results.
grid_results = []
mini_results = []
-
- for i in range(len(GRID_INCS)):
- GRID_INC = GRID_INCS[i]
- # Perform Grid Search.
- self.interpreter.grid_search(lower=None, upper=None,
inc=GRID_INC, constraints=True, verbosity=1)
-
- # Print info out.
- for spin, mol_name, resi, resn, spin_id in
spin_loop(full_info=True, return_id=True, skip_desel=True):
- # Print info.
- print("INC=%i r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f
kex=%3.2f spin_id=%s resi=%i resn=%s"%(GRID_INC, spin.r2[r20_key_600],
spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin_id, resi, resn))
-
- # Store grid results.
- grid_results.append([spin.r2[r20_key_600],
spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin_id, resi, resn])
-
- # Resetting back to nothing.
- if i != len(GRID_INCS)-1:
- print("Resetting values")
- spin.kex, spin.pA, spin.dw, spin.r2[r20_key_500],
spin.r2[r20_key_600] = None, None, None, None, None
+ clust_results = []
+
+ # Set the R20 parameters in the default grid search using the
minimum R2eff value.
+ self.interpreter.relax_disp.set_grid_r20_from_min_r2eff(force=False)
+
+ # Deselect insignificant spins.
+ self.interpreter.relax_disp.insignificance(level=1.0)
+
+ # Perform Grid Search.
+ self.interpreter.grid_search(lower=None, upper=None, inc=GRID_INC,
constraints=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 grid results.
+ grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
## Now do minimisation.
- self.interpreter.minimise(min_algor='simplex', func_tol=1e-10,
max_iter=100000, constraints=True, scaling=True, verbosity=1)
-
- ## Now test values.
+ # Standard parameters are: func_tol=1e-25, grad_tol=None,
max_iter=10000000,
+ set_func_tol = 1e-9
+ set_max_iter = 100000
+ self.interpreter.minimise(min_algor='simplex',
func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True,
verbosity=1)
+
+ # Store result.
+ pA_values = []
+ kex_values = []
for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
- # Print info
- print("r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f
spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500],
spin.dw, spin.pA, spin.kex, spin_id, resi, resn))
-
# Store minimisation results.
- mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500],
spin.dw, spin.pA, spin.kex, spin_id, resi, resn])
-
- # Make tests.
+ mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500],
spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn])
+
+ # Store pA values.
+ pA_values.append(spin.pA)
+
+ # Store kex values.
+ kex_values.append(spin.kex)
+
+ print("\n# Now print before and after minimisation.\n")
+
+ # Print results.
for i in range(len(grid_results)):
# Get values.
- g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_spin_id, g_resi, g_resn
= grid_results[i]
- m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_spin_id, m_resi, m_resn
= mini_results[i]
-
- print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f
spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex,
g_spin_id, g_resi, g_resn))
- print("MIN r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f
spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex,
m_spin_id, m_resi, m_resn))
+ g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id,
g_resi, g_resn = grid_results[i]
+ m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id,
m_resi, m_resn = mini_results[i]
+
+ print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f
chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA,
g_kex, g_chi2, g_spin_id, g_resi, g_resn))
+ print("MIN r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f
chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA,
m_kex, m_chi2, m_spin_id, m_resi, m_resn))
+
+ ## Prepare for clustering
+ # 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)
+
+ # Define cluster id.
+ cluster_id = 'clust'
+
+ # Loop over spins to cluster them.
+ for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
+ self.interpreter.relax_disp.cluster(cluster_id, spin_id)
+
+ # Copy over values.
+
self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL,
pipe_to=pipe_name_MODEL_CLUSTER)
+
+ # Test the median values is correct
+ for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True,
return_id=True, skip_desel=True):
+ print(pA_values)
+ # The the median pA value returned.
+ self.assertEqual(median(pA_values), spin.pA)
+
+ # The the median kex value returned.
+ self.assertEqual(median(kex_values), spin.kex)
+
+ ## Now do minimisation.
+ 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 clust results.
+ clust_results.append([spin.r2[r20_key_600],
spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi,
resn])
+
+ # Store the outcome of the clustering minimisation.
+ clust_pA = spin.pA
+ clust_kex = spin.kex
+
+ print("\n# Now testing.\n")
+
+ # Define results
+ test_res = {}
+ test_res[':10@N'] = {}
+ test_res[':10@N']['r2600'] = 18.429755324773360
+ test_res[':10@N']['r2500'] = 16.981349161968630
+ test_res[':10@N']['dw'] = 2.700755859433969
+ test_res[':10@N']['pA'] = 0.971531659288657
+ test_res[':10@N']['kex'] = 3831.766337047963134
+ test_res[':11@N'] = {}
+ test_res[':11@N']['r2600'] = 18.193409421115213
+ test_res[':11@N']['r2500'] = 17.308838135567765
+ test_res[':11@N']['dw'] = 2.706650302761793
+ test_res[':11@N']['pA'] = 0.971531659288657
+ test_res[':11@N']['kex'] = 3831.766337047963134
+
+ # Then make tests.
+ for i in range(len(grid_results)):
+ # Get values.
+ g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id,
g_resi, g_resn = grid_results[i]
+ m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id,
m_resi, m_resn = mini_results[i]
+ c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id,
c_resi, c_resn = clust_results[i]
+
+ print("%s GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f
kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600,
g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn))
+ print("%s MIN r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f
kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600,
m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn))
+ print("%s Clust r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f
kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600,
c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn))
# Make tests.
- self.assert_(m_kex > 1000.)
+ self.assertEqual(clust_pA , c_pA)
+ self.assertEqual(clust_kex , c_kex)
+
+ # Test values.
+ if c_spin_id in test_res:
+ self.assertAlmostEqual(c_r2_600,
test_res[c_spin_id]['r2600'], 4)
+ self.assertAlmostEqual(c_r2_500,
test_res[c_spin_id]['r2500'], 4)
+ self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3)
+ self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5)
+ self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1)
# Save disp graph to temp.
#self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test",
num_points=1000, extend=500.0, force=True).
r22884 - /trunk/test_suite/system_tests/relax_disp.py