Hi Edward.
This part is in systemtest: Relax_disp.test_sod1wt_t25_to_cr72
# 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)
2014-04-30 10:53 GMT+02:00 Edward d'Auvergne <edward@xxxxxxxxxxxxx>:
Hi Troels,
I would recommend creating a new system test for this code. This part
is not tested in the test suite, hence it is a weak point in relax
that will probably fail again with future code changes. So having a
system test where hardcoded values are checked will ensure that this
part of relax is rock solid.
Cheers,
Edward
On 30 April 2014 10:19, Edward d'Auvergne <edward@xxxxxxxxxxxxx> wrote:
Ah, that was a remnant of the parameter averaging to parameter median
change for the clustering
(http://thread.gmane.org/gmane.science.nmr.relax.devel/4647/focus=4648).
Could you retroactively create a bug report for this? That would be
useful for the release notes.
Cheers,
Edward
On 29 April 2014 19:56, <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Tue Apr 29 19:56:12 2014
New Revision: 22883
URL: http://svn.gna.org/viewcvs/relax?rev=22883&view=rev
Log:
Fix for the relax_disp.parameter_copy function.
The median of the values was not performed properly, since 0.0 was
already in the starting list of values.
Modified:
trunk/specific_analyses/relax_disp/parameters.py
Modified: trunk/specific_analyses/relax_disp/parameters.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/specific_analyses/relax_disp/parameters.py?rev=22883&r1=22882&r2=22883&view=diff
==============================================================================
--- trunk/specific_analyses/relax_disp/parameters.py (original)
+++ trunk/specific_analyses/relax_disp/parameters.py Tue Apr 29
19:56:12 2014
@@ -162,17 +162,17 @@
for spin_ids in loop_cluster():
# Initialise some variables.
model = None
- pA = [0.0]
- pB = [0.0]
- pC = [0.0]
- kex = [0.0]
- kex_AB = [0.0]
- kex_AC = [0.0]
- kex_BC = [0.0]
- k_AB = [0.0]
- kB = [0.0]
- kC = [0.0]
- tex = [0.0]
+ pA = []
+ pB = []
+ pC = []
+ kex = []
+ kex_AB = []
+ kex_AC = []
+ kex_BC = []
+ k_AB = []
+ kB = []
+ kC = []
+ tex = []
count = 0
spins_from = []
spins_to = []
@@ -240,38 +240,38 @@
# Take median of parameters.
if len(pA) > 1:
- pA = [median(pA)]
- print("Median pA value: %.15f" % pA[0])
+ pA = median(pA)
+ print("Median pA value: %.15f" % pA)
if len(pB) > 1:
- pB = [median(pB)]
- print("Median pA value: %.15f" % pA[0])
+ pB = median(pB)
+ print("Median pB value: %.15f" % pB)
if len(pC) > 1:
- pC = [median(pC)]
- print("Median pC value: %.15f" % pC[0])
+ pC = median(pC)
+ print("Median pC value: %.15f" % pC)
if len(kex) > 1:
- kex = [median(kex)]
- print("Median kex value: %.15f" % kex[0])
+ kex = median(kex)
+ print("Median kex value: %.15f" % kex)
if len(kex_AB) > 1:
- kex_AB = [median(kex_AB)]
- print("Median k_AB value: %.15f" % kex_AB[0])
+ kex_AB = median(kex_AB)
+ print("Median k_AB value: %.15f" % kex_AB)
if len(kex_AC) > 1:
- kex_AC = [median(kex_AC)]
- print("Median k_AC value: %.15f" % kex_AC[0])
+ kex_AC = median(kex_AC)
+ print("Median k_AC value: %.15f" % kex_AC)
if len(kex_BC) > 1:
- kex_BC = [median(kex_BC)]
- print("Median k_BC value: %.15f" % kex_BC[0])
+ kex_BC = median(kex_BC)
+ print("Median k_BC value: %.15f" % kex_BC)
if len(k_AB) > 1:
- k_AB = [median(k_AB)]
- print("Median k_AB value: %.15f" % k_AB[0])
+ k_AB = median(k_AB)
+ print("Median k_AB value: %.15f" % k_AB)
if len(kB) > 1:
- kB = [median(kB)]
- print("Median kB value: %.15f" % kB[0])
+ kB = median(kB)
+ print("Median kB value: %.15f" % kB)
if len(kC) > 1:
- kC = [median(kC)]
- print("Median kC value: %.15f" % kC[0])
+ kC = median(kC)
+ print("Median kC value: %.15f" % kC)
if len(tex) > 1:
- tex = [median(tex)]
- print("Median tex value: %.15f" % tex[0])
+ tex = median(tex)
+ print("Median tex value: %.15f" % tex)
# Loop over the spins, this time copying the parameters.
for i in range(len(spin_ids)):
@@ -293,28 +293,28 @@
# The median parameters.
if 'pB' in spin_from.params and 'pC' not in
spin_from.params:
- spin_to.pA = pA[0]
- spin_to.pB = pB[0]
- spin_to.pC = 1.0 - pA[0] - pB[0]
+ spin_to.pA = pA
+ spin_to.pB = pB
+ spin_to.pC = 1.0 - pA - pB
elif 'pA' in spin_from.params:
- spin_to.pA = pA[0]
- spin_to.pB = 1.0 - pA[0]
+ spin_to.pA = pA
+ spin_to.pB = 1.0 - pA
if 'kex' in spin_from.params:
- spin_to.kex = kex[0]
+ spin_to.kex = kex
if 'kex_AB' in spin_from.params:
- spin_to.kex_AB = kex_AB[0]
+ spin_to.kex_AB = kex_AB
if 'kex_AC' in spin_from.params:
- spin_to.kex_AC = kex_AC[0]
+ spin_to.kex_AC = kex_AC
if 'kex_BC' in spin_from.params:
- spin_to.kex_BC = kex_BC[0]
+ spin_to.kex_BC = kex_BC
if 'k_AB' in spin_from.params:
- spin_to.k_AB = k_AB[0]
+ spin_to.k_AB = k_AB
if 'kB' in spin_from.params:
- spin_to.kB = kB[0]
+ spin_to.kB = kB
if 'kC' in spin_from.params:
- spin_to.kC = kC[0]
+ spin_to.kC = kC
if 'tex' in spin_from.params:
- spin_to.tex = tex[0]
+ spin_to.tex = tex
# All other spin specific parameters.
for param in spin_from.params:
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