Ok, re-regenerating the statistics now ;)
On 18 June 2014 15:58, <tlinnet@xxxxxxxxxxxxx> wrote:
Author: tlinnet
Date: Wed Jun 18 15:58:31 2014
New Revision: 24092
URL: http://svn.gna.org/viewcvs/relax?rev=24092&view=rev
Log:
Modified profiling script for TSMK01, to use correct parameters k_AB and
r20a.
Or else, the lib functions is just calculating with zero?
Task #7807 (https://gna.org/task/index.php?7807): Speed-up of
dispersion models for Clustered analysis.
Modified:
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
Modified:
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py?rev=24092&r1=24091&r2=24092&view=diff
==============================================================================
---
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
(original)
+++
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py
Wed Jun 18 15:58:31 2014
@@ -110,7 +110,7 @@
Class Profile inherits the Dispersion container class object.
"""
- def __init__(self, num_spins=1, model=None, r2=None, r2a=None,
r2b=None, dw=None, pA=None, kex=None, spins_params=None):
+ def __init__(self, num_spins=1, model=None, r2=None, r2a=None,
r2b=None, dw=None, pA=None, kex=None, k_AB=None, spins_params=None):
"""
Special method __init__() is called first (acts as Constructor).
It brings in data from outside the class like the variable
num_spins.
@@ -136,6 +136,8 @@
@type pA: float
@keyword kex: The rate of exchange.
@type kex: float
+ @keyword k_AB: The exchange rate from state A to state
B
+ @type k_AB: float
@keyword spins_params: List of parameter strings used in
dispersion model.
@type spins_params: array of strings
"""
@@ -172,7 +174,7 @@
self.error.append([1.0]*len(cpmg_point))
# Assemble param vector.
- self.params = self.assemble_param_vector(r2=r2, r2a=r2a,
r2b=r2b, dw=dw, pA=pA, kex=kex, spins_params=spins_params)
+ self.params = self.assemble_param_vector(r2=r2, r2a=r2a,
r2b=r2b, dw=dw, pA=pA, kex=kex, k_AB=k_AB, spins_params=spins_params)
# Make nested list arrays of data. And return them.
values, errors, cpmg_frqs, missing, frqs, exp_types,
relax_times, offsets = self.return_r2eff_arrays()
@@ -316,7 +318,7 @@
return values, errors, cpmg_frqs, missing, frqs, exp_types,
relax_times, offsets
- def assemble_param_vector(self, r2=None, r2a=None, r2b=None,
dw=None, pA=None, kex=None, spins_params=None):
+ def assemble_param_vector(self, r2=None, r2a=None, r2b=None,
dw=None, pA=None, kex=None, k_AB=None, spins_params=None):
"""Assemble the dispersion relaxation dispersion curve fitting
parameter vector.
@keyword r2: The transversal relaxation rate.
@@ -331,6 +333,8 @@
@type pA: float
@keyword kex: The rate of exchange.
@type kex: float
+ @keyword k_AB: The exchange rate from state A to state
B
+ @type k_AB: float
@keyword spins_params: List of parameter strings used in
dispersion model.
@type spins_params: array of strings
@return: An array of the parameter values of the
dispersion relaxation model.
@@ -357,6 +361,8 @@
value = pA
elif param_name == 'kex':
value = kex
+ elif param_name == 'k_AB':
+ value = k_AB
# Add to the vector.
param_vector.append(value)
@@ -411,6 +417,8 @@
yield 'pA', 0, 0
elif param == 'kex':
yield 'kex', 0, 0
+ elif param == 'k_AB':
+ yield 'k_AB', 0, 0
def calc(self, params):
@@ -441,7 +449,7 @@
"""
# Instantiate class
- C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, r2b=10.0,
dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
+ C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, dw=3.0,
k_AB=10.0, spins_params=['r2a', 'dw', 'k_AB'])
# Loop 100 times for each spin in the clustered analysis (to make
the timing numbers equivalent).
for spin_index in xrange(100):
@@ -465,7 +473,7 @@
"""
# Instantiate class
- C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, r2b=10.0,
dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
+ C1 = Profile(num_spins=num_spins, model=model, r2a=5.0, dw=3.0,
k_AB=10.0, spins_params=['r2a', 'dw', 'k_AB'])
# Repeat the function call, to simulate minimisation.
for i in xrange(iter):
@@ -476,38 +484,3 @@
# Execute main function.
if __name__ == "__main__":
main()
-
-def test_reshape():
- C1 = Profile(num_spins=1, model=MODEL_TSMFK01, r2a=5.0, r2b=10.0,
dw=3.0, pA=0.9, kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
- end_index = C1.model.end_index
- #print("end_index:", end_index)
- num_spins = C1.model.num_spins
- #print("num_spins:", num_spins)
- num_frq = C1.model.num_frq
- #print("num_frq:", num_frq)
- params = C1.params
- #print("params", params)
-
- R20 = params[:end_index[1]].reshape(num_spins*2, num_frq)
- R20A = R20[::2].flatten()
- R20B = R20[1::2].flatten()
- dw = params[end_index[1]:end_index[2]]
- pA = params[end_index[2]]
- kex = params[end_index[2]+1]
- print("R20A", R20A, len(R20A))
- print("R20B", R20B, len(R20B))
- print("dw", dw, len(dw))
- print("dw", pA)
- print("kex", kex)
-
- for si in range(num_spins):
- for mi in range(num_frq):
- r20_index = mi + si*num_frq
- r20a=R20A[r20_index]
- r20b=R20B[r20_index]
- print("r20a", r20a, "r20b", r20b)
-
- model = C1.calc(params)
- print(model)
-
-#test_reshape()
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Re: r24092 - /branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_tsmfk01.py