Author: tlinnet
Date: Sat Jun 7 21:43:16 2014
New Revision: 23722
URL: http://svn.gna.org/viewcvs/relax?rev=23722&view=rev
Log:
Modified profiling script to have different number of NCYC points per
frequency.
This is to complicate the data, so any errournous reshaping of data is
discovered.
It is expected, that experiments can have different number of NCYC points per
spectrometer frequency.
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_cr72.py
Modified:
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py?rev=23722&r1=23721&r2=23722&view=diff
==============================================================================
---
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py
(original)
+++
branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py
Sat Jun 7 21:43:16 2014
@@ -24,7 +24,7 @@
# Python module imports.
import cProfile
from os import getcwd, path
-from numpy import array, int32, float64, ones, pi, zeros
+from numpy import array, arange, asarray, int32, float64, ones, pi, zeros
import pstats
import sys
@@ -51,11 +51,11 @@
def main():
s_filename = 'single'
# Profile for a single spin.
- cProfile.run('single(iter=100)', s_filename)
+ cProfile.run('single(iter=1000)', s_filename)
c_filename = 'cluster'
# Profile for a cluster of 100 spins.
- cProfile.run('cluster(iter=100)', c_filename)
+ cProfile.run('cluster(iter=1000)', c_filename)
# Read all stats files into a single object
s_stats = pstats.Stats(s_filename)
@@ -79,7 +79,7 @@
Class Profile inherits the Dispersion container class object.
"""
- def __init__(self, num_spins=1, num_points=10, model=None):
+ def __init__(self, num_spins=1, model=None):
"""
Special method __init__() is called first (acts as Constructor).
It brings in data from outside the class like the variable num_spins.
@@ -93,19 +93,25 @@
# Define parameters
self.model = model
self.num_spins = num_spins
- #self.fields = [800. * 1E6]
- self.fields = [600. * 1E6, 800. * 1E6]
- #self.fields = [600. * 1E6, 800. * 1E6, 900. * 1E6]
+ #self.fields = array([800. * 1E6])
+ #self.fields = array([600. * 1E6, 800. * 1E6])
+ self.fields = array([600. * 1E6, 800. * 1E6, 900. * 1E6])
self.exp_type = [EXP_TYPE_CPMG_SQ]
self.offset = [0]
# Required data structures.
- self.num_points = num_points
- self.ncyc_list = range(2, 2*self.num_points + 1, 2)
- self.relax_time = 0.04
- self.points = array(self.ncyc_list) / self.relax_time
- self.value = array(range(1,len(self.ncyc_list)+1), float64) * 1.00
- self.error = ones(len(self.ncyc_list), float64) * 0.01
+ self.relax_times = self.fields / (100 * 100. *1E6 )
+ self.ncycs = []
+ for i in range(len(self.fields)):
+ inp = arange(2, 1000. * self.relax_times[i], 4)
+ self.ncycs.append(inp)
+ print("sfrq: ", self.fields[i], "number of cpmg frq", len(inp))
+ self.ncycs = asarray(self.ncycs)
+
+ self.points = self.ncycs / self.relax_times
+
+ self.value = self.points * 1.1
+ self.error = self.value * 0.1
# Make nested list arrays of data. And return them.
values, errors, cpmg_frqs, missing, frqs, exp_types, relax_times,
offsets = self.return_r2eff_arrays()
@@ -184,22 +190,22 @@
for mi in range(len(self.fields)):
frq = self.fields[mi]
for oi in range(len(self.offset)):
- for di in range(len(self.points)):
+ for di in range(len(self.points[mi])):
# The Larmor frequency for this spin (and that
of an attached proton for the MMQ models) and field strength (in MHz*2pi to
speed up the ppm to rad/s conversion).
frqs[ei][si][mi] = 2.0 * pi * frq / g1H * g15N *
1e-6
- cpmg_frqs[ei][mi][oi] = self.points
+ cpmg_frqs[ei][mi][oi] = self.points[mi]
missing[ei][si][mi][oi].append(0)
# Values
- values[ei][si][mi][oi].append(self.value[di])
+ values[ei][si][mi][oi].append(self.value[mi][di])
# The errors.
- errors[ei][si][mi][oi].append(self.error[di])
+ errors[ei][si][mi][oi].append(self.error[mi][di])
# The relaxation times.
# Found.
- relax_time = self.relax_time
+ relax_time = self.relax_times[mi]
# Store the time.
relax_times[ei][mi] = relax_time
@@ -216,6 +222,7 @@
values[ei][si][mi][oi] =
array(values[ei][si][mi][oi], float64)
errors[ei][si][mi][oi] =
array(errors[ei][si][mi][oi], float64)
missing[ei][si][mi][oi] =
array(missing[ei][si][mi][oi], int32)
+
# Return the structures.
return values, errors, cpmg_frqs, missing, frqs, exp_types,
relax_times, offsets
@@ -332,13 +339,11 @@
return chi2
-def single(num_spins=1, num_points=20, model=MODEL_CR72_FULL, iter=None):
+def single(num_spins=1, model=MODEL_CR72_FULL, iter=None):
"""Calculate for a single spin.
@keyword num_spins: Number of spins in the cluster.
@type num_spins: integer
- @keyword num_points: The number of points the R2eff array should
consists of.
- @type num_points: integer
@keyword model: The dispersion model to instantiate the
Dispersion class with.
@type model: string
@keyword iter: The number of iterations to perform the function
call.
@@ -348,7 +353,7 @@
"""
# Instantiate class
- C1 = Profile(num_spins=num_spins, num_points=num_points, model=model)
+ C1 = Profile(num_spins=num_spins, model=model)
# Assemble the parameter list.
params = C1.assemble_param_vector(r2a=5.0, r2b=10.0, dw=3.0, pA=0.9,
kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
@@ -358,13 +363,11 @@
chi2 = C1.calc(params)
-def cluster(num_spins=100, num_points=20, model=MODEL_CR72_FULL, iter=None):
+def cluster(num_spins=100, model=MODEL_CR72_FULL, iter=None):
"""Calculate for a number of clustered spins.
@keyword num_spins: Number of spins in the cluster.
@type num_spins: integer
- @keyword num_points: The number of points the R2eff array should
consists of.
- @type num_points: integer
@keyword model: The dispersion model to instantiate the
Dispersion class with.
@type model: string
@keyword iter: The number of iterations to perform the function
call.
@@ -374,7 +377,7 @@
"""
# Instantiate class
- C1 = Profile(num_spins=num_spins, num_points=num_points, model=model)
+ C1 = Profile(num_spins=num_spins, model=model)
# Assemble the parameter list.
params = C1.assemble_param_vector(r2a=5.0, r2b=10.0, dw=3.0, pA=0.9,
kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
@@ -389,15 +392,15 @@
main()
def test_reshape():
- C1 = Profile(num_spins=4, num_points=20, model=MODEL_CR72_FULL)
+ C1 = Profile(num_spins=2, model=MODEL_CR72_FULL)
end_index = C1.model.end_index
- print("end_index:", end_index)
+ #print("end_index:", end_index)
num_spins = C1.model.num_spins
- print("num_spins:", num_spins)
+ #print("num_spins:", num_spins)
num_frq = C1.model.num_frq
- print("num_frq:", num_frq)
+ #print("num_frq:", num_frq)
params = C1.assemble_param_vector(r2a=5.0, r2b=10.0, dw=3.0, pA=0.9,
kex=1000.0, spins_params=['r2a', 'r2b', 'dw', 'pA', 'kex'])
- print("params", params)
+ #print("params", params)
R20 = params[:end_index[1]].reshape(num_spins*2, num_frq)
R20A = R20[::2].flatten()
@@ -416,24 +419,11 @@
r20_index = mi + si*num_frq
r20a=R20A[r20_index]
r20b=R20B[r20_index]
- print "r20a", r20a, "r20b", r20b
-
- for mi in range(num_frq):
- mi_s = mi*num_spins
- mi_e = mi_s + num_spins
- r20a=R20A[mi_s:mi_e]
- r20b=R20B[mi_s:mi_e]
- print "r20a", r20a, "r20b", r20b
+ print("r20a", r20a, "r20b", r20b)
values = array(C1.model.values)
values = array(values)
- ex = values
- # (1, 4, 3, 1, 20): ex, spin, frq, off, disp
- #print type(ex), len(ex), ex.shape, ex
- ex2 = ex.reshape(num_frq*20*num_spins)
- #print type(ex2), len(ex2), ex2.shape, ex2
- #print "here"
model = C1.calc(params)
- print model
-
-#test_par()
+ print(model)
+
+#test_reshape()
r23722 - /branches/disp_spin_speed/test_suite/shared_data/dispersion/profiling/profiling_cr72.py