Author: bugman
Date: Sun Nov 24 17:50:44 2013
New Revision: 21624
URL: http://svn.gna.org/viewcvs/relax?rev=21624&view=rev
Log:
Interpolated curves are now produced for the numeric CPMG-type models.
This if for the relax_disp.plot_disp_curves user function. The resolution of
these are limited to
the frequency of a single CPMG block in the relaxation time period.
Therefore the plots are
produced slightly differently.
To enable this functionality, the new count_exp() and return_relax_times()
functions have been added
to the specific_analyses.relax_disp.disp_data module.
Modified:
branches/relax_disp/specific_analyses/relax_disp/disp_data.py
Modified: branches/relax_disp/specific_analyses/relax_disp/disp_data.py
URL:
http://svn.gna.org/viewcvs/relax/branches/relax_disp/specific_analyses/relax_disp/disp_data.py?rev=21624&r1=21623&r2=21624&view=diff
==============================================================================
--- branches/relax_disp/specific_analyses/relax_disp/disp_data.py (original)
+++ branches/relax_disp/specific_analyses/relax_disp/disp_data.py Sun Nov 24
17:50:44 2013
@@ -33,8 +33,7 @@
"""
# Python module imports.
-from copy import deepcopy
-from math import atan, pi, sqrt
+from math import atan, floor, pi, sqrt
from numpy import array, float64, int32, ones, zeros
from random import gauss
import sys
@@ -134,6 +133,17 @@
return intensity
+def count_exp():
+ """Count the number of experiments present.
+
+ @return: The experiment count
+ @rtype: int
+ """
+
+ # The normal count variable.
+ return len(cdp.exp_type_list)
+
+
def count_frq():
"""Count the number of spectrometer frequencies present.
@@ -1137,6 +1147,7 @@
set_colours = []
x_axis_type_zero = []
symbols = []
+ symbol_sizes = []
linetype = []
linestyle = []
@@ -1154,35 +1165,66 @@
# Set up the interpolated curve data structures.
interpolated_flag = False
- if not spin.model in [MODEL_R2EFF] + MODEL_LIST_NUMERIC_CPMG:
+ if not spin.model in [MODEL_R2EFF]:
# Set the flag.
interpolated_flag = True
- # Interpolate the CPMG frequencies.
- cpmg_frqs = return_cpmg_frqs(ref_flag=False)
- cpmg_frqs_new = deepcopy(cpmg_frqs)
- if cpmg_frqs != None and len(cpmg_frqs[0][0]):
- cpmg_frqs_new = []
- for exp_type_index in range(len(cpmg_frqs)):
- # Add a new dimension.
- cpmg_frqs_new.append([])
-
- # Then loop over the spectrometer frequencies.
- for frq_index in range(len(cpmg_frqs[exp_type_index])):
+ # Initialise some structures.
+ cpmg_frqs_new = None
+ spin_lock_nu1_new = None
+
+ # Interpolate the CPMG frequencies (numeric models).
+ if spin.model in MODEL_LIST_NUMERIC_CPMG:
+ cpmg_frqs = return_cpmg_frqs(ref_flag=False)
+ relax_times = return_relax_times()
+ if cpmg_frqs != None and len(cpmg_frqs[0][0]):
+ cpmg_frqs_new = []
+ for exp_type_index in range(len(cpmg_frqs)):
# Add a new dimension.
- cpmg_frqs_new[exp_type_index].append([])
-
- # Interpolate (adding the extended amount to the
end).
- for point_index in range(num_points):
- point = (point_index + 1) *
(max(cpmg_frqs[exp_type_index][frq_index])+extend) / num_points
-
cpmg_frqs_new[exp_type_index][frq_index].append(point)
-
- # Convert to a numpy array.
- cpmg_frqs_new[exp_type_index][frq_index] =
array(cpmg_frqs_new[exp_type_index][frq_index], float64)
+ cpmg_frqs_new.append([])
+
+ # Then loop over the spectrometer frequencies.
+ for frq_index in
range(len(cpmg_frqs[exp_type_index])):
+ # Add a new dimension.
+ cpmg_frqs_new[exp_type_index].append([])
+
+ # The minimum frequency unit.
+ min_frq = 1.0 /
relax_times[exp_type_index][frq_index]
+ max_frq =
max(cpmg_frqs[exp_type_index][frq_index]) + floor(extend / min_frq) * min_frq
+ num_points = int(max_frq / min_frq)
+
+ # Interpolate (adding the extended amount to the
end).
+ for point_index in range(num_points):
+ point = (point_index + 1) * max_frq /
num_points
+
cpmg_frqs_new[exp_type_index][frq_index].append(point)
+
+ # Convert to a numpy array.
+ cpmg_frqs_new[exp_type_index][frq_index] =
array(cpmg_frqs_new[exp_type_index][frq_index], float64)
+
+ # Interpolate the CPMG frequencies (analytic models).
+ else:
+ cpmg_frqs = return_cpmg_frqs(ref_flag=False)
+ if cpmg_frqs != None and len(cpmg_frqs[0][0]):
+ cpmg_frqs_new = []
+ for exp_type_index in range(len(cpmg_frqs)):
+ # Add a new dimension.
+ cpmg_frqs_new.append([])
+
+ # Then loop over the spectrometer frequencies.
+ for frq_index in
range(len(cpmg_frqs[exp_type_index])):
+ # Add a new dimension.
+ cpmg_frqs_new[exp_type_index].append([])
+
+ # Interpolate (adding the extended amount to the
end).
+ for point_index in range(num_points):
+ point = (point_index + 1) *
(max(cpmg_frqs[exp_type_index][frq_index])+extend) / num_points
+
cpmg_frqs_new[exp_type_index][frq_index].append(point)
+
+ # Convert to a numpy array.
+ cpmg_frqs_new[exp_type_index][frq_index] =
array(cpmg_frqs_new[exp_type_index][frq_index], float64)
# Interpolate the spin-lock field strengths.
spin_lock_nu1 = return_spin_lock_nu1(ref_flag=False)
- spin_lock_nu1_new = deepcopy(spin_lock_nu1)
if spin_lock_nu1 != None and len(spin_lock_nu1[0][0]):
spin_lock_nu1_new = []
for exp_type_index in range(len(spin_lock_nu1)):
@@ -1214,6 +1256,7 @@
set_colours.append([])
x_axis_type_zero.append([])
symbols.append([])
+ symbol_sizes.append([])
linetype.append([])
linestyle.append([])
@@ -1242,6 +1285,7 @@
set_colours[graph_index].append(color_order[frq_index])
x_axis_type_zero[graph_index].append(True)
symbols[graph_index].append(1)
+ symbol_sizes[graph_index].append(0.45)
linetype[graph_index].append(0)
linestyle[graph_index].append(0)
@@ -1283,6 +1327,7 @@
set_colours[graph_index].append(color_order[frq_index])
x_axis_type_zero[graph_index].append(True)
symbols[graph_index].append(4)
+ symbol_sizes[graph_index].append(0.45)
linetype[graph_index].append(1)
if interpolated_flag:
linestyle[graph_index].append(2)
@@ -1326,7 +1371,11 @@
# The other settings.
set_colours[graph_index].append(color_order[frq_index])
x_axis_type_zero[graph_index].append(True)
- symbols[graph_index].append(0)
+ if spin.model in MODEL_LIST_NUMERIC_CPMG:
+ symbols[graph_index].append(8)
+ else:
+ symbols[graph_index].append(0)
+ symbol_sizes[graph_index].append(0.20)
linetype[graph_index].append(1)
linestyle[graph_index].append(1)
@@ -1363,6 +1412,7 @@
set_colours[graph_index].append(color_order[frq_index])
x_axis_type_zero[graph_index].append(True)
symbols[graph_index].append(9)
+ symbol_sizes[graph_index].append(0.45)
linetype[graph_index].append(1)
linestyle[graph_index].append(3)
@@ -1412,7 +1462,7 @@
sets.append(len(data[gi]))
legend.append(False)
legend[0] = True
- write_xy_header(file=file, title=title, graph_num=graph_num,
sets=sets, set_names=set_labels, set_colours=set_colours,
x_axis_type_zero=x_axis_type_zero, symbols=symbols, linetype=linetype,
linestyle=linestyle, axis_labels=axis_labels, legend=legend,
legend_box_fill_pattern=[0]*graph_num, legend_char_size=[0.8]*graph_num)
+ write_xy_header(file=file, title=title, graph_num=graph_num,
sets=sets, set_names=set_labels, set_colours=set_colours,
x_axis_type_zero=x_axis_type_zero, symbols=symbols,
symbol_sizes=symbol_sizes, linetype=linetype, linestyle=linestyle,
axis_labels=axis_labels, legend=legend,
legend_box_fill_pattern=[0]*graph_num, legend_char_size=[0.8]*graph_num)
# Write the data.
graph_type = 'xy'
@@ -2469,6 +2519,36 @@
return values, errors, missing, frqs, frqs_H, exp_types, relax_times
+def return_relax_times():
+ """Return the list of relaxation times.
+
+ @return: The list of relaxation times in s.
+ @rtype: list of lists of numpy rank-1 float64 array
+ """
+
+ # No data.
+ if not hasattr(cdp, 'relax_times'):
+ return None
+
+ # Initialise.
+ relax_times = zeros((count_exp(), count_frq()), float64)
+
+ # Loop over the experiment types.
+ for exp_type, frq, point, time, exp_type_index, frq_index, point_index,
time_index in loop_exp_frq_point_time(return_indices=True):
+ # Fetch all of the matching intensity keys.
+ keys = find_intensity_keys(exp_type=exp_type, frq=frq, point=point,
time=time, raise_error=False)
+
+ # No data.
+ if not len(keys):
+ continue
+
+ # Add the data.
+ relax_times[exp_type_index][frq_index] = cdp.relax_times[keys[0]]
+
+ # Return the data.
+ return relax_times
+
+
def return_spin_lock_nu1(ref_flag=True):
"""Return the list of spin-lock field strengths.
r21624 - /branches/relax_disp/specific_analyses/relax_disp/disp_data.py