Author: tlinnet
Date: Tue Sep 9 18:18:11 2014
New Revision: 25718
URL: http://svn.gna.org/viewcvs/relax?rev=25718&view=rev
Log:
For the class of repeated analysis, implemented method to collect peak
intensity, and function to plot the correlation.
Task #7826 (https://gna.org/task/index.php?7826): Write an python class for
the repeated analysis of dispersion data.
Modified:
trunk/auto_analyses/relax_disp_repeat_cpmg.py
trunk/test_suite/system_tests/relax_disp.py
Modified: trunk/auto_analyses/relax_disp_repeat_cpmg.py
URL:
http://svn.gna.org/viewcvs/relax/trunk/auto_analyses/relax_disp_repeat_cpmg.py?rev=25718&r1=25717&r2=25718&view=diff
==============================================================================
--- trunk/auto_analyses/relax_disp_repeat_cpmg.py (original)
+++ trunk/auto_analyses/relax_disp_repeat_cpmg.py Tue Sep 9 18:18:11
2014
@@ -43,7 +43,7 @@
from pipe_control.mol_res_spin import display_spin, generate_spin_string,
return_spin, spin_loop
from pipe_control import pipes
from prompt.interpreter import Interpreter
-from specific_analyses.relax_disp.data import generate_r20_key,
has_exponential_exp_type, is_r1_optimised, loop_exp_frq_offset,
loop_exp_frq_offset_point, return_param_key_from_data, spin_loop
+from specific_analyses.relax_disp.data import generate_r20_key,
has_exponential_exp_type, is_r1_optimised, loop_exp_frq_offset,
loop_exp_frq_offset_point, return_param_key_from_data
from specific_analyses.relax_disp.variables import MODEL_NOREX,
MODEL_PARAMS, MODEL_R2EFF, PARAMS_R20
from status import Status; status = Status()
@@ -864,6 +864,116 @@
return list_dub_mapping
+ def col_int(self, method=None, list_glob_ini=None, selection=None):
+
+ # Loop over the glob ini:
+ res_dic = {}
+ res_dic['method'] = method
+ for glob_ini in list_glob_ini:
+ # Store under glob_ini
+ res_dic[str(glob_ini)] = {}
+
+ # Get the pipe name for peak_intensity values.
+ pipe_name = self.name_pipe(method=method, model='setup',
analysis='int', glob_ini=glob_ini)
+
+ # Check if pipe exists, or else calculate.
+ if not pipes.has_pipe(pipe_name):
+ self.set_int(methods=[method], list_glob_ini=[glob_ini])
+
+ if pipes.get_pipe() != pipe_name:
+ self.interpreter.pipe.switch(pipe_name)
+
+ # Results dictionary.
+ res_dic[str(glob_ini)] = {}
+ res_dic[str(glob_ini)]['peak_intensity'] = {}
+ res_dic[str(glob_ini)]['peak_intensity_err'] = {}
+ spin_point_peak_intensity_list = []
+ spin_point_peak_intensity_err_list = []
+
+ # Loop over the spins.
+ for cur_spin, mol_name, resi, resn, spin_id in
spin_loop(selection=selection, full_info=True, return_id=True,
skip_desel=True):
+ # Make spin dic.
+ res_dic[str(glob_ini)]['peak_intensity'][spin_id] = {}
+ res_dic[str(glob_ini)]['peak_intensity_err'][spin_id] = {}
+
+ # Loop over spectrum_ids.
+ for s_id in cdp.spectrum_ids:
+ # Check for bad data has skipped peak_intensity points
+ if s_id in cur_spin.peak_intensity:
+ peak_intensity_point = cur_spin.peak_intensity[s_id]
+ peak_intensity_err_point =
cur_spin.peak_intensity_err[s_id]
+
+
res_dic[str(glob_ini)]['peak_intensity'][spin_id][s_id] = peak_intensity_point
+
res_dic[str(glob_ini)]['peak_intensity_err'][spin_id][s_id] =
peak_intensity_err_point
+
spin_point_peak_intensity_list.append(peak_intensity_point)
+
spin_point_peak_intensity_err_list.append(peak_intensity_err_point)
+
+ res_dic[str(glob_ini)]['peak_intensity_arr'] =
asarray(spin_point_peak_intensity_list)
+ res_dic[str(glob_ini)]['peak_intensity_err_arr'] =
asarray(spin_point_peak_intensity_err_list)
+
+ return res_dic
+
+
+ def plot_int_corr(self, corr_data, show=False):
+
+ # Define figure.
+ # Nr of columns is number of datasets.
+ nr_cols = len(corr_data)
+ # Nr of rows, is 2. With and without scaling.
+ nr_rows = 2
+
+ # Define figure
+ fig, axises = plt.subplots(nrows=nr_rows, ncols=nr_cols)
+ fig.suptitle('Correlation plot')
+
+ # axises is a tuple with number of elements corresponding to number
of rows.
+ # Each sub-tuple contains axis for each column.
+
+ # Loop over the rows.
+ for i, row_axises in enumerate(axises):
+ # Loop over the columns.
+ for j, ax in enumerate(row_axises) :
+ # Extract from lists.
+ data, methods, glob_inis = corr_data[j]
+ data_x, data_y = data
+ method_x, method_y = methods
+ glob_ini_x, glob_ini_y = glob_inis
+
+ x = data_x[str(glob_ini_x)]['peak_intensity_arr']
+ y = data_y[str(glob_ini_y)]['peak_intensity_arr']
+
+ # If row 1.
+ if i == 0:
+ ax.plot(x, x, '-', label='%s vs. %s' % (method_x,
method_x))
+ ax.plot(x, y, '.', label='%s vs. %s' % (method_y,
method_x) )
+
+ np = len(y)
+ ax.set_title('Intensity for %s %i vs. %s %i. np=%i' %
(method_y, glob_ini_y, method_x, glob_ini_x, np), fontsize=10)
+ ax.legend(loc='upper left', shadow=True, prop = fontP)
+ ax.ticklabel_format(style='sci', axis='x',
scilimits=(0,0))
+ ax.ticklabel_format(style='sci', axis='y',
scilimits=(0,0))
+ ax.set_xlabel('Intensity')
+ ax.set_ylabel('Intensity')
+
+ # Scale intensity
+ if 1 == 1:
+
+ x_norm = x / x.max()
+ y_norm = y / y.max()
+
+ ax.plot(x_norm, x_norm, '-', label='%s vs. %s' %
(method_x, method_x))
+ ax.plot(x_norm, y_norm, '.', label='%s vs. %s' %
(method_y, method_x) )
+
+ np = len(y_norm)
+ ax.set_title('Norm. int. for %s %i vs. %s %i. np=%i' %
(method_y, glob_ini_y, method_x, glob_ini_x, np), fontsize=10)
+ ax.legend(loc='upper left', shadow=True, prop = fontP)
+ ax.set_xlabel('Normalized Intensity')
+ ax.set_ylabel('Normalized Intensity')
+
+ if show:
+ plt.show()
+
+
def col_r2eff(self, method=None, list_glob_ini=None):
# Loop over the glob ini:
@@ -995,10 +1105,6 @@
for method in methods:
if method not in r2eff_stat_dic:
continue
-
- if not dep_check.matplotlib_module:
- continue
-
x = r2eff_stat_dic[method]['glob_ini']
y = r2eff_stat_dic[method]['r2eff_norm_std']
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=25718&r1=25717&r2=25718&view=diff
==============================================================================
--- trunk/test_suite/system_tests/relax_disp.py (original)
+++ trunk/test_suite/system_tests/relax_disp.py Tue Sep 9 18:18:11 2014
@@ -5959,9 +5959,33 @@
#methods = ['FT']
# Set the intensity.
- #RDR.set_int(methods=methods, list_glob_ini=[128, 126])
-
+ RDR.set_int(methods=methods, list_glob_ini=[128, 126])
+
+ # Try plot some intensity correlations.
if True:
+ # Collect intensity values.
+ # For all spins, ft
+ int_ft_all = RDR.col_int(method='FT', list_glob_ini=[128, 126],
selection=None)
+
+ # Now make a spin selection.
+ selection = ':2,3'
+ int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126],
selection=selection)
+ # Print the length of datasets, depending on selection.
+ print( "All spins",
len(int_ft_all['128']['peak_intensity_arr']), "Selection spins",
len(int_ft_sel['128']['peak_intensity_arr']) )
+
+ # For all spins, mdd
+ int_mdd_all = RDR.col_int(method='MDD', list_glob_ini=[128,
126], selection=None)
+ int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128,
126], selection=selection)
+
+ # Plot correlation of intensity
+ fig1 = [[int_ft_all, int_mdd_all], ['FT', 'MDD'], [128, 128]]
+ fig2 = [[int_ft_sel, int_mdd_sel], ['FT sel', 'MDD sel'], [128,
128]]
+ corr_data = [fig1, fig2]
+
+ RDR.plot_int_corr(corr_data=corr_data, show=False)
+
+
+ if False:
# Now calculate R2eff.
RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126])
r25718 - in /trunk: auto_analyses/relax_disp_repeat_cpmg.py test_suite/system_tests/relax_disp.py