Author: tlinnet
Date: Tue Sep 23 14:41:49 2014
New Revision: 25968
URL: http://svn.gna.org/viewcvs/relax?rev=25968&view=rev
Log:
Implemented writing out of particular correlation plots to file.
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=25968&r1=25967&r2=25968&view=diff
==============================================================================
--- trunk/auto_analyses/relax_disp_repeat_cpmg.py (original)
+++ trunk/auto_analyses/relax_disp_repeat_cpmg.py Tue Sep 23 14:41:49
2014
@@ -1231,7 +1231,7 @@
return res_dic
- def plot_r2eff_corr(self, corr_data, show=False):
+ def plot_r2eff_corr(self, corr_data, show=False, write_stats=False):
# Define figure.
# Nr of columns is number of datasets.
@@ -1245,6 +1245,9 @@
# axises is a tuple with number of elements corresponding to number
of rows.
# Each sub-tuple contains axis for each column.
+
+ # For writing out stats.
+ data_dic = OrderedDict()
# Loop over the rows.
for i, row_axises in enumerate(axises):
@@ -1258,16 +1261,20 @@
x = data_x[str(glob_ini_x)]['r2eff_arr']
x_err = data_x[str(glob_ini_x)]['r2eff_err_arr']
+ np = len(x)
y = data_y[str(glob_ini_y)]['r2eff_arr']
y_err = data_y[str(glob_ini_y)]['r2eff_err_arr']
# If row 1.
if i == 0:
+ # Add to data dic.
+ method_xy_NI = "r2eff_%s%s_%s%s" % (method_x,
glob_ini_x, method_y, glob_ini_y)
+ data_dic[method_xy_NI] = []
+
ax.plot(x, x, 'o', 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(r'$R_{2,\mathrm{eff}}$' + ' 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))
@@ -1275,8 +1282,16 @@
ax.set_xlabel(r'$R_{2,\mathrm{eff}}$')
ax.set_ylabel(r'$R_{2,\mathrm{eff}}$')
+ # Add to data.
+ for k, x_k in enumerate(x):
+ y_k = y[k]
+ data_dic[method_xy_NI].append(["%3.5f"%x_k,
"%3.5f"%y_k])
+
# R2eff to error.
if i == 1:
+ # Add to data dic.
+ method_xy_NI = "r2eff_to_err_%s%s_%s%s" % (method_x,
glob_ini_x, method_y, glob_ini_y)
+ data_dic[method_xy_NI] = []
x_to_x_err = x / x_err
y_to_y_err = y / y_err
@@ -1284,7 +1299,10 @@
# Calculate straight line.
# Linear a, with no intercept.
a = sum(x_to_x_err * y_to_y_err) / sum(x_to_x_err**2)
- x_to_x_err_arange = arange(min(x_to_x_err),
max(x_to_x_err), (max(x_to_x_err) - min(x_to_x_err)) / 10)
+ min_x = min(x_to_x_err)
+ max_x = max(x_to_x_err)
+ step_x = (max_x - min_x) / np
+ x_to_x_err_arange = arange(min_x, max_x, step_x)
y_to_x_err_arange = a * x_to_x_err_arange
ax.plot(x_to_x_err, x_to_x_err, 'o', label='%s vs. %s' %
(method_x, method_x))
@@ -1292,13 +1310,108 @@
ax.plot(x_to_x_err, y_to_y_err, '.', label='%s vs. %s' %
(method_y, method_x) )
ax.plot(x_to_x_err_arange, y_to_x_err_arange, 'g--')
- np = len(y_to_y_err)
ax.set_title(r'$R_{2,\mathrm{eff}}/\sigma(R_{2,\mathrm{eff}})$' + ' 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(r'$R_{2,\mathrm{eff}}/\sigma(R_{2,\mathrm{eff}})$')
ax.set_ylabel(r'$R_{2,\mathrm{eff}}/\sigma(R_{2,\mathrm{eff}})$')
- plt.tight_layout()
+ # Add to data.
+ for k, x_to_x_err_k in enumerate(x_to_x_err):
+ y_to_y_err_k = y_to_y_err[k]
+ x_to_x_err_arange_k = x_to_x_err_arange[k]
+ y_to_x_err_arange_k = y_to_x_err_arange[k]
+ data_dic[method_xy_NI].append(["%3.5f"%x_to_x_err_k,
"%3.5f"%y_to_y_err_k, "%3.5f"%x_to_x_err_arange_k,
"%3.5f"%y_to_x_err_arange_k])
+
+
+ plt.tight_layout()
+
+ # Loop over columns for writing data.
+ # Write to file.
+ if write_stats:
+ # Re-order the data.
+ headings_all = []
+ method_xy_NI_all = []
+ # Loop over the columns.
+ for j in range(nr_cols):
+ headings_j = []
+ method_xy_NI_j = []
+ # Loop over rows
+ for i in range(nr_rows):
+ # Extract from lists.
+ data, methods, glob_inis = corr_data[j]
+ method_x, method_y = methods
+ glob_ini_x, glob_ini_y = glob_inis
+
+ # If row 1.
+ if i == 0:
+ # Add to headings.
+ method_x_NI = "r2eff_%s%s" % (method_x, glob_ini_x)
+ method_y_NI = "r2eff_%s%s" % (method_y, glob_ini_y)
+ headings_j = headings_j + [method_x_NI, method_y_NI]
+
+ method_xy_NI = "r2eff_%s%s_%s%s" % (method_x,
glob_ini_x, method_y, glob_ini_y)
+ method_xy_NI_j.append(method_xy_NI)
+
+ # R2eff to error.
+ if i == 1:
+ # Add to headings
+ method_x_NI = "r2eff_to_err_%s%s" % (method_x,
glob_ini_x)
+ method_y_NI = "r2eff_to_err_%s%s" % (method_y,
glob_ini_y)
+ method_x_NI_lin = "r2eff_to_err_lin_%s%s" %
(method_x, glob_ini_x)
+ method_y_NI_lin = "r2eff_to_err_lin_%s%s" %
(method_y, glob_ini_y)
+ headings_j = headings_j + [method_x_NI, method_y_NI,
method_x_NI_lin, method_y_NI_lin]
+
+ method_xy_NI = "r2eff_to_err_%s%s_%s%s" % (method_x,
glob_ini_x, method_y, glob_ini_y)
+ method_xy_NI_j.append(method_xy_NI)
+
+ headings_all.append(headings_j)
+ method_xy_NI_all.append(method_xy_NI_j)
+
+ # Loop over the columns.
+ for j, headings_j in enumerate(headings_all):
+ method_xy_NI_j = method_xy_NI_all[j]
+
+ data_w = []
+ data_r2eff = data_dic[method_xy_NI_j[0]]
+ data_r2eff_to_err = data_dic[method_xy_NI_j[1]]
+
+ for k, data_r2eff_k in enumerate(data_r2eff):
+ data_r2eff_to_err_k = data_r2eff_to_err[k]
+ data_w.append(data_r2eff_k + data_r2eff_to_err_k)
+
+ # Define file name.
+ 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
+ np = len(data_r2eff)
+
+ # Get the spin selection for correlation.
+ selection = data_x['selection']
+
+ file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x,
glob_ini_x, method_y, glob_ini_y, np)
+ if selection == None:
+ file_name_ini = file_name_ini + '_all'
+ else:
+ file_name_ini = file_name_ini + '_sel'
+
+ file_name = file_name_ini + '.txt'
+ path = self.results_dir
+
+ # save figure
+ # Write png.
+ png_file_name = file_name_ini + '.png'
+ png_file_path = get_file_path(file_name=png_file_name,
dir=path)
+ plt.savefig(png_file_path, bbox_inches='tight')
+
+ # Write file
+ file_obj, file_path = open_write_file(file_name=file_name,
dir=path, force=True, compress_type=0, verbosity=1, return_path=True)
+
+ # Write data.
+ write_data(out=file_obj, headings=headings_j, data=data_w)
+
+ # Close file.
+ file_obj.close()
if show:
plt.show()
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=25968&r1=25967&r2=25968&view=diff
==============================================================================
--- trunk/test_suite/system_tests/relax_disp.py (original)
+++ trunk/test_suite/system_tests/relax_disp.py Tue Sep 23 14:41:49 2014
@@ -6047,6 +6047,47 @@
RDR.plot_r2eff_corr(corr_data=corr_data, show=True)
+ # Try write some R2eff correlations.
+ if True:
+ selection = None
+ # Collect r2eff values.
+ r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128],
selection=selection)
+
+ # For all spins, mdd
+ r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128,
126], selection=selection)
+
+ # Plot correlation of intensity
+ fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]]
+ fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]]
+ corr_data = [fig1, fig2]
+
+ write_stats = True
+ RDR.plot_r2eff_corr(corr_data=corr_data, show=True,
write_stats=write_stats)
+
+ # Open stat file.
+ if write_stats:
+ for i, corr_data_i in enumerate(corr_data):
+ data, methods, glob_inis = corr_data[i]
+ 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)]['r2eff_arr']
+ np = len(x)
+
+ file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' %
(method_x, glob_ini_x, method_y, glob_ini_y, np)
+
+ if selection == None:
+ file_name = file_name_ini + '_all.txt'
+ else:
+ file_name = file_name_ini + '_sel.txt'
+ path = RDR.results_dir
+ data = extract_data(file=file_name, dir=path)
+
+ # Loop over the lines.
+ for i, data_i in enumerate(data):
+ print(i, data_i)
+
+
# Try plot some R2eff statistics.
if False:
# Collect r2eff values.
r25968 - in /trunk: auto_analyses/relax_disp_repeat_cpmg.py test_suite/system_tests/relax_disp.py