[dd_test] a few fixes

lib/lib_dd/decomposition/ccd_single_stateless.py

@@ -161,10 +161,14 @@ def fit_one_spectrum(fit_data):
     # run the inversion
     ND.run_inversion()
 
-    # extract the (only) iteration
+    # extract the last iteration
     final_iteration = ND.iterations[-1]
 
     # renormalize data (we deal only with one spectrum here)
+    # WARNING/NOTE: Renormalization MUST occur before either rms values
+    # (iteration.rms_values) or integrated parameters (iteration.stat_pars) are
+    # accessed/computed, as these parameters are sensitive to the normalized
+    # parameters/values.
     if fit_data['inv_opts']['norm_factors'] is not None:
         norm_factors = fit_data['inv_opts']['norm_factors']
 
@@ -173,12 +177,6 @@ def fit_one_spectrum(fit_data):
             # parameterization !)
             iteration.m[0] -= np.log10(norm_factors)
             iteration.f = iteration.Model.f(iteration.m)
-            # note that we use .stat_pars as a parameter. This is a property
-            # which triggers the initial aggregation/computation of the
-            # parameters. Only then can we modify them.
-            # iteration.statpars = renormalize_statpars(
-            #     iteration.stat_pars, norm_factors
-            # )
 
         # data
         # note: the normalization factor can be applied either to the
@@ -195,60 +193,6 @@ def fit_one_spectrum(fit_data):
     return ND
 
 
-def renormalize_statpars(stat_pars_dict, norm_factors):
-    """Given normalization factors for each spectrum, renormalize relevant stat
-    pars. Return the modified dictionary.
-
-    Parameters
-    ----------
-    stat_pars_dict : dict
-        dictionary containing the stat pars of an iteration
-        (iteration.stat_pars)
-    norm_factors : numpy.ndarray
-        Normalization factors for the spectra
-
-    Returns
-    -------
-    stat_pars_dict : dict
-        dictionary containing the stat pars of an iteration
-        (iteration.stat_pars)
-
-    """
-    if norm_factors is None:
-        return stat_pars_dict
-
-    # renormalize all parameters containing rho0
-    # Note: When the conductivity model is used, the normalisation factors
-    # refer to the data in conductivities, and correspondingly, sigma_0. As we
-    # apply the normalisation to a resistivity (rho_0) parameter, we have to
-    # invert the normalisations, which manifests as a sign change in the log
-    # operations
-    # if key == 'rho0' and norm_factors is not None):
-    # rho0 is log10
-    if int(os.environ.get('DD_COND', 0)) == 1:
-        stat_pars_dict['rho0'] += np.log10(norm_factors).squeeze()
-    else:
-        stat_pars_dict['rho0'] -= np.log10(norm_factors).squeeze()
-
-    # if(key == 'sigma0' and norm_factors is not None):
-    #     # sigma0 is log10
-    #     # renormalize
-    #     values -= np.log10(norm_factors).squeeze()
-
-    # if key == 'sigma_infty' and norm_factors is not None:
-    #     # sigma0 is log10
-    #     # renormalize
-    #     values -= np.log10(norm_factors).squeeze()
-
-    # if(key == 'm_tot_n' and norm_factors is not None):
-    #     # renormalize
-    #     if int(os.environ.get('DD_COND', 0)) == 1:
-    #         values -= np.log10(norm_factors).squeeze()
-    #     else:
-    #         values += np.log10(norm_factors).squeeze()
-    return stat_pars_dict
-
-
 def call_fit_functions(fit_data, ND):
     # only proceed if one of the plot functions will be called. This makes sure
     # that we can run without an existing output directory, and only fail if we

lib/lib_dd/io/helper.py

@@ -19,12 +19,7 @@ def save_f(fid, final_iterations, norm_factors):
             extra_dim = 1
         f_data = f_data.T
 
-        # import pdb
-        # pdb.set_trace()
         f_data = f_data.reshape(extra_dim, base_dim)
-        if norm_factors is not None:
-            print('normalising')
-            f_data /= norm_factors[index]
         np.savetxt(fid, f_data)
 
     open('f_format.dat', 'w').write(itd[0].Data.obj.data_format)

src/dd_test/dd_test.py

@@ -94,7 +94,7 @@ def write_pc_infos(fid):
         'git log -1 | grep commit',
         shell=True
     )
-    git_branch = subprocess.check_output('git branch | grep "\*"', shell=True)
+    git_branch = subprocess.check_output(r'git branch | grep "\*"', shell=True)
     uname = subprocess.check_output('uname -a', shell=True)
     cpu = subprocess.check_output(
         'cat /proc/cpuinfo  | grep "model name" | head -1', shell=True)
@@ -107,7 +107,7 @@ def write_pc_infos(fid):
 
 
 def _get_data_files_for_binary(options):
-    return available_binaries[options.binary + '.py']['data_files'].values()
+    return list(available_binaries[options.binary]['data_files'].values())
 
 
 def initialize_new_test_dir(options):
@@ -136,7 +136,7 @@ def initialize_new_test_dir(options):
         # now write default dd_single.py call
         default_N = 20
         default_nr_cores = 1
-        fid.write(options.binary + '.py\n')
+        fid.write(options.binary + '\n')
         fid.write('-n {0}\n-c {1}\n--silent\n'.format(
             default_N, default_nr_cores))