The output directory is a bit of a mess, with it being defined in different...

The output directory is a bit of a mess, with it being defined in different places. As we never make use of the possibility of changing it, let's simply hardcode it to out/. It makes filenames slightly easier to read too.

pcigale/analysis_modules/__init__.py

@@ -12,8 +12,6 @@ import shutil
 import numpy as np
 from astropy.table import Column
 
-OUT_DIR = 'out/'
-
 class AnalysisModule(object):
     """Abstract class, the pCigale analysis modules are based on.
     """
@@ -53,16 +51,16 @@ class AnalysisModule(object):
         """
         raise NotImplementedError()
 
-    def prepare_dirs(self, directory=OUT_DIR):
+    def prepare_dirs(self):
         # Create a new out/ directory and move existing one if needed
-        if os.path.exists(directory):
-            name = datetime.now().strftime("%Y%m%d%H%M") + '_' + directory
-            os.rename(directory, name)
-            print("The {} directory was renamed to {}".format(directory, name))
-
-        os.mkdir(directory)
-        shutil.copy('pcigale.ini', directory)
-        shutil.copy('pcigale.ini.spec', directory)
+        if os.path.exists('out/'):
+            name = datetime.now().strftime("%Y%m%d%H%M") + '_out/'
+            os.rename('out/', name)
+            print("The out/ directory was renamed to {}".format(name))
+
+        os.mkdir('out/')
+        shutil.copy('pcigale.ini', 'out/')
+        shutil.copy('pcigale.ini.spec', 'out/')
 
     def process(self, configuration):
         """Process with the analysis

pcigale/analysis_modules/pdf_analysis/utils.py

@@ -11,8 +11,6 @@ import numpy as np
 from scipy import optimize
 from scipy.special import erf
 
-from ..utils import OUT_DIR
-
 log.setLevel('ERROR')
 
 
@@ -29,7 +27,7 @@ def save_best_sed(obsid, sed, norm):
         Normalisation factor to scale the scale to the observations
 
     """
-    sed.to_fits(OUT_DIR + "{}".format(obsid), mass=norm)
+    sed.to_fits("out/{}".format(obsid), mass=norm)
 
 
 def _save_pdf(obsid, name, model_variable, likelihood):
@@ -80,7 +78,7 @@ def _save_pdf(obsid, name, model_variable, likelihood):
             Column(pdf_grid, name=name),
             Column(pdf_prob, name="probability density")
         ))
-        table.write(OUT_DIR + "{}_{}_pdf.fits".format(obsid, name))
+        table.write("out/{}_{}_pdf.fits".format(obsid, name))
 
 
 def save_pdf(obsid, names, mass_proportional, model_variables, scaling,
@@ -133,7 +131,7 @@ def _save_chi2(obsid, name, model_variable, chi2):
     """
     table = Table((Column(model_variable, name=name),
                    Column(chi2, name="chi2")))
-    table.write(OUT_DIR + "{}_{}_chi2.fits".format(obsid, name))
+    table.write("out/{}_{}_chi2.fits".format(obsid, name))
 
 
 def save_chi2(obsid, names, mass_proportional, model_variables, scaling, chi2):
@@ -234,9 +232,9 @@ def save_results(filename, obsid, bayes_variables, bayes_mean, bayes_std, chi2,
         table.add_column(Column(np_fluxes[:, idx], name="best."+name,
                                 unit='mJy'))
 
-    table.write(OUT_DIR+filename+".txt", format='ascii.fixed_width',
+    table.write('out/'+filename+".txt", format='ascii.fixed_width',
                 delimiter=None)
-    table.write(OUT_DIR+filename+".fits", format='fits')
+    table.write('out/'+filename+".fits", format='fits')
 
 
 def dchi2_over_ds2(s, obs_fluxes, obs_errors, mod_fluxes):

pcigale/analysis_modules/savefluxes/workers.py

@@ -10,7 +10,6 @@ import time
 import numpy as np
 
 from ...warehouse import SedWarehouse
-from ..utils import OUT_DIR
 from ..utils import nothread
 
 
@@ -98,7 +97,7 @@ def fluxes(idx):
                                            gbl_variables])
 
     if gbl_save_sed is True:
-        sed.to_fits(OUT_DIR + "{}".format(idx))
+        sed.to_fits("out/{}".format(idx))
     with gbl_n_computed.get_lock():
         gbl_n_computed.value += 1
         n_computed = gbl_n_computed.value

pcigale/analysis_modules/utils.py

@@ -13,11 +13,7 @@ from astropy.table import Table, Column
 
 log.setLevel('ERROR')
 
-# Directory where the output files are stored
-OUT_DIR = "out/"
-
-def save_fluxes(model_fluxes, model_parameters, filters, names,
-                directory=OUT_DIR):
+def save_fluxes(model_fluxes, model_parameters, filters, names):
     """Save fluxes and associated parameters into a table.
 
     Parameters
@@ -30,8 +26,6 @@ def save_fluxes(model_fluxes, model_parameters, filters, names,
         Contains the filter names.
     names: List
         Contains the parameters names.
-    directory: str
-        Directory under which the file should be saved.
 
     """
     out_fluxes = np.ctypeslib.as_array(model_fluxes[0])
@@ -46,9 +40,9 @@ def save_fluxes(model_fluxes, model_parameters, filters, names,
     out_table.add_column(Column(np.arange(model_fluxes[1][0]), name='id'),
                          index=0)
 
-    out_table.write("{}/computed_fluxes.fits".format(directory))
-    out_table.write("{}/computed_fluxes.txt".format(directory),
-                    format='ascii.fixed_width', delimiter=None)
+    out_table.write("out/computed_fluxes.fits")
+    out_table.write("out/computed_fluxes.txt", format='ascii.fixed_width',
+                    delimiter=None)
 
 
 def nothread():

pcigale_plots/__init__.py

@@ -33,8 +33,6 @@ __version__ = "0.1-alpha"
 # Name of the file containing the best models information
 BEST_RESULTS = "results.fits"
 MOCK_RESULTS = "results_mock.fits"
-# Directory where the output files are stored
-OUT_DIR = "out/"
 # Wavelength limits (restframe) when plotting the best SED.
 PLOT_L_MIN = 0.1
 PLOT_L_MAX = 5e5
@@ -51,9 +49,8 @@ def _chi2_worker(obj_name, var_name):
         Name of the analysed variable..
 
     """
-    if os.path.isfile(OUT_DIR + "{}_{}_chi2.fits".format(obj_name, var_name)):
-        chi2 = Table.read(OUT_DIR + "{}_{}_chi2.fits".format(obj_name,
-                                                             var_name))
+    if os.path.isfile("out/{}_{}_chi2.fits".format(obj_name, var_name)):
+        chi2 = Table.read("out/{}_{}_chi2.fits".format(obj_name, var_name))
         figure = plt.figure()
         ax = figure.add_subplot(111)
         ax.scatter(chi2[var_name], chi2['chi2'], color='k', s=.1)
@@ -63,7 +60,7 @@ def _chi2_worker(obj_name, var_name):
         ax.minorticks_on()
         figure.suptitle("Reduced $\chi^2$ distribution of {} for {}."
                         .format(var_name, obj_name))
-        figure.savefig(OUT_DIR + "{}_{}_chi2.pdf".format(obj_name, var_name))
+        figure.savefig("out/{}_{}_chi2.pdf".format(obj_name, var_name))
         plt.close(figure)
     else:
         print("No chi² found for {}. No plot created.".format(obj_name))
@@ -80,8 +77,8 @@ def _pdf_worker(obj_name, var_name):
         Name of the analysed variable..
 
     """
-    if os.path.isfile(OUT_DIR + "{}_{}_pdf.fits".format(obj_name, var_name)):
-        pdf = Table.read(OUT_DIR + "{}_{}_pdf.fits".format(obj_name, var_name))
+    if os.path.isfile("out/{}_{}_pdf.fits".format(obj_name, var_name)):
+        pdf = Table.read("out/{}_{}_pdf.fits".format(obj_name, var_name))
         figure = plt.figure()
         ax = figure.add_subplot(111)
         ax.plot(pdf[var_name], pdf['probability density'], color='k')
@@ -90,7 +87,7 @@ def _pdf_worker(obj_name, var_name):
         ax.minorticks_on()
         figure.suptitle("Probability distribution function of {} for {}"
                         .format(var_name, obj_name))
-        figure.savefig(OUT_DIR + "{}_{}_pdf.pdf".format(obj_name, var_name))
+        figure.savefig("out/{}_{}_pdf.pdf".format(obj_name, var_name))
         plt.close(figure)
     else:
         print("No PDF found for {}. No plot created.".format(obj_name))
@@ -115,9 +112,9 @@ def _sed_worker(obs, mod, filters, sed_type, nologo):
 
     """
 
-    if os.path.isfile(OUT_DIR + "{}_best_model.fits".format(obs['id'])):
+    if os.path.isfile("out/{}_best_model.fits".format(obs['id'])):
 
-        sed = Table.read(OUT_DIR + "{}_best_model.fits".format(obs['id']))
+        sed = Table.read("out/{}_best_model.fits".format(obs['id']))
 
         filters_wl = np.array([filt.effective_wavelength
                                for filt in filters.values()])
@@ -308,7 +305,7 @@ def _sed_worker(obs, mod, filters, sed_type, nologo):
                                    "data/CIGALE.png"))
                 figure.figimage(image, 75, 330, origin='upper', zorder=10,
                                 alpha=1)
-            figure.savefig(OUT_DIR + "{}_best_model.pdf".format(obs['id']))
+            figure.savefig("out/{}_best_model.pdf".format(obs['id']))
             plt.close(figure)
         else:
             print("No valid best SED found for {}. No plot created.".
@@ -360,7 +357,7 @@ def _mock_worker(exact, estimated, param, nologo):
         plt.figimage(image, 510, 55, origin='upper', zorder=10, alpha=1)
 
     plt.tight_layout()
-    plt.savefig(OUT_DIR + 'mock_{}.pdf'.format(param))
+    plt.savefig('out/mock_{}.pdf'.format(param))
 
     plt.close()
 
@@ -395,7 +392,7 @@ def sed(config, sed_type, nologo):
     """Plot the best SED with associated observed and modelled fluxes.
     """
     obs = read_table(config.configuration['data_file'])
-    mod = Table.read(OUT_DIR + BEST_RESULTS)
+    mod = Table.read('out/' + BEST_RESULTS)
 
     with Database() as base:
         filters = OrderedDict([(name, base.get_filter(name))
@@ -414,15 +411,15 @@ def mock(config, nologo):
     """
 
     try:
-        exact = Table.read(OUT_DIR + BEST_RESULTS)
+        exact = Table.read('out/' + BEST_RESULTS)
     except FileNotFoundError:
-        print("Best models file {} not found.".format(OUT_DIR + BEST_RESULTS))
+        print("Best models file {} not found.".format('out/' + BEST_RESULTS))
         sys.exit(1)
 
     try:
-        estimated = Table.read(OUT_DIR + MOCK_RESULTS)
+        estimated = Table.read('out/' + MOCK_RESULTS)
     except FileNotFoundError:
-        print("Mock models file {} not found.".format(OUT_DIR + MOCK_RESULTS))
+        print("Mock models file {} not found.".format('out/' + MOCK_RESULTS))
         sys.exit(1)
 
     params = config.configuration['analysis_params']['variables']