clean code, flake8 fix linted errors, add important comments

tracegroomer/__main__.py

@@ -66,7 +66,7 @@ def prep_args() -> argparse.ArgumentParser:
                         action=argparse.BooleanOptionalAction, default=True,
                         help="Stomps fractional contributions (synonym: \
                         mean enrichment), and isotopologue proportions, \
-                        to max 1.0 and min 0.0")  #meanenrich_or_fracfontrib
+                        to max 1.0 and min 0.0")  # meanenrich_or_fracfontrib
 
     # for total abundance only if VIB data
     parser.add_argument("--under_detection_limit_set_nan",
@@ -95,7 +95,7 @@ def main() -> int:
     parser = prep_args()
     args = parser.parse_args()
     logger.info(
-        f"Running TraceGroomer with the following parameters:")
+        "Running TraceGroomer with the following parameters:")
     for x in vars(args).keys():
         logger.info(f"{x} = {vars(args)[x]} ")
 

tracegroomer/tests/test_tidy.py

@@ -126,8 +126,8 @@ def test_stomp_fraction_values(self):
         )
 
     def test_pull_internal_standard(self):
-        df = pd.DataFrame({ "sample-a": [87, 64, 14],
-                            "sample-b": [85, 37, 17]})
+        df = pd.DataFrame({"sample-a": [87, 64, 14],
+                           "sample-b": [85, 37, 17]})
         df.index = ["X", "W_acid", "Z"]
         config = {
             "mean_enrichment": "FracContribs", "isotopologues": None,

tracegroomer/tests/test_utils.py

@@ -69,7 +69,7 @@ def test_compute_isotopologues_proportions_from_absolute(self):
             df, metabolites2isotopologues_df
         )
 
-        self.assertAlmostEqual(result.loc['acCoA_m+0','sampleA2'],
+        self.assertAlmostEqual(result.loc['acCoA_m+0', 'sampleA2'],
                                0.529913, places=6)
         self.assertAlmostEqual(result.loc['acCoA_m+1', 'sampleB1'],
                                0.313908, places=6)
@@ -121,14 +121,14 @@ def test_compute_sums_isotopol_props(self):
     def test_impute_custom_levels_to_df(self):
         melted_df = pd.DataFrame({
             "metabolite": ["AcCoA", "AcCoA", "AcCoA", "unknown", "unknown",
-                         "gly", "gly", "gly", "AcCoA", "AcCoA", "AcCoA",
-                         "unknown", "unknown", "gly", "gly", "gly"  ],
-          "isotopologue_type": [0, 1, 2, 0, 1, 0, 1, 2, 0, 1, 2, 0, 1, 0, 1,
-                                2],
-          "samples": ["s1", "s1", "s1", "s1", "s1", "s1", "s1", "s1", "s2",
-                      "s2", "s2", "s2", "s2", "s2", "s2", "s2"],
-          "value": [0.3, 0.6, 0.1, 0.4, 0.6, 0.2, 0.5, 0.3,
-                    0.25, 0.62, 0.15, 0.5, 0.5, 0.23, 0.46, 0.31]
+                           "gly", "gly", "gly", "AcCoA", "AcCoA", "AcCoA",
+                           "unknown", "unknown", "gly", "gly", "gly"],
+            "isotopologue_type": [0, 1, 2, 0, 1, 0, 1, 2, 0, 1, 2,
+                                  0, 1, 0, 1, 2],
+            "samples": ["s1", "s1", "s1", "s1", "s1", "s1", "s1", "s1", "s2",
+                        "s2", "s2", "s2", "s2", "s2", "s2", "s2"],
+            "value": [0.3, 0.6, 0.1, 0.4, 0.6, 0.2, 0.5, 0.3,
+                      0.25, 0.62, 0.15, 0.5, 0.5, 0.23, 0.46, 0.31]
           })
         result = utils.impute_custom_levels_to_df(melted_df)
 
@@ -188,8 +188,8 @@ def test_divide_by_amount_material(self):
         confdict = {"isotopologues": "MyIsotopes"}
 
         result = utils.divide_by_amount_material(
-            frames_dict,confdict, material_df=micrograms_weight,
-            alternative_method=True, metric="isotopologues" )
+            frames_dict, confdict, material_df=micrograms_weight,
+            alternative_method=True, metric="isotopologues")
 
         witness = (df.loc["acCoA_m+1", "sampleA2"] / micrograms_weight.loc[
             "sampleA2", "0"]) * micrograms_weight["0"].mean()
@@ -202,7 +202,7 @@ def test_divide_by_amount_material(self):
             np.around(
                 result['MyIsotopes'].loc['acCoA_m+0', :], 6
             ) == np.array(
-                [ 10277.580938, 8869.973775, 6527.904882, 56000.880682]))
+                [10277.580938, 8869.973775, 6527.904882, 56000.880682]))
         )
         self.assertTrue(np.all(
             np.around(

tracegroomer/tidy.py

@@ -30,6 +30,7 @@ def __init__(self, type_of_file):
                                        'isotopologue_proportions',
                                        'isotopologues',
                                        'abundances']
+        self.metabolites2isotopologues_df = None
         self.user_given_names = dict()
 
     def load_metadata(self, metadata_path):
@@ -124,19 +125,21 @@ def transpose_frames(self):
     def load_metabolite_to_isotopologue_df(self, confdict):
         """df of correspondences between isotopologues and metabolites
         proper to the given data"""
-        try:
-            isotopologues_full = list(self.frames_dict[confdict[
-                                     "isotopologue_proportions"]].index)
-        # ok apply same proposed solution whether Key or Type error:
-        except TypeError:
-            isotopologues_full = list(self.frames_dict[confdict[
-                                      "isotopologues"]].index)
-        except KeyError:
-            isotopologues_full = list(self.frames_dict[confdict[
-                                    "isotopologues"]].index)
-
-        self.metabolites2isotopologues_df = ut.isotopologues_meaning_df(
-            isotopologues_full)
+        if (confdict['isotopologue_proportions'] is not None) or (
+                confdict['isotopologues'] is not None):
+            try:
+                isotopologues_full = list(self.frames_dict[confdict[
+                                         "isotopologue_proportions"]].index)
+            # ok apply same proposed solution whether Key or Type error:
+            except TypeError:
+                isotopologues_full = list(self.frames_dict[confdict[
+                                          "isotopologues"]].index)
+            except KeyError:
+                isotopologues_full = list(self.frames_dict[confdict[
+                                        "isotopologues"]].index)
+
+            self.metabolites2isotopologues_df = ut.isotopologues_meaning_df(
+                isotopologues_full)
 
     def set_user_given_names(self, confdict):
         """
@@ -178,19 +181,23 @@ def update_truly_available_frames(self, confdict):
         for h in self.frames_dict.keys():
             # if the quantification content and key exists
             if (self.frames_dict[h] is not None) and (h is not None):
-                avail_dict[reverse_dict[h]] = h
-                true_reverse_dict[h] = reverse_dict[h]
+                try:
+                    avail_dict[reverse_dict[h]] = h
+                    true_reverse_dict[h] = reverse_dict[h]
+                except Exception as e:
+                    print(e)
+                    continue
 
         self.available_frames = avail_dict
         self.reverse_available_frames = true_reverse_dict
 
     def save_isotopologues_preview(self, args, confdict, groom_out_path):
-        compartmentalized_dict = ut.df_to__dic_bycomp(
-            self.frames_dict[confdict['isotopologue_proportions']],
-            self.metadata)
-        output_plots_dir = os.path.join(groom_out_path, "preview_plots")
         if args.isotopologues_preview:
-            logger.info(f"prepare isotopologue proportions overview figures")
+            compartmentalized_dict = ut.df_to__dic_bycomp(
+                self.frames_dict[confdict['isotopologue_proportions']],
+                self.metadata)
+            output_plots_dir = os.path.join(groom_out_path, "preview_plots")
+            logger.info("prepare isotopologue proportions overview figures")
             if not os.path.exists(output_plots_dir):
                 os.makedirs(output_plots_dir)
             ut.save_isos_preview(
@@ -204,8 +211,8 @@ def pull_internal_standard(self, confdict, args):
         ):
             try:
                 x = self.frames_dict[confdict['abundances']].columns.tolist()
-                y = self.frames_dict[confdict['abundances']
-                                     ].loc[args.use_internal_standard, :].tolist()
+                y = self.frames_dict[confdict['abundances']].loc[
+                    args.use_internal_standard, :].tolist()
                 instandard_abun_df = pd.DataFrame(
                     {"sample": x,
                      args.use_internal_standard: y
@@ -255,8 +262,13 @@ def normalize_by_internal_standard(self, args, confdict):
             self.frames_dict = frames_dict
 
     def set_final_files_names(self):
+        """
+        Set final names of output files:
+          1. set final names dictionary and add as attribute, and
+          2. assign the values of 1. to the keys of the object.frames_dict
+        """
         not_user_defined_dict = ut.retrieve_dict_not_user_defined()
-        final_files_names_d = dict()
+        final_files_names_d = dict()  # set final names dictionary
         for valuename in self.reverse_available_frames.keys():
             keyname = self.reverse_available_frames[valuename]
             if keyname in list(self.user_given_names.keys()):
@@ -267,7 +279,7 @@ def set_final_files_names(self):
                         keyname]
         # end for
         frames_names_list = list(self.frames_dict.keys())
-        for frame_name in frames_names_list:
+        for frame_name in frames_names_list:  # assign final names to frames
             if frame_name == "abundances_computed":
                 self.frames_dict[final_files_names_d[
                     "abundances"]] = self.frames_dict[frame_name]
@@ -313,7 +325,8 @@ def drop_metabolites(self):
     def frames_filterby_min_admited_isotopol_proportions(
             self, confdict, isosprop_min_admitted: float
     ):
-        isos_propor_dic = self.frames_dict[confdict['isotopologue_proportions']]
+        isos_propor_dic = self.frames_dict[
+            confdict['isotopologue_proportions']]
         bad_mets = dict()
         for co in isos_propor_dic.keys():
             tmp = isos_propor_dic[co]

tracegroomer/utils.py

@@ -401,7 +401,8 @@ def save_isos_preview(dict_isos_prop, metadata, output_plots_dir,
             dfmelt = impute_custom_levels_to_df(dfmelt)
             table_minimalbymet(dfmelt, os.path.join(output_plots_dir,
                                f"minextremesIso_{k}.{output_extension}"))
-            outputfigure = os.path.join(output_plots_dir, f"allsampleIsos_{k}.pdf")
+            outputfigure = os.path.join(
+                output_plots_dir, f"allsampleIsos_{k}.pdf")
             figtitle = f"{k} compartment, Isotopologues (proportions) \
             across all samples"
             save_rawisos_plot(dfmelt, figuretitle=figtitle,
@@ -742,5 +743,3 @@ def transformmyisotopologues(isos_list, style) -> List[str]:
         outli = isos_list
         raise ValueError("isotopologues style not vib nor generic")
     return outli
-
-