Improve prog. bars compatiblity w/Jupyter Notebook

pyss3/cmd_line.py

@@ -727,7 +727,8 @@ def do_grid_search(self, args):
             Evaluation.grid_search(
                 CLF, x_data, y_data,
                 hparams["s"], hparams["l"], hparams["p"], hparams["a"],
-                k_fold, n_grams, def_cat, data_path, cache=cache
+                k_fold, n_grams, def_cat, data_path,
+                cache=cache, extended_pbar=True
             )
             Print.warn(
                 "Suggestion: use the command 'plot %s' to visualize the results"

pyss3/util.py

@@ -698,7 +698,7 @@ def __evaluation_result__(
     @staticmethod
     def __grid_search_loop__(
         clf, x_test, y_test, ss, ll, pp, aa, k_fold,
-        i_fold, def_cat, tag, categories, cache=True, leave_pbar=True
+        i_fold, def_cat, tag, categories, cache=True, leave_pbar=True, extended_pbar=False
     ):
         """Grid search main loop."""
         ss = [round_fix(s) for s in list_by_force(ss)]
@@ -713,7 +713,8 @@ def __grid_search_loop__(
         )
         progress_desc = tqdm(
             total=0,
-            bar_format='{desc}', leave=leave_pbar
+            bar_format='{desc}', leave=leave_pbar,
+            disable=not extended_pbar
         )
 
         method = Evaluation.__kfold2method__(k_fold)
@@ -1339,7 +1340,7 @@ def kfold_cross_validation(
     def grid_search(
         clf, x_data, y_data, s=None, l=None, p=None, a=None,
         k_fold=None, n_grams=None, def_cat=STR_MOST_PROBABLE, tag=None,
-        metric='accuracy', avg='macro', cache=True
+        metric='accuracy', avg='macro', cache=True, extended_pbar=False
     ):
         """
         Perform a grid search using the provided hyperparameter values.
@@ -1437,6 +1438,9 @@ def grid_search(
                       to completely perform the evaluation ignoring cached values
                       (default: True).
         :type cache: bool
+        :param extended_pbar: whether to show an extra status bar along with
+                              the progress bar (default: False).
+        :type extended_pbar: bool
         :returns: a tuple of hyperparameter values (s, l, p, a) with the best
                   values for the given metric
         :rtype: tuple
@@ -1455,17 +1459,18 @@ def grid_search(
 
         Evaluation.__set_last_evaluation__(tag, method, def_cat)
 
-        s = s or clf.get_s()
-        l = l or clf.get_l()
-        p = p or clf.get_p()
-        a = a or clf.get_a()
+        s = s if s is not None else clf.get_s()
+        l = l if l is not None else clf.get_l()
+        p = p if p is not None else clf.get_p()
+        a = a if a is not None else clf.get_a()
 
         Print.show()
         if not k_fold:  # if test
             x_test, y_test = x_data, [clf.get_category_index(y) for y in y_data]
             Evaluation.__grid_search_loop__(
                 clf, x_test, y_test, s, l, p, a, 1, 0,
-                def_cat, tag, clf.get_categories(), cache
+                def_cat, tag, clf.get_categories(), cache,
+                extended_pbar=extended_pbar
             )
         else:  # if k-fold
             Print.verbosity_region_begin(VERBOSITY.NORMAL)
@@ -1490,7 +1495,8 @@ def grid_search(
 
                 Evaluation.__grid_search_loop__(
                     clf_fold, x_test, y_test, s, l, p, a, k_fold, i_fold,
-                    def_cat, tag, categories, cache, leave_pbar=False
+                    def_cat, tag, categories, cache,
+                    leave_pbar=False, extended_pbar=extended_pbar
                 )
 
                 Evaluation.__cache_update__()
@@ -1547,22 +1553,20 @@ def load_from_files(data_path, folder_label=True, as_single_doc=False):
 
                     cat_info[cat] = len(docs)
         else:
-
             folders = listdir(data_path)
-            for item in tqdm(folders, desc=" Categories",
-                             leave=False, disable=Print.is_quiet()):
-                item_path = path.join(data_path, item)
-                if not path.isfile(item_path):
-                    cat_info[item] = 0
-                    files = listdir(item_path)
-                    for file in tqdm(files, desc=" Documents",
-                                     leave=False, disable=Print.is_quiet()):
-                        file_path = path.join(item_path, file)
+            for icat, cat in enumerate(folders):
+                cat_path = path.join(data_path, cat)
+                if not path.isfile(cat_path):
+                    cat_info[cat] = 0
+                    files = listdir(cat_path)
+                    pbar_desc = "Loading documents for '%s' [%d/%d]" % (cat, icat + 1, len(folders))
+                    for file in tqdm(files, desc=pbar_desc, disable=Print.is_quiet()):
+                        file_path = path.join(cat_path, file)
                         if path.isfile(file_path):
                             with open(file_path, "r", encoding=ENCODING) as ffile:
                                 x_data.append(ffile.read())
-                                y_data.append(item)
-                            cat_info[item] += 1
+                                y_data.append(cat)
+                            cat_info[cat] += 1
 
         Print.info("%d categories found" % len(cat_info))
         for cat in cat_info: