Replacing get_first and get_last method by first and last properties. Improving notes and warning. Properly ordering splited columns in dataframe.

1 files changed, 52 insertions, 23 deletions

diff --git a/src/argaze/DataStructures.py b/src/argaze/DataStructures.py
index 0c1dd5e..9339227 100644
--- a/src/argaze/DataStructures.py
+++ b/src/argaze/DataStructures.py
@@ -28,11 +28,10 @@ class TimeStampedBuffer(collections.OrderedDict):
         }
     ```
 
-    .. warning::
-       Timestamps must be numbers.
+    .. warning:: Timestamps must be numbers.
 
-    .. warning::
-       Timestamps are not sorted by any order.
+    .. warning:: Timestamps are not sorted internally.
+       Data are considered to be stored according at their coming time.
     """
 
     def __new__(cls, args = None):
@@ -60,7 +59,8 @@ class TimeStampedBuffer(collections.OrderedDict):
 
         return self
 
-    def get_first(self) -> Tuple[TimeStampType, DataType]:
+    @property
+    def first(self) -> Tuple[TimeStampType, DataType]:
         """Easing access to first item."""
 
         return list(self.items())[0]
@@ -73,7 +73,7 @@ class TimeStampedBuffer(collections.OrderedDict):
     def pop_first_until(self, ts: TimeStampType) -> Tuple[TimeStampType, DataType]:
         """Pop all item until a given timestamped value and return the last poped item."""
 
-        # get last timestamp before given timestamp
+        # get last item before given timestamp
         earliest_ts, earliest_value = self.get_last_before(ts)
 
         popep_ts, poped_value = self.pop_first()
@@ -83,7 +83,8 @@ class TimeStampedBuffer(collections.OrderedDict):
 
         return popep_ts, poped_value
 
-    def get_last(self) -> Tuple[TimeStampType, DataType]:
+    @property
+    def last(self) -> Tuple[TimeStampType, DataType]:
         """Easing access to last item."""
 
         return list(self.items())[-1]
@@ -109,33 +110,51 @@ class TimeStampedBuffer(collections.OrderedDict):
             
             raise KeyError(f'No data stored before {ts} timestamp.')
 
-    def export_as_json(self, filepath):
-        """Write buffer content into a json file."""
-
-        try:
-            with open(filepath, 'w', encoding='utf-8') as jsonfile:
-                json.dump(self, jsonfile, ensure_ascii = False, default=vars)
+    def as_dataframe(self, exclude=[], split={}) -> pandas.DataFrame:
+        """Convert as [pandas dataframe](https://pandas.pydata.org/docs/reference/frame.html).  
+        
+        The optional *split* argument allows tuple values to be stored in a dedicated columns.  
+        For example: to convert {"point": (0, 0)} data as two separated "x" and "y" columns, use split={"point":["x", "y"]}  
 
-        except:
-            raise RuntimeError(f'Can\' write {filepath}')
+        .. warning:: Values must be dictionaries.
+           Each key is stored as a column name.
 
-    def as_dataframe(self, exclude=[], split={}) -> pandas.DataFrame:
-        """Convert buffer as pandas dataframe. Timestamped values must be stored as dictionary where each keys will be related to a column."""
+        .. note:: Timestamps are stored as index column called 'timestamp'.
+        """
 
         df = pandas.DataFrame.from_dict(self.values())
+
+        # Exclude columns
         df.drop(exclude, inplace=True, axis=True)
 
-        for key, columns in split.items():
-            df[columns] = pandas.DataFrame(df[key].tolist(), index=df.index)
-            df.drop(key, inplace=True, axis=True)
+        # Split columns
+        splited_columns = []
+        for column in df.columns:
+
+            if column in split.keys():
+
+                df[split[column]] = pandas.DataFrame(df[column].tolist(), index=df.index)
+                df.drop(column, inplace=True, axis=True)
+
+                for new_column in split[column]:
 
+                    splited_columns.append(new_column)
+
+            else:
+
+                splited_columns.append(column)
+
+        # Reorder splited columns
+        df = df[splited_columns]
+
+        # Append timestamps as index column
         df['timestamp'] = self.keys()
         df.set_index('timestamp', inplace=True)
 
         return df
 
-    def export_as_csv(self, filepath, exclude=[]):
-        """Write buffer content into a csv file."""
+    def save_as_csv(self, filepath, exclude=[]):
+        """Write into a csv file."""
 
         try:
             self.as_dataframe(exclude=exclude).to_csv(filepath, index=True)
@@ -143,8 +162,18 @@ class TimeStampedBuffer(collections.OrderedDict):
         except:
             raise RuntimeError(f'Can\' write {filepath}')
 
+    def save_as_json(self, filepath):
+        """Write into a json file."""
+
+        try:
+            with open(filepath, 'w', encoding='utf-8') as jsonfile:
+                json.dump(self, jsonfile, ensure_ascii = False, default=vars)
+
+        except:
+            raise RuntimeError(f'Can\' write {filepath}')
+
     def plot(self, names=[], colors=[], split={}, samples=None) -> list:
-        """Plot data into time chart."""
+        """Plot as [matplotlib](https://matplotlib.org/) time chart."""
 
         df = self.as_dataframe(split=split)
         legend_patches = []