add new arg (no plot) + analyse data function

drees.py

@@ -167,6 +167,9 @@ def get_np_data(dic_data_grouped: Dict[dt, Any]) -> Tuple[np.ndarray, np.ndarray
                     idx_field = get_enum_field(field)
                     np_data[idx_date, idx_age, idx_vac, idx_field] = value
     logging.info("date and data generated")
+    date_start = np_date[0]
+    date_end = np_date[len(np_date) - 1]
+    logging.info(f"range period : {date_start} - {date_end}")
     return np_data, np_date
 
 
@@ -185,7 +188,7 @@ def get_vaccine_percent(np_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
     return np_percent_vac, np_percent_unvac
 
 
-def get_percent_age_by_date_field(
+def get_percent_age_by_date_field_vac_splited(
     np_data: np.ndarray, field: Field
 ) -> Tuple[np.ndarray, np.ndarray]:
     """
@@ -213,10 +216,32 @@ def get_percent_age_by_date_field(
     return np_percent_age_vac, np_percent_age_unvac
 
 
+def get_percent_age_by_date_field(np_data: np.ndarray, field: Field) -> np.ndarray:
+    """
+    get numpy percent age grouped by date and field
+    """
+    np_percent_age = np.empty((len(np_data), len(AgeGroup)))
+    for idx_date in range(len(np_data)):
+        sum_effectif = np.nansum(
+            np.nansum(np_data[idx_date, :, :, field.value], axis=1)
+        )
+        for age_group in AgeGroup:
+            np_percent_age[idx_date, age_group.value] = np.round(
+                (
+                    np.sum(np_data[idx_date, age_group.value, :, field.value], axis=0)
+                    / sum_effectif
+                )
+                * 100,
+                2,
+            )
+    return np_percent_age
+
+
 def get_plot_fig(
     grid: Optional[bool] = True,
     date_format: Optional[str] = DATE_FORMAT,
     figsize: Optional[Tuple[int, int]] = None,
+    locator: Optional[Any] = md.MonthLocator(),
 ) -> plt.figure:
     """
     return pyplot fig, ax to plot data over range period with date formatting
@@ -224,7 +249,7 @@ def get_plot_fig(
     fig, ax = plt.subplots(figsize=figsize)
     ax.grid(grid)
     date_formatter = md.DateFormatter(date_format)
-    ax.xaxis.set_major_locator(md.AutoDateLocator())
+    ax.xaxis.set_major_locator(locator)
     ax.xaxis.set_major_formatter(date_formatter)
     fig.autofmt_xdate()
     return fig, ax
@@ -253,7 +278,7 @@ def analyse(np_data: np.ndarray, np_date: np.ndarray) -> None:
     logging.info("analysing data...")
     np_percent_vac, _ = get_vaccine_percent(np_data)
 
-    logging.info("--- vaccine mean percent ---")
+    logging.info("--- field by age vaccine mean percent ---")
     for age_group in AgeGroup:
         for field in Field:
             mean_vac_percent = np.round(
@@ -261,11 +286,43 @@ def analyse(np_data: np.ndarray, np_date: np.ndarray) -> None:
             )
             print(f"{field.label} - {age_group.label} - vac : {mean_vac_percent}%")
 
+    logging.info("--- age by field and vac status mean percent ---")
+    for field in Field:
+        np_percent_age = get_percent_age_by_date_field(np_data, field)
+        (
+            np_percent_age_vac,
+            np_percent_age_unvac,
+        ) = get_percent_age_by_date_field_vac_splited(np_data, field)
+        for age_group in AgeGroup:
+            percent_age_mean = np.round(
+                np.nanmean(np_percent_age[:, age_group.value]), 2
+            )
+            print(
+                f"age: {age_group.label} - field: {field.label} = {percent_age_mean}%"
+            )
+
+            percent_age_vac_mean = np.round(
+                np.nanmean(np_percent_age_vac[:, age_group.value]), 2
+            )
+            print(
+                f"age: {age_group.label} - status: vac - field: {field.label} = {percent_age_vac_mean}%"
+            )
+
+            percent_age_unvac_mean = np.round(
+                np.nanmean(np_percent_age_unvac[:, age_group.value]), 2
+            )
+            print(
+                f"age: {age_group.label} - status: unvac - field: {field.label} = {percent_age_unvac_mean}%"
+            )
+
 
 def plot_bar_age_percent_vac_status_by_field(
-    np_data_vac_status: np.ndarray, field: Field, is_vac: Optional[bool] = True
+    np_data_vac_status: np.ndarray,
+    np_date: np.ndarray,
+    field: Field,
+    is_vac: Optional[bool] = True,
 ) -> None:
-    fig, ax = get_plot_fig(figsize=(22, 8))
+    fig, ax = get_plot_fig(figsize=(22, 8), locator=md.WeekdayLocator())
     bottom = np_data_vac_status[:, 0]
     title = "vac" if is_vac else "no vac"
     for age_group in AgeGroup:
@@ -299,15 +356,20 @@ def plot_bar_age_percent_vac_status_by_field(
     )
 
 
-def plot_bar_age_percent_by_field(np_data: np.ndarray, field: Field) -> None:
+def plot_bar_age_percent_by_field(
+    np_data: np.ndarray, np_date: np.ndarray, field: Field
+) -> None:
     """
     plot percent vaccinated field group by age bar diagram
     """
-    np_percent_age_vac, np_percent_age_unvac = get_percent_age_by_date_field(
+    (
-        np_data, field
+        np_percent_age_vac,
+        np_percent_age_unvac,
+    ) = get_percent_age_by_date_field_vac_splited(np_data, field)
+    plot_bar_age_percent_vac_status_by_field(np_percent_age_vac, np_date, field)
+    plot_bar_age_percent_vac_status_by_field(
+        np_percent_age_unvac, np_date, field, is_vac=False
     )
-    plot_bar_age_percent_vac_status_by_field(np_percent_age_vac, field)
-    plot_bar_age_percent_vac_status_by_field(np_percent_age_unvac, field, is_vac=False)
 
 
 def plot_cumulative_field(
@@ -366,7 +428,6 @@ def plot_bar_data_by_age_field(
     """
     display a bar graph by field and age over the data period
     bars display vaccine status percent
-    a limit days period is set to have an readable plot
     """
     np_percent_vac, np_percent_unvac = get_vaccine_percent(np_data)
     # adjust the fig size to display correctly bars and labels
@@ -451,6 +512,13 @@ if __name__ == "__main__":
         default=False,
         help="redownload data for updates",
     )
+    parser.add_argument(
+        "-np",
+        "--no-plot",
+        action="store_true",
+        default=False,
+        help="redownload data for updates",
+    )
 
     args = parser.parse_args()
 
@@ -460,11 +528,11 @@ if __name__ == "__main__":
         file_path=os.path.join(DATA_REPOSITORY, "dress.json"), refresh=args.refresh
     )
     dic_data_grouped: Dict[dt, Any] = group_by_age_date(dic_data)
-
     np_data, np_date = get_np_data(dic_data_grouped)
 
     analyse(np_data, np_date)
 
+    if not args.no_plot:
         plot_fields_args = get_age_vac_args()
         f_fields = partial(plot_fields_by_age_vac, np_data, np_date)
         plot_vac_percent_age_args = get_age_field_args()
@@ -475,4 +543,4 @@ if __name__ == "__main__":
 
         for field in Field:
             plot_cumulative_field(np_data, np_date, field)
-        plot_bar_age_percent_by_field(np_data, field)
+            plot_bar_age_percent_by_field(np_data, np_date, field)