add fields plot by vac status grouped by age

drees.py

@@ -22,6 +22,15 @@ DATA_URL = "https://data.drees.solidarites-sante.gouv.fr/api/records/1.0/search/
 DATA_REPOSITORY = "data"
 OUTPUT_REPOSITORY = "output"
 
+# cycler could be better, but for ages plots it's ok
+AGE_COLORS = {
+    0: "pink",
+    1: "green",
+    2: "blue",
+    3: "red",
+    4: "gray",
+}
+
 
 class DreesEnum(bytes, Enum):
     def __new__(cls, value, label):
@@ -65,7 +74,6 @@ def get_data(
     """
     collect covid data by age from DREES
     """
-    logging.info("fetching data...")
     os.makedirs(DATA_REPOSITORY, exist_ok=True)
     data_url = DATA_URL.format(extension=extension)
     if data_url.endswith("/"):
@@ -76,12 +84,14 @@ def get_data(
         else file_path
     )
     if not os.path.isfile(file_path) or refresh:
+        logging.info("fetching data...")
         r = requests.get(data_url)
         if not r.content:
             raise ValueError("no data provided froim the url : {}".format(data_url))
         with open(file_path, "wb") as f:
             f.write(r.content)
             return json.loads(r.content)
+    logging.info(f"opening {file_path}...")
     return json.load(open(file_path, "rb"))
 
 
@@ -160,6 +170,49 @@ def get_np_data(dic_data_grouped: Dict[dt, Any]) -> Tuple[np.ndarray, np.ndarray
     return np_data, np_date
 
 
+def split_by_vac_status(np_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+    return np.sum(np_data[:, :, 1:, :], axis=2), np_data[:, :, VacStatus.NC.value, :]
+
+
+def get_vaccine_percent(np_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+    """
+    get the vaccine percent per date, age and field
+    the vaccine data holds all the vaccine status except unvaccine
+    """
+    np_data_vac, np_data_unvac = split_by_vac_status(np_data)
+    np_percent_vac = np_data_vac / np.sum(np_data, axis=2)
+    np_percent_unvac = np_data_unvac / np.sum(np_data, axis=2)
+    return np_percent_vac, np_percent_unvac
+
+
+def get_percent_age_by_date_field(
+    np_data: np.ndarray, field: Field
+) -> Tuple[np.ndarray, np.ndarray]:
+    """
+    get numpy percent age grouped by date and field splited by vaccine status
+    """
+    np_percent_age_vac = np.empty((len(np_data), len(AgeGroup)))
+    np_percent_age_unvac = np.copy(np_percent_age_vac)
+    np_data_vac, np_data_unvac = split_by_vac_status(np_data)
+    for idx_date in range(len(np_data_vac)):
+        sum_effectif = np.nansum(np_data_vac[idx_date, :, field.value])
+        for age_group in AgeGroup:
+            np_percent_age_vac[idx_date, age_group.value] = np.round(
+                (np_data_vac[idx_date, age_group.value, field.value] / sum_effectif)
+                * 100,
+                2,
+            )
+    for idx_date in range(len(np_data_unvac)):
+        sum_effectif = np.nansum(np_data_unvac[idx_date, :, field.value])
+        for age_group in AgeGroup:
+            np_percent_age_unvac[idx_date, age_group.value] = np.round(
+                (np_data_unvac[idx_date, age_group.value, field.value] / sum_effectif)
+                * 100,
+                2,
+            )
+    return np_percent_age_vac, np_percent_age_unvac
+
+
 def get_plot_fig(
     grid: Optional[bool] = True,
     date_format: Optional[str] = DATE_FORMAT,
@@ -193,8 +246,68 @@ def save_and_close_fig(
     logging.info(f"{output_path} plotted")
 
 
-def split_by_vac_status(np_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
+def analyse(np_data: np.ndarray, np_date: np.ndarray) -> None:
-    return np.sum(np_data[:, :, 1:, :], axis=2), np_data[:, :, VacStatus.NC.value, :]
+    """
+    analyse data
+    """
+    logging.info("analysing data...")
+    np_percent_vac, _ = get_vaccine_percent(np_data)
+
+    logging.info("--- vaccine mean percent ---")
+    for age_group in AgeGroup:
+        for field in Field:
+            mean_vac_percent = np.round(
+                np.nanmean(np_percent_vac[:, age_group.value, field.value]) * 100, 2
+            )
+            print(f"{field.label} - {age_group.label} - vac : {mean_vac_percent}%")
+
+
+def plot_bar_age_percent_vac_status_by_field(
+    np_data_vac_status: np.ndarray, field: Field, is_vac: Optional[bool] = True
+) -> None:
+    fig, ax = get_plot_fig(figsize=(22, 8))
+    bottom = np_data_vac_status[:, 0]
+    title = "vac" if is_vac else "no vac"
+    for age_group in AgeGroup:
+        percents_age = np_data_vac_status[:, age_group.value]
+        if age_group.value > 0:
+            ax.bar(
+                np_date,
+                percents_age,
+                label=age_group.label,
+                bottom=bottom,
+                color=AGE_COLORS[age_group.value],
+            )
+            bottom += percents_age
+        else:
+            ax.bar(
+                np_date,
+                percents_age,
+                label=age_group.label,
+                color=AGE_COLORS[age_group.value],
+            )
+
+        ax.set_ylabel("%")
+        ax.set_title(f"{field.label} - {title}")
+        plt.legend(
+            [age_group.label for age_group in AgeGroup], loc="upper right", frameon=True
+        )
+    save_and_close_fig(
+        fig,
+        os.path.join(OUTPUT_REPOSITORY, f"age_percent_{title}_{field.label}"),
+        has_legend=False,
+    )
+
+
+def plot_bar_age_percent_by_field(np_data: 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
+    )
+    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(
@@ -210,8 +323,8 @@ def plot_cumulative_field(
         np_cumulate_unvac: np.ndarray = np.cumsum(
             np_data_unvac[:, age_group.value, field.value], axis=0
         )
-        plt.plot(np_date, np_cumulate_vac, label=f"{age_group.label} vax")
+        plt.plot(np_date, np_cumulate_vac, label=f"{age_group.label} vac")
-        plt.plot(np_date, np_cumulate_unvac, label=f"{age_group.label} no vax")
+        plt.plot(np_date, np_cumulate_unvac, label=f"{age_group.label} no vac")
 
     plt.title(f"nombre de {field.label} cumulé par age")
     plt.xlabel("date")
@@ -244,17 +357,6 @@ def plot_fields_by_age_vac(
     )
 
 
-def get_vaccine_percent(np_data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
-    """
-    get the vaccine percent per date, age and field
-    the vaccine data holds all the vaccine status except unvaccine
-    """
-    np_data_vac, np_data_unvac = split_by_vac_status(np_data)
-    np_percent_vac = np_data_vac / np.sum(np_data, axis=2)
-    np_percent_unvac = np_data_unvac / np.sum(np_data, axis=2)
-    return np_percent_vac, np_percent_unvac
-
-
 def plot_bar_data_by_age_field(
     np_data: np.ndarray,
     np_date: np.ndarray,
@@ -272,14 +374,16 @@ def plot_bar_data_by_age_field(
 
     for idx_date in range(len(np_date)):
         vac_percent = np.round(
-            np_percent_vac[idx_date, age_group.value, field.value] * 100
+            np_percent_vac[idx_date, age_group.value, field.value] * 100, 2
         )
         unvac_percent = np.round(
-            np_percent_unvac[idx_date, age_group.value, field.value] * 100
+            np_percent_unvac[idx_date, age_group.value, field.value] * 100, 2
+        )
+        bar_vac = ax.bar(idx_date, vac_percent, color="b", label="vac")
+        ax.bar(idx_date, unvac_percent, bottom=vac_percent, color="r", label="no vac")
+        ax.bar_label(
+            bar_vac, label_type="edge", color="black", fontsize="7", fmt="%.0f"
         )
-        bar_vac = ax.bar(idx_date, vac_percent, color="b", label="vax")
-        ax.bar(idx_date, unvac_percent, bottom=vac_percent, color="r", label="no vax")
-        ax.bar_label(bar_vac, label_type="edge", color="black", fontsize="8")
         ax.set_ylim(top=105)  # to display 100% label
 
     ax.set_ylabel("%")
@@ -293,7 +397,7 @@ def plot_bar_data_by_age_field(
             for idx, d in enumerate(np_date.astype(dt))
         ],
     )
-    plt.legend(["vax", "no vax"], loc=0, frameon=True)
+    plt.legend(["vac", "no vac"], loc="upper right", frameon=True)
 
     save_and_close_fig(
         fig,
@@ -331,10 +435,12 @@ if __name__ == "__main__":
         - cumulative deaths by age
         - hc, sc, dc by vaccine status and age
         - hc, sc, dc (vaccine/unvaccine percent) by age
+        - hc, sc, dc (age grouped percent) by field
     Main indicators are :
         - hospitalisations (hc)
         - criticals (sc)
         - deaths (dc)
+    hc, sc, dc include positive PCR tests
     """
 
     parser = argparse.ArgumentParser()
@@ -357,6 +463,8 @@ if __name__ == "__main__":
 
     np_data, np_date = get_np_data(dic_data_grouped)
 
+    analyse(np_data, np_date)
+
     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()
@@ -367,3 +475,4 @@ if __name__ == "__main__":
 
     for field in Field:
         plot_cumulative_field(np_data, np_date, field)
+        plot_bar_age_percent_by_field(np_data, field)