rmanach/covid-plotter
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add new arg (no plot) + analyse data function

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rmanach 2021-12-27 16:36:13 +01:00
parent 2357303295
commit a994f96eea
1 changed files with 95 additions and 27 deletions
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122
drees.py
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@ -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:
@ -287,11 +344,11 @@ def plot_bar_age_percent_vac_status_by_field(
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
)
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}"),
@ -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()
@ -460,19 +528,19 @@ 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)
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()
f_bars = partial(plot_bar_data_by_age_field, np_data, np_date)
with Pool(2) as pool:
pool.starmap(f_fields, plot_fields_args)
pool.starmap(f_bars, plot_vac_percent_age_args)
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()
f_bars = partial(plot_bar_data_by_age_field, np_data, np_date)
with Pool(2) as pool:
pool.starmap(f_fields, plot_fields_args)
pool.starmap(f_bars, plot_vac_percent_age_args)
for field in Field:
plot_cumulative_field(np_data, np_date, field)
plot_bar_age_percent_by_field(np_data, field)
for field in Field:
plot_cumulative_field(np_data, np_date, field)
plot_bar_age_percent_by_field(np_data, np_date, field)