rain_wind_10m
import pandas as pd
from cedarkit.plots.types import AreaRange
from cedar_graph.plots.cn.rain_wind_10m.default import PlotMetadata, plot, load_data
from cedar_graph.data import LocalDataSource, DataLoader# 数据环境配置：使用本地数据目录（可用环境变量 CEDARKIT_NOTEBOOK_DATA_ROOT 覆盖）
from cedarkit_notebook.data import get_data_root, get_dataset_query
DATA_CLASS = "cmadaas"
STORAGE_BASE = str(get_data_root())Notebook Cell
import sys
from loguru import logger
logger.remove()
logger.add(sys.stderr, level="INFO")1# 起报时次与预报时效固定为本地已下载数据（见 data/metadata/cma-meso-3km.yaml）
query = get_dataset_query("cma-meso-3km")
start_time = pd.to_datetime(query["start_time"], format="%Y%m%d%H")
forecast_time = pd.to_timedelta(query["forecast_time"])
default_sample_step = 0.09
interval = pd.to_timedelta("12h")绘制东亚区域¶
使用 CMA-MESO-3KM 数据
system_name = "CMA-MESO-3KM"metadata = PlotMetadata(
start_time=start_time,
forecast_time=forecast_time,
system_name=system_name,
sample_step=default_sample_step,
interval=interval,
)
data_source = LocalDataSource(system_name=system_name, data_class=DATA_CLASS, storage_base=STORAGE_BASE)
data_loader = DataLoader(data_source=data_source)
plot_data = load_data(
data_loader=data_loader,
start_time=start_time,
forecast_time=forecast_time,
interval=metadata.interval,
)
panel = plot(
plot_data=plot_data,
plot_metadata=metadata,
)
panel.show()/home/wangdp/project/cedarkit/notebook-project/notebook-devel/repo/cedarkit-notebook-project/cedarkit-notebook/.venv/lib/python3.14/site-packages/gribapi/__init__.py:23: UserWarning: ecCodes 2.42.0 or higher is recommended. You are running version 2.34.1
warnings.warn(
绘制区域¶
使用 CMA-MESO-3KM 数据，绘制华北区域
system_name = "CMA-MESO-3KM"area_name = "NorthChina"
area_range = AreaRange.from_tuple((105, 125, 34, 45))metadata = PlotMetadata(
start_time=start_time,
forecast_time=forecast_time,
system_name=system_name,
interval=interval,
area_name=area_name,
area_range=area_range,
)
data_source = LocalDataSource(system_name=system_name, data_class=DATA_CLASS, storage_base=STORAGE_BASE)
data_loader = DataLoader(data_source=data_source)
plot_data = load_data(
data_loader=data_loader,
start_time=start_time,
forecast_time=forecast_time,
interval=metadata.interval,
)
panel = plot(
plot_data=plot_data,
plot_metadata=metadata,
)