Alaea
Installation
pip3 install Alaea
KML 转 Shapefile 是可选功能，需要 GDAL：
pip3 install 'Alaea[gdal]'
Release
Direct execution cleans old artifacts, builds the package, uploads it with Twine, and cleans the artifacts after a successful upload:
./run_twine.py
Use --repository NAME to select a configured Twine repository. A failed build
does not attempt upload; a failed upload retains the new archives for diagnosis
and retry. Directly rerunning the script skips files already present on PyPI and
continues uploading the remaining archives.
Standard atmosphere datasets
xr_atmos_dataset builds any supported combination of wind, 2 metre air
temperature, per-period precipitation, mean sea-level pressure, visibility,
entire-atmosphere total cloud cover, hourly sunshine duration, 2 metre
relative humidity, surface wind gust, 2 metre dew point temperature, and
2 metre apparent temperature. The
single-element xr_wind_dataset, xr_air_temperature_dataset,
xr_precipitation_dataset, and xr_slp_dataset interfaces use the same
metadata and encoding path. Integer packing is enabled by default and can be
disabled with _COMPRESS=False when a caller needs to apply it after merging.
_TIME_type="str" writes a NetCDF string variable, while "char" writes a
fixed character matrix with a DateStr dimension. write_netcdf uses zlib by
default; write_netcdf(ds, path, compression="zstd") selects standard HDF5
Zstd filter 32015 with byte shuffle and fails clearly when its reader/writer
plugin is unavailable.
run_storage_fallback executes an explicit storage method or an ordered
AUTO method list. Applications provide their own operations and recoverable
error boundary, so input staging and output publication can share fallback
policy without sharing incompatible lifecycle code.
open_netcdf_input adds a shared single-file NetCDF reader for direct, local
SSD, memory, named-file, and Linux O_TMPFILE modes. For xarray.open_mfdataset,
stage_netcdf_inputs preserves input order while copying through a bounded
worker pool and removes only its own staged files when the context exits.
Unified spatial interpolation
s2s, g2s, s2g, and g2g use the same argument order. s means
scattered points and g means a grid. Grid coordinates may be one-dimensional
longitude/latitude axes or matching two-dimensional coordinate arrays.
import numpy as np
from Alaea.exutils import g2s, s2g
lon = np.array([120.0, 121.0])
lat = np.array([30.0, 31.0])
value = np.array([[1.0, 2.0], [3.0, 4.0]])
point_value = g2s(lon, lat, value, 120.5, 30.5)
station_lon = np.array([120.0, 121.0, 120.0, 121.0])
station_lat = np.array([30.0, 30.0, 31.0, 31.0])
station_value = np.array([1.0, 2.0, 3.0, 4.0])
grid_value = s2g(station_lon, station_lat, station_value, lon, lat)
All four functions accept method="linear", method="nearest",
method="cubic", or method="idw". IDW also accepts neighbors (default 8)
and power (default 2). Data may have leading dimensions such as
(time, lat, lon) or (time, point); these dimensions are preserved in the
result.
Coastline filling
from Alaea.baysalt.erosion_coastline import erosion_cal_id, erosion_via_id
weight = erosion_cal_id(lon, lat, value, k=4, judge_num=1, method='np.nan')
filled = erosion_via_id(weight, value)
method may be np.nan, nc.mask, or txt.mask. The input used to calculate
weights must be two-dimensional; applying weights supports any data whose last
two dimensions are latitude and longitude.
Legacy file-generation helpers remain available from their explicit modules,
for example Alaea.exutils.Interp.Interp_g2s.Grid2Sca, but are no longer
re-exported from Alaea.exutils; new interpolation code should use the four
unified functions above.
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