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Merged
daliwang merged 1 commit into from
Dec 23, 2025
Merged

update extract_elm_restart_point.py #51

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56 changes: 46 additions & 10 deletions scripts/extract_elm_restart_point.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,12 +12,12 @@
from datetime import datetime

# ==================== Configuration Parameters (Default Values) ====================

SOURCE_NC = '/global/cfs/cdirs/m4814/daweigao/14_Code/all_dataset_1_degree/20250117_trendytest_ICB1850CNRDCTCBC_ad_spinup.elm.r.0021-01-01-00000.nc'
OUTPUT_NC = 'single_point_20_year_restart_extracted_43_56.nc' # Output filename
# SOURCE_NC = '/global/cfs/cdirs/m4814/daweigao/14_Code/all_dataset_1_degree/20250117_trendytest_ICB1850CNPRDCTCBC.elm.r.0781-01-01-00000.nc'
OUTPUT_NC = 'single_point_20_year_restart_extracted_303_17.nc' # Output filename
# Target coordinates
TARGET_LAT = 35.833332
TARGET_LON = -84.208336
TARGET_LAT = -17.4246
TARGET_LON = 303.75

# ==================== Command Line Argument Parser ====================
def parse_arguments():
Expand Down Expand Up @@ -109,14 +109,50 @@ def extract_single_point_elm(source_nc=None, output_nc=None, target_lat=None, ta
lat_vals = ds['grid1d_lat'].values
lon_vals = ds['grid1d_lon'].values

# Print unique latitude and longitude values in dataset
unique_lats = np.unique(lat_vals)
unique_lons = np.unique(lon_vals)
print(f" Dataset coordinate ranges:")
print(f" - Unique latitudes: {len(unique_lats)} values, range [{unique_lats.min():.6f}, {unique_lats.max():.6f}]")
print(f" - Unique longitudes (original): {len(unique_lons)} values, range [{unique_lons.min():.6f}, {unique_lons.max():.6f}]")
print(f" - All unique latitudes: {unique_lats}")
print(f" - All unique longitudes (original): {unique_lons}")

# Handle longitude format conversion (0-360° vs -180 to 180°)
lon_adjusted = lon_vals.copy()
if lon_vals.max() > 200:
# 智能选择：如果数据集和目标都是同一格式，保持原格式；否则统一转换
dataset_uses_360 = lon_vals.max() > 200
# 判断目标经度格式：> 180 肯定是 0-360，< 0 肯定是 -180~180，0-180 之间默认认为是 0-360
target_uses_360 = lon > 180 or (lon >= 0 and lon <= 180 and dataset_uses_360)

# 如果数据集和目标都是 0-360 格式，保持原格式比较（更高效）
if dataset_uses_360 and target_uses_360:
lon_adjusted = lon_vals.copy() # 保持 0-360 格式
target_lon_adjusted = lon # 保持 0-360 格式
print(f" Dataset uses 0-360° format, target also in 0-360° format ({lon:.6f})")
print(f" → Using 0-360° format for comparison (no conversion needed)")
# 如果数据集是 0-360 但目标是 -180~180，转换数据集
elif dataset_uses_360 and not target_uses_360:
lon_adjusted = np.where(lon_vals > 180, lon_vals - 360, lon_vals)
print(f" Detected 0-360° longitude format, converted to -180 to 180° format")

# Calculate Euclidean distance and find nearest neighbor
dist = np.sqrt((lat_vals - lat)**2 + (lon_adjusted - lon)**2)
target_lon_adjusted = lon # 目标已经是 -180~180 格式
print(f" Dataset uses 0-360° format, target uses -180~180° format")
print(f" → Converting dataset to -180~180° format for comparison")
unique_lons_adjusted = np.unique(lon_adjusted)
print(f" - Unique longitudes (adjusted): {len(unique_lons_adjusted)} values, range [{unique_lons_adjusted.min():.6f}, {unique_lons_adjusted.max():.6f}]")
print(f" - All unique longitudes (adjusted): {unique_lons_adjusted}")
# 如果数据集是 -180~180 但目标是 0-360，转换目标
elif not dataset_uses_360 and target_uses_360:
lon_adjusted = lon_vals.copy() # 数据集已经是 -180~180 格式
target_lon_adjusted = lon - 360 if lon > 180 else lon # 转换目标到 -180~180
print(f" Dataset uses -180~180° format, target uses 0-360° format ({lon:.6f})")
print(f" → Converting target to -180~180° format ({target_lon_adjusted:.6f}) for comparison")
# 如果两者都是 -180~180 格式，直接使用
else:
lon_adjusted = lon_vals.copy()
target_lon_adjusted = lon
print(f" Both dataset and target use -180~180° format")

# Calculate Euclidean distance using the ADJUSTED target
dist = np.sqrt((lat_vals - lat)**2 + (lon_adjusted - target_lon_adjusted)**2)
gridcell_idx_py = int(np.argmin(dist)) # Python 0-based index
gridcell_idx_elm = gridcell_idx_py + 1 # ELM 1-based index

Expand Down
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