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Added reference DEM field to melt extent and snowline data imports #140

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Merged
albinwwells merged 4 commits into from
Oct 10, 2025
Merged

Added reference DEM field to melt extent and snowline data imports #140

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815a550
Added reference DEM field to melt extent and snowline data imports
albinwwells Oct 10, 2025
9b69c3c
Fixed type
albinwwells Oct 10, 2025
509dcf6
Updated melt extent json conversion to include ref_dem
albinwwells Oct 10, 2025
c4e2cd1
Ruffed up
btobers Oct 10, 2025
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40 changes: 38 additions & 2 deletions pygem/shop/meltextent_and_snowline_1d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -62,6 +62,7 @@ def meltextent_1d_to_gdir(
'z_min': Melt extent elevation minimum (meters)
'z_max': Melt extent elevation maximum (meters)
'direction': SAR path direction, stored as a string (e.g., 'ascending' or 'descending')
'ref_dem': Reference DEM used for elevation values
'ref_dem_year': Reference DEM year for elevation value of observations (m a.s.l.) (e.g., 2013 if using COP30)
"""
# get dataset file path
Expand All @@ -86,7 +87,15 @@ def meltextent_1d_to_gdir(
def validate_meltextent_1d_structure(data):
"""Validate that meltextent_1d CSV structure matches expected format."""

required_cols = ['date', 'z', 'z_min', 'z_max', 'direction', 'ref_dem_year']
required_cols = [
'date',
'z',
'z_min',
'z_max',
'direction',
'ref_dem',
'ref_dem_year',
]
for col in required_cols:
if col not in data.columns:
raise ValueError(f"Missing required column '{col}' in melt extent CSV.")
Expand Down Expand Up @@ -131,6 +140,13 @@ def validate_meltextent_1d_structure(data):
if not all(isinstance(x, str) for x in direction):
raise ValueError("All 'direction' values must be strings.")

# Validate reference DEM
ref_dem = data['ref_dem'].dropna().unique()
if not isinstance(ref_dem, (str)):
raise TypeError(
f"'ref_dem' must be an string, but got {ref_dem} ({type(ref_dem).__name__})."
)

# Validate reference DEM year
dem_year = data['ref_dem_year'].dropna().unique()
if len(dem_year) != 1:
Expand All @@ -153,6 +169,7 @@ def meltextent_csv_to_dict(data):
z_min = data['z_min'].astype(float).tolist()
z_max = data['z_max'].astype(float).tolist()
direction = data['direction'].astype(str).tolist()
ref_dem = data['ref_dem'].astype(str).tolist()[0]
ref_dem_year = data['ref_dem_year'].astype(int).tolist()[0]

data_dict = {
Expand All @@ -161,6 +178,7 @@ def meltextent_csv_to_dict(data):
'z_min': z_min,
'z_max': z_max,
'direction': direction,
'ref_dem': ref_dem,
'ref_dem_year': ref_dem_year,
}
return data_dict
Expand All @@ -185,6 +203,7 @@ def snowline_1d_to_gdir(
'z_min': Snowline elevation minimum (m a.s.l.)
'z_max': Snowline elevation maximum (m a.s.l.)
'direction': SAR path direction, stored as a string (e.g., 'ascending' or 'descending')
'ref_dem': Reference DEM used for elevation values
'ref_dem_year': Reference DEM year for elevation value of observations (m a.s.l.) (e.g., 2013 if using COP30)
"""
# get dataset file path
Expand All @@ -209,7 +228,15 @@ def snowline_1d_to_gdir(
def validate_snowline_1d_structure(data):
"""Validate that snowline_1d CSV structure matches expected format."""

required_cols = ['date', 'z', 'z_min', 'z_max', 'direction', 'ref_dem_year']
required_cols = [
'date',
'z',
'z_min',
'z_max',
'direction',
'ref_dem',
'ref_dem_year',
]
for col in required_cols:
if col not in data.columns:
raise ValueError(f"Missing required column '{col}' in snowline CSV.")
Expand Down Expand Up @@ -254,6 +281,13 @@ def validate_snowline_1d_structure(data):
if not all(isinstance(x, str) for x in direction):
raise ValueError("All 'direction' values must be strings.")

# Validate reference DEM
ref_dem = data['ref_dem'].dropna().unique()
if not isinstance(ref_dem, (str)):
raise TypeError(
f"'ref_dem' must be an string, but got {ref_dem} ({type(ref_dem).__name__})."
)

# Validate reference DEM year
dem_year = data['ref_dem_year'].dropna().unique()
if len(dem_year) != 1:
Expand All @@ -276,6 +310,7 @@ def snowline_csv_to_dict(data):
z_min = data['z_min'].astype(float).tolist()
z_max = data['z_max'].astype(float).tolist()
direction = data['direction'].astype(str).tolist()
ref_dem = data['ref_dem'].astype(str).tolist()[0]
ref_dem_year = data['ref_dem_year'].astype(int).tolist()[0]

data_dict = {
Expand All @@ -284,6 +319,7 @@ def snowline_csv_to_dict(data):
'z_min': z_min,
'z_max': z_max,
'direction': direction,
'ref_dem': ref_dem,
'ref_dem_year': ref_dem_year,
}
return data_dict