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crm.py
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crm.py
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"""Certified reference material (CRM) data."""
import numpy as np
class ReferenceMaterial:
"""A generic reference material."""
def __init__(self, **kwargs):
assert all(
[
key
in [
"batch",
"salinity",
"dissolved_inorganic_carbon",
"dissolved_inorganic_carbon_std",
"total_alkalinity",
"total_alkalinity_std",
"phosphate",
"silicate",
"nitrite",
"nitrate",
]
for key in kwargs
]
)
self.__dict__.update((k, v) for k, v in kwargs.items())
dickson_certified_values = {
171: ReferenceMaterial(
batch=171,
salinity=33.434,
dissolved_inorganic_carbon=2029.19,
dissolved_inorganic_carbon_std=0.87,
total_alkalinity=2217.40,
total_alkalinity_std=0.63,
phosphate=0.43,
silicate=2.3,
nitrite=0.00,
nitrate=3.1,
),
186: ReferenceMaterial(
batch=186,
salinity=33.525,
dissolved_inorganic_carbon=2012.59,
dissolved_inorganic_carbon_std=0.80,
total_alkalinity=2212.00,
total_alkalinity_std=0.53,
phosphate=0.42,
silicate=3.3,
nitrite=0.01,
nitrate=2.8,
),
}
def dickson(crm_batches, fields):
"""Dickson seawater certified reference material."""
if isinstance(fields, str):
if fields == "all":
fields = [
"batch",
"salinity",
"dissolved_inorganic_carbon",
"dissolved_inorganic_carbon_std",
"total_alkalinity",
"total_alkalinity_std",
"phosphate",
"silicate",
"nitrite",
"nitrate",
]
else:
fields = [fields]
return {
field: np.array(
[
dickson_certified_values[crm_batch].__dict__[field]
if crm_batch in dickson_certified_values
else np.nan
for crm_batch in crm_batches
]
)
for field in fields
}
def dic_calibration_factor(
data=None,
dic_certified="dic_certified",
density_analysis="density_analysis",
counts_corrected="counts_corrected",
):
"""Calculate volume-cancelling DIC calibration factor."""
if data is not None:
dic_certified = data[dic_certified]
density_analysis = data[density_analysis]
counts_corrected = data[counts_corrected]
return dic_certified * density_analysis / counts_corrected
def calibrate_dic(
data=None,
calibration_factor="dic_calibration_factor",
counts_corrected="counts_corrected",
density_analysis="density_analysis",
):
"""Apply volume-cancelling DIC calibration factor."""
if data is not None:
calibration_factor = data[calibration_factor]
counts_corrected = data[counts_corrected]
density_analysis = data[density_analysis]
return calibration_factor * counts_corrected / density_analysis