Finnrick stringent

Stringent analysis set using Python with stricter quality control rules (98/95 purity, ±15% quantity, catastrophic endotoxin failures)

pythonFinnrick

Created: Thu 27 Nov 2025 05:15

Updated: Thu 27 Nov 2025 05:15

Analysis Rules (4)

identity

Identity confirmation test

Created Thu 27 Nov 2025 05:15

Python Code:

def analyze(result, sample, test):
    """Identity test: Pass if measure_flag is 'Pass', else Catastrophic"""
    if result["measure_flag"] == "Pass":
        return "Pass"
    return "Catastrophic"

purity

Purity percentage measurement

Created Thu 27 Nov 2025 05:15

Python Code:

def analyze(result, sample, test):
    """Purity test: >98% Pass, <95% Catastrophic, between is Fail"""
    value = result["measure_value"]
    if value is None:
        return "Neutral"
    if value > 98:
        return "Pass"
    if value < 95:
        return "Catastrophic"
    return "Fail"

quantity

Quantity measurement in mg

Created Thu 27 Nov 2025 05:15

Python Code:

def analyze(result, sample, test):
    """Quantity test: compare measure_value vs reference quantity.
    Within ±15% Pass, ±30% Fail, beyond Catastrophic.
    Uses batch_quantity if available, falls back to label_quantity.
    """
    value = result["measure_value"]
    if value is None:
        return "Neutral"
    
    # Determine reference quantity (batch_quantity preferred)
    ref_qty = sample["batch_quantity"]
    if ref_qty is None:
        ref_qty = sample["label_quantity"]
    
    if ref_qty is None:
        return "Neutral"
    
    # Calculate deviation percentage
    lower_pass = ref_qty * 0.85  # -15%
    upper_pass = ref_qty * 1.15  # +15%
    lower_fail = ref_qty * 0.7   # -30%
    upper_fail = ref_qty * 1.3   # +30%
    
    if lower_pass <= value <= upper_pass:
        return "Pass"
    if lower_fail <= value <= upper_fail:
        return "Fail"
    return "Catastrophic"

endotoxins

Endotoxin test

Created Thu 27 Nov 2025 05:15

Python Code:

def analyze(result, sample, test):
    """Endotoxins test: Pass only if measure_flag is 'Negative', 'Below LOQ' is Fail, any other flag is Catastrophic"""
    flag = result["measure_flag"]
    if flag == "Positive":
        return "Catastrophic"
    if flag == "Below LOQ":
        return "Fail"
    if flag == "Negative":
        return "Pass"
    return "Neutral"

Python Data Context

The analyze(result, sample, test) function receives these objects:

result

• .measure_value (number | null)

• .measure_flag (string | null)

• .result_date (string)

• .unit (string | null)

• .notes (string | null)

• .exception (string | null)

• .loq (number | null)

• .method (string | null)

sample

• .batch_quantity (number | null)

• .label_quantity (number | null)

• .registered_date (string)

• .batch_id (string | null)

• .batch_source (string | null)

• .storage_location (string | null)

test

• .tested_date (string | null)

• .coa_date (string | null)

• .coa_url (string | null)

• .coa_id (string | null)

Valid Return Values

• "Pass"

• "Fail"

• "Catastrophic"

• "Neutral"

Python code runs in a sandboxed environment with restricted builtins. Must define analyze(result, sample, test) function.