senaduka/old-riskletpy
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Promenjene vrednosti weight + likelihood

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Amir
2025-05-12 22:48:16 +02:00
parent 1109489ef3
commit cbd0832ca1
5 changed files with 69 additions and 78 deletions
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70
backend/core/tables.py
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@@ -4,56 +4,48 @@ from backend.core.utils import calculate_aggregate_likelihood, calculate_aggrega
def risk_matrix_table():
likelihood_labels = [
"Certain (90-100%)",
"Almost Certain (80-89%)",
"Very Probable (70-79%)",
"Probable (60-69%)",
"Highly Likely (50-59%)",
"Likely (40-49%)",
"Occasional (30-39%)",
"Possible (20-29%)",
"Unlikely (10-19%)",
"Rare (0-9%)"
"Almost Certain (90-100%) (5)",
"Probable (51-89%) (4)",
"Possible (25-50%) (3)",
"Unlikely (11-24%) (2)",
"Rare (0-10%) (1)"
]
impact_labels = [
"Insignificant",
"Minor",
"Moderate",
"Major",
"Severe",
"Catastrophic",
"Critical",
"Extreme",
"Disastrous",
"Unrecoverable"
"Insignificant (1)",
"Significant (2)",
"Severe (3)",
"Material (4)",
"Major (5)"
]
color_mapping = {
"Very Low": "green",
"Low": "lightgreen",
"Very Low": "lightgreen",
"Low": "green",
"Medium": "yellow",
"High": "orange",
"Critical": "red"
}
table_matrix_risk = [["Impact ↓ / Likelihood →"] + impact_labels]
def get_label(score):
if score <= 2:
return "Very Low"
elif score <= 4:
return "Low"
elif score <= 10:
return "Medium"
elif score <= 16:
return "High"
else:
return "Critical"
for likelihood_index, likelihood_label in enumerate(likelihood_labels, start=1):
reversed_index = 11 - likelihood_index
row = [likelihood_label]
for impact_index in range(1, 11):
score = reversed_index * impact_index
if score <= 20:
label = "Very Low"
elif score <= 40:
label = "Low"
elif score <= 60:
label = "Medium"
elif score <= 80:
label = "High"
else:
label = "Critical"
table_matrix_risk = [["Likelihood ↓ / Impact →"] + impact_labels]
for likelihood in range(5, 0, -1):
row = [likelihood_labels[5 - likelihood]]
for impact in range(1, 6):
score = likelihood * impact
label = get_label(score)
color_class = color_mapping[label]
row.append((score, label, color_class))
table_matrix_risk.append(row)
@@ -82,7 +74,7 @@ def get_risk_table(document):
.values('control', 'control__name', 'weight', 'likelihood')
.distinct()
)
max_weight = 10*10
max_weight = 10*5
total_weight = calculate_aggregate_weight(controls)
total_likelihood = calculate_aggregate_likelihood(controls)
impact, likelihood = map_weight_to_impact_likelihood(total_weight, total_likelihood, max_weight)