presentation

Author: Morgan Squire

Diff for: README.md

@@ -15,8 +15,8 @@ graph TB
     p2 --> I[Industry]
     p3 --> A[Asset Size]
     p3 --> D[Difference]
-    D --> R[Retention]
     D --> L[Limit]
+    D --> R[Retention]
 ```
 When the `calculate()` method is called on the root object, it calls the `calculate()` method on its child nodes. When a terminal node is reached, the factor is returned and when a non-terminal node is reached, the CompoundFactor calls the `calculate()` method on its children.
 

Diff for: demo/create_rate_plan.pdf

@@ -1,7 +1,14 @@
+---
+title: "Pyrateer Demo"
+---
+```{python}
 from pyrateer.factors import NumericFactor, CategoricalFactor, ConstantFactor
 import pickle
+```
 
+## Create the Rate Plan
 
+```{python}
 asset_size = NumericFactor(
     "Asset Size",
     {
@@ -88,9 +95,17 @@
     }
 )
 loss_cost = ConstantFactor("Loss Cost", 1.7)
+```
 
+Once the rate plan factors have been created, they can be combined using arithmetic operators.
+
+```{python}
 rate_plan = asset_size * (limit - retention) * industry * loss_cost
+```
+
+## Test
 
+```{python}
 json_input = {
     "Asset Size": 1_200_000,
     "Limit": 5_000_000,
@@ -101,6 +116,10 @@
 rate = rate_plan.calculate(**json_input)
 
 print(rate)
+```
 
+## Pickle the Rate Plan
+```{python}
 with open("rate_plan.pkl", "wb") as f:
-    pickle.dump(rate_plan, f)
+    pickle.dump(rate_plan, f)
+```

Diff for: example.py renamed to demo/create_rate_plan.qmd

@@ -0,0 +1,62 @@
+---
+title: "Pyrateer Demo"
+author: "Morgan Squire"
+format: revealjs
+---
+
+## Actuarial Analysis
+
+- See Excel file
+
+## Pyrateer Package
+
+- Python rating engine
+- Uses base class for quick implementation of new subclasses
+  - `ConstantFactor` was added later in a matter of minutes
+- Overloads arithmetic operators so ROC formulas can be typed directly
+```{.python code-line-numbers="|1|2-7|8"}
+rate_plan = asset_size * (limit - retention) * industry * loss_cost
+json_input = {
+    "Asset Size": 1_200_000,
+    "Limit": 5_000_000,
+    "Retention": 1_000_000,
+    "Industry": "Hazard Group 2"
+}
+print(rate_plan.calculate(json_input))
+```
+
+## Classes
+
+- `RatingFactor`: base class
+  - `NumericFactor`: numeric inputs
+  - `CategoricalFactor`: categorical inputs
+  - `ConstantFactor`: no inputs
+  - `CompoundFactor`: the result of arithmetic operators
+
+## Compound Factors
+
+Created with arithmetic operators
+
+Has a special calculate function that calculates the component objects and combines them using the provided operator
+
+```{mermaid}
+graph TB
+    p1[Product] --> p2[Product]
+    p1 --> LC[Loss Cost Factor]
+    p2 --> p3[Product]
+    p2 --> I[Industry]
+    p3 --> A[Asset Size]
+    p3 --> D[Difference]
+    D --> L[Limit]
+    D --> R[Retention]
+```
+
+## Rate Plan PDFs
+
+See rate plan pdfs
+
+## Room for Improvement
+
+- Tree navigation functions
+- Interaction Factors
+- JSON rate_plan definition (better than pickling)