Adding a new use case - fix syntax issues (#255)

wesleyboar · nbonfante · sebabedin · web-flow · commit 0d26325df4c3 · 2025-12-11T15:40:59.000-06:00
## What Did You Change? 1. [fix: use local "Open in DesignSafe" image](da0864b) 2. [fix: use 4 spaces (or tab char) for indentation](5129fe5) 3. [fix: use new lines around nested lists](993275c) 4. [fix: nest list item content correctly](b5a7386) 5. [fix: clarify two paragraphs, not just a new line](7622f4e) 6. [chore: consistent formatting for \*\*Output/s:\*\*](46d59d3) 7. [chore: remove superfluous spaces](8a83d11) 8. [feat: add to navigation](2f5e29b) ## Do You Want Support (syntax, design, etc)? I present to @nbonfante, to guide future contributions. Preview: [deploy-preview-255--ds-user-guide.netlify.app](https://deploy-preview-255--ds-user-guide.netlify.app/) | Before | After | | - | - | | <img width="900" height="470" alt="2 before" src="https://github.com/user-attachments/assets/3b49527a-3505-4aa4-8fae-73f2fcefb3c4" /> | <img width="900" height="470" alt="2 after" src="https://github.com/user-attachments/assets/8ff45727-e6e4-4163-8a28-407888641aa7" /> | | <img width="900" height="470" alt="3 before" src="https://github.com/user-attachments/assets/8f277302-208f-4455-b1eb-006086f4d9dd" /> | <img width="900" height="470" alt="3 after" src="https://github.com/user-attachments/assets/d670d0f4-1e31-4df5-a2cf-6f52a8c2de3f" /> | | <img width="900" height="470" alt="4 before" src="https://github.com/user-attachments/assets/ef9651a2-2604-477e-9b38-460982e8c61d" /> | <img width="900" height="470" alt="4 after" src="https://github.com/user-attachments/assets/c5e7b4e9-681a-472b-a47d-68c074f801cf" /> | | <img width="900" height="470" alt="5 before" src="https://github.com/user-attachments/assets/9d54dcdf-1b08-4672-819e-eb1af6f8a666" /> | <img width="900" height="470" alt="5 after" src="https://github.com/user-attachments/assets/6f4fe96b-102b-4c11-baee-1cd9145b14c3" /> | | <img width="900" height="470" alt="6 before" src="https://github.com/user-attachments/assets/2d9bce7b-c5c8-4320-a450-a74dae8ddae9" /> | <img width="900" height="470" alt="6 after" src="https://github.com/user-attachments/assets/62c9c69c-c6bd-4624-b635-62e6dfd162e4" /> | | <img width="900" height="470" alt="7 before" src="https://github.com/user-attachments/assets/9cf2c964-c571-4c24-b0eb-790a0b2d42a2" /> | <img width="900" height="470" alt="7 after" src="https://github.com/user-attachments/assets/0d09d1d7-eaba-413a-886c-29990a3f5b3f" /> | | <img width="900" height="470" alt="8 before" src="https://github.com/user-attachments/assets/8d3d271c-61f0-40e6-82e9-28bf0058fd79" /> | <img width="900" height="470" alt="8 after" src="https://github.com/user-attachments/assets/1040afc6-d3bc-4cf1-a0dc-1e09fdf076c3" /> | ## Any Reference Material Worth Sharing? Fixes issues found in #251 / #252. --------- Co-authored-by: nbonfante <nbonfante2023@my.fit.edu> Co-authored-by: Seb <sebabedin@gmail.com>
diff --git a/mkdocs.yml b/mkdocs.yml
@@ -160,6 +160,7 @@ nav:
       - Field Sensing Wind Events: usecases/pinelli/usecase.md
       - Hurricane Data Integration Visualization: usecases/pinelli/2usecase.md
       - Wind Speed Estimation and Conversion: usecases/pinelli/3usecase.md
+      - Empirical Hurricane Vulnerability and Fragility Curves: usecases/pinelli/4usecase.md
       - ADCIRC Datasets: usecases/dawson/usecase2.md
       - Large-Scale Storm Surge: usecases/dawson/usecase.md
       - CFD Analysis of Winds on Structures: usecases/kareem/usecase.md
diff --git a/user-guide/usecases/pinelli/4usecase.md b/user-guide/usecases/pinelli/4usecase.md
@@ -17,7 +17,7 @@ The uniqueness of this project lies in its transparency, flexibility, and modula
 
 The primary audience for this project includes researchers in wind engineering, structural safety, and risk analysis who require transparent methods for vulnerability modeling. It is also intended for insurance and reinsurance professionals seeking empirically derived curves for underwriting, pricing, and capital allocation. Policy makers and engineers can use the results to support evidence-based decision making and improvements in building codes. Finally, educators and students can adopt the notebooks as teaching material for courses on catastrophe modeling, vulnerability analysis, and disaster risk reduction.
 
-**Key steps:** 
+**Key steps:**
 
 - **Data Processing:** Cleaning raw datasets and producing an integrated hazard–damage file.
 - **Damage Ratio Calculation:** Computing losses relative to replacement value and assigning wind-speed bins.
@@ -35,62 +35,64 @@ You can access and run them directly on **DesignSafe** by clicking the link belo
 
 | **Scope** | **Notebook** | **Open in DesignSafe** |
 |-----------|--------------|-------------------------|
-| Generate processed hazard & exposure dataset | `00_generator_of_processed_Info_Natural_Event.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
-| Compute damage ratios and define wind ranges | `03_damage_ratios_&_ranges.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
-| Build empirical vulnerability matrix | `05_vulnerability_matrix.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
-| Fit and visualize vulnerability curves | `08_vulnerability_curve_analysis.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
-| Generate fragility curves | `13_Fragility_curve_analysis.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
-| Compare curves across structural classes | `18_Comparison_of_curves_analysis.ipynb` | [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Generate processed hazard & exposure dataset | `00_generator_of_processed_Info_Natural_Event.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Compute damage ratios and define wind ranges | `03_damage_ratios_&_ranges.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Build empirical vulnerability matrix | `05_vulnerability_matrix.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Fit and visualize vulnerability curves | `08_vulnerability_curve_analysis.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Generate fragility curves | `13_Fragility_curve_analysis.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
+| Compare curves across structural classes | `18_Comparison_of_curves_analysis.ipynb` | [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2) |
 
 ### DesignSafe Resources
 
 The following DesignSafe resources were used in developing this Use Case:
 
-- [Jupyter notebook on DesignSafe JupyterHub](https://www.designsafe-ci.org/rw/workspace/jupyter/)  
+- [Jupyter notebook on DesignSafe JupyterHub](https://www.designsafe-ci.org/rw/workspace/jupyter/)
 - [DesignSafe Publication: Empirical Hurricane Vulnerability and Fragility Curves (DOI: 10.17603/ds2-q60v-z247)](https://doi.org/10.17603/ds2-q60v-z247)
 
 ## System Requirements
 
-- **Python 3.11+**  
-- **Jupyter Notebook environment** (DesignSafe JupyterHub or local)  
+- **Python 3.11+**
+- **Jupyter Notebook environment** (DesignSafe JupyterHub or local)
 
 ## Required Libraries
 
 Before running the notebook, make sure the following Python libraries are installed:
 
 | **Package** | **Description** |
 |-------------|-----------------|
-|  `numpy` | Numerical operations and array handling |
-|   `pandas` | Data manipulation and tabular data processing |
-|   `scipy` | Curve fitting and optimization routines (`curve_fit`) |
-|  `scikit-learn` | Regression metrics (R², MAE, RMSE) used for evaluating fitted curves |
-|  `matplotlib` | Plotting vulnerability and fragility curves |
-|   `seaborn` | Statistical visualization and enhanced plotting (used in damage ratio analysis) |
+| `numpy` | Numerical operations and array handling |
+| `pandas` | Data manipulation and tabular data processing |
+| `scipy` | Curve fitting and optimization routines (`curve_fit`) |
+| `scikit-learn` | Regression metrics (R², MAE, RMSE) used for evaluating fitted curves |
+| `matplotlib` | Plotting vulnerability and fragility curves |
+| `seaborn` | Statistical visualization and enhanced plotting (used in damage ratio analysis) |
 
 ## Steps to Run
 
-1. **Download or access the repository:** [![Open in DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2)
+1. **Download or access the repository:** [![Open in DesignSafe](/user-guide/img/Open-in-DesignSafe.svg)](https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-6138?version=2)
 
 2. **Open the Jupyter notebooks** located in the root directory:
-   - `00_generator_of_processed_Info_Natural_Event.ipynb`
-   - `03_damage_ratios_&_ranges.ipynb`
-   - `05_vulnerability_matrix.ipynb`
-   - `08_vulnerability_curve_analysis.ipynb`
-   - `13_Fragility_curve_analysis.ipynb`
-   - `18_Comparison_of_curves_analysis.ipynb`
+
+    - `00_generator_of_processed_Info_Natural_Event.ipynb`
+    - `03_damage_ratios_&_ranges.ipynb`
+    - `05_vulnerability_matrix.ipynb`
+    - `08_vulnerability_curve_analysis.ipynb`
+    - `13_Fragility_curve_analysis.ipynb`
+    - `18_Comparison_of_curves_analysis.ipynb`
+
 3. **Use the input CSV files already provided** inside the folder:
-   ```
-   00_data_cleaned/
-   ```
+    ```
+    00_data_cleaned/
+    ```
 4. **Execute the notebooks in sequence**, from `00_` to `18_`, ensuring that all cells run successfully.
 
 5. **Processed outputs** will be automatically generated at each stage, including:
-   - Combined and cleaned datasets
-   - Damage ratios
-   - Vulnerability matrices
-   - Vulnerability curves (empirical and logistic regression)
-   - Fragility curves
-   - Comparative vulnerability/fragility plots
+    - Combined and cleaned datasets
+    - Damage ratios
+    - Vulnerability matrices
+    - Vulnerability curves (empirical and logistic regression)
+    - Fragility curves
+    - Comparative vulnerability/fragility plots
 
 6. All output files are saved in the same directory as the notebooks, following the sequential numbering (00–22) generated throughout the workflow.
 
@@ -102,63 +104,73 @@ The following guidance summarizes what each notebook does, what to expect, and h
 
 1. **Generate the processed hazard–exposure dataset**
 
-**Notebook:** `00_generator_of_processed_Info_Natural_Event.ipynb`  
-This notebook loads the cleaned input files found in `00_data_cleaned/`, verifies their structure, and merges hazard data (wind speeds) with exposure and damage attributes.  
-It produces the first standardized dataset used by all subsequent steps.  
-**Outputs:** `01_checking_data.csv`, `02_combined_processed_files.csv`.
+    **Notebook:** `00_generator_of_processed_Info_Natural_Event.ipynb`  
+    This notebook loads the cleaned input files found in `00_data_cleaned/`, verifies their structure, and merges hazard data (wind speeds) with exposure and damage attributes.  
+    It produces the first standardized dataset used by all subsequent steps.
 
+    **Outputs:**  
+    `01_checking_data.csv`,  
+    `02_combined_processed_files.csv`.
 
 2. **Compute damage ratios and define wind-speed ranges**
 
-**Notebook:** `03_damage_ratios_&_ranges.ipynb`  
-This step calculates the *damage ratio* for each record (loss divided by replacement value) and assigns each row to a wind-speed bin.  
-The notebook also produces exploratory visualizations to understand early behavior of the data.  
-**Output:** `04_combined_processed_with_ratios.csv`.
+    **Notebook:** `03_damage_ratios_&_ranges.ipynb`  
+    This step calculates the *damage ratio* for each record (loss divided by replacement value) and assigns each row to a wind-speed bin.  
+    The notebook also produces exploratory visualizations to understand early behavior of the data.
+
+    **Output:**  
+    `04_combined_processed_with_ratios.csv`.
 
 3. **Build the empirical vulnerability matrix**
 
-**Notebook:** `05_vulnerability_matrix.ipynb`  
-This notebook aggregates thousands of records into an empirical vulnerability matrix, where each wind-speed bin is associated with an Expected Damage Ratio (EDR).  
-It also generates a graphical summary of empirical EDR values.  
-**Outputs:** `06_vulnerability_matrix.csv`, `07_vulnerability_matrix.png`.
+    **Notebook:** `05_vulnerability_matrix.ipynb`  
+    This notebook aggregates thousands of records into an empirical vulnerability matrix, where each wind-speed bin is associated with an Expected Damage Ratio (EDR).  
+    It also generates a graphical summary of empirical EDR values.
+
+    **Outputs:**  
+    `06_vulnerability_matrix.csv`,  
+    `07_vulnerability_matrix.png`.
 
 4. **Fit and visualize vulnerability curves**
 
-**Notebook:** `08_vulnerability_curve_analysis.ipynb`  
-This step transforms the empirical matrix into a smooth functional curve.  
-Two representations are produced:
-- **Empirical curve** derived directly from observed data.  
-- **Logistic-regression curve** that provides a smooth vulnerability function across all wind speeds.
+    **Notebook:** `08_vulnerability_curve_analysis.ipynb`  
+    This step transforms the empirical matrix into a smooth functional curve.  
+    Two representations are produced:
 
-Model performance is evaluated using R², RMSE, MAE, and visual comparison.  
-**Outputs:** `09_vulnerability_data.csv`, `10_vulnerability_data.png`,  
-`11_vulnerability_curve_with_logistic_regression.csv`,  
-`12_vulnerability_curve_with_logistic_regression.png`.
+    - **Empirical curve** derived directly from observed data.  
+    - **Logistic-regression curve** that provides a smooth vulnerability function across all wind speeds.
 
+    Model performance is evaluated using R², RMSE, MAE, and visual comparison.
 
+    **Outputs:**  
+    `09_vulnerability_data.csv`,  
+    `10_vulnerability_data.png`,  
+    `11_vulnerability_curve_with_logistic_regression.csv`,  
+    `12_vulnerability_curve_with_logistic_regression.png`.
 
 5. **Generate fragility curves**
 
-**Notebook:** `13_Fragility_curve_analysis.ipynb`  
-This notebook converts vulnerability information into *fragility curves*, which express the probability that damage exceeds a specified threshold.  
-These curves are useful for engineering applications, insurance analysis, and risk modeling.  
-**Outputs:** `14_fragility_data.csv`, `15_fragility_data.png`,  
-`16_fragility_curves_with_logistic_regression.csv`,  
-`17_fragility_curves_with_logistic_regression.png`.
-
+    **Notebook:** `13_Fragility_curve_analysis.ipynb`  
+    This notebook converts vulnerability information into *fragility curves*, which express the probability that damage exceeds a specified threshold.  
+    These curves are useful for engineering applications, insurance analysis, and risk modeling.
 
+    **Outputs:**  
+    `14_fragility_data.csv`,  
+    `15_fragility_data.png`,  
+    `16_fragility_curves_with_logistic_regression.csv`,  
+    `17_fragility_curves_with_logistic_regression.png`.
 
 6. **Compare vulnerability and fragility across classes**
 
-**Notebook:** `18_Comparison_of_curves_analysis.ipynb`  
-The final step allows side-by-side comparisons of vulnerability and fragility curves across construction classes, building types, or datasets.  
-This notebook highlights differences in performance and produces publication-ready figures.  
-**Outputs:**  
-`19_comparison_vulnerability_curves.csv`,  
-`20_comparison_vulnerability_curves.png`,  
-`21_fragility_comparison_Fragility_10.csv`,  
-`22_fragility_comparison_Fragility_10.png`.
+    **Notebook:** `18_Comparison_of_curves_analysis.ipynb`  
+    The final step allows side-by-side comparisons of vulnerability and fragility curves across construction classes, building types, or datasets.  
+    This notebook highlights differences in performance and produces publication-ready figures.
 
+    **Outputs:**  
+    `19_comparison_vulnerability_curves.csv`,  
+    `20_comparison_vulnerability_curves.png`,  
+    `21_fragility_comparison_Fragility_10.csv`,  
+    `22_fragility_comparison_Fragility_10.png`.
 
 
 ### Summary
@@ -200,7 +212,7 @@ This enables evaluation across construction periods, structural types, and datas
 ## Citation
 > Bonfante, N., Pinelli, J.-P., Bakhshandeh, M., & Guennec, T. (2025). *Empirical Hurricane Vulnerability and Fragility Curves*. DesignSafe-CI. DOI: [10.17603/ds2-q60v-z247](https://doi.org/10.17603/ds2-q60v-z247)
 ## Licensing
-**License:** BSD 3-Clause License  
+**License:** BSD 3-Clause License
 
 ## Acknowledgment:
 This research was supported by the **National Science Foundation (NSF)** under **Award No. 1520817**, through the **NHERI DesignSafe Cyberinfrastructure**. The opinions and conclusions expressed are those of the authors and do not necessarily reflect the views of the NSF.
