Minor fixes

README.md

@@ -24,14 +24,14 @@
   <p align="center">
     This repository contains an open source library that provides modelling of multi-degree-of-freedom systems and assessment via nonlinear time-history analyses for regional vulnerability and risk calculations. The vulnerability toolkit is developed by the Global Earthquake Model (GEM) Foundation and its collaborators.
     <br />
-    <a href="https://github.com/GEMScienceTools/vulnerability-toolkit/docs"><strong>Explore the docs »</strong></a>
+    <a href="https://gemsciencetools.github.io/oq-vmtk/"><strong>Explore the docs »</strong></a>
     <br />
     <br />
-    <a href="https://github.com/GEMScienceTools/vulnerability-toolkit/demos">View Demos</a>
+    <a href="https://github.com/GEMScienceTools/oq-vmtk/tree/main/demos">View Demos</a>
     ·
-    <a href="https://github.com/GEMScienceTools/vulnerability-toolkit/issues/new?labels=bug&template=bug-report---.md">Report Bug</a>
+    <a href="https://github.com/GEMScienceTools/oq-vmtk/issues/new?labels=bug&template=bug-report---.md">Report Bug</a>
     ·
-    <a href="https://github.com/GEMScienceTools/vulnerability-toolkit/issues/new?labels=enhancement&template=feature-request---.md">Request Feature</a>
+    <a href="https://github.com/GEMScienceTools/oq-vmtk/issues/new?labels=enhancement&template=feature-request---.md">Request Feature</a>
   </p>
 </div>
 
@@ -93,6 +93,9 @@ It is highly recommended to use a **virtual environment** to install this tool.
    source .venv/Scripts/activate  # On Linux
    ```
 
+<img src="imgs/virtual-env.gif" alt="Logo" >
+
+
 ### 3. Install Dependencies
    Install the required packages listed in `requirements.txt`.
 

demos/README.md

@@ -5,13 +5,10 @@ This folder contains an ensemble of example python notebooks demonstrating vario
 ## Example 1: Ground-Motion Record Processing
 This example provides a workflow for processing ground-motion records, such as spectral analysis and identification if intensity measure values for distinct intensity measure types (e.g., PGA, Arias Intensity, etc.).
 
-## Example 2: Nonlinear Time-History Analysis on an MDOF System using Cloud Analysis
-This example performs nonlinear time-history analysis on a multi-degree-of-freedom (MDOF) structural system calibrated using SDOF global capacity and using cloud analysis to assess seismic performance.
+## Example 2: End-to-End Vulnerability Analysis of an MDOF System using Cloud Analysis
+This example performs nonlinear time-history analysis on a multi-degree-of-freedom (MDOF) structural system calibrated using SDOF global capacity and using cloud analysis to assess seismic performance. The example additionally demonstrates postprocessing of cloud analysis results, including fragility curve estimation and vulnerability assessment visualization.
 
-## Example 3: Postprocessing and Visualizing Cloud Analysis Results for Fragility and Vulnerability Analysis
-This example demonstrates postprocessing of cloud analysis results, including fragility curve estimation and vulnerability assessment visualization.
-
-## Example 4: Generating and Visualizing Storey Loss Functions
+## Example 3: Generating and Visualizing Storey Loss Functions
 This example focuses on computing and visualizing storey loss functions, providing insights into seismic damage assessment and economic loss estimation.
 
 Each example includes relevant scripts, input data, and instructions to guide users through the analysis. Feel free to explore and modify them to suit your specific needs! 

openquake/vmtk/slf_generator.py

@@ -579,7 +579,7 @@ def _validate_component_data_schema(self):
         # Validate base fields
         id_set = set()
         for row in component_data:
-            model = component_data_model.parse_obj(row)
+            model = component_data_model.model_validate(row)
             if model.Component_ID is not None and model.Component_ID in id_set:
                 raise ValueError(f'Duplicate ITEM: {model.Component_ID}')
             id_set.add(model.Component_ID)
@@ -613,7 +613,7 @@ def _validate_correlation_tree_schema(self,
         # Validate base fields
         id_set = set()
         for row in corr_dict:
-            model = correlation_tree_model.parse_obj(row)
+            model = correlation_tree_model.model_validate(row)
             if model.ITEM in id_set:
                 raise ValueError(f'Duplicate ITEM: {model.ITEM}')
             id_set.add(model.ITEM)