From 97c91223eaea35bae44dbac1dcff7ba539b22165 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 10:26:37 -0500
Subject: [PATCH 01/10] Update README.md
- Changed steps 4 and 5... maybe better recommend to test before submitting the PR/
- Windows user cannot use the makefile, so easier to recommend the docker commands directly
---
README.md | 22 +++++++++++++++-------
1 file changed, 15 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
index 53cae5da..7393014a 100644
--- a/README.md
+++ b/README.md
@@ -12,11 +12,11 @@ DesignSafe [MkDocs](https://mkdocs.readthedocs.io/) documentation with **customi
2. [Edit](https://docs.github.com/en/repositories/working-with-files/managing-files/editing-files) relevant files that need update.\
([upload images](https://docs.github.com/en/repositories/working-with-files/managing-files/adding-a-file-to-a-repository) as necessary)
4. [Commit](https://docs.github.com/en/pull-requests/committing-changes-to-your-project/creating-and-editing-commits/about-commits) your changes.
-5. [Request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request) a review.\
- (a.k.a. create a "Pull Request")
-6. [Test](#testing) your changes.\
+5. [Test](#testing) your changes.\
(if comfortable using a command prompt)
-
+6. [Request](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request) a review.\
+ (a.k.a. create a "Pull Request")
+
### Resources
* [Markdown syntax (extended)](https://www.markdownguide.org/extended-syntax/) via [MkDocs' Markdown support](https://www.mkdocs.org/user-guide/writing-your-docs/#writing-with-markdown)
@@ -66,13 +66,21 @@ DesignSafe [MkDocs](https://mkdocs.readthedocs.io/) documentation with **customi
0. Have Docker installed.\
We recommend doing so via [Docker-Desktop](https://www.docker.com/products/docker-desktop).
1. Navigate into your clone of this repository.
-2. Start the Docker container to serve the docs.
- ```shell
+2. Start the Docker container to serve the docs.
+
+ Linux or Mac (macOS) user:
+ ```shell
make build
make start
```
-3. Open the website at the URL provided e.g.
+ Windows user:
+ ```shell
+ docker-compose -f ./docker-compose.yml build
+ docker-compose -f docker-compose.yml up
+
+ ```
+4. Open the website at the URL provided e.g.
[http://0.0.0.1:8000/user-guide/](http://0.0.0.1:8000/user-guide/).
From ef9295acf1fd6f465b779124e379a64727a6ef5e Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 10:47:36 -0500
Subject: [PATCH 02/10] Update usecase_JN_viz.md
Change the link on the button. It was directed to silvia's DS jupyter
---
user-guide/docs/usecases/padgett/usecase_JN_viz.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/user-guide/docs/usecases/padgett/usecase_JN_viz.md b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
index d027e43f..a7f0b09c 100644
--- a/user-guide/docs/usecases/padgett/usecase_JN_viz.md
+++ b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
@@ -18,7 +18,7 @@ The following Jupyter notebook is the basis for the use case described in this s
| Scope | Notebook |
| :-------: | :---------: |
-| visualization of
spatially-distributed Data | visualization_risk_resilience.ipynb
[![Open In DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://jupyter.designsafe-ci.org/user/silvia/lab/workspaces/auto-k/tree/NHERI-Published/PRJ-3939v3/visualization_risk_resilience.ipynb)|
+| visualization of
spatially-distributed Data | visualization_risk_resilience.ipynb
[![Open In DesignSafe](https://raw.githubusercontent.com/geoelements/LearnMPM/main/DesignSafe-Badge.svg)](https://jupyter.designsafe-ci.org/hub/user-redirect/lab/tree/NHERI-Published/PRJ-3939v3/visualization_risk_resilience.ipynb)|
From c0cea2eaf8ecb9a68aa6f3743be0c85492c503d5 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:04:25 -0500
Subject: [PATCH 03/10] Update mkdocs.yml
Usecase user-guide/docs/usecases/padgett/usecase_JN_viz.md is not rendering the equations (inline)
---
user-guide/mkdocs.yml | 16 ++++++++++++++++
1 file changed, 16 insertions(+)
diff --git a/user-guide/mkdocs.yml b/user-guide/mkdocs.yml
index 0703ab88..0f4b88e0 100644
--- a/user-guide/mkdocs.yml
+++ b/user-guide/mkdocs.yml
@@ -95,6 +95,22 @@ nav:
- HPC Allocations Policy: tools/advanced/hpcallocations.md
+# ----------------------------------------------------------------
+# Checking how to render Katex.
+# From: https://squidfunk.github.io/mkdocs-material/reference/math/#katex-mkdocsyml
+markdown_extensions:
+ - pymdownx.arithmatex:
+ generic: true
+
+extra_javascript:
+ - javascripts/katex.js
+ - https://unpkg.com/katex@0/dist/katex.min.js
+ - https://unpkg.com/katex@0/dist/contrib/auto-render.min.js
+
+extra_css:
+ - https://unpkg.com/katex@0/dist/katex.min.css
+# ----------------------------------------------------------------
+
# Old navigation for unflattened use cases
# - Data Analytics: usecases/dataanalytics-usecases.md
# - Basic Image Browsing and Mapping: usecases/haan/usecase.md
From 2888e12fb393624cc3e09746dfb542f1a4a32207 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:13:54 -0500
Subject: [PATCH 04/10] Revert "Update mkdocs.yml"
This reverts commit c0cea2eaf8ecb9a68aa6f3743be0c85492c503d5.
---
user-guide/mkdocs.yml | 16 ----------------
1 file changed, 16 deletions(-)
diff --git a/user-guide/mkdocs.yml b/user-guide/mkdocs.yml
index 0f4b88e0..0703ab88 100644
--- a/user-guide/mkdocs.yml
+++ b/user-guide/mkdocs.yml
@@ -95,22 +95,6 @@ nav:
- HPC Allocations Policy: tools/advanced/hpcallocations.md
-# ----------------------------------------------------------------
-# Checking how to render Katex.
-# From: https://squidfunk.github.io/mkdocs-material/reference/math/#katex-mkdocsyml
-markdown_extensions:
- - pymdownx.arithmatex:
- generic: true
-
-extra_javascript:
- - javascripts/katex.js
- - https://unpkg.com/katex@0/dist/katex.min.js
- - https://unpkg.com/katex@0/dist/contrib/auto-render.min.js
-
-extra_css:
- - https://unpkg.com/katex@0/dist/katex.min.css
-# ----------------------------------------------------------------
-
# Old navigation for unflattened use cases
# - Data Analytics: usecases/dataanalytics-usecases.md
# - Basic Image Browsing and Mapping: usecases/haan/usecase.md
From 0d901b2b54ee021b76a8c3c18c18cc0668d7b3c7 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:24:24 -0500
Subject: [PATCH 05/10] Update mkdocs.yml
added existing IN-CORE docs to the nav pane
---
user-guide/mkdocs.yml | 1 +
1 file changed, 1 insertion(+)
diff --git a/user-guide/mkdocs.yml b/user-guide/mkdocs.yml
index 0703ab88..2022960c 100644
--- a/user-guide/mkdocs.yml
+++ b/user-guide/mkdocs.yml
@@ -52,6 +52,7 @@ nav:
- ADCIRC: tools/simulation/adcirc/adcirc.md
- ClawPack: tools/simulation/clawpack.md
- Dakota: tools/simulation/dakota.md
+ - IN-CORE: tools/simulation/in-core.md
- LS-DYNA: tools/simulation/lsdyna.md
- OpenFoam: tools/simulation/openfoam.md
- OpenSees : tools/simulation/opensees/opensees.md
From 3a2f56446e1f2716c984f6201b3f3918ffc7440b Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:32:02 -0500
Subject: [PATCH 06/10] Update usecase_JN_viz.md
Testing new way to inline formulas
---
user-guide/docs/usecases/padgett/usecase_JN_viz.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/user-guide/docs/usecases/padgett/usecase_JN_viz.md b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
index a7f0b09c..b87f0249 100644
--- a/user-guide/docs/usecases/padgett/usecase_JN_viz.md
+++ b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
@@ -103,7 +103,7 @@ In this use case, damage state exceedance probabilities are obtained for each br
Here, interactive Python libraries are used to visualize and inspect fine information on the different components that comprise the map, such as bridge location, basic information, and damage condition (see [Figure 3](#Fig3)). These interactive functionalities are integrated using Python libraries such as Plotly and Folium; these allow the user to pan over the different geospatially distributed systems and inspect the region or assets of interest. Also, these enable the user to construct icon objects that display data of interest (e.g. the ‘construction year’ and the ‘exceeding probability of damage state 3’ in [Figure 3a](#Fig3)) when hovering over the bridge locations. If additional data is also important to display (e.g. hazard intensity, link, or bridge IDs, among others), ‘pop-up’ functionalities can be used to present this information when the user clicks on a particular object (shown in [Figure 3b](#Fig3)).
-As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when $\mathbb{P}(DS≥ds_3 )≥0.15$, yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
+As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\mathbb{P}(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
![Visualization of interactive plots](./img/Figure3_viz.jpg){: id="Fig3" style="display: block;max-width: 85%;height: auto;margin: auto;" }
From 616f6e37e3bd87ee16b575350a6d7d21e17c4316 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:37:53 -0500
Subject: [PATCH 07/10] Update usecase_JN_viz.md
New test for inline equations
---
user-guide/docs/usecases/padgett/usecase_JN_viz.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/user-guide/docs/usecases/padgett/usecase_JN_viz.md b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
index b87f0249..5014e4f2 100644
--- a/user-guide/docs/usecases/padgett/usecase_JN_viz.md
+++ b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
@@ -99,11 +99,11 @@ In general, web tiles (available through Python libraries such as `Contextily`)
#### 2. Interactive exploration of spatially distributed information { #Title2 }
These interactive maps are useful in situations when data visualization is not fully addressed through static maps, so it is necessary to be able to reveal data on elements (points, lines, or polygons) interactively by the user. For example, for inspecting post-event hazard damages, depicting current conditions on situational awareness tools, or displaying information on the infrastructure assets during the restoration processes.
-In this use case, damage state exceedance probabilities are obtained for each bridge (i.e., considered as an outcome of applying fragility models to the hazard scenario). An example of this output is presented in the ‘bridge_result.csv’ file for one hazard scenario. In this file format, damage state exceedance probabilities $\mathbb{P}(DS \geq ds_i)$ are named as "$LS_i$", for $i=1,…,4$; similarly, probabilities of being in a damage state $\mathbb{P}(DS = ds_i)$ are named as "$DS_i$", for $i=1,…,4$. For such cases, there may be interest in visualizing the spatial distribution of damage to infrastructure components.
+In this use case, damage state exceedance probabilities are obtained for each bridge (i.e., considered as an outcome of applying fragility models to the hazard scenario). An example of this output is presented in the ‘bridge_result.csv’ file for one hazard scenario. In this file format, damage state exceedance probabilities $P(DS \geq ds_i)$ are named as "$LS_i$", for $i=1,…,4$; similarly, probabilities of being in a damage state $\mathbb{P}(DS = ds_i)$ are named as "$DS_i$", for $i=1,…,4$. For such cases, there may be interest in visualizing the spatial distribution of damage to infrastructure components.
Here, interactive Python libraries are used to visualize and inspect fine information on the different components that comprise the map, such as bridge location, basic information, and damage condition (see [Figure 3](#Fig3)). These interactive functionalities are integrated using Python libraries such as Plotly and Folium; these allow the user to pan over the different geospatially distributed systems and inspect the region or assets of interest. Also, these enable the user to construct icon objects that display data of interest (e.g. the ‘construction year’ and the ‘exceeding probability of damage state 3’ in [Figure 3a](#Fig3)) when hovering over the bridge locations. If additional data is also important to display (e.g. hazard intensity, link, or bridge IDs, among others), ‘pop-up’ functionalities can be used to present this information when the user clicks on a particular object (shown in [Figure 3b](#Fig3)).
-As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\mathbb{P}(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
+As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\P(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
![Visualization of interactive plots](./img/Figure3_viz.jpg){: id="Fig3" style="display: block;max-width: 85%;height: auto;margin: auto;" }
From 89caea1631b551560c5fced1fc84535879a6b0b3 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:39:54 -0500
Subject: [PATCH 08/10] Revert "Update usecase_JN_viz.md"
This reverts commit 616f6e37e3bd87ee16b575350a6d7d21e17c4316.
---
user-guide/docs/usecases/padgett/usecase_JN_viz.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/user-guide/docs/usecases/padgett/usecase_JN_viz.md b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
index 5014e4f2..b87f0249 100644
--- a/user-guide/docs/usecases/padgett/usecase_JN_viz.md
+++ b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
@@ -99,11 +99,11 @@ In general, web tiles (available through Python libraries such as `Contextily`)
#### 2. Interactive exploration of spatially distributed information { #Title2 }
These interactive maps are useful in situations when data visualization is not fully addressed through static maps, so it is necessary to be able to reveal data on elements (points, lines, or polygons) interactively by the user. For example, for inspecting post-event hazard damages, depicting current conditions on situational awareness tools, or displaying information on the infrastructure assets during the restoration processes.
-In this use case, damage state exceedance probabilities are obtained for each bridge (i.e., considered as an outcome of applying fragility models to the hazard scenario). An example of this output is presented in the ‘bridge_result.csv’ file for one hazard scenario. In this file format, damage state exceedance probabilities $P(DS \geq ds_i)$ are named as "$LS_i$", for $i=1,…,4$; similarly, probabilities of being in a damage state $\mathbb{P}(DS = ds_i)$ are named as "$DS_i$", for $i=1,…,4$. For such cases, there may be interest in visualizing the spatial distribution of damage to infrastructure components.
+In this use case, damage state exceedance probabilities are obtained for each bridge (i.e., considered as an outcome of applying fragility models to the hazard scenario). An example of this output is presented in the ‘bridge_result.csv’ file for one hazard scenario. In this file format, damage state exceedance probabilities $\mathbb{P}(DS \geq ds_i)$ are named as "$LS_i$", for $i=1,…,4$; similarly, probabilities of being in a damage state $\mathbb{P}(DS = ds_i)$ are named as "$DS_i$", for $i=1,…,4$. For such cases, there may be interest in visualizing the spatial distribution of damage to infrastructure components.
Here, interactive Python libraries are used to visualize and inspect fine information on the different components that comprise the map, such as bridge location, basic information, and damage condition (see [Figure 3](#Fig3)). These interactive functionalities are integrated using Python libraries such as Plotly and Folium; these allow the user to pan over the different geospatially distributed systems and inspect the region or assets of interest. Also, these enable the user to construct icon objects that display data of interest (e.g. the ‘construction year’ and the ‘exceeding probability of damage state 3’ in [Figure 3a](#Fig3)) when hovering over the bridge locations. If additional data is also important to display (e.g. hazard intensity, link, or bridge IDs, among others), ‘pop-up’ functionalities can be used to present this information when the user clicks on a particular object (shown in [Figure 3b](#Fig3)).
-As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\P(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
+As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\mathbb{P}(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
![Visualization of interactive plots](./img/Figure3_viz.jpg){: id="Fig3" style="display: block;max-width: 85%;height: auto;margin: auto;" }
From 6119eae1d9252b9e32a1d2e61eb2cd6fcab1071d Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 11:40:15 -0500
Subject: [PATCH 09/10] Revert "Update usecase_JN_viz.md"
This reverts commit 3a2f56446e1f2716c984f6201b3f3918ffc7440b.
---
user-guide/docs/usecases/padgett/usecase_JN_viz.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/user-guide/docs/usecases/padgett/usecase_JN_viz.md b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
index b87f0249..a7f0b09c 100644
--- a/user-guide/docs/usecases/padgett/usecase_JN_viz.md
+++ b/user-guide/docs/usecases/padgett/usecase_JN_viz.md
@@ -103,7 +103,7 @@ In this use case, damage state exceedance probabilities are obtained for each br
Here, interactive Python libraries are used to visualize and inspect fine information on the different components that comprise the map, such as bridge location, basic information, and damage condition (see [Figure 3](#Fig3)). These interactive functionalities are integrated using Python libraries such as Plotly and Folium; these allow the user to pan over the different geospatially distributed systems and inspect the region or assets of interest. Also, these enable the user to construct icon objects that display data of interest (e.g. the ‘construction year’ and the ‘exceeding probability of damage state 3’ in [Figure 3a](#Fig3)) when hovering over the bridge locations. If additional data is also important to display (e.g. hazard intensity, link, or bridge IDs, among others), ‘pop-up’ functionalities can be used to present this information when the user clicks on a particular object (shown in [Figure 3b](#Fig3)).
-As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when \(\mathbb{P}(DS≥ds_3 )≥0.15\), yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
+As shown in this use case, interactive maps can be enhanced by handling the icons, points, and link characteristics such as type, icon figure, color, etc. [Figure 3](#Fig3) presents the bridge condition using a common color coding related to post-hazard tagging. Red tag is used here when $\mathbb{P}(DS≥ds_3 )≥0.15$, yellow tag is used if $0.05≤\mathbb{P}(DS≥ds_3 )<0.15$, and green tag is used if $\mathbb{P}(DS≥ds_3)<0.05$; note that these limits have been arbitrarily selected for display purposes. Moreover, objects such as legends and color bars can be easily included in such interactive maps to add additional layers of information. Given the possibility of presenting the data "online", these are very useful tools for communication with stakeholders, inspection teams, or simply for data analysis during damage simulation or recovery processes.
![Visualization of interactive plots](./img/Figure3_viz.jpg){: id="Fig3" style="display: block;max-width: 85%;height: auto;margin: auto;" }
From b0f78a2c6ceede9fd50802e1ebd34c83b43bae52 Mon Sep 17 00:00:00 2001
From: Raul Rincon <61350784+rinconraul@users.noreply.github.com>
Date: Tue, 11 Jun 2024 18:00:51 -0500
Subject: [PATCH 10/10] Update README.md
Co-authored-by: Wesley B <62723358+wesleyboar@users.noreply.github.com>
---
README.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/README.md b/README.md
index 7393014a..2b1140f8 100644
--- a/README.md
+++ b/README.md
@@ -76,7 +76,7 @@ DesignSafe [MkDocs](https://mkdocs.readthedocs.io/) documentation with **customi
```
Windows user:
```shell
- docker-compose -f ./docker-compose.yml build
+ docker-compose -f docker-compose.yml build
docker-compose -f docker-compose.yml up
```