🥧 not loving the venn - so we move

_freeze/notebooks/model_qualitative/execute-results/html.json

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-    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\nFirst we need to create the \n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\ngenes <- paste(\"gene\",1:1000,sep=\"\")\nset.seed(20231214)\nx <- list(A=sample(genes,300),\n          B=sample(genes,525),\n          C=sample(genes,440),\n          D=sample(genes,350))\n```\n:::\n\n\nCreate spatial plot:\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x) + \n  scale_fill_gradient(low=\"grey90\",\n                      high = \"red\")\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-html/fig-venn-1.png){#fig-venn fig-alt='TODO' width=672}\n:::\n:::\n\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
+    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\nFirst we need to create the df with the relevant 'traits' for each model\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nx <- list(Niche=c(\"species agnostic\", \"structural\", \"synthetic network\"),\n          ADBM=c(\"node-level\", \"mechanistic\"),\n          `Transfer`=c(\"node-level\", \"embedding\", \"metaweb\"),\n          PFIM=c(\"node-level\", \"mechanistic\", \"metaweb\"),\n          Cascade=c(\"species agnostic\", \"structural\", \"synthetic network\"))\n\nvenn <- Venn(x)\ndata <- process_data(venn)\n```\n:::\n\n\nCreate venn diagram:\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x, \n              label = \"none\") +\n  theme_void() +\n  theme(legend.position = 'none')\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-html/fig-venn-1.png){#fig-venn fig-alt='TODO' width=672}\n:::\n:::\n\n\nLooking at it now I don't think this is the wayTM and trying to sort of 'ordinate' modelling space might actually be more meaningful... Specifically thinking here that I need to also actually just read about model comparison (but without the performance aspect)\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
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_freeze/notebooks/model_qualitative/execute-results/ipynb.json

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-    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\nFirst we need to create the \n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\ngenes <- paste(\"gene\",1:1000,sep=\"\")\nset.seed(20231214)\nx <- list(A=sample(genes,300),\n          B=sample(genes,525),\n          C=sample(genes,440),\n          D=sample(genes,350))\n```\n:::\n\n\nCreate spatial plot:\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x) + \n  scale_fill_gradient(low=\"grey90\",\n                      high = \"red\")\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-ipynb/fig-venn-1.png){#fig-venn fig-alt='TODO'}\n:::\n:::\n\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
+    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\nFirst we need to create the df with the relevant 'traits' for each model\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nx <- list(Niche=c(\"species agnostic\", \"structural\", \"synthetic network\"),\n          ADBM=c(\"node-level\", \"mechanistic\"),\n          `Transfer`=c(\"node-level\", \"embedding\", \"metaweb\"),\n          PFIM=c(\"node-level\", \"mechanistic\", \"metaweb\"),\n          Cascade=c(\"species agnostic\", \"structural\", \"synthetic network\"))\n\nvenn <- Venn(x)\ndata <- process_data(venn)\n```\n:::\n\n\nCreate venn diagram:\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x, \n              label = \"none\") +\n  theme_void() +\n  theme(legend.position = 'none')\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-ipynb/fig-venn-1.png){#fig-venn fig-alt='TODO'}\n:::\n:::\n\n\nLooking at it now I don't think this is the wayTM and trying to sort of 'ordinate' modelling space might actually be more meaningful... Specifically thinking here that I need to also actually just read about model comparison (but without the performance aspect)\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
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@@ -1,8 +1,8 @@
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-    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\n\n\nFirst we need to create the \n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\ngenes <- paste(\"gene\",1:1000,sep=\"\")\nset.seed(20231214)\nx <- list(A=sample(genes,300),\n          B=sample(genes,525),\n          C=sample(genes,440),\n          D=sample(genes,350))\n```\n:::\n\n\n\n\nCreate spatial plot:\n\n\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x) + \n  scale_fill_gradient(low=\"grey90\",\n                      high = \"red\")\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-jats/fig-venn-1.png){#fig-venn fig-alt='TODO'}\n:::\n:::\n\n\n\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
+    "markdown": "---\ntitle: Qualitative approach to topology generators\nauthor: Tanya Strydom\n---\n\n\n\n\nHere we will use the standard [REF FOR TIDYVERSE] and @gaoGgVennDiagramIntuitiveEasytoUse2021 to create a venn diagram for the quantitative portion of or generator/model overview process.\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nlibrary(tidyverse)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──\n✔ dplyr     1.1.4     ✔ readr     2.1.5\n✔ forcats   1.0.0     ✔ stringr   1.5.1\n✔ ggplot2   3.4.4     ✔ tibble    3.2.1\n✔ lubridate 1.9.3     ✔ tidyr     1.3.1\n✔ purrr     1.0.2     \n── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──\n✖ dplyr::filter() masks stats::filter()\n✖ dplyr::lag()    masks stats::lag()\nℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors\n```\n\n\n:::\n\n```{.r .cell-code .hidden}\nlibrary(ggVennDiagram)\n```\n\n::: {.cell-output .cell-output-stderr .hidden}\n\n```\n\nAttaching package: 'ggVennDiagram'\n\nThe following object is masked from 'package:tidyr':\n\n    unite\n```\n\n\n:::\n:::\n\n\n\n\n\nFirst we need to create the df with the relevant 'traits' for each model\n\n\n\n\n::: {.cell}\n\n```{.r .cell-code .hidden}\nx <- list(Niche=c(\"species agnostic\", \"structural\", \"synthetic network\"),\n          ADBM=c(\"node-level\", \"mechanistic\"),\n          `Transfer`=c(\"node-level\", \"embedding\", \"metaweb\"),\n          PFIM=c(\"node-level\", \"mechanistic\", \"metaweb\"),\n          Cascade=c(\"species agnostic\", \"structural\", \"synthetic network\"))\n\nvenn <- Venn(x)\ndata <- process_data(venn)\n```\n:::\n\n\n\n\nCreate venn diagram:\n\n\n\n\n::: {#cell-fig-venn .cell}\n\n```{.r .cell-code .hidden}\n#| label: fig-venn\n#| fig-cap: \"Venn diagram for qualitative analysis/overview of the fancy maths things\"\n#| fig-alt: \"TODO\"\nggVennDiagram(x, \n              label = \"none\") +\n  theme_void() +\n  theme(legend.position = 'none')\n```\n\n::: {.cell-output-display}\n![Venn diagram for qualitative analysis/overview of the fancy maths things](model_qualitative_files/figure-jats/fig-venn-1.png){#fig-venn fig-alt='TODO'}\n:::\n:::\n\n\n\n\nLooking at it now I don't think this is the wayTM and trying to sort of 'ordinate' modelling space might actually be more meaningful... Specifically thinking here that I need to also actually just read about model comparison (but without the performance aspect)\n\n## References {.unnumbered}\n\n::: {#refs}\n:::",
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index.qmd

@@ -68,6 +68,7 @@ I know table are awful but in this case they may make more sense. Also I don't t
 | Stochastic        | @rossbergFoodWebsExperts2006                 |                    | | | | | | |
 | Graph Embedding   | @strydomGraphEmbeddingTransfer2023           | latent trait space | @strydomFoodWebReconstruction2022 | Generate metaweb for specific species pool | Probabilistic metaweb | interactions are 'encoded' and can thus be extracted and transferred to similar species | evolutionary backbones/signals |
 | Trait-based       | @caronAddressingEltonianShortfall2022        | mechanistic        | @caronTrophicInteractionModels2023| | metaweb | traits determine interactions | feeding mechanisms are trait correlated |
+| Random       |     |   | | |  | | chaos and anarchy |
 
 : Lets make a table that gives an overview of the different topology generators that we will look at {#tbl-history}
 

notebooks/model_qualitative.qmd

@@ -11,28 +11,34 @@ library(ggVennDiagram)
 ```
 
 
-First we need to create the 
+First we need to create the df with the relevant 'traits' for each model
 
 ```{r}
-genes <- paste("gene",1:1000,sep="")
-set.seed(20231214)
-x <- list(A=sample(genes,300),
-          B=sample(genes,525),
-          C=sample(genes,440),
-          D=sample(genes,350))
+
+x <- list(Niche=c("species agnostic", "structural", "synthetic network"),
+          ADBM=c("node-level", "mechanistic"),
+          `Transfer`=c("node-level", "embedding", "metaweb"),
+          PFIM=c("node-level", "mechanistic", "metaweb"),
+          Cascade=c("species agnostic", "structural", "synthetic network"))
+
+venn <- Venn(x)
+data <- process_data(venn)
 ```
 
-Create spatial plot:
+Create venn diagram:
 
 ```{r}
 #| label: fig-venn
 #| fig-cap: "Venn diagram for qualitative analysis/overview of the fancy maths things"
 #| fig-alt: "TODO"
-ggVennDiagram(x) + 
-  scale_fill_gradient(low="grey90",
-                      high = "red")
+ggVennDiagram(x, 
+              label = "none") +
+  theme_void() +
+  theme(legend.position = 'none')
 ```
 
+Looking at it now I don't think this is the wayTM and trying to sort of 'ordinate' modelling space might actually be more meaningful... Specifically thinking here that I need to also actually just read about model comparison (but without the performance aspect)
+
 ## References {.unnumbered}
 
 ::: {#refs}