Ecoregionalization workflow

Seguineau Pauline

Last updated Sep 16, 2024

Launch in Tutorial Mode question
License: MIT
Tests: ✅ Results: Not yet automated

flowchart TD
  0["ℹ️ Input Dataset\noccurrence.txt"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\npivot_wider_jupytool_notebook.ipynb"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nceamarc_env.tsv"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["Advanced Cut"];
  0 -->|output| 3;
  4["Column Regex Find And Replace"];
  3 -->|output| 4;
  5["Column Regex Find And Replace"];
  4 -->|out_file1| 5;
  6["Column Regex Find And Replace"];
  5 -->|out_file1| 6;
  7["Column Regex Find And Replace"];
  6 -->|out_file1| 7;
  8["Filter Tabular"];
  7 -->|out_file1| 8;
  9["Column Regex Find And Replace"];
  8 -->|output| 9;
  10["Column Regex Find And Replace"];
  9 -->|out_file1| 10;
  11["Column Regex Find And Replace"];
  10 -->|out_file1| 11;
  12["Column Regex Find And Replace"];
  11 -->|out_file1| 12;
  13["Column Regex Find And Replace"];
  12 -->|out_file1| 13;
  14["Merge Columns"];
  13 -->|out_file1| 14;
  15["Advanced Cut"];
  14 -->|out_file1| 15;
  16["Interactive JupyTool and notebook"];
  1 -->|output| 16;
  15 -->|output| 16;
  e7343e27-e3ba-4037-849d-fa5e3624c62e["Output\nocc_out"];
  16 --> e7343e27-e3ba-4037-849d-fa5e3624c62e;
  style e7343e27-e3ba-4037-849d-fa5e3624c62e stroke:#2c3143,stroke-width:4px;
  17["GeoNearestNeighbor"];
  2 -->|output| 17;
  16 -->|output_dataset| 17;
  afa22961-a75f-434b-8308-e277cca40f57["Output\nocc_env_out"];
  17 --> afa22961-a75f-434b-8308-e277cca40f57;
  style afa22961-a75f-434b-8308-e277cca40f57 stroke:#2c3143,stroke-width:4px;
  0026a7d8-a1ca-4c9a-98ce-8afec1442ffd["Output\ninfo_out"];
  17 --> 0026a7d8-a1ca-4c9a-98ce-8afec1442ffd;
  style 0026a7d8-a1ca-4c9a-98ce-8afec1442ffd stroke:#2c3143,stroke-width:4px;
  18["BRT tool prediction"];
  2 -->|output| 18;
  17 -->|occ_env_out| 18;
  d95d783c-67cc-4a36-813d-e6e7235a511f["Output\ncoll_pred"];
  18 --> d95d783c-67cc-4a36-813d-e6e7235a511f;
  style d95d783c-67cc-4a36-813d-e6e7235a511f stroke:#2c3143,stroke-width:4px;
  d974e78b-8a8b-4f30-8992-e97a99f8398f["Output\ncoll_val"];
  18 --> d974e78b-8a8b-4f30-8992-e97a99f8398f;
  style d974e78b-8a8b-4f30-8992-e97a99f8398f stroke:#2c3143,stroke-width:4px;
  37ca81f3-5b66-4899-bc62-f7883fb28c0e["Output\ncoll_distri"];
  18 --> 37ca81f3-5b66-4899-bc62-f7883fb28c0e;
  style 37ca81f3-5b66-4899-bc62-f7883fb28c0e stroke:#2c3143,stroke-width:4px;
  dd1e3e32-92d1-4a9e-8e6e-bdf8bab6599a["Output\ncoll_plots"];
  18 --> dd1e3e32-92d1-4a9e-8e6e-bdf8bab6599a;
  style dd1e3e32-92d1-4a9e-8e6e-bdf8bab6599a stroke:#2c3143,stroke-width:4px;
  19["TaxaSeeker"];
  2 -->|output| 19;
  17 -->|occ_env_out| 19;
  18 -->|outputpred| 19;
  0dd0aabc-da76-4848-b14e-342861cc9d84["Output\nsummary"];
  19 --> 0dd0aabc-da76-4848-b14e-342861cc9d84;
  style 0dd0aabc-da76-4848-b14e-342861cc9d84 stroke:#2c3143,stroke-width:4px;
  d6289bd0-ca71-422a-8f2e-9fe5054535f0["Output\ntaxa"];
  19 --> d6289bd0-ca71-422a-8f2e-9fe5054535f0;
  style d6289bd0-ca71-422a-8f2e-9fe5054535f0 stroke:#2c3143,stroke-width:4px;
  4c230ca6-fe05-40b0-a3fc-6f3e02fc54c3["Output\ntaxa_clean"];
  19 --> 4c230ca6-fe05-40b0-a3fc-6f3e02fc54c3;
  style 4c230ca6-fe05-40b0-a3fc-6f3e02fc54c3 stroke:#2c3143,stroke-width:4px;
  20["ClusterEstimate"];
  2 -->|output| 20;
  18 -->|outputpred| 20;
  19 -->|output2| 20;
  0220eba1-ea64-4f16-8de8-b67ccee44b2e["Output\nSIH_index"];
  20 --> 0220eba1-ea64-4f16-8de8-b67ccee44b2e;
  style 0220eba1-ea64-4f16-8de8-b67ccee44b2e stroke:#2c3143,stroke-width:4px;
  473fb144-5f89-40cc-be26-af84972bb1b6["Output\ndata_to_clus"];
  20 --> 473fb144-5f89-40cc-be26-af84972bb1b6;
  style 473fb144-5f89-40cc-be26-af84972bb1b6 stroke:#2c3143,stroke-width:4px;
  05282afc-781c-4044-97d5-c03584d74134["Output\ndatabio_table"];
  20 --> 05282afc-781c-4044-97d5-c03584d74134;
  style 05282afc-781c-4044-97d5-c03584d74134 stroke:#2c3143,stroke-width:4px;
  21["ClaraClust"];
  2 -->|output| 21;
  20 -->|output3| 21;
  20 -->|output2| 21;
  c2e059e8-c8b6-42e2-8b15-be9e05b88c4f["Output\nSIH_plot"];
  21 --> c2e059e8-c8b6-42e2-8b15-be9e05b88c4f;
  style c2e059e8-c8b6-42e2-8b15-be9e05b88c4f stroke:#2c3143,stroke-width:4px;
  95d996b2-b4f6-4be5-b154-b7bb64b08c11["Output\ncluster_points"];
  21 --> 95d996b2-b4f6-4be5-b154-b7bb64b08c11;
  style 95d996b2-b4f6-4be5-b154-b7bb64b08c11 stroke:#2c3143,stroke-width:4px;
  b91d7e98-a6d7-4fff-8d40-8b77b846c3d2["Output\ncluster_info"];
  21 --> b91d7e98-a6d7-4fff-8d40-8b77b846c3d2;
  style b91d7e98-a6d7-4fff-8d40-8b77b846c3d2 stroke:#2c3143,stroke-width:4px;
  22["EcoMap"];
  21 -->|output2| 22;
  9e315fc3-fa52-4e3e-98f5-335f811ecf06["Output\neco_map"];
  22 --> 9e315fc3-fa52-4e3e-98f5-335f811ecf06;
  style 9e315fc3-fa52-4e3e-98f5-335f811ecf06 stroke:#2c3143,stroke-width:4px;