Keep only one maxent pipeline.

pipelines/SDM/SDM_maxEnt.json

@@ -366,6 +366,7 @@
       "data": {
         "type": "text[]",
         "value": [
+          "L",
           "LQ",
           "LQHP"
         ]
@@ -383,7 +384,8 @@
         "type": "float[]",
         "value": [
           0.5,
-          1
+          1,
+          2
         ]
       }
     },
@@ -447,6 +449,65 @@
         "type": "text",
         "value": ""
       }
+    },
+    {
+      "id": "121",
+      "type": "userInput",
+      "position": {
+        "x": -99.11140411718372,
+        "y": 29.79005439129935
+      },
+      "dragHandle": ".dragHandle",
+      "data": {
+        "type": "text[]",
+        "value": [
+          "Acer saccharum"
+        ]
+      }
+    },
+    {
+      "id": "122",
+      "type": "output",
+      "position": {
+        "x": 992.1384684097497,
+        "y": 946.4221163262583
+      },
+      "data": {
+        "label": "Output"
+      }
+    },
+    {
+      "id": "123",
+      "type": "output",
+      "position": {
+        "x": 2072.485002668447,
+        "y": 864.8588132070321
+      },
+      "data": {
+        "label": "Output"
+      }
+    },
+    {
+      "id": "124",
+      "type": "output",
+      "position": {
+        "x": 1515.756121480585,
+        "y": 761.8398538185598
+      },
+      "data": {
+        "label": "Output"
+      }
+    },
+    {
+      "id": "125",
+      "type": "output",
+      "position": {
+        "x": 2618.2185181765944,
+        "y": 804.1771194366862
+      },
+      "data": {
+        "label": "Output"
+      }
     }
   ],
   "edges": [
@@ -750,6 +811,41 @@
       "target": "119",
       "targetHandle": "weight_matrix_with_ids",
       "id": "reactflow__edge-120-119weight_matrix_with_ids"
+    },
+    {
+      "source": "121",
+      "sourceHandle": null,
+      "target": "96",
+      "targetHandle": "taxa",
+      "id": "reactflow__edge-121-96taxa"
+    },
+    {
+      "source": "121",
+      "sourceHandle": null,
+      "target": "122",
+      "targetHandle": null,
+      "id": "reactflow__edge-121-122"
+    },
+    {
+      "source": "34",
+      "sourceHandle": "clean_presence",
+      "target": "123",
+      "targetHandle": null,
+      "id": "reactflow__edge-34clean_presence-123"
+    },
+    {
+      "source": "97",
+      "sourceHandle": "rasters_selected",
+      "target": "124",
+      "targetHandle": null,
+      "id": "reactflow__edge-97rasters_selected-124"
+    },
+    {
+      "source": "67",
+      "sourceHandle": "raster",
+      "target": "125",
+      "targetHandle": null,
+      "id": "reactflow__edge-67raster-125"
     }
   ],
   "inputs": {
@@ -761,8 +857,7 @@
         "random",
         "inclusion_buffer",
         "weighted_raster",
-        "unweighted_raster",
-        "thickening"
+        "unweighted_raster"
       ],
       "example": "random"
     },
@@ -808,7 +903,7 @@
         "amphibians",
         "all"
       ],
-      "example": "plants"
+      "example": "reptiles"
     },
     "data>pyLoadObservations>pyLoadObservations.yml@96|data_source": {
       "description": "Source of the data (One of gbif_pc - Planetary computer or gbif_api - GBIF Download API)",
@@ -820,14 +915,6 @@
       ],
       "example": "gbif_api"
     },
-    "data>pyLoadObservations>pyLoadObservations.yml@96|taxa": {
-      "description": "Array of taxa values",
-      "label": "Taxa list",
-      "type": "text[]",
-      "example": [
-        "Acer saccharum"
-      ]
-    },
     "data>pyLoadObservations>pyLoadObservations.yml@96|min_year": {
       "description": "Min year observations wanted",
       "label": "minimum year",
@@ -865,51 +952,92 @@
       "type": "text[]",
       "example": [
         "chelsa-clim|bio1",
-        "chelsa-clim|bio7",
-        "chelsa-clim|bio12",
-        "earthenv_topography|elevation_median",
-        "earthenv_landcover|class_3",
-        "earthenv_landcover|class_12"
+        "chelsa-clim|bio2"
       ]
     },
     "data>loadFromStac.yml@119|spatial_res": {
       "description": "Integer, spatial resolution of the rasters",
       "label": "spatial resolution",
       "type": "float",
-      "example": 5000.0
+      "example": 1000
     },
     "data>loadFromStac.yml@119|mask": {
       "description": "Shapefile, used to mask the output rasters",
       "label": "mask",
-      "type": "application/dbf"
+      "type": "application/dbf",
+      "example": null
+    },
+    "pipeline@121": {
+      "label": "Taxa list",
+      "description": "Array of taxa values",
+      "type": "text[]",
+      "example": [
+        "Acer saccharum"
+      ]
     }
   },
   "outputs": {
     "SDM>rangePredictions.yml@68|range_predictions": {
-      "description": "range (max - min) of a set of predictions",
-      "label": "range predictions",
-      "type": "image/tiff;application=geotiff"
+      "description": "Variability of predictions based on range method",
+      "label": "Variability of predictions",
+      "type": "image/tiff;application=geotiff",
+      "weight": 6
     },
     "SDM>runMaxent.yml@108|sdm_pred": {
-      "description": "model predictions while trained on the whole dataset",
-      "label": "predictions",
+      "description": "Model predictions from Maxent algorithm",
+      "label": "Predictions",
       "type": "image/tiff;application=geotiff",
       "range": [
         0,
         1
-      ]
+      ],
+      "weight": 5
+    },
+    "pipeline@121|defaultOutput": {
+      "label": "Species",
+      "description": "Species for which this model was run.",
+      "example": [
+        "Acer saccharum"
+      ],
+      "type": "text[]"
+    },
+    "filtering>cleanCoordinates.yml@34|clean_presence": {
+      "description": "Occurrences from GBIF after cleaning",
+      "label": "Presences",
+      "type": "text/tab-separated-values",
+      "weight": 2
+    },
+    "SDM>removeCollinearity.yml@97|rasters_selected": {
+      "description": "Environmental layers used as predictors in species distribution modeling",
+      "label": "Environmental predictors",
+      "type": "image/tiff;application=geotiff[]",
+      "weight": 3
+    },
+    "data>heatmapFromSTAC.yml@67|raster": {
+      "description": "Heatmap of GBIF occurences for plants used for bias correction",
+      "label": "Density of GBIF occurrences",
+      "type": "image/tiff;application=geotiff",
+      "weight": 4
     }
   },
   "metadata": {
-    "name": "Maxent SDM pipeline",
-    "description": "A pipeline to produce species distribution models using Maxent",
+    "name": "Species distribution modeling with Maxent",
+    "description": "This pipeline generates predictions for a species distribution model using the Maxent algorithm. Several background methods are possible, including randomly  distributed pseudo-absences throughout the region, background thickening  (Vollering et al. 2019, [https://doi.org/10.1111/ecog.04503] and  target-group background selection (Phillips et al. 2009, [https://doi.org/10.1890/07-2153.1]).  Bias correction is achieved using the target-group background selection method.  A variance map to represent the prediction  uncertainty is generated through bootstraping.",
     "author": [
       {
         "name": "Sarah Valentin",
         "identifier": "https://orcid.org/0000-0002-9028-681X"
+      },
+      {
+        "name": "Guillaume Larocque",
+        "identifier": "https://orcid.org/0000-0002-5967-9156"
+      },
+      {
+        "name": "François Rousseu",
+        "identifier": "https://orcid.org/0000-0002-2400-2479"
       }
     ],
-    "license": null,
-    "external_link": null
+    "license": "MIT",
+    "external_link": "https://github.com/GEO-BON/biab-2.0/blob/main/scripts/SDM/runMaxent.R"
   }
 }