diff --git a/background/allocation.html b/background/allocation.html index 066a943c4..86d837ae5 100644 --- a/background/allocation.html +++ b/background/allocation.html @@ -601,7 +601,7 @@

4.4 Example

The following is an example of an optimization problem for the example shown here:

-
+
Code
using Ribasim
@@ -624,39 +624,39 @@ 

println(p.allocation.allocation_models[1].problem)

-
Min F[(Basin #12, UserDemand #13)]² + F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²
+
Min F[(Basin #2, UserDemand #3)]² + F[(Basin #12, UserDemand #13)]² + F[(Basin #5, UserDemand #6)]²
 Subject to
- flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] + F[(Basin #5, TabulatedRatingCurve #7)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0
- flow_conservation[FractionalFlow #9] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(FractionalFlow #9, Basin #12)] = 0
+ flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] = 0
  flow_conservation[FractionalFlow #8] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(FractionalFlow #8, Terminal #10)] = 0
+ flow_conservation[Basin #2] : -F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] + F[(UserDemand #3, Basin #2)] = 0
+ flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0
+ flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0
  flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0
+ flow_conservation[FractionalFlow #9] : -F[(FractionalFlow #9, Basin #12)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] = 0
  flow_conservation[Terminal #10] : F[(UserDemand #13, Terminal #10)] + F[(FractionalFlow #8, Terminal #10)] = 0
- flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0
- flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] = 0
- flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] = 0
  source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
- source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
  source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 0
  source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
- fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #8)] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - 0.6 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0
- fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #9)] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - 0.4 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0
+ source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
+ fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #8)] : -0.6 F[(Basin #5, TabulatedRatingCurve #7)] + F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≤ 0
+ fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #9)] : -0.4 F[(Basin #5, TabulatedRatingCurve #7)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≤ 0
  flow_buffer_outflow[TabulatedRatingCurve #7] : F_flow_buffer_out[TabulatedRatingCurve #7] ≤ 0
  F[(LinearResistance #4, Basin #5)] ≥ 0
  F[(Basin #5, LinearResistance #4)] ≥ 0
- F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0
- F[(UserDemand #13, Terminal #10)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
- F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
  F[(UserDemand #6, Basin #5)] ≥ 0
- F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
  F[(FractionalFlow #9, Basin #12)] ≥ 0
  F[(Basin #12, UserDemand #13)] ≥ 0
- F[(FractionalFlow #8, Terminal #10)] ≥ 0
+ F[(UserDemand #13, Terminal #10)] ≥ 0
  F[(Basin #5, UserDemand #6)] ≥ 0
- F[(FlowBoundary #1, Basin #2)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
+ F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
+ F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0
+ F[(FractionalFlow #8, Terminal #10)] ≥ 0
  F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0
  F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 0
 
diff --git a/background/equations.html b/background/equations.html index 6093df73c..b09e2ef2e 100644 --- a/background/equations.html +++ b/background/equations.html @@ -463,7 +463,7 @@

Here \(p > 0\) is the threshold value which determines the interval \([0,p]\) of the smooth transition between \(0\) and \(1\), see the plot below.

-
+
Code
import numpy as np
diff --git a/background/validation.html b/background/validation.html
index 8d75bddd3..9ebdb647c 100644
--- a/background/validation.html
+++ b/background/validation.html
@@ -298,7 +298,7 @@ 

Validation

1 Connectivity

In the table below, each column shows which node types are allowed to be downstream (or ‘down-control’) of the node type at the top of the column.

-
+
Code
using Ribasim
@@ -648,7 +648,7 @@ 

1 Connectivity

2 Neighbor amounts

The table below shows for each node type between which bounds the amount of in- and outneighbors must be, for both flow and control edges.

-
+
Code
flow_in_min = Vector{String}()
diff --git a/guides/examples_files/figure-html/cell-71-output-1.png b/guides/examples_files/figure-html/cell-71-output-1.png
index 2e273a56f..42dfff946 100644
Binary files a/guides/examples_files/figure-html/cell-71-output-1.png and b/guides/examples_files/figure-html/cell-71-output-1.png differ
diff --git a/reference/test-models.html b/reference/test-models.html
index 3547e4be2..6dc0691ed 100644
--- a/reference/test-models.html
+++ b/reference/test-models.html
@@ -325,7 +325,7 @@ 

Test models

Ribasim developers use the following models in their testbench and in order to test new features.

-
+
Code
import ribasim_testmodels
diff --git a/search.json b/search.json
index 02eb3d682..8d78b49e3 100644
--- a/search.json
+++ b/search.json
@@ -304,7 +304,7 @@
     "href": "background/allocation.html#example",
     "title": "Allocation",
     "section": "4.4 Example",
-    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, NodeID(:FlowBoundary, 1), NodeID(:Basin, 2), 1.0)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #12, UserDemand #13)]² + F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²\nSubject to\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] + F[(Basin #5, TabulatedRatingCurve #7)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0\n flow_conservation[FractionalFlow #9] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(FractionalFlow #9, Basin #12)] = 0\n flow_conservation[FractionalFlow #8] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(FractionalFlow #8, Terminal #10)] = 0\n flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0\n flow_conservation[Terminal #10] : F[(UserDemand #13, Terminal #10)] + F[(FractionalFlow #8, Terminal #10)] = 0\n flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0\n flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] = 0\n flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] - F[(Basin #5, UserDemand #6)] = 0\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 0\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #8)] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - 0.6 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0\n fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #9)] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - 0.4 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0\n flow_buffer_outflow[TabulatedRatingCurve #7] : F_flow_buffer_out[TabulatedRatingCurve #7] ≤ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0\n F[(UserDemand #13, Terminal #10)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(FractionalFlow #9, Basin #12)] ≥ 0\n F[(Basin #12, UserDemand #13)] ≥ 0\n F[(FractionalFlow #8, Terminal #10)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0\n F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 0",
+    "text": "4.4 Example\nThe following is an example of an optimization problem for the example shown here:\n\n\nCode\nusing Ribasim\nusing Ribasim: NodeID\nusing SQLite\nusing ComponentArrays: ComponentVector\n\ntoml_path = normpath(@__DIR__, \"../../generated_testmodels/allocation_example/ribasim.toml\")\np = Ribasim.Model(toml_path).integrator.p\nu = ComponentVector(; storage = zeros(length(p.basin.node_id)))\n\nallocation_model = p.allocation.allocation_models[1]\nt = 0.0\npriority_idx = 1\n\nRibasim.set_flow!(p.graph, NodeID(:FlowBoundary, 1), NodeID(:Basin, 2), 1.0)\nRibasim.set_objective_priority!(allocation_model, p, u, t, priority_idx)\nRibasim.set_initial_values!(allocation_model, p, u, t)\n\nprintln(p.allocation.allocation_models[1].problem)\n\n\nMin F[(Basin #2, UserDemand #3)]² + F[(Basin #12, UserDemand #13)]² + F[(Basin #5, UserDemand #6)]²\nSubject to\n flow_conservation[Basin #5] : F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] = 0\n flow_conservation[FractionalFlow #8] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(FractionalFlow #8, Terminal #10)] = 0\n flow_conservation[Basin #2] : -F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] + F[(UserDemand #3, Basin #2)] = 0\n flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0\n flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0\n flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0\n flow_conservation[FractionalFlow #9] : -F[(FractionalFlow #9, Basin #12)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] = 0\n flow_conservation[Terminal #10] : F[(UserDemand #13, Terminal #10)] + F[(FractionalFlow #8, Terminal #10)] = 0\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 0\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #8)] : -0.6 F[(Basin #5, TabulatedRatingCurve #7)] + F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≤ 0\n fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #9)] : -0.4 F[(Basin #5, TabulatedRatingCurve #7)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≤ 0\n flow_buffer_outflow[TabulatedRatingCurve #7] : F_flow_buffer_out[TabulatedRatingCurve #7] ≤ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(FractionalFlow #9, Basin #12)] ≥ 0\n F[(Basin #12, UserDemand #13)] ≥ 0\n F[(UserDemand #13, Terminal #10)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0\n F[(FractionalFlow #8, Terminal #10)] ≥ 0\n F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0\n F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 0",
     "crumbs": [
       "Background",
       "Implementation",