From 7ade9a17521c264e318126e744fd2245ed9a8d2c Mon Sep 17 00:00:00 2001 From: visr Date: Tue, 4 Jun 2024 19:13:09 +0000 Subject: [PATCH] deploy: 632237ccb7a1c08038b750d3b94866323fa24d90 --- core/allocation.html | 36 +++++++++--------- core/equations.html | 2 +- core/validation.html | 4 +- .../figure-html/cell-71-output-1.png | Bin 46502 -> 46488 bytes python/test-models.html | 2 +- search.json | 2 +- 6 files changed, 23 insertions(+), 23 deletions(-) diff --git a/core/allocation.html b/core/allocation.html index 672589e24..4cbaf868b 100644 --- a/core/allocation.html +++ b/core/allocation.html @@ -666,7 +666,7 @@

4.4 Example

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

-
+
Code
using Ribasim
@@ -689,41 +689,41 @@ 

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

-
Min F[(Basin #5, UserDemand #6)]² + F[(Basin #12, UserDemand #13)]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
+ F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0
+ F[(FractionalFlow #8, Terminal #10)] ≥ 0
  F[(UserDemand #6, Basin #5)] ≥ 0
+ F[(FlowBoundary #1, Basin #2)] ≥ 0
  F[(FractionalFlow #9, Basin #12)] ≥ 0
  F[(Basin #2, LinearResistance #4)] ≥ 0
  F[(LinearResistance #4, Basin #2)] ≥ 0
- F[(Basin #5, UserDemand #6)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
- F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0
- F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0
  F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
- F[(FractionalFlow #8, Terminal #10)] ≥ 0
- F[(Basin #12, UserDemand #13)] ≥ 0
  F[(LinearResistance #4, Basin #5)] ≥ 0
  F[(Basin #5, LinearResistance #4)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
- F[(FlowBoundary #1, Basin #2)] ≥ 0
  F[(UserDemand #13, Terminal #10)] ≥ 0
+ F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(Basin #12, UserDemand #13)] ≥ 0
+ F[(Basin #5, UserDemand #6)] ≥ 0
  F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0
  F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 0
  source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
- source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 0
  source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
  source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
- fractional_flow[(TabulatedRatingCurve #7, FractionalFlow #8)] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - 0.6 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0
+ source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 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)] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - 0.4 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0
  flow_buffer_outflow[TabulatedRatingCurve #7] : F_flow_buffer_out[TabulatedRatingCurve #7] ≤ 0
- flow_conservation[FractionalFlow #9] : -F[(FractionalFlow #9, Basin #12)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] = 0
- flow_conservation[Terminal #10] : F[(FractionalFlow #8, Terminal #10)] + F[(UserDemand #13, Terminal #10)] = 0
- flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(TabulatedRatingCurve #7, FractionalFlow #9)] + F[(Basin #5, TabulatedRatingCurve #7)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0
- flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] = 0
  flow_conservation[LinearResistance #4] : F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] - F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] = 0
+ flow_conservation[FractionalFlow #8] : -F[(FractionalFlow #8, Terminal #10)] + F[(TabulatedRatingCurve #7, FractionalFlow #8)] = 0
+ flow_conservation[FractionalFlow #9] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(FractionalFlow #9, Basin #12)] = 0
+ flow_conservation[Terminal #10] : F[(FractionalFlow #8, Terminal #10)] + F[(UserDemand #13, Terminal #10)] = 0
+ flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, UserDemand #6)] = 0
+ flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] - F[(Basin #2, UserDemand #3)] + F[(UserDemand #3, Basin #2)] = 0
  flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0
- flow_conservation[Basin #2] : -F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] + F[(FlowBoundary #1, Basin #2)] = 0
- flow_conservation[FractionalFlow #8] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(FractionalFlow #8, Terminal #10)] = 0
+ flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #9)] + F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0
 
diff --git a/core/equations.html b/core/equations.html index 960b69a1d..7f6f36aaf 100644 --- a/core/equations.html +++ b/core/equations.html @@ -528,7 +528,7 @@

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/core/validation.html b/core/validation.html
index dfdf15ac6..d1dc41e89 100644
--- a/core/validation.html
+++ b/core/validation.html
@@ -363,7 +363,7 @@ 

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
@@ -713,7 +713,7 @@ 

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/python/examples_files/figure-html/cell-71-output-1.png b/python/examples_files/figure-html/cell-71-output-1.png
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z9|ma_iDG7w!O7a96`@$3@>zwx(7GAFd7yGr~U;!!Cwg&IA;e6)@osE!1gBE=>1hYjsM(ptr_H?XRzmDIb94q z$O5>BakU+UZx68#t&?}vN@9S{VrI$Vs7UW78Xv|o?RGDTs~RzOL8*d>ysg5^;<08> zG~-6^gfZ$=U!6facC{Hi1YzbJQOih!`HLh8<1kH01AYu!atDZtO+Z3O{o1m! zqjED3nN&-^M8sYHEkEXIJ{3ha^UQVKcg$Z%V7 z5{W7d57Bzaw71~di29KApG-Sq}Y;@y*#{IPTduATXm1<>7D3;-&*`Uc7=vyeW zpf<{z>P?Pt*h^LQVj8X(KTest 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 500ed5d66..6e6fd1025 100644
--- a/search.json
+++ b/search.json
@@ -1675,7 +1675,7 @@
     "href": "core/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 #5, UserDemand #6)]² + F[(Basin #12, UserDemand #13)]² + F[(Basin #2, UserDemand #3)]²\nSubject to\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(FractionalFlow #9, Basin #12)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(FractionalFlow #8, Terminal #10)] ≥ 0\n F[(Basin #12, UserDemand #13)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(UserDemand #13, Terminal #10)] ≥ 0\n F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0\n F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 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)] : 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 flow_conservation[FractionalFlow #9] : -F[(FractionalFlow #9, Basin #12)] + F[(TabulatedRatingCurve #7, FractionalFlow #9)] = 0\n flow_conservation[Terminal #10] : F[(FractionalFlow #8, Terminal #10)] + F[(UserDemand #13, Terminal #10)] = 0\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(TabulatedRatingCurve #7, FractionalFlow #9)] + F[(Basin #5, TabulatedRatingCurve #7)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0\n flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] = 0\n flow_conservation[LinearResistance #4] : F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] - F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] = 0\n flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0\n flow_conservation[Basin #2] : -F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] + F[(FlowBoundary #1, Basin #2)] = 0\n flow_conservation[FractionalFlow #8] : F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F[(FractionalFlow #8, Terminal #10)] = 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 F[(TabulatedRatingCurve #7, FractionalFlow #9)] ≥ 0\n F[(FractionalFlow #8, Terminal #10)] ≥ 0\n F[(UserDemand #6, Basin #5)] ≥ 0\n F[(FlowBoundary #1, Basin #2)] ≥ 0\n F[(FractionalFlow #9, Basin #12)] ≥ 0\n F[(Basin #2, LinearResistance #4)] ≥ 0\n F[(LinearResistance #4, Basin #2)] ≥ 0\n F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0\n F[(LinearResistance #4, Basin #5)] ≥ 0\n F[(Basin #5, LinearResistance #4)] ≥ 0\n F[(UserDemand #13, Terminal #10)] ≥ 0\n F[(TabulatedRatingCurve #7, FractionalFlow #8)] ≥ 0\n F[(Basin #2, UserDemand #3)] ≥ 0\n F[(UserDemand #3, Basin #2)] ≥ 0\n F[(Basin #12, UserDemand #13)] ≥ 0\n F[(Basin #5, UserDemand #6)] ≥ 0\n F_flow_buffer_in[TabulatedRatingCurve #7] ≥ 0\n F_flow_buffer_out[TabulatedRatingCurve #7] ≥ 0\n source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800\n source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0\n source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0\n source_user[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 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)] : 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 flow_conservation[LinearResistance #4] : F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] - F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] = 0\n flow_conservation[FractionalFlow #8] : -F[(FractionalFlow #8, Terminal #10)] + F[(TabulatedRatingCurve #7, FractionalFlow #8)] = 0\n flow_conservation[FractionalFlow #9] : F[(TabulatedRatingCurve #7, FractionalFlow #9)] - F[(FractionalFlow #9, Basin #12)] = 0\n flow_conservation[Terminal #10] : F[(FractionalFlow #8, Terminal #10)] + F[(UserDemand #13, Terminal #10)] = 0\n flow_conservation[Basin #5] : F[(UserDemand #6, Basin #5)] - F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] - F[(Basin #5, UserDemand #6)] = 0\n flow_conservation[Basin #2] : F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] - F[(Basin #2, UserDemand #3)] + F[(UserDemand #3, Basin #2)] = 0\n flow_conservation[Basin #12] : F[(FractionalFlow #9, Basin #12)] - F[(Basin #12, UserDemand #13)] = 0\n flow_conservation[TabulatedRatingCurve #7] : -F[(TabulatedRatingCurve #7, FractionalFlow #9)] + F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, FractionalFlow #8)] - F_flow_buffer_in[TabulatedRatingCurve #7] + F_flow_buffer_out[TabulatedRatingCurve #7] = 0",
     "crumbs": [
       "Julia core",
       "Allocation"