technically speaking, solving the models is analysis

src/analysis/solver.jl

@@ -0,0 +1,42 @@
+
+# Copyright (c) 2021-2024, University of Luxembourg
+# Copyright (c) 2021-2024, Heinrich-Heine University Duesseldorf
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+$(TYPEDSIGNATURES)
+
+Make an JuMP model out of `constraints` using [`optimization_model`](@ref)
+(most arguments are forwarded there), then apply the `settings`, optimize
+the model, and return either `nothing` if the optimization failed, or `output`
+substituted with the solved values (`output` defaults to `constraints`.
+
+For a "nice" version for simpler finding of metabolic model optima, use
+[`flux_balance`](@ref).
+"""
+function optimized_constraints(
+    constraints::C.ConstraintTree;
+    settings = [],
+    output::C.ConstraintTreeElem = constraints,
+    kwargs...,
+)
+    om = optimization_model(constraints; kwargs...)
+    for m in settings
+        m(om)
+    end
+
+    optimized_model(om; output)
+end
+
+export optimized_constraints