Update Project.toml

sebapersson · Apr 28, 2023 · a857de5 · a857de5 · RafaelArutjunjan · Apr 28, 2023
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Showing 3 changed files with 10 additions and 10 deletions.
diff --git a/Project.toml b/Project.toml
@@ -34,13 +34,13 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 [compat]
 CSV = "0.10"
 ChainRulesCore = "1"
-DataFrames = "0.2 - 1.5"
+DataFrames = "1.0, 1.1, 1.2, 1.3, 1.4, 1.5"
 DiffEqCallbacks = "2"
 Distributions = "0.21 - 0.25"
 FiniteDifferences = "0.11, 0.12"
 ForwardDiff = "0.10"
 ModelingToolkit = "6 - 8"
-NonlinearSolve = "0.6 - 1.6"
+NonlinearSolve = "1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6"
 OrdinaryDiffEq = "6"
 PreallocationTools = "0.4"
 PyCall = "1"

diff --git a/src/Create_PEtab_ODEProblem.jl b/src/Create_PEtab_ODEProblem.jl
@@ -134,7 +134,7 @@ function setupPEtabODEProblem(petabModel::PEtabModel,
     elseif gradientMethod === :Adjoint
         @assert (typeof(sensealg) <: SciMLSensitivity.AbstractAdjointSensitivityAlgorithm) "For adjoint sensitivity analysis allowed sensealg are InterpolatingAdjoint() or QuadratureAdjoint()"
     elseif gradientMethod === :Zygote
-        @assert (typeof(sensealg) <: SciMLSensitivity.AbstractSensitivityAlgorithm) "For Zygote an abstract sensitivity algorithm from SciMLSensitivity must be used"
+        @assert (typeof(sensealg) <: SciMLBase.AbstractSensitivityAlgorithm) "For Zygote an abstract sensitivity algorithm from SciMLSensitivity must be used"
     end
     odeProblemGradient = gradientMethod === :ForwardEquations ? getODEProblemForwardEquations(odeProblem, sensealg) : getODEProblemForwardEquations(odeProblem, :NoSpecialProblem)
     # ssSolverGradient defaults to the same options as for the cost, but with tolerances set in relation to gradient ODE solver                                                 

diff --git a/test/Test_model2.jl b/test/Test_model2.jl
@@ -26,9 +26,9 @@ include(joinpath(@__DIR__, "Common.jl"))
 
 """
     testOdeSol(solver, tol; printRes=false)
-    Compare analytical vs numeric ODE solver using a provided solver with
-    tolerance tol for the Test_model2.
-    Returns true if passes test (sqDiff less than 1e-8) else returns false.
+Compare analytical vs numeric ODE solver using a provided solver with
+tolerance tol for the Test_model2.
+Returns true if passes test (sqDiff less than 1e-8) else returns false.
 """
 function testODESolverTestModel2(petabModel::PEtabModel, solverOptions)
 
@@ -118,10 +118,10 @@ end
 
 """
     testCostGradientOrHessianTestModel2(solver, tol; printRes::Bool=false)
-    Compare cost, gradient and hessian computed via the analytical solution
-    vs the PeTab importer functions (to check PeTab importer) for five random
-    parameter vectors for Test_model2. For the analytical solution the gradient
-    and hessian are computed via ForwardDiff.
+Compare cost, gradient and hessian computed via the analytical solution
+vs the PeTab importer functions (to check PeTab importer) for five random
+parameter vectors for Test_model2. For the analytical solution the gradient
+and hessian are computed via ForwardDiff.
 """
 function testCostGradientOrHessianTestModel2(petabModel::PEtabModel, solverOptions)