Change AnalysisPipeline into "package"-like project (#229)

* Change AnalysisPipeline into "package"-like project

* add exeflag to `addprocs`

* reformat

pipeline/Project.toml

@@ -1,4 +1,5 @@
-name = "Analysis pipeline"
+name = "AnalysisPipeline"
+uuid = "66314692-3678-4cbb-b3ac-6fcb54505317"
 authors = ["Sam Abbott", "Sam Brand", "Zach Susswein"]
 
 [deps]
@@ -16,6 +17,7 @@ JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 RCall = "6f49c342-dc21-5d91-9882-a32aef131414"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
 CSV = "0.10"

pipeline/scripts/run_pipeline.jl

@@ -11,10 +11,9 @@ using Dagger
 # Define the backend resources to use for the pipeline
 # in this case we are using distributed local workers with loaded modules
 using Distributed
-pids = addprocs()
+pids = addprocs(; exeflags = ["--project=$(Base.active_project())"])
 
-@everywhere include("../src/AnalysisPipeline.jl")
-@everywhere using .AnalysisPipeline
+@everywhere using AnalysisPipeline
 
 # Create an instance of the pipeline behaviour
 pipeline = RtwithoutRenewalPipeline()

pipeline/scripts/run_priorpred_pipeline.jl

@@ -11,10 +11,9 @@ using Dagger
 # Define the backend resources to use for the pipeline
 # in this case we are using distributed local workers with loaded modules
 using Distributed
-pids = addprocs()
+pids = addprocs(; exeflags = ["--project=$(Base.active_project())"])
 
-@everywhere include("../src/AnalysisPipeline.jl")
-@everywhere using .AnalysisPipeline
+@everywhere using AnalysisPipeline
 
 # Create an instance of the pipeline behaviour
 pipeline = RtwithoutRenewalPriorPipeline()

pipeline/src/constructors/constructors.jl

@@ -7,4 +7,3 @@ include("make_truth_data_configs.jl")
 include("make_inference_configs.jl")
 include("make_Rt.jl")
 include("make_tspan.jl")
-include("make_inference_method.jl")

pipeline/test/constructors/test_constructors.jl

@@ -1,5 +1,5 @@
 @testset "make_gi_params: returns a dictionary with correct keys" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
     params = make_gi_params(pipeline)
 
@@ -9,30 +9,30 @@
 end
 
 @testset "make_inf_generating_processes" begin
-    using .AnalysisPipeline, EpiAware
+    using AnalysisPipeline, EpiAware
     pipeline = RtwithoutRenewalPipeline()
     igps = make_inf_generating_processes(pipeline)
     @test igps == [DirectInfections, ExpGrowthRate, Renewal]
 end
 
 @testset "make_Rt: returns an array" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
 
     Rt = make_Rt(pipeline)
     @test Rt isa Array
 end
 
 @testset "default_tspan: returns an Tuple{Integer, Integer}" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
 
     tspan = make_tspan(pipeline)
     @test tspan isa Tuple{Integer, Integer}
 end
 
 @testset "make_latent_model_priors: generates a dict with correct keys and distributions" begin
-    using .AnalysisPipeline, Distributions
+    using AnalysisPipeline, Distributions
     pipeline = RtwithoutRenewalPipeline()
 
     priors_dict = make_latent_model_priors(pipeline)
@@ -47,7 +47,7 @@ end
 end
 
 @testset "make_epiaware_name_model_pairs: generates a vector of Pairs with correct keys and latent models" begin
-    using .AnalysisPipeline, EpiAware
+    using AnalysisPipeline, EpiAware
     pipeline = RtwithoutRenewalPipeline()
 
     namemodel_vect = make_epiaware_name_model_pairs(pipeline)
@@ -57,7 +57,7 @@ end
 end
 
 @testset "make_inference_method: constructor and defaults" begin
-    using .AnalysisPipeline, EpiAware, ADTypes, AbstractMCMC
+    using AnalysisPipeline, EpiAware, ADTypes, AbstractMCMC
     pipeline = RtwithoutRenewalPipeline()
 
     method = make_inference_method(pipeline)
@@ -74,7 +74,7 @@ end
 end
 
 @testset "make_inference_method: for prior predictive checking" begin
-    using .AnalysisPipeline, EpiAware, ADTypes, AbstractMCMC
+    using AnalysisPipeline, EpiAware, ADTypes, AbstractMCMC
     pipeline = RtwithoutRenewalPriorPipeline()
 
     method = make_inference_method(pipeline)
@@ -84,7 +84,7 @@ end
 end
 
 @testset "make_truth_data_configs" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
     @testset "make_truth_data_configs should return a dictionary" begin
         config_dicts = make_truth_data_configs(pipeline)
@@ -99,7 +99,7 @@ end
 end
 
 @testset "default inference configurations" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
 
     inference_configs = make_inference_configs(pipeline)

pipeline/test/infer/test_InferenceConfig.jl

@@ -1,7 +1,7 @@
 
 # Test the InferenceConfig struct constructor
 @testset "InferenceConfig" begin
-    using Distributions, .AnalysisPipeline, EpiAware
+    using Distributions, AnalysisPipeline, EpiAware
 
     struct TestLatentModel <: AbstractLatentModel
     end

pipeline/test/pipeline/test_pipelinetypes.jl

@@ -1,5 +1,5 @@
 @testset "EpiAwarePipeline Tests" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     @testset "AbstractEpiAwarePipeline" begin
         @test_throws MethodError AbstractEpiAwarePipeline()
     end

pipeline/test/runtests.jl

@@ -1,10 +1,7 @@
 using DrWatson, Test
-quickactivate(@__DIR__(), "Analysis pipeline")
+quickactivate(@__DIR__(), "AnalysisPipeline")
 
-# Load analysis module
-include(srcdir("AnalysisPipeline.jl"));
-
-#run tests
+# Run tests
 include("pipeline/test_pipelinetypes.jl");
 include("constructors/test_constructors.jl");
 include("simulate/test_TruthSimulationConfig.jl");

pipeline/test/simulate/test_SimulationConfig.jl

@@ -1,7 +1,7 @@
 
 # Test the TruthSimulationConfig struct constructor
 @testset "TruthSimulationConfig" begin
-    using Distributions, .AnalysisPipeline, EpiAware
+    using Distributions, AnalysisPipeline, EpiAware
     gi = Gamma(2, 2)
     config = TruthSimulationConfig(
         truth_process = [0.5, 0.8, 1.2], gi_mean = 3.0, gi_std = 2.0)

pipeline/test/simulate/test_TruthSimulationConfig.jl

@@ -1,5 +1,5 @@
 @testset "simulate runs" begin
-    using Distributions, .AnalysisPipeline, EpiAware
+    using Distributions, AnalysisPipeline, EpiAware
     # Define a mock TruthSimulationConfig object for testing
     config = TruthSimulationConfig(
         truth_process = fill(1.5, 10), gi_mean = 2.0, gi_std = 2.0)
@@ -19,7 +19,7 @@
 end
 
 @testset "generate_truthdata" begin
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
     truth_data_config = Dict("gi_mean" => 0.5, "gi_std" => 0.1)
     truthdata = generate_truthdata(truth_data_config, pipeline)

pipeline/test/test_full_inference.jl

@@ -1,10 +1,9 @@
 using Test
 @testset "run inference for random scenario with short toy data" begin
-    using DrWatson, EpiAware
-    quickactivate(@__DIR__(), "Analysis pipeline")
-    include(srcdir("AnalysisPipeline.jl"))
+    using DrWatson
+    quickactivate(@__DIR__(), "AnalysisPipeline")
 
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPipeline()
 
     tspan = (1, 28)

pipeline/test/test_prior_predictive.jl

@@ -4,7 +4,7 @@ using Test
     quickactivate(@__DIR__(), "Analysis pipeline")
     include(srcdir("AnalysisPipeline.jl"))
 
-    using .AnalysisPipeline
+    using AnalysisPipeline
     pipeline = RtwithoutRenewalPriorPipeline()
 
     tspan = (1, 28)