fixes

examples/model_coupling/external-linearmodel-ascii.jl

@@ -0,0 +1,14 @@
+#TODO this does NOT work; `parameters` are not required to be Ordered Dictionary
+paramfile = open("parameters.dat")
+parameters = Meta.parse.(readlines(paramfile))
+close(paramfile)
+
+f(t) = parameters[1] * t - parameters[2] # a * t - b; linear model
+times = 1:4
+predictions = map(f, times)
+
+predicfile = open("predictions.dat", "w")
+for prediction in predictions
+	write(predicfile, string(prediction, "\n"))
+end
+close(predicfile)

examples/model_coupling/external-linearmodel-ascii.mads

@@ -0,0 +1,11 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-ascii.jl"
+ASCIIParameters: parameters.dat
+ASCIIPredictions: predictions.dat

examples/model_coupling/external-linearmodel-jld.jl

@@ -0,0 +1,10 @@
+import JLD
+import OrderedCollections
+
+parameters = JLD.load("parameters.jld") # JLD file created to write current model parameters
+JLD
+f(t) = parameters["a"] * t - parameters["b"] # a * t - b; linear model
+times = 1:4
+predictions = OrderedCollections.OrderedDict(zip(map(i -> string("o", i), times), map(f, times)))
+
+JLD.save("predictions.jld", predictions) # JLD file created to write current model predictions

examples/model_coupling/external-linearmodel-jld.mads

@@ -0,0 +1,13 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- c : { longname: "parameter b", init: -1, type: null, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-jld.jl"
+JLDParameters: parameters.jld
+JLDPredictions:
+- predictions.jld

examples/model_coupling/external-linearmodel-jld2.jl

@@ -0,0 +1,10 @@
+import JLD2
+import OrderedCollections
+
+parameters = JLD2.load("parameters.jld2") # JLD file created to write current model parameters
+
+f(t) = parameters["a"] * t - parameters["b"] # a * t - b; linear model
+times = 1:4
+predictions = OrderedCollections.OrderedDict(zip(map(i -> string("o", i), times), map(f, times)))
+
+JLD2.save("predictions.jld2", predictions) # JLD file created to write current model predictions

examples/model_coupling/external-linearmodel-jld2.mads

@@ -0,0 +1,13 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- c : { longname: "parameter b", init: -1, type: null, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-jld2.jl"
+JLDParameters: parameters.jld2
+JLDPredictions:
+- predictions.jld2

examples/model_coupling/external-linearmodel-json-exp.mads

@@ -0,0 +1,12 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", exp: a*-1 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-json.jl"
+JSONParameters: parameters.json
+JSONPredictions:
+- predictions.json

examples/model_coupling/external-linearmodel-json.jl

@@ -0,0 +1,15 @@
+import JSON
+import OrderedCollections
+
+parameters = JSON.parsefile("parameters.json")
+@show parameters
+
+f(t) = parameters["a"] * t - parameters["b"] # a * t - b; linear model
+times = 1:4
+@show map(i -> string("o", i), times), map(f, times)
+predictions = OrderedCollections.OrderedDict(zip(map(i -> string("o", i), times), map(f, times)))
+
+@show predictions
+jo = open("predictions.json", "w")
+JSON.print(jo, predictions)
+close(jo)

examples/model_coupling/external-linearmodel-json.mads

@@ -0,0 +1,12 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-json.jl"
+JSONParameters: parameters.json
+JSONPredictions:
+- predictions.json

examples/model_coupling/external-linearmodel-parameters.inst

@@ -0,0 +1 @@
+internal-linearmodel-parameters.inst

examples/model_coupling/external-linearmodel-parameters.tpl

@@ -0,0 +1 @@
+internal-linearmodel-parameters.tpl

examples/model_coupling/external-linearmodel-yaml.jl

@@ -0,0 +1,14 @@
+import OrderedCollections
+import YAML
+
+parameters = YAML.load("parameters.yaml")
+if isfile(parameters)
+	parameters = YAML.load_file(parameters)
+end
+
+f(t) = parameters["a"] * t - parameters["b"] # a * t - b; linear model
+times = 1:4
+predictions = OrderedCollections.OrderedDict(zip(map(i -> string("o", i), times), map(f, times)))
+
+@show predictions
+YAML.write_file("predictions.yaml", predictions)

examples/model_coupling/external-linearmodel-yaml.mads

@@ -0,0 +1,13 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- c : { longname: "parameter b", init: -1, type: null, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-yaml.jl"
+YAMLParameters: parameters.yaml
+YAMLPredictions:
+- predictions.yaml

examples/model_coupling/internal-linearmodel.jl

@@ -0,0 +1 @@
+../models/internal-linear-model/internal-linearmodel.jl

examples/model_coupling/internal-linearmodel.mads

@@ -0,0 +1 @@
+../models/internal-linear-model/internal-linearmodel.mads

examples/montecarlo/internal-linearmodel.jl

@@ -0,0 +1 @@
+../models/internal-linear-model/internal-linearmodel.jl

examples/montecarlo/internal-linearmodel.mads

@@ -0,0 +1 @@
+../models/internal-linear-model/internal-linearmodel.mads

examples/optimization/external-ascii-linearmodel.jl

@@ -0,0 +1,14 @@
+#TODO this does NOT work; `parameters` are not required to be Ordered Dictionary
+paramfile = open("parameters.dat")
+parameters = Meta.parse.(readlines(paramfile))
+close(paramfile)
+
+f(t) = parameters[1] * t - parameters[2] # a * t - b; linear model
+times = 1:4
+predictions = map(f, times)
+
+predicfile = open("predictions.dat", "w")
+for prediction in predictions
+	write(predicfile, string(prediction, "\n"))
+end
+close(predicfile)

examples/optimization/external-ascii.mads

@@ -0,0 +1,11 @@
+Parameters:
+- a : { longname: "parameter a", init:  1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+- b : { longname: "parameter b", init: -1, type: opt, log: no, step: 0.1, min: -10, max: 10 }
+Observations:
+- o1: { longname: "observation 1", log: false, max: 20, min: -20, target: -3, weight: 1}
+- o2: { longname: "observation 2", log: false, max: 20, min: -20, target:  1, weight: 1}
+- o3: { longname: "observation 3", log: false, max: 20, min: -20, target:  5, weight: 1}
+- o4: { longname: "observation 4", log: false, max: 20, min: -20, target:  9, weight: 1}
+Command: "julia external-linearmodel-ascii.jl"
+ASCIIParameters: parameters.dat
+ASCIIPredictions: predictions.dat