Refactore/use project

pyglotaran_examples/ex_two_datasets/ex_two_datasets2.py

@@ -0,0 +1,40 @@
+from datetime import datetime
+
+import matplotlib.pyplot as plt  # 3.3 or higher
+from glotaran.project.project import Project
+from pyglotaran_extras.plotting.plot_overview import plot_overview
+from pyglotaran_extras.plotting.style import PlotStyle
+
+
+project = Project.open(".")
+print(project.markdown())
+
+
+project.optimize(
+    "model_ex_two_datasets",
+    "parameters_ex_two_datasets",
+    name="result_ex_two_datasets",
+    maximum_number_function_evaluations=15,
+)
+
+result = project.load_result("result_ex_two_datasets")
+print(result.markdown(True))
+
+# recreation
+# result_recreated = result.recreate()
+
+# %% Plot and save as PDF
+# This set subsequent plots to the glotaran style
+plot_style = PlotStyle()
+plt.rc("axes", prop_cycle=plot_style.cycler)
+
+results_folder = project.get_result_path("result_ex_two_datasets")
+fig1 = plot_overview(result.data["data1"], linlog=True)
+timestamp = datetime.today().strftime("%y%m%d_%H%M")
+fig1.savefig(results_folder.joinpath(f"plot_overview_1of2_{timestamp}.pdf"), bbox_inches="tight")
+
+fig2 = plot_overview(result.data["data2"], linlog=True)
+timestamp = datetime.today().strftime("%y%m%d_%H%M")
+fig2.savefig(results_folder.joinpath(f"plot_overview_2of2_{timestamp}.pdf"), bbox_inches="tight")
+
+plt.show()

pyglotaran_examples/ex_two_datasets/models/model.yml → pyglotaran_examples/ex_two_datasets/models/model_ex_two_datasets.yml

@@ -1,12 +1,12 @@
 type: kinetic-spectrum
 
 dataset:
-  dataset1:
+  data1:
     megacomplex: [complex1]
     initial_concentration: input1
     irf: irf1
     scale: scale.1
-  dataset2:
+  data2:
     megacomplex: [complex1]
     initial_concentration: input2
     irf: irf1

pyglotaran_examples/ex_two_datasets/project.gta

@@ -0,0 +1 @@
+version: 0.6.0.dev0

pyglotaran_examples/ex_two_datasets/results/result_ex_two_datasets/initial_parameters.csv

@@ -0,0 +1,14 @@
+label,value,expression,minimum,maximum,non-negative,vary,standard-error
+inputs.1,0.5,None,-inf,inf,True,False,None
+inputs.2,0.251,None,-inf,inf,True,True,None
+inputs.3,0.252,None,-inf,inf,True,True,None
+inputs.7,0.21,None,-inf,inf,True,True,None
+inputs.8,0.22,None,-inf,inf,True,True,None
+scale.1,1.0,None,-inf,inf,False,False,None
+scale.2,1.2,None,-inf,inf,False,True,None
+rates.k1,0.199,None,-inf,inf,True,True,None
+rates.k2,0.5,None,-inf,inf,True,True,None
+rates.k3,1.1,None,-inf,inf,True,True,None
+irf.center,0.5,None,-inf,inf,False,True,None
+irf.width,0.1,None,-inf,inf,False,True,None
+area.1,1.0,None,-inf,inf,False,False,None

pyglotaran_examples/ex_two_datasets/results/result_ex_two_datasets/model.yml

@@ -0,0 +1,79 @@
+default_megacomplex: decay
+dataset_groups:
+  default:
+    residual_function: variable_projection
+    link_clp: null
+clp_area_penalties:
+- source: s1
+  source_intervals: [[300, 3000]]
+  target: s2
+  target_intervals: [[300, 3000]]
+  parameter: area.1
+  weight: 0.1
+- source: s1
+  source_intervals: [[300, 3000]]
+  target: s3
+  target_intervals: [[300, 3000]]
+  parameter: area.1
+  weight: 0.1
+k_matrix:
+  km1:
+    matrix:
+      (s1, s1): rates.k1
+      (s2, s2): rates.k2
+      (s3, s3): rates.k3
+initial_concentration:
+  input1:
+    compartments: [s1, s2, s3]
+    parameters:
+    - inputs.1
+    - inputs.2
+    - inputs.3
+    exclude_from_normalize: &id001 []
+  input2:
+    compartments: [s1, s2, s3]
+    parameters:
+    - inputs.1
+    - inputs.7
+    - inputs.8
+    exclude_from_normalize: *id001
+irf:
+  irf1:
+    type: spectral-multi-gaussian
+    center:
+    - irf.center
+    width:
+    - irf.width
+    normalize: true
+    backsweep: false
+    center_dispersion_coefficients: []
+    width_dispersion_coefficients: []
+    model_dispersion_with_wavenumber: false
+  irf1_no_dispersion:
+    type: spectral-multi-gaussian
+    center:
+    - irf.center
+    width:
+    - irf.width
+    normalize: true
+    backsweep: false
+    center_dispersion_coefficients: []
+    width_dispersion_coefficients: []
+    model_dispersion_with_wavenumber: false
+megacomplex:
+  complex1:
+    dimension: time
+    k_matrix: [km1]
+dataset:
+  data1:
+    group: default
+    megacomplex: [complex1]
+    scale: scale.1
+    initial_concentration: input1
+    irf: irf1
+  data2:
+    group: default
+    megacomplex: [complex1]
+    scale: scale.2
+    initial_concentration: input2
+    irf: irf1

pyglotaran_examples/ex_two_datasets/results/result_ex_two_datasets/optimized_parameters.csv

@@ -0,0 +1,14 @@
+label,value,expression,minimum,maximum,non-negative,vary,standard-error
+inputs.1,0.5,None,-inf,inf,True,False,None
+inputs.2,0.3241735606305694,None,-inf,inf,True,True,0.006016512068269458
+inputs.3,0.6637030039362178,None,-inf,inf,True,True,0.0019604282258593145
+inputs.7,0.07199305634408268,None,-inf,inf,True,True,0.007473183032103718
+inputs.8,0.28038519367032166,None,-inf,inf,True,True,0.001703415408630161
+scale.1,1.0,None,-inf,inf,False,False,None
+scale.2,1.0988429227695649,None,-inf,inf,False,True,5.0687678682918585e-05
+rates.k1,0.2609087519506281,None,-inf,inf,True,True,0.0003594210205855631
+rates.k2,1.1764960957874322,None,-inf,inf,True,True,0.0018332582913621488
+rates.k3,0.6161191387338244,None,-inf,inf,True,True,0.001294924541886501
+irf.center,0.3999993625795483,None,-inf,inf,False,True,5.5115045961994905e-06
+irf.width,0.0599642034148812,None,-inf,inf,False,True,7.46734564090631e-06
+area.1,1.0,None,-inf,inf,False,False,None