Modeling frameworks
for separable data

from glotaran.testing.simulated_data import sequential_spectral_decay
from glotaran.project import Project
from pyglotaran_extras import plot_overview, plot_data_overview

my_dataset = sequential_spectral_decay.DATASET
my_project = Project.open("my_project")
my_project.import_data(my_dataset, dataset_name="my_data")
plot_data_overview(my_dataset)  # to explore the dataset

result = my_project.optimize("my_model", "my_parameters")

# Run each in a separate cell:
result  # to inspect the optimization result
result.optimized_parameters  # view optimized parameters
plot_overview(result)  # result plot

initial_concentration:
  input:
    compartments: [s1, s2, s3]
    parameters: [input.1, input.0, input.0]
k_matrix:
  k1:
    matrix:
      (s2, s1): kinetic.1
      (s3, s2): kinetic.2
      (s3, s3): kinetic.3
megacomplex:
  m1:
    k_matrix: [k1]
    type: decay
irf:
  irf1:
    type: gaussian
    center: irf.center
    width: irf.width
dataset:
  my_data:
    initial_concentration: input
    megacomplex: [m1]
    irf: irf1

input:
  - ["1", 1, { "vary": false }]
  - ["0", 0, { "vary": false }]

kinetic: [0.51, 0.31, 0.11]

irf:
  - ["center", 0.31]
  - ["width", 0.11]