Visualization methods

doc/api.rst

@@ -16,5 +16,6 @@ petab-select Python API
    petab_select.model_space
    petab_select.model_subspace
    petab_select.petab
+   petab_select.plot
    petab_select.problem
    petab_select.ui

doc/examples.rst

@@ -7,5 +7,6 @@ Various example notebooks.
    :maxdepth: 1
 
    examples/example_cli_famos.ipynb
+   examples/visualization.ipynb
    examples/workflow_cli.ipynb
    examples/workflow_python.ipynb

doc/examples/calibrated_models/calibrated_models.yaml

@@ -0,0 +1,115 @@
+- criteria:
+    AICc: 37.97523003111246
+    NLLH: 17.48761501555623
+  estimated_parameters:
+    sigma_x2: 4.462298385653177
+  model_hash: M_0-000
+  model_id: M_0-000
+  model_subspace_id: M_0
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: 0
+    k2: 0
+    k3: 0
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: virtual_initial_model
+- criteria:
+    AICc: -0.1754060811089051
+    NLLH: -4.0877030405544525
+  estimated_parameters:
+    k3: 0.0
+    sigma_x2: 0.12242920113658744
+  model_hash: M_1-000
+  model_id: M_1-000
+  model_subspace_id: M_1
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: 0.2
+    k2: 0.1
+    k3: estimate
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: M_0-000
+- criteria:
+    AICc: -0.27451405630430337
+    NLLH: -4.137257028152152
+  estimated_parameters:
+    k2: 0.10147827639089564
+    sigma_x2: 0.12142256779953603
+  model_hash: M_2-000
+  model_id: M_2-000
+  model_subspace_id: M_2
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: 0.2
+    k2: estimate
+    k3: 0
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: M_0-000
+- criteria:
+    AICc: -0.7053270517931587
+    NLLH: -4.352663525896579
+  estimated_parameters:
+    k1: 0.20160888007873565
+    sigma_x2: 0.11713858557052499
+  model_hash: M_3-000
+  model_id: M_3-000
+  model_subspace_id: M_3
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: estimate
+    k2: 0.1
+    k3: 0
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: M_0-000
+- criteria:
+    AICc: 9.294672948206841
+    NLLH: -4.352663525896579
+  estimated_parameters:
+    k1: 0.20160888007873565
+    k3: 0.0
+    sigma_x2: 0.11713858557052499
+  model_hash: M_5-000
+  model_id: M_5-000
+  model_subspace_id: M_5
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: estimate
+    k2: 0.1
+    k3: estimate
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: M_3-000
+- criteria:
+    AICc: 7.852170288089528
+    NLLH: -5.073914855955236
+  estimated_parameters:
+    k1: 0.20924739987621038
+    k2: 0.0859065470362628
+    sigma_x2: 0.1038731029818225
+  model_hash: M_6-000
+  model_id: M_6-000
+  model_subspace_id: M_6
+  model_subspace_indices:
+  - 0
+  - 0
+  - 0
+  parameters:
+    k1: estimate
+    k2: estimate
+    k3: 0
+  petab_yaml: petab_problem.yaml
+  predecessor_model_hash: M_3-000

doc/examples/calibrated_models/conditions.tsv

@@ -0,0 +1,2 @@
+conditionId	conditionName
+model1_data1	condition1

doc/examples/calibrated_models/measurements.tsv

@@ -0,0 +1,7 @@
+observableId	simulationConditionId	measurement	time	noiseParameters
+obs_x2	model1_data1	0	0	sigma_x2
+obs_x2	model1_data1	0.19421762	1	sigma_x2
+obs_x2	model1_data1	0.0484032	5	sigma_x2
+obs_x2	model1_data1	0.61288016	10	sigma_x2
+obs_x2	model1_data1	4.07930835	30	sigma_x2
+obs_x2	model1_data1	10.12008893	60	sigma_x2