Adapted examples to pyglotaran v0.3.0 release

Updated examples Updated LICENSE text Updated setup.py dependency information, authors Updated README with basic instructions
glotaran · Feb 21, 2021 · 956716e · 956716e
1 parent 76c26bf
commit 956716e
Show file tree

Hide file tree

Showing 24 changed files with 158 additions and 955 deletions.
diff --git a/LICENSE b/LICENSE
diff --git a/README.md b/README.md
@@ -1,3 +1,23 @@
 # pyglotaran_examples
 
-This repository hold examples showcasing the use of the pyglotaran package
+This repository hold examples showcasing the use of the pyglotaran package, version 0.3.0.
+Can be installed as a python package from sources, but is not released on pypi or conda.
+
+## Installation
+
+Prerequisites:
+
+- Python 3.8
+- Python package `pyglotaran` v0.3.0
+
+Note for Windows Users: The easiest way to get python for Windows is via [Anaconda](https://www.anaconda.com/)
+
+### Stable Release
+
+To install pyglotaran_examples from sources, either clone this repository or download the latest release, then run this command in your terminal:
+
+```shell
+git clone https://github.com/glotaran/pyglotaran_examples.git
+cd pyglotaran_examples
+pip install -e .
+```
diff --git a/pyglotaran_examples/ex_spectral_constraints/ex_spectral_constraints.py b/pyglotaran_examples/ex_spectral_constraints/ex_spectral_constraints.py
@@ -35,5 +35,9 @@
     print(model.markdown(parameters=parameters))
     scheme = Scheme(model, parameters, {"dataset1": dataset})
     result = optimize(scheme)
+    # Second optimization with results of the first:
+    scheme2 = result.get_scheme()
+    result2 = optimize(scheme2)
     simple_plot_overview(result.data["dataset1"], key)
+    simple_plot_overview(result2.data["dataset1"], key)
 plt.show()
diff --git a/pyglotaran_examples/ex_two_datasets/ex_two_datasets.py b/pyglotaran_examples/ex_two_datasets/ex_two_datasets.py
@@ -33,7 +33,14 @@
 print(model.validate(parameters=parameters))
 
 # %% Construct the analysis scheme
-scheme = Scheme(model, parameters, {"dataset1": dataset1, "dataset2": dataset2})
+scheme = Scheme(
+    model,
+    parameters,
+    {"dataset1": dataset1, "dataset2": dataset2},
+    maximum_number_function_evaluations=11,
+    non_negative_least_squares=True,
+    optimization_method="TrustRegionReflection",
+)
 
 # %% Optimize the analysis scheme (and estimate parameters)
 result = optimize(scheme)

diff --git a/pyglotaran_examples/ex_two_datasets/models/model.yml b/pyglotaran_examples/ex_two_datasets/models/model.yml
@@ -57,3 +57,10 @@ equal_area_penalties:
     target_intervals: [[300, 3000]]
     parameter: area.1
     weight: 0.1
+
+# Example of weight application:
+# weights:
+#   - datasets: [dataset1, dataset2]
+#     global_interval: [100, 102]
+#     model_interval: [301, 502]
+#     value: 0.95
diff --git a/pyglotaran_examples/study_transient_absorption/target_analysis_script.py b/pyglotaran_examples/study_transient_absorption/target_analysis_script.py
@@ -13,7 +13,7 @@
 from glotaran.analysis.scheme import Scheme
 from glotaran.io import read_data_file
 
-DATA_PATH = "data/data.ascii"
+DATA_PATH = "data/demo_data_Hippius_etal_JPCC2007_111_13988_Figs5_9.ascii"
 MODEL_PATH = "models/model.yml"
 PARAMETERS_FILE_PATH = "models/parameters.yml"
 

diff --git a/pyglotaran_examples/study_transient_absorption/two_dataset_analysis.py b/pyglotaran_examples/study_transient_absorption/two_dataset_analysis.py
@@ -15,8 +15,8 @@
 from glotaran.analysis.scheme import Scheme
 from glotaran.io.reader import read_data_file
 
-TARGET_MODEL = "models/co_co2_TA_model.yaml"
-TARGET_PARAMS = "models/co_co2_TA_parameters.yaml"
+TARGET_MODEL = "models/model_2d_co_co2.yml"
+TARGET_PARAMS = "models/parameters_2d_co_co2.yml"
 
 
 # %%

diff --git a/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsima.ascii b/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsima.ascii
diff --git a/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsimb.ascii b/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsimb.ascii
diff --git a/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsimc.ascii b/pyglotaran_examples/test/simultaneous_analysis_2d_weight/equareaIRFdispscalsimc.ascii
diff --git a/pyglotaran_examples/test/simultaneous_analysis_3d_disp/model.yml b/pyglotaran_examples/test/simultaneous_analysis_3d_disp/model.yml
@@ -77,8 +77,8 @@ equal_area_penalties:
     parameter: area.1
     weight: 0.1
 
-weights:
-  - datasets: [dataset1, dataset2, dataset3]
-    global_interval: [400, 450]
-    # model_interval: [301, 502]
-    value: 0.5
+# weights:
+#   - datasets: [dataset1, dataset2, dataset3]
+#     global_interval: [400, 450]
+#     # model_interval: [301, 502]
+#     value: 0.5
diff --git a/pyglotaran_examples/test/simultaneous_analysis_3d_disp/parameters.yml b/pyglotaran_examples/test/simultaneous_analysis_3d_disp/parameters.yml
@@ -1,33 +1,33 @@
 rates:
-  - ["k1", 0.05]
-  - ["k2", 0.5]
-  - ["k3", 2.1]
+  - ["k1", 0.0499]
+  - ["k2", 2.31]
+  - ["k3", 0.509]
   - {"vary": True,"non-negative": True}
 
 inputs:
   - ["1", 0.5, {"vary": False}]
-  - ["2", 0.251]
-  - ["3", 0.252]
-  - ["7", 0.21]
-  - ["8", 0.22]
-  - ["9", 0.22]
-  - ["10", 0.22]
+  - ["2", 0.180]
+  - ["3", 0.303]
+  - ["7", 0.387]
+  - ["8", 0.394]
+  - ["9", 0.288]
+  - ["10", 0.352]
   - {"non-negative": True}
 
 irf:
-  - ["center1",0.5]
-  - ["center2",0.5]
-  - ["center3",0.5]
-  - ["width", 0.06]
+  - ["center1",0.4]
+  - ["center2",0.41]
+  - ["center3",0.42]
+  - ["width", 0.05998]
   - ['dispc',500, {vary: False}]
   - ['disp1',0.01]
   - ['disp2',0.001]
 
 
 scale:
   - ["1", 1, {"vary": False}]
-  - ["2", 1.3, {"vary": True}]
-  - ["3", 1.1, {"vary": True}]
+  - ["2", 1.30557, {"vary": True}]
+  - ["3", 1.1635, {"vary": True}]
 
 pen:
   - ["1", 1, {"vary": False}]

diff --git a/pyglotaran_examples/test/simultaneous_analysis_3d_disp/sim_analysis_script_3d_disp.py b/pyglotaran_examples/test/simultaneous_analysis_3d_disp/sim_analysis_script_3d_disp.py
@@ -21,7 +21,7 @@
 # output folder for this specific analysis
 output_folder = results_folder.joinpath("simultaneous_analysis_3d_disp")
 
-# data inlezen
+# read in data
 data_path = script_folder.joinpath("equareaIRFdispscalsima.ascii")
 dataset1 = gta.io.read_data_file(data_path)
 # print(dataset1)
@@ -36,54 +36,53 @@
 
 model = gta.read_model_from_yaml_file(model_path)
 
+# if the optimized parameters from a previous run are available, use those
 parameter_file = output_folder.joinpath("optimized_parameters.csv")
 if parameter_file.exists():
     print("Optimized parameters exists: please check")
-    parameter = read_parameters_from_csv_file(str(parameter_file))
+    parameters = read_parameters_from_csv_file(str(parameter_file))
 else:
-    parameter = gta.read_parameters_from_yaml_file(parameters_path)
+    parameters = gta.read_parameters_from_yaml_file(parameters_path)
 
-print(model.validate(parameters=parameter))
+print(model.validate(parameters=parameters))
 
-# analysis schema definieren
+# define the analysis scheme to optimize
 scheme = Scheme(
     model,
-    parameter,
+    parameters,
     {"dataset1": dataset1, "dataset2": dataset2, "dataset3": dataset3},
-    maximum_number_function_evaluations=5,
+    maximum_number_function_evaluations=99,
     non_negative_least_squares=True,
+    # optimization_method="Levenberg-Marquardt",
 )
 # optimize
 result = optimize(scheme)
-# %%
-# evt opslaan
-
-
+# %% Save results
 result.save(str(output_folder))
-# evt plotten
-# %% Set subsequent plots to the glotaran style
+
+# %% Plot results
+# Set subsequent plots to the glotaran style
 plot_style = PlotStyle()
 plt.rc("axes", prop_cycle=plot_style.cycler)
 
-# %%
 # TODO: enhance plot_overview to handle multiple datasets
 result_datafile1 = output_folder.joinpath("dataset1.nc")
 result_datafile2 = output_folder.joinpath("dataset2.nc")
 result_datafile3 = output_folder.joinpath("dataset3.nc")
-fig1 = plot_overview(result_datafile1, linlog=True, linthresh=5)
+fig1 = plot_overview(result_datafile1, linlog=True, linthresh=1)
 fig1.savefig(
-    output_folder.joinpath("plot_overview_dummy1.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d1.pdf"),
     bbox_inches="tight",
 )
 
-fig2 = plot_overview(result_datafile2, linlog=True, linthresh=5)
+fig2 = plot_overview(result_datafile2, linlog=True, linthresh=1)
 fig2.savefig(
-    output_folder.joinpath("plot_overview_dummy2.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d2.pdf"),
     bbox_inches="tight",
 )
 
-fig3 = plot_overview(result_datafile3, linlog=True, linthresh=5)
+fig3 = plot_overview(result_datafile3, linlog=True, linthresh=1)
 fig3.savefig(
-    output_folder.joinpath("plot_overview_dummy3.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d3.pdf"),
     bbox_inches="tight",
 )
diff --git a/pyglotaran_examples/test/simultaneous_analysis_3d_nodisp/parameters.yml b/pyglotaran_examples/test/simultaneous_analysis_3d_nodisp/parameters.yml
@@ -1,27 +1,27 @@
 rates:
-  - ["k1", 0.199]
-  - ["k2", 0.5]
-  - ["k3", 2.1]
+  - ["k1", 0.05]
+  - ["k2", 2.0]
+  - ["k3", 0.5]
   - {"vary": True,"non-negative": True}
 
 inputs:
   - ["1", 0.5, {"vary": False}]
-  - ["2", 0.251]
-  - ["3", 0.252]
-  - ["7", 0.21]
-  - ["8", 0.22]
-  - ["9", 0.22]
-  - ["10", 0.22]
+  - ["2", 0.161]
+  - ["3", 0.311]
+  - ["7", 0.322]
+  - ["8", 0.415]
+  - ["9", 0.242]
+  - ["10", 0.363]
   - {"non-negative": True}
 
 irf:
-  - ["center",0.5]
-  - ["width", 0.1]
+  - ["center",0.4]
+  - ["width", 0.05998]
 
 scale:
   - ["1", 1, {"vary": False}]
-  - ["2", 0.991, {"vary": True}]
-  - ["3", 0.991, {"vary": True}]
+  - ["2", 1.27, {"vary": True}]
+  - ["3", 1.13, {"vary": True}]
 
 pen:
   - ["1", 1, {"vary": False}]

diff --git a/pyglotaran_examples/test/simultaneous_analysis_3d_nodisp/sim_analysis_script_3d.py b/pyglotaran_examples/test/simultaneous_analysis_3d_nodisp/sim_analysis_script_3d.py
@@ -21,7 +21,7 @@
 # output folder for this specific analysis
 output_folder = results_folder.joinpath("simultaneous_analysis_3d_nodisp")
 
-# data inlezen
+# read in data
 data_path = script_folder.joinpath("equareaIRFsim3a.ascii")
 dataset1 = gta.io.read_data_file(data_path)
 # print(dataset1)
@@ -36,54 +36,53 @@
 
 model = gta.read_model_from_yaml_file(model_path)
 
+# if the optimized parameters from a previous run are available, use those
 parameter_file = output_folder.joinpath("optimized_parameters.csv")
 if parameter_file.exists():
     print("Optimized parameters exists: please check")
-    parameter = read_parameters_from_csv_file(str(parameter_file))
+    parameters = read_parameters_from_csv_file(str(parameter_file))
 else:
-    parameter = gta.read_parameters_from_yaml_file(parameters_path)
+    parameters = gta.read_parameters_from_yaml_file(parameters_path)
 
-print(model.validate(parameters=parameter))
+print(model.validate(parameters=parameters))
 
-# analysis schema definieren
+# define the analysis scheme to optimize
 scheme = Scheme(
     model,
-    parameter,
+    parameters,
     {"dataset1": dataset1, "dataset2": dataset2, "dataset3": dataset3},
-    maximum_number_function_evaluations=5,
+    maximum_number_function_evaluations=99,
     non_negative_least_squares=True,
+    # optimization_method="Levenberg-Marquardt",
 )
 # optimize
 result = optimize(scheme)
-# %%
-# evt opslaan
-
-
+# %% Save results
 result.save(str(output_folder))
-# evt plotten
-# %% Set subsequent plots to the glotaran style
+
+# %% Plot results
+# Set subsequent plots to the glotaran style
 plot_style = PlotStyle()
 plt.rc("axes", prop_cycle=plot_style.cycler)
 
-# %%
 # TODO: enhance plot_overview to handle multiple datasets
 result_datafile1 = output_folder.joinpath("dataset1.nc")
 result_datafile2 = output_folder.joinpath("dataset2.nc")
 result_datafile3 = output_folder.joinpath("dataset3.nc")
-fig1 = plot_overview(result_datafile1, linlog=True, linthresh=5)
+fig1 = plot_overview(result_datafile1, linlog=True, linthresh=1)
 fig1.savefig(
-    output_folder.joinpath("plot_overview_dummy1.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d1.pdf"),
     bbox_inches="tight",
 )
 
-fig2 = plot_overview(result_datafile2, linlog=True, linthresh=5)
+fig2 = plot_overview(result_datafile2, linlog=True, linthresh=1)
 fig2.savefig(
-    output_folder.joinpath("plot_overview_dummy2.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d2.pdf"),
     bbox_inches="tight",
 )
 
-fig3 = plot_overview(result_datafile3, linlog=True, linthresh=5)
+fig3 = plot_overview(result_datafile3, linlog=True, linthresh=1)
 fig3.savefig(
-    output_folder.joinpath("plot_overview_dummy3.pdf"),
+    output_folder.joinpath("plot_overview_sim3d_d3.pdf"),
     bbox_inches="tight",
 )
diff --git a/...s_analysis_2d_weight/equareaIRFsim5.ascii → ...s_analysis_3d_weight/equareaIRFsim5.ascii b/...s_analysis_2d_weight/equareaIRFsim5.ascii → ...s_analysis_3d_weight/equareaIRFsim5.ascii
diff --git a/...s_analysis_2d_weight/equareaIRFsim6.ascii → ...s_analysis_3d_weight/equareaIRFsim6.ascii b/...s_analysis_2d_weight/equareaIRFsim6.ascii → ...s_analysis_3d_weight/equareaIRFsim6.ascii
diff --git a/...s_analysis_2d_weight/equareaIRFsim7.ascii → ...s_analysis_3d_weight/equareaIRFsim7.ascii b/...s_analysis_2d_weight/equareaIRFsim7.ascii → ...s_analysis_3d_weight/equareaIRFsim7.ascii
diff --git a/...s_analysis_2d_weight/equareaIRFsim8.ascii → ...s_analysis_3d_weight/equareaIRFsim8.ascii b/...s_analysis_2d_weight/equareaIRFsim8.ascii → ...s_analysis_3d_weight/equareaIRFsim8.ascii
diff --git a/...simultaneous_analysis_2d_weight/model.yml → ...simultaneous_analysis_3d_weight/model.yml b/...simultaneous_analysis_2d_weight/model.yml → ...simultaneous_analysis_3d_weight/model.yml
diff --git a/...taneous_analysis_2d_weight/parameters.yml → ...taneous_analysis_3d_weight/parameters.yml b/...taneous_analysis_2d_weight/parameters.yml → ...taneous_analysis_3d_weight/parameters.yml