diff --git a/CITATION.cff b/CITATION.cff index 31ec633..502a6c7 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -11,7 +11,7 @@ authors: given-names: "Georges" orcid: "https://orcid.org/0000-0003-4168-8254" title: "Interactive polar diagrams for model comparison" -version: 1.1.0 +version: 1.2.0 doi: 10.1016/j.cmpb.2023.107843 date-released: 2023-10-06 url: "https://github.com/AAnzel/Polar-Diagrams-for-Model-Comparison" diff --git a/Source/main.ipynb b/Source/main.ipynb index 9d6b98c..a0dadb1 100644 --- a/Source/main.ipynb +++ b/Source/main.ipynb @@ -64,7 +64,7 @@ "__copyright__ = ''\n", "__credits__ = ['Aleksandar Anžel', 'Georges Hattab']\n", "__license__ = 'GNU General Public License v3.0'\n", - "__version__ = '1.1.1'\n", + "__version__ = '1.2.0'\n", "__maintainer__ = 'Aleksandar Anžel'\n", "__email__ = 'AnzelA@rki.de'\n", "__status__ = 'Stable'" @@ -6371,7 +6371,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -7995,7 +7995,7 @@ ], "showlegend": false, "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -9580,7 +9580,7 @@ "showlegend": false, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -27703,7 +27703,7 @@ ], "showlegend": true, "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" } @@ -42494,7 +42494,7 @@ "showlegend": false, "subplot": "polar2", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -53339,7 +53339,7 @@ "showlegend": false, "subplot": "polar2", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -62769,7 +62769,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 8.537736462515939e-07 + 8.537736462515939e-7 ], "type": "scatterpolar" }, @@ -67616,7 +67616,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -72474,7 +72474,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 8.537736462515939e-07 + 8.537736462515939e-7 ], "type": "scatterpolar" }, @@ -82190,7 +82190,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -87017,7 +87017,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -87311,7 +87311,7 @@ "showlegend": false, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -91785,7 +91785,7 @@ "showlegend": true, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -93182,7 +93182,7 @@ "showlegend": false, "subplot": "polar", "theta": [ - 1.2074182697257333e-06 + 0.0000012074182697257333 ], "type": "scatterpolar" }, @@ -125569,7 +125569,7 @@ "showlegend": false, "subplot": "polar2", "theta": [ - 1.7075472925031877e-06 + 0.0000017075472925031877 ], "type": "scatterpolar" } diff --git a/Source/polar_diagrams/docs/polar_diagrams.md b/Source/polar_diagrams/docs/polar_diagrams.md index 26282da..3d902cb 100644 --- a/Source/polar_diagrams/docs/polar_diagrams.md +++ b/Source/polar_diagrams/docs/polar_diagrams.md @@ -1,32 +1,28 @@ # Table of Contents -* [\_\_init\_\_](#__init__) * [polar\_diagrams](#polar_diagrams) - * [df\_calculate\_td\_properties](#polar_diagrams.df_calculate_td_properties) - * [df\_calculate\_mid\_properties](#polar_diagrams.df_calculate_mid_properties) - * [df\_calculate\_all\_properties](#polar_diagrams.df_calculate_all_properties) - * [chart\_create\_taylor\_diagram](#polar_diagrams.chart_create_taylor_diagram) - * [chart\_create\_mi\_diagram](#polar_diagrams.chart_create_mi_diagram) - * [chart\_create\_all\_diagrams](#polar_diagrams.chart_create_all_diagrams) - - - -# \_\_init\_\_ - -.. include:: ../README.md +* [polar\_diagrams.polar\_diagrams](#polar_diagrams.polar_diagrams) + * [df\_calculate\_td\_properties](#polar_diagrams.polar_diagrams.df_calculate_td_properties) + * [df\_calculate\_mid\_properties](#polar_diagrams.polar_diagrams.df_calculate_mid_properties) + * [df\_calculate\_all\_properties](#polar_diagrams.polar_diagrams.df_calculate_all_properties) + * [chart\_create\_taylor\_diagram](#polar_diagrams.polar_diagrams.chart_create_taylor_diagram) + * [chart\_create\_mi\_diagram](#polar_diagrams.polar_diagrams.chart_create_mi_diagram) + * [chart\_create\_all\_diagrams](#polar_diagrams.polar_diagrams.chart_create_all_diagrams) # polar\_diagrams - + + +# polar\_diagrams.polar\_diagrams + + -## df\_calculate\_td\_properties +#### df\_calculate\_td\_properties ```python -def df_calculate_td_properties(df_input, - string_reference_model, - string_corr_method='pearson') +def df_calculate_td_properties(df_input, string_reference_model, string_corr_method='pearson') ``` df_calculate_td_properties caclulates all necessary statistical information @@ -57,14 +53,12 @@ for the Taylor diagram from the input data set. - `pandas.DataFrame` - This dataframe contains model names as indices and statistical properties as columns. - + -## df\_calculate\_mid\_properties +#### df\_calculate\_mid\_properties ```python -def df_calculate_mid_properties(df_input, - string_reference_model, - dict_mi_parameters=dict( +def df_calculate_mid_properties(df_input, string_reference_model, dict_mi_parameters=dict( string_entropy_method='auto', int_mi_n_neighbors=3, discrete_models='auto', @@ -105,20 +99,17 @@ properties for the Mutual Information diagram from the input data set. - `pandas.DataFrame` - This dataframe contains model names as indices and information theory properties as columns. - + -## df\_calculate\_all\_properties +#### df\_calculate\_all\_properties ```python -def df_calculate_all_properties(df_input, - string_reference_model, - dict_mi_parameters=dict( +def df_calculate_all_properties(df_input, string_reference_model, dict_mi_parameters=dict( string_entropy_method='auto', int_mi_n_neighbors=3, discrete_models='auto', bool_discrete_reference_model=False, - int_random_state=_INT_RANDOM_SEED), - string_corr_method='pearson') + int_random_state=_INT_RANDOM_SEED), string_corr_method='pearson') ``` df_calculate_all_properties caclulates all necessary statistical and @@ -150,15 +141,12 @@ from the input data set. - `pandas.DataFrame` - This dataframe contains model names as indices and statistical and information theory properties as columns. - + -## chart\_create\_taylor\_diagram +#### chart\_create\_taylor\_diagram ```python -def chart_create_taylor_diagram(list_df_input, - string_reference_model, - string_corr_method='pearson', - bool_normalized_measures=False) +def chart_create_taylor_diagram(list_df_input, string_reference_model, string_corr_method='pearson', bool_normalized_measures=False) ``` chart_create_taylor_diagram creates the Taylor diagram according to the @@ -207,21 +195,17 @@ model predictions. - `plotly.graph_objects.Figure` - This chart contains the resulting Taylor diagram. - + -## chart\_create\_mi\_diagram +#### chart\_create\_mi\_diagram ```python -def chart_create_mi_diagram(list_df_input, - string_reference_model, - string_mid_type='scaled', - dict_mi_parameters=dict( +def chart_create_mi_diagram(list_df_input, string_reference_model, string_mid_type='scaled', dict_mi_parameters=dict( string_entropy_method='auto', int_mi_n_neighbors=3, discrete_models='auto', bool_discrete_reference_model=False, - int_random_state=_INT_RANDOM_SEED), - bool_normalized_measures=False) + int_random_state=_INT_RANDOM_SEED), bool_normalized_measures=False) ``` chart_create_mi_diagram creates the Mutual Information diagram according @@ -277,22 +261,17 @@ contain model predictions. - `plotly.graph_objects.Figure` - This chart contains the resulting Mutual Information diagram. - + -## chart\_create\_all\_diagrams +#### chart\_create\_all\_diagrams ```python -def chart_create_all_diagrams(list_df_input, - string_reference_model, - string_mid_type='scaled', - string_corr_method='pearson', - dict_mi_parameters=dict( +def chart_create_all_diagrams(list_df_input, string_reference_model, string_mid_type='scaled', string_corr_method='pearson', dict_mi_parameters=dict( string_entropy_method='auto', int_mi_n_neighbors=3, discrete_models='auto', bool_discrete_reference_model=False, - int_random_state=_INT_RANDOM_SEED), - bool_normalized_measures=False) + int_random_state=_INT_RANDOM_SEED), bool_normalized_measures=False) ``` chart_create_all_diagrams creates both the Taylor and the Mutual diff --git a/Source/polar_diagrams/setup.cfg b/Source/polar_diagrams/setup.cfg index 50e951f..42d9a5d 100644 --- a/Source/polar_diagrams/setup.cfg +++ b/Source/polar_diagrams/setup.cfg @@ -1,7 +1,7 @@ [metadata] name = polar_diagrams -version = 1.1.1 +version = 1.2.0 author = Aleksandar Anžel author_email = AnzelA@rki.de description = Interactive Polar Diagrams for Model Comparison diff --git a/Source/polar_diagrams/src/polar_diagrams/polar_diagrams.py b/Source/polar_diagrams/src/polar_diagrams/polar_diagrams.py index 1c37c30..d8f65ca 100644 --- a/Source/polar_diagrams/src/polar_diagrams/polar_diagrams.py +++ b/Source/polar_diagrams/src/polar_diagrams/polar_diagrams.py @@ -18,7 +18,7 @@ __copyright__ = '' __credits__ = ['Aleksandar Anžel'] __license__ = 'GNU General Public License v3.0' -__version__ = '1.1.1' +__version__ = '1.2.0' __maintainer__ = 'Aleksandar Anžel' __email__ = 'aleksandar.anzel@uni-marburg.de' __status__ = 'Stable'