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'