Output results as a dataframe + return short names, hctsa names and values as standard.

.github/CODE_OF_CONDUCT.md

@@ -0,0 +1,127 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge 🤝
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that contribute to an open, welcoming,
+diverse, inclusive, and healthy community.
+
+## Our Standards 🌟
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+* Demonstrating empathy and kindness toward other people
+* Being respectful of differing opinions, viewpoints, and experiences
+* Giving and gracefully accepting constructive feedback
+* Accepting responsibility and apologizing to those affected by our mistakes,
+  and learning from the experience
+* Focusing on what is best not just for us as individuals, but for the
+  overall community
+
+Examples of unacceptable behavior include:
+
+* The use of sexualized language or imagery, and sexual attention or
+  advances of any kind
+* Trolling, insulting or derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or email
+  address, without their explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Enforcement Responsibilities 🛡️
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope 🌐
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement 👮🏻
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement [here]([email protected]).
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines 📋
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction ✔️
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning ❗
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interactions in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban ⏳
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban ❌
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior,  harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution 👍
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.0, available at
+https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
+
+Community Impact Guidelines were inspired by [Mozilla's code of conduct
+enforcement ladder](https://github.com/mozilla/diversity).
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see the FAQ at
+https://www.contributor-covenant.org/faq. Translations are available at
+https://www.contributor-covenant.org/translations.

.github/SECURITY.md

@@ -0,0 +1,17 @@
+# Reporting Security Issues 🛡️
+
+The _catch22_ team and community take security bugs in _catch22_ seriously. We appreciate your efforts to responsibly disclose your findings, and will make every effort to acknowledge your contributions.
+
+To report a security issue, please use the GitHub Security Advisory tab.
+
+The _catch22_ team will send a response indicating the next steps in handling your report. After the initial reply to your report, the security team will keep you informed of the progress towards a fix and full announcement, and may ask for additional information or guidance.
+
+## Supported Versions
+
+The following versions of _catch22_ are
+currently being supported with security updates.
+
+| Version | Supported          |
+| ------- | ------------------ |
+| 0.5.0   | :white_check_mark: |
+| 0.4.5   | :white_check_mark: |

.github/workflows/run_unit_tests.yaml

@@ -9,7 +9,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
     steps:
       - uses: actions/checkout@v3
       - name: Setup python ${{ matrix.python-version }}

README.md

@@ -1,10 +1,17 @@
-<p align="center"><img src="img/catch22_logo_square.png" alt="catch22 logo" height="220"/></p>
+<p align="center">
+    <picture>
+        <source srcset="img/catch22_logo_square_darkmode.png" media="(prefers-color-scheme: dark)">
+        <img src="img/catch22_logo_square.png" alt="catch22 logo" height="220"/>
+    </picture>
+</p>
 
 <h1 align="center"><em>pycatch22</em>: CAnonical Time-series CHaracteristics in python</h1>
 
 <p align="center">
     <a href="https://www.gnu.org/licenses/gpl-3.0"><img src="https://img.shields.io/badge/License-GPLv3-blue.svg" height="20"/></a>
  	  <a href="https://twitter.com/compTimeSeries"><img src="https://img.shields.io/twitter/url/https/twitter.com/compTimeSeries.svg?style=social&label=Follow%20%40compTimeSeries" height="20"/></a>
+    <a href="https://github.com/DynamicsAndNeuralSystems/pycatch22/actions/workflows/run_unit_tests.yaml"><img src="https://github.com/DynamicsAndNeuralSystems/pycatch22/actions/workflows/run_unit_tests.yaml/badge.svg?branch=main" height="20"/></a><br>
+    <a href="https://www.python.org"><img src="https://img.shields.io/badge/Python-3.8%20|%203.9%20|%203.10%20|%203.11%20|%203.12-3776AB.svg?style=flat&logo=python&logoColor=white" alt="Python 3.8 | 3.9 | 3.10 | 3.11 | 3.12"></a>
 </p>
 
 
@@ -63,7 +70,10 @@ tsData = [1,2,4,3] # (or more interesting data!)
 pycatch22.CO_f1ecac(tsData)
 ```
 
-All features are bundled in the method `catch22_all`, which also accepts `numpy` arrays and gives back a dictionary containing the entries `catch22_all['names']` for feature names and `catch22_all['values']` for feature outputs.
+All features are bundled in the method `catch22_all`, which also accepts `numpy` arrays and gives back a `DataFrame` containing the columns:
+- `feature` for (short) feature names (as outlined in the GitBook [Feature overview table](https://time-series-features.gitbook.io/catch22/feature-descriptions/feature-overview-table)).
+- `hctsa_name` for (long) feature names as they appear in HCTSA.
+- `value` for feature outputs.
 
 Usage (computing 22 features: _catch22_):
 
@@ -77,13 +87,6 @@ Usage (computing 24 features: _catch24_ = _catch22_ + mean + standard deviation)
 pycatch22.catch22_all(tsData,catch24=True)
 ```
 
-We also include a 'short name' for each feature for easier reference (as outlined in the GitBook [Feature overview table](https://time-series-features.gitbook.io/catch22/feature-descriptions/feature-overview-table)).
-These short names can be included in the output from `catch22_all()` by setting `short_names=True` as follows:
-
-```python3
-pycatch22.catch22_all(tsData,catch24=True,short_names=True)
-```
-
 ### Template analysis script
 
 Thanks to [@jmoo2880](https://github.com/jmoo2880) for putting together a [demonstration notebook](https://github.com/jmoo2880/c22-usage-examples/) for using pycatch22 to extract features from a time-series dataset.

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "pycatch22"
-version = "0.4.5"
+version = "1.0.0"
 authors = [
     {name = "Carl H Lubba"},
     {email = "[email protected]"},
@@ -17,6 +17,10 @@ classifiers = [
     "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
     "Operating System :: OS Independent",
 ]
+dependencies = [
+    "pandas", 
+    "numpy"
+]
 
 [project.urls]
 "GitHub Repository (pycatch22)" = "https://github.com/DynamicsAndNeuralSystems/pycatch22"

setup.py

@@ -26,5 +26,6 @@
     packages = find_packages(where = "src",
                             include = ["pycatch22"]),
     package_dir = {"": "src"},
-    ext_modules = [extension_mod]
+    ext_modules = [extension_mod],
+    install_requires = ["numpy", "pandas"]
 )

src/pycatch22/catch22.py

@@ -1,6 +1,7 @@
 import catch22_C
+import pandas as pd
 
-def catch22_all(data, catch24=False, short_names=False):
+def catch22_all(data, catch24=False):
     '''
     Extract the catch22 feature set from an input time series.
 
@@ -10,12 +11,10 @@ def catch22_all(data, catch24=False, short_names=False):
         Input time-series data.
     catch24 : bool, optional
         If True, include the two catch24 features (mean and standard deviation) in the output.
-    short_names : bool, optional
-        If True, also include the short names of the features in the output.
 
     '''
 
-    features = [
+    features_hctsa = [
         'DN_HistogramMode_5',
         'DN_HistogramMode_10',
         'CO_f1ecac',
@@ -40,7 +39,7 @@ def catch22_all(data, catch24=False, short_names=False):
         'FC_LocalSimple_mean3_stderr'
     ]
 
-    features_short = [
+    features = [
         'mode_5',
         'mode_10',
         'acf_timescale',
@@ -66,18 +65,18 @@ def catch22_all(data, catch24=False, short_names=False):
     ]
 
     if catch24:
-        features.append('DN_Mean')
-        features.append('DN_Spread_Std')
-        features_short.append('mean')
-        features_short.append('SD')
+        features_hctsa.append('DN_Mean')
+        features_hctsa.append('DN_Spread_Std')
+        features.append('mean')
+        features.append('SD')
 
     data = list(data)
     featureOut = []
-    for f in features:
+    for f in features_hctsa:
         featureFun = getattr(catch22_C, f)
         featureOut.append(featureFun(data))
 
-    if short_names:
-        return {'names': features, 'short_names': features_short, 'values': featureOut}
-    else:
-        return {'names': features, 'values': featureOut}
+    # convert to a dataframe
+    feature_results = pd.DataFrame({'feature': features, 'value': featureOut, 'hctsa_name': features_hctsa})
+
+    return feature_results 

tests/test_features.py

@@ -50,7 +50,7 @@ def load_expected_outputs():
 def compute_new_features():
     """Computes new feature outputs on same benchmarking dataset and
     then returns dictionary of datasets in the same format as
-    the loaded expected outputs dictionary"""
+    the loaded expected outputs dictionary for direct comparison."""
 
     benchmark_datasets = load_benchmark_datasets()
     datasets = benchmark_datasets.keys()
@@ -60,7 +60,7 @@ def compute_new_features():
         print(f"Computing features for: {dset}...")
         test_data = benchmark_datasets[dset]
         res = catch22.catch22_all(test_data, catch24=True)
-        for (name, val) in zip(res['names'], res['values']):
+        for (name, val) in zip(res['hctsa_name'], res['value']):
             dataset_dict_single[name] = float(val)
         dataset_dicts[dset] = dataset_dict_single