Rlign v1.1

.github/workflows/gitlab-mirror-actions.yml

@@ -3,7 +3,8 @@ name: Mirror and run GitLab CI
 on: 
   push:
     branches: 
-      -  main
+      - main
+      - 'dev-*'
   workflow_dispatch: {} # manual dispatch
 
 jobs:

.gitignore

@@ -4,6 +4,7 @@ __pycache__/
 *$py.class
 .DS_Store
 .idea/*
+.vscode/*
 
 # C extensions
 *.so

.gitlab-ci.yml

@@ -1,6 +1,18 @@
 stages:
+    - test
     - build
 
+tests:
+  stage: test
+  image: python:3.11-slim-bookworm
+  environment: production
+  before_script:
+    - pip install pytest
+  script:
+    - pip install .
+    - pytest -W error test/
+
+
 build:
   stage: build
   image: python:3.11-slim-bookworm

README.md

@@ -34,23 +34,23 @@ normalizer = rlign.Rlign(scale_method='hrc')
 ecg_aligned = normalizer.transform(ecg)
 
 # You can set different configuration like median_beat-averaging or the template_bpm
-normalizer = rlign.Rlign(scale_method='hrc', median_beat=True, template_bpm=80)
+normalizer = rlign.Rlign(scale_method='hrc', agg_beat='median', template_bpm=80)
 
-ecg_aligned_80hz = normalizer.transform(ecg)
+ecg_aligned_80bpm = normalizer.transform(ecg)
 ```
 
 ### Configurations
 
 * `sampling_rate`: Defines the sampling rate for all ECG recordings and the template. Default is set to 500.
 
-* `seconds_len`: Determines the duration of all ECG recordings and the template in seconds.
+* `seconds_len`: Determines the duration of all ECG recordings and the template in seconds. Default is 10 (sec).
 
 * `template_bpm`: The desired normalized BPM value for the template. 
     This parameter sets the heart rate around which the QRST pattern 
     is structured, thereby standardizing the R-peak positions according to a specific BPM.
 
 * `offset`: The offset specifies the starting point for the first normalized QRS complex in the 
-    template. In percentage of sampling_rate. Default is set to 0.5.
+    template. In percentage of sampling_rate. Default is set to 0.01.
 
 * `select_lead`: Specifies the lead (e.g., 'Lead II', 'Lead V1') for R-peak detection. 
     Different leads can provide varying levels of clarity for these features. 
@@ -62,11 +62,11 @@ ecg_aligned_80hz = normalizer.transform(ecg)
 
 * `neurokit_method`: Chooses the algorithm for R-peak detection from the 
     NeuroKit package. Different algorithms may offer varying performance 
-    based on the ECG signal characteristics.
+    based on the ECG signal characteristics. Default is 'neurokit'.
 
 * `correct_artifacts`: If set to True, artifact correction is applied 
     exclusively for R-peak detections, enhancing the accuracy of peak
-    identification in noisy signals.
+    identification in noisy signals. Default is True.
 
 * `scale_method`: Selects the scaling method from options like 'resampling' 
     or 'hrc'. This choice dictates the interval used for resampling
@@ -77,10 +77,16 @@ ecg_aligned_80hz = normalizer.transform(ecg)
     set to True, the problematic ECG is excluded from the dataset. If False, 
     the original, unscaled ECG signal is returned instead. Default is False.
 
-* `median_beat`: Calculates the median from a set of aligned beats 
-    and returns a single, representative beat.
+* `agg_beat`: Calculates the aggregated beat from a set of aligned beats 
+    and returns a single, representative beat if using 'mean' or 'median'.
+    'list' returns the additional dimension of aligned beats without per-lead
+    aggregation. 'none' disables any aggregation and returns as a time-series.
+    Also works with a lambda function, such as 'np.std'. Default is 'none'.
 
-* `silent`: Disable all warnings. Default True.
+* `detrend`: Detrend each beat individually using the robust median of slopes.
+    This is only computed if using `agg_beat`. Default is True.
+
+* `silent`: Disable all warnings. Default is True.
 
 ## Citation
 Please use the following citation:

pyproject.toml

@@ -11,16 +11,16 @@ requires = [
 
 [project]
 name='rlign'
-version='1.0.post2'
+version='1.1'
 description='Beat normalization for ECG data.'
 readme = "README.md"
-requires-python = ">=3.11"
+requires-python = ">=3.10"
 authors=[
     {name="Lucas Bickmann"},
     {name="Lucas Plagwitz"}
 ]
 dependencies = [
-    'neurokit2>=0.2.7',
+    'neurokit2>=0.2.10',
     'numpy>=1.24.2',
     'scipy>=1.12.0',
     'pandas>=2.2.0',