Merge a31c408 into f5c4e77

.coveragerc

@@ -1,3 +1,4 @@
 [run]
+relative_files = True
 branch = True
 omit = */test_*.py

.github/workflows/build.yml

@@ -0,0 +1,55 @@
+name: Build
+
+on:
+  push:
+  pull_request:
+  schedule:
+    - cron: '0 0 1 * *'
+
+jobs:
+
+  build:
+    name: Build for ${{ matrix.python-version }}
+    runs-on: 'ubuntu-latest'
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ['3.7', '3.8', '3.9']
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Python info
+        shell: bash -l {0}
+        run: |
+          which python
+          python --version
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+      - name: Build
+        shell: bash -l {0}
+        run: |
+          python setup.py build
+      - name: Test
+        shell: bash -l {0}
+        run: |
+          pip install pytest pytest-cov
+          pytest --cov=laserchicken --cov-report xml:coverage.xml
+      - name: Coveralls
+        uses: AndreMiras/coveralls-python-action@develop
+        with:
+          parallel: true
+          flag-name: Unit Test
+
+  coveralls_finish:
+    needs: build
+    runs-on: ubuntu-latest
+    steps:
+    - name: Coveralls Finished
+      uses: AndreMiras/coveralls-python-action@develop
+      with:
+        parallel-finished: true

.github/workflows/pypi.yml

@@ -0,0 +1,25 @@
+name: Publish
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v1
+      with:
+        python-version: 3.7
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+        python setup.py bdist_wheel
+    - name: Publish package
+      uses: pypa/gh-action-pypi-publish@master
+      with:
+        user: __token__
+        password: ${{ secrets.PYPI_TOKEN }}

.zenodo.json

@@ -59,7 +59,7 @@
   "license": {
     "id": "Apache-2.0"
   },
-  "publication_date": "2022-05-20",
+  "publication_date": "2022-09-05",
   "title": "Laserchicken: toolkit for ALS point clouds",
-  "version": "0.5.0"
+  "version": "0.6.0"
 }

CHANGELOG.md

@@ -6,6 +6,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
+## 0.6.0 - 2022-09-05
+## Changed:
+- continuous integration moved from travis to GH actions
+- naming of band ratio's modified (symbol "<" dropped from label)
+
+## Added 
+- releases published on PyPI using GH actions
+- checklists included
+
+## Fixed 
+- Fixed import of deprecated `scipy.stats.stats`
+
 ## 0.5.0 - 2022-05-20
 ## Changed:
 - update documentation with table of features

CITATION.cff

@@ -52,7 +52,7 @@ authors:
     family-names: Koma
     given-names: Zsófia
 cff-version: "1.0.3"
-date-released: 2022-05-20
+date-released: 2022-09-05
 doi: "10.5281/zenodo.1219422"
 keywords:
   - "airborne laser scanning"
@@ -62,5 +62,5 @@ keywords:
 license: "Apache-2.0"
 message: "If you use this software, please cite it using these metadata."
 title: "Laserchicken: toolkit for ALS point clouds"
-version: "0.5.0"
+version: "0.6.0"
 ...

README.md

@@ -3,17 +3,18 @@ Please cite the software if you are using it in your scientific publication.
   <img src="https://raw.githubusercontent.com/eEcoLiDAR/laserchicken/master/laserchicken_logo.png" width="500"/>
 </p>
 
-[![Build Status](https://travis-ci.org/eEcoLiDAR/laserchicken.svg?branch=master)](https://travis-ci.org/eEcoLiDAR/laserchicken)
+[![Build Status](https://github.com/eEcoLiDAR/laserchicken/workflows/Build/badge.svg)](https://github.com/eEcoLiDAR/laserchicken/actions)
 [![Codacy Badge](https://api.codacy.com/project/badge/Grade/6e3836750fe14f34ba85e26956e8ef10)](https://www.codacy.com/app/c-meijer/eEcoLiDAR?utm_source=www.github.com&amp;utm_medium=referral&amp;utm_content=eEcoLiDAR/eEcoLiDAR&amp;utm_campaign=Badge_Grade)
-[![Coverage Status](https://coveralls.io/repos/github/eEcoLiDAR/eEcoLiDAR/badge.svg)](https://coveralls.io/github/eEcoLiDAR/eEcoLiDAR)
+[![Coverage Status](https://coveralls.io/repos/github/eEcoLiDAR/laserchicken/badge.svg)](https://coveralls.io/github/eEcoLiDAR/laserchicken)
 [![DOI](https://zenodo.org/badge/95649056.svg)](https://zenodo.org/badge/latestdoi/95649056)
 [![Documentation Status](https://readthedocs.org/projects/laserchicken/badge/?version=latest)](https://laserchicken.readthedocs.io/en/latest/)
+[![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/4524/badge)](https://bestpractices.coreinfrastructure.org/projects/4524)
 
 Toolkit for handling point clouds created using airborne laser scanning (ALS). Find neighboring points in your point cloud and describe them as feature values. Read our [user manual](https://laserchicken.readthedocs.io/) and our (very modest) [tutorial](https://github.com/eEcoLiDAR/laserchicken/blob/master/tutorial.ipynb).
 
 # Installation
 Prerequisites:
-- Python 3.6 or higher
+- Python 3.7 or higher
 - pip
 ```
 pip install laserchicken
@@ -29,7 +30,7 @@ pip install laserchicken
 * Edit Changelog (based on commits in https://github.com/eecolidar/laserchicken/compare/v0.3.2...master)
 * Test if package can be installed with pip (`pip install .`)
 * Create Github release
-* Upload to pypi:  
+* Upload to pypi (now implemented via GitHub Actions):  
 ```python setup.py sdist bdist_wheel```  
 ```python -m twine upload --repository-url https://upload.pypi.org/legacy/ dist/*```  
 (or ```python -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*``` to test first)

laserchicken/_version.txt

@@ -1 +1 @@
-0.5.0
+0.6.0

laserchicken/feature_extractor/band_ratio_feature_extractor.py

@@ -47,10 +47,10 @@ def provides(self):
         """
         name = 'band_ratio_'
         if self.lower_limit is not None:
-            name += str(self.lower_limit) + '<'
+            name += str(self.lower_limit) + '_'
         name += self.data_key
         if self.upper_limit is not None:
-            name += '<' + str(self.upper_limit)
+            name += '_' + str(self.upper_limit)
         return [name]
 
     def extract(self, point_cloud, neighborhoods, target_point_cloud, target_index, volume_description):

laserchicken/feature_extractor/kurtosis_feature_extractor.py

@@ -1,5 +1,5 @@
 import numpy as np
-import scipy.stats.stats as stat
+import scipy.stats as stats
 
 from laserchicken.feature_extractor.base_feature_extractor import FeatureExtractor
 from laserchicken.keys import point
@@ -23,7 +23,7 @@ def extract(self, point_cloud, neighborhoods, target_point_cloud, target_indices
     def _extract_one(self, sourcepc, neighborhood):
         if neighborhood:
             z = sourcepc[point][self.data_key]['data'][neighborhood]
-            kurtosis_z = stat.kurtosis(z)
+            kurtosis_z = stats.kurtosis(z)
         else:
             kurtosis_z = np.NaN
         return kurtosis_z

laserchicken/feature_extractor/percentile_feature_extractor.py

@@ -1,4 +1,4 @@
-import scipy.stats.stats as stats
+import scipy.stats as stats
 
 from laserchicken.feature_extractor.base_feature_extractor import FeatureExtractor
 from laserchicken.keys import point

laserchicken/feature_extractor/skew_feature_extractor.py

@@ -1,5 +1,5 @@
 import numpy as np
-import scipy.stats.stats as stat
+import scipy.stats as stats
 
 from laserchicken.feature_extractor.base_feature_extractor import FeatureExtractor
 from laserchicken.keys import point
@@ -23,7 +23,7 @@ def extract(self, point_cloud, neighborhoods, target_point_cloud, target_indices
     def _extract_one(self, point_cloud, neighborhood):
         if neighborhood:
             source_data = point_cloud[point][self.data_key]['data'][neighborhood]
-            skew = stat.skew(source_data)
+            skew = stats.skew(source_data)
         else:
             skew = np.NaN
         return skew

laserchicken/feature_extractor/test_band_ratio_feature_extractor.py

@@ -86,22 +86,22 @@ def test_cell_volume(self):
         assert_expected_ratio(volume=InfiniteCylinder(5))
 
     def test_provides_simple(self):
-        self.assertEqual(['band_ratio_6<z<20'], BandRatioFeatureExtractor(6, 20).provides())
+        self.assertEqual(['band_ratio_6_z_20'], BandRatioFeatureExtractor(6, 20).provides())
 
     def test_provides_with_only_upper_limit(self):
-        self.assertEqual(['band_ratio_z<20'], BandRatioFeatureExtractor(None, 20).provides())
+        self.assertEqual(['band_ratio_z_20'], BandRatioFeatureExtractor(None, 20).provides())
 
     def test_provides_with_only_lower_limit(self):
-        self.assertEqual(['band_ratio_20<z'], BandRatioFeatureExtractor(20, None).provides())
+        self.assertEqual(['band_ratio_20_z'], BandRatioFeatureExtractor(20, None).provides())
 
     def test_provides_with_zero_lower_limit(self):
-        self.assertEqual(['band_ratio_0<z'], BandRatioFeatureExtractor(0, None).provides())
+        self.assertEqual(['band_ratio_0_z'], BandRatioFeatureExtractor(0, None).provides())
 
     def test_provides_with_zero_upper_limit(self):
-        self.assertEqual(['band_ratio_z<0'], BandRatioFeatureExtractor(None, 0).provides())
+        self.assertEqual(['band_ratio_z_0'], BandRatioFeatureExtractor(None, 0).provides())
 
     def test_provides_with_data_key(self):
-        self.assertEqual(['band_ratio_1<normalized_height<3'],
+        self.assertEqual(['band_ratio_1_normalized_height_3'],
                          BandRatioFeatureExtractor(1, 3, data_key=keys.normalized_height).provides())
 
 

laserchicken/feature_extractor/test_skew_z_feature_extractor.py

@@ -38,7 +38,7 @@ def test_use_norm_z(self):
         point_cloud = create_point_cloud(x, y, z, normalized_z=normalized_z)
         neighborhood = [[0, 1, 2]]
 
-        skew = self.extractor.extract(point_cloud, [neighborhood], None, None, None)[0]
+        skew = self.extractor.extract(point_cloud, neighborhood, None, None, None)[0]
 
         self.assertGreater(skew, 0.1)
 

laserchicken/test_integration_tests.py

@@ -48,7 +48,7 @@ def test_tutorial_once(self):
 
         cylinder = build_volume("infinite cylinder", radius=5)
         neighborhoods = compute_neighborhoods(point_cloud, targets, cylinder)
-        compute_features(point_cloud, neighborhoods, targets, ['band_ratio_1<normalized_height<2'], cylinder)
+        compute_features(point_cloud, neighborhoods, targets, ['band_ratio_1_normalized_height_2'], cylinder)
 
         from laserchicken import export
         export(point_cloud, 'my_output.ply')