Add tests for example data to CI

CHANGELOG.md

@@ -1,6 +1,7 @@
 ## [1.16.2] - 2019-??-??
 ### Added
 - Allow loading from already opened file objects, e.g. in-memory files or network streams ([#51](https://github.com/xdf-modules/xdf-python/pull/51) by [Tristan Stenner](https://github.com/tstenner)).
+- Add CI tests with example data ([#49](https://github.com/xdf-modules/xdf-Python/pull/49) by [Clemens Brunner](https://github.com/cbrnr)).
 
 ### Fixed
 - Compare nominal to effective sampling rates only for regularly sampled streams ([#47](https://github.com/xdf-modules/xdf-Python/pull/47) by [Clemens Brunner](https://github.com/cbrnr)).

azure-pipelines.yml

@@ -31,16 +31,20 @@ steps:
 - script: |
     python -m pip install --upgrade pip wheel twine setuptools_scm
     pip install numpy
-  displayName: 'Install Dependencies'
+  displayName: 'Install dependencies'
+
+- script: |
+    git clone --depth 1 https://github.com/xdf-modules/example-files.git
+  displayName: 'Download test data'
 
 - script: |
     pip install pytest pytest-azurepipelines
     pytest
-  displayName: 'pytest'
+  displayName: 'Test'
 
 - script: |
     python setup.py sdist bdist_wheel
-  displayName: 'Build Wheel'
+  displayName: 'Build wheel'
 
 - task: TwineAuthenticate@0
   condition: and(succeeded(), contains(variables['Build.SourceBranch'], 'refs/tags/'))

pyxdf/test/test_data.py

@@ -0,0 +1,68 @@
+from pathlib import Path
+from pyxdf import load_xdf
+import pytest
+import numpy as np
+
+
+# requires git clone https://github.com/xdf-modules/example-files.git
+# into the root xdf-python folder
+path = Path("example-files")
+extensions = ["*.xdf", "*.xdfz", "*.xdf.gz"]
+files = []
+for ext in extensions:
+    files.extend(path.glob(ext))
+files = [str(file) for file in files]
+
+
+@pytest.mark.parametrize("file", files)
+def test_load_file(file):
+    streams, header = load_xdf(file)
+
+    if file.endswith("minimal.xdf"):
+        assert header["info"]["version"][0] == "1.0"
+
+        assert len(streams) == 2
+        assert streams[0]["info"]["name"][0] == "SendDataC"
+        assert streams[0]["info"]["type"][0] == "EEG"
+        assert streams[0]["info"]["channel_count"][0] == "3"
+        assert streams[0]["info"]["nominal_srate"][0] == "10"
+        assert streams[0]["info"]["channel_format"][0] == "int16"
+        assert streams[0]["info"]["stream_id"] == 0
+
+        s = np.array([[192, 255, 238],
+                      [12, 22, 32],
+                      [13, 23, 33],
+                      [14, 24, 34],
+                      [15, 25, 35],
+                      [12, 22, 32],
+                      [13, 23, 33],
+                      [14, 24, 34],
+                      [15, 25, 35]], dtype=np.int16)
+        t = np.array([5., 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8])
+        np.testing.assert_array_equal(streams[0]["time_series"], s)
+        np.testing.assert_array_almost_equal(streams[0]["time_stamps"], t)
+
+        assert streams[1]["info"]["name"][0] == "SendDataString"
+        assert streams[1]["info"]["type"][0] == "StringMarker"
+        assert streams[1]["info"]["channel_count"][0] == "1"
+        assert streams[1]["info"]["nominal_srate"][0] == "10"
+        assert streams[1]["info"]["channel_format"][0] == "string"
+        assert streams[1]["info"]["stream_id"] == 0x02C0FFEE
+
+        s = [['<?xml version="1.0"?><info><writer>LabRecorder xdfwriter'
+              '</writer><first_timestamp>5.1</first_timestamp><last_timestamp>'
+              '5.9</last_timestamp><sample_count>9</sample_count>'
+              '<clock_offsets><offset><time>50979.76</time><value>-.01</value>'
+              '</offset><offset><time>50979.86</time><value>-.02</value>'
+              '</offset></clock_offsets></info>'],
+             ['Hello'],
+             ['World'],
+             ['from'],
+             ['LSL'],
+             ['Hello'],
+             ['World'],
+             ['from'],
+             ['LSL']]
+        t = np.array([5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9])
+        assert streams[1]["time_series"] == s
+        np.testing.assert_array_almost_equal(streams[1]["time_stamps"], t)