Integrate basic test.

.github/workflows/nanobind.yml

@@ -31,3 +31,7 @@ jobs:
     - name: Build
       # TODO there are A LOT of warnings in the logs from nanobind (-pedantic, -Wshadow).
       run: cmake --build ${{github.workspace}}/build
+
+    - name: Test
+      working-directory: ${{github.workspace}}
+      run: PYTHONPATH=. python test/test_nanobind_extension.py

examples/nanobind.py

@@ -1,23 +1,9 @@
-#!/usr/bin/python3.12
-
 import lib.tapkee as tapkee
-import numpy as np
 from utils import generate_data, plot
 
-def parse_reduction_method(method_name: str):
-    return tapkee.parse_reduction_method(method_name)
-
-def test_exception_unknown_method():
-    try:
-        parse_reduction_method('unknown')
-        assert(False)
-    except:
-        pass
-
 if __name__=='__main__':
-    test_exception_unknown_method()
     parameters = tapkee.ParametersSet()
-    method = parse_reduction_method('lle')
+    method = tapkee.parse_reduction_method('lle')
     parameters.add(tapkee.Parameter.create('dimension reduction method', method))
     data, colors = generate_data('swissroll')
     embedded_data = tapkee.initialize().withParameters(parameters).embedUsing(data).embedding

src/python/nanobind_extension.cpp

@@ -43,5 +43,6 @@ NB_MODULE(tapkee, m) {
         .def_rw("name", &DimensionReductionMethod::name_);
 
     nb::class_<Parameter>(m, "Parameter")
-        .def_static("create", &Parameter::create<DimensionReductionMethod>);
+        .def_static("create", &Parameter::create<DimensionReductionMethod>)
+        .def_static("create", &Parameter::create<int>);
 }

test/test_nanobind_extension.py

@@ -0,0 +1,21 @@
+import lib.tapkee as tapkee
+import numpy as np
+
+def test_exception_unknown_method():
+    try:
+        tapkee.parse_reduction_method('unknown')
+        assert(False)
+    except:
+        pass
+
+if __name__=='__main__':
+    test_exception_unknown_method()
+    parameters = tapkee.ParametersSet()
+    method = tapkee.parse_reduction_method('spe')
+    assert(method.name == 'Stochastic Proximity Embedding (SPE)')
+    parameters.add(tapkee.Parameter.create('dimension reduction method', method))
+    target_dimension = 2
+    parameters.add(tapkee.Parameter.create('target dimension', target_dimension))
+    data = np.random.randn(124, 3)
+    embedded_data = tapkee.initialize().withParameters(parameters).embedUsing(data).embedding
+    assert(embedded_data.shape == tuple([data.shape[1], target_dimension]))