Python Interface with Nanobind (#99)

Summary cherry-picking the squashed messages:

* Nanobind extension

* Basic test and example.

* CI workflow.

* Update extension.

.github/workflows/nanobind.yml

@@ -0,0 +1,37 @@
+name: Nanobind
+
+on:
+  # TODO probably change/add main later. Ah, perhaps this wf can be part of linux.yml?
+  push:
+    branches: [ "nanobind" ]
+  # pull_request:
+    # branches: [ ]
+
+jobs:
+  build:
+    name: "Build Python interface"
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Python setup
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.11.9'
+
+    - name: Install dependencies
+      run: |
+        sudo apt-get install -y libarpack2-dev libcxxopts-dev libeigen3-dev libfmt-dev python3.11-dev 
+        python -m pip install nanobind numpy
+
+    - name: Configure
+      run: cmake -B ${{github.workspace}}/build -DBUILD_NANOBIND=ON
+
+    - 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

CMakeLists.txt

@@ -123,8 +123,12 @@ if (MSVC)
 	set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /bigobj")
 endif()
 
-if (NOT CMAKE_BUILD_TYPE)
-	set(CMAKE_BUILD_TYPE Release)
+# Part of nanobind's setting up the build system, configuring optimized build
+# unless otherwise specified, to avoid slow binding code and large binaries.
+# https://nanobind.readthedocs.io/en/latest/building.html#preliminaries
+if (NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
+	set(CMAKE_BUILD_TYPE Release CACHE STRING "Choose the type of build." FORCE)
+	set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release" "MinSizeRel" "RelWithDebInfo")
 endif()
 
 if (CMAKE_BUILD_TYPE MATCHES Debug)
@@ -164,6 +168,69 @@ if (BUILD_TESTS)
 	endforeach()
 endif()
 
+option(BUILD_NANOBIND "Build nanobind Python extension" OFF)
+
+# https://nanobind.readthedocs.io/en/latest/building.html
+# TODO for faster nanobind build, I tried removing the
+# add_executable tapkee and that quickly didn't work. It would
+# be nice if it could be done without requiring a new option
+# BUILD_CLI, or so, maybe if there's a CMake command to
+# configure not building tapkee inside the if BUILD_NANOBIND.
+if (BUILD_NANOBIND)
+	message(STATUS "Detecting and configuring nanobind")
+	find_package(Python COMPONENTS Interpreter Development.Module REQUIRED)
+	# Detect the installed nanobind package and import it into CMake
+	execute_process(
+		COMMAND "${Python_EXECUTABLE}" -m nanobind --cmake_dir
+		OUTPUT_VARIABLE NB_DIR OUTPUT_STRIP_TRAILING_WHITESPACE
+		ERROR_VARIABLE NB_DIR)
+	list(APPEND CMAKE_PREFIX_PATH "${NB_DIR}")
+	find_package(nanobind CONFIG REQUIRED)
+
+	# Build extension (the library that'll be imported from the Python interpreter)
+	include_directories("${TAPKEE_SRC_DIR}") # about TODO in nanobind_extension.cpp including src/utils.hpp
+	nanobind_add_module(pytapkee src/python/nanobind_extension.cpp) # TODO fix paths.
+	target_link_libraries(pytapkee PRIVATE "${EIGEN3_LIBRARY_TO_LINK}")
+	target_link_libraries(pytapkee PRIVATE arpack) # TODO ARPACK guard; TODO without ARPACK(?)
+	target_link_libraries(pytapkee PRIVATE "${FMT_LIBRARY_TO_LINK}")
+
+	# Rename so that it can be imported as tapkee iso pytapkee.
+	# TODO can this go into a separate CMake file?
+	add_custom_command(TARGET pytapkee POST_BUILD
+		COMMAND ${CMAKE_COMMAND} -P ${CMAKE_BINARY_DIR}/rename_pytapkee.cmake
+		COMMENT "Renaming nanobind's extension pytapkee*.so to tapkee*.so")
+	# Create the custom script to rename the file
+	file(WRITE ${CMAKE_BINARY_DIR}/rename_pytapkee.cmake
+		" # Find the file that starts with 'pytapkee' and ends with '.so' in the lib directory
+file(GLOB PYLIBRARY_FILE \"${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/pytapkee*.so\")
+
+# Ensure exactly one file is found
+list(LENGTH PYLIBRARY_FILE FILE_COUNT)
+if(NOT FILE_COUNT EQUAL 1)
+	message(FATAL_ERROR \"Expected exactly one file starting with 'pytapkee' in lib, but found \${FILE_COUNT}\")
+endif()
+
+# Get the first (and only) matched file
+list(GET PYLIBRARY_FILE 0 SOURCE_FILE)
+
+# Extract the filename from the full path
+get_filename_component(FILENAME \${SOURCE_FILE} NAME)
+
+string(REPLACE \"pytapkee\" \"tapkee\" DEST_FILENAME \${FILENAME})
+
+# Construct the full destination path
+set(DEST_FILE \"${CMAKE_LIBRARY_OUTPUT_DIRECTORY}/\${DEST_FILENAME}\")
+
+file(RENAME \${SOURCE_FILE} \${DEST_FILE})
+
+if(EXISTS \${DEST_FILE} AND NOT EXISTS \${SOURCE_FILE})
+	message(STATUS \"File renamed from \${SOURCE_FILE} to \${DEST_FILE}\")
+else()
+	message(FATAL_ERROR \"Error renaming file from \${SOURCE_FILE} to \${DEST_FILE}\")
+endif()")
+  message(STATUS "Detecting and configuring nanobind - done")
+endif()
+
 export(
 	TARGETS tapkee_library
 	NAMESPACE tapkee::

examples/go.py

@@ -8,55 +8,25 @@
 import tempfile
 
 import numpy as np
-import matplotlib.pyplot as plt
-from mpl_toolkits.mplot3d import Axes3D
-
-def generate_data(type, N=1000, random_state=None):
-	rng = np.random.RandomState(random_state)
-	if type=='swissroll':
-		tt = np.array((3*np.pi/2)*(1+2*rng.rand(N)))
-		height = np.array((rng.rand(N)-0.5))
-		X = np.array([tt*np.cos(tt), 10*height, tt*np.sin(tt)])
-		return X, tt
-	if type=='scurve':
-		tt = np.array((3*np.pi*(rng.rand(N)-0.5)))
-		height = np.array((rng.rand(N)-0.5))
-		X = np.array([np.sin(tt), 10*height, np.sign(tt)*(np.cos(tt)-1)])
-		return X, tt
-	if type=='helix':
-		tt = np.linspace(1,N,N).T / N
-		tt = tt*2*np.pi
-		X = np.r_[[(2+np.cos(8*tt))*np.cos(tt)],
-			[(2+np.cos(8*tt))*np.sin(tt)],
-			[np.sin(8*tt)]]
-		return X, tt
-	if type=='twinpeaks':
-		X = rng.uniform(-1, 1, size=(N, 2))
-		tt = np.sin(np.pi * X[:, 0]) * np.tanh(X[:, 1])
-		tt += 0.1 * rng.normal(size=tt.shape)
-		X = np.vstack([X.T, tt])
-		return X, tt
-	if type=='klein':
-		u = rng.uniform(0, 2 * np.pi, N)
-		v = rng.uniform(0, 2 * np.pi, N)
-		x = (2 + np.cos(u / 2) * np.sin(v) - np.sin(u / 2) * np.sin(2 * v)) * np.cos(u)
-		y = (2 + np.cos(u / 2) * np.sin(v) - np.sin(u / 2) * np.sin(2 * v)) * np.sin(u)
-		z = np.sin(u / 2) * np.sin(v) + np.cos(u / 2) * np.sin(2 * v)
-
-		noise = 0.01
-		x += noise * rng.normal(size=x.shape)
-		y += noise * rng.normal(size=y.shape)
-		z += noise * rng.normal(size=z.shape)
-		return np.vstack((x, y, z)), u
-
-	raise Exception('Dataset is not supported')
-
+from utils import generate_data, plot
+
+supported_methods = {
+	'lle': 'Locally Linear Embedding',
+	'ltsa': 'Local Tangent Space Alignment',
+	'isomap': 'Isomap',
+	'mds': 'Multidimensional Scaling',
+	'pca': 'Principal Component Analysis',
+	'kpca': 'Kernel Principal Component Analysis',
+	't-sne': 't-distributed Stochastic Neighborhood Embedding',
+	'dm': 'Diffusion Map',
+}
 
 def embed(data,method):
 	input_file = tempfile.NamedTemporaryFile(prefix='tapkee_input')
 	output_file = tempfile.NamedTemporaryFile(prefix='tapkee_output')
 	np.savetxt(input_file.name, data.T,delimiter=',')
 	tapkee_binary = 'bin/tapkee'
+
 	runner_string = '%s -i %s -o %s -m %s -k 20 --precompute --debug --verbose --transpose-output --benchmark' % (
 		tapkee_binary, input_file.name, output_file.name, method
 	)
@@ -71,59 +41,9 @@ def embed(data,method):
 	else:
 		used_method = ''
 
-
 	embedded_data = np.loadtxt(output_file, delimiter=',')
 	return embedded_data, used_method
 
-def plot(data, embedded_data, colors='m', method=None):
-	fig = plt.figure()
-	fig.set_facecolor('white')
-
-	ax_original = fig.add_subplot(121, projection='3d')
-	scatter_original = ax_original.scatter(data[0], data[1], data[2], c=colors, cmap=plt.cm.Spectral, s=5, picker=True)
-	plt.axis('tight')
-	plt.axis('off')
-	plt.title('Original', fontsize=9)
-
-	ax_embedding = fig.add_subplot(122)
-	scatter_embedding = ax_embedding.scatter(embedded_data[0], embedded_data[1], c=colors, cmap=plt.cm.Spectral, s=5, picker=True)
-	plt.axis('tight')
-	plt.axis('off')
-	plt.title('Embedding' + (' with ' + method) if method else '', fontsize=9, wrap=True)
-
-	highlighted_points = []  # To store highlighted points
-
-	# Function to highlight points on both plots
-	def highlight(index):
-		# Reset previous highlighted points
-		for point in highlighted_points:
-			point.remove()
-		highlighted_points.clear()
-
-		# Highlight the current point on both scatter plots
-		point1 = ax_original.scatter([data[0][index]], [data[1][index]], [data[2][index]], color='white', s=25, edgecolor='black', zorder=3)
-		point2 = ax_embedding.scatter([embedded_data[0][index]], [embedded_data[1][index]], color='white', s=25, edgecolor='black', zorder=3)
-		highlighted_points.append(point1)
-		highlighted_points.append(point2)
-		fig.canvas.draw_idle()
-
-	# Event handler for mouse motion
-	def on_hover(event):
-		if event.inaxes == ax_original:
-			cont, ind = scatter_original.contains(event)
-		elif event.inaxes == ax_embedding:
-			cont, ind = scatter_embedding.contains(event)
-		else:
-			return
-
-		if cont:
-			index = ind['ind'][0]
-			highlight(index)
-
-	fig.canvas.mpl_connect('motion_notify_event', on_hover)
-
-	plt.show()
-
 if __name__ == "__main__":
 	import argparse
 	parser = argparse.ArgumentParser(description='Graphical example of dimension reduction with Tapkee.')

examples/nanobind.py

@@ -0,0 +1,10 @@
+import lib.tapkee as tapkee
+from utils import generate_data, plot
+
+if __name__=='__main__':
+    parameters = tapkee.ParametersSet()
+    method = tapkee.parse_reduction_method('lle')
+    parameters.add(tapkee.Parameter.create('dimension reduction method', method))
+    data, colors = generate_data('swissroll')
+    embedded_data = tapkee.withParameters(parameters).embedUsing(data).embedding
+    plot(data, embedded_data.T, colors)

examples/utils.py

@@ -0,0 +1,91 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+def generate_data(type, N=1000, random_state=None):
+	rng = np.random.RandomState(random_state)
+	if type=='swissroll':
+		tt = np.array((3*np.pi/2)*(1+2*rng.rand(N)))
+		height = np.array((rng.rand(N)-0.5))
+		X = np.array([tt*np.cos(tt), 10*height, tt*np.sin(tt)])
+		return X, tt
+	if type=='scurve':
+		tt = np.array((3*np.pi*(rng.rand(N)-0.5)))
+		height = np.array((rng.rand(N)-0.5))
+		X = np.array([np.sin(tt), 10*height, np.sign(tt)*(np.cos(tt)-1)])
+		return X, tt
+	if type=='helix':
+		tt = np.linspace(1,N,N).T / N
+		tt = tt*2*np.pi
+		X = np.r_[[(2+np.cos(8*tt))*np.cos(tt)],
+			[(2+np.cos(8*tt))*np.sin(tt)],
+			[np.sin(8*tt)]]
+		return X, tt
+	if type=='twinpeaks':
+		X = rng.uniform(-1, 1, size=(N, 2))
+		tt = np.sin(np.pi * X[:, 0]) * np.tanh(X[:, 1])
+		tt += 0.1 * rng.normal(size=tt.shape)
+		X = np.vstack([X.T, tt])
+		return X, tt
+	if type=='klein':
+		u = rng.uniform(0, 2 * np.pi, N)
+		v = rng.uniform(0, 2 * np.pi, N)
+		x = (2 + np.cos(u / 2) * np.sin(v) - np.sin(u / 2) * np.sin(2 * v)) * np.cos(u)
+		y = (2 + np.cos(u / 2) * np.sin(v) - np.sin(u / 2) * np.sin(2 * v)) * np.sin(u)
+		z = np.sin(u / 2) * np.sin(v) + np.cos(u / 2) * np.sin(2 * v)
+
+		noise = 0.01
+		x += noise * rng.normal(size=x.shape)
+		y += noise * rng.normal(size=y.shape)
+		z += noise * rng.normal(size=z.shape)
+		return np.vstack((x, y, z)), u
+
+	raise Exception('Dataset is not supported')
+
+def plot(data, embedded_data, colors='m', method=None):
+	fig = plt.figure()
+	fig.set_facecolor('white')
+
+	ax_original = fig.add_subplot(121, projection='3d')
+	scatter_original = ax_original.scatter(data[0], data[1], data[2], c=colors, cmap=plt.cm.Spectral, s=5, picker=True)
+	plt.axis('tight')
+	plt.axis('off')
+	plt.title('Original', fontsize=9)
+
+	ax_embedding = fig.add_subplot(122)
+	scatter_embedding = ax_embedding.scatter(embedded_data[0], embedded_data[1], c=colors, cmap=plt.cm.Spectral, s=5, picker=True)
+	plt.axis('tight')
+	plt.axis('off')
+	plt.title('Embedding' + (' with ' + method) if method else '', fontsize=9, wrap=True)
+
+	highlighted_points = []  # To store highlighted points
+
+	# Function to highlight points on both plots
+	def highlight(index):
+		# Reset previous highlighted points
+		for point in highlighted_points:
+			point.remove()
+		highlighted_points.clear()
+
+		# Highlight the current point on both scatter plots
+		point1 = ax_original.scatter([data[0][index]], [data[1][index]], [data[2][index]], color='white', s=25, edgecolor='black', zorder=3)
+		point2 = ax_embedding.scatter([embedded_data[0][index]], [embedded_data[1][index]], color='white', s=25, edgecolor='black', zorder=3)
+		highlighted_points.append(point1)
+		highlighted_points.append(point2)
+		fig.canvas.draw_idle()
+
+	# Event handler for mouse motion
+	def on_hover(event):
+		if event.inaxes == ax_original:
+			cont, ind = scatter_original.contains(event)
+		elif event.inaxes == ax_embedding:
+			cont, ind = scatter_embedding.contains(event)
+		else:
+			return
+
+		if cont:
+			index = ind['ind'][0]
+			highlight(index)
+
+	fig.canvas.mpl_connect('motion_notify_event', on_hover)
+
+	plt.show()

include/stichwort/parameter.hpp

@@ -29,6 +29,7 @@
 
 #include <stichwort/value_keeper.hpp>
 
+#include <functional>
 #include <iostream>
 #include <list>
 #include <map>

include/tapkee/chain_interface.hpp

@@ -420,8 +420,8 @@ class ParametersInitializedState
     ParametersInitializedState(const ParametersSet& that) : parameters(that)
     {
     }
-    ParametersInitializedState(const ParametersInitializedState&);
-    ParametersInitializedState& operator=(const ParametersInitializedState&);
+    ParametersInitializedState(const ParametersInitializedState&) = default;
+    ParametersInitializedState& operator=(const ParametersInitializedState&) = default;
 
     /** Sets kernel callback.
      *

src/cli/util.hpp

@@ -225,6 +225,11 @@ typename Mapping::mapped_type parse_multiple(Mapping mapping, const std::string&
     throw std::logic_error(str);
 }
 
+auto parse_reduction_method(const std::string& str)
+{
+    return parse_multiple(DIMENSION_REDUCTION_METHODS, str);
+}
+
 template <class PairwiseCallback>
 tapkee::DenseMatrix matrix_from_callback(const tapkee::IndexType N, PairwiseCallback callback)
 {