remove some python files

Author: dance858

CMakeLists.txt

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+cmake_minimum_required(VERSION 3.15)
+project(DNLP_Diff_Engine C)
+set(CMAKE_C_STANDARD 99)
+
+set(DIFF_ENGINE_VERSION_MAJOR 0)
+set(DIFF_ENGINE_VERSION_MINOR 0)
+set(DIFF_ENGINE_VERSION_PATCH 1)
+set(DIFF_ENGINE_VERSION "${DIFF_ENGINE_VERSION_MAJOR}.${DIFF_ENGINE_VERSION_MINOR}.${DIFF_ENGINE_VERSION_PATCH}")
+add_compile_definitions(DIFF_ENGINE_VERSION="${DIFF_ENGINE_VERSION}")
+
+message(STATUS "Configuring DNLP Differentiation Engine (version ${DIFF_ENGINE_VERSION})")
+
+
+#Set default build type to Release if not specified
+if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
+  message(STATUS "Setting build type to 'Release' as none was specified.")
+  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")
+else()
+  message(STATUS "Build type: ${CMAKE_BUILD_TYPE}")
+endif()
+
+# Warning flags (always enabled)
+add_compile_options(
+    -Wall                  # Enable most warnings
+    -Wextra                # Extra warnings
+    -Wpedantic             # Strict ISO C compliance
+    -Wshadow               # Warn about variable shadowing
+    -Wformat=2             # Extra format string checks
+    -Wcast-qual            # Warn about cast that removes qualifiers
+    -Wcast-align           # Warn about pointer cast alignment issues
+    -Wunused               # Warn about unused variables/functions
+    -Wdouble-promotion     # Warn about float->double promotion
+    -Wnull-dereference     # Warn about null pointer dereference
+)
+
+# Include directories
+include_directories(${PROJECT_SOURCE_DIR}/include)
+
+# Source files - automatically gather all .c files from src/
+file(GLOB_RECURSE SOURCES "src/*.c")
+
+
+# Create core library
+add_library(dnlp_diff ${SOURCES})
+target_link_libraries(dnlp_diff m)
+
+# Config-specific compile options
+target_compile_options(dnlp_diff PRIVATE
+  $<$<CONFIG:Debug>:-g -O0>
+  $<$<CONFIG:Release>:-O3 -DNDEBUG>
+  $<$<CONFIG:RelWithDebInfo>:-O2 -g -DNDEBUG>
+  $<$<CONFIG:MinSizeRel>:-Os -DNDEBUG>
+)
+
+# This is needed for clock_gettime on Linux without compiler extensions
+if(CMAKE_SYSTEM_NAME STREQUAL "Linux")
+    add_compile_definitions(_POSIX_C_SOURCE=200809L)
+endif()
+
+# Enable position-independent code for shared library compatibility
+set_property(TARGET dnlp_diff PROPERTY POSITION_INDEPENDENT_CODE ON)
+
+# =============================================================================
+# Python bindings (built when using scikit-build-core)
+# =============================================================================
+if(SKBUILD)
+    find_package(Python3 REQUIRED COMPONENTS Interpreter Development.Module NumPy)
+
+    # Create Python extension module
+    Python3_add_library(_core MODULE python/bindings.c)
+    target_include_directories(_core PRIVATE
+        ${PROJECT_SOURCE_DIR}/include
+        ${PROJECT_SOURCE_DIR}/python
+        ${Python3_NumPy_INCLUDE_DIRS}
+    )
+    target_link_libraries(_core PRIVATE dnlp_diff)
+
+    # Install to the package directory
+    install(TARGETS _core LIBRARY DESTINATION dnlp_diff_engine)
+endif()
+
+# =============================================================================
+# C tests (only for standalone builds)
+# =============================================================================
+if(NOT SKBUILD)
+    include_directories(${PROJECT_SOURCE_DIR}/tests)
+    enable_testing()
+
+    add_executable(all_tests
+        tests/all_tests.c
+        tests/test_helpers.c
+    )
+    target_link_libraries(all_tests dnlp_diff)
+    add_test(NAME AllTests COMMAND all_tests)
+endif()

tests/utils/multiply_test.py

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+import numpy as np
+import scipy.sparse as sp
+
+# test 1
+A = np.array([[1.0, 0.0, 2.0], [0.0, 3.0, 0.0], [4.0, 0.0, 5.0], [0.0, 6.0, 0.0]])
+B = np.array([[1.0, 0.0, 4], [0.0, 2.0, 7], [3.0, 0.0, 2], [0.0, 4.0, -1]])
+w = np.array([1.0, 2.0, 3.0, 4.0])
+H = A.T @ np.diag(w) @ B + B.T @ np.diag(w) @ A
+print(H)
+H_csr = sp.csr_matrix(H)
+print("H in CSR format:")
+print("data:", H_csr.data)
+print("indices:", H_csr.indices)
+print("indptr:", H_csr.indptr)
+
+# test 2
+m = 5
+n = 10
+density = 0.2
+A = sp.random(m, n, density=density, format="csr", data_rvs=np.random.randn)
+B = sp.random(m, n, density=density, format="csr", data_rvs=np.random.randn)
+w = np.random.rand(m)
+H = A.T @ sp.diags(w) @ B + B.T @ sp.diags(w) @ A
+H = H.tocsr()
+print("Random sparse H in CSR format:")
+print("data:", H.data)
+print("indices:", H.indices)
+print("indptr:", H.indptr)
+
+print("A in csr:")
+print("data:", A.data)
+print("indices:", A.indices)
+print("indptr:", A.indptr)
+
+print("B in csr:")
+print("data:", B.data)
+print("indices:", B.indices)
+print("indptr:", B.indptr)
+
+print("w:", w)

tests/utils/python_test.py

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+import scipy.sparse as sp
+import numpy as np
+
+np.random.seed(42)
+m = 10
+n = 15
+# density = 0.1
+# A = sp.random(m, n, density=density, format="csc", dtype=float)
+
+Ap = np.array([0, 1, 1, 1, 1, 4, 5, 6, 7, 8, 9, 11, 11, 11, 13, 15])
+Ai = np.array([5, 0, 6, 9, 0, 5, 1, 3, 6, 0, 6, 3, 6, 6, 8])
+Ax = np.random.randint(1, 10, size=len(Ai))
+d = np.random.randint(1, 10, size=m)
+A = sp.csc_matrix((Ax, Ai, Ap), shape=(m, n))
+
+
+C = A.T @ sp.diags(d) @ A
+
+C.sort_indices()
+
+import pdb
+
+pdb.set_trace()

tests/utils/python_test_csr_to_csc.py

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+import numpy as np
+import scipy.sparse as sp
+
+m = 20
+n = 30
+density = 0.2
+A = sp.random(m, n, density=density, format="csr", dtype=float)
+A.data = np.random.randint(1, 10, size=A.nnz)
+
+Ap = A.indptr
+Ai = A.indices
+Ax = A.data
+
+print("CSR matrix A:")
+print("Ap:", Ap)
+print("Ai:", Ai)
+print("Ax:", Ax)
+print("Annz:", A.nnz)
+
+A_csc = A.tocsc()
+
+Cp = A_csc.indptr
+Ci = A_csc.indices
+Cx = A_csc.data
+
+print("CSC matrix A_csc:")
+print("Cp:", Cp)
+print("Ci:", Ci)
+print("Cx:", Cx)
+print("len(Ci):", len(Ci))
+print("len(Cp):", len(Cp))