merge modificaitons

Author: mohanchen

.github/workflows/build_test_cmake.yml

@@ -17,10 +17,10 @@ jobs:
             name: "Build with Intel toolchain"
 
           - tag: gnu
-            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_MLKEDF=1 -DENABLE_LIBRI=1"
+            build_args: "-DENABLE_LIBXC=1 -DDENABLE_MLALGO=1 -DENABLE_LIBRI=1"
             name: "Build extra components with GNU toolchain"
           - tag: intel
-            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_MLKEDF=1 -DENABLE_LIBRI=1"
+            build_args: "-DENABLE_LIBXC=1 -DENABLE_MLALGO=1 -DENABLE_LIBRI=1"
             name: "Build extra components with Intel toolchain"
 
           - tag: cuda

.github/workflows/coverage.yml

@@ -18,7 +18,7 @@ jobs:
           apt update && apt install -y lcov gpg curl jq ca-certificates
       - name: Building
         run: |
-          cmake -B build -DENABLE_COVERAGE=ON -DBUILD_TESTING=ON -DENABLE_DEEPKS=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON
+          cmake -B build -DENABLE_COVERAGE=ON -DBUILD_TESTING=ON -DENABLE_MLALGO=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON
           cmake --build build -j`nproc`
           cmake --install build
       - name: Testing

.github/workflows/dynamic.yml

@@ -16,7 +16,7 @@ jobs:
         uses: actions/checkout@v4
       - name: Building
         run: |
-          cmake -B build -DENABLE_ASAN=1 -DENABLE_DEEPKS=1 -DENABLE_LIBXC=1
+          cmake -B build -DENABLE_ASAN=1 -DENABLE_MLALGO=1 -DENABLE_LIBXC=1
           cmake --build build -j8
           cmake --install build
       - name: Testing

.github/workflows/test.yml

@@ -31,7 +31,7 @@ jobs:
 
       - name: Configure
         run: |
-          cmake -B build -DBUILD_TESTING=ON -DENABLE_DEEPKS=ON -DENABLE_MLKEDF=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON  -DCMAKE_EXPORT_COMPILE_COMMANDS=1 -DENABLE_FLOAT_FFTW=ON
+          cmake -B build -DBUILD_TESTING=ON -DENABLE_MLALGO=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON  -DCMAKE_EXPORT_COMPILE_COMMANDS=1 -DENABLE_FLOAT_FFTW=ON
 
 # Temporarily removed because no one maintains this now.
 # And it will break the CI test workflow.

CMakeLists.txt

@@ -21,8 +21,11 @@ option(USE_DSP "Enable DSP" OFF)
 option(USE_ABACUS_LIBM "Build libmath from source to speed up" OFF)
 option(ENABLE_LIBXC "Enable using the LibXC package" OFF)
 option(ENABLE_FLOAT_FFTW "Enable using single-precision FFTW library." OFF)
-option(ENABLE_DEEPKS "Enable the DeePKS algorithm" OFF)
-option(ENABLE_MLKEDF "Enable the Machine-Learning-based KEDF for OFDFT" OFF)
+
+# option(ENABLE_DEEPKS "Enable the DeePKS algorithm" OFF)
+# option(ENABLE_MLKEDF "Enable the Machine-Learning-based KEDF for OFDFT" OFF)
+
+option(ENABLE_MLALGO "Enable the machine learning algorithms" OFF)
 
 option(ENABLE_LCAO "Enable LCAO algorithm" ON)
 option(USE_ELPA "Enable ELPA for LCAO" ON)
@@ -115,7 +118,7 @@ endif()
 # Serial version of ABACUS will not use ELPA
 if(NOT ENABLE_MPI)
   set(USE_ELPA OFF)
-  set(ENABLE_DEEPKS OFF)
+  set(ENABLE_MLALGO OFF)
 endif()
 
 # Different exe files of ABACUS
@@ -253,7 +256,7 @@ if(ENABLE_LCAO)
     add_compile_definitions(__NEW_GINT)
   endif()
 else()
-  set(ENABLE_DEEPKS OFF)
+  set(ENABLE_MLALGO OFF)
   set(ENABLE_LIBRI OFF)
 endif()
 
@@ -480,8 +483,9 @@ if(ENABLE_FLOAT_FFTW)
   add_definitions(-D__ENABLE_FLOAT_FFTW)
 endif()
 
-if(ENABLE_DEEPKS)
-  target_link_libraries(${ABACUS_BIN_NAME} deepks)
+if(ENABLE_MLALGO)
+  target_link_libraries(${ABACUS_BIN_NAME} deepks) # deepks
+  target_link_libraries(${ABACUS_BIN_NAME} hamilt_mlkedf) # mlkedf
 
   find_path(libnpy_SOURCE_DIR npy.hpp HINTS ${libnpy_INCLUDE_DIR})
   if(NOT libnpy_SOURCE_DIR)
@@ -496,32 +500,14 @@ if(ENABLE_DEEPKS)
     include_directories(${libnpy_INCLUDE_DIR})
   endif()
   include_directories(${libnpy_SOURCE_DIR}/include)
-  add_compile_definitions(__DEEPKS)
-endif()
-
-if(ENABLE_MLKEDF)
-  target_link_libraries(${ABACUS_BIN_NAME} hamilt_mlkedf)
-
-  find_path(libnpy_SOURCE_DIR npy.hpp HINTS ${libnpy_INCLUDE_DIR})
-  if(NOT libnpy_SOURCE_DIR)
-    include(FetchContent)
-    FetchContent_Declare(
-      libnpy
-      GIT_REPOSITORY https://github.com/llohse/libnpy.git
-      GIT_SHALLOW TRUE
-      GIT_PROGRESS TRUE)
-    FetchContent_MakeAvailable(libnpy)
-  else()
-    include_directories(${libnpy_INCLUDE_DIR})
-  endif()
-  include_directories(${libnpy_SOURCE_DIR}/include)
-  add_compile_definitions(__MLKEDF)
+  
+  add_compile_definitions(__MLALGO)
 endif()
 
 # Torch uses outdated components to detect CUDA arch, causing failure on
 # latest CUDA kits. Set CMake variable TORCH_CUDA_ARCH_LIST in the form of
 # "major.minor" if required.
-if(ENABLE_DEEPKS OR ENABLE_MLKEDF OR DEFINED Torch_DIR)
+if(ENABLE_MLALGO OR DEFINED Torch_DIR)
   find_package(Torch REQUIRED)
   if(NOT Torch_VERSION VERSION_LESS "2.1.0")
     set_if_higher(CMAKE_CXX_STANDARD 17)

Dockerfile.gnu

@@ -34,7 +34,7 @@ ADD https://api.github.com/repos/deepmodeling/abacus-develop/git/refs/heads/deve
 
 RUN git clone https://github.com/deepmodeling/abacus-develop.git --depth 1 && \
     cd abacus-develop && \
-    cmake -B build -DENABLE_DEEPKS=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_RAPIDJSON=ON && \
+    cmake -B build -DENABLE_MLALGO=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_RAPIDJSON=ON && \
     cmake --build build -j`nproc` && \
     cmake --install build && \
     rm -rf build

Dockerfile.intel

@@ -58,7 +58,7 @@ ADD https://api.github.com/repos/deepmodeling/abacus-develop/git/refs/heads/deve
 RUN source /opt/intel/oneapi/setvars.sh && \
     git clone https://github.com/deepmodeling/abacus-develop.git --depth 1 && \
     cd abacus-develop && \
-    cmake -B build -DENABLE_DEEPKS=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_RAPIDJSON=ON && \
+    cmake -B build -DENABLE_MLALGO=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_RAPIDJSON=ON && \
     cmake --build build -j`nproc` && \
     cmake --install build && \
     rm -rf build && \

conda/meta.yaml

@@ -26,7 +26,7 @@ build:
   skip: true  # [not linux]
   script: |
     export CMAKE_PREFIX_PATH=`python -c "import torch;print(torch.__path__[0])"`/share/cmake:$CMAKE_PREFIX_PATH
-    cmake -B conda_build ${CMAKE_ARGS} -DCMAKE_BUILD_TYPE=Release -DENABLE_DEEPKS=1 -DENABLE_LIBXC=1
+    cmake -B conda_build ${CMAKE_ARGS} -DCMAKE_BUILD_TYPE=Release -DENABLE_MLALGO=1 -DENABLE_LIBXC=1
     cmake --build conda_build -j`nproc`
     cmake --install conda_build
   # ${CMAKE_ARGS} applys restrictions for CMake to search libs under conda building env.

docs/advanced/input_files/input-main.md

@@ -65,6 +65,8 @@
     - [nupdown](#nupdown)
     - [dft\_functional](#dft_functional)
     - [xc\_temperature](#xc_temperature)
+    - [xc\_exch\_ext](#xc_exch_ext)
+    - [xc\_corr\_ext](#xc_corr_ext)
     - [pseudo\_rcut](#pseudo_rcut)
     - [pseudo\_mesh](#pseudo_mesh)
     - [nspin](#nspin)
@@ -1060,6 +1062,26 @@ calculations.
 - **Default**: 0.0
 - **Unit**: Ry
 
+### xc_exch_ext
+
+- **Type**: Integer Real ...
+- **Description**: Customized parameterization on the exchange part of XC functional. The first value should be the LibXC ID of the original functional, and latter values are external parameters. Default values are those of Perdew-Burke-Ernzerhof (PBE) functional. For more information on LibXC ID of functionals, please refer to [LibXC](https://libxc.gitlab.io/functionals/). For parameters of functionals of interest, please refer to the source code of LibXC, such as PBE functional interface in LibXC: [gga_x_pbe.c](https://gitlab.com/libxc/libxc/-/blob/7.0.0/src/gga_x_pbe.c).
+- **Default**: 101 0.8040 0.2195149727645171
+- **Note**:
+  1. Solely setting this keyword will take no effect on XC functionals. One should also set `dft_functional` to corresponding functional to apply the customized parameterization. For example, if you want to use the PBE functional with customized parameters, you should set `dft_functional` to `GGA_X_PBE+GGA_C_PBE` and `xc_exch_ext` to `101 0.8040 0.2195149727645171`.
+  2. For functionals that do not have separate exchange and correlation parts, such as HSE06 whose corresponding LibXC notation is `HYB_GGA_XC_HSE06` and LibXC id is 428, you can set either `xc_exch_ext` or `xc_corr_ext` to `428 0.25 0.11 0.11` (which means 25% Hartree-Fock fraction, 0.11 as range-seperation) and leave the other one unset.
+  3. Presently this feature can only support parameterization on **one** exchange functional.
+
+### xc_corr_ext
+
+- **Type**: Integer Real ...
+- **Description**: Customized parameterization on the correlation part of XC functional. The first value should be the LibXC ID of the original functional, and latter values are external parameters. Default values are those of Perdew-Burke-Ernzerhof (PBE) functional. For more information on LibXC ID of functionals, please refer to [LibXC](https://libxc.gitlab.io/functionals/). For parameters of functionals of interest, please refer to the source code of LibXC, such as PBE functional interface in LibXC: [gga_c_pbe.c](https://gitlab.com/libxc/libxc/-/blob/7.0.0/src/gga_c_pbe.c).
+- **Default**: 130 0.06672455060314922 0.031090690869654895034 1.0
+- **Note**:
+  1. Solely setting this keyword will take no effect on XC functionals. One should also set `dft_functional` to corresponding functional to apply the customized parameterization. For example, if you want to use the PBE functional with customized parameters, you should set `dft_functional` to `GGA_X_PBE+GGA_C_PBE` and `xc_corr_ext` to `130 0.06672455060314922 0.031090690869654895034 1.0`.
+  2. For functionals that do not have separate exchange and correlation parts, such as HSE06 whose corresponding LibXC notation is `HYB_GGA_XC_HSE06` and LibXC id is 428, you can set either `xc_exch_ext` or `xc_corr_ext` to `428 0.25 0.11 0.11` (which means 25% Hartree-Fock fraction, 0.11 as range-seperation) and leave the other one unset.
+  3. Presently this feature can only support parameterization on **one** correlation functional.
+
 ### pseudo_rcut
 
 - **Type**: Real
@@ -2378,8 +2400,29 @@ Warning: this function is not robust enough for the current version. Please try
 ### of_ml_gene_data
 
 - **Type**: Boolean
-- **Availability**: OFDFT
-- **Description**: Generate training data or not.
+- **Availability**: Used only for KSDFT with plane wave basis
+- **Description**: Controls the generation of machine learning training data. When enabled, training data in `.npy` format will be saved in the directory `OUT.${suffix}/MLKEDF_Descriptors/`. The generated descriptors are categorized as follows:
+  - Local/Semilocal Descriptors. Files are named as `{var}.npy`, where `{var}` corresponds to the descriptor type:
+    - `gamma`: Enabled by [of_ml_gamma](#of_ml_gamma)  
+    - `p`: Enabled by [of_ml_p](#of_ml_p)  
+    - `q`: Enabled by [of_ml_q](#of_ml_q)  
+    - `tanhp`: Enabled by [of_ml_tanhp](#of_ml_tanhp)  
+    - `tanhq`: Enabled by [of_ml_tanhq](#of_ml_tanhq)  
+  - Nonlocal Descriptors generated using kernels configured via [of_ml_nkernel](#of_ml_nkernel), [of_ml_kernel](#of_ml_kernel), and [of_ml_kernel_scaling](#of_ml_kernel_scaling). Files follow the naming convention `{var}_{kernel_type}_{kernel_scaling}.npy`, where `{kernel_type}` and `{kernel_scaling}` are specified by [of_ml_kernel](#of_ml_kernel), and [of_ml_kernel_scaling](#of_ml_kernel_scaling), respectively, and `{val}` denotes the kind of the descriptor, including 
+      - `gammanl`: Enabled by [of_ml_gammanl](#of_ml_gammanl)  
+      - `pnl`: Enabled by [of_ml_pnl](#of_ml_pnl)  
+      - `qnl`: Enabled by [of_ml_qnl](#of_ml_qnl)  
+      - `xi`: Enabled by [of_ml_xi](#of_ml_xi)  
+      - `tanhxi`: Enabled by [of_ml_tanhxi](#of_ml_tanhxi)  
+      - `tanhxi_nl`: Enabled by [of_ml_tanhxi_nl](#of_ml_tanhxi_nl)  
+      - `tanh_pnl`: Enabled by [of_ml_tanh_pnl](#of_ml_tanh_pnl)  
+      - `tanh_qnl`: Enabled by [of_ml_tanh_qnl](#of_ml_tanh_qnl)  
+      - `tanhp_nl`: Enabled by [of_ml_tanhp_nl](#of_ml_tanhp_nl)  
+      - `tanhq_nl`: Enabled by [of_ml_tanhq_nl](#of_ml_tanhq_nl) 
+  - Training Targets, including key quantum mechanical quantities:
+    - `enhancement.npy`: Pauli energy enhancement factor $T_\theta/T_{\rm{TF}}$, where $T_{\rm{TF}}$ is the Thomas-Fermi functional  
+    - `pauli.npy`: Pauli potential $V_\theta$
+    - `veff.npy`: Effective potential
 - **Default**: False
 
 ### of_ml_device

docs/advanced/install.md

@@ -16,32 +16,17 @@ If Libxc is not installed in standard path (i.e. installed with a custom prefix
 cmake -B build -DLibxc_DIR=~/libxc
 ```
 
-## Build with DeePKS
+## Build with ML-ALGO
 
-If DeePKS feature is required for [DeePKS-kit](https://github.com/deepmodeling/deepks-kit), the following prerequisites and steps are needed:
-
-- C++ compiler, supporting **C++14** (GCC >= 5 is sufficient)
-- CMake >= 3.18
-- [LibTorch](https://pytorch.org/) with cxx11 ABI supporting CPU
-- [Libnpy](https://github.com/llohse/libnpy/)
-
-```bash
-cmake -B build -DENABLE_DEEPKS=1 -DTorch_DIR=~/libtorch/share/cmake/Torch/ -Dlibnpy_INCLUDE_DIR=~/libnpy/include
-```
-
-> CMake will try to download Libnpy if it cannot be found locally.
-
-## Build with ML-KEDF
-
-If machine learning based kinetic energy density functional (ML-KEDF) is required for OFDFT calculation, the following prerequisites and steps are needed:
+If machine learning algorithms, including DeePKS and machine learning based kinetic energy density functional (ML-KEDF) for OFDFT, is required for DFT calculation, the following prerequisites and steps are needed:
 
 - C++ compiler, supporting **C++14** (GCC >= 5 is sufficient)
 - CMake >= 3.18
 - [LibTorch](https://pytorch.org/) with cxx11 ABI supporting CPU or GPU
 - [Libnpy](https://github.com/llohse/libnpy/)
 
 ```bash
-cmake -B build -DENABLE_MLKEDF=1 -DTorch_DIR=~/libtorch/share/cmake/Torch/ -Dlibnpy_INCLUDE_DIR=~/libnpy/include
+cmake -B build -DENABLE_MLALGO=1 -DTorch_DIR=~/libtorch/share/cmake/Torch/ -Dlibnpy_INCLUDE_DIR=~/libnpy/include
 ```
 
 > CMake will try to download Libnpy if it cannot be found locally.
@@ -206,8 +191,8 @@ CEREAL_DIR    = /usr/local/include/cereal
 
 
 ##-------------------  OPTIONAL LIBS  ---------------------------------
-## To use DEEPKS: set ENABLE_DEEPKS = ON, and set LIBTORCH_DIR and LIBNPY_DIR
-## To use MLKEDF: set ENABLE_MLKEDF = ON, and set LIBTORCH_DIR and LIBNPY_DIR
+## To use MLALGO: set ENABLE_MLALGO = ON, and set LIBTORCH_DIR and LIBNPY_DIR
+
 ## To use LIBXC:  set LIBXC_DIR which contains include and lib/libxc.a (>5.1.7)
 ## To use DeePMD: set DeePMD_DIR LIBTORCH_DIR and TensorFlow_DIR
 ## To use LibRI:  set LIBRI_DIR and LIBCOMM_DIR
@@ -216,8 +201,7 @@ CEREAL_DIR    = /usr/local/include/cereal
 
 # LIBTORCH_DIR  = /usr/local
 # LIBNPY_DIR    = /usr/local
-ENABLE_DEEPKS   = OFF
-ENABLE_MLKEDF   = OFF
+ENABLE_MLALGO   = OFF
 
 # LIBXC_DIR    		= /public/soft/libxc
 
@@ -292,25 +276,16 @@ make LIBXC_DIR=/pulic/soft/libxc
 
 directly.
 
-### Add DeePKS Support
+### Add ML-ALGO Support
 
-To compile ABACUS with DEEPKS, you need to set `ENABLE_DEEPKS = ON`, and define `LIBTORCH_DIR` and `LIBNPY_DIR` in the file `Makefile.vars` or use
+To compile ABACUS with machine learning algorithms, you need to set `ENABLE_MLALGO = ON`, and define `LIBTORCH_DIR` and `LIBNPY_DIR` in the file `Makefile.vars` or use
 
 ```makefile
-make ENABLE_DEEPKS=ON LIBTORCH_DIR=/opt/libtorch/ LIBNPY_DIR=/opt/libnpy/
+make ENABLE_MLALGO=ON LIBTORCH_DIR=/opt/libtorch/ LIBNPY_DIR=/opt/libnpy/
 ```
 
 directly.
 
-### Add ML-KEDF Support
-
-To compile ABACUS with ML-KEDF, you need to set `ENABLE_MLKEDF = ON`, and define `LIBTORCH_DIR` and `LIBNPY_DIR` in the file `Makefile.vars` or use
-
-```makefile
-make ENABLE_MLKEDF=ON LIBTORCH_DIR=/opt/libtorch/ LIBNPY_DIR=/opt/libnpy/
-```
-
-directly.
 
 ### Add DeePMD-kit Support