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Merge branch 'develop' into fix-set-command

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This commit is contained in:
Axel Kohlmeyer
2025-05-29 05:21:46 -04:00
parent 1668bcffcf 2744647c75
commit 129a3a83e5
207 changed files with 12636 additions and 4187 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
cmake/CMakeLists.txt
View File

@ -131,7 +131,9 @@ if((CMAKE_CXX_COMPILER_ID STREQUAL "NVHPC") OR (CMAKE_CXX_COMPILER_ID STREQUAL "
endif()
# silence nvcc warnings
if((PKG_KOKKOS) AND (Kokkos_ENABLE_CUDA) AND NOT (CMAKE_CXX_COMPILER_ID STREQUAL "Clang"))
if((PKG_KOKKOS) AND (Kokkos_ENABLE_CUDA) AND NOT
((CMAKE_CXX_COMPILER_ID STREQUAL "Clang") OR (CMAKE_CXX_COMPILER_ID STREQUAL "IntelLLVM")
OR (CMAKE_CXX_COMPILER_ID STREQUAL "XLClang") OR (CMAKE_CXX_COMPILER_ID STREQUAL "CrayClang")))
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Xcudafe --diag_suppress=unrecognized_pragma,--diag_suppress=128")
endif()

5
cmake/Modules/Packages/COLVARS.cmake
View File

@ -26,6 +26,11 @@ if(BUILD_OMP)
target_link_libraries(colvars PRIVATE OpenMP::OpenMP_CXX)
endif()
if(BUILD_MPI)
target_compile_definitions(colvars PUBLIC -DCOLVARS_MPI)
target_link_libraries(colvars PUBLIC MPI::MPI_CXX)
endif()
if(COLVARS_DEBUG)
# Need to export the define publicly to be valid in interface code
target_compile_definitions(colvars PUBLIC -DCOLVARS_DEBUG)

10
cmake/Modules/Packages/MC.cmake
View File

@ -7,3 +7,13 @@ if(NOT PKG_MANYBODY)
list(REMOVE_ITEM LAMMPS_SOURCES ${LAMMPS_SOURCE_DIR}/MC/fix_sgcmc.cpp)
set_property(TARGET lammps PROPERTY SOURCES "${LAMMPS_SOURCES}")
endif()
# fix neighbor/swap may only be installed if also the VORONOI package is installed
if(NOT PKG_VORONOI)
get_property(LAMMPS_FIX_HEADERS GLOBAL PROPERTY FIX)
list(REMOVE_ITEM LAMMPS_FIX_HEADERS ${LAMMPS_SOURCE_DIR}/MC/fix_neighbor_swap.h)
set_property(GLOBAL PROPERTY FIX "${LAMMPS_FIX_HEADERS}")
get_target_property(LAMMPS_SOURCES lammps SOURCES)
list(REMOVE_ITEM LAMMPS_SOURCES ${LAMMPS_SOURCE_DIR}/MC/fix_neighbor_swap.cpp)
set_property(TARGET lammps PROPERTY SOURCES "${LAMMPS_SOURCES}")
endif()

15
cmake/Modules/Packages/SCAFACOS.cmake
View File

@ -14,27 +14,16 @@ endif()
option(DOWNLOAD_SCAFACOS "Download ScaFaCoS library instead of using an already installed one" ${DOWNLOAD_SCAFACOS_DEFAULT})
if(DOWNLOAD_SCAFACOS)
message(STATUS "ScaFaCoS download requested - we will build our own")
set(SCAFACOS_URL "https://github.com/scafacos/scafacos/releases/download/v1.0.1/scafacos-1.0.1.tar.gz" CACHE STRING "URL for SCAFACOS tarball")
set(SCAFACOS_MD5 "bd46d74e3296bd8a444d731bb10c1738" CACHE STRING "MD5 checksum of SCAFACOS tarball")
set(SCAFACOS_URL "https://github.com/scafacos/scafacos/releases/download/v1.0.4/scafacos-1.0.4.tar.gz" CACHE STRING "URL for SCAFACOS tarball")
set(SCAFACOS_MD5 "23867540ec32e63ce71d6ecc105278d2" CACHE STRING "MD5 checksum of SCAFACOS tarball")
mark_as_advanced(SCAFACOS_URL)
mark_as_advanced(SCAFACOS_MD5)
GetFallbackURL(SCAFACOS_URL SCAFACOS_FALLBACK)
# version 1.0.1 needs a patch to compile and linke cleanly with GCC 10 and later.
file(DOWNLOAD ${LAMMPS_THIRDPARTY_URL}/scafacos-1.0.1-fix.diff ${CMAKE_CURRENT_BINARY_DIR}/scafacos-1.0.1.fix.diff
EXPECTED_HASH MD5=4baa1333bb28fcce102d505e1992d032)
find_program(HAVE_PATCH patch)
if(NOT HAVE_PATCH)
message(FATAL_ERROR "The 'patch' program is required to build the ScaFaCoS library")
endif()
include(ExternalProject)
ExternalProject_Add(scafacos_build
URL ${SCAFACOS_URL} ${SCAFACOS_FALLBACK}
URL_MD5 ${SCAFACOS_MD5}
PATCH_COMMAND patch -p1 < ${CMAKE_CURRENT_BINARY_DIR}/scafacos-1.0.1.fix.diff
CONFIGURE_COMMAND <SOURCE_DIR>/configure --prefix=<INSTALL_DIR> --disable-doc
--enable-fcs-solvers=fmm,p2nfft,direct,ewald,p3m
--with-internal-fftw --with-internal-pfft

6
doc/graphviz/lammps-releases.dot
View File

@ -5,13 +5,13 @@ digraph releases {
github -> develop [label="Merge commits"];
{
rank = "same";
work [shape="none" label="Development branches:"]
work [shape="none" label="Development branches:" fontname="bold"]
develop [label="'develop' branch" height=0.75];
maintenance [label="'maintenance' branch" height=0.75];
};
{
rank = "same";
upload [shape="none" label="Release branches:"]
upload [shape="none" label="Release branches:" fontname="bold"]
release [label="'release' branch" height=0.75];
stable [label="'stable' branch" height=0.75];
};
@ -22,7 +22,7 @@ digraph releases {
maintenance -> stable [label="Updates to stable release"];
{
rank = "same";
tag [shape="none" label="Applied tags:"];
tag [shape="none" label="Applied tags:" fontname="bold"];
patchtag [shape="box" label="patch_<date>"];
stabletag [shape="box" label="stable_<date>"];
updatetag [shape="box" label="stable_<date>_update<num>"];

24
doc/src/Build.rst
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@ -14,32 +14,10 @@ As an alternative, you can download a package with pre-built executables
or automated build trees, as described in the :doc:`Install <Install>`
section of the manual.
Prerequisites
-------------
Which software you need to compile and use LAMMPS strongly depends on
which :doc:`features and settings <Build_settings>` and which
:doc:`optional packages <Packages_list>` you are trying to include.
Common to all is that you need a C++ and C compiler, where the C++
compiler has to support at least the C++11 standard (note that some
compilers require command-line flag to activate C++11 support).
Furthermore, if you are building with CMake, you need at least CMake
version 3.20 and a compatible build tool (make or ninja-build); if you
are building the the legacy GNU make based build system you need GNU
make (other make variants are not going to work since the build system
uses features unique to GNU make) and a Unix-like build environment with
a Bourne shell, and shell tools like "sed", "grep", "touch", "test",
"tr", "cp", "mv", "rm", "ln", "diff" and so on. Parts of LAMMPS
interface with or use Python version 3.6 or later.
The LAMMPS developers aim to keep LAMMPS very portable and usable -
at least in parts - on most operating systems commonly used for
running MD simulations. Please see the :doc:`section on portablility
<Intro_portability>` for more details.
.. toctree::
:maxdepth: 1
Build_prerequisites
Build_cmake
Build_make
Build_link

22
doc/src/Build_prerequisites.rst Normal file
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@ -0,0 +1,22 @@
Prerequisites
-------------
Which software you need to compile and use LAMMPS strongly depends on
which :doc:`features and settings <Build_settings>` and which
:doc:`optional packages <Packages_list>` you are trying to include.
Common to all is that you need a C++ and C compiler, where the C++
compiler has to support at least the C++11 standard (note that some
compilers require command-line flag to activate C++11 support).
Furthermore, if you are building with CMake, you need at least CMake
version 3.20 and a compatible build tool (make or ninja-build); if you
are building the the legacy GNU make based build system you need GNU
make (other make variants are not going to work since the build system
uses features unique to GNU make) and a Unix-like build environment with
a Bourne shell, and shell tools like "sed", "grep", "touch", "test",
"tr", "cp", "mv", "rm", "ln", "diff" and so on. Parts of LAMMPS
interface with or use Python version 3.6 or later.
The LAMMPS developers aim to keep LAMMPS very portable and usable -
at least in parts - on most operating systems commonly used for
running MD simulations. Please see the :doc:`section on portablility
<Intro_portability>` for more details.

2
doc/src/Commands_fix.rst
View File

@ -77,6 +77,7 @@ OPT.
* :doc:`flow/gauss <fix_flow_gauss>`
* :doc:`freeze (k) <fix_freeze>`
* :doc:`gcmc <fix_gcmc>`
* :doc:`gjf <fix_gjf>`
* :doc:`gld <fix_gld>`
* :doc:`gle <fix_gle>`
* :doc:`gravity (ko) <fix_gravity>`
@ -111,6 +112,7 @@ OPT.
* :doc:`mvv/tdpd <fix_mvv_dpd>`
* :doc:`neb <fix_neb>`
* :doc:`neb/spin <fix_neb_spin>`
* :doc:`neighbor/swap <fix_neighbor_swap>`
* :doc:`nonaffine/displacement <fix_nonaffine_displacement>`
* :doc:`nph (ko) <fix_nh>`
* :doc:`nph/asphere (o) <fix_nph_asphere>`

17
doc/src/Commands_removed.rst
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@ -1,7 +1,7 @@
Removed commands and packages
=============================
.. contents:: \
.. contents::
------
@ -12,10 +12,21 @@ stop LAMMPS and print a suitable error message in most cases, when a
style/command is used that has been removed or will replace the command
with the direct alternative (if available) and print a warning.
GJF formulation in fix langevin
-------------------------------
.. deprecated:: TBD
The *gjf* keyword in fix langevin is deprecated and will be removed
soon. The GJF functionality has been moved to its own fix style
:doc:`fix gjf <fix_gjf>` and it is strongly recommended to use that
fix instead.
LAMMPS shell
------------
.. versionchanged:: 29Aug2024
.. deprecated:: 29Aug2024
The LAMMPS shell has been removed from the LAMMPS distribution. Users
are encouraged to use the :ref:`LAMMPS-GUI <lammps_gui>` tool instead.
@ -23,7 +34,7 @@ are encouraged to use the :ref:`LAMMPS-GUI <lammps_gui>` tool instead.
i-PI tool
---------
.. versionchanged:: 27Jun2024
.. deprecated:: 27Jun2024
The i-PI tool has been removed from the LAMMPS distribution. Instead,
instructions to install i-PI from PyPI via pip are provided.

18
doc/src/Errors_details.rst
View File

@ -159,13 +159,17 @@ angle, dihedral, or improper with just one atom in the actual
sub-domain. Typically, this cutoff is set to the largest cutoff from
the :doc:`pair style(s) <pair_style>` plus the :doc:`neighbor list skin
distance <neighbor>` and will typically be sufficient for all bonded
interactions. But if the pair style cutoff is small, this may not be
enough. LAMMPS will print a warning in this case using some heuristic
based on the equilibrium bond length, but that still may not be
sufficient for cases where the force constants are small and thus bonds
may be stretched very far. The communication cutoff can be adjusted
with :doc:`comm_modify cutoff \<value\> <comm_modify>`, but setting this
too large will waste CPU time and memory.
interactions. But if the pair style cutoff is small (e.g. with a
repulsive-only Lennard-Jones potential) this may not be enough. It is
even worse if there is no pair style defined (or the pair style is set
to "none"), since then there will be no ghost atoms created at all.
The communication cutoff can be set or adjusted with :doc:`comm_modify
cutoff \<value\> <comm_modify>`, but setting this too large will waste
CPU time and memory. LAMMPS will print warnings in these cases. For
bonds it uses some heuristic based on the equilibrium bond length, but
that still may not be sufficient for cases where the force constants are
small and thus bonds may be stretched very far.
.. _hint09:

1
doc/src/Howto.rst
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@ -66,6 +66,7 @@ Force fields howto
:name: force_howto
:maxdepth: 1
Howto_FFgeneral
Howto_bioFF
Howto_amoeba
Howto_tip3p

55
doc/src/Howto_FFgeneral.rst Normal file
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@ -0,0 +1,55 @@
Some general force field considerations
=======================================
A compact summary of the concepts, definitions, and properties of force
fields with explicit bonded interactions (like the ones discussed in
this HowTo) is given in :ref:`(Gissinger) <Typelabel2>`.
A force field has 2 parts: the formulas that define its potential
functions and the coefficients used for a particular system. To assign
parameters it is first required to assign atom types. Those are not
only based on the elements, but also on the chemical environment due to
the atoms bound to them. This often follows the chemical concept of
*functional groups*. Example: a carbon atom bound with a single bond to
a single OH-group (alcohol) would be a different atom type than a carbon
atom bound to a methyl CH3 group (aliphatic carbon). The atom types
usually then determine the non-bonded Lennard-Jones parameters and the
parameters for bonds, angles, dihedrals, and impropers. On top of that,
partial charges have to be applied. Those are usually independent of
the atom types and are determined either for groups of atoms called
residues with some fitting procedure based on quantum mechanical
calculations, or based on some increment system that add or subtract
increments from the partial charge of an atom based on the types of
the neighboring atoms.
Force fields differ in the strategies they employ to determine the
parameters and charge distribution in how generic or specific they are
which in turn has an impact on the accuracy (compare for example
CGenFF to CHARMM and GAFF to Amber). Because of the different
strategies, it is not a good idea to use a mix of parameters from
different force field *families* (like CHARMM, Amber, or GROMOS)
and that extends to the parameters for the solvent, especially
water. The publication describing the parameterization of a force
field will describe which water model to use. Changing the water
model usually leads to overall worse results (even if it may improve
on the water itself).
In addition, one has to consider that *families* of force fields like
CHARMM, Amber, OPLS, or GROMOS have evolved over time and thus provide
different *revisions* of the force field parameters. These often
corresponds to changes in the functional form or the parameterization
strategies. This may also result in changes required for simulation
settings like the preferred cutoff or how Coulomb interactions are
computed (cutoff, smoothed/shifted cutoff, or long-range with Ewald
summation or equivalent). Unless explicitly stated in the publication
describing the force field, the Coulomb interaction cannot be chosen at
will but must match the revision of the force field. That said,
liberties may be taken during the initial equilibration of a system to
speed up the process, but not for production simulations.
----------
.. _Typelabel2:
**(Gissinger)** J. R. Gissinger, I. Nikiforov, Y. Afshar, B. Waters, M. Choi, D. S. Karls, A. Stukowski, W. Im, H. Heinz, A. Kohlmeyer, and E. B. Tadmor, J Phys Chem B, 128, 3282-3297 (2024).

38
doc/src/Howto_bioFF.rst
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@ -1,22 +1,16 @@
CHARMM, AMBER, COMPASS, DREIDING, and OPLS force fields
=======================================================
A compact summary of the concepts, definitions, and properties of
force fields with explicit bonded interactions (like the ones discussed
in this HowTo) is given in :ref:`(Gissinger) <Typelabel2>`.
A force field has 2 parts: the formulas that define it and the
coefficients used for a particular system. Here we only discuss
formulas implemented in LAMMPS that correspond to formulas commonly used
in the CHARMM, AMBER, COMPASS, and DREIDING force fields. Setting
coefficients is done either from special sections in an input data file
via the :doc:`read_data <read_data>` command or in the input script with
commands like :doc:`pair_coeff <pair_coeff>` or :doc:`bond_coeff
<bond_coeff>` and so on. See the :doc:`Tools <Tools>` doc page for
additional tools that can use CHARMM, AMBER, or Materials Studio
generated files to assign force field coefficients and convert their
output into LAMMPS input. LAMMPS input scripts can also be generated by
`charmm-gui.org <https://charmm-gui.org/>`_.
Here we only discuss formulas implemented in LAMMPS that correspond to
formulas commonly used in the CHARMM, AMBER, COMPASS, and DREIDING force
fields. Setting coefficients is done either from special sections in an
input data file via the :doc:`read_data <read_data>` command or in the
input script with commands like :doc:`pair_coeff <pair_coeff>` or
:doc:`bond_coeff <bond_coeff>` and so on. See the :doc:`Tools <Tools>`
doc page for additional tools that can use CHARMM, AMBER, or Materials
Studio generated files to assign force field coefficients and convert
their output into LAMMPS input. LAMMPS input scripts can also be
generated by `charmm-gui.org <https://charmm-gui.org/>`_.
CHARMM and AMBER
----------------
@ -203,9 +197,11 @@ rather than individual force constants and geometric parameters that
depend on the particular combinations of atoms involved in the bond,
angle, or torsion terms. DREIDING has an :doc:`explicit hydrogen bond
term <pair_hbond_dreiding>` to describe interactions involving a
hydrogen atom on very electronegative atoms (N, O, F). Unlike CHARMM
or AMBER, the DREIDING force field has not been parameterized for
considering solvents (like water).
hydrogen atom on very electronegative atoms (N, O, F). Unlike CHARMM or
AMBER, the DREIDING force field has not been parameterized for
considering solvents (like water) and has no rules for assigning
(partial) charges. That will seriously limit its accuracy when used for
simulating systems where those matter.
See :ref:`(Mayo) <howto-Mayo>` for a description of the DREIDING force field
@ -272,10 +268,6 @@ compatible with a subset of OPLS interactions.
----------
.. _Typelabel2:
**(Gissinger)** J. R. Gissinger, I. Nikiforov, Y. Afshar, B. Waters, M. Choi, D. S. Karls, A. Stukowski, W. Im, H. Heinz, A. Kohlmeyer, and E. B. Tadmor, J Phys Chem B, 128, 3282-3297 (2024).
.. _howto-MacKerell:
**(MacKerell)** MacKerell, Bashford, Bellott, Dunbrack, Evanseck, Field, Fischer, Gao, Guo, Ha, et al (1998). J Phys Chem, 102, 3586 . https://doi.org/10.1021/jp973084f

5
doc/src/Howto_lammps_gui.rst
View File

@ -308,7 +308,10 @@ of the *Output* window showing how many warnings and errors were
detected and how many lines the entire output has. By clicking on the
button on the right with the warning symbol or by using the keyboard
shortcut `Ctrl-N` (`Command-N` on macOS), you can jump to the next
line with a warning or error.
line with a warning or error. If there is a URL pointing to additional
explanations in the online manual, that URL will be highlighted and
double-clicking on it shall open the corresponding manual page in
the web browser. The option is also available from the context menu.
By default, the *Output* window is replaced each time a run is started.
The runs are counted and the run number for the current run is displayed

4
doc/src/Howto_spc.rst
View File

@ -1,5 +1,5 @@
SPC water model
===============
SPC and SPC/E water model
=========================
The SPC water model specifies a 3-site rigid water molecule with
charges and Lennard-Jones parameters assigned to each of the three atoms.

9
doc/src/Howto_thermostat.rst
View File

@ -21,9 +21,14 @@ can be invoked via the *dpd/tstat* pair style:
* :doc:`fix nvt/sllod <fix_nvt_sllod>`
* :doc:`fix temp/berendsen <fix_temp_berendsen>`
* :doc:`fix temp/csvr <fix_temp_csvr>`
* :doc:`fix ffl <fix_ffl>`
* :doc:`fix gjf <fix_gjf>`
* :doc:`fix gld <fix_gld>`
* :doc:`fix gle <fix_gle>`
* :doc:`fix langevin <fix_langevin>`
* :doc:`fix temp/rescale <fix_temp_rescale>`
* :doc:`pair_style dpd/tstat <pair_dpd>`
* :doc:`pair_style dpd/ext/tstat <pair_dpd_ext>`
:doc:`Fix nvt <fix_nh>` only thermostats the translational velocity of
particles. :doc:`Fix nvt/sllod <fix_nvt_sllod>` also does this,
@ -82,10 +87,10 @@ that:
.. note::
Only the nvt fixes perform time integration, meaning they update
Not all thermostat fixes perform time integration, meaning they update
the velocities and positions of particles due to forces and velocities
respectively. The other thermostat fixes only adjust velocities; they
do NOT perform time integration updates. Thus they should be used in
do NOT perform time integration updates. Thus, they should be used in
conjunction with a constant NVE integration fix such as these:
* :doc:`fix nve <fix_nve>`

129
doc/src/Howto_tip4p.rst
View File

@ -1,5 +1,5 @@
TIP4P water model
=================
TIP4P and OPC water models
==========================
The four-point TIP4P rigid water model extends the traditional
:doc:`three-point TIP3P <Howto_tip3p>` model by adding an additional
@ -9,9 +9,11 @@ the oxygen along the bisector of the HOH bond angle. A bond style of
:doc:`harmonic <bond_harmonic>` and an angle style of :doc:`harmonic
<angle_harmonic>` or :doc:`charmm <angle_charmm>` should also be used.
In case of rigid bonds also bond style :doc:`zero <bond_zero>` and angle
style :doc:`zero <angle_zero>` can be used.
style :doc:`zero <angle_zero>` can be used. Very similar to the TIP4P
model is the OPC water model. It can be realized the same way as TIP4P
but has different geometry and force field parameters.
There are two ways to implement TIP4P water in LAMMPS:
There are two ways to implement TIP4P-like water in LAMMPS:
#. Use a specially written pair style that uses the :ref:`TIP3P geometry
<tip3p_molecule>` without the point M. The point M location is then
@ -21,7 +23,10 @@ There are two ways to implement TIP4P water in LAMMPS:
computationally very efficient, but the charge distribution in space
is only correct within the tip4p labeled styles. So all other
computations using charges will "see" the negative charge incorrectly
on the oxygen atom.
located on the oxygen atom unless they are specially written for using
the TIP4P geometry internally as well, e.g. :doc:`compute dipole/tip4p
<compute_dipole>`, :doc:`fix efield/tip4p <fix_efield>`, or
:doc:`kspace_style pppm/tip4p <kspace_style>`.
This can be done with the following pair styles for Coulomb with a cutoff:
@ -68,77 +73,90 @@ TIP4P/2005 model :ref:`(Abascal2) <Abascal2>` and a version of TIP4P
parameters adjusted for use with a long-range Coulombic solver
(e.g. Ewald or PPPM in LAMMPS). Note that for implicit TIP4P models the
OM distance is specified in the :doc:`pair_style <pair_style>` command,
not as part of the pair coefficients.
not as part of the pair coefficients. Also parameters for the OPC
model (:ref:`Izadi <Izadi>`) are provided.
.. list-table::
:header-rows: 1
:widths: 36 19 13 15 17
:widths: 40 12 12 14 11 11
* - Parameter
- TIP4P (original)
- TIP4P/Ice
- TIP4P/2005
- TIP4P (Ewald)
- OPC
* - O mass (amu)
- 15.9994
- 15.9994
- 15.9994
- 15.9994
- 15.9994
* - H mass (amu)
- 1.008
- 1.008
- 1.008
- 1.008
- 1.008
* - O or M charge (:math:`e`)
- -1.040
- -1.1794
- -1.1128
- -1.04844
- -1.3582
* - H charge (:math:`e`)
- 0.520
- 0.5897
- 0.5564
- 0.52422
- 0.6791
* - LJ :math:`\epsilon` of OO (kcal/mole)
- 0.1550
- 0.21084
- 0.1852
- 0.16275
- 0.21280
* - LJ :math:`\sigma` of OO (:math:`\AA`)
- 3.1536
- 3.1668
- 3.1589
- 3.16435
- 3.1660
* - LJ :math:`\epsilon` of HH, MM, OH, OM, HM (kcal/mole)
- 0.0
- 0.0
- 0.0
- 0.0
- 0.0
* - LJ :math:`\sigma` of HH, MM, OH, OM, HM (:math:`\AA`)
- 1.0
- 1.0
- 1.0
- 1.0
- 1.0
* - :math:`r_0` of OH bond (:math:`\AA`)
- 0.9572
- 0.9572
- 0.9572
- 0.9572
- 0.8724
* - :math:`\theta_0` of HOH angle
- 104.52\ :math:`^{\circ}`
- 104.52\ :math:`^{\circ}`
- 104.52\ :math:`^{\circ}`
- 104.52\ :math:`^{\circ}`
- 103.60\ :math:`^{\circ}`
* - OM distance (:math:`\AA`)
- 0.15
- 0.1577
- 0.1546
- 0.1250
- 0.1594
Note that the when using the TIP4P pair style, the neighbor list cutoff
Note that the when using a TIP4P pair style, the neighbor list cutoff
for Coulomb interactions is effectively extended by a distance 2 \* (OM
distance), to account for the offset distance of the fictitious charges
on O atoms in water molecules. Thus it is typically best in an
on O atoms in water molecules. Thus, it is typically best in an
efficiency sense to use a LJ cutoff >= Coulomb cutoff + 2\*(OM
distance), to shrink the size of the neighbor list. This leads to
slightly larger cost for the long-range calculation, so you can test the
@ -192,6 +210,94 @@ file changed):
run 20000
write_data tip4p-implicit.data nocoeff
When constructing an OPC model, we cannot use the ``tip3p.mol`` file due
to the different geometry. Below is a molecule file providing the 3
sites of an implicit OPC geometry for use with TIP4P styles. Note, that
the "Shake" and "Special" sections are missing here. Those will be
auto-generated by LAMMPS when the molecule file is loaded *after* the
simulation box has been created. These sections are required only when
the molecule file is loaded *before*.
.. _opc3p_molecule:
.. code-block::
# Water molecule. 3 point geometry for OPC model
3 atoms
2 bonds
1 angles
Coords
1 0.00000 -0.06037 0.00000
2 0.68558 0.50250 0.00000
3 -0.68558 0.50250 0.00000
Types
1 1 # O
2 2 # H
3 2 # H
Charges
1 -1.3582
2 0.6791
3 0.6791
Bonds
1 1 1 2
2 1 1 3
Angles
1 1 2 1 3
Below is a LAMMPS input file using the implicit method to implement
the OPC model using the molecule file from above and including the
PPPM long-range Coulomb solver.
.. code-block:: LAMMPS
units real
atom_style full
region box block -5 5 -5 5 -5 5
create_box 2 box bond/types 1 angle/types 1 &
extra/bond/per/atom 2 extra/angle/per/atom 1 extra/special/per/atom 2
mass 1 15.9994
mass 2 1.008
pair_style lj/cut/tip4p/long 1 2 1 1 0.1594 12.0
pair_coeff 1 1 0.2128 3.166
pair_coeff 2 2 0.0 1.0
bond_style zero
bond_coeff 1 0.8724
angle_style zero
angle_coeff 1 103.6
kspace_style pppm/tip4p 1.0e-5
molecule water opc3p.mol # this file has the OPC geometry but is without M
create_atoms 0 random 33 34564 NULL mol water 25367 overlap 1.33
fix rigid all shake 0.001 10 10000 b 1 a 1
minimize 0.0 0.0 1000 10000
reset_timestep 0
timestep 1.0
velocity all create 300.0 5463576
fix integrate all nvt temp 300 300 100.0
thermo_style custom step temp press etotal pe
thermo 1000
run 20000
write_data opc-implicit.data nocoeff
Below is the code for a LAMMPS input file using the explicit method and
a TIP4P molecule file. Because of using :doc:`fix rigid/small
<fix_rigid>` no bonds need to be defined and thus no extra storage needs
@ -279,3 +385,8 @@ Phys, 79, 926 (1983).
**(Abascal2)** Abascal, J Chem Phys, 123, 234505 (2005)
https://doi.org/10.1063/1.2121687
.. _Izadi:
**(Izadi)** Izadi, Anandakrishnan, Onufriev, J. Phys. Chem. Lett., 5, 21, 3863 (2014)
https://doi.org/10.1021/jz501780a

5
doc/src/Intro_authors.rst
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@ -84,8 +84,9 @@ lammps.org". General questions about LAMMPS should be posted in the
\normalsize
Past developers include Paul Crozier and Mark Stevens, both at SNL,
and Ray Shan, now at Materials Design.
Past core developers include Paul Crozier and Mark Stevens, both at SNL,
and Ray Shan while at SNL and later at Materials Design, now at Thermo
Fisher Scientific.
----------

25
doc/src/Intro_portability.rst
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@ -28,8 +28,9 @@ Build systems
LAMMPS can be compiled from source code using a (traditional) build
system based on shell scripts, a few shell utilities (grep, sed, cat,
tr) and the GNU make program. This requires running within a Bourne
shell (``/bin/sh``). Alternatively, a build system with different back
ends can be created using CMake. CMake must be at least version 3.16.
shell (``/bin/sh`` or ``/bin/bash``). Alternatively, a build system
with different back ends can be created using CMake. CMake must be
at least version 3.16.
Operating systems
^^^^^^^^^^^^^^^^^
@ -40,11 +41,18 @@ Also, compilation and correct execution on macOS and Windows (using
Microsoft Visual C++) is checked automatically for the largest part of
the source code. Some (optional) features are not compatible with all
operating systems, either through limitations of the corresponding
LAMMPS source code or through incompatibilities of source code or
build system of required external libraries or packages.
LAMMPS source code or through incompatibilities or build system
limitations of required external libraries or packages.
Executables for Windows may be created natively using either Cygwin or
Visual Studio or with a Linux to Windows MinGW cross-compiler.
Executables for Windows may be created either natively using Cygwin,
MinGW, Intel, Clang, or Microsoft Visual C++ compilers, or with a Linux
to Windows MinGW cross-compiler. Native compilation is supported using
Microsoft Visual Studio or a terminal window (using the CMake build
system).
Executables for macOS may be created either using Xcode or GNU compilers
installed with Homebrew. In the latter case, building of LAMMPS through
Homebrew instead of a manual compile is also possible.
Additionally, FreeBSD and Solaris have been tested successfully to
run LAMMPS and produce results consistent with those on Linux.
@ -61,8 +69,9 @@ CPU architectures
^^^^^^^^^^^^^^^^^
The primary CPU architecture for running LAMMPS is 64-bit x86, but also
32-bit x86, and 64-bit ARM and PowerPC (64-bit, Little Endian) are
regularly tested.
64-bit ARM and PowerPC (64-bit, Little Endian) are currently regularly
tested. Further architectures are tested by Linux distributions that
bundle LAMMPS.
Portability compliance
^^^^^^^^^^^^^^^^^^^^^^

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@ -46,6 +46,8 @@ Here is a brief list of some the class methods in the Pair class that
+---------------------------------+------------------------------------------------------------------------+
| compute_inner/middle/outer | versions of compute used by rRESPA |
+---------------------------------+------------------------------------------------------------------------+
| compute_atomic_energy | energy of one atom, equivalent to per-atom energy |
+---------------------------------+------------------------------------------------------------------------+
| memory_usage | return estimated amount of memory used by the pair style |
+---------------------------------+------------------------------------------------------------------------+
| modify_params | process arguments to pair_modify command |
@ -122,3 +124,5 @@ setting.
+---------------------------------+-------------------------------------------------------------+---------+
| spinflag | 1 if compatible with spin kspace_style | 0 |
+---------------------------------+-------------------------------------------------------------+---------+
| atomic_energy_enable | 1 if compute_atomic_energy() routine exists | 0 |
+---------------------------------+-------------------------------------------------------------+---------+

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16
doc/src/Tools.rst
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@ -475,9 +475,13 @@ beginners to start with LAMMPS, it is also the expectation that
LAMMPS-GUI users will eventually transition to workflows that most
experienced LAMMPS users employ.
All features have been extensively exposed to keyboard shortcuts, so
that there is also appeal for experienced LAMMPS users for prototyping
and testing simulation setups.
.. image:: JPG/lammps-gui-screen.png
:align: center
:scale: 50%
Features have been extensively exposed to keyboard shortcuts, so that
there is also appeal for experienced LAMMPS users for prototyping and
testing simulation setups.
Features
^^^^^^^^
@ -502,7 +506,7 @@ Here are a few highlights of LAMMPS-GUI
- Visualization of current state in Image Viewer (via calling :doc:`write_dump image <dump_image>`)
- Capture of images created via :doc:`dump image <dump_image>` in Slide show window
- Dialog to set variables, similar to the LAMMPS command-line flag '-v' / '-var'
- Support for GPU, INTEL, KOKKOS/OpenMP, OPENMAP, and OPT and accelerator packages
- Support for GPU, INTEL, KOKKOS/OpenMP, OPENMP, and OPT accelerator packages
Parallelization
^^^^^^^^^^^^^^^
@ -523,8 +527,8 @@ with CMake is required.
The LAMMPS-GUI has been successfully compiled and tested on:
- Ubuntu Linux 20.04LTS x86_64 using GCC 9, Qt version 5.12
- Fedora Linux 40 x86\_64 using GCC 14 and Clang 17, Qt version 5.15LTS
- Fedora Linux 40 x86\_64 using GCC 14, Qt version 6.7
- Fedora Linux 41 x86\_64 using GCC 14 and Clang 17, Qt version 5.15LTS
- Fedora Linux 41 x86\_64 using GCC 14, Qt version 6.8
- Apple macOS 12 (Monterey) and macOS 13 (Ventura) with Xcode on arm64 and x86\_64, Qt version 5.15LTS
- Windows 10 and 11 x86_64 with Visual Studio 2022 and Visual C++ 14.36, Qt version 5.15LTS
- Windows 10 and 11 x86_64 with Visual Studio 2022 and Visual C++ 14.40, Qt version 6.7

30
doc/src/compute_bond_local.rst
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@ -64,20 +64,32 @@ All these properties are computed for the pair of atoms in a bond,
whether the two atoms represent a simple diatomic molecule, or are part
of some larger molecule.
The value *dist* is the current length of the bond.
The values *dx*, *dy*, and *dz* are the xyz components of the
*distance* between the pair of atoms. This value is always the
distance from the atom of lower to the one with the higher id.
.. versionchanged:: TBD
The sign of *dx*, *dy*, *dz* is no longer determined by the atom IDs
of the bonded atoms but by their order in the bond list to be
consistent with *fx*, *fy*, and *fz*.
The value *dist* is the current length of the bond. The values *dx*,
*dy*, and *dz* are the :math:`(x,y,z)` components of the distance vector
:math:`\vec{x_i} - \vec{x_j}` between the atoms in the bond. The order
of the atoms is determined by the bond list and the respective atom-IDs
can be output with :doc:`compute property/local
<compute_property_local>`.
The value *engpot* is the potential energy for the bond,
based on the current separation of the pair of atoms in the bond.
The value *force* is the magnitude of the force acting between the
pair of atoms in the bond.
The value *force* is the magnitude of the force acting between the pair
of atoms in the bond, which is positive for a repulsive force and
negative for an attractive force.
The values *fx*, *fy*, and *fz* are the xyz components of
*force* between the pair of atoms in the bond. For bond styles that apply
non-central forces, such as :doc:`bond_style bpm/rotational
The values *fx*, *fy*, and *fz* are the :math:`(x,y,z)` components of
the force on the first atom *i* in the bond due to the second atom *j*.
Mathematically, they are obtained by multiplying the value of *force*
from above with a unit vector created from the *dx*, *dy*, and *dz*
components of the distance vector also described above. For bond styles
that apply non-central forces, such as :doc:`bond_style bpm/rotational
<bond_bpm_rotational>`, these values only include the :math:`(x,y,z)`
components of the normal force component.

30
doc/src/compute_pair_local.rst
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@ -56,19 +56,33 @@ force cutoff distance for that interaction, as defined by the
:doc:`pair_style <pair_style>` and :doc:`pair_coeff <pair_coeff>`
commands.
The value *dist* is the distance between the pair of atoms.
The values *dx*, *dy*, and *dz* are the :math:`(x,y,z)` components of the
*distance* between the pair of atoms. This value is always the
distance from the atom of higher to the one with the lower atom ID.
.. versionchanged:: TBD
The sign of *dx*, *dy*, *dz* is no longer determined by the value of
their atom-IDs but by their order in the neighbor list to be
consistent with *fx*, *fy*, and *fz*.
The value *dist* is the distance between the pair of atoms. The values
*dx*, *dy*, and *dz* are the :math:`(x,y,z)` components of the distance
vector :math:`\vec{x_i} - \vec{x_j}` between the pair of atoms. The
order of the atoms is determined by the neighbor list and the respective
atom-IDs can be output with :doc:`compute property/local
<compute_property_local>`.
The value *eng* is the interaction energy for the pair of atoms.
The value *force* is the force acting between the pair of atoms, which
is positive for a repulsive force and negative for an attractive
force. The values *fx*, *fy*, and *fz* are the :math:`(x,y,z)` components of
*force* on atom I. For pair styles that apply non-central forces,
such as :doc:`granular pair styles <pair_gran>`, these values only include
the :math:`(x,y,z)` components of the normal force component.
force.
The values *fx*, *fy*, and *fz* are the :math:`(x,y,z)` components of
the force vector on the first atom *i* of a pair in the neighbor list
due to the second atom *j*. Mathematically, they are obtained by
multiplying the value of *force* from above with a unit vector created
from the *dx*, *dy*, and *dz* components of the distance vector also
described above. For pair styles that apply non-central forces, such as
:doc:`granular pair styles <pair_gran>`, these values only include the
:math:`(x,y,z)` components of the normal force component.
A pair style may define additional pairwise quantities which can be
accessed as *p1* to *pN*, where :math:`N` is defined by the pair style.

2
doc/src/fix.rst
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@ -256,6 +256,7 @@ accelerated styles exist.
* :doc:`flow/gauss <fix_flow_gauss>` - Gaussian dynamics for constant mass flux
* :doc:`freeze <fix_freeze>` - freeze atoms in a granular simulation
* :doc:`gcmc <fix_gcmc>` - grand canonical insertions/deletions
* :doc:`gjf <fix_gjf>` - statistically correct Langevin temperature control using the GJ methods
* :doc:`gld <fix_gld>` - generalized Langevin dynamics integrator
* :doc:`gle <fix_gle>` - generalized Langevin equation thermostat
* :doc:`gravity <fix_gravity>` - add gravity to atoms in a granular simulation
@ -290,6 +291,7 @@ accelerated styles exist.
* :doc:`mvv/tdpd <fix_mvv_dpd>` - constant temperature DPD using the modified velocity-Verlet algorithm
* :doc:`neb <fix_neb>` - nudged elastic band (NEB) spring forces
* :doc:`neb/spin <fix_neb_spin>` - nudged elastic band (NEB) spring forces for spins
* :doc:`neighbor/swap <fix_neighbor_swap>` - kinetic Monte Carlo (kMC) atom swapping
* :doc:`nonaffine/displacement <fix_nonaffine_displacement>` - calculate nonaffine displacement of atoms
* :doc:`nph <fix_nh>` - constant NPH time integration via Nose/Hoover
* :doc:`nph/asphere <fix_nph_asphere>` - NPH for aspherical particles

208
doc/src/fix_gjf.rst Normal file
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@ -0,0 +1,208 @@
.. index:: fix gjf
fix gjf command
========================
Syntax
""""""
.. code-block:: LAMMPS
fix ID group-ID gjf Tstart Tstop damp seed keyword values ...
* ID, group-ID are documented in :doc:`fix <fix>` command
* gjf = style name of this fix command
* Tstart,Tstop = desired temperature at start/end of run (temperature units)
* Tstart can be a variable (see below)
* damp = damping parameter (time units)
* seed = random number seed to use for white noise (positive integer)
* zero or more keyword/value pairs may be appended
* keyword = *vel* or *method*
.. parsed-literal::
*vel* value = *vfull* or *vhalf*
*vfull* = use on-site velocity
*vhalf* = use half-step velocity
*method* value = *1-8*
*1-8* = choose one of the many GJ formulations
*7* = requires input of additional scalar between 0 and 1
Examples
""""""""
.. code-block:: LAMMPS
fix 3 boundary gjf 10.0 10.0 1.0 699483
fix 1 all gjf 10.0 100.0 100.0 48279 vel vfull method 4
fix 2 all gjf 10.0 10.0 1.0 26488 method 7 0.95
Description
"""""""""""
.. versionadded:: TBD
Apply a Langevin thermostat as described in :ref:`(Gronbech-Jensen-2020) <Gronbech-Jensen-2020>`
to a group of atoms which models an interaction with a background
implicit solvent. As described in the papers cited below, the GJ methods
provide exact diffusion, drift, and Boltzmann sampling for linear systems for
any time step within the stability limit. The purpose of this set of methods
is therefore to significantly improve statistical accuracy at longer time steps
compared to other thermostats.
The current implementation provides the user with the option to output
the velocity in one of two forms: *vfull* or *vhalf*. The option *vhalf*
outputs the 2GJ half-step velocity given in :ref:`Gronbech Jensen/Gronbech-Jensen
<Gronbech-Jensen-2019>`; for linear systems, this velocity is shown to not
have any statistical errors for any stable time step. The option *vfull*
outputs the on-site velocity given in :ref:`Gronbech-Jensen/Farago
<Gronbech-Jensen-Farago>`; this velocity is shown to be systematically lower
than the target temperature by a small amount, which grows
quadratically with the timestep. An overview of statistically correct Boltzmann
and Maxwell-Boltzmann sampling of true on-site and true half-step velocities is
given in :ref:`Gronbech-Jensen-2020 <Gronbech-Jensen-2020>`.
This fix allows the use of several GJ methods as listed in :ref:`Gronbech-Jensen-2020 <Gronbech-Jensen-2020>`.
The GJ-VII method is described in :ref:`Finkelstein <Finkelstein>` and GJ-VIII
is described in :ref:`Gronbech-Jensen-2024 <Gronbech-Jensen-2024>`.
The implementation follows the splitting form provided in Eqs. (24) and (25)
in :ref:`Gronbech-Jensen-2024 <Gronbech-Jensen-2024>`, including the application
of Gaussian noise values, per the description in
:ref:`Gronbech-Jensen-2023 <Gronbech-Jensen-2023>`.
.. note::
Unlike the :doc:`fix langevin <fix_langevin>` command which performs force
modifications only, this fix performs thermostatting and time integration.
Thus you no longer need a separate time integration fix, like :doc:`fix nve <fix_nve>`.
See the :doc:`Howto thermostat <Howto_thermostat>` page for
a discussion of different ways to compute temperature and perform
thermostatting.
The desired temperature at each timestep is a ramped value during the
run from *Tstart* to *Tstop*\ .
*Tstart* can be specified as an equal-style or atom-style
:doc:`variable <variable>`. In this case, the *Tstop* setting is
ignored. If the value is a variable, it should be specified as
v_name, where name is the variable name. In this case, the variable
will be evaluated each timestep, and its value used to determine the
target temperature.
Equal-style variables can specify formulas with various mathematical
functions, and include :doc:`thermo_style <thermo_style>` command
keywords for the simulation box parameters and timestep and elapsed
time. Thus it is easy to specify a time-dependent temperature.
Atom-style variables can specify the same formulas as equal-style
variables but can also include per-atom values, such as atom
coordinates. Thus it is easy to specify a spatially-dependent
temperature with optional time-dependence as well.
Like other fixes that perform thermostatting, this fix can be used
with :doc:`compute commands <compute>` that remove a "bias" from the
atom velocities. E.g. to apply the thermostat only to atoms within a
spatial :doc:`region <region>`, or to remove the center-of-mass
velocity from a group of atoms, or to remove the x-component of
velocity from the calculation.
This is not done by default, but only if the :doc:`fix_modify
<fix_modify>` command is used to assign a temperature compute to this
fix that includes such a bias term. See the doc pages for individual
:doc:`compute temp commands <compute>` to determine which ones include
a bias.
The *damp* parameter is specified in time units and determines how
rapidly the temperature is relaxed. For example, a value of 100.0 means
to relax the temperature in a timespan of (roughly) 100 time units
(:math:`\tau` or fs or ps - see the :doc:`units <units>` command). The
damp factor can be thought of as inversely related to the viscosity of
the solvent. I.e. a small relaxation time implies a high-viscosity
solvent and vice versa. See the discussion about :math:`\gamma` and
viscosity in the documentation for the :doc:`fix viscous <fix_viscous>`
command for more details.
The random # *seed* must be a positive integer. A Marsaglia random
number generator is used. Each processor uses the input seed to
generate its own unique seed and its own stream of random numbers.
Thus the dynamics of the system will not be identical on two runs on
different numbers of processors.
----------
The keyword/value option pairs are used in the following ways.
The keyword *vel* determines which velocity is used to determine
quantities of interest in the simulation.
The keyword *method* selects one of the eight GJ-methods implemented in LAMMPS.
----------
Restart, fix_modify, output, run start/stop, minimize info
"""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
No information about this fix is written to :doc:`binary restart files <restart>`.
Because the state of the random number generator is not saved in restart files,
this means you cannot do "exact" restarts with this fix, where the simulation
continues on the same as if no restart had taken place. However, in a
statistical sense, a restarted simulation should produce the same behavior.
Additionally, the GJ methods implement noise exclusively within each time step
(unlike the BBK thermostat of the fix-langevin). The restart is done with
either vfull or vhalf velocity output for as long as the choice of vfull/vhalf
is the same for the simulation as it is in the restart file.
The :doc:`fix_modify <fix_modify>` *temp* option is supported by this
fix. You can use it to assign a temperature :doc:`compute <compute>`
you have defined to this fix which will be used in its thermostatting
procedure, as described above. For consistency, the group used by
this fix and by the compute should be the same.
This fix can ramp its target temperature over multiple runs, using the
*start* and *stop* keywords of the :doc:`run <run>` command. See the
:doc:`run <run>` command for details of how to do this.
This fix is not invoked during :doc:`energy minimization <minimize>`.
Restrictions
""""""""""""
This fix is not compatible with run_style respa. It is not compatible with
accelerated packages such as KOKKOS.
Related commands
""""""""""""""""
:doc:`fix langevin <fix_langevin>`, :doc:`fix nvt <fix_nh>`
Default
"""""""
The option defaults are vel = vhalf, method = 1.
----------
.. _Gronbech-Jensen-2020:
**(Gronbech-Jensen-2020)** Gronbech-Jensen, Mol Phys 118, e1662506 (2020).
.. _Gronbech-Jensen-2019:
**(Gronbech Jensen/Gronbech-Jensen)** Gronbech Jensen and Gronbech-Jensen, Mol Phys, 117, 2511 (2019)
.. _Gronbech-Jensen-Farago:
**(Gronbech-Jensen/Farago)** Gronbech-Jensen and Farago, Mol Phys, 111, 983 (2013).
.. _Finkelstein:
**(Finkelstein)** Finkelstein, Cheng, Florin, Seibold, Gronbech-Jensen, J. Chem. Phys., 155, 18 (2021)
.. _Gronbech-Jensen-2024:
**(Gronbech-Jensen-2024)** Gronbech-Jensen, J. Stat. Phys. 191, 137 (2024).
.. _Gronbech-Jensen-2023:
**(Gronbech-Jensen-2023)** Gronbech-Jensen, J. Stat. Phys. 190, 96 (2023).

19
doc/src/fix_langevin.rst
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@ -56,7 +56,7 @@ Examples
Description
"""""""""""
Apply a Langevin thermostat as described in :ref:`(Schneider) <Schneider1>`
Apply a Langevin thermostat as described in :ref:`(Bruenger) <Bruenger1>`
to a group of atoms which models an interaction with a background
implicit solvent. Used with :doc:`fix nve <fix_nve>`, this command
performs Brownian dynamics (BD), since the total force on each atom
@ -241,6 +241,13 @@ to zero by subtracting off an equal part of it from each atom in the
group. As a result, the center-of-mass of a system with zero initial
momentum will not drift over time.
.. deprecated:: TDB
The *gjf* keyword in fix langevin is deprecated and will be removed
soon. The GJF functionality has been moved to its own fix style
:doc:`fix gjf <fix_gjf>` and it is strongly recommended to use that
fix instead.
The keyword *gjf* can be used to run the :ref:`Gronbech-Jensen/Farago
<Gronbech-Jensen>` time-discretization of the Langevin model. As
described in the papers cited below, the purpose of this method is to
@ -324,14 +331,16 @@ types, tally = no, zero = no, gjf = no.
----------
.. _Bruenger1:
**(Bruenger)** Bruenger, Brooks, and Karplus, Chem. Phys. Lett. 105, 495 (1982).
[Previously attributed to Schneider and Stoll, Phys. Rev. B 17, 1302 (1978).
Implementation remains unchanged.]
.. _Dunweg1:
**(Dunweg)** Dunweg and Paul, Int J of Modern Physics C, 2, 817-27 (1991).
.. _Schneider1:
**(Schneider)** Schneider and Stoll, Phys Rev B, 17, 1302 (1978).
.. _Gronbech-Jensen:
**(Gronbech-Jensen)** Gronbech-Jensen and Farago, Mol Phys, 111, 983

264
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@ -0,0 +1,264 @@
.. index:: fix neighbor/swap
fix neighbor/swap command
=========================
Syntax
""""""
.. code-block:: LAMMPS
fix ID group-ID neighbor/swap N X seed T R0 voro-ID keyword values ...
* ID, group-ID are documented in :doc:`fix <fix>` command
* neighbor/swap = style name of this fix command
* N = invoke this fix every N steps
* X = number of swaps to attempt every N steps
* seed = random # seed (positive integer)
* T = scaling temperature of the MC swaps (temperature units)
* R0 = scaling swap probability of the MC swaps (distance units)
* voro-ID = valid voronoi compute id (compute voronoi/atom)
* one or more keyword/value pairs may be appended to args
* keywords *types* and *diff* are mutually exclusive, but one must be specified
* keyword = *types* or *diff* or *ke* or *region* or *rates*
.. parsed-literal::
*types* values = two or more atom types (Integers in range [1,Ntypes] or type labels)
*diff* values = one atom type
*ke* value = *yes* or *no*
*yes* = kinetic energy is conserved after atom swaps
*no* = no conservation of kinetic energy after atom swaps
*region* value = region-ID
region-ID = ID of region to use as an exchange/move volume
*rates* values = V1 V2 . . . Vntypes values to conduct variable diffusion for different atom types (unitless)
Examples
""""""""
.. code-block:: LAMMPS
compute voroN all voronoi/atom neighbors yes
fix mc all neighbor/swap 10 160 15238 1000.0 3.0 voroN diff 2
fix myFix all neighbor/swap 100 1 12345 298.0 3.0 voroN region my_swap_region types 5 6
fix kmc all neighbor/swap 1 100 345 1.0 3.0 voroN diff 3 rates 3 1 6
Description
"""""""""""
.. versionadded:: TBD
This fix performs Monte-Carlo (MC) evaluations to enable kinetic
Monte Carlo (kMC)-type behavior during MD simulation by allowing
neighboring atoms to swap their positions. In contrast to the :doc:`fix
atom/swap <fix_atom_swap>` command which swaps pairs of atoms anywhere
in the simulation domain, the restriction of the MC swapping to
neighbors enables a hybrid MD/kMC-like simulation.
Neighboring atoms are defined by using a Voronoi tesselation performed
by the :doc:`compute voronoi/atom <compute_voronoi_atom>` command.
Two atoms are neighbors if their Voronoi cells share a common face
(3d) or edge (2d).
The selection of a swap neighbor is made using a distance-based
criterion for weighting the selection probability of each swap, in the
same manner as kMC selects a next event using relative probabilities.
The acceptance or rejection of each swap is determined via the
Metropolis criterion after evaluating the change in system energy due
to the swap.
A detailed explanation of the original implementation of this
algorithm can be found in :ref:`(Tavenner 2023) <TavennerMDkMC>`
where it was used to simulated accelerated diffusion in an MD context.
Simulating inherently kinetically-limited behaviors which rely on rare
events (such as atomic diffusion in a solid) is challenging for
traditional MD since its relatively short timescale will not naturally
sample many events. This fix addresses this challenge by allowing rare
neighbor hopping events to be sampled in a kMC-like fashion at a much
faster rate (set by the specified *N* and *X* parameters). This enables
the processes of atomic diffusion to be approximated during an MD
simulation, effectively decoupling the MD atomic vibrational timescale
and the atomic hopping (kMC event) timescale.
The algorithm implemented by this fix is as follows:
- The MD simulation is paused every *N* steps
- A Voronoi tesselation is performed for the current atom configuration.
- Then *X* atom swaps are attempted, one after the other.
- For each swap, an atom *I* is selected randomly from the list of
atom types specified by either the *types* or *diff* keywords.
- One of *I*'s Voronoi neighbors *J* is selected using the
distance-weighted probability for each neighbor detailed below.
- The *I,J* atom IDs are communicated to all processors so that a
global energy evaluation can be performed for the post-swap state
of the system.
- The swap is accepted or rejected based on the Metropolis criterion
using the energy change of the system and the specified temperature
*T*.
Here are a few comments on the computational cost of the swapping
algorithm.
1. The cost of a global energy evaluation is similar to that of an MD
timestep.
2. Similar to other MC algorithms in LAMMPS, improved parallel
efficiency is achieved with a smaller number of atoms per
processor than would typically be used in an standard MD
simulation. This is because the per-energy evaluation cost
increases relative to the balance of MD/MC steps as indicated by
1., but the communication cost remains relatively constant for a
given number of MD steps.
3. The MC portion of the simulation will run dramatically slower if
the pair style uses different cutoffs for different atom types (or
type pairs). This is because each atom swap then requires a
rebuild of the neighbor list to ensure the post-swap global energy
can be computed correctly.
Limitations are imposed on selection of *I,J* atom pairs to avoid
swapping of atoms which are outside of a reasonable cutoff (e.g. due to
a Voronoi tesselation near free surfaces) though the use of a
distance-weighted probability scaling.
----------
This section gives more details on other arguments and keywords.
The random number generator (RNG) used by all the processors for MC
operations is initialized with the specified *seed*.
The distance-based probability is weighted by the specified *R0* which
sets the radius :math:`r_0` in this formula
.. math::
p_{ij} = e^{(\frac{r_{ij}}{r_0})^2}
where :math:`p_{ij}` is the probability of selecting atom :math:`j` to
swap with atom :math:`i`. Typically, a value for *R0* around the
average nearest-neighbor spacing is appropriate. Since this is simply a
probability weighting, the swapping behavior is not very sensitive to
the exact value of *R0*.
The required *voro-ID* value is the compute-ID of a
:doc:`compute voronoi/atom <compute_voronoi_atom>` command like
this:
.. code-block:: LAMMPS
compute compute-ID group-ID voronoi/atom neighbors yes
It must return per-atom list of valid neighbor IDs as in the
:doc:`compute voronoi/atom <compute_voronoi_atom>` command.
The keyword *types* takes two or more atom types as its values. Only
atoms *I* of the first atom type will be selected. Only atoms *J* of the
remaining atom types will be considered as potential swap partners.
The keyword *diff* take a single atom type as its value. Only atoms
*I* of the that atom type will be selected. Atoms *J* of all
remaining atom types will be considered as potential swap partners.
This includes the atom type specified with the *diff* keyword to
account for self-diffusive hops between two atoms of the same type.
Note that the *neighbors yes* option must be enabled for use with this
fix. The group-ID should include all the atoms which this fix will
potentially select. I.e. the group-ID used in the voronoi compute should
include the same atoms as that indicated by the *types* keyword. If the
*diff* keyword is used, the group-ID should include atoms of all types
in the simulation.
The keyword *ke* takes *yes* (default) or *no* as its value. It two
atoms are swapped with different masses, then a value of *yes* will
rescale their respective velocities to conserve the kinetic energy of
the system. A value of *no* will perform no rescaling, so that
kinetic energy is not conserved. See the restriction on this keyword
below.
The *region* keyword takes a *region-ID* as its value. If specified,
then only atoms *I* and *J* within the geometric region will be
considered as swap partners. See the :doc:`region <region>` command
for details. This means the group-ID for the :doc:`compute
voronoi/atom <compute_voronoi_atom>` command also need only contain
atoms within the region.
The keyword *rates* can modify the swap rate based on the type of atom
*J*. Ntype values must be specified, where Ntype = the number of atom
types in the system. Each value is used to scale the probability
weighting given by the equation above. In the third example command
above, a simulation has 3 atoms types. Atom *I*s of type 1 are
eligible for swapping. Swaps may occur with atom *J*s of all 3 types.
Assuming all *J* atoms are equidistant from an atom *I*, *J* atoms of
type 1 will be 3x more likely to be selected as a swap partner than
atoms of type 2. And *J* atoms of type 3 will be 6.5x more likely to
be selected than atoms of type 2. If the *rates* keyword is not used,
all atom types will be treated with the same probability during selection
of swap attempts.
Restart, fix_modify, output, run start/stop, minimize info
""""""""""""""""""""""""""""""""""""""""""""""""""""""""""
This fix writes the state of the fix to :doc:`binary restart files
<restart>`. This includes information about the random number generator
seed, the next timestep for MC exchanges, and the number of exchange
attempts and successes. See the :doc:`read_restart <read_restart>`
command for info on how to re-specify a fix in an input script that
reads a restart file, so that the operation of the fix continues in an
uninterrupted fashion.
None of the :doc:`fix_modify <fix_modify>` options are relevant to this
fix.
This fix computes a global vector of length 2, which can be accessed
by various :doc:`output commands <Howto_output>`. The vector values are
the following global cumulative quantities:
#. swap attempts
#. swap accepts
The vector values calculated by this fix are "intensive".
No parameter of this fix can be used with the *start/stop* keywords of
the :doc:`run <run>` command. This fix is not invoked during
:doc:`energy minimization <minimize>`.
Restrictions
""""""""""""
This fix is part of the MC package. It is only enabled if LAMMPS was
built with that package. See the :doc:`Build package <Build_package>`
doc page for more info. Also this fix requires that the :ref:`VORONOI
package <PKG-VORONOI>` is installed, otherwise the fix will not be
compiled.
The :doc:`compute voronoi/atom <compute_voronoi_atom>` command
referenced by the required voro-ID must return neighboring atoms as
illustrated in the examples above.
If this fix is used with systems that do not have per-type masses
(e.g. atom style sphere), the *ke* keyword must be set to *off* since
the implemented algorithm will not be able to re-scale velocities
properly.
Related commands
""""""""""""""""
:doc:`fix nvt <fix_nh>`, :doc:`compute voronoi/atom <compute_voronoi_atom>`
:doc:`delete_atoms <delete_atoms>`, :doc:`fix gcmc <fix_gcmc>`,
:doc:`fix atom/swap <fix_atom_swap>`, :doc:`fix mol/swap <fix_mol_swap>`,
:doc:`fix sgcmc <fix_sgcmc>`
Default
"""""""
The option defaults are *ke* = yes and *rates* = 1 for all atom types.
----------
.. _TavennerMDkMC:
**(Tavenner 2023)** J Tavenner, M Mendelev, J Lawson, Computational
Materials Science, 218, 111929 (2023).

31
doc/src/fix_qeq_rel_reaxff.rst
View File

@ -37,18 +37,18 @@ Examples
Description
"""""""""""
.. versionadded:: 19Nov2024
.. versionadded:: 2Apr2025
This fix implements the QEqR method for charge equilibration, which
differs from the QEq charge equilibration method :ref:`(Rappe and
Goddard) <Rappe4>` only in how external electric fields are accounted
for. This fix therefore raises a warning when used without :doc:`fix
efield <fix_efield>` since :doc:`fix qeq/reaxff <fix_qeq_reaxff>` should
be used without an external electric field. Charges are computed with
the QEqR method by minimizing the electrostatic energy of the system in
the same way as the QEq method but where the absolute electronegativity,
:math:`\chi_i`, of each atom in the QEq method is replaced with an
effective electronegativity given by
This fix implements the QEqR method :ref:`(Lalli) <lalli2>` for charge
equilibration, which differs from the QEq charge equilibration method
:ref:`(Rappe and Goddard) <Rappe4>` only in how external electric fields
are accounted for. This fix therefore raises a warning when used without
:doc:`fix efield <fix_efield>` since :doc:`fix qeq/reaxff <fix_qeq_reaxff>`
should be used when no external electric field is present. Charges are
computed with the QEqR method by minimizing the electrostatic energy of
the system in the same way as the QEq method but where the absolute
electronegativity, :math:`\chi_i`, of each atom in the QEq method is
replaced with an effective electronegativity given by
.. math::
\chi_{\mathrm{r}i} = \chi_i + \frac{\sum_{j=1}^{N} \beta(\phi_i - \phi_j) S_{ij}}
@ -61,8 +61,9 @@ external electric field and :math:`S_{ij}` is the overlap integral
between atoms :math:`i` and :math:`j`. This formulation is advantageous
over the method used by :doc:`fix qeq/reaxff <fix_qeq_reaxff>` to
account for an external electric field in that it permits periodic
boundaries in the direction of an external electric field and in that it
does not worsen long-range charge transfer seen with QEq.
boundaries in the direction of an external electric field and in
that it does not worsen long-range charge transfer seen with
QEq. See :ref:`Lalli <lalli2>` for further details.
This fix is typically used in conjunction with the ReaxFF force field
model as implemented in the :doc:`pair_style reaxff <pair_reaxff>`
@ -184,6 +185,10 @@ scale = 1.0 and maxiter = 200
----------
.. _lalli2:
**(Lalli)** Lalli and Giusti, Journal of Chemical Physics, 162, 174311 (2025).
.. _Rappe4:
**(Rappe)** Rappe and Goddard III, Journal of Physical Chemistry, 95,

11
doc/src/fix_qtpie_reaxff.rst
View File

@ -59,8 +59,7 @@ and atom :math:`j`.
The effect of an external electric field can be incorporated into the QTPIE
method by modifying the absolute or effective electronegativities of each
atom :ref:`(Chen) <qtpie-Chen>`. This fix models the effect of an external
electric field by using the effective electronegativity given in
:ref:`(Gergs) <Gergs>`:
electric field by using the effective electronegativity :ref:`(Lalli) <lalli>`
.. math::
\tilde{\chi}_{\mathrm{r}i} = \frac{\sum_{j=1}^{N} (\chi_i - \chi_j + \beta(\phi_i - \phi_j)) S_{ij}}
@ -68,7 +67,8 @@ electric field by using the effective electronegativity given in
where :math:`\beta` is a scaling factor and :math:`\phi_i` and :math:`\phi_j`
are the electric potentials at the positions of atoms :math:`i` and :math:`j`
due to the external electric field.
due to the external electric field. Additional details regarding the
implementation and performance of this fix are provided in :ref:`Lalli <lalli>`.
This fix is typically used in conjunction with the ReaxFF force
field model as implemented in the :doc:`pair_style reaxff <pair_reaxff>`
@ -206,10 +206,9 @@ scale = 1.0 and maxiter = 200
**(Chen)** Chen, Jiahao. Theory and applications of fluctuating-charge models.
University of Illinois at Urbana-Champaign, 2009.
.. _Gergs:
.. _lalli:
**(Gergs)** Gergs, Dirkmann and Mussenbrock.
Journal of Applied Physics 123.24 (2018).
**(Lalli)** Lalli and Giusti, Journal of Chemical Physics, 162, 174311 (2025).
.. _qeq-Aktulga2:

43
doc/src/fix_sgcmc.rst
View File

@ -30,7 +30,9 @@ Syntax
N = number of times sampling window is moved during one MC cycle
*window_size* frac
frac = size of sampling window (must be between 0.5 and 1.0)
*atomic/energy* yes/no
yes = use the atomic energy method to calculate energy changes
no = use the default method to calculate energy changes
Examples
""""""""
@ -127,6 +129,14 @@ The number of times the window is moved during a MC cycle is set using
the parameter *window_moves* (see Sect. III.B in :ref:`Sadigh1
<Sadigh1>` for details).
The *atomic/energy* keyword controls which method is used for calculating
the energy change when atom types are swapped. A value of *no*
uses the default method, see discussion below in Restrictions section.
A value of *yes* uses the atomic energy method,
if the method has been implemented for the LAMMPS energy model,
otherwise LAMMPS will exit with an error message.
So far this has only been implemented for EAM type potentials.
------------
Restart, fix_modify, output, run start/stop, minimize info
@ -159,16 +169,26 @@ page for more info.
This fix style requires an :doc:`atom style <atom_style>` with per atom
type masses.
At present the fix provides optimized subroutines for EAM type
potentials (see above) that calculate potential energy changes due to
*local* atom type swaps very efficiently. Other potentials are
supported by using the generic potential functions. This, however, will
lead to exceedingly slow simulations since it implies that the
energy of the *entire* system is recomputed at each MC trial step. If
other potentials are to be used it is strongly recommended to modify and
optimize the existing generic potential functions for this purpose.
Also, the generic energy calculation can not be used for parallel
execution i.e. it only works with a single MPI process.
The fix provides three methods for calculating the potential energy
change due to atom type swaps. For EAM type potentials, the default
method is a carefully optimized local energy change calculation that
is part of the source code for this fix. It takes advantage of the
specific computational and communication requirements of EAM. Customizing
the local method to handle other energy models such as Tersoff has been done,
but these cases are not supported in the public LAMMPS code.
For all other LAMMPS energy models, the default method calculates
the *total* potential energy of the system before and after each
atom type swap. This method does not depend on the details of the
energy model and so is guaranteed to be correct. It is also
orders of magnitude slower than the custom EAM calculation.
In addition, it can not be used with parallel execution i.e. only
a single MPI process is allowed.
The third method uses the *atomic/energy* keyword described above.
This allows parallel execution and it is also a local calculation,
making it only a bit slower than a fully-optimized local calculation.
So far, this has been implemented for EAM type potentials.
It is straightforward to extend this to other potentials,
requiring adding an atomic energy method to the pair style.
------------
@ -180,6 +200,7 @@ The optional parameters default to the following values:
* *randseed* = 324234
* *window_moves* = 8
* *window_size* = automatic
* *atomic/energy* = no
------------

64
doc/src/pair_granular.rst
View File

@ -44,7 +44,7 @@ Examples
pair_coeff * * hertz 1000.0 50.0 tangential mindlin 1000.0 1.0 0.4 heat area 0.1
pair_style granular
pair_coeff * * mdr 5e6 0.4 1.9e5 2.0 0.5 0.5 tangential linear_history 940.0 0.0 0.7 rolling sds 2.7e5 0.0 0.6 damping none
pair_coeff * * mdr 5e6 0.4 1.9e5 2.0 0.5 0.5 tangential linear_history 940.0 1.0 0.7 rolling sds 2.7e5 0.0 0.6 damping mdr 1
Description
"""""""""""
@ -88,7 +88,8 @@ and their required arguments are:
3. *hertz/material* : E, :math:`\eta_{n0}` (or :math:`e`), :math:`\nu`
4. *dmt* : E, :math:`\eta_{n0}` (or :math:`e`), :math:`\nu`, :math:`\gamma`
5. *jkr* : E, :math:`\eta_{n0}` (or :math:`e`), :math:`\nu`, :math:`\gamma`
6. *mdr* : :math:`E`, :math:`\nu`, :math:`Y`, :math:`\Delta\gamma`, :math:`\psi_b`, :math:`e`
6. *mdr* : :math:`E`, :math:`\nu`, :math:`Y`, :math:`\Delta\gamma`,
:math:`\psi_b`, :math:`\eta_{n0}`
Here, :math:`k_n` is spring stiffness (with units that depend on model
choice, see below); :math:`\eta_{n0}` is a damping prefactor (or, in its
@ -177,6 +178,8 @@ two-part series :ref:`Zunker and Kamrin Part I <Zunker2024I>` and
:ref:`Zunker and Kamrin Part II <Zunker2024II>`. Further development
and demonstrations of its application to industrially relevant powder
compaction processes are presented in :ref:`Zunker et al. <Zunker2025>`.
If you use the *mdr* normal model the only supported damping option is
the *mdr* damping class described below.
The model requires the following inputs:
@ -200,8 +203,8 @@ The model requires the following inputs:
triggered. Lower values of :math:`\psi_b` delay the onset of the bulk elastic
response.
6. *Coefficient of restitution* :math:`0 \le e \le 1` : The coefficient of
restitution is a tunable parameter that controls damping in the normal direction.
6. *Damping coefficent* :math:`\eta_{n0} \ge 0` : The damping coefficient
is a tunable parameter that controls damping in the normal direction.
.. note::
@ -213,18 +216,12 @@ The *mdr* model produces a nonlinear force-displacement response, therefore the
critical timestep :math:`\Delta t` depends on the inputs and level of
deformation. As a conservative starting point the timestep can be assumed to be
dictated by the bulk elastic response such that
:math:`\Delta t = 0.35\sqrt{m/k_\textrm{bulk}}`, where :math:`m` is the mass of
:math:`\Delta t = 0.08\sqrt{m/k_\textrm{bulk}}`, where :math:`m` is the mass of
the smallest particle and :math:`k_\textrm{bulk} = \kappa R_\textrm{min}` is an
effective stiffness related to the bulk elastic response.
Here, :math:`\kappa = E/(3(1-2\nu))` is the bulk modulus and
:math:`R_\textrm{min}` is the radius of the smallest particle.
.. note::
The *mdr* model requires some specific settings to function properly,
please read the following text carefully to ensure all requirements are
followed.
The *atom_style* must be set to *sphere 1* to enable dynamic particle
radii. The *mdr* model is designed to respect the incompressibility of
plastic deformation and inherently tracks free surface displacements
@ -253,13 +250,6 @@ algorithm see :ref:`Zunker et al. <Zunker2025>`.
newton off
The damping model must be set to *none*. The *mdr* model already has a built
in damping model.
.. code-block:: LAMMPS
pair_coeff * * mdr 5e6 0.4 1.9e5 2 0.5 0.5 damping none
The definition of multiple *mdr* models in the *pair_style* is currently not
supported. Similarly, the *mdr* model cannot be combined with a different normal
model in the *pair_style*. Physically this means that only one homogeneous
@ -270,7 +260,7 @@ The *mdr* model currently only supports *fix wall/gran/region*, not
any *fix wall/gran/region* commands must also use the *mdr* model.
Additionally, the following *mdr* inputs must match between the
*pair_style* and *fix wall/gran/region* definitions: :math:`E`,
:math:`\nu`, :math:`Y`, :math:`\psi_b`, and :math:`e`. The exception
:math:`\nu`, :math:`Y`, :math:`\psi_b`, and :math:`\eta_{n0}`. The exception
is :math:`\Delta\gamma`, which may vary, permitting different
adhesive behaviors between particle-particle and particle-wall interactions.
@ -336,6 +326,7 @@ for the damping model currently supported are:
3. *viscoelastic*
4. *tsuji*
5. *coeff_restitution*
6. *mdr* (class) : :math:`d_{type}`
If the *damping* keyword is not specified, the *viscoelastic* model is
used by default.
@ -425,6 +416,37 @@ the damping coefficient, it accurately reproduces the specified coefficient of
restitution for both monodisperse and polydisperse particle pairs. This damping
model is not compatible with cohesive normal models such as *JKR* or *DMT*.
The *mdr* damping class contains multiple damping models that can be toggled between
by specifying different integer values for the :math:`d_{type}` input parameter. This
damping option is only compatible with the normal *mdr* contact model.
Setting :math:`d_{type} = 1` is the suggested damping option. This specifies a damping
model that takes into account the contact stiffness :math:`k_{mdr}` calculated
by the normal *mdr* contact model to determine the damping coefficient:
.. math::
\eta_n = \eta_{n0} (m_{eff}k_{mdr})^{1/2},
where :math:`k_{mdr}` is proportional to contact radius :math:`a_{mdr}` tracked by the
normal *mdr* contact model:
.. math::
k_{mdr} = 2 E_{eff} a_{mdr}.
In this case, :math:`\eta_{n0}` is simply a dimensionless coefficient that scales the
the overall damping coefficient.
The other supported option is :math:`d_{type} = 2`, which defines a simple damping model
similar to the *velocity* option
.. math::
\eta_n = \eta_{n0},
but has additional checks to avoid non-physical damping after plastic deformation.
The total normal force is computed as the sum of the elastic and
damping components:
@ -1068,8 +1090,8 @@ a bulk elastic response. Journal of the Mechanics and Physics of Solids,
**(Zunker et al, 2025)** Zunker, W., Dunatunga, S., Thakur, S.,
Tang, P., & Kamrin, K. (2025). Experimentally validated DEM for large
deformation powder compaction: mechanically-derived contact model and
screening of non-physical contacts.
deformation powder compaction: Mechanically-derived contact model and
screening of non-physical contacts. Powder Technology, 120972.
.. _Luding2008:

23
doc/src/pair_lj_smooth.rst
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@ -48,13 +48,19 @@ At the inner cutoff the force and its first derivative
will match the non-smoothed LJ formula. At the outer cutoff the force
and its first derivative will be 0.0. The inner cutoff cannot be 0.0.
Explicit expressions for the coefficients C1, C2, C3, C4, as well as the
energy discontinuity at the cutoff can be found here :ref:`(Leoni_1) <Leoni_1>`
and here :ref:`(Leoni_2) <Leoni_2>`
.. note::
this force smoothing causes the energy to be discontinuous both
in its values and first derivative. This can lead to poor energy
conservation and may require the use of a thermostat. Plot the energy
and force resulting from this formula via the
:doc:`pair_write <pair_write>` command to see the effect.
conservation and may require the use of a thermostat. The energy
value discontinuity can be eliminated by shifting the potential
energy to be zero at the outer cutoff using the pair_modify shift
option. With or without shifting, you can plot the resulting energy
and force via the :doc:`pair_write <pair_write>` command to see the effect.
The following coefficients must be defined for each pair of atoms
types via the :doc:`pair_coeff <pair_coeff>` command as in the examples
@ -122,3 +128,14 @@ Default
"""""""
none
----------
.. _Leoni_1:
**(Leoni_1)** F. Leoni et al., Phys Rev Lett, 134, 128201 (2025).
.. _Leoni_2:
**(Leoni_2)** F. Leoni et al., Phys Rev Lett, 134, Supplementary Material (2025).

23
doc/utils/sphinx-config/false_positives.txt
View File

@ -103,6 +103,7 @@ Amit
amsmath
amu
Amzallag
Anandakrishnan
analytical
Anders
Andric
@ -110,6 +111,7 @@ Andrienko
Andzelm
Ang
anglegrad
anglelist
angleoffset
angletangrad
angmom
@ -347,6 +349,7 @@ Bomont
BondAngle
BondBond
bondchk
bondlist
bondmax
bondscreened
bondscreenedspin
@ -395,6 +398,7 @@ Broglie
brownian
brownw
Broyden
Bruenger
Bruskin
Brusselle
Bryantsev
@ -819,6 +823,7 @@ diffusively
diffusivities
diffusivity
dihedral
dihedrallist
dihedrals
Dihedrals
dihydride
@ -1197,6 +1202,7 @@ filesystem
filesystems
Fily
Fincham
Finkelstein
Fint
fingerprintconstants
fingerprintsperelement
@ -1323,7 +1329,6 @@ Geocomputing
georg
Georg
Geotechnica
Gergs
germain
Germann
Germano
@ -1351,6 +1356,8 @@ Gillan
Gingold
Gissinger
github
Giusti
GJ
gjf
gjwagne
gl
@ -1609,6 +1616,7 @@ imagename
imd
Impey
impl
improperlist
impropers
Impropers
imulator
@ -1725,6 +1733,7 @@ Iyz
iz
izcm
ized
Izadi
Izrailev
Izumi
Izvekov
@ -1853,6 +1862,7 @@ Kloss
Kloza
kmax
Kmax
kMC
KMP
kmu
Knizhnik
@ -1917,6 +1927,7 @@ Lachet
Lackmann
Ladd
lagrangian
Lalli
lambdai
LambdaLanczos
Lambrecht
@ -1979,6 +1990,7 @@ lennard
Lennard
Lenosky
Lenz
Leoni
Lett
Leuven
Leven
@ -2477,6 +2489,7 @@ namespaces
nan
NaN
Nandor
nanglelist
nangles
Nangletype
nangletypes
@ -2513,6 +2526,7 @@ nbodies
nbody
Nbody
nbond
nbondlist
nbonds
nbondtype
Nbondtype
@ -2534,6 +2548,7 @@ ncount
nd
ndactrung
ndescriptors
ndihedrallist
ndihedrals
Ndihedraltype
ndihedraltypes
@ -2591,6 +2606,7 @@ NiAlH
Nicklas
Niklasson
Nikolskiy
nimproperlist
nimpropers
Nimpropertype
nimpropertypes
@ -2795,6 +2811,7 @@ oneMKL
oneway
onlysalt
ons
Onufriev
OO
Oord
opencl
@ -3463,6 +3480,7 @@ sectoring
sed
Seddon
segmental
Seibold
Seifert
Seleson
sellerio
@ -4082,9 +4100,11 @@ versa
Verstraelen
ves
vf
vfull
vflag
vflow
vfrac
vhalf
vhi
vibrational
Vij
@ -4116,6 +4136,7 @@ volpress
volumetric
von
Voro
voro
Vorobyov
voronoi
Voronoi

1
examples/COUPLE/plugin/liblammpsplugin.c
View File

@ -144,6 +144,7 @@ liblammpsplugin_t *liblammpsplugin_load(const char *lib)
ADDSYM(find_pair_neighlist);
ADDSYM(find_fix_neighlist);
ADDSYM(find_compute_neighlist);
ADDSYM(request_single_neighlist);
ADDSYM(neighlist_num_elements);
ADDSYM(neighlist_element_neighbors);

18
examples/COUPLE/plugin/liblammpsplugin.h
View File

@ -94,6 +94,17 @@ enum _LMP_VAR_CONST {
LMP_VAR_STRING = 3 /*!< return value will be a string (catch-all) */
};
/** Neighbor list settings constants
*
* Must be kept in sync with the equivalent constants in ``python/lammps/constants.py``,
* ``fortran/lammps.f90``, ``tools/swig/lammps.i``, and
* ``examples/COUPLE/plugin/liblammpsplugin.h`` */
enum _LMP_NEIGH_CONST {
LMP_NEIGH_HALF = 0, /*!< request (default) half neighbor list */
LMP_NEIGH_FULL = 1, /*!< request full neighbor list */
};
#ifdef __cplusplus
extern "C" {
#endif
@ -189,14 +200,17 @@ struct _liblammpsplugin {
* caller must match to how LAMMPS library is built */
#if !defined(LAMMPS_BIGBIG)
int (*create_atoms)(void *, int, int *, int *, double *, double *, int *, int);
int (*create_atoms)(void *, int, const int *, const int *, const double *, const double *,
const int *, int);
#else
int (*create_atoms)(void *, int, int64_t *, int *, double *, double *, int64_t *, int);
int (*create_atoms)(void *, int, const int64_t *, const int *, const double *, const double *,
const int64_t *, int);
#endif
int (*find_pair_neighlist)(void *, const char *, int, int, int);
int (*find_fix_neighlist)(void *, const char *, int);
int (*find_compute_neighlist)(void *, const char *, int);
int (*request_single_neighlist)(void *, const char *, int, double);
int (*neighlist_num_elements)(void *, int);
void (*neighlist_element_neighbors)(void *, int, int, int *, int *, int **);

4
examples/PACKAGES/imd/in.bucky-plus-cnt
View File

@ -46,8 +46,8 @@ fix integrate mobile nve
fix thermostat mobile langevin 300.0 300.0 2000.0 234624
# IMD setup.
fix comm all imd 6789 unwrap on trate 10
#fix comm all imd 6789 unwrap on trate 10 nowait on
#fix comm all imd 6789 unwrap on trate 10
fix comm all imd 6789 unwrap on trate 10 nowait on
# temperature is based on mobile atoms only
compute mobtemp mobile temp

15
examples/PACKAGES/imd/in.bucky-plus-cnt-gpu
View File

@ -1,16 +1,20 @@
# stick a buckyball into a nanotube
# enable GPU package from within the input:
package gpu 0 pair/only on
suffix gpu
units real
dimension 3
boundary f f f
atom_style molecular
newton off
processors * * 1
# read topology
read_data data.bucky-plus-cnt
pair_style lj/cut/gpu 10.0
pair_style lj/cut 10.0
bond_style harmonic
angle_style charmm
dihedral_style charmm
@ -29,9 +33,6 @@ neigh_modify delay 0 every 1 check yes
timestep 2.0
# required for GPU acceleration
fix gpu all gpu force 0 0 1.0
# we only move some atoms.
group mobile type 1
@ -49,8 +50,8 @@ fix integrate mobile nve
fix thermostat mobile langevin 300.0 300.0 2000.0 234624
# IMD setup.
fix comm all imd 6789 unwrap on trate 10
#fix comm all imd 6789 unwrap on trate 10 nowait on
#fix comm all imd 6789 unwrap on trate 10
fix comm all imd 6789 unwrap on trate 10 nowait on
# temperature is based on mobile atoms only
compute mobtemp mobile temp

14
examples/PACKAGES/imd/in.deca-ala_imd-gpu
View File

@ -1,8 +1,12 @@
#
#
# enable GPU package from within the input:
package gpu 0 pair/only on
suffix gpu
units real
neighbor 2.5 bin
neigh_modify delay 1 every 1
newton off
atom_style full
bond_style harmonic
@ -10,20 +14,18 @@ angle_style charmm
dihedral_style charmm
improper_style harmonic
pair_style lj/charmm/coul/long/gpu 8 10
pair_style lj/charmm/coul/long 8 10
pair_modify mix arithmetic
special_bonds charmm
read_data data.deca-ala-solv
fix 0 all gpu force/neigh 0 0 1.0
group peptide id <= 103
fix rigidh all shake 1e-6 100 1000 t 1 2 3 4 5 a 23
thermo 100
thermo_style multi
timestep 2.0
kspace_style pppm/gpu 1e-5
kspace_style pppm 1e-5
fix ensemble all npt temp 300.0 300.0 100.0 iso 1.0 1.0 1000.0 drag 0.2

38
examples/PACKAGES/imd/in.melt_imd-gpu
View File

@ -1,30 +1,32 @@
# 3d Lennard-Jones melt
# 3d Lennard-Jones melt with GPU package acceleration
units lj
atom_style atomic
newton off
# enable GPU package from within the input:
package gpu 0
suffix gpu
lattice fcc 0.8442
region box block 0 10 0 10 0 10
create_box 1 box
create_atoms 1 box
mass 1 1.0
units lj
atom_style atomic
velocity all create 3.0 87287
lattice fcc 0.8442
region box block 0 10 0 10 0 10
create_box 1 box
create_atoms 1 box
mass 1 1.0
pair_style lj/cut/gpu 2.5
pair_coeff 1 1 1.0 1.0 2.5
velocity all create 3.0 87287
neighbor 0.3 bin
neigh_modify every 5 delay 10 check yes
pair_style lj/cut 2.5
pair_coeff 1 1 1.0 1.0 2.5
neighbor 0.3 bin
neigh_modify every 5 delay 10 check yes
thermo_style custom step pe ke spcpu
fix 0 all gpu force/neigh 0 0 1.0
fix 1 all nve
fix 1 all nve
# IMD setup.
fix comm all imd 5678 unwrap off fscale 20.0 trate 20 nowait on
thermo 500
run 5000000
thermo 500
run 5000000

47
examples/gjf/README Normal file
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@ -0,0 +1,47 @@
LAMMPS GJ THERMOSTAT EXAMPLE
Required LAMMPS packages: EXTRA-FIX, MOLECULE, EXTRA-PAIR
This directory contains the ingredients to run an NVT simulation using the
GJ thermostats.
Example:
NP=4 #number of processors
mpirun -np $NP lmp_mpi -in.gjf.vhalf
Compared to other thermostats, the GJ thermostat allows for larger timesteps
with the correct Boltzmann statistics. A comparison using averaged properties
from this example's input file is shown below. 'X' denotes a failed simulation.
The theoretical value for KE is 1.1168 eV.
POTENTIAL ENERGY (eV)
| Δt || 0.01 | 0.05 | 0.10 | 0.11 | 0.12 | 0.13 | 0.14 |
|===================||========|========|========|========|========|========|========|
| gjf half || -55.11 | -55.11 | -55.11 | -55.11 | -55.11 | -55.10 | -55.07 |
| gjf full || -55.11 | -55.11 | -55.11 | -55.11 | -55.11 | -55.10 | -55.07 |
| langevin || -55.11 | -55.07 | -54.87 | -54.79 | -54.65 | X | X |
| nvt (Nose-Hoover) || -55.14 | -55.07 | -54.90 | -54.84 | -54.76 | X | X |
|-------------------||--------|--------|--------|--------|--------|--------|--------|
KINETIC ENERGY (eV)
| Δt || 0.01 | 0.05 | 0.10 | 0.11 | 0.12 | 0.13 | 0.14 |
|===================||========|========|========|========|========|========|========|
| gjf half || 1.117 | 1.116 | 1.119 | 1.119 | 1.123 | 1.136 | 1.170 |
| gjf full || 1.116 | 1.071 | 0.938 | 0.898 | 0.858 | 0.817 | 0.780 |
| langevin || 1.110 | 1.113 | 1.121 | 1.129 | 1.157 | X | X |
| nvt (Nose-Hoover) || 1.083 | 1.109 | 1.112 | 1.113 | 1.114 | X | X |
|-------------------||--------|--------|--------|--------|--------|--------|--------|
Script Commands:
--
fix lang all gjf 10 10 1 26488
--
fix lang all gjf 10 10 1 26488 vel vfull
--
fix nve all nve
fix lang all langevin 10 10 1 26488
--
fix noho all nvt temp 10 10 1
--

13
examples/gjf/README.md
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@ -1,13 +0,0 @@
# LAMMPS GJF-2GJ THERMOSTAT EXAMPLE
## GJF-2GJ THERMOSTAT
This directory contains the ingredients to run an NVT simulation using the GJF-2GJ thermostat.
Example:
```
NP=4 #number of processors
mpirun -np $NP lmp_mpi -in.gjf.vhalf
```
## Required LAMMPS packages: MOLECULE package

14
examples/gjf/in.gjf.vfull
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@ -1,23 +1,25 @@
# GJF-2GJ thermostat
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
include ff-argon.lmp
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vfull
fix nve all nve
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488 vel vfull method 1
thermo 200
run 5000
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000

14
examples/gjf/in.gjf.vhalf
View File

@ -1,23 +1,25 @@
# GJF-2GJ thermostat
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
include ff-argon.lmp
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vhalf
fix nve all nve
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488
thermo 200
run 5000
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000

125
examples/gjf/log.15Oct19.gjf.vfull.g++.1
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@ -1,125 +0,0 @@
LAMMPS (19 Sep 2019)
using 1 OpenMP thread(s) per MPI task
# GJF-2GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 1 by 1 MPI processor grid
reading atoms ...
864 atoms
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000150019 secs
read_data CPU = 0.001946 secs
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vfull
fix nve all nve
thermo 200
run 5000
Neighbor list info ...
update every 1 steps, delay 10 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.94072
ghost atom cutoff = 6.94072
binsize = 3.47036, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.875 | 6.875 | 6.875 Mbytes
Step Temp E_pair E_mol TotEng Press
0 11.080223 -56.207655 0 -54.97164 37.215524
200 8.2588471 -55.073602 0 -54.152316 339.80416
400 8.1427292 -55.072244 0 -54.16391 338.91883
600 8.7595618 -55.066739 0 -54.089596 344.25426
800 8.550633 -55.148315 0 -54.194479 318.9385
1000 8.5394337 -55.125709 0 -54.173122 326.59471
1200 8.565973 -55.114892 0 -54.159345 328.5193
1400 8.2092914 -55.109233 0 -54.193475 329.56161
1600 8.209495 -55.138161 0 -54.22238 321.39971
1800 8.4039924 -55.13355 0 -54.196072 322.64214
2000 8.4548937 -55.062994 0 -54.119838 343.29888
2200 8.3775139 -55.13364 0 -54.199116 323.63744
2400 8.537332 -55.163702 0 -54.21135 315.62864
2600 8.672488 -55.112054 0 -54.144625 330.1106
2800 8.3000218 -55.147275 0 -54.221396 318.73112
3000 8.3552421 -55.135164 0 -54.203124 323.53075
3200 8.4126798 -55.135753 0 -54.197306 321.48817
3400 8.4986413 -55.135408 0 -54.187372 323.42951
3600 8.38431 -55.103932 0 -54.16865 330.68929
3800 8.8262454 -55.103648 0 -54.119067 332.97779
4000 7.9658136 -55.120402 0 -54.231803 324.9595
4200 8.2265544 -55.129011 0 -54.211327 323.87069
4400 8.1253738 -55.153089 0 -54.246691 316.304
4600 8.2010823 -55.124053 0 -54.20921 325.98402
4800 8.5512149 -55.075877 0 -54.121976 338.30137
5000 8.4737659 -55.158604 0 -54.213343 316.22418
Loop time of 2.73236 on 1 procs for 5000 steps with 864 atoms
Performance: 15810.507 ns/day, 0.002 hours/ns, 1829.920 timesteps/s
99.7% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 1.4262 | 1.4262 | 1.4262 | 0.0 | 52.20
Bond | 0.00042836 | 0.00042836 | 0.00042836 | 0.0 | 0.02
Neigh | 0.12819 | 0.12819 | 0.12819 | 0.0 | 4.69
Comm | 0.058611 | 0.058611 | 0.058611 | 0.0 | 2.15
Output | 0.00047283 | 0.00047283 | 0.00047283 | 0.0 | 0.02
Modify | 1.0924 | 1.0924 | 1.0924 | 0.0 | 39.98
Other | | 0.02605 | | | 0.95
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1593 ave 1593 max 1593 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18143 ave 18143 max 18143 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18143
Ave neighs/atom = 20.9988
Ave special neighs/atom = 0
Neighbor list builds = 158
Dangerous builds = 5
Total wall time: 0:00:02

125
examples/gjf/log.15Oct19.gjf.vfull.g++.4
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@ -1,125 +0,0 @@
LAMMPS (19 Sep 2019)
using 1 OpenMP thread(s) per MPI task
# GJF-2GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 2 by 2 MPI processor grid
reading atoms ...
864 atoms
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000556268 secs
read_data CPU = 0.003817 secs
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vfull
fix nve all nve
thermo 200
run 5000
Neighbor list info ...
update every 1 steps, delay 10 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.94072
ghost atom cutoff = 6.94072
binsize = 3.47036, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.808 | 6.808 | 6.808 Mbytes
Step Temp E_pair E_mol TotEng Press
0 11.080228 -56.207655 0 -54.971639 37.215541
200 8.4818184 -55.127334 0 -54.181174 324.96159
400 8.5960916 -55.09236 0 -54.133453 334.83136
600 8.1607556 -55.073136 0 -54.162791 339.035
800 8.8350489 -55.133382 0 -54.147819 324.48149
1000 8.5692704 -55.118463 0 -54.162548 327.26328
1200 8.4174147 -55.126297 0 -54.187322 324.4248
1400 8.6362603 -55.123075 0 -54.159688 326.7798
1600 8.222512 -55.153799 0 -54.236565 317.8147
1800 8.324523 -55.116698 0 -54.188085 327.35373
2000 7.9615959 -55.155825 0 -54.267697 315.37215
2200 8.495968 -55.083943 0 -54.136205 336.67775
2400 7.7926986 -55.044816 0 -54.175529 344.87758
2600 8.1551351 -55.069404 0 -54.159687 339.60901
2800 8.2593599 -55.084151 0 -54.162807 336.54935
3000 8.2860869 -55.110296 0 -54.185971 328.99074
3200 8.4074534 -55.123576 0 -54.185712 326.06823
3400 8.6694364 -55.128925 0 -54.161836 324.67512
3600 8.5718984 -55.129861 0 -54.173653 325.20586
3800 8.508102 -55.099093 0 -54.150001 333.91437
4000 8.2966658 -55.117782 0 -54.192276 327.13516
4200 8.7641728 -55.135792 0 -54.158136 324.00844
4400 8.8827909 -55.096369 0 -54.10548 335.08467
4600 8.7666577 -55.127213 0 -54.149279 326.15539
4800 8.6670762 -55.163395 0 -54.19657 316.48383
5000 8.1893094 -55.073756 0 -54.160226 337.95271
Loop time of 0.870594 on 4 procs for 5000 steps with 864 atoms
Performance: 49621.267 ns/day, 0.000 hours/ns, 5743.202 timesteps/s
96.5% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.33582 | 0.35125 | 0.3724 | 2.3 | 40.35
Bond | 0.00030267 | 0.00031316 | 0.00033538 | 0.0 | 0.04
Neigh | 0.034246 | 0.03479 | 0.035904 | 0.4 | 4.00
Comm | 0.15068 | 0.17419 | 0.19191 | 3.6 | 20.01
Output | 0.00044776 | 0.00054703 | 0.00083177 | 0.0 | 0.06
Modify | 0.27679 | 0.28079 | 0.28849 | 0.9 | 32.25
Other | | 0.02871 | | | 3.30
Nlocal: 216 ave 216 max 216 min
Histogram: 4 0 0 0 0 0 0 0 0 0
Nghost: 888.75 ave 899 max 876 min
Histogram: 1 0 1 0 0 0 0 0 0 2
Neighs: 4536 ave 4737 max 4335 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 178
Dangerous builds = 11
Total wall time: 0:00:00

125
examples/gjf/log.15Oct19.gjf.vhalf.g++.1
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@ -1,125 +0,0 @@
LAMMPS (19 Sep 2019)
using 1 OpenMP thread(s) per MPI task
# GJF-2GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 1 by 1 MPI processor grid
reading atoms ...
864 atoms
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000147804 secs
read_data CPU = 0.00194898 secs
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vhalf
fix nve all nve
thermo 200
run 5000
Neighbor list info ...
update every 1 steps, delay 10 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.94072
ghost atom cutoff = 6.94072
binsize = 3.47036, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.5 | 6.5 | 6.5 Mbytes
Step Temp E_pair E_mol TotEng Press
0 11.080223 -56.207655 0 -54.97164 37.215524
200 9.8808568 -55.073602 0 -53.971378 345.62207
400 9.8712816 -55.072244 0 -53.971088 345.11889
600 10.528988 -55.066739 0 -53.892214 350.60093
800 10.167171 -55.148315 0 -54.014152 324.73679
1000 10.029026 -55.125709 0 -54.006956 331.93766
1200 10.194424 -55.114892 0 -53.977688 334.36032
1400 9.3473846 -55.109233 0 -54.066518 333.64378
1600 9.7774071 -55.138161 0 -54.047477 327.02358
1800 9.9814275 -55.13355 0 -54.020107 328.30017
2000 10.2515 -55.062994 0 -53.919424 349.74304
2200 9.8126922 -55.13364 0 -54.039019 328.78521
2400 10.044314 -55.163702 0 -54.043244 321.03397
2600 10.543316 -55.112054 0 -53.935932 336.82099
2800 9.7874375 -55.147275 0 -54.055472 324.06626
3000 9.7703821 -55.135164 0 -54.045263 328.60665
3200 10.141958 -55.135753 0 -54.004402 327.69084
3400 10.160576 -55.135408 0 -54.00198 329.39063
3600 10.044652 -55.103932 0 -53.983436 336.64469
3800 10.662403 -55.103648 0 -53.914241 339.56382
4000 9.2921047 -55.120402 0 -54.083853 329.71671
4200 9.8744553 -55.129011 0 -54.027501 329.78147
4400 9.4085964 -55.153089 0 -54.103546 320.90673
4600 9.5463801 -55.124053 0 -54.05914 330.80941
4800 10.223884 -55.075877 0 -53.935387 344.30099
5000 9.6243338 -55.158604 0 -54.084996 320.3511
Loop time of 2.29551 on 1 procs for 5000 steps with 864 atoms
Performance: 18819.358 ns/day, 0.001 hours/ns, 2178.166 timesteps/s
99.7% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 1.4393 | 1.4393 | 1.4393 | 0.0 | 62.70
Bond | 0.0004441 | 0.0004441 | 0.0004441 | 0.0 | 0.02
Neigh | 0.12136 | 0.12136 | 0.12136 | 0.0 | 5.29
Comm | 0.059342 | 0.059342 | 0.059342 | 0.0 | 2.59
Output | 0.00046968 | 0.00046968 | 0.00046968 | 0.0 | 0.02
Modify | 0.64937 | 0.64937 | 0.64937 | 0.0 | 28.29
Other | | 0.02522 | | | 1.10
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1593 ave 1593 max 1593 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18143 ave 18143 max 18143 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18143
Ave neighs/atom = 20.9988
Ave special neighs/atom = 0
Neighbor list builds = 158
Dangerous builds = 5
Total wall time: 0:00:02

125
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@ -1,125 +0,0 @@
LAMMPS (19 Sep 2019)
using 1 OpenMP thread(s) per MPI task
# GJF-2GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 2 by 2 MPI processor grid
reading atoms ...
864 atoms
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000315903 secs
read_data CPU = 0.0653752 secs
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
fix lang all langevin 10 10 1 26488 gjf vhalf
fix nve all nve
thermo 200
run 5000
Neighbor list info ...
update every 1 steps, delay 10 steps, check yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.94072
ghost atom cutoff = 6.94072
binsize = 3.47036, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d/newton
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.433 | 6.433 | 6.433 Mbytes
Step Temp E_pair E_mol TotEng Press
0 11.080228 -56.207655 0 -54.971639 37.215541
200 9.8046716 -55.127334 0 -54.033608 329.70647
400 10.174622 -55.09236 0 -53.957366 340.49331
600 9.9812299 -55.073136 0 -53.959714 345.56477
800 10.512874 -55.133382 0 -53.960655 330.4996
1000 9.9587885 -55.118463 0 -54.007545 332.24728
1200 10.236607 -55.126297 0 -53.984388 330.94998
1400 10.134679 -55.123075 0 -53.992537 332.15441
1600 9.8934078 -55.153799 0 -54.050174 323.80795
1800 10.064966 -55.116698 0 -53.993936 333.59644
2000 9.6736107 -55.155825 0 -54.076719 321.5129
2200 10.264537 -55.083943 0 -53.938918 343.02135
2400 9.5640032 -55.044816 0 -53.977937 351.23099
2600 9.6581077 -55.069404 0 -53.992028 344.99996
2800 9.9622575 -55.084151 0 -53.972846 342.6574
3000 9.8724909 -55.110296 0 -54.009005 334.68094
3200 10.032027 -55.123576 0 -54.004488 331.89534
3400 10.221132 -55.128925 0 -53.988742 330.24082
3600 10.085802 -55.129861 0 -54.004774 330.63601
3800 10.098545 -55.099093 0 -53.972585 339.61905
4000 10.000257 -55.117782 0 -54.002238 333.24569
4200 10.20477 -55.135792 0 -53.997435 329.17565
4400 10.545132 -55.096369 0 -53.920044 341.04725
4600 10.376108 -55.127213 0 -53.969743 331.92825
4800 10.247392 -55.163395 0 -54.020283 322.15219
5000 9.7753102 -55.073756 0 -53.983305 343.64146
Loop time of 1.19785 on 4 procs for 5000 steps with 864 atoms
Performance: 36064.674 ns/day, 0.001 hours/ns, 4174.152 timesteps/s
88.6% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.36387 | 0.38652 | 0.44086 | 5.1 | 32.27
Bond | 0.00028847 | 0.00030833 | 0.000338 | 0.0 | 0.03
Neigh | 0.033934 | 0.034959 | 0.036917 | 0.6 | 2.92
Comm | 0.39292 | 0.47821 | 0.52198 | 7.3 | 39.92
Output | 0.00050343 | 0.0012343 | 0.0023338 | 1.9 | 0.10
Modify | 0.1605 | 0.17963 | 0.19457 | 2.9 | 15.00
Other | | 0.117 | | | 9.77
Nlocal: 216 ave 216 max 216 min
Histogram: 4 0 0 0 0 0 0 0 0 0
Nghost: 888.75 ave 899 max 876 min
Histogram: 1 0 1 0 0 0 0 0 0 2
Neighs: 4536 ave 4737 max 4335 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 178
Dangerous builds = 11
Total wall time: 0:00:01

193
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LAMMPS (2 Apr 2025 - Development - d4867ab55e-modified)
OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:99)
using 1 OpenMP thread(s) per MPI task
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
Reading data file ...
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 1 by 1 MPI processor grid
reading atoms ...
864 atoms
Finding 1-2 1-3 1-4 neighbors ...
special bond factors lj: 0 0 0
special bond factors coul: 0 0 0
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000 seconds
read_data CPU = 0.007 seconds
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488 vel vfull method 1
run 5000
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- GJ methods: doi:10.1080/00268976.2019.1662506
@Article{gronbech-jensen_complete_2020,
title = {Complete set of stochastic Verlet-type thermostats for correct Langevin simulations},
volume = {118},
number = {8},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1662506},
doi = {10.1080/00268976.2019.1662506},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels},
year = {2020}
}
- GJ-I vfull method: doi:10.1080/00268976.2012.760055
@Article{gronbech-jensen_simple_2013,
title = {A simple and effective Verlet-type algorithm for simulating Langevin dynamics},
volume = {111},
url = {http://www.tandfonline.com/doi/abs/10.1080/00268976.2012.760055},
doi = {10.1080/00268976.2012.760055},
pages = {983-991},
number = {8},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels and Farago, Oded},
year = {2013}
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.9407173
ghost atom cutoff = 6.9407173
binsize = 3.4703587, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.481 | 6.481 | 6.481 Mbytes
Step Temp E_pair E_mol TotEng Press
0 10 -56.207652 0 -55.092137 33.341103
5000 8.4535562 -55.150518 0 -54.207511 318.20862
Loop time of 2.26831 on 1 procs for 5000 steps with 864 atoms
Performance: 19044.977 ns/day, 0.001 hours/ns, 2204.280 timesteps/s, 1.904 Matom-step/s
99.9% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 1.2802 | 1.2802 | 1.2802 | 0.0 | 56.44
Bond | 0.00051213 | 0.00051213 | 0.00051213 | 0.0 | 0.02
Neigh | 0.27007 | 0.27007 | 0.27007 | 0.0 | 11.91
Comm | 0.057527 | 0.057527 | 0.057527 | 0.0 | 2.54
Output | 6.3876e-05 | 6.3876e-05 | 6.3876e-05 | 0.0 | 0.00
Modify | 0.63364 | 0.63364 | 0.63364 | 0.0 | 27.93
Other | | 0.02635 | | | 1.16
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1593 ave 1593 max 1593 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18143 ave 18143 max 18143 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18143
Ave neighs/atom = 20.998843
Ave special neighs/atom = 0
Neighbor list builds = 258
Dangerous builds = 0
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 6.481 | 6.481 | 6.481 Mbytes
Step Temp E_pair E_mol TotEng Press
5000 8.4535562 -55.150518 0 -54.207511 318.20862
6000 8.4899401 -55.108242 0 -54.161176 331.10703
8000 8.3618893 -55.092171 0 -54.15939 334.11831
10000 8.8684311 -55.100316 0 -54.111029 334.09931
12000 8.4339192 -55.07343 0 -54.132614 340.00487
14000 8.072393 -55.115121 0 -54.214633 327.98965
16000 8.3420289 -55.077813 0 -54.147247 337.74926
18000 8.3803911 -55.12201 0 -54.187164 326.10485
20000 8.4676985 -55.176339 0 -54.231754 311.57092
22000 8.8560138 -55.110505 0 -54.122603 330.66179
24000 8.3187826 -55.120592 0 -54.192619 327.01148
26000 8.0327666 -55.116664 0 -54.220596 326.25179
28000 8.3672169 -55.130413 0 -54.197037 324.2368
30000 8.1669275 -55.057678 0 -54.146645 344.9168
32000 8.3819314 -55.08989 0 -54.154873 335.45317
34000 8.109088 -55.17222 0 -54.267639 310.83717
36000 8.3048574 -55.079475 0 -54.153056 338.04291
38000 8.8708544 -55.108991 0 -54.119434 330.70097
40000 8.4012779 -55.080817 0 -54.143642 338.54326
Loop time of 18.9699 on 1 procs for 35000 steps with 864 atoms
Performance: 15941.040 ns/day, 0.002 hours/ns, 1845.028 timesteps/s, 1.594 Matom-step/s
99.9% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 11.593 | 11.593 | 11.593 | 0.0 | 61.11
Bond | 0.0041801 | 0.0041801 | 0.0041801 | 0.0 | 0.02
Neigh | 2.2671 | 2.2671 | 2.2671 | 0.0 | 11.95
Comm | 0.42339 | 0.42339 | 0.42339 | 0.0 | 2.23
Output | 0.00062204 | 0.00062204 | 0.00062204 | 0.0 | 0.00
Modify | 4.4976 | 4.4976 | 4.4976 | 0.0 | 23.71
Other | | 0.1839 | | | 0.97
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1592 ave 1592 max 1592 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18144 ave 18144 max 18144 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 2122
Dangerous builds = 0
Total wall time: 0:00:21

193
examples/gjf/log.2Apr25.gjf.vfull.g++.4 Normal file
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@ -0,0 +1,193 @@
LAMMPS (2 Apr 2025 - Development - d4867ab55e-modified)
OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:99)
using 1 OpenMP thread(s) per MPI task
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
Reading data file ...
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 2 by 2 MPI processor grid
reading atoms ...
864 atoms
Finding 1-2 1-3 1-4 neighbors ...
special bond factors lj: 0 0 0
special bond factors coul: 0 0 0
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.002 seconds
read_data CPU = 0.015 seconds
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488 vel vfull method 1
run 5000
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- GJ methods: doi:10.1080/00268976.2019.1662506
@Article{gronbech-jensen_complete_2020,
title = {Complete set of stochastic Verlet-type thermostats for correct Langevin simulations},
volume = {118},
number = {8},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1662506},
doi = {10.1080/00268976.2019.1662506},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels},
year = {2020}
}
- GJ-I vfull method: doi:10.1080/00268976.2012.760055
@Article{gronbech-jensen_simple_2013,
title = {A simple and effective Verlet-type algorithm for simulating Langevin dynamics},
volume = {111},
url = {http://www.tandfonline.com/doi/abs/10.1080/00268976.2012.760055},
doi = {10.1080/00268976.2012.760055},
pages = {983-991},
number = {8},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels and Farago, Oded},
year = {2013}
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.9407173
ghost atom cutoff = 6.9407173
binsize = 3.4703587, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.427 | 6.427 | 6.427 Mbytes
Step Temp E_pair E_mol TotEng Press
0 10 -56.207652 0 -55.092137 33.341103
5000 7.946377 -55.076514 0 -54.190084 337.31999
Loop time of 2.0998 on 4 procs for 5000 steps with 864 atoms
Performance: 20573.405 ns/day, 0.001 hours/ns, 2381.181 timesteps/s, 2.057 Matom-step/s
65.2% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.53641 | 0.54389 | 0.54721 | 0.6 | 25.90
Bond | 0.00056487 | 0.0006195 | 0.00068462 | 0.0 | 0.03
Neigh | 0.10567 | 0.1086 | 0.11128 | 0.7 | 5.17
Comm | 0.96913 | 0.97758 | 0.98191 | 0.5 | 46.56
Output | 0.00025213 | 0.00025642 | 0.00026405 | 0.0 | 0.01
Modify | 0.25061 | 0.25105 | 0.25172 | 0.1 | 11.96
Other | | 0.2178 | | | 10.37
Nlocal: 216 ave 216 max 216 min
Histogram: 4 0 0 0 0 0 0 0 0 0
Nghost: 884.75 ave 885 max 884 min
Histogram: 1 0 0 0 0 0 0 0 0 3
Neighs: 4536 ave 4737 max 4335 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 273
Dangerous builds = 0
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 6.428 | 6.428 | 6.428 Mbytes
Step Temp E_pair E_mol TotEng Press
5000 7.946377 -55.076514 0 -54.190084 337.31999
6000 8.2565866 -55.129244 0 -54.208209 324.57967
8000 7.9942397 -55.101417 0 -54.209648 331.24127
10000 8.5413968 -55.083292 0 -54.130486 337.82599
12000 8.3682078 -55.090905 0 -54.157419 335.08066
14000 8.5082065 -55.085051 0 -54.135948 336.2765
16000 8.1944037 -55.090733 0 -54.176635 334.03786
18000 8.2607106 -55.030131 0 -54.108637 352.49892
20000 8.1154691 -55.104072 0 -54.198779 330.14203
22000 8.5592601 -55.152019 0 -54.197221 318.03507
24000 8.3182914 -55.115242 0 -54.187324 328.46084
26000 8.3691375 -55.125275 0 -54.191685 325.43673
28000 8.531632 -55.107097 0 -54.155381 331.42771
30000 8.1102222 -55.099011 0 -54.194304 332.04678
32000 8.5558571 -55.077016 0 -54.122598 339.87746
34000 8.4213946 -55.097068 0 -54.157649 333.34935
36000 8.0936615 -55.152202 0 -54.249342 316.20169
38000 7.999652 -55.048407 0 -54.156034 345.07945
40000 8.6699753 -55.087634 0 -54.120485 337.23709
Loop time of 17.6726 on 4 procs for 35000 steps with 864 atoms
Performance: 17111.263 ns/day, 0.001 hours/ns, 1980.470 timesteps/s, 1.711 Matom-step/s
65.4% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 5.0739 | 5.1178 | 5.1689 | 1.5 | 28.96
Bond | 0.0043764 | 0.004688 | 0.0051706 | 0.4 | 0.03
Neigh | 0.83797 | 0.85506 | 0.87554 | 1.8 | 4.84
Comm | 6.816 | 6.8932 | 6.9215 | 1.7 | 39.00
Output | 0.0043624 | 0.0045336 | 0.004998 | 0.4 | 0.03
Modify | 3.3008 | 3.3033 | 3.3066 | 0.1 | 18.69
Other | | 1.494 | | | 8.45
Nlocal: 216 ave 222 max 210 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Nghost: 905.5 ave 911 max 899 min
Histogram: 1 1 0 0 0 0 0 0 0 2
Neighs: 4535.75 ave 4837 max 4218 min
Histogram: 1 0 0 1 0 0 1 0 0 1
Total # of neighbors = 18143
Ave neighs/atom = 20.998843
Ave special neighs/atom = 0
Neighbor list builds = 2140
Dangerous builds = 0
Total wall time: 0:00:19

192
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@ -0,0 +1,192 @@
LAMMPS (2 Apr 2025 - Development - d4867ab55e-modified)
OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:99)
using 1 OpenMP thread(s) per MPI task
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
Reading data file ...
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 1 by 1 MPI processor grid
reading atoms ...
864 atoms
Finding 1-2 1-3 1-4 neighbors ...
special bond factors lj: 0 0 0
special bond factors coul: 0 0 0
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.000 seconds
read_data CPU = 0.010 seconds
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488
run 5000
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- GJ methods: doi:10.1080/00268976.2019.1662506
@Article{gronbech-jensen_complete_2020,
title = {Complete set of stochastic Verlet-type thermostats for correct Langevin simulations},
volume = {118},
number = {8},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1662506},
doi = {10.1080/00268976.2019.1662506},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels},
year = {2020}
}
- GJ-I vhalf method: doi:10.1080/00268976.2019.1570369
@Article{jensen_accurate_2019,
title = {Accurate configurational and kinetic statistics in discrete-time Langevin systems},
volume = {117},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1570369},
doi = {10.1080/00268976.2019.1570369},
number = {18},
journal = {Molecular Physics},
author = {Jensen, Lucas Frese Grønbech and Grønbech-Jensen, Niels},
year = {2019}
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.9407173
ghost atom cutoff = 6.9407173
binsize = 3.4703587, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.481 | 6.481 | 6.481 Mbytes
Step Temp E_pair E_mol TotEng Press
0 10 -56.207652 0 -55.092137 33.341103
5000 9.7731898 -55.150518 0 -54.060304 322.94195
Loop time of 2.28421 on 1 procs for 5000 steps with 864 atoms
Performance: 18912.438 ns/day, 0.001 hours/ns, 2188.940 timesteps/s, 1.891 Matom-step/s
99.9% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 1.2715 | 1.2715 | 1.2715 | 0.0 | 55.66
Bond | 0.00057126 | 0.00057126 | 0.00057126 | 0.0 | 0.03
Neigh | 0.27008 | 0.27008 | 0.27008 | 0.0 | 11.82
Comm | 0.057938 | 0.057938 | 0.057938 | 0.0 | 2.54
Output | 6.1954e-05 | 6.1954e-05 | 6.1954e-05 | 0.0 | 0.00
Modify | 0.658 | 0.658 | 0.658 | 0.0 | 28.81
Other | | 0.0261 | | | 1.14
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1593 ave 1593 max 1593 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18143 ave 18143 max 18143 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18143
Ave neighs/atom = 20.998843
Ave special neighs/atom = 0
Neighbor list builds = 258
Dangerous builds = 0
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 6.481 | 6.481 | 6.481 Mbytes
Step Temp E_pair E_mol TotEng Press
5000 9.7731898 -55.150518 0 -54.060304 322.94195
6000 10.024842 -55.108242 0 -53.989956 336.6125
8000 10.118994 -55.092171 0 -53.963382 340.42078
10000 10.541359 -55.100316 0 -53.924412 340.09986
12000 10.023234 -55.07343 0 -53.955323 345.70551
14000 9.5912018 -55.115121 0 -54.045208 333.43739
16000 9.9450498 -55.077813 0 -53.968428 343.49906
18000 10.113744 -55.12201 0 -53.993806 332.32214
20000 9.9345204 -55.176339 0 -54.068128 316.83219
22000 10.585719 -55.110505 0 -53.929652 336.86599
24000 10.024757 -55.120592 0 -54.002315 333.13056
26000 9.7787474 -55.116664 0 -54.02583 332.51437
28000 9.6092087 -55.130413 0 -54.058491 328.69165
30000 9.8245787 -55.057678 0 -53.961731 350.86255
32000 10.066994 -55.08989 0 -53.966902 341.49724
34000 9.5677059 -55.17222 0 -54.104928 316.06902
36000 9.7252627 -55.079475 0 -53.994608 343.13769
38000 10.438984 -55.108991 0 -53.944506 336.32562
40000 10.238268 -55.080817 0 -53.938723 345.13228
Loop time of 19.138 on 1 procs for 35000 steps with 864 atoms
Performance: 15801.041 ns/day, 0.002 hours/ns, 1828.824 timesteps/s, 1.580 Matom-step/s
99.9% CPU use with 1 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 11.568 | 11.568 | 11.568 | 0.0 | 60.44
Bond | 0.0042372 | 0.0042372 | 0.0042372 | 0.0 | 0.02
Neigh | 2.2577 | 2.2577 | 2.2577 | 0.0 | 11.80
Comm | 0.42841 | 0.42841 | 0.42841 | 0.0 | 2.24
Output | 0.00060128 | 0.00060128 | 0.00060128 | 0.0 | 0.00
Modify | 4.694 | 4.694 | 4.694 | 0.0 | 24.53
Other | | 0.1852 | | | 0.97
Nlocal: 864 ave 864 max 864 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 1592 ave 1592 max 1592 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 18144 ave 18144 max 18144 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 2122
Dangerous builds = 0
Total wall time: 0:00:21

192
examples/gjf/log.2Apr25.gjf.vhalf.g++.4 Normal file
View File

@ -0,0 +1,192 @@
LAMMPS (2 Apr 2025 - Development - d4867ab55e-modified)
OMP_NUM_THREADS environment is not set. Defaulting to 1 thread. (src/comm.cpp:99)
using 1 OpenMP thread(s) per MPI task
# GJ thermostat
units metal
atom_style full
boundary p p p
read_data argon.lmp
Reading data file ...
orthogonal box = (0 0 0) to (32.146 32.146 32.146)
1 by 2 by 2 MPI processor grid
reading atoms ...
864 atoms
Finding 1-2 1-3 1-4 neighbors ...
special bond factors lj: 0 0 0
special bond factors coul: 0 0 0
0 = max # of 1-2 neighbors
0 = max # of 1-3 neighbors
0 = max # of 1-4 neighbors
1 = max # of special neighbors
special bonds CPU = 0.002 seconds
read_data CPU = 0.015 seconds
include ff-argon.lmp
#############################
#Atoms types - mass - charge#
#############################
#@ 1 atom types #!THIS LINE IS NECESSARY DON'T SPEND HOURS FINDING THAT OUT!#
variable Ar equal 1
#############
#Atom Masses#
#############
mass ${Ar} 39.903
mass 1 39.903
###########################
#Pair Potentials - Tersoff#
###########################
pair_style lj/cubic
pair_coeff * * 0.0102701 3.42
velocity all create 10 2357 mom yes dist gaussian
neighbor 1 bin
timestep 0.1
compute myKE all ke
compute myPE all pe
fix lang all gjf 10 10 1 26488
run 5000
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- GJ methods: doi:10.1080/00268976.2019.1662506
@Article{gronbech-jensen_complete_2020,
title = {Complete set of stochastic Verlet-type thermostats for correct Langevin simulations},
volume = {118},
number = {8},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1662506},
doi = {10.1080/00268976.2019.1662506},
journal = {Molecular Physics},
author = {Grønbech-Jensen, Niels},
year = {2020}
}
- GJ-I vhalf method: doi:10.1080/00268976.2019.1570369
@Article{jensen_accurate_2019,
title = {Accurate configurational and kinetic statistics in discrete-time Langevin systems},
volume = {117},
url = {https://www.tandfonline.com/doi/full/10.1080/00268976.2019.1570369},
doi = {10.1080/00268976.2019.1570369},
number = {18},
journal = {Molecular Physics},
author = {Jensen, Lucas Frese Grønbech and Grønbech-Jensen, Niels},
year = {2019}
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 6.9407173
ghost atom cutoff = 6.9407173
binsize = 3.4703587, bins = 10 10 10
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair lj/cubic, perpetual
attributes: half, newton on
pair build: half/bin/newton
stencil: half/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 6.427 | 6.427 | 6.427 Mbytes
Step Temp E_pair E_mol TotEng Press
0 10 -56.207652 0 -55.092137 33.341103
5000 9.3726166 -55.076514 0 -54.030985 342.43571
Loop time of 2.11818 on 4 procs for 5000 steps with 864 atoms
Performance: 20394.822 ns/day, 0.001 hours/ns, 2360.512 timesteps/s, 2.039 Matom-step/s
63.1% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.53987 | 0.54922 | 0.56044 | 1.2 | 25.93
Bond | 0.00058281 | 0.00063674 | 0.00075153 | 0.0 | 0.03
Neigh | 0.10821 | 0.10912 | 0.11017 | 0.2 | 5.15
Comm | 0.96075 | 0.97484 | 0.98645 | 1.1 | 46.02
Output | 0.00026318 | 0.00026575 | 0.00027192 | 0.0 | 0.01
Modify | 0.26142 | 0.2634 | 0.26465 | 0.2 | 12.44
Other | | 0.2207 | | | 10.42
Nlocal: 216 ave 216 max 216 min
Histogram: 4 0 0 0 0 0 0 0 0 0
Nghost: 884.75 ave 885 max 884 min
Histogram: 1 0 0 0 0 0 0 0 0 3
Neighs: 4536 ave 4737 max 4335 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Total # of neighbors = 18144
Ave neighs/atom = 21
Ave special neighs/atom = 0
Neighbor list builds = 273
Dangerous builds = 0
fix energies all ave/time 1 20000 20000 c_myKE c_myPE #file ave.out
thermo 2000
run 35000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 6.428 | 6.428 | 6.428 Mbytes
Step Temp E_pair E_mol TotEng Press
5000 9.3726166 -55.076514 0 -54.030985 342.43571
6000 9.6911866 -55.129244 0 -54.048177 329.72537
8000 9.7296551 -55.101417 0 -54.016059 337.46595
10000 10.098808 -55.083292 0 -53.956755 343.4122
12000 10.114344 -55.090905 0 -53.962635 341.3438
14000 10.230012 -55.085051 0 -53.943878 342.45237
16000 9.5989709 -55.090733 0 -54.019954 339.07584
18000 10.016071 -55.030131 0 -53.912824 358.79514
20000 9.7197057 -55.104072 0 -54.019824 335.89619
22000 9.959647 -55.152019 0 -54.041005 323.05805
24000 10.075138 -55.115242 0 -53.991345 334.76239
26000 10.227192 -55.125275 0 -53.984416 332.10131
28000 10.177109 -55.107097 0 -53.971825 337.32979
30000 9.521036 -55.099011 0 -54.036925 337.10716
32000 10.265633 -55.077016 0 -53.93187 346.01018
34000 10.173978 -55.097068 0 -53.962146 339.63562
36000 9.6032778 -55.152202 0 -54.080942 321.61646
38000 9.8802995 -55.048407 0 -53.946245 351.82506
40000 10.372288 -55.087634 0 -53.93059 343.34304
Loop time of 17.867 on 4 procs for 35000 steps with 864 atoms
Performance: 16925.013 ns/day, 0.001 hours/ns, 1958.914 timesteps/s, 1.693 Matom-step/s
65.3% CPU use with 4 MPI tasks x 1 OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 5.0932 | 5.1683 | 5.2256 | 2.5 | 28.93
Bond | 0.0044473 | 0.0048347 | 0.0058137 | 0.8 | 0.03
Neigh | 0.85262 | 0.8601 | 0.87438 | 0.9 | 4.81
Comm | 6.8164 | 6.8981 | 6.9859 | 2.6 | 38.61
Output | 0.0046884 | 0.0047093 | 0.0047322 | 0.0 | 0.03
Modify | 3.4107 | 3.4186 | 3.4248 | 0.3 | 19.13
Other | | 1.512 | | | 8.47
Nlocal: 216 ave 222 max 210 min
Histogram: 2 0 0 0 0 0 0 0 0 2
Nghost: 905.5 ave 911 max 899 min
Histogram: 1 1 0 0 0 0 0 0 0 2
Neighs: 4535.75 ave 4837 max 4218 min
Histogram: 1 0 0 1 0 0 1 0 0 1
Total # of neighbors = 18143
Ave neighs/atom = 20.998843
Ave special neighs/atom = 0
Neighbor list builds = 2140
Dangerous builds = 0
Total wall time: 0:00:21

24
examples/granular/in.tableting.200
View File

@ -28,19 +28,20 @@ variable dieHeight equal 1e-2
pair_style granular
# mdr = E, nu, Y, gamma, psi_b, CoR
# mdr = E, nu, Y, gamma, psi_b, damp
variable YoungsModulus equal 5e6
variable YieldStress equal 1.9e5
variable PoissonsRatio equal 0.4
variable SurfaceEnergy equal 2
variable SurfaceEnergyWall equal 0.0
variable CoR equal 0.5
variable psi_b equal 0.5
variable damp equal 0.2
variable damp_type equal 1
# linear_history = k_t, x_gammat, mu_s
variable kt equal 2/7*${YoungsModulus}*${atomRadius}
variable kt_wall equal 2/7*${YoungsModulus}*${atomRadius}
variable xgammat equal 0.0
variable xgammat equal 1.0
variable mu_s equal 0.7
variable mu_s_wall equal 0.1
@ -49,14 +50,17 @@ variable mu_roll equal 0.6
variable k_roll equal 2.25*${mu_roll}*${mu_roll}*${YoungsModulus}*${atomRadius}
variable gamma_roll equal 0.0
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${CoR} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll} damping none
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} &
damping mdr ${damp_type} &
tangential linear_history ${kt} ${xgammat} ${mu_s} &
rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
######################################### ADD DIE AND PUNCH WALLS ############################################
variable disp_upper equal 0.0
variable disp_lower equal 0.0
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergyWall} ${psi_b} ${CoR} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll} damping none"
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergyWall} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}"
variable dieHeight2 equal 2*${dieHeight}
@ -73,7 +77,7 @@ variable avgUpperPunchForce equal c_avgUpperPunchForce
compute avgLowerPunchForce all reduce sum f_lowerPunch[4]
variable avgLowerPunchForce equal c_avgLowerPunchForce
fix printFD all print 1 "${disp_upper} ${avgUpperPunchForce} ${avgLowerPunchForce}" file punch_force_disp_tableting200.csv screen no
#fix printFD all print 1 "${disp_upper} ${avgUpperPunchForce} ${avgLowerPunchForce}" file punch_force_disp_tableting200.csv screen no
##################################### INTEGRATION AND GRAVITY #################################################
@ -109,13 +113,13 @@ variable syy_ave equal c_sigmayy_ave
variable szz_ave equal c_sigmazz_ave
variable Vparticles equal c_Velas_sum
fix log all print 1 "${sxx_ave} ${syy_ave} ${szz_ave} ${Vparticles}" file average_normal_stresses_tableting200.csv screen no
dump dumpParticles all custom ${output_rate} tableting200.dump id type mass diameter x y z vx vy vz fx fy fz c_ke c_sigmaxx c_sigmayy c_sigmazz
#fix log all print 1 "${sxx_ave} ${syy_ave} ${szz_ave} ${Vparticles}" file average_normal_stresses_tableting200.csv screen no
#dump dumpParticles all custom ${output_rate} tableting200.dump id type mass diameter x y z vx vy vz fx fy fz c_ke c_sigmaxx c_sigmayy c_sigmazz
#dump dumpParticlesVTK all vtk ${output_rate} post/particles_*.vtk id x y z fx fy fz vx vy vz c_ke radius c_sigmaxx c_sigmayy c_sigmazz
############################################## RUN SIMULATION #################################################
variable upper_punch_stroke equal 0.6733*${dieHeight}
variable upper_punch_stroke equal 0.7*${dieHeight}
variable vel_upper equal 0.25
variable settling_steps equal round(0.02/dt)
@ -146,4 +150,4 @@ run ${ejection_steps}
variable disp_lower equal ${dieHeight}
variable disp_upper equal ${dieHeight}*0.9
variable max_disp equal ${dieRadius}*0.75
run ${free_float_steps}
run ${free_float_steps}

25
examples/granular/in.triaxial.compaction.12
View File

@ -1,7 +1,7 @@
############################### SIMULATION SETTINGS ###################################################
atom_style sphere 1
atom_modify map array
atom_modify map array
comm_modify vel yes
units si
newton off
@ -24,20 +24,23 @@ variable atomRadius equal 0.5
pair_style granular
# mdr = E, nu, Y, gamma, psi_b, CoR
# mdr = E, nu, Y, gamma, psi_b, damp
variable YoungsModulus equal 1e9
variable PoissonsRatio equal 0.3
variable YieldStress equal 50e6
variable SurfaceEnergy equal 0.0
variable psi_b equal 0.5
variable CoR equal 0.5
variable damp equal 0.2
variable damp_type equal 1
# linear_history = k_t, x_gamma,t, mu_s
variable kt equal 2/7*${YoungsModulus}*${atomRadius}
variable xgammat equal 0.0
variable mu_s equal 0.5
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${CoR} tangential linear_history ${kt} ${xgammat} ${mu_s} damping none
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} &
damping mdr ${damp_type} &
tangential linear_history ${kt} ${xgammat} ${mu_s}
######################################### ADD IN PLANES ################################################
@ -54,7 +57,7 @@ region plane_xz_neg plane 0 -${halfBoxWidth} 0 0 1 0 side in move NULL v_plane_d
region plane_xy_pos plane 0 0 ${halfBoxWidth} 0 0 -1 side in move NULL NULL v_plane_disp_neg units box
region plane_xy_neg plane 0 0 -${halfBoxWidth} 0 0 1 side in move NULL NULL v_plane_disp units box
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${CoR} tangential linear_history ${kt} ${xgammat} ${mu_s} damping none"
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} "
fix plane_yz_pos all wall/gran/region ${wall_contact_string} region plane_yz_pos contacts
fix plane_yz_neg all wall/gran/region ${wall_contact_string} region plane_yz_neg contacts
@ -72,12 +75,12 @@ variable plane_xz_neg_force equal c_plane_xz_neg_force
compute plane_yz_neg_force all reduce sum f_plane_yz_neg[2]
variable plane_yz_neg_force equal c_plane_yz_neg_force
fix print1 all print 1 "${plane_disp} ${plane_xy_neg_force} ${plane_xz_neg_force} ${plane_yz_neg_force}" file force_disp_triaxial12.csv screen no
#fix print1 all print 1 "${plane_disp} ${plane_xy_neg_force} ${plane_xz_neg_force} ${plane_yz_neg_force}" file force_disp_triaxial12.csv screen no
######################################## SCREEN OUTPUT ####################################################
######################################## SCREEN OUTPUT ####################################################
compute 1 all erotate/sphere
thermo_style custom dt step atoms ke c_1 vol
thermo_style custom dt step atoms ke c_1 vol
thermo 100
thermo_modify lost ignore norm no
@ -89,8 +92,8 @@ variable compression_steps equal round(${disp_max}/${ddisp})
variable output_rate equal round(${compression_steps}/100)
##################################### SET UP DUMP OUTPUTS ####################################################
dump dumpParticles all custom ${output_rate} triaxial_compaction_12.dump id type mass x y z vx vy vz fx fy fz radius
#dump dumpParticles all custom ${output_rate} triaxial_compaction_12.dump id type mass x y z vx vy vz fx fy fz radius
#dump dmp all vtk ${output_rate} post/triaxial12particles_*.vtk id type mass x y z vx vy vz fx fy fz radius
#################################### COMPRESS THE PARTICLES ##################################################
@ -101,7 +104,7 @@ run 0
compute Ac_1_12 particles_1_12 pair/local p13 cutoff radius
compute Ac_1_12_sum particles_1_12 reduce sum c_Ac_1_12 inputs local
variable Ac_1_12 equal c_Ac_1_12_sum
fix logArea all print 100 "${plane_disp} ${Ac_1_12}" file pair_1_12_contact_area_triaxial12.csv screen no
#fix logArea all print 100 "${plane_disp} ${Ac_1_12}" file pair_1_12_contact_area_triaxial12.csv screen no
variable plane_disp equal ${ddisp}*elapsed
variable plane_disp_neg equal -${ddisp}*elapsed

795
examples/granular/log.4Feb25.tableting.200.g++.1 Normal file
View File

@ -0,0 +1,795 @@
LAMMPS (4 Feb 2025 - Development - patch_5May2020-22356-g0c29a0a0c9-modified)
##################################### SIMULATION SETTINGS ###################################################
atom_style sphere 1
atom_modify map array
comm_modify vel yes
units si
newton off
neighbor 1.0e-3 bin
neigh_modify every 10 delay 60 check no
timestep 4e-6
#processors 2 2 1
############################## SIMULATION BOUNDING BOX AND INSERT PARTICLES #################################
boundary f f f
read_data spheres200.data
Reading data file ...
orthogonal box = (-0.005 -0.005 -0.001) to (0.005 0.005 0.02)
1 by 1 by 1 MPI processor grid
reading atoms ...
200 atoms
read_data CPU = 0.024 seconds
#################################### ADD DIE AND ATOM PARAMETERIZATION ######################################
variable atomRadius equal 0.44e-3*1.25
variable atomDiameter equal 2*${atomRadius}
variable atomDiameter equal 2*0.00055
variable atomDensity equal 1560
variable atomMassAvg equal ${atomDensity}*4.0/3.0*PI*${atomRadius}^3.0
variable atomMassAvg equal 1560*4.0/3.0*PI*${atomRadius}^3.0
variable atomMassAvg equal 1560*4.0/3.0*PI*0.00055^3.0
variable dieRadius equal 4e-3
variable dieHeight equal 1e-2
############################## PARTICLE MATERIAL PROPERTIES AND FORCE MODEL ##################################
pair_style granular
# mdr = E, nu, Y, gamma, psi_b, damp
variable YoungsModulus equal 5e6
variable YieldStress equal 1.9e5
variable PoissonsRatio equal 0.4
variable SurfaceEnergy equal 2
variable SurfaceEnergyWall equal 0.0
variable psi_b equal 0.5
variable damp equal 0.2
variable damp_type equal 1
# linear_history = k_t, x_gammat, mu_s
variable kt equal 2/7*${YoungsModulus}*${atomRadius}
variable kt equal 2/7*5000000*${atomRadius}
variable kt equal 2/7*5000000*0.00055
variable kt_wall equal 2/7*${YoungsModulus}*${atomRadius}
variable kt_wall equal 2/7*5000000*${atomRadius}
variable kt_wall equal 2/7*5000000*0.00055
variable xgammat equal 1.0
variable mu_s equal 0.7
variable mu_s_wall equal 0.1
# sds = mu_roll, k_roll, gamma_roll
variable mu_roll equal 0.6
variable k_roll equal 2.25*${mu_roll}*${mu_roll}*${YoungsModulus}*${atomRadius}
variable k_roll equal 2.25*0.6*${mu_roll}*${YoungsModulus}*${atomRadius}
variable k_roll equal 2.25*0.6*0.6*${YoungsModulus}*${atomRadius}
variable k_roll equal 2.25*0.6*0.6*5000000*${atomRadius}
variable k_roll equal 2.25*0.6*0.6*5000000*0.00055
variable gamma_roll equal 0.0
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history ${kt} ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 ${xgammat} ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 ${mu_s} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.7 rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.7 rolling sds 2227.5 ${gamma_roll} ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.7 rolling sds 2227.5 0 ${mu_roll}
pair_coeff * * mdr 5000000 0.4 190000 2 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.7 rolling sds 2227.5 0 0.6
######################################### ADD DIE AND PUNCH WALLS ############################################
variable disp_upper equal 0.0
variable disp_lower equal 0.0
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergyWall} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}"
granular mdr 5000000 ${PoissonsRatio} ${YieldStress} ${SurfaceEnergyWall} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 ${YieldStress} ${SurfaceEnergyWall} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 ${SurfaceEnergyWall} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 ${damp} damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr ${damp_type} tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history ${kt_wall} ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 ${xgammat} ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 ${mu_s_wall} rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds ${k_roll} ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 ${gamma_roll} ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 0 ${mu_roll}
granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 0 0.6
variable dieHeight2 equal 2*${dieHeight}
variable dieHeight2 equal 2*0.01
region lowerPunch plane 0 0 0 0 0 1 side in units box move NULL NULL v_disp_lower units box
region upperPunch plane 0 0 ${dieHeight} 0 0 -1 side in move NULL NULL v_disp_upper units box
region upperPunch plane 0 0 0.01 0 0 -1 side in move NULL NULL v_disp_upper units box
region die cylinder z 0 0 ${dieRadius} 0 ${dieHeight2} side in units box
region die cylinder z 0 0 0.004 0 ${dieHeight2} side in units box
region die cylinder z 0 0 0.004 0 0.02 side in units box
fix lowerPunch all wall/gran/region ${wall_contact_string} region lowerPunch contacts
fix lowerPunch all wall/gran/region granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 0 0.6 region lowerPunch contacts
fix upperPunch all wall/gran/region ${wall_contact_string} region upperPunch contacts
fix upperPunch all wall/gran/region granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 0 0.6 region upperPunch contacts
fix die all wall/gran/region ${wall_contact_string} region die contacts
fix die all wall/gran/region granular mdr 5000000 0.4 190000 0 0.5 0.2 damping mdr 1 tangential linear_history 785.714285714286 1 0.1 rolling sds 2227.5 0 0.6 region die contacts
compute avgUpperPunchForce all reduce sum f_upperPunch[4]
variable avgUpperPunchForce equal c_avgUpperPunchForce
compute avgLowerPunchForce all reduce sum f_lowerPunch[4]
variable avgLowerPunchForce equal c_avgLowerPunchForce
#fix printFD all print 1 "${disp_upper} ${avgUpperPunchForce} ${avgLowerPunchForce}" file punch_force_disp_tableting200.csv screen no
##################################### INTEGRATION AND GRAVITY #################################################
fix 1 all nve/sphere
fix grav all gravity 9.81 vector 0 0 -1
########################################### SCREEN OUTPUT ####################################################
compute 1 all erotate/sphere
thermo_style custom dt step atoms ke vol v_disp_upper
thermo 100
thermo_modify lost ignore norm no
##################################### SET UP DUMP OUTPUTS ####################################################
compute ke all ke/atom
variable output_rate equal round(1e-3/dt)
run 0
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- MDR contact model command: (i) https://doi.org/10.1016/j.jmps.2023.105492 || (ii) https://doi.org/10.1016/j.jmps.2023.105493 || (iii) https://doi.org/10.31224/4289
@Article{zunker2024mechanicallyI,
author = {Zunker, William and Kamrin, Ken},
title = {A mechanically-derived contact model for adhesive elastic-perfectly plastic particles,
Part I: Utilizing the method of dimensionality reduction},
journal = {Journal of the Mechanics and Physics of Solids},
year = {2024},
volume = {183},
pages = {105492},
}
@Article{zunker2024mechanicallyII,
author = {Zunker, William and Kamrin, Ken},
title = {A mechanically-derived contact model for adhesive elastic-perfectly plastic particles,
Part II: Contact under high compaction—modeling a bulk elastic response},
journal = {Journal of the Mechanics and Physics of Solids},
year = {2024},
volume = {183},
pages = {105493},
}
@Article{zunker2025experimentally,
author = {Zunker, William and Dunatunga, Sachith and Thakur, Subhash and Tang, Pingjun and Kamrin, Ken},
title = {Experimentally validated DEM for large deformation powder compaction:
mechanically-derived contact model and screening of non-physical contacts},
journal = {Powder Technology},
year = {2025},
pages = {120972},
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 10 steps, delay = 60 steps, check = no
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 0.002318
ghost atom cutoff = 0.002318
binsize = 0.001159, bins = 9 9 19
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair granular, perpetual
attributes: half, newton off, size, history
pair build: half/size/bin/atomonly/newtoff
stencil: full/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 72.3 | 72.3 | 72.3 Mbytes
Dt Step Atoms KinEng Volume v_disp_upper
4e-06 0 200 0 2.1e-06 0
Loop time of 7.43e-07 on 1 procs for 0 steps with 200 atoms
134.6% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0 | 0 | 0 | 0.0 | 0.00
Neigh | 0 | 0 | 0 | 0.0 | 0.00
Comm | 0 | 0 | 0 | 0.0 | 0.00
Output | 0 | 0 | 0 | 0.0 | 0.00
Modify | 0 | 0 | 0 | 0.0 | 0.00
Other | | 7.43e-07 | | |100.00
Nlocal: 200 ave 200 max 200 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 1341 ave 1341 max 1341 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 1341
Ave neighs/atom = 6.705
Neighbor list builds = 0
Dangerous builds not checked
compute sigmaxx all property/atom d_sigmaxx
compute sigmayy all property/atom d_sigmayy
compute sigmazz all property/atom d_sigmazz
compute Velas all property/atom d_Velas
compute sigmaxx_ave all reduce ave c_sigmaxx
compute sigmayy_ave all reduce ave c_sigmayy
compute sigmazz_ave all reduce ave c_sigmazz
compute Velas_sum all reduce sum c_Velas
variable sxx_ave equal c_sigmaxx_ave
variable syy_ave equal c_sigmayy_ave
variable szz_ave equal c_sigmazz_ave
variable Vparticles equal c_Velas_sum
#fix log all print 1 "${sxx_ave} ${syy_ave} ${szz_ave} ${Vparticles}" file average_normal_stresses_tableting200.csv screen no
#dump dumpParticles all custom ${output_rate} tableting200.dump id type mass diameter x y z vx vy vz fx fy fz c_ke c_sigmaxx c_sigmayy c_sigmazz
#dump dumpParticlesVTK all vtk ${output_rate} post/particles_*.vtk id x y z fx fy fz vx vy vz c_ke radius c_sigmaxx c_sigmayy c_sigmazz
############################################## RUN SIMULATION #################################################
variable upper_punch_stroke equal 0.7*${dieHeight}
variable upper_punch_stroke equal 0.7*0.01
variable vel_upper equal 0.25
variable settling_steps equal round(0.02/dt)
variable compression_steps equal 2*round(${upper_punch_stroke}/${vel_upper}/dt)
variable compression_steps equal 2*round(0.007/${vel_upper}/dt)
variable compression_steps equal 2*round(0.007/0.25/dt)
variable ejection_steps equal ${compression_steps}
variable ejection_steps equal 14000
variable free_float_steps equal round(0.02/dt)
##### SETTLING #####
run ${settling_steps}
run 5000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 72.3 | 72.3 | 72.3 Mbytes
Dt Step Atoms KinEng Volume v_disp_upper
4e-06 0 200 0 2.1e-06 0
4e-06 100 200 1.5945503e-09 2.1e-06 0
4e-06 200 200 6.3750614e-09 2.1e-06 0
4e-06 300 200 1.4225143e-08 2.1e-06 0
4e-06 400 200 2.5255561e-08 2.1e-06 0
4e-06 500 200 3.947508e-08 2.1e-06 0
4e-06 600 200 5.6839079e-08 2.1e-06 0
4e-06 700 200 7.7346494e-08 2.1e-06 0
4e-06 800 200 1.0075645e-07 2.1e-06 0
4e-06 900 200 1.2660105e-07 2.1e-06 0
4e-06 1000 200 1.5571123e-07 2.1e-06 0
4e-06 1100 200 1.8785107e-07 2.1e-06 0
4e-06 1200 200 2.2200974e-07 2.1e-06 0
4e-06 1300 200 2.6009223e-07 2.1e-06 0
4e-06 1400 200 3.0148646e-07 2.1e-06 0
4e-06 1500 200 3.4269724e-07 2.1e-06 0
4e-06 1600 200 3.8502938e-07 2.1e-06 0
4e-06 1700 200 4.2763891e-07 2.1e-06 0
4e-06 1800 200 4.6779321e-07 2.1e-06 0
4e-06 1900 200 5.1285578e-07 2.1e-06 0
4e-06 2000 200 5.6630973e-07 2.1e-06 0
4e-06 2100 200 6.1904302e-07 2.1e-06 0
4e-06 2200 200 6.7462868e-07 2.1e-06 0
4e-06 2300 200 7.3066636e-07 2.1e-06 0
4e-06 2400 200 7.7407334e-07 2.1e-06 0
4e-06 2500 200 8.3353557e-07 2.1e-06 0
4e-06 2600 200 9.0017986e-07 2.1e-06 0
4e-06 2700 200 9.5154909e-07 2.1e-06 0
4e-06 2800 200 1.0110977e-06 2.1e-06 0
4e-06 2900 200 1.0661364e-06 2.1e-06 0
4e-06 3000 200 1.1226841e-06 2.1e-06 0
4e-06 3100 200 1.1703917e-06 2.1e-06 0
4e-06 3200 200 1.2254551e-06 2.1e-06 0
4e-06 3300 200 1.2239859e-06 2.1e-06 0
4e-06 3400 200 1.273437e-06 2.1e-06 0
4e-06 3500 200 1.3357598e-06 2.1e-06 0
4e-06 3600 200 1.3949477e-06 2.1e-06 0
4e-06 3700 200 1.459988e-06 2.1e-06 0
4e-06 3800 200 1.5053806e-06 2.1e-06 0
4e-06 3900 200 1.4952453e-06 2.1e-06 0
4e-06 4000 200 1.5037857e-06 2.1e-06 0
4e-06 4100 200 1.5225204e-06 2.1e-06 0
4e-06 4200 200 1.5375323e-06 2.1e-06 0
4e-06 4300 200 1.5552328e-06 2.1e-06 0
4e-06 4400 200 1.581097e-06 2.1e-06 0
4e-06 4500 200 1.6066427e-06 2.1e-06 0
4e-06 4600 200 1.6061944e-06 2.1e-06 0
4e-06 4700 200 1.6110891e-06 2.1e-06 0
4e-06 4800 200 1.6072997e-06 2.1e-06 0
4e-06 4900 200 1.5907992e-06 2.1e-06 0
4e-06 5000 200 1.5501104e-06 2.1e-06 0
Loop time of 0.592588 on 1 procs for 5000 steps with 200 atoms
99.4% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.20465 | 0.20465 | 0.20465 | 0.0 | 34.53
Neigh | 0.013252 | 0.013252 | 0.013252 | 0.0 | 2.24
Comm | 0.00037594 | 0.00037594 | 0.00037594 | 0.0 | 0.06
Output | 0.00037454 | 0.00037454 | 0.00037454 | 0.0 | 0.06
Modify | 0.37295 | 0.37295 | 0.37295 | 0.0 | 62.93
Other | | 0.0009914 | | | 0.17
Nlocal: 200 ave 200 max 200 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 1632 ave 1632 max 1632 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 1632
Ave neighs/atom = 8.16
Neighbor list builds = 83
Dangerous builds not checked
##### Compression & Release #####
variable punch_frequency equal PI/2/(dt*${compression_steps}/2)
variable punch_frequency equal PI/2/(dt*14000/2)
variable disp_upper equal -${upper_punch_stroke}*sin(${punch_frequency}*elapsed*dt)
variable disp_upper equal -0.007*sin(${punch_frequency}*elapsed*dt)
variable disp_upper equal -0.007*sin(56.0998688141035*elapsed*dt)
variable short_release equal round(${compression_steps}*1.0)
variable short_release equal round(14000*1.0)
run ${short_release}
run 14000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 72.3 | 72.3 | 72.3 Mbytes
Dt Step Atoms KinEng Volume v_disp_upper
4e-06 5000 200 1.5501104e-06 2.1e-06 0
4e-06 5100 200 1.5146077e-06 2.1e-06 -0.00015706645
4e-06 5200 200 1.4902158e-06 2.1e-06 -0.00031405381
4e-06 5300 200 1.3871134e-06 2.1e-06 -0.00047088304
4e-06 5400 200 1.3531184e-06 2.1e-06 -0.00062747516
4e-06 5500 200 1.3154278e-06 2.1e-06 -0.00078375133
4e-06 5600 200 1.2461265e-06 2.1e-06 -0.00093963286
4e-06 5700 200 1.1840322e-06 2.1e-06 -0.0010950413
4e-06 5800 200 1.083844e-06 2.1e-06 -0.0012498983
4e-06 5900 200 9.8572649e-07 2.1e-06 -0.0014041259
4e-06 6000 200 8.6605656e-07 2.1e-06 -0.0015576465
4e-06 6100 200 7.6694391e-07 2.1e-06 -0.0017103828
4e-06 6200 200 7.1292979e-07 2.1e-06 -0.0018622579
4e-06 6300 200 6.475067e-07 2.1e-06 -0.0020131953
4e-06 6400 200 5.378202e-07 2.1e-06 -0.002163119
4e-06 6500 200 4.5668598e-07 2.1e-06 -0.0023119534
4e-06 6600 200 3.1208987e-07 2.1e-06 -0.0024596238
4e-06 6700 200 2.2996407e-07 2.1e-06 -0.0026060556
4e-06 6800 200 1.658813e-07 2.1e-06 -0.0027511752
4e-06 6900 200 1.4495016e-07 2.1e-06 -0.0028949095
4e-06 7000 200 1.6172966e-07 2.1e-06 -0.0030371862
4e-06 7100 200 4.6620591e-07 2.1e-06 -0.0031779335
4e-06 7200 200 6.8121833e-07 2.1e-06 -0.0033170806
4e-06 7300 200 1.5506154e-06 2.1e-06 -0.0034545575
4e-06 7400 200 2.5919669e-06 2.1e-06 -0.0035902949
4e-06 7500 200 2.9403576e-06 2.1e-06 -0.0037242245
4e-06 7600 200 2.7726732e-06 2.1e-06 -0.0038562789
4e-06 7700 200 2.6586936e-06 2.1e-06 -0.0039863915
4e-06 7800 200 2.7059447e-06 2.1e-06 -0.0041144968
4e-06 7900 200 2.8454301e-06 2.1e-06 -0.0042405303
4e-06 8000 200 2.7747574e-06 2.1e-06 -0.0043644286
4e-06 8100 200 2.6329747e-06 2.1e-06 -0.0044861293
4e-06 8200 200 2.3654294e-06 2.1e-06 -0.0046055711
4e-06 8300 200 2.616465e-06 2.1e-06 -0.0047226938
4e-06 8400 200 2.6920973e-06 2.1e-06 -0.0048374385
4e-06 8500 200 2.6041158e-06 2.1e-06 -0.0049497475
4e-06 8600 200 1.8236056e-06 2.1e-06 -0.005059564
4e-06 8700 200 2.1290462e-06 2.1e-06 -0.005166833
4e-06 8800 200 1.8723934e-06 2.1e-06 -0.0052715003
4e-06 8900 200 1.7196474e-06 2.1e-06 -0.0053735132
4e-06 9000 200 1.558001e-06 2.1e-06 -0.0054728204
4e-06 9100 200 1.1714433e-06 2.1e-06 -0.0055693718
4e-06 9200 200 1.7973167e-06 2.1e-06 -0.005663119
4e-06 9300 200 1.4951874e-06 2.1e-06 -0.0057540145
4e-06 9400 200 1.197557e-06 2.1e-06 -0.0058420128
4e-06 9500 200 1.1638085e-06 2.1e-06 -0.0059270694
4e-06 9600 200 1.2591061e-06 2.1e-06 -0.0060091416
4e-06 9700 200 1.2747299e-06 2.1e-06 -0.0060881879
4e-06 9800 200 1.2424243e-06 2.1e-06 -0.0061641687
4e-06 9900 200 1.1624586e-06 2.1e-06 -0.0062370457
4e-06 10000 200 1.0724272e-06 2.1e-06 -0.0063067821
4e-06 10100 200 1.0806622e-06 2.1e-06 -0.0063733428
4e-06 10200 200 9.2046484e-07 2.1e-06 -0.0064366944
4e-06 10300 200 8.1801156e-07 2.1e-06 -0.0064968049
4e-06 10400 200 7.74927e-07 2.1e-06 -0.0065536441
4e-06 10500 200 6.85447e-07 2.1e-06 -0.0066071833
4e-06 10600 200 5.4693931e-07 2.1e-06 -0.0066573956
4e-06 10700 200 4.5275522e-07 2.1e-06 -0.0067042557
4e-06 10800 200 4.2807826e-07 2.1e-06 -0.00674774
4e-06 10900 200 3.5676739e-07 2.1e-06 -0.0067878266
4e-06 11000 200 2.9448839e-07 2.1e-06 -0.0068244954
4e-06 11100 200 2.7397196e-07 2.1e-06 -0.0068577278
4e-06 11200 200 1.8313029e-07 2.1e-06 -0.0068875071
4e-06 11300 200 1.4616679e-07 2.1e-06 -0.0069138184
4e-06 11400 200 1.0916404e-07 2.1e-06 -0.0069366483
4e-06 11500 200 7.4608897e-08 2.1e-06 -0.0069559855
4e-06 11600 200 4.9799693e-08 2.1e-06 -0.0069718201
4e-06 11700 200 2.996701e-08 2.1e-06 -0.0069841441
4e-06 11800 200 1.1810054e-08 2.1e-06 -0.0069929515
4e-06 11900 200 3.9455661e-09 2.1e-06 -0.0069982376
4e-06 12000 200 7.0818836e-11 2.1e-06 -0.007
4e-06 12100 200 3.989114e-09 2.1e-06 -0.0069982376
4e-06 12200 200 1.0481589e-08 2.1e-06 -0.0069929515
4e-06 12300 200 2.3561653e-08 2.1e-06 -0.0069841441
4e-06 12400 200 4.1819363e-08 2.1e-06 -0.0069718201
4e-06 12500 200 6.5328826e-08 2.1e-06 -0.0069559855
4e-06 12600 200 9.3738095e-08 2.1e-06 -0.0069366483
4e-06 12700 200 1.3058219e-07 2.1e-06 -0.0069138184
4e-06 12800 200 1.7668602e-07 2.1e-06 -0.0068875071
4e-06 12900 200 2.1482809e-07 2.1e-06 -0.0068577278
4e-06 13000 200 2.7185589e-07 2.1e-06 -0.0068244954
4e-06 13100 200 3.3577426e-07 2.1e-06 -0.0067878266
4e-06 13200 200 3.9749034e-07 2.1e-06 -0.00674774
4e-06 13300 200 5.0743398e-07 2.1e-06 -0.0067042557
4e-06 13400 200 5.6629069e-07 2.1e-06 -0.0066573956
4e-06 13500 200 5.9092105e-07 2.1e-06 -0.0066071833
4e-06 13600 200 7.313638e-07 2.1e-06 -0.0065536441
4e-06 13700 200 1.0954352e-06 2.1e-06 -0.0064968049
4e-06 13800 200 7.1637332e-07 2.1e-06 -0.0064366944
4e-06 13900 200 8.5398051e-07 2.1e-06 -0.0063733428
4e-06 14000 200 1.0429888e-06 2.1e-06 -0.0063067821
4e-06 14100 200 1.6673022e-07 2.1e-06 -0.0062370457
4e-06 14200 200 2.0206568e-08 2.1e-06 -0.0061641687
4e-06 14300 200 5.6062261e-09 2.1e-06 -0.0060881879
4e-06 14400 200 4.5198973e-09 2.1e-06 -0.0060091416
4e-06 14500 200 2.5522353e-09 2.1e-06 -0.0059270694
4e-06 14600 200 9.091094e-10 2.1e-06 -0.0058420128
4e-06 14700 200 1.3992806e-10 2.1e-06 -0.0057540145
4e-06 14800 200 1.0208666e-11 2.1e-06 -0.005663119
4e-06 14900 200 8.4078334e-11 2.1e-06 -0.0055693718
4e-06 15000 200 1.2567311e-10 2.1e-06 -0.0054728204
4e-06 15100 200 5.2285722e-10 2.1e-06 -0.0053735132
4e-06 15200 200 1.5839179e-10 2.1e-06 -0.0052715003
4e-06 15300 200 3.2283374e-11 2.1e-06 -0.005166833
4e-06 15400 200 2.9516435e-12 2.1e-06 -0.005059564
4e-06 15500 200 1.0302118e-11 2.1e-06 -0.0049497475
4e-06 15600 200 1.7289975e-11 2.1e-06 -0.0048374385
4e-06 15700 200 1.4850209e-11 2.1e-06 -0.0047226938
4e-06 15800 200 8.0260964e-12 2.1e-06 -0.0046055711
4e-06 15900 200 2.616591e-12 2.1e-06 -0.0044861293
4e-06 16000 200 3.0793261e-13 2.1e-06 -0.0043644286
4e-06 16100 200 4.9187696e-13 2.1e-06 -0.0042405303
4e-06 16200 200 3.9849142e-13 2.1e-06 -0.0041144968
4e-06 16300 200 5.2823345e-13 2.1e-06 -0.0039863915
4e-06 16400 200 3.9902725e-13 2.1e-06 -0.0038562789
4e-06 16500 200 1.9259043e-13 2.1e-06 -0.0037242245
4e-06 16600 200 5.3557316e-14 2.1e-06 -0.0035902949
4e-06 16700 200 3.7734621e-15 2.1e-06 -0.0034545575
4e-06 16800 200 3.0867115e-15 2.1e-06 -0.0033170806
4e-06 16900 200 1.1841579e-14 2.1e-06 -0.0031779335
4e-06 17000 200 1.3850503e-14 2.1e-06 -0.0030371862
4e-06 17100 200 9.8491914e-15 2.1e-06 -0.0028949095
4e-06 17200 200 4.7140149e-15 2.1e-06 -0.0027511752
4e-06 17300 200 1.3440466e-15 2.1e-06 -0.0026060556
4e-06 17400 200 1.0627828e-16 2.1e-06 -0.0024596238
4e-06 17500 200 6.2015781e-17 2.1e-06 -0.0023119534
4e-06 17600 200 2.8723007e-16 2.1e-06 -0.002163119
4e-06 17700 200 3.6601367e-16 2.1e-06 -0.0020131953
4e-06 17800 200 2.7862312e-16 2.1e-06 -0.0018622579
4e-06 17900 200 1.4268051e-16 2.1e-06 -0.0017103828
4e-06 18000 200 4.5443603e-17 2.1e-06 -0.0015576465
4e-06 18100 200 5.2330376e-18 2.1e-06 -0.0014041259
4e-06 18200 200 7.3566254e-19 2.1e-06 -0.0012498983
4e-06 18300 200 6.5880468e-18 2.1e-06 -0.0010950413
4e-06 18400 200 9.5744931e-18 2.1e-06 -0.00093963286
4e-06 18500 200 7.8604487e-18 2.1e-06 -0.00078375133
4e-06 18600 200 4.3166295e-18 2.1e-06 -0.00062747516
4e-06 18700 200 1.5188792e-18 2.1e-06 -0.00047088304
4e-06 18800 200 2.3221067e-19 2.1e-06 -0.00031405381
4e-06 18900 200 4.7558964e-21 2.1e-06 -0.00015706645
4e-06 19000 200 1.4567292e-19 2.1e-06 2.0903119e-17
Loop time of 6.96616 on 1 procs for 14000 steps with 200 atoms
99.5% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 3.8534 | 3.8534 | 3.8534 | 0.0 | 55.32
Neigh | 0.038778 | 0.038778 | 0.038778 | 0.0 | 0.56
Comm | 0.0015081 | 0.0015081 | 0.0015081 | 0.0 | 0.02
Output | 0.0018007 | 0.0018007 | 0.0018007 | 0.0 | 0.03
Modify | 3.0668 | 3.0668 | 3.0668 | 0.0 | 44.02
Other | | 0.003851 | | | 0.06
Nlocal: 200 ave 200 max 200 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 3031 ave 3031 max 3031 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 3031
Ave neighs/atom = 15.155
Neighbor list builds = 233
Dangerous builds not checked
##### EJECTION #####
variable punch_frequency equal PI/2/(dt*${ejection_steps})
variable punch_frequency equal PI/2/(dt*14000)
variable disp_lower equal ${dieHeight}*sin(${punch_frequency}*elapsed*dt)
variable disp_lower equal 0.01*sin(${punch_frequency}*elapsed*dt)
variable disp_lower equal 0.01*sin(28.0499344070517*elapsed*dt)
variable disp_upper equal 0.9*v_disp_lower
run ${ejection_steps}
run 14000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 72.31 | 72.31 | 72.31 Mbytes
Dt Step Atoms KinEng Volume v_disp_upper
4e-06 19000 200 1.4567292e-19 2.1e-06 0
4e-06 19100 200 1.9132195e-05 2.1e-06 0.00010097765
4e-06 19200 200 3.1561748e-06 2.1e-06 0.00020194258
4e-06 19300 200 1.4462178e-05 2.1e-06 0.00030288209
4e-06 19400 200 4.6622112e-06 2.1e-06 0.00040378347
4e-06 19500 200 1.1929852e-05 2.1e-06 0.00050463403
4e-06 19600 200 5.6933661e-06 2.1e-06 0.00060542105
4e-06 19700 200 1.0429976e-05 2.1e-06 0.00070613186
4e-06 19800 200 6.6580254e-06 2.1e-06 0.00080675378
4e-06 19900 200 9.1721686e-06 2.1e-06 0.00090727414
4e-06 20000 200 7.4553343e-06 2.1e-06 0.0010076803
4e-06 20100 200 8.3534813e-06 2.1e-06 0.0011079596
4e-06 20200 200 7.8671075e-06 2.1e-06 0.0012080994
4e-06 20300 200 7.9115898e-06 2.1e-06 0.0013080871
4e-06 20400 200 8.2222312e-06 2.1e-06 0.0014079102
4e-06 20500 200 7.5281175e-06 2.1e-06 0.001507556
4e-06 20600 200 8.4242027e-06 2.1e-06 0.0016070121
4e-06 20700 200 7.3282364e-06 2.1e-06 0.0017062658
4e-06 20800 200 8.3501222e-06 2.1e-06 0.0018053047
4e-06 20900 200 7.3417566e-06 2.1e-06 0.0019041164
4e-06 21000 200 8.0702927e-06 2.1e-06 0.0020026884
4e-06 21100 200 7.5896194e-06 2.1e-06 0.0021010083
4e-06 21200 200 7.6596342e-06 2.1e-06 0.0021990637
4e-06 21300 200 7.7009755e-06 2.1e-06 0.0022968422
4e-06 21400 200 7.4010568e-06 2.1e-06 0.0023943316
4e-06 21500 200 7.7254953e-06 2.1e-06 0.0024915196
4e-06 21600 200 7.2931076e-06 2.1e-06 0.0025883939
4e-06 21700 200 7.5667043e-06 2.1e-06 0.0026849424
4e-06 21800 200 7.2767179e-06 2.1e-06 0.0027811529
4e-06 21900 200 7.3632148e-06 2.1e-06 0.0028770133
4e-06 22000 200 7.2563523e-06 2.1e-06 0.0029725116
4e-06 22100 200 7.2003226e-06 2.1e-06 0.0030676356
4e-06 22200 200 7.1862422e-06 2.1e-06 0.0031623734
4e-06 22300 200 7.0035785e-06 2.1e-06 0.0032567132
4e-06 22400 200 7.1023437e-06 2.1e-06 0.0033506429
4e-06 22500 200 6.8767896e-06 2.1e-06 0.0034441509
4e-06 22600 200 6.9556381e-06 2.1e-06 0.0035372253
4e-06 22700 200 6.7754491e-06 2.1e-06 0.0036298544
4e-06 22800 200 6.7752923e-06 2.1e-06 0.0037220265
4e-06 22900 200 6.6947789e-06 2.1e-06 0.0038137301
4e-06 23000 200 6.5811876e-06 2.1e-06 0.0039049537
4e-06 23100 200 6.5600064e-06 2.1e-06 0.0039956856
4e-06 23200 200 6.407054e-06 2.1e-06 0.0040859145
4e-06 23300 200 6.4635326e-06 2.1e-06 0.0041756291
4e-06 23400 200 6.2604509e-06 2.1e-06 0.004264818
4e-06 23500 200 6.2914059e-06 2.1e-06 0.00435347
4e-06 23600 200 6.1416598e-06 2.1e-06 0.004441574
4e-06 23700 200 6.0839487e-06 2.1e-06 0.0045291188
4e-06 23800 200 6.0216029e-06 2.1e-06 0.0046160935
4e-06 23900 200 5.896464e-06 2.1e-06 0.0047024871
4e-06 24000 200 5.8682556e-06 2.1e-06 0.0047882887
4e-06 24100 200 5.8744357e-06 2.1e-06 0.0048734875
4e-06 24200 200 5.6172509e-06 2.1e-06 0.0049580728
4e-06 24300 200 5.6527872e-06 2.1e-06 0.005042034
4e-06 24400 200 5.4706998e-06 2.1e-06 0.0051253604
4e-06 24500 200 5.4368713e-06 2.1e-06 0.0052080417
4e-06 24600 200 5.3496195e-06 2.1e-06 0.0052900673
4e-06 24700 200 5.2020248e-06 2.1e-06 0.0053714269
4e-06 24800 200 5.2035809e-06 2.1e-06 0.0054521104
4e-06 24900 200 5.0302031e-06 2.1e-06 0.0055321075
4e-06 25000 200 5.0094633e-06 2.1e-06 0.0056114082
4e-06 25100 200 4.8588064e-06 2.1e-06 0.0056900025
4e-06 25200 200 4.8221437e-06 2.1e-06 0.0057678805
4e-06 25300 200 4.7117322e-06 2.1e-06 0.0058450324
4e-06 25400 200 4.6148719e-06 2.1e-06 0.0059214485
4e-06 25500 200 4.5348297e-06 2.1e-06 0.0059971192
4e-06 25600 200 4.4325937e-06 2.1e-06 0.0060720349
4e-06 25700 200 4.3587865e-06 2.1e-06 0.0061461862
4e-06 25800 200 4.2449842e-06 2.1e-06 0.0062195638
4e-06 25900 200 4.1730814e-06 2.1e-06 0.0062921585
4e-06 26000 200 4.0712085e-06 2.1e-06 0.006363961
4e-06 26100 200 3.9603603e-06 2.1e-06 0.0064349624
4e-06 26200 200 3.9152641e-06 2.1e-06 0.0065051538
4e-06 26300 200 3.7864366e-06 2.1e-06 0.0065745262
4e-06 26400 200 3.7211553e-06 2.1e-06 0.006643071
4e-06 26500 200 3.6038142e-06 2.1e-06 0.0067107795
4e-06 26600 200 3.5518456e-06 2.1e-06 0.0067776432
4e-06 26700 200 3.4213616e-06 2.1e-06 0.0068436537
4e-06 26800 200 3.348649e-06 2.1e-06 0.0069088027
4e-06 26900 200 3.2592054e-06 2.1e-06 0.0069730819
4e-06 27000 200 3.1640896e-06 2.1e-06 0.0070364833
4e-06 27100 200 3.1491467e-06 2.1e-06 0.007098999
4e-06 27200 200 2.9475347e-06 2.1e-06 0.0071606209
4e-06 27300 200 2.9234007e-06 2.1e-06 0.0072213415
4e-06 27400 200 2.8106832e-06 2.1e-06 0.0072811529
4e-06 27500 200 2.7190831e-06 2.1e-06 0.0073400478
4e-06 27600 200 2.6595021e-06 2.1e-06 0.0073980187
4e-06 27700 200 2.5384163e-06 2.1e-06 0.0074550582
4e-06 27800 200 2.4906759e-06 2.1e-06 0.0075111593
4e-06 27900 200 2.3760852e-06 2.1e-06 0.0075663148
4e-06 28000 200 2.3135864e-06 2.1e-06 0.0076205178
4e-06 28100 200 2.206388e-06 2.1e-06 0.0076737615
4e-06 28200 200 2.1580755e-06 2.1e-06 0.0077260391
4e-06 28300 200 2.0541807e-06 2.1e-06 0.0077773442
4e-06 28400 200 1.9879886e-06 2.1e-06 0.0078276702
4e-06 28500 200 1.9080731e-06 2.1e-06 0.0078770108
4e-06 28600 200 1.8244513e-06 2.1e-06 0.0079253598
4e-06 28700 200 1.7612085e-06 2.1e-06 0.0079727111
4e-06 28800 200 1.6725418e-06 2.1e-06 0.0080190587
4e-06 28900 200 1.6108221e-06 2.1e-06 0.0080643969
4e-06 29000 200 1.5315923e-06 2.1e-06 0.0081087198
4e-06 29100 200 1.4668177e-06 2.1e-06 0.008152022
4e-06 29200 200 1.389947e-06 2.1e-06 0.0081942979
4e-06 29300 200 1.3244327e-06 2.1e-06 0.0082355423
4e-06 29400 200 1.2613389e-06 2.1e-06 0.00827575
4e-06 29500 200 1.189317e-06 2.1e-06 0.0083149158
4e-06 29600 200 1.1328651e-06 2.1e-06 0.0083530349
4e-06 29700 200 1.0634003e-06 2.1e-06 0.0083901025
4e-06 29800 200 1.0089659e-06 2.1e-06 0.0084261138
4e-06 29900 200 9.452383e-07 2.1e-06 0.0084610645
4e-06 30000 200 8.8857387e-07 2.1e-06 0.00849495
4e-06 30100 200 8.3934751e-07 2.1e-06 0.0085277661
4e-06 30200 200 7.7404495e-07 2.1e-06 0.0085595086
4e-06 30300 200 7.2760888e-07 2.1e-06 0.0085901737
4e-06 30400 200 6.7239685e-07 2.1e-06 0.0086197574
4e-06 30500 200 6.245416e-07 2.1e-06 0.0086482559
4e-06 30600 200 5.7834155e-07 2.1e-06 0.0086756657
4e-06 30700 200 5.2814574e-07 2.1e-06 0.0087019834
4e-06 30800 200 4.8878902e-07 2.1e-06 0.0087272057
4e-06 30900 200 4.4241206e-07 2.1e-06 0.0087513293
4e-06 31000 200 4.0442514e-07 2.1e-06 0.0087743512
4e-06 31100 200 3.642199e-07 2.1e-06 0.0087962686
4e-06 31200 200 3.2738558e-07 2.1e-06 0.0088170786
4e-06 31300 200 2.9389397e-07 2.1e-06 0.0088367787
4e-06 31400 200 2.5861566e-07 2.1e-06 0.0088553663
4e-06 31500 200 2.2934636e-07 2.1e-06 0.0088728392
4e-06 31600 200 1.9888494e-07 2.1e-06 0.0088891951
4e-06 31700 200 1.7250531e-07 2.1e-06 0.0089044319
4e-06 31800 200 1.4678036e-07 2.1e-06 0.0089185479
4e-06 31900 200 1.2324632e-07 2.1e-06 0.0089315411
4e-06 32000 200 1.0248084e-07 2.1e-06 0.0089434099
4e-06 32100 200 8.2609273e-08 2.1e-06 0.0089541529
4e-06 32200 200 6.551679e-08 2.1e-06 0.0089637686
4e-06 32300 200 5.0080052e-08 2.1e-06 0.008972256
4e-06 32400 200 3.6856646e-08 2.1e-06 0.0089796139
4e-06 32500 200 2.5648284e-08 2.1e-06 0.0089858413
4e-06 32600 200 1.637837e-08 2.1e-06 0.0089909376
4e-06 32700 200 9.2578154e-09 2.1e-06 0.008994902
4e-06 32800 200 4.0824723e-09 2.1e-06 0.0089977341
4e-06 32900 200 1.0371165e-09 2.1e-06 0.0089994335
4e-06 33000 200 6.1012168e-14 2.1e-06 0.009
Loop time of 7.70808 on 1 procs for 14000 steps with 200 atoms
99.6% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 4.4414 | 4.4414 | 4.4414 | 0.0 | 57.62
Neigh | 0.040941 | 0.040941 | 0.040941 | 0.0 | 0.53
Comm | 0.001526 | 0.001526 | 0.001526 | 0.0 | 0.02
Output | 0.0019617 | 0.0019617 | 0.0019617 | 0.0 | 0.03
Modify | 3.2183 | 3.2183 | 3.2183 | 0.0 | 41.75
Other | | 0.003942 | | | 0.05
Nlocal: 200 ave 200 max 200 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 3026 ave 3026 max 3026 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 3026
Ave neighs/atom = 15.13
Neighbor list builds = 233
Dangerous builds not checked
##### FREE FLOAT #####
variable disp_lower equal ${dieHeight}
variable disp_lower equal 0.01
variable disp_upper equal ${dieHeight}*0.9
variable disp_upper equal 0.01*0.9
variable max_disp equal ${dieRadius}*0.75
variable max_disp equal 0.004*0.75
run ${free_float_steps}
run 5000
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Per MPI rank memory allocation (min/avg/max) = 72.31 | 72.31 | 72.31 Mbytes
Dt Step Atoms KinEng Volume v_disp_upper
4e-06 33000 200 6.1012168e-14 2.1e-06 0.009
4e-06 33100 200 6.7902539e-11 2.1e-06 0.009
4e-06 33200 200 2.0896758e-11 2.1e-06 0.009
4e-06 33300 200 2.5200405e-11 2.1e-06 0.009
4e-06 33400 200 2.1747895e-12 2.1e-06 0.009
4e-06 33500 200 1.1228817e-11 2.1e-06 0.009
4e-06 33600 200 3.3597579e-12 2.1e-06 0.009
4e-06 33700 200 1.4808583e-12 2.1e-06 0.009
4e-06 33800 200 3.5132295e-12 2.1e-06 0.009
4e-06 33900 200 8.2438639e-14 2.1e-06 0.009
4e-06 34000 200 1.3267378e-12 2.1e-06 0.009
4e-06 34100 200 6.2365031e-13 2.1e-06 0.009
4e-06 34200 200 1.1820072e-13 2.1e-06 0.009
4e-06 34300 200 5.2797742e-13 2.1e-06 0.009
4e-06 34400 200 3.2199555e-14 2.1e-06 0.009
4e-06 34500 200 1.553388e-13 2.1e-06 0.009
4e-06 34600 200 1.1458173e-13 2.1e-06 0.009
4e-06 34700 200 5.8686124e-15 2.1e-06 0.009
4e-06 34800 200 7.3486748e-14 2.1e-06 0.009
4e-06 34900 200 1.0877367e-14 2.1e-06 0.009
4e-06 35000 200 1.5284442e-14 2.1e-06 0.009
4e-06 35100 200 2.0294057e-14 2.1e-06 0.009
4e-06 35200 200 1.5385334e-17 2.1e-06 0.009
4e-06 35300 200 9.5858898e-15 2.1e-06 0.009
4e-06 35400 200 3.1985384e-15 2.1e-06 0.009
4e-06 35500 200 1.1327574e-15 2.1e-06 0.009
4e-06 35600 200 3.3810722e-15 2.1e-06 0.009
4e-06 35700 200 1.2867327e-16 2.1e-06 0.009
4e-06 35800 200 1.0755232e-15 2.1e-06 0.009
4e-06 35900 200 7.3381985e-16 2.1e-06 0.009
4e-06 36000 200 3.7750251e-17 2.1e-06 0.009
4e-06 36100 200 4.8518794e-16 2.1e-06 0.009
4e-06 36200 200 8.361623e-17 2.1e-06 0.009
4e-06 36300 200 8.9347649e-17 2.1e-06 0.009
4e-06 36400 200 1.4528409e-16 2.1e-06 0.009
4e-06 36500 200 8.2328133e-19 2.1e-06 0.009
4e-06 36600 200 5.9628413e-17 2.1e-06 0.009
4e-06 36700 200 2.857306e-17 2.1e-06 0.009
4e-06 36800 200 4.1078269e-18 2.1e-06 0.009
4e-06 36900 200 2.4094514e-17 2.1e-06 0.009
4e-06 37000 200 2.6153896e-18 2.1e-06 0.009
4e-06 37100 200 5.6577297e-18 2.1e-06 0.009
4e-06 37200 200 6.5849416e-18 2.1e-06 0.009
4e-06 37300 200 4.5596918e-21 2.1e-06 0.009
4e-06 37400 200 3.2329813e-18 2.1e-06 0.009
4e-06 37500 200 1.123288e-18 2.1e-06 0.009
4e-06 37600 200 3.4227094e-19 2.1e-06 0.009
4e-06 37700 200 1.1782135e-18 2.1e-06 0.009
4e-06 37800 200 6.9535961e-20 2.1e-06 0.009
4e-06 37900 200 3.4055174e-19 2.1e-06 0.009
4e-06 38000 200 2.8968649e-19 2.1e-06 0.009
Loop time of 2.65906 on 1 procs for 5000 steps with 200 atoms
99.6% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 1.5595 | 1.5595 | 1.5595 | 0.0 | 58.65
Neigh | 0.012904 | 0.012904 | 0.012904 | 0.0 | 0.49
Comm | 0.00041333 | 0.00041333 | 0.00041333 | 0.0 | 0.02
Output | 0.00053486 | 0.00053486 | 0.00053486 | 0.0 | 0.02
Modify | 1.0844 | 1.0844 | 1.0844 | 0.0 | 40.78
Other | | 0.001336 | | | 0.05
Nlocal: 200 ave 200 max 200 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 3026 ave 3026 max 3026 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 3026
Ave neighs/atom = 15.13
Neighbor list builds = 83
Dangerous builds not checked
Total wall time: 0:00:18

784
examples/granular/log.4Feb25.triaxial.compaction.12.g++.1 Normal file
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LAMMPS (4 Feb 2025 - Development - patch_5May2020-22356-g0c29a0a0c9-modified)
############################### SIMULATION SETTINGS ###################################################
atom_style sphere 1
atom_modify map array
comm_modify vel yes
units si
newton off
neighbor 2 bin
neigh_modify delay 0
timestep 1e-6
##################### SIMULATION BOUNDING BOX, INSERT PARTICLES, AND INTEGRATION #######################
boundary f f f
read_data spheres12.data
Reading data file ...
orthogonal box = (-10 -10 -10) to (10 10 10)
1 by 1 by 1 MPI processor grid
reading atoms ...
12 atoms
read_data CPU = 0.029 seconds
fix integr all nve/sphere
# create pair group for contact area outputs
group particles_1_12 id 1 12
2 atoms in group particles_1_12
########################### PARTICLE MATERIAL PROPERTIES AND FORCE MODEL ###############################
variable atomRadius equal 0.5
pair_style granular
# mdr = E, nu, Y, gamma, psi_b, damp
variable YoungsModulus equal 1e9
variable PoissonsRatio equal 0.3
variable YieldStress equal 50e6
variable SurfaceEnergy equal 0.0
variable psi_b equal 0.5
variable damp equal 0.2
variable damp_type equal 1
# linear_history = k_t, x_gamma,t, mu_s
variable kt equal 2/7*${YoungsModulus}*${atomRadius}
variable kt equal 2/7*1000000000*${atomRadius}
variable kt equal 2/7*1000000000*0.5
variable xgammat equal 0.0
variable mu_s equal 0.5
pair_coeff * * mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history ${kt} ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 ${xgammat} ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 ${mu_s}
pair_coeff * * mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5
######################################### ADD IN PLANES ################################################
variable boxWidth equal 3
variable halfBoxWidth equal ${boxWidth}/2
variable halfBoxWidth equal 3/2
variable plane_disp equal 0.0
variable plane_disp_neg equal 0.0
region plane_yz_pos plane ${halfBoxWidth} 0 0 -1 0 0 side in move v_plane_disp_neg NULL NULL units box
region plane_yz_pos plane 1.5 0 0 -1 0 0 side in move v_plane_disp_neg NULL NULL units box
region plane_yz_neg plane -${halfBoxWidth} 0 0 1 0 0 side in move v_plane_disp NULL NULL units box
region plane_yz_neg plane -1.5 0 0 1 0 0 side in move v_plane_disp NULL NULL units box
region plane_xz_pos plane 0 ${halfBoxWidth} 0 0 -1 0 side in move NULL v_plane_disp_neg NULL units box
region plane_xz_pos plane 0 1.5 0 0 -1 0 side in move NULL v_plane_disp_neg NULL units box
region plane_xz_neg plane 0 -${halfBoxWidth} 0 0 1 0 side in move NULL v_plane_disp NULL units box
region plane_xz_neg plane 0 -1.5 0 0 1 0 side in move NULL v_plane_disp NULL units box
region plane_xy_pos plane 0 0 ${halfBoxWidth} 0 0 -1 side in move NULL NULL v_plane_disp_neg units box
region plane_xy_pos plane 0 0 1.5 0 0 -1 side in move NULL NULL v_plane_disp_neg units box
region plane_xy_neg plane 0 0 -${halfBoxWidth} 0 0 1 side in move NULL NULL v_plane_disp units box
region plane_xy_neg plane 0 0 -1.5 0 0 1 side in move NULL NULL v_plane_disp units box
variable wall_contact_string string "granular mdr ${YoungsModulus} ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s} "
granular mdr 1000000000 ${PoissonsRatio} ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 ${YieldStress} ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 ${SurfaceEnergy} ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 ${psi_b} ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 ${damp} damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr ${damp_type} tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history ${kt} ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 ${xgammat} ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 ${mu_s}
granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5
fix plane_yz_pos all wall/gran/region ${wall_contact_string} region plane_yz_pos contacts
fix plane_yz_pos all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_yz_pos contacts
fix plane_yz_neg all wall/gran/region ${wall_contact_string} region plane_yz_neg contacts
fix plane_yz_neg all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_yz_neg contacts
fix plane_xz_pos all wall/gran/region ${wall_contact_string} region plane_xz_pos contacts
fix plane_xz_pos all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_xz_pos contacts
fix plane_xz_neg all wall/gran/region ${wall_contact_string} region plane_xz_neg contacts
fix plane_xz_neg all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_xz_neg contacts
fix plane_xy_pos all wall/gran/region ${wall_contact_string} region plane_xy_pos contacts
fix plane_xy_pos all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_xy_pos contacts
fix plane_xy_neg all wall/gran/region ${wall_contact_string} region plane_xy_neg contacts
fix plane_xy_neg all wall/gran/region granular mdr 1000000000 0.3 50000000 0 0.5 0.2 damping mdr 1 tangential linear_history 142857142.857143 0 0.5 region plane_xy_neg contacts
compute plane_xy_neg_force all reduce sum f_plane_xy_neg[4]
variable plane_xy_neg_force equal c_plane_xy_neg_force
compute plane_xz_neg_force all reduce sum f_plane_xz_neg[3]
variable plane_xz_neg_force equal c_plane_xz_neg_force
compute plane_yz_neg_force all reduce sum f_plane_yz_neg[2]
variable plane_yz_neg_force equal c_plane_yz_neg_force
#fix print1 all print 1 "${plane_disp} ${plane_xy_neg_force} ${plane_xz_neg_force} ${plane_yz_neg_force}" file force_disp_triaxial12.csv screen no
######################################## SCREEN OUTPUT ####################################################
compute 1 all erotate/sphere
thermo_style custom dt step atoms ke c_1 vol
thermo 100
thermo_modify lost ignore norm no
##################################### DEFINE WALL MOVEMENT #################################################
variable disp_max equal 0.499
variable ddisp equal 0.00001
variable compression_steps equal round(${disp_max}/${ddisp})
variable compression_steps equal round(0.499/${ddisp})
variable compression_steps equal round(0.499/1e-05)
variable output_rate equal round(${compression_steps}/100)
variable output_rate equal round(49900/100)
##################################### SET UP DUMP OUTPUTS ####################################################
#dump dumpParticles all custom ${output_rate} triaxial_compaction_12.dump id type mass x y z vx vy vz fx fy fz radius
#dump dmp all vtk ${output_rate} post/triaxial12particles_*.vtk id type mass x y z vx vy vz fx fy fz radius
#################################### COMPRESS THE PARTICLES ##################################################
run 0
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Your simulation uses code contributions which should be cited:
- MDR contact model command: (i) https://doi.org/10.1016/j.jmps.2023.105492 || (ii) https://doi.org/10.1016/j.jmps.2023.105493 || (iii) https://doi.org/10.31224/4289
@Article{zunker2024mechanicallyI,
author = {Zunker, William and Kamrin, Ken},
title = {A mechanically-derived contact model for adhesive elastic-perfectly plastic particles,
Part I: Utilizing the method of dimensionality reduction},
journal = {Journal of the Mechanics and Physics of Solids},
year = {2024},
volume = {183},
pages = {105492},
}
@Article{zunker2024mechanicallyII,
author = {Zunker, William and Kamrin, Ken},
title = {A mechanically-derived contact model for adhesive elastic-perfectly plastic particles,
Part II: Contact under high compaction—modeling a bulk elastic response},
journal = {Journal of the Mechanics and Physics of Solids},
year = {2024},
volume = {183},
pages = {105493},
}
@Article{zunker2025experimentally,
author = {Zunker, William and Dunatunga, Sachith and Thakur, Subhash and Tang, Pingjun and Kamrin, Ken},
title = {Experimentally validated DEM for large deformation powder compaction:
mechanically-derived contact model and screening of non-physical contacts},
journal = {Powder Technology},
year = {2025},
pages = {120972},
}
CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE-CITE
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 3.2
ghost atom cutoff = 3.2
binsize = 1.6, bins = 13 13 13
1 neighbor lists, perpetual/occasional/extra = 1 0 0
(1) pair granular, perpetual
attributes: half, newton off, size, history
pair build: half/size/bin/atomonly/newtoff
stencil: full/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 74.54 | 74.54 | 74.54 Mbytes
Dt Step Atoms KinEng c_1 Volume
1e-06 0 12 0 0 8000
Loop time of 8.28e-07 on 1 procs for 0 steps with 12 atoms
0.0% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0 | 0 | 0 | 0.0 | 0.00
Neigh | 0 | 0 | 0 | 0.0 | 0.00
Comm | 0 | 0 | 0 | 0.0 | 0.00
Output | 0 | 0 | 0 | 0.0 | 0.00
Modify | 0 | 0 | 0 | 0.0 | 0.00
Other | | 8.28e-07 | | |100.00
Nlocal: 12 ave 12 max 12 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 66 ave 66 max 66 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 66
Ave neighs/atom = 5.5
Neighbor list builds = 0
Dangerous builds = 0
# print out contact area evolution for particles 1 and 12
compute Ac_1_12 particles_1_12 pair/local p13 cutoff radius
compute Ac_1_12_sum particles_1_12 reduce sum c_Ac_1_12 inputs local
variable Ac_1_12 equal c_Ac_1_12_sum
#fix logArea all print 100 "${plane_disp} ${Ac_1_12}" file pair_1_12_contact_area_triaxial12.csv screen no
variable plane_disp equal ${ddisp}*elapsed
variable plane_disp equal 1e-05*elapsed
variable plane_disp_neg equal -${ddisp}*elapsed
variable plane_disp_neg equal -1e-05*elapsed
run ${compression_steps}
run 49900
Generated 0 of 0 mixed pair_coeff terms from geometric mixing rule
Neighbor list info ...
update: every = 1 steps, delay = 0 steps, check = yes
max neighbors/atom: 2000, page size: 100000
master list distance cutoff = 3.2
ghost atom cutoff = 3.2
binsize = 1.6, bins = 13 13 13
2 neighbor lists, perpetual/occasional/extra = 1 1 0
(1) pair granular, perpetual
attributes: half, newton off, size, history
pair build: half/size/bin/atomonly/newtoff
stencil: full/bin/3d
bin: standard
(2) compute pair/local, occasional
attributes: half, newton off, size
pair build: half/size/bin/atomonly/newtoff
stencil: full/bin/3d
bin: standard
Per MPI rank memory allocation (min/avg/max) = 75.17 | 75.17 | 75.17 Mbytes
Dt Step Atoms KinEng c_1 Volume
1e-06 0 12 0 0 8000
1e-06 100 12 0.063728867 0 8000
1e-06 200 12 0.79328888 0 8000
1e-06 300 12 3.1671095 0 8000
1e-06 400 12 8.7248683 0 8000
1e-06 500 12 20.158012 0 8000
1e-06 600 12 41.157061 0 8000
1e-06 700 12 76.628872 0 8000
1e-06 800 12 132.88829 0 8000
1e-06 900 12 217.80403 0 8000
1e-06 1000 12 340.91325 0 8000
1e-06 1100 12 513.50254 0 8000
1e-06 1200 12 748.65202 0 8000
1e-06 1300 12 1061.2394 0 8000
1e-06 1400 12 1467.9017 0 8000
1e-06 1500 12 1986.9524 0 8000
1e-06 1600 12 2638.2542 0 8000
1e-06 1700 12 3443.0464 0 8000
1e-06 1800 12 4423.728 0 8000
1e-06 1900 12 5603.6004 0 8000
1e-06 2000 12 7006.5697 0 8000
1e-06 2100 12 8656.8153 0 8000
1e-06 2200 12 10575.061 0.00041930161 8000
1e-06 2300 12 12776.34 0.031472922 8000
1e-06 2400 12 15285.834 0.16547279 8000
1e-06 2500 12 18123.472 0.48824818 8000
1e-06 2600 12 21306.73 1.1172148 8000
1e-06 2700 12 24850.635 2.2101203 8000
1e-06 2800 12 28767.448 3.9742876 8000
1e-06 2900 12 33066.341 6.6765245 8000
1e-06 3000 12 37753.104 10.653677 8000
1e-06 3100 12 42829.905 16.323673 8000
1e-06 3200 12 48295.143 24.196804 8000
1e-06 3300 12 54143.784 34.886968 8000
1e-06 3400 12 60367.427 49.122473 8000
1e-06 3500 12 66954.459 67.756017 8000
1e-06 3600 12 73890.367 91.773371 8000
1e-06 3700 12 81158.051 122.30029 8000
1e-06 3800 12 88738.15 160.60714 8000
1e-06 3900 12 96609.374 208.11075 8000
1e-06 4000 12 104748.82 266.37305 8000
1e-06 4100 12 113132.27 337.09603 8000
1e-06 4200 12 121734.46 422.11267 8000
1e-06 4300 12 130529.26 523.37361 8000
1e-06 4400 12 139489.96 642.8869 8000
1e-06 4500 12 148590.48 781.76659 8000
1e-06 4600 12 157805.54 939.73777 8000
1e-06 4700 12 167102.78 1115.3765 8000
1e-06 4800 12 176408.3 1304.8823 8000
1e-06 4900 12 185727.22 1506.1791 8000
1e-06 5000 12 195037.08 1715.5141 8000
1e-06 5100 12 204311.37 1928.3496 8000
1e-06 5200 12 213522.05 2139.6607 8000
1e-06 5300 12 222640.01 2344.2078 8000
1e-06 5400 12 231635.3 2536.8271 8000
1e-06 5500 12 240477.26 2712.7272 8000
1e-06 5600 12 249036.18 2865.4067 8000
1e-06 5700 12 257225.21 2990.2307 8000
1e-06 5800 12 265107.22 3088.4777 8000
1e-06 5900 12 272662.78 3160.202 8000
1e-06 6000 12 279867.43 3206.6334 8000
1e-06 6100 12 286696.38 3230.2607 8000
1e-06 6200 12 293126.06 3234.7442 8000
1e-06 6300 12 299135.09 3224.7366 8000
1e-06 6400 12 304704.84 3205.6378 8000
1e-06 6500 12 309820.07 3183.3082 8000
1e-06 6600 12 314469.34 3163.76 8000
1e-06 6700 12 318645.43 3152.8517 8000
1e-06 6800 12 322345.74 3156.004 8000
1e-06 6900 12 325572.61 3177.9574 8000
1e-06 7000 12 328333.69 3222.5849 8000
1e-06 7100 12 330642.36 3292.7692 8000
1e-06 7200 12 332518.34 3390.3494 8000
1e-06 7300 12 333988.86 3516.133 8000
1e-06 7400 12 335091.17 3669.9688 8000
1e-06 7500 12 335881.45 3850.8676 8000
1e-06 7600 12 336541.99 4057.1561 8000
1e-06 7700 12 337100.25 4286.6487 8000
1e-06 7800 12 337436.07 4536.819 8000
1e-06 7900 12 337576.23 4804.9572 8000
1e-06 8000 12 337553.74 5088.3001 8000
1e-06 8100 12 337412.69 5384.125 8000
1e-06 8200 12 337266.12 5689.8034 8000
1e-06 8300 12 337141.16 6002.815 8000
1e-06 8400 12 336990.23 6320.7444 8000
1e-06 8500 12 336832.35 6645.3584 8000
1e-06 8600 12 336684.67 6980.6347 8000
1e-06 8700 12 336479.86 7317.4769 8000
1e-06 8800 12 336286.29 7653.1265 8000
1e-06 8900 12 336134.3 7982.859 8000
1e-06 9000 12 336043.31 8307.1796 8000
1e-06 9100 12 336035 8626.669 8000
1e-06 9200 12 336134.55 8942.2162 8000
1e-06 9300 12 336370.73 9254.9724 8000
1e-06 9400 12 336775.97 9566.1537 8000
1e-06 9500 12 337386.26 9876.5005 8000
1e-06 9600 12 338238.87 10185.038 8000
1e-06 9700 12 339373.93 10490.42 8000
1e-06 9800 12 340832.84 10792.816 8000
1e-06 9900 12 342649.99 11091.69 8000
1e-06 10000 12 344857.32 11386.232 8000
1e-06 10100 12 347498.52 11676.525 8000
1e-06 10200 12 350625.53 11966.038 8000
1e-06 10300 12 354228.27 12250.382 8000
1e-06 10400 12 358314.64 12529.915 8000
1e-06 10500 12 362887.71 12806.586 8000
1e-06 10600 12 367944.26 13083.935 8000
1e-06 10700 12 373508.47 13375.901 8000
1e-06 10800 12 379544.75 13682.748 8000
1e-06 10900 12 385955.58 13992.431 8000
1e-06 11000 12 392687 14307.793 8000
1e-06 11100 12 399676.01 14631.631 8000
1e-06 11200 12 406851.99 14966.316 8000
1e-06 11300 12 414139.37 15312.299 8000
1e-06 11400 12 421458.35 15668.76 8000
1e-06 11500 12 428725.85 16034.567 8000
1e-06 11600 12 435860.63 16408.01 8000
1e-06 11700 12 442914.03 16784.22 8000
1e-06 11800 12 449956.98 17165.7 8000
1e-06 11900 12 456943.52 17548.894 8000
1e-06 12000 12 463832.6 17927.761 8000
1e-06 12100 12 470563.99 18302.718 8000
1e-06 12200 12 477048.89 18678.218 8000
1e-06 12300 12 483212.97 19059.367 8000
1e-06 12400 12 489085.23 19458.596 8000
1e-06 12500 12 494661.19 19885.306 8000
1e-06 12600 12 499940 20344.66 8000
1e-06 12700 12 504927.83 20838.53 8000
1e-06 12800 12 509641.24 21366.554 8000
1e-06 12900 12 514117.28 21934.019 8000
1e-06 13000 12 518378.2 22538.416 8000
1e-06 13100 12 522458.77 23167.62 8000
1e-06 13200 12 525853.3 23780.032 8000
1e-06 13300 12 528815.22 24345.078 8000
1e-06 13400 12 531513.34 24883.702 8000
1e-06 13500 12 534014.75 25400.482 8000
1e-06 13600 12 536357.43 25891.923 8000
1e-06 13700 12 538572.95 26355.972 8000
1e-06 13800 12 540657.99 26795.836 8000
1e-06 13900 12 542612.1 27223.435 8000
1e-06 14000 12 544466.84 27647.413 8000
1e-06 14100 12 546241.59 28080.229 8000
1e-06 14200 12 547953.9 28538.741 8000
1e-06 14300 12 549620.46 29043.928 8000
1e-06 14400 12 551260.1 29617.65 8000
1e-06 14500 12 552886.91 30280.697 8000
1e-06 14600 12 554517.93 31050.292 8000
1e-06 14700 12 556175.17 31938.659 8000
1e-06 14800 12 557897.11 32951.814 8000
1e-06 14900 12 559696.65 34092.387 8000
1e-06 15000 12 561564.33 35360.561 8000
1e-06 15100 12 563512.54 36749.828 8000
1e-06 15200 12 565557.63 38246.838 8000
1e-06 15300 12 567718.92 39832.256 8000
1e-06 15400 12 569910.41 41477.599 8000
1e-06 15500 12 572038.38 43132.458 8000
1e-06 15600 12 573913.47 44763.446 8000
1e-06 15700 12 575651.62 46334.905 8000
1e-06 15800 12 577306.75 47812.828 8000
1e-06 15900 12 578897.86 49166.374 8000
1e-06 16000 12 580431.98 50370.863 8000
1e-06 16100 12 581917.67 51410.025 8000
1e-06 16200 12 583392.37 52290.363 8000
1e-06 16300 12 584896.54 53001.616 8000
1e-06 16400 12 586445.21 53535.481 8000
1e-06 16500 12 588052.51 53896.917 8000
1e-06 16600 12 589732.17 54102.867 8000
1e-06 16700 12 591496.83 54180.423 8000
1e-06 16800 12 593357.37 54163.728 8000
1e-06 16900 12 595249.77 54088.894 8000
1e-06 17000 12 597130.72 53987.792 8000
1e-06 17100 12 598744.15 53852.584 8000
1e-06 17200 12 600057.69 53662.064 8000
1e-06 17300 12 601263.08 53505.031 8000
1e-06 17400 12 602411.57 53452.104 8000
1e-06 17500 12 603541.22 53553.609 8000
1e-06 17600 12 604067.01 53875.668 8000
1e-06 17700 12 602571.09 54490.575 8000
1e-06 17800 12 600292.75 55434.526 8000
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1e-06 46900 12 277578.87 44223.038 8000
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1e-06 47600 12 282130.22 51780.572 8000
1e-06 47700 12 277128.82 53385.936 8000
1e-06 47800 12 271407.61 54873.773 8000
1e-06 47900 12 265556.17 56217.287 8000
1e-06 48000 12 260082.32 57338.782 8000
1e-06 48100 12 255399.15 58166.789 8000
1e-06 48200 12 251785.89 58653.934 8000
1e-06 48300 12 249277.86 58789.891 8000
1e-06 48400 12 247494.11 58609.44 8000
1e-06 48500 12 245660.12 58192.865 8000
1e-06 48600 12 242968.44 57656.856 8000
1e-06 48700 12 238968.69 57140.878 8000
1e-06 48800 12 233565.17 56788.953 8000
1e-06 48900 12 227411.99 56720.334 8000
1e-06 49000 12 221053.64 57003.014 8000
1e-06 49100 12 215153.96 57629.419 8000
1e-06 49200 12 210402.16 58574.859 8000
1e-06 49300 12 207216.41 59750.238 8000
1e-06 49400 12 205860.43 61020.818 8000
1e-06 49500 12 206382.26 62237.849 8000
1e-06 49600 12 208600.44 63264.958 8000
1e-06 49700 12 212280.2 63999.734 8000
1e-06 49800 12 217167.6 64388.533 8000
1e-06 49900 12 223002.61 64430.977 8000
Loop time of 0.997677 on 1 procs for 49900 steps with 12 atoms
99.2% CPU use with 1 MPI tasks x no OpenMP threads
MPI task timing breakdown:
Section | min time | avg time | max time |%varavg| %total
---------------------------------------------------------------
Pair | 0.24529 | 0.24529 | 0.24529 | 0.0 | 24.59
Neigh | 0 | 0 | 0 | 0.0 | 0.00
Comm | 0.0019929 | 0.0019929 | 0.0019929 | 0.0 | 0.20
Output | 0.0024977 | 0.0024977 | 0.0024977 | 0.0 | 0.25
Modify | 0.74056 | 0.74056 | 0.74056 | 0.0 | 74.23
Other | | 0.007341 | | | 0.74
Nlocal: 12 ave 12 max 12 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Nghost: 0 ave 0 max 0 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Neighs: 66 ave 66 max 66 min
Histogram: 1 0 0 0 0 0 0 0 0 0
Total # of neighbors = 66
Ave neighs/atom = 5.5
Neighbor list builds = 0
Dangerous builds = 0
Total wall time: 0:00:01

52
fortran/lammps.f90
View File

@ -74,7 +74,9 @@ MODULE LIBLAMMPS
LMP_VAR_EQUAL = 0, & ! equal-style variables (and compatible)
LMP_VAR_ATOM = 1, & ! atom-style variables
LMP_VAR_VECTOR = 2, & ! vector variables
LMP_VAR_STRING = 3 ! string variables (everything else)
LMP_VAR_STRING = 3, & ! string variables (everything else)
LMP_NEIGH_HALF = 0, & ! request (default) half neighbor list
LMP_NEIGH_FULL = 1 ! request full neighbor list
! Constants we set once (in the constructor) and never need to check again
INTEGER(c_int), SAVE :: SIZE_TAGINT, SIZE_BIGINT, SIZE_IMAGEINT
@ -195,10 +197,11 @@ MODULE LIBLAMMPS
PROCEDURE, PRIVATE :: lmp_create_atoms_bigbig
GENERIC :: create_atoms => lmp_create_atoms_int, &
lmp_create_atoms_bigbig
PROCEDURE :: find_pair_neighlist => lmp_find_pair_neighlist
PROCEDURE :: find_fix_neighlist => lmp_find_fix_neighlist
PROCEDURE :: find_compute_neighlist => lmp_find_compute_neighlist
PROCEDURE :: neighlist_num_elements => lmp_neighlist_num_elements
PROCEDURE :: find_pair_neighlist => lmp_find_pair_neighlist
PROCEDURE :: find_fix_neighlist => lmp_find_fix_neighlist
PROCEDURE :: find_compute_neighlist => lmp_find_compute_neighlist
PROCEDURE :: request_single_neighlist => lmp_request_single_neighlist
PROCEDURE :: neighlist_num_elements => lmp_neighlist_num_elements
PROCEDURE :: neighlist_element_neighbors => lmp_neighlist_element_neighbors
PROCEDURE :: version => lmp_version
PROCEDURE, NOPASS :: get_os_info => lmp_get_os_info
@ -778,6 +781,15 @@ MODULE LIBLAMMPS
INTEGER(c_int) :: lammps_find_compute_neighlist
END FUNCTION lammps_find_compute_neighlist
FUNCTION lammps_request_single_neighlist(handle, id, flags, cutoff) BIND(C)
IMPORT :: c_int, c_double, c_ptr
IMPLICIT NONE
TYPE(c_ptr), VALUE :: handle, id
INTEGER(c_int), VALUE :: flags
REAL(c_double), VALUE :: cutoff
INTEGER(c_int) :: lammps_request_single_neighlist
END FUNCTION lammps_request_single_neighlist
FUNCTION lammps_neighlist_num_elements(handle, idx) BIND(C)
IMPORT :: c_ptr, c_int
TYPE(c_ptr), VALUE :: handle
@ -2942,6 +2954,36 @@ CONTAINS
CALL lammps_free(Cid)
END FUNCTION lmp_find_compute_neighlist
! equivalent function to lammps_request_single_neighlist
INTEGER(c_int) FUNCTION lmp_request_single_neighlist(self, id, flags, cutoff) RESULT(idx)
CLASS(lammps), INTENT(IN) :: self
CHARACTER(LEN=*), INTENT(IN) :: id
INTEGER(c_int), INTENT(IN), OPTIONAL :: flags
REAL(c_double), INTENT(IN), OPTIONAL :: cutoff
TYPE(c_ptr) :: Cid
INTEGER(c_int) :: Cflags
REAL(c_double) :: Ccutoff
IF (PRESENT(flags)) THEN
Cflags = flags
ELSE
Cflags = LMP_NEIGH_HALF
END IF
IF (PRESENT(cutoff)) THEN
Ccutoff = cutoff
ELSE
Ccutoff = 1.0_c_double
END IF
Cid = f2c_string(id)
idx = lammps_request_single_neighlist(self%handle, Cid, Cflags, Ccutoff)
IF (idx < 0) THEN
CALL lmp_error(self, LMP_ERROR_WARNING + LMP_ERROR_WORLD, &
'neighbor list build failed [Fortran/request_single_neighlist]')
END IF
CALL lammps_free(Cid)
END FUNCTION lmp_request_single_neighlist
INTEGER(c_int) FUNCTION lmp_neighlist_num_elements(self, idx) RESULT(inum)
CLASS(lammps), INTENT(IN) :: self
INTEGER(c_int), INTENT(IN) :: idx

2
lib/colvars/Makefile.common
View File

@ -32,6 +32,7 @@ COLVARS_SRCS = \
colvarbias_histogram_reweight_amd.cpp \
colvarbias_meta.cpp \
colvarbias_restraint.cpp \
colvarbias_opes.cpp \
colvarcomp_alchlambda.cpp \
colvarcomp_angles.cpp \
colvarcomp_apath.cpp \
@ -40,6 +41,7 @@ COLVARS_SRCS = \
colvarcomp_distances.cpp \
colvarcomp_gpath.cpp \
colvarcomp_neuralnetwork.cpp \
colvarcomp_torchann.cpp \
colvarcomp_combination.cpp \
colvarcomp_protein.cpp \
colvarcomp_rotations.cpp \

16
lib/colvars/Makefile.deps
View File

@ -52,6 +52,12 @@ $(COLVARS_OBJ_DIR)colvarbias_restraint.o: colvarbias_restraint.cpp \
colvarproxy_tcl.h colvarproxy_volmaps.h colvarvalue.h \
colvarbias_restraint.h colvarbias.h colvar.h colvarparse.h \
colvarparams.h colvardeps.h
$(COLVARS_OBJ_DIR)colvarbias_opes.o: colvarbias_opes.cpp \
colvarmodule.h colvars_version.h colvarproxy.h colvartypes.h \
../../src/math_eigen_impl.h colvarproxy_io.h colvarproxy_system.h \
colvarproxy_tcl.h colvarproxy_volmaps.h colvarvalue.h \
colvarbias_opes.h colvarbias.h colvar.h colvarparse.h \
colvarparams.h colvardeps.h
$(COLVARS_OBJ_DIR)colvarcomp_alchlambda.o: colvarcomp_alchlambda.cpp \
colvarmodule.h colvars_version.h colvarvalue.h colvartypes.h \
../../src/math_eigen_impl.h colvar.h colvarparse.h colvarparams.h \
@ -101,6 +107,11 @@ $(COLVARS_OBJ_DIR)colvarcomp_neuralnetwork.o: \
colvarproxy.h colvarproxy_io.h colvarproxy_system.h colvarproxy_tcl.h \
colvarproxy_volmaps.h colvar_geometricpath.h \
colvar_neuralnetworkcompute.h
$(COLVARS_OBJ_DIR)colvarcomp_torchann.o: \
colvarcomp_torchann.cpp colvarmodule.h colvars_version.h \
colvarvalue.h colvartypes.h colvarparse.h colvarparams.h colvar.h \
colvardeps.h colvarcomp.h colvarcomp_torchann.h colvaratoms.h colvarproxy.h colvarproxy_io.h \
colvarproxy_system.h colvarproxy_tcl.h
$(COLVARS_OBJ_DIR)colvarcomp_combination.o: colvarcomp_combination.cpp \
colvarcomp.h colvarmodule.h colvars_version.h colvaratoms.h \
colvarproxy.h colvartypes.h ../../src/math_eigen_impl.h colvarproxy_io.h \
@ -127,7 +138,7 @@ $(COLVARS_OBJ_DIR)colvarcomp_volmaps.o: colvarcomp_volmaps.cpp \
colvar_geometricpath.h
$(COLVARS_OBJ_DIR)colvar.o: colvar.cpp colvarmodule.h colvars_version.h \
colvarvalue.h colvartypes.h ../../src/math_eigen_impl.h colvarparse.h \
colvarparams.h colvarcomp.h colvaratoms.h colvarproxy.h colvarproxy_io.h \
colvarparams.h colvarcomp.h colvarcomp_torchann.h colvaratoms.h colvarproxy.h colvarproxy_io.h \
colvarproxy_system.h colvarproxy_tcl.h colvarproxy_volmaps.h \
colvardeps.h colvar.h colvar_geometricpath.h colvarbias.h \
colvars_memstream.h
@ -152,7 +163,8 @@ $(COLVARS_OBJ_DIR)colvarmodule.o: colvarmodule.cpp colvarmodule.h \
colvarbias_histogram_reweight_amd.h colvarbias_meta.h colvarscript.h \
colvarscript_commands.h colvarscript_commands_colvar.h \
colvarscript_commands_bias.h colvaratoms.h colvarcomp.h \
colvar_geometricpath.h colvars_memstream.h colvarmodule_refs.h
colvar_geometricpath.h colvars_memstream.h colvarmodule_refs.h \
colvarbias_opes.h
$(COLVARS_OBJ_DIR)colvarparams.o: colvarparams.cpp colvarmodule.h \
colvars_version.h colvarvalue.h colvartypes.h \
../../src/math_eigen_impl.h colvarparams.h

231
lib/colvars/colvar.cpp
View File

@ -21,6 +21,7 @@
#include "colvarbias.h"
#include "colvars_memstream.h"
#include "colvarcomp_torchann.h"
std::map<std::string, std::function<colvar::cvc *()>> colvar::global_cvc_map =
std::map<std::string, std::function<colvar::cvc *()>>();
@ -95,6 +96,12 @@ int colvar::init(std::string const &conf)
if (error_code != COLVARS_OK) {
return cvm::get_error();
}
#else
if (key_lookup(conf, "customFunction")) {
return cvm::error(
"Error: customFunction keyword is used, but the Lepton library is not available.\n",
COLVARS_NOT_IMPLEMENTED);
}
#endif
// Setup colvar as scripted function of components
@ -175,12 +182,6 @@ int colvar::init(std::string const &conf)
set_enabled(f_cv_scalar, (value().type() == colvarvalue::type_scalar));
// If using scripted biases, any colvar may receive bias forces
// and will need its gradient
if (cvm::scripted_forces()) {
enable(f_cv_gradient);
}
// check for linear combinations
{
bool lin = !(is_enabled(f_cv_scripted) || is_enabled(f_cv_custom_function));
@ -311,9 +312,27 @@ int colvar::init(std::string const &conf)
// Detect if we have a single component that is an alchemical lambda
if (is_enabled(f_cv_single_cvc) && cvcs[0]->function_type() == "alchLambda") {
enable(f_cv_external);
static_cast<colvar::alch_lambda *>(cvcs[0].get())->init_alchemy(time_step_factor);
}
// If using scripted biases, any colvar may receive bias forces
if (cvm::scripted_forces()) {
enable(f_cv_apply_force);
}
error_code |= init_extended_Lagrangian(conf);
// when total atomic forces are obtained from the previous time step,
// we cannot (currently) have colvar values and projected total forces for the same timestep
// (that would require anticipating the total force request by one timestep)
// i.e. the combination of f_cv_total_force_calc and f_cv_multiple_ts requires f_cv_total_force_current_step
// Because f_cv_total_force_current_step is static, we can hard-code this, once other features are set
// that is f_cv_external and f_cv_extended_Lagrangian
if (!is_enabled(f_cv_total_force_current_step)) {
exclude_feature_self(f_cv_multiple_ts, f_cv_total_force_calc);
}
error_code |= init_output_flags(conf);
// Now that the children are defined we can solve dependencies
@ -495,8 +514,6 @@ int colvar::init_grid_parameters(std::string const &conf)
{
int error_code = COLVARS_OK;
colvarmodule *cv = cvm::main();
cvm::real default_width = width;
if (!key_already_set("width")) {
@ -522,34 +539,68 @@ int colvar::init_grid_parameters(std::string const &conf)
if (is_enabled(f_cv_scalar)) {
if (is_enabled(f_cv_single_cvc)) {
// Get the default boundaries from the component
// Record the CVC's intrinsic boundaries, and set them as default values for the user's choice
colvarvalue cvc_lower_boundary, cvc_upper_boundary;
if (is_enabled(f_cv_single_cvc)) { // Get the intrinsic boundaries of the CVC
if (cvcs[0]->is_enabled(f_cvc_lower_boundary)) {
enable(f_cv_lower_boundary);
enable(f_cv_hard_lower_boundary);
lower_boundary =
lower_boundary = cvc_lower_boundary =
*(reinterpret_cast<colvarvalue const *>(cvcs[0]->get_param_ptr("lowerBoundary")));
}
if (cvcs[0]->is_enabled(f_cvc_upper_boundary)) {
enable(f_cv_upper_boundary);
enable(f_cv_hard_upper_boundary);
upper_boundary =
*(reinterpret_cast<colvarvalue const *>(cvcs[0]->get_param_ptr("upperBoundary")));
upper_boundary = cvc_upper_boundary =
*(reinterpret_cast<colvarvalue const *>(cvcs[0]->get_param_ptr("upperBoundary")));
}
}
if (get_keyval(conf, "lowerBoundary", lower_boundary, lower_boundary)) {
enable(f_cv_lower_boundary);
// Because this is the user's choice, we cannot assume it is a true
// physical boundary
disable(f_cv_hard_lower_boundary);
if (is_enabled(f_cv_single_cvc) && is_enabled(f_cv_hard_lower_boundary)) {
if (cvm::sqrt(dist2(lower_boundary, cvc_lower_boundary))/width > colvar_boundaries_tol) {
// The user choice is different from the CVC's default
disable(f_cv_hard_lower_boundary);
}
}
}
if (get_keyval(conf, "upperBoundary", upper_boundary, upper_boundary)) {
enable(f_cv_upper_boundary);
disable(f_cv_hard_upper_boundary);
if (is_enabled(f_cv_single_cvc) && is_enabled(f_cv_hard_upper_boundary)) {
if (cvm::sqrt(dist2(upper_boundary, cvc_upper_boundary))/width > colvar_boundaries_tol) {
disable(f_cv_hard_upper_boundary);
}
}
}
get_keyval_feature(this, conf, "hardLowerBoundary", f_cv_hard_lower_boundary,
is_enabled(f_cv_hard_lower_boundary));
get_keyval_feature(this, conf, "hardUpperBoundary", f_cv_hard_upper_boundary,
is_enabled(f_cv_hard_upper_boundary));
get_keyval(conf, "expandBoundaries", expand_boundaries, expand_boundaries);
error_code |= parse_legacy_wall_params(conf);
error_code |= check_grid_parameters();
}
return error_code;
}
int colvar::parse_legacy_wall_params(std::string const &conf)
{
int error_code = COLVARS_OK;
colvarmodule *cv = cvm::main();
if (is_enabled(f_cv_scalar)) {
// Parse legacy wall options and set up a harmonicWalls bias if needed
cvm::real lower_wall_k = 0.0, upper_wall_k = 0.0;
cvm::real lower_wall = 0.0, upper_wall = 0.0;
@ -603,13 +654,14 @@ harmonicWalls {\n\
}
}
get_keyval_feature(this, conf, "hardLowerBoundary", f_cv_hard_lower_boundary,
is_enabled(f_cv_hard_lower_boundary));
return error_code;
}
get_keyval_feature(this, conf, "hardUpperBoundary", f_cv_hard_upper_boundary,
is_enabled(f_cv_hard_upper_boundary));
// consistency checks for boundaries and walls
int colvar::check_grid_parameters()
{
int error_code = COLVARS_OK;
if (is_enabled(f_cv_lower_boundary) && is_enabled(f_cv_upper_boundary)) {
if (lower_boundary >= upper_boundary) {
error_code |= cvm::error("Error: the upper boundary, "+
@ -620,7 +672,6 @@ harmonicWalls {\n\
}
}
get_keyval(conf, "expandBoundaries", expand_boundaries, expand_boundaries);
if (expand_boundaries && periodic_boundaries()) {
error_code |= cvm::error("Error: trying to expand boundaries that already "
"cover a whole period of a periodic colvar.\n",
@ -654,14 +705,15 @@ int colvar::init_extended_Lagrangian(std::string const &conf)
x_ext.type(colvarvalue::type_notset);
v_ext.type(value());
fr.type(value());
const bool temp_provided = get_keyval(conf, "extendedTemp", temp,
proxy->target_temperature());
const bool temp_provided = get_keyval(conf, "extendedTemp", temp, proxy->target_temperature());
if (is_enabled(f_cv_external)) {
// In the case of an "external" coordinate, there is no coupling potential:
// In the case of a driven external parameter in the back-end, there is no coupling potential:
// only the fictitious mass is meaningful
get_keyval(conf, "extendedMass", ext_mass);
// Ensure that the computed restraint energy term is zero
ext_force_k = 0.0;
// Then we need forces from the back-end
enable(f_cv_total_force_calc);
} else {
// Standard case of coupling to a geometric colvar
if (temp <= 0.0) { // Then a finite temperature is required
@ -779,6 +831,7 @@ int colvar::init_components_type(const std::string& conf, const char* def_config
&def_conf,
&pos) ) {
cvm::increase_depth();
cvm::log("Initializing "
"a new \""+std::string(def_config_key)+"\" component"+
(cvm::debug() ? ", with configuration:\n"+def_conf
@ -791,7 +844,6 @@ int colvar::init_components_type(const std::string& conf, const char* def_config
}
cvcs.push_back(std::shared_ptr<colvar::cvc>(cvcp));
cvm::increase_depth();
int error_code_this = cvcp->init(def_conf);
if (error_code_this == COLVARS_OK) {
// Checking for invalid keywords only if the parsing was successful, otherwise any
@ -851,12 +903,8 @@ void colvar::define_component_types()
add_component_type<dipole_angle>("dipole angle", "dipoleAngle");
add_component_type<dihedral>("dihedral", "dihedral");
add_component_type<h_bond>("hydrogen bond", "hBond");
if (proxy->check_atom_name_selections_available() == COLVARS_OK) {
add_component_type<alpha_angles>("alpha helix", "alpha");
add_component_type<dihedPC>("dihedral principal component", "dihedralPC");
}
add_component_type<alpha_angles>("alpha helix", "alpha");
add_component_type<dihedPC>("dihedral principal component", "dihedralPC");
add_component_type<orientation>("orientation", "orientation");
add_component_type<orientation_angle>("orientation angle", "orientationAngle");
add_component_type<orientation_proj>("orientation projection", "orientationProj");
@ -888,6 +936,8 @@ void colvar::define_component_types()
add_component_type<neuralNetwork>("neural network CV for other CVs", "neuralNetwork");
add_component_type<torchANN>("CV defined by PyTorch artifical neural network models", "torchANN");
if (proxy->check_volmaps_available() == COLVARS_OK) {
add_component_type<map_total>("total value of atomic map", "mapTotal");
}
@ -1098,6 +1148,9 @@ int colvar::init_dependencies() {
init_feature(f_cv_gradient, "gradient", f_type_dynamic);
require_feature_children(f_cv_gradient, f_cvc_gradient);
init_feature(f_cv_apply_force, "apply_force", f_type_dynamic);
require_feature_alt(f_cv_apply_force, f_cv_gradient, f_cv_external);
init_feature(f_cv_collect_gradient, "collect_gradient", f_type_dynamic);
require_feature_self(f_cv_collect_gradient, f_cv_gradient);
require_feature_self(f_cv_collect_gradient, f_cv_scalar);
@ -1116,6 +1169,10 @@ int colvar::init_dependencies() {
init_feature(f_cv_total_force, "total_force", f_type_dynamic);
require_feature_alt(f_cv_total_force, f_cv_extended_Lagrangian, f_cv_total_force_calc);
// If this is active, the total force reported to biases (ABF / TI) is from the current step
// therefore it does not include Colvars biases -> it is a "system force"
init_feature(f_cv_total_force_current_step, "total_force_current_step", f_type_dynamic);
// Deps for explicit total force calculation
init_feature(f_cv_total_force_calc, "total_force_calculation", f_type_dynamic);
require_feature_self(f_cv_total_force_calc, f_cv_scalar);
@ -1134,13 +1191,15 @@ int colvar::init_dependencies() {
init_feature(f_cv_extended_Lagrangian, "extended_Lagrangian", f_type_user);
require_feature_self(f_cv_extended_Lagrangian, f_cv_scalar);
require_feature_self(f_cv_extended_Lagrangian, f_cv_gradient);
require_feature_self(f_cv_extended_Lagrangian, f_cv_apply_force);
init_feature(f_cv_Langevin, "Langevin_dynamics", f_type_user);
require_feature_self(f_cv_Langevin, f_cv_extended_Lagrangian);
init_feature(f_cv_external, "external", f_type_user);
init_feature(f_cv_external, "external_parameter", f_type_static);
require_feature_self(f_cv_external, f_cv_single_cvc);
// External parameters always report the total force for current step
require_feature_self(f_cv_external, f_cv_total_force_current_step);
init_feature(f_cv_single_cvc, "single_component", f_type_static);
@ -1201,10 +1260,7 @@ int colvar::init_dependencies() {
init_feature(f_cv_linear, "linear", f_type_static);
init_feature(f_cv_homogeneous, "homogeneous", f_type_static);
// because total forces are obtained from the previous time step,
// we cannot (currently) have colvar values and total forces for the same timestep
init_feature(f_cv_multiple_ts, "multiple_timestep", f_type_static);
exclude_feature_self(f_cv_multiple_ts, f_cv_total_force_calc);
// check that everything is initialized
for (i = 0; i < colvardeps::f_cv_ntot; i++) {
@ -1225,6 +1281,10 @@ int colvar::init_dependencies() {
feature_states[f_cv_fdiff_velocity].available =
cvm::main()->proxy->simulation_running();
// Some back-ends report current total forces for all colvars
if (cvm::main()->proxy->total_forces_same_step())
enable(f_cv_total_force_current_step);
return COLVARS_OK;
}
@ -1351,7 +1411,6 @@ int colvar::calc_cvcs(int first_cvc, size_t num_cvcs)
cvm::log("Calculating colvar \""+this->name+"\", components "+
cvm::to_str(first_cvc)+" through "+cvm::to_str(first_cvc+num_cvcs)+".\n");
colvarproxy *proxy = cvm::main()->proxy;
int error_code = COLVARS_OK;
error_code |= check_cvc_range(first_cvc, num_cvcs);
@ -1359,7 +1418,7 @@ int colvar::calc_cvcs(int first_cvc, size_t num_cvcs)
return error_code;
}
if ((cvm::step_relative() > 0) && (!proxy->total_forces_same_step())){
if ((cvm::step_relative() > 0) && (!is_enabled(f_cv_total_force_current_step))){
// Use Jacobian derivative from previous timestep
error_code |= calc_cvc_total_force(first_cvc, num_cvcs);
}
@ -1367,7 +1426,7 @@ int colvar::calc_cvcs(int first_cvc, size_t num_cvcs)
error_code |= calc_cvc_values(first_cvc, num_cvcs);
error_code |= calc_cvc_gradients(first_cvc, num_cvcs);
error_code |= calc_cvc_Jacobians(first_cvc, num_cvcs);
if (proxy->total_forces_same_step()){
if (is_enabled(f_cv_total_force_current_step)){
// Use Jacobian derivative from this timestep
error_code |= calc_cvc_total_force(first_cvc, num_cvcs);
}
@ -1384,10 +1443,9 @@ int colvar::collect_cvc_data()
if (cvm::debug())
cvm::log("Calculating colvar \""+this->name+"\"'s properties.\n");
colvarproxy *proxy = cvm::main()->proxy;
int error_code = COLVARS_OK;
if ((cvm::step_relative() > 0) && (!proxy->total_forces_same_step())){
if ((cvm::step_relative() > 0) && (!is_enabled(f_cv_total_force_current_step))){
// Total force depends on Jacobian derivative from previous timestep
// collect_cvc_total_forces() uses the previous value of jd
error_code |= collect_cvc_total_forces();
@ -1395,7 +1453,7 @@ int colvar::collect_cvc_data()
error_code |= collect_cvc_values();
error_code |= collect_cvc_gradients();
error_code |= collect_cvc_Jacobians();
if (proxy->total_forces_same_step()){
if (is_enabled(f_cv_total_force_current_step)){
// Use Jacobian derivative from this timestep
error_code |= collect_cvc_total_forces();
}
@ -1609,22 +1667,20 @@ int colvar::collect_cvc_total_forces()
if (is_enabled(f_cv_total_force_calc)) {
ft.reset();
if (cvm::step_relative() > 0) {
// get from the cvcs the total forces from the PREVIOUS step
for (size_t i = 0; i < cvcs.size(); i++) {
if (!cvcs[i]->is_enabled()) continue;
if (cvm::debug())
cvm::log("Colvar component no. "+cvm::to_str(i+1)+
" within colvar \""+this->name+"\" has total force "+
cvm::to_str((cvcs[i])->total_force(),
cvm::cv_width, cvm::cv_prec)+".\n");
// linear combination is assumed
ft += (cvcs[i])->total_force() * (cvcs[i])->sup_coeff / active_cvc_square_norm;
}
for (size_t i = 0; i < cvcs.size(); i++) {
if (!cvcs[i]->is_enabled()) continue;
if (cvm::debug())
cvm::log("Colvar component no. "+cvm::to_str(i+1)+
" within colvar \""+this->name+"\" has total force "+
cvm::to_str((cvcs[i])->total_force(),
cvm::cv_width, cvm::cv_prec)+".\n");
// linear combination is assumed
ft += (cvcs[i])->total_force() * (cvcs[i])->sup_coeff / active_cvc_square_norm;
}
if (!(is_enabled(f_cv_hide_Jacobian) && is_enabled(f_cv_subtract_applied_force))) {
// add the Jacobian force to the total force, and don't apply any silent
// This is by far the most common case
// Add the Jacobian force to the total force, and don't apply any silent
// correction internally: biases such as colvarbias_abf will handle it
// If f_cv_hide_Jacobian is enabled, a force of -fj is present in ft due to the
// Jacobian-compensating force
@ -1632,6 +1688,10 @@ int colvar::collect_cvc_total_forces()
}
}
if (is_enabled(f_cv_total_force_current_step)) {
// Report total force value without waiting for calc_colvar_properties()
ft_reported = ft;
}
return COLVARS_OK;
}
@ -1733,12 +1793,15 @@ int colvar::calc_colvar_properties()
// But we report values at the beginning of the timestep (value at t=0 on the first timestep)
x_reported = x_ext;
v_reported = v_ext;
// the "total force" with the extended Lagrangian is
// calculated in update_forces_energy() below
// the "total force" for the extended Lagrangian is calculated in update_forces_energy() below
// A future improvement could compute a "system force" here, borrowing a part of update_extended_Lagrangian()
// this would change the behavior of eABF with respect to other biases
// by enabling f_cv_total_force_current_step, and reducing the total force to a system force
// giving the behavior of f_cv_subtract_applied_force - this is correct for WTM-eABF etc.
} else {
if (is_enabled(f_cv_subtract_applied_force)) {
if (is_enabled(f_cv_subtract_applied_force) && !cvm::proxy->total_forces_same_step()) {
// correct the total force only if it has been measured
// TODO add a specific test instead of relying on sq norm
if (ft.norm2() > 0.0) {
@ -1825,7 +1888,8 @@ void colvar::update_extended_Lagrangian()
// Integrate with slow timestep (if time_step_factor != 1)
cvm::real dt = cvm::dt() * cvm::real(time_step_factor);
colvarvalue f_ext(fr.type()); // force acting on the extended variable
// Force acting on the extended variable
colvarvalue f_ext(fr.type());
f_ext.reset();
if (is_enabled(f_cv_external)) {
@ -1834,13 +1898,13 @@ void colvar::update_extended_Lagrangian()
f += fb_actual;
}
// fr: bias force on extended variable (without harmonic spring), for output in trajectory
fr = f;
// External force has been scaled for an inner-timestep impulse (for the back-end integrator)
// here we scale it back because this integrator uses only the outer (long) timestep
f_ext = f / cvm::real(time_step_factor);
// fr: bias force on extended variable (without harmonic spring), for output in trajectory
fr = f_ext;
colvarvalue f_system(fr.type()); // force exterted by the system on the extended DOF
if (is_enabled(f_cv_external)) {
@ -1863,14 +1927,18 @@ void colvar::update_extended_Lagrangian()
}
f_ext += f_system;
if (is_enabled(f_cv_subtract_applied_force)) {
// Report a "system" force without the biases on this colvar
// that is, just the spring force (or alchemical force)
ft_reported = f_system;
} else {
// The total force acting on the extended variable is f_ext
// This will be used in the next timestep
ft_reported = f_ext;
if ( ! is_enabled(f_cv_total_force_current_step)) {
if (is_enabled(f_cv_subtract_applied_force)) {
// Report a "system" force without the biases on this colvar
// that is, just the spring force (or alchemical force)
ft_reported = f_system;
} else {
// The total force acting on the extended variable is f_ext
// This will be used in the next timestep
ft_reported = f_ext;
}
// Since biases have already been updated, this ft_reported will only be
// communicated to biases at the next timestep
}
// backup in case we need to revert this integration timestep
@ -2184,12 +2252,10 @@ int colvar::set_cvc_param(std::string const &param_name, void const *new_value)
bool colvar::periodic_boundaries(colvarvalue const &lb, colvarvalue const &ub) const
{
if (period > 0.0) {
if ( ((cvm::sqrt(this->dist2(lb, ub))) / this->width)
< 1.0E-10 ) {
if (((cvm::sqrt(this->dist2(lb, ub))) / this->width) < colvar_boundaries_tol) {
return true;
}
}
return false;
}
@ -2347,6 +2413,11 @@ int colvar::set_state_params(std::string const &conf)
cvm::to_str(x)+"\n");
x_restart = x;
after_restart = true;
// Externally driven cv (e.g. alchemical lambda) is imposed by restart value
if (is_enabled(f_cv_external) && is_enabled(f_cv_extended_Lagrangian)) {
// Request immediate sync of driven parameter to back-end code
cvcs[0]->set_value(x, true);
}
}
if (is_enabled(f_cv_extended_Lagrangian)) {
@ -2489,8 +2560,14 @@ std::string const colvar::get_state_params() const
os << " name " << name << "\n"
<< " x "
<< std::setprecision(cvm::cv_prec)
<< std::setw(cvm::cv_width)
<< x << "\n";
<< std::setw(cvm::cv_width);
if (is_enabled(f_cv_external) && is_enabled(f_cv_extended_Lagrangian)) {
// For an external colvar, x is one timestep in the future after integration
// write x at beginning of timestep
os << x_reported << "\n";
} else {
os << x << "\n";
}
if (is_enabled(f_cv_output_velocity)) {
os << " v "

15
lib/colvars/colvar.h
View File

@ -263,6 +263,12 @@ public:
/// Init defaults for grid options
int init_grid_parameters(std::string const &conf);
/// Consistency check for the grid paramaters
int check_grid_parameters();
/// Read legacy wall keyword (these are biases now)
int parse_legacy_wall_params(std::string const &conf);
/// Init extended Lagrangian parameters
int init_extended_Lagrangian(std::string const &conf);
@ -633,6 +639,7 @@ public:
class euler_psi;
class euler_theta;
class neuralNetwork;
class torchANN;
class customColvar;
// non-scalar components
@ -753,7 +760,7 @@ inline colvarvalue const & colvar::total_force() const
inline void colvar::add_bias_force(colvarvalue const &force)
{
check_enabled(f_cv_gradient,
check_enabled(f_cv_apply_force,
std::string("applying a force to the variable \""+name+"\""));
if (cvm::debug()) {
cvm::log("Adding biasing force "+cvm::to_str(force)+" to colvar \""+name+"\".\n");
@ -778,4 +785,10 @@ inline void colvar::reset_bias_force() {
fb_actual.reset();
}
namespace {
// Tolerance parameter to decide when two boundaries coincide
constexpr cvm::real colvar_boundaries_tol = 1.0e-10;
}
#endif

102
lib/colvars/colvar_rotation_derivative.h
View File

@ -5,11 +5,21 @@
#include <type_traits>
#include <cstring>
#ifndef _noalias
#if defined(__INTEL_COMPILER) || (defined(__PGI) && !defined(__NVCOMPILER))
#define _noalias restrict
#elif defined(__GNUC__) || defined(__INTEL_LLVM_COMPILER) || defined(__NVCOMPILER)
#define _noalias __restrict
#else
#define _noalias
#endif
#endif
/// \brief Helper function for loading the ia-th atom in the vector pos to x, y and z (C++11 SFINAE is used)
template <typename T, typename std::enable_if<std::is_same<T, cvm::atom_pos>::value, bool>::type = true>
inline void read_atom_coord(
size_t ia, const std::vector<T>& pos,
cvm::real* x, cvm::real* y, cvm::real* z) {
cvm::real* _noalias x, cvm::real* _noalias y, cvm::real* _noalias z) {
*x = pos[ia].x;
*y = pos[ia].y;
*z = pos[ia].z;
@ -18,7 +28,7 @@ inline void read_atom_coord(
template <typename T, typename std::enable_if<std::is_same<T, cvm::atom>::value, bool>::type = true>
inline void read_atom_coord(
size_t ia, const std::vector<T>& pos,
cvm::real* x, cvm::real* y, cvm::real* z) {
cvm::real* _noalias x, cvm::real* _noalias y, cvm::real* _noalias z) {
*x = pos[ia].pos.x;
*y = pos[ia].pos.y;
*z = pos[ia].pos.z;
@ -26,9 +36,9 @@ inline void read_atom_coord(
/// \brief Helper enum class for specifying options in rotation_derivative::prepare_derivative
enum class rotation_derivative_dldq {
/// Require the derivative of the leading eigenvalue with respect to the atom coordinats
/// Require the derivative of the leading eigenvalue with respect to the atom coordinates
use_dl = 1 << 0,
/// Require the derivative of the leading eigenvector with respect to the atom coordinats
/// Require the derivative of the leading eigenvector with respect to the atom coordinates
use_dq = 1 << 1
};
@ -327,12 +337,13 @@ struct rotation_derivative {
* @param[out] dq0_out The output of derivative of Q
* @param[out] ds_out The output of derivative of overlap matrix S
*/
template <bool use_dl, bool use_dq, bool use_ds>
void calc_derivative_impl(
const cvm::rvector (&ds)[4][4],
cvm::rvector* const dl0_out,
cvm::vector1d<cvm::rvector>* const dq0_out,
cvm::matrix2d<cvm::rvector>* const ds_out) const {
if (ds_out != nullptr) {
cvm::rvector* _noalias const dl0_out,
cvm::vector1d<cvm::rvector>* _noalias const dq0_out,
cvm::matrix2d<cvm::rvector>* _noalias const ds_out) const {
if (use_ds) {
// this code path is for debug_gradients, so not necessary to unroll the loop
*ds_out = cvm::matrix2d<cvm::rvector>(4, 4);
for (int i = 0; i < 4; ++i) {
@ -341,7 +352,7 @@ struct rotation_derivative {
}
}
}
if (dl0_out != nullptr) {
if (use_dl) {
/* manually loop unrolling of the following loop:
dl0_1.reset();
for (size_t i = 0; i < 4; i++) {
@ -367,7 +378,7 @@ struct rotation_derivative {
tmp_Q0Q0[3][2] * ds[3][2] +
tmp_Q0Q0[3][3] * ds[3][3];
}
if (dq0_out != nullptr) {
if (use_dq) {
// we can skip this check if a fixed-size array is used
if (dq0_out->size() != 4) dq0_out->resize(4);
/* manually loop unrolling of the following loop:
@ -462,32 +473,21 @@ struct rotation_derivative {
* @param[out] ds_1_out The output of derivative of overlap matrix S with
* respect to ia-th atom of group 1
*/
template <bool use_dl, bool use_dq, bool use_ds>
void calc_derivative_wrt_group1(
size_t ia, cvm::rvector* const dl0_1_out = nullptr,
cvm::vector1d<cvm::rvector>* const dq0_1_out = nullptr,
cvm::matrix2d<cvm::rvector>* const ds_1_out = nullptr) const {
if (dl0_1_out == nullptr && dq0_1_out == nullptr) return;
size_t ia, cvm::rvector* _noalias const dl0_1_out = nullptr,
cvm::vector1d<cvm::rvector>* _noalias const dq0_1_out = nullptr,
cvm::matrix2d<cvm::rvector>* _noalias const ds_1_out = nullptr) const {
// if (dl0_1_out == nullptr && dq0_1_out == nullptr) return;
cvm::real a2x, a2y, a2z;
// we can get rid of the helper function read_atom_coord if C++17 (constexpr) is available
read_atom_coord(ia, m_pos2, &a2x, &a2y, &a2z);
cvm::rvector ds_1[4][4];
ds_1[0][0].set( a2x, a2y, a2z);
ds_1[1][0].set( 0.0, a2z, -a2y);
ds_1[0][1] = ds_1[1][0];
ds_1[2][0].set(-a2z, 0.0, a2x);
ds_1[0][2] = ds_1[2][0];
ds_1[3][0].set( a2y, -a2x, 0.0);
ds_1[0][3] = ds_1[3][0];
ds_1[1][1].set( a2x, -a2y, -a2z);
ds_1[2][1].set( a2y, a2x, 0.0);
ds_1[1][2] = ds_1[2][1];
ds_1[3][1].set( a2z, 0.0, a2x);
ds_1[1][3] = ds_1[3][1];
ds_1[2][2].set(-a2x, a2y, -a2z);
ds_1[3][2].set( 0.0, a2z, a2y);
ds_1[2][3] = ds_1[3][2];
ds_1[3][3].set(-a2x, -a2y, a2z);
calc_derivative_impl(ds_1, dl0_1_out, dq0_1_out, ds_1_out);
const cvm::rvector ds_1[4][4] = {
{{ a2x, a2y, a2z}, { 0.0, a2z, -a2y}, {-a2z, 0.0, a2x}, { a2y, -a2x, 0.0}},
{{ 0.0, a2z, -a2y}, { a2x, -a2y, -a2z}, { a2y, a2x, 0.0}, { a2z, 0.0, a2x}},
{{-a2z, 0.0, a2x}, { a2y, a2x, 0.0}, {-a2x, a2y, -a2z}, { 0.0, a2z, a2y}},
{{ a2y, -a2x, 0.0}, { a2z, 0.0, a2x}, { 0.0, a2z, a2y}, {-a2x, -a2y, a2z}}};
calc_derivative_impl<use_dl, use_dq, use_ds>(ds_1, dl0_1_out, dq0_1_out, ds_1_out);
}
/*! @brief Calculate the derivatives of S, the leading eigenvalue L and
* the leading eigenvector Q with respect to `m_pos2`
@ -499,32 +499,21 @@ struct rotation_derivative {
* @param[out] ds_2_out The output of derivative of overlap matrix S with
* respect to ia-th atom of group 2
*/
template <bool use_dl, bool use_dq, bool use_ds>
void calc_derivative_wrt_group2(
size_t ia, cvm::rvector* const dl0_2_out = nullptr,
cvm::vector1d<cvm::rvector>* const dq0_2_out = nullptr,
cvm::matrix2d<cvm::rvector>* const ds_2_out = nullptr) const {
if (dl0_2_out == nullptr && dq0_2_out == nullptr) return;
size_t ia, cvm::rvector* _noalias const dl0_2_out = nullptr,
cvm::vector1d<cvm::rvector>* _noalias const dq0_2_out = nullptr,
cvm::matrix2d<cvm::rvector>* _noalias const ds_2_out = nullptr) const {
// if (dl0_2_out == nullptr && dq0_2_out == nullptr) return;
cvm::real a1x, a1y, a1z;
// we can get rid of the helper function read_atom_coord if C++17 (constexpr) is available
read_atom_coord(ia, m_pos1, &a1x, &a1y, &a1z);
cvm::rvector ds_2[4][4];
ds_2[0][0].set( a1x, a1y, a1z);
ds_2[1][0].set( 0.0, -a1z, a1y);
ds_2[0][1] = ds_2[1][0];
ds_2[2][0].set( a1z, 0.0, -a1x);
ds_2[0][2] = ds_2[2][0];
ds_2[3][0].set(-a1y, a1x, 0.0);
ds_2[0][3] = ds_2[3][0];
ds_2[1][1].set( a1x, -a1y, -a1z);
ds_2[2][1].set( a1y, a1x, 0.0);
ds_2[1][2] = ds_2[2][1];
ds_2[3][1].set( a1z, 0.0, a1x);
ds_2[1][3] = ds_2[3][1];
ds_2[2][2].set(-a1x, a1y, -a1z);
ds_2[3][2].set( 0.0, a1z, a1y);
ds_2[2][3] = ds_2[3][2];
ds_2[3][3].set(-a1x, -a1y, a1z);
calc_derivative_impl(ds_2, dl0_2_out, dq0_2_out, ds_2_out);
const cvm::rvector ds_2[4][4] = {
{{ a1x, a1y, a1z}, { 0.0, -a1z, a1y}, { a1z, 0.0, -a1x}, {-a1y, a1x, 0.0}},
{{ 0.0, -a1z, a1y}, { a1x, -a1y, -a1z}, { a1y, a1x, 0.0}, { a1z, 0.0, a1x}},
{{ a1z, 0.0, -a1x}, { a1y, a1x, 0.0}, {-a1x, a1y, -a1z}, { 0.0, a1z, a1y}},
{{-a1y, a1x, 0.0}, { a1z, 0.0, a1x}, { 0.0, a1z, a1y}, {-a1x, -a1y, a1z}}};
calc_derivative_impl<use_dl, use_dq, use_ds>(ds_2, dl0_2_out, dq0_2_out, ds_2_out);
}
};
@ -585,10 +574,7 @@ void debug_gradients(
cvm::real S_new_eigval[4];
cvm::real S_new_eigvec[4][4];
for (size_t ia = 0; ia < pos2.size(); ++ia) {
// cvm::real const &a1x = pos1[ia].x;
// cvm::real const &a1y = pos1[ia].y;
// cvm::real const &a1z = pos1[ia].z;
deriv.calc_derivative_wrt_group2(ia, &dl0_2, &dq0_2, &ds_2);
deriv.template calc_derivative_wrt_group2<true, true, true>(ia, &dl0_2, &dq0_2, &ds_2);
// make an infitesimal move along each cartesian coordinate of
// this atom, and solve again the eigenvector problem
for (size_t comp = 0; comp < 3; comp++) {

144
lib/colvars/colvaratoms.cpp
View File

@ -673,7 +673,7 @@ int cvm::atom_group::add_atom_numbers(std::string const &numbers_conf)
}
int cvm::atom_group::add_index_group(std::string const &index_group_name)
int cvm::atom_group::add_index_group(std::string const &index_group_name, bool silent)
{
std::vector<std::string> const &index_group_names =
cvm::main()->index_group_names;
@ -687,7 +687,10 @@ int cvm::atom_group::add_index_group(std::string const &index_group_name)
}
if (i_group >= index_group_names.size()) {
return cvm::error("Error: could not find index group "+
if (silent)
return COLVARS_INPUT_ERROR;
else
return cvm::error("Error: could not find index group "+
index_group_name+" among those already provided.\n",
COLVARS_INPUT_ERROR);
}
@ -1055,6 +1058,14 @@ void cvm::atom_group::calc_apply_roto_translation()
}
}
if (is_enabled(f_ag_fit_gradients) && !b_dummy) {
// Save the unrotated frame for fit gradients
pos_unrotated.resize(size());
for (size_t i = 0; i < size(); ++i) {
pos_unrotated[i] = atoms[i].pos;
}
}
if (is_enabled(f_ag_rotate)) {
// rotate the group (around the center of geometry if f_ag_center is
// enabled, around the origin otherwise)
@ -1217,23 +1228,30 @@ void cvm::atom_group::calc_fit_gradients()
if (cvm::debug())
cvm::log("Calculating fit gradients.\n");
cvm::atom_group *group_for_fit = fitting_group ? fitting_group : this;
auto accessor_main = [this](size_t i){return atoms[i].grad;};
auto accessor_fitting = [&group_for_fit](size_t j, const cvm::rvector& grad){group_for_fit->fit_gradients[j] = grad;};
if (is_enabled(f_ag_center) && is_enabled(f_ag_rotate))
calc_fit_gradients_impl<true, true>();
calc_fit_forces_impl<true, true>(accessor_main, accessor_fitting);
if (is_enabled(f_ag_center) && !is_enabled(f_ag_rotate))
calc_fit_gradients_impl<true, false>();
calc_fit_forces_impl<true, false>(accessor_main, accessor_fitting);
if (!is_enabled(f_ag_center) && is_enabled(f_ag_rotate))
calc_fit_gradients_impl<false, true>();
calc_fit_forces_impl<false, true>(accessor_main, accessor_fitting);
if (!is_enabled(f_ag_center) && !is_enabled(f_ag_rotate))
calc_fit_gradients_impl<false, false>();
calc_fit_forces_impl<false, false>(accessor_main, accessor_fitting);
if (cvm::debug())
cvm::log("Done calculating fit gradients.\n");
}
template <bool B_ag_center, bool B_ag_rotate>
void cvm::atom_group::calc_fit_gradients_impl() {
cvm::atom_group *group_for_fit = fitting_group ? fitting_group : this;
template <bool B_ag_center, bool B_ag_rotate,
typename main_force_accessor_T, typename fitting_force_accessor_T>
void cvm::atom_group::calc_fit_forces_impl(
main_force_accessor_T accessor_main,
fitting_force_accessor_T accessor_fitting) const {
const cvm::atom_group *group_for_fit = fitting_group ? fitting_group : this;
// the center of geometry contribution to the gradients
cvm::rvector atom_grad;
// the rotation matrix contribution to the gradients
@ -1243,17 +1261,13 @@ void cvm::atom_group::calc_fit_gradients_impl() {
cvm::vector1d<cvm::rvector> dq0_1(4);
// loop 1: iterate over the current atom group
for (size_t i = 0; i < size(); i++) {
cvm::atom_pos pos_orig;
if (B_ag_center) {
atom_grad += atoms[i].grad;
if (B_ag_rotate) pos_orig = rot_inv * (atoms[i].pos - ref_pos_cog);
} else {
if (B_ag_rotate) pos_orig = atoms[i].pos;
atom_grad += accessor_main(i);
}
if (B_ag_rotate) {
// calculate \partial(R(q) \vec{x}_i)/\partial q) \cdot \partial\xi/\partial\vec{x}_i
cvm::quaternion const dxdq =
rot.q.position_derivative_inner(pos_orig, atoms[i].grad);
rot.q.position_derivative_inner(pos_unrotated[i], accessor_main(i));
sum_dxdq[0] += dxdq[0];
sum_dxdq[1] += dxdq[1];
sum_dxdq[2] += dxdq[2];
@ -1261,26 +1275,45 @@ void cvm::atom_group::calc_fit_gradients_impl() {
}
}
if (B_ag_center) {
if (B_ag_rotate) atom_grad = rot.inverse().matrix() * atom_grad;
if (B_ag_rotate) atom_grad = rot_inv * atom_grad;
atom_grad *= (-1.0)/(cvm::real(group_for_fit->size()));
}
// loop 2: iterate over the fitting group
if (B_ag_rotate) rot_deriv->prepare_derivative(rotation_derivative_dldq::use_dq);
for (size_t j = 0; j < group_for_fit->size(); j++) {
cvm::rvector fitting_force_grad{0, 0, 0};
if (B_ag_center) {
group_for_fit->fit_gradients[j] = atom_grad;
fitting_force_grad += atom_grad;
}
if (B_ag_rotate) {
rot_deriv->calc_derivative_wrt_group1(j, nullptr, &dq0_1);
rot_deriv->calc_derivative_wrt_group1<false, true, false>(j, nullptr, &dq0_1);
// multiply by {\partial q}/\partial\vec{x}_j and add it to the fit gradients
group_for_fit->fit_gradients[j] += sum_dxdq[0] * dq0_1[0] +
sum_dxdq[1] * dq0_1[1] +
sum_dxdq[2] * dq0_1[2] +
sum_dxdq[3] * dq0_1[3];
fitting_force_grad += sum_dxdq[0] * dq0_1[0] +
sum_dxdq[1] * dq0_1[1] +
sum_dxdq[2] * dq0_1[2] +
sum_dxdq[3] * dq0_1[3];
}
if (cvm::debug()) {
cvm::log(cvm::to_str(fitting_force_grad));
}
accessor_fitting(j, fitting_force_grad);
}
}
template <typename main_force_accessor_T, typename fitting_force_accessor_T>
void cvm::atom_group::calc_fit_forces(
main_force_accessor_T accessor_main,
fitting_force_accessor_T accessor_fitting) const {
if (is_enabled(f_ag_center) && is_enabled(f_ag_rotate))
calc_fit_forces_impl<true, true, main_force_accessor_T, fitting_force_accessor_T>(accessor_main, accessor_fitting);
if (is_enabled(f_ag_center) && !is_enabled(f_ag_rotate))
calc_fit_forces_impl<true, false, main_force_accessor_T, fitting_force_accessor_T>(accessor_main, accessor_fitting);
if (!is_enabled(f_ag_center) && is_enabled(f_ag_rotate))
calc_fit_forces_impl<false, true, main_force_accessor_T, fitting_force_accessor_T>(accessor_main, accessor_fitting);
if (!is_enabled(f_ag_center) && !is_enabled(f_ag_rotate))
calc_fit_forces_impl<false, false, main_force_accessor_T, fitting_force_accessor_T>(accessor_main, accessor_fitting);
}
std::vector<cvm::atom_pos> cvm::atom_group::positions() const
{
@ -1452,17 +1485,72 @@ void cvm::atom_group::apply_force(cvm::rvector const &force)
return;
}
if (is_enabled(f_ag_rotate)) {
auto ag_force = get_group_force_object();
for (size_t i = 0; i < size(); ++i) {
ag_force.add_atom_force(i, atoms[i].mass / total_mass * force);
}
}
const auto rot_inv = rot.inverse().matrix();
for (cvm::atom_iter ai = this->begin(); ai != this->end(); ai++) {
ai->apply_force(rot_inv * ((ai->mass/total_mass) * force));
cvm::atom_group::group_force_object cvm::atom_group::get_group_force_object() {
return cvm::atom_group::group_force_object(this);
}
cvm::atom_group::group_force_object::group_force_object(cvm::atom_group* ag):
m_ag(ag), m_group_for_fit(m_ag->fitting_group ? m_ag->fitting_group : m_ag),
m_has_fitting_force(m_ag->is_enabled(f_ag_center) || m_ag->is_enabled(f_ag_rotate)) {
if (m_has_fitting_force) {
if (m_ag->group_forces.size() != m_ag->size()) {
m_ag->group_forces.assign(m_ag->size(), 0);
} else {
std::fill(m_ag->group_forces.begin(),
m_ag->group_forces.end(), 0);
}
}
}
cvm::atom_group::group_force_object::~group_force_object() {
if (m_has_fitting_force) {
apply_force_with_fitting_group();
}
}
void cvm::atom_group::group_force_object::add_atom_force(size_t i, const cvm::rvector& force) {
if (m_has_fitting_force) {
m_ag->group_forces[i] += force;
} else {
// Apply the force directly if we don't use fitting
(*m_ag)[i].apply_force(force);
}
}
for (cvm::atom_iter ai = this->begin(); ai != this->end(); ai++) {
ai->apply_force((ai->mass/total_mass) * force);
void cvm::atom_group::group_force_object::apply_force_with_fitting_group() {
const cvm::rmatrix rot_inv = m_ag->rot.inverse().matrix();
if (cvm::debug()) {
cvm::log("Applying force on main group " + m_ag->name + ":\n");
}
for (size_t ia = 0; ia < m_ag->size(); ++ia) {
const cvm::rvector f_ia = rot_inv * m_ag->group_forces[ia];
(*m_ag)[ia].apply_force(f_ia);
if (cvm::debug()) {
cvm::log(cvm::to_str(f_ia));
}
}
// Gradients are only available with scalar components, so for a scalar component,
// if f_ag_fit_gradients is disabled, then the forces on the fitting group is not
// computed. For a vector component, we can only know the forces on the fitting
// group, but checking this flag can mimic results that the users expect (if
// "enableFitGradients no" then there is no force on the fitting group).
if (!m_ag->b_dummy && m_ag->is_enabled(f_ag_fit_gradients)) {
auto accessor_main = [this](size_t i){return m_ag->group_forces[i];};
auto accessor_fitting = [this](size_t j, const cvm::rvector& fitting_force){
(*(m_group_for_fit))[j].apply_force(fitting_force);
};
if (cvm::debug()) {
cvm::log("Applying force on the fitting group of main group" + m_ag->name + ":\n");
}
m_ag->calc_fit_forces(accessor_main, accessor_fitting);
if (cvm::debug()) {
cvm::log("Done applying force on the fitting group of main group" + m_ag->name + ":\n");
}
}
}

109
lib/colvars/colvaratoms.h
View File

@ -194,7 +194,7 @@ public:
int add_atom_numbers(std::string const &numbers_conf);
int add_atoms_of_group(atom_group const * ag);
int add_index_group(std::string const &index_group_name);
int add_index_group(std::string const &index_group_name, bool silent = false);
int add_atom_numbers_range(std::string const &range_conf);
int add_atom_name_residue_range(std::string const &psf_segid,
std::string const &range_conf);
@ -257,8 +257,63 @@ protected:
/// \brief Index in the colvarproxy arrays (if the group is scalable)
int index;
/// \brief The temporary forces acting on the main group atoms.
/// Currently this is only used for calculating the fitting group forces for
/// non-scalar components.
std::vector<cvm::rvector> group_forces;
public:
/*! @class group_force_object
* @brief A helper class for applying forces on an atom group in a way that
* is aware of the fitting group. NOTE: you are encouraged to use
* get_group_force_object() to get an instance of group_force_object
* instead of constructing directly.
*/
class group_force_object {
public:
/*! @brief Constructor of group_force_object
* @param ag The pointer to the atom group that forces will be applied on.
*/
group_force_object(cvm::atom_group* ag);
/*! @brief Destructor of group_force_object
*/
~group_force_object();
/*! @brief Apply force to atom i
* @param i The i-th of atom in the atom group.
* @param force The force being added to atom i.
*
* The function can be used as follows,
* @code
* // In your colvar::cvc::apply_force() loop of a component:
* auto ag_force = atoms->get_group_force_object();
* for (ia = 0; ia < atoms->size(); ia++) {
* const cvm::rvector f = compute_force_on_atom_ia();
* ag_force.add_atom_force(ia, f);
* }
* @endcode
* There are actually two scenarios under the hood:
* (i) If the atom group does not have a fitting group, then the force is
* added to atom i directly;
* (ii) If the atom group has a fitting group, the force on atom i will just
* be temporary stashed into ag->group_forces. At the end of the loop
* of apply_force(), the destructor ~group_force_object() will be called,
* which then call apply_force_with_fitting_group(). The forces on the
* main group will be rotated back by multiplying ag->group_forces with
* the inverse rotation. The forces on the fitting group (if
* enableFitGradients is on) will be calculated by calling
* calc_fit_forces.
*/
void add_atom_force(size_t i, const cvm::rvector& force);
private:
cvm::atom_group* m_ag;
cvm::atom_group* m_group_for_fit;
bool m_has_fitting_force;
void apply_force_with_fitting_group();
};
group_force_object get_group_force_object();
inline cvm::atom & operator [] (size_t const i)
{
return atoms[i];
@ -423,6 +478,9 @@ private:
/// \brief Center of geometry before any fitting
cvm::atom_pos cog_orig;
/// \brief Unrotated atom positions for fit gradients
std::vector<cvm::atom_pos> pos_unrotated;
public:
/// \brief Return the center of geometry of the atomic positions
@ -497,15 +555,60 @@ public:
/// \brief Calculate the derivatives of the fitting transformation
void calc_fit_gradients();
/*! @brief Actual implementation of `calc_fit_gradients`. The template is
/*! @brief Actual implementation of `calc_fit_gradients` and
* `calc_fit_forces`. The template is
* used to avoid branching inside the loops in case that the CPU
* branch prediction is broken (or further migration to GPU code).
* @tparam B_ag_center Centered the reference to origin? This should follow
* the value of `is_enabled(f_ag_center)`.
* @tparam B_ag_rotate Calculate the optimal rotation? This should follow
* the value of `is_enabled(f_ag_rotate)`.
* @tparam main_force_accessor_T The type of accessor of the main
* group forces or gradients acting on the rotated frame.
* @tparam fitting_force_accessor_T The type of accessor of the fitting group
* forces or gradients.
* @param accessor_main The accessor of the main group forces or gradients.
* accessor_main(i) should return the i-th force or gradient of the
* rotated main group.
* @param accessor_fitting The accessor of the fitting group forces or gradients.
* accessor_fitting(j, v) should store/apply the j-th atom gradient or
* force in the fitting group.
*
* This function is used to (i) project the gradients of CV with respect to
* rotated main group atoms to fitting group atoms, or (ii) project the forces
* on rotated main group atoms to fitting group atoms, by the following two steps
* (using the goal (ii) for example):
* (1) Loop over the positions of main group atoms and call cvm::quaternion::position_derivative_inner
* to project the forces on rotated main group atoms to the forces on quaternion.
* (2) Loop over the positions of fitting group atoms, compute the gradients of
* \f$\mathbf{q}\f$ with respect to the position of each atom, and then multiply
* that with the force on \f$\mathbf{q}\f$ (chain rule).
*/
template <bool B_ag_center, bool B_ag_rotate> void calc_fit_gradients_impl();
template <bool B_ag_center, bool B_ag_rotate,
typename main_force_accessor_T, typename fitting_force_accessor_T>
void calc_fit_forces_impl(
main_force_accessor_T accessor_main,
fitting_force_accessor_T accessor_fitting) const;
/*! @brief Calculate or apply the fitting group forces from the main group forces.
* @tparam main_force_accessor_T The type of accessor of the main
* group forces or gradients.
* @tparam fitting_force_accessor_T The type of accessor of the fitting group
* forces or gradients.
* @param accessor_main The accessor of the main group forces or gradients.
* accessor_main(i) should return the i-th force or gradient of the
* main group.
* @param accessor_fitting The accessor of the fitting group forces or gradients.
* accessor_fitting(j, v) should store/apply the j-th atom gradient or
* force in the fitting group.
*
* This function just dispatches the parameters to calc_fit_forces_impl that really
* performs the calculations.
*/
template <typename main_force_accessor_T, typename fitting_force_accessor_T>
void calc_fit_forces(
main_force_accessor_T accessor_main,
fitting_force_accessor_T accessor_fitting) const;
/// \brief Derivatives of the fitting transformation
std::vector<cvm::atom_pos> fit_gradients;

57
lib/colvars/colvarbias.cpp
View File

@ -93,6 +93,8 @@ int colvarbias::init(std::string const &conf)
cvm::log("Reinitializing bias \""+name+"\".\n");
}
feature_states[f_cvb_step_zero_data].available = true;
colvar_values.resize(num_variables());
for (i = 0; i < num_variables(); i++) {
colvar_values[i].type(colvars[i]->value().type());
@ -157,7 +159,7 @@ int colvarbias::init_dependencies() {
init_feature(f_cvb_step_zero_data, "step_zero_data", f_type_user);
init_feature(f_cvb_apply_force, "apply_force", f_type_user);
require_feature_children(f_cvb_apply_force, f_cv_gradient);
require_feature_children(f_cvb_apply_force, f_cv_apply_force);
init_feature(f_cvb_bypass_ext_lagrangian, "bypass_extended_Lagrangian_coordinates", f_type_user);
@ -199,6 +201,8 @@ int colvarbias::init_dependencies() {
init_feature(f_cvb_extended, "Bias on extended-Lagrangian variables", f_type_static);
init_feature(f_cvb_smp, "smp_computation", f_type_user);
// check that everything is initialized
for (i = 0; i < colvardeps::f_cvb_ntot; i++) {
if (is_not_set(i)) {
@ -221,8 +225,9 @@ int colvarbias::init_dependencies() {
// The feature f_cvb_bypass_ext_lagrangian is only implemented by some derived classes
// (initially, harmonicWalls)
feature_states[f_cvb_bypass_ext_lagrangian].available = false;
// disabled by default; can be changed by derived classes that implement it
feature_states[f_cvb_bypass_ext_lagrangian].enabled = false;
// Most biases cannot currently be processed in parallel over threads
feature_states[f_cvb_smp].available = false;
return COLVARS_OK;
}
@ -704,7 +709,7 @@ int colvarbias::read_state_string(char const *buffer)
std::ostream &colvarbias::write_state_data_key(std::ostream &os, std::string const &key,
bool header)
bool header) const
{
os << (header ? "\n" : "") << key << (header ? "\n" : " ");
return os;
@ -712,7 +717,7 @@ std::ostream &colvarbias::write_state_data_key(std::ostream &os, std::string con
cvm::memory_stream &colvarbias::write_state_data_key(cvm::memory_stream &os, std::string const &key,
bool /* header */)
bool /* header */) const
{
os << std::string(key);
return os;
@ -792,6 +797,8 @@ int colvarbias_ti::init(std::string const &conf)
{
int error_code = COLVARS_OK;
key_lookup(conf, "grid", &grid_conf);
get_keyval_feature(this, conf, "writeTISamples",
f_cvb_write_ti_samples,
is_enabled(f_cvb_write_ti_samples));
@ -800,18 +807,16 @@ int colvarbias_ti::init(std::string const &conf)
f_cvb_write_ti_pmf,
is_enabled(f_cvb_write_ti_pmf));
if (is_enabled(f_cvb_write_ti_pmf)) {
enable(f_cvb_write_ti_samples);
}
if ((num_variables() > 1) && is_enabled(f_cvb_write_ti_pmf)) {
return cvm::error("Error: only 1-dimensional PMFs can be written "
"on the fly.\n"
"Consider using writeTISamples instead and "
"post-processing the sampled free-energy gradients.\n",
COLVARS_NOT_IMPLEMENTED);
} else {
error_code |= init_grids();
}
if (is_enabled(f_cvb_write_ti_pmf)) {
enable(f_cvb_write_ti_samples);
}
if (is_enabled(f_cvb_calc_ti_samples)) {
@ -831,6 +836,8 @@ int colvarbias_ti::init(std::string const &conf)
}
}
error_code |= colvarbias_ti::init_grids();
if (is_enabled(f_cvb_write_ti_pmf) || is_enabled(f_cvb_write_ti_samples)) {
cvm::main()->cite_feature("Internal-forces free energy estimator");
}
@ -844,16 +851,15 @@ int colvarbias_ti::init_grids()
if (is_enabled(f_cvb_calc_ti_samples)) {
if (!ti_avg_forces) {
ti_bin.resize(num_variables());
ti_bin.assign(ti_bin.size(), -1);
ti_system_forces.resize(num_variables());
for (size_t icv = 0; icv < num_variables(); icv++) {
ti_system_forces[icv].type(variables(icv)->value());
ti_system_forces[icv].is_derivative();
ti_system_forces[icv].reset();
}
ti_avg_forces.reset(new colvar_grid_gradient(colvars));
ti_count.reset(new colvar_grid_count(colvars));
ti_avg_forces->samples = ti_count;
ti_count->has_parent_data = true;
ti_count.reset(new colvar_grid_count(colvars, grid_conf));
ti_avg_forces.reset(new colvar_grid_gradient(colvars, ti_count));
}
}
@ -884,8 +890,12 @@ int colvarbias_ti::update_system_forces(std::vector<colvarvalue> const
size_t i;
if (proxy->total_forces_same_step()) {
for (i = 0; i < num_variables(); i++) {
if (cvm::debug()) {
cvm::log("TI bin for bias \"" + name + "\" = " + cvm::to_str(ti_bin) + ".\n");
}
for (i = 0; i < num_variables(); i++) {
if (variables(i)->is_enabled(f_cv_total_force_current_step)) {
ti_bin[i] = ti_avg_forces->current_bin_scalar(i);
}
}
@ -894,8 +904,10 @@ int colvarbias_ti::update_system_forces(std::vector<colvarvalue> const
if ((cvm::step_relative() > 0) || proxy->total_forces_same_step()) {
if (ti_avg_forces->index_ok(ti_bin)) {
for (i = 0; i < num_variables(); i++) {
if (variables(i)->is_enabled(f_cv_subtract_applied_force)) {
if (variables(i)->is_enabled(f_cv_subtract_applied_force) ||
(cvm::proxy->total_forces_same_step() && !variables(i)->is_enabled(f_cv_external))) {
// this colvar is already subtracting all applied forces
// or the "total force" is really a system force at current step
ti_system_forces[i] = variables(i)->total_force();
} else {
ti_system_forces[i] = variables(i)->total_force() -
@ -904,14 +916,17 @@ int colvarbias_ti::update_system_forces(std::vector<colvarvalue> const
}
}
if (cvm::step_relative() > 0 || is_enabled(f_cvb_step_zero_data)) {
if (cvm::debug()) {
cvm::log("Accumulating TI forces for bias \"" + name + "\".\n");
}
ti_avg_forces->acc_value(ti_bin, ti_system_forces);
}
}
}
if (!proxy->total_forces_same_step()) {
// Set the index for use in the next iteration, when total forces come in
for (i = 0; i < num_variables(); i++) {
for (i = 0; i < num_variables(); i++) {
if (!variables(i)->is_enabled(f_cv_total_force_current_step)) {
// Set the index for use in the next iteration, when total forces come in
ti_bin[i] = ti_avg_forces->current_bin_scalar(i);
}
}

7
lib/colvars/colvarbias.h
View File

@ -174,14 +174,14 @@ public:
/// \param[in,out] os Output stream
/// \param[in] key Keyword labeling the header block
/// \param[in] header Whether this is the header of a multi-line segment vs a single line
std::ostream &write_state_data_key(std::ostream &os, std::string const &key, bool header = true);
std::ostream &write_state_data_key(std::ostream &os, std::string const &key, bool header = true) const;
/// Write a keyword header for a data sequence to an unformatted stream
/// \param[in,out] os Output stream
/// \param[in] key Keyword labeling the header block
/// \param[in] header Ignored
cvm::memory_stream &write_state_data_key(cvm::memory_stream &os, std::string const &key,
bool header = true);
bool header = true) const;
private:
@ -358,6 +358,9 @@ protected:
/// \brief Forces exerted from the system to the associated variables
std::vector<colvarvalue> ti_system_forces;
/// Grid configuration parameters (also used by grids in derived classes)
std::string grid_conf;
/// Averaged system forces
std::shared_ptr<colvar_grid_gradient> ti_avg_forces;

120
lib/colvars/colvarbias_abf.cpp
View File

@ -87,24 +87,25 @@ int colvarbias_abf::init(std::string const &conf)
get_keyval(conf, "shared", shared_on, false);
if (shared_on) {
cvm::main()->cite_feature("Multiple-walker ABF implementation");
if ((proxy->replica_enabled() != COLVARS_OK) ||
(proxy->num_replicas() <= 1)) {
return cvm::error("Error: shared ABF requires more than one replica.",
COLVARS_INPUT_ERROR);
}
cvm::log("shared ABF will be applied among "+
cvm::to_str(proxy->num_replicas()) + " replicas.\n");
cvm::main()->cite_feature("Updated multiple-walker ABF implementation");
// Cannot check this here because the replica communicator is obtained later
// in Gromacs
// if ((proxy->check_replicas_enabled() != COLVARS_OK) ||
// (proxy->num_replicas() <= 1)) {
// return cvm::error("Error: shared ABF requires more than one replica.",
// COLVARS_INPUT_ERROR);
// }
// cvm::log("shared ABF will be applied among "+
// cvm::to_str(proxy->num_replicas()) + " replicas.\n");
// If shared_freq is not set, we default to output_freq
get_keyval(conf, "sharedFreq", shared_freq, output_freq);
if ( shared_freq && output_freq % shared_freq ) {
return cvm::error("Error: outputFreq must be a multiple of sharedFreq.\n");
}
// Allocate these at init time if possible
local_samples.reset(new colvar_grid_count(colvars));
local_gradients.reset(new colvar_grid_gradient(colvars, local_samples));
local_pmf.reset(new integrate_potential(colvars, local_gradients));
}
// ************* checking the associated colvars *******************
@ -124,10 +125,17 @@ int colvarbias_abf::init(std::string const &conf)
colvars[i]->enable(f_cv_hide_Jacobian);
}
// If any colvar is extended-system, we need to collect the extended
// system gradient
if (colvars[i]->is_enabled(f_cv_extended_Lagrangian))
// If any colvar is extended-system (restrained, not driven external param), we are running eABF
if (colvars[i]->is_enabled(f_cv_extended_Lagrangian)
&& !colvars[i]->is_enabled(f_cv_external)) {
enable(f_cvb_extended);
}
if (!colvars[i]->is_enabled(f_cv_total_force_current_step)) {
// If any colvar does not have current-step total force, then
// we can't do step 0 data
provide(f_cvb_step_zero_data, false);
}
// Cannot mix and match coarse time steps with ABF because it gives
// wrong total force averages - total force needs to be averaged over
@ -181,12 +189,23 @@ int colvarbias_abf::init(std::string const &conf)
cvm::log("Allocating count and free energy gradient grids.\n");
}
samples.reset(new colvar_grid_count(colvars));
gradients.reset(new colvar_grid_gradient(colvars, samples));
{
/// Optional custom configuration string for grid parameters
std::string grid_conf;
key_lookup(conf, "grid", &grid_conf);
samples.reset(new colvar_grid_count(colvars, grid_conf));
}
gradients.reset(new colvar_grid_gradient(colvars, samples)); // Also use samples as template for sizes
gradients->full_samples = full_samples;
gradients->min_samples = min_samples;
if (shared_on) {
local_samples.reset(new colvar_grid_count(colvars, samples));
local_gradients.reset(new colvar_grid_gradient(colvars, local_samples));
}
// Data for eABF z-based estimator
if (is_enabled(f_cvb_extended)) {
get_keyval(conf, "CZARestimator", b_CZAR_estimator, true);
@ -198,11 +217,11 @@ int colvarbias_abf::init(std::string const &conf)
colvarparse::parse_silent);
z_bin.assign(num_variables(), 0);
z_samples.reset(new colvar_grid_count(colvars));
z_samples.reset(new colvar_grid_count(colvars, samples));
z_samples->request_actual_value();
z_gradients.reset(new colvar_grid_gradient(colvars, z_samples));
z_gradients->request_actual_value();
czar_gradients.reset(new colvar_grid_gradient(colvars));
czar_gradients.reset(new colvar_grid_gradient(colvars, nullptr, samples));
}
get_keyval(conf, "integrate", b_integrate, num_variables() <= 3); // Integrate for output if d<=3
@ -216,6 +235,9 @@ int colvarbias_abf::init(std::string const &conf)
if (b_CZAR_estimator) {
czar_pmf.reset(new integrate_potential(colvars, czar_gradients));
}
if (shared_on) {
local_pmf.reset(new integrate_potential(colvars, local_gradients));
}
// Parameters for integrating initial (and final) gradient data
get_keyval(conf, "integrateMaxIterations", integrate_iterations, 10000, colvarparse::parse_silent);
get_keyval(conf, "integrateTol", integrate_tol, 1e-6, colvarparse::parse_silent);
@ -228,9 +250,9 @@ int colvarbias_abf::init(std::string const &conf)
if (b_CZAR_estimator && shared_on && cvm::main()->proxy->replica_index() == 0) {
// The pointers below are used for outputting CZAR data
// Allocate grids for collected global data, on replica 0 only
global_z_samples.reset(new colvar_grid_count(colvars));
global_z_samples.reset(new colvar_grid_count(colvars, samples));
global_z_gradients.reset(new colvar_grid_gradient(colvars, global_z_samples));
global_czar_gradients.reset(new colvar_grid_gradient(colvars));
global_czar_gradients.reset(new colvar_grid_gradient(colvars, nullptr, samples));
global_czar_pmf.reset(new integrate_potential(colvars, global_czar_gradients));
} else {
// otherwise they are just aliases for the local CZAR grids
@ -244,10 +266,10 @@ int colvarbias_abf::init(std::string const &conf)
// This used to be only if "shared" was defined,
// but now we allow calling share externally (e.g. from Tcl).
if (b_CZAR_estimator) {
z_samples_in.reset(new colvar_grid_count(colvars));
z_samples_in.reset(new colvar_grid_count(colvars, samples));
z_gradients_in.reset(new colvar_grid_gradient(colvars, z_samples_in));
}
last_samples.reset(new colvar_grid_count(colvars));
last_samples.reset(new colvar_grid_count(colvars, samples));
last_gradients.reset(new colvar_grid_gradient(colvars, last_samples));
// Any data collected after now is new for shared ABF purposes
shared_last_step = cvm::step_absolute();
@ -315,27 +337,36 @@ int colvarbias_abf::update()
size_t i;
for (i = 0; i < num_variables(); i++) {
bin[i] = samples->current_bin_scalar(i);
if (colvars[i]->is_enabled(f_cv_total_force_current_step)) {
force_bin[i] = bin[i];
}
}
// ***********************************************************
// ****** ABF Part I: update the FE gradient estimate ******
// ***********************************************************
if (cvm::proxy->total_forces_same_step()) {
// e.g. in LAMMPS, total forces are current
force_bin = bin;
// Share data first, so that 2d/3d PMF is refreshed using new data for mw-pABF.
// shared_on can be true with shared_freq 0 if we are sharing via script
if (shared_on && shared_freq &&
shared_last_step >= 0 && // we have already collected some data
cvm::step_absolute() > shared_last_step && // time has passed since the last sharing timestep
// (avoid re-sharing at last and first ts of successive run statements)
cvm::step_absolute() % shared_freq == 0) {
// Share gradients and samples for shared ABF.
replica_share();
}
if (can_accumulate_data() && is_enabled(f_cvb_history_dependent)) {
if (cvm::step_relative() > 0 || cvm::proxy->total_forces_same_step()) {
// Note: this will skip step 0 data when available in some cases (extended system),
// but not doing so would make the code more complex
if (samples->index_ok(force_bin)) {
// Only if requested and within bounds of the grid...
// get total forces (lagging by 1 timestep) from colvars
// and subtract previous ABF force if necessary
// get total force and subtract previous ABF force if necessary
update_system_force();
gradients->acc_force(force_bin, system_force);
@ -368,21 +399,11 @@ int colvarbias_abf::update()
}
}
if (!(cvm::proxy->total_forces_same_step())) {
// e.g. in NAMD, total forces will be available for next timestep
// hence we store the current colvar bin
force_bin = bin;
}
// In some cases, total forces are stored for next timestep
// hence we store the current colvar bin - this is overwritten on a per-colvar basis
// at the top of update()
force_bin = bin;
// Share data after force sample is collected for this time step
// shared_on can be true with shared_freq 0 if we are sharing via script
if (shared_on && shared_freq &&
cvm::step_absolute() > shared_last_step && // time has passed since the last sharing timestep
// (avoid re-sharing at last and first ts of successive run statements)
cvm::step_absolute() % shared_freq == 0) {
// Share gradients and samples for shared ABF.
replica_share();
}
// ******************************************************************
// ****** ABF Part II: calculate and apply the biasing force ******
@ -452,10 +473,13 @@ int colvarbias_abf::update_system_force()
// System force from atomic forces (or extended Lagrangian if applicable)
for (i = 0; i < num_variables(); i++) {
if (colvars[i]->is_enabled(f_cv_subtract_applied_force)) {
if (colvars[i]->is_enabled(f_cv_subtract_applied_force)
|| colvars[i]->is_enabled(f_cv_total_force_current_step)) {
// this colvar is already subtracting the ABF force
// or the "total force" is from current step and cannot possibly contain Colvars biases
system_force[i] = colvars[i]->total_force().real_value;
} else {
// Subtract previous step's bias force from previous step's total force
system_force[i] = colvars[i]->total_force().real_value
- colvar_forces[i].real_value;
}
@ -525,7 +549,7 @@ int colvarbias_abf::replica_share() {
colvarproxy *proxy = cvm::main()->proxy;
if (proxy->replica_enabled() != COLVARS_OK) {
if (proxy->check_replicas_enabled() != COLVARS_OK) {
cvm::error("Error: shared ABF: No replicas.\n");
return COLVARS_ERROR;
}
@ -542,7 +566,7 @@ int colvarbias_abf::replica_share() {
if (!local_samples) {
// We arrive here if sharing has just been enabled by a script
// in which case local arrays have not been initialized yet
local_samples.reset(new colvar_grid_count(colvars));
local_samples.reset(new colvar_grid_count(colvars, samples));
local_gradients.reset(new colvar_grid_gradient(colvars, local_samples));
local_pmf.reset(new integrate_potential(colvars, local_gradients));
}
@ -662,9 +686,9 @@ int colvarbias_abf::replica_share_CZAR() {
// We arrive here if sharing has just been enabled by a script
// Allocate grids for collective data, on replica 0 only
// overriding CZAR grids that are equal to local ones by default
global_z_samples.reset(new colvar_grid_count(colvars));
global_z_samples.reset(new colvar_grid_count(colvars, samples));
global_z_gradients.reset(new colvar_grid_gradient(colvars, global_z_samples));
global_czar_gradients.reset(new colvar_grid_gradient(colvars));
global_czar_gradients.reset(new colvar_grid_gradient(colvars, nullptr, samples));
global_czar_pmf.reset(new integrate_potential(colvars, global_czar_gradients));
}

6
lib/colvars/colvarbias_histogram.cpp
View File

@ -98,10 +98,10 @@ int colvarbias_histogram::init(std::string const &conf)
}
{
std::string grid_conf;
if (key_lookup(conf, "histogramGrid", &grid_conf)) {
if (key_lookup(conf, "histogramGrid", &grid_conf) ||
key_lookup(conf, "grid", &grid_conf)) {
grid->parse_params(grid_conf);
grid->check_keywords(grid_conf, "histogramGrid");
grid->check_keywords(grid_conf, "grid");
}
}

1
lib/colvars/colvarbias_histogram.h
View File

@ -38,6 +38,7 @@ protected:
/// n-dim histogram
colvar_grid_scalar *grid;
std::string grid_conf;
std::vector<int> bin;
std::string out_name, out_name_dx;

60
lib/colvars/colvarbias_histogram_reweight_amd.cpp
View File

@ -11,43 +11,9 @@
#include "colvarproxy.h"
#include "colvars_memstream.h"
colvarbias_reweightaMD::colvarbias_reweightaMD(char const *key)
: colvarbias_histogram(key), grid_count(NULL), grid_dV(NULL),
grid_dV_square(NULL), pmf_grid_exp_avg(NULL), pmf_grid_cumulant(NULL),
grad_grid_exp_avg(NULL), grad_grid_cumulant(NULL)
{
}
colvarbias_reweightaMD::colvarbias_reweightaMD(char const *key) : colvarbias_histogram(key) {}
colvarbias_reweightaMD::~colvarbias_reweightaMD() {
if (grid_dV) {
delete grid_dV;
grid_dV = NULL;
}
if (grid_dV_square) {
delete grid_dV_square;
grid_dV_square = NULL;
}
if (grid_count) {
delete grid_count;
grid_count = NULL;
}
if (pmf_grid_exp_avg) {
delete pmf_grid_exp_avg;
pmf_grid_exp_avg = NULL;
}
if (pmf_grid_cumulant) {
delete pmf_grid_cumulant;
pmf_grid_cumulant = NULL;
}
if (grad_grid_exp_avg) {
delete grad_grid_exp_avg;
grad_grid_exp_avg = NULL;
}
if (grad_grid_cumulant) {
delete grad_grid_cumulant;
grad_grid_cumulant = NULL;
}
}
colvarbias_reweightaMD::~colvarbias_reweightaMD() {}
int colvarbias_reweightaMD::init(std::string const &conf) {
if (cvm::proxy->accelMD_enabled() == false) {
@ -60,21 +26,21 @@ int colvarbias_reweightaMD::init(std::string const &conf) {
get_keyval(conf, "WritePMFGradients", b_write_gradients, true);
get_keyval(conf, "historyFreq", history_freq, 0);
b_history_files = (history_freq > 0);
grid_count = new colvar_grid_scalar(colvars);
grid_count.reset(new colvar_grid_scalar(colvars, nullptr, false, grid_conf));
grid_count->request_actual_value();
grid->request_actual_value();
pmf_grid_exp_avg = new colvar_grid_scalar(colvars);
pmf_grid_exp_avg.reset(new colvar_grid_scalar(colvars, grid_count));
if (b_write_gradients) {
grad_grid_exp_avg = new colvar_grid_gradient(colvars);
grad_grid_exp_avg.reset(new colvar_grid_gradient(colvars, nullptr, grid_count));
}
if (b_use_cumulant_expansion) {
grid_dV = new colvar_grid_scalar(colvars);
grid_dV_square = new colvar_grid_scalar(colvars);
pmf_grid_cumulant = new colvar_grid_scalar(colvars);
grid_dV.reset(new colvar_grid_scalar(colvars, grid_count));
grid_dV_square.reset(new colvar_grid_scalar(colvars, grid_count));
pmf_grid_cumulant.reset(new colvar_grid_scalar(colvars, grid_count));
grid_dV->request_actual_value();
grid_dV_square->request_actual_value();
if (b_write_gradients) {
grad_grid_cumulant = new colvar_grid_gradient(colvars);
grad_grid_cumulant.reset(new colvar_grid_gradient(colvars, nullptr, grid_count));
}
}
previous_bin.assign(num_variables(), -1);
@ -193,7 +159,7 @@ int colvarbias_reweightaMD::write_exponential_reweighted_pmf(
pmf_grid_exp_avg->set_value(i, tmp / count);
}
}
hist_to_pmf(pmf_grid_exp_avg, grid_count);
hist_to_pmf(pmf_grid_exp_avg.get(), grid_count.get());
pmf_grid_exp_avg->write_multicol(pmf_grid_os);
if (!keep_open) {
cvm::proxy->close_output_stream(output_pmf);
@ -231,9 +197,9 @@ int colvarbias_reweightaMD::write_cumulant_expansion_pmf(
if (!pmf_grid_cumulant_os) {
return COLVARS_FILE_ERROR;
}
compute_cumulant_expansion_factor(grid_dV, grid_dV_square,
grid_count, pmf_grid_cumulant);
hist_to_pmf(pmf_grid_cumulant, grid_count);
compute_cumulant_expansion_factor(grid_dV.get(), grid_dV_square.get(),
grid_count.get(), pmf_grid_cumulant.get());
hist_to_pmf(pmf_grid_cumulant.get(), grid_count.get());
pmf_grid_cumulant->write_multicol(pmf_grid_cumulant_os);
if (!keep_open) {
cvm::proxy->close_output_stream(output_pmf);

14
lib/colvars/colvarbias_histogram_reweight_amd.h
View File

@ -68,9 +68,9 @@ protected:
/// Use cumulant expansion to second order?
bool b_use_cumulant_expansion;
colvar_grid_scalar* grid_count;
colvar_grid_scalar* grid_dV;
colvar_grid_scalar* grid_dV_square;
std::shared_ptr<colvar_grid_scalar> grid_count;
std::unique_ptr<colvar_grid_scalar> grid_dV;
std::unique_ptr<colvar_grid_scalar> grid_dV_square;
/// Number of timesteps between recording data in history files (if non-zero)
size_t history_freq;
@ -90,10 +90,10 @@ protected:
private:
/// temporary grids for evaluating PMFs
colvar_grid_scalar *pmf_grid_exp_avg;
colvar_grid_scalar *pmf_grid_cumulant;
colvar_grid_gradient *grad_grid_exp_avg;
colvar_grid_gradient *grad_grid_cumulant;
std::unique_ptr<colvar_grid_scalar> pmf_grid_exp_avg;
std::unique_ptr<colvar_grid_scalar> pmf_grid_cumulant;
std::unique_ptr<colvar_grid_gradient> grad_grid_exp_avg;
std::unique_ptr<colvar_grid_gradient> grad_grid_cumulant;
};
#endif // COLVARBIAS_HISTOGRAM_REWEIGHT_AMD

215
lib/colvars/colvarbias_meta.cpp
View File

@ -11,27 +11,10 @@
#include <iomanip>
#include <algorithm>
// Define function to get the absolute path of a replica file
#if defined(_WIN32) && !defined(__CYGWIN__)
#include <direct.h>
#define GETCWD(BUF, SIZE) ::_getcwd(BUF, SIZE)
#define PATHSEP "\\"
#else
#include <unistd.h>
#define GETCWD(BUF, SIZE) ::getcwd(BUF, SIZE)
#define PATHSEP "/"
#endif
#ifdef __cpp_lib_filesystem
// When std::filesystem is available, use it
#include <filesystem>
#undef GETCWD
#define GETCWD(BUF, SIZE) (std::filesystem::current_path().string().c_str())
#endif
#include "colvarmodule.h"
#include "colvarproxy.h"
#include "colvar.h"
#include "colvargrid.h"
#include "colvarbias_meta.h"
#include "colvars_memstream.h"
@ -49,8 +32,6 @@ colvarbias_meta::colvarbias_meta(char const *key)
use_grids = true;
grids_freq = 0;
rebin_grids = false;
hills_energy = NULL;
hills_energy_gradients = NULL;
dump_fes = true;
keep_hills = false;
@ -161,9 +142,9 @@ int colvarbias_meta::init(std::string const &conf)
get_keyval(conf, "keepHills", keep_hills, keep_hills);
get_keyval(conf, "keepFreeEnergyFiles", dump_fes_save, dump_fes_save);
if (hills_energy == NULL) {
hills_energy = new colvar_grid_scalar(colvars);
hills_energy_gradients = new colvar_grid_gradient(colvars);
if (!hills_energy) {
hills_energy.reset(new colvar_grid_scalar(colvars, nullptr, false, grid_conf));
hills_energy_gradients.reset(new colvar_grid_gradient(colvars, nullptr, hills_energy));
}
} else {
@ -209,7 +190,7 @@ int colvarbias_meta::init_replicas_params(std::string const &conf)
get_keyval(conf, "replicaID", replica_id, replica_id);
if (!replica_id.size()) {
if (proxy->replica_enabled() == COLVARS_OK) {
if (proxy->check_replicas_enabled() == COLVARS_OK) {
// Obtain replicaID from the communicator
replica_id = cvm::to_str(proxy->replica_index());
cvm::log("Setting replicaID from communication layer: replicaID = "+
@ -272,7 +253,6 @@ int colvarbias_meta::init_ebmeta_params(std::string const &conf)
{
int error_code = COLVARS_OK;
// for ebmeta
target_dist = NULL;
get_keyval(conf, "ebMeta", ebmeta, false);
if(ebmeta){
cvm::main()->cite_feature("Ensemble-biased metadynamics (ebMetaD)");
@ -283,7 +263,7 @@ int colvarbias_meta::init_ebmeta_params(std::string const &conf)
"targetDistFile accordingly.\n",
COLVARS_INPUT_ERROR);
}
target_dist = new colvar_grid_scalar();
target_dist.reset(new colvar_grid_scalar());
error_code |= target_dist->init_from_colvars(colvars);
std::string target_dist_file;
get_keyval(conf, "targetDistFile", target_dist_file);
@ -336,33 +316,15 @@ colvarbias_meta::~colvarbias_meta()
{
colvarbias_meta::clear_state_data();
colvarproxy *proxy = cvm::main()->proxy;
proxy->close_output_stream(replica_hills_file);
proxy->close_output_stream(hills_traj_file_name());
if (target_dist) {
delete target_dist;
target_dist = NULL;
}
}
int colvarbias_meta::clear_state_data()
{
if (hills_energy) {
delete hills_energy;
hills_energy = NULL;
}
if (hills_energy_gradients) {
delete hills_energy_gradients;
hills_energy_gradients = NULL;
}
hills.clear();
hills_off_grid.clear();
return COLVARS_OK;
}
@ -451,8 +413,11 @@ int colvarbias_meta::update()
error_code |= update_grid_params();
// add new biasing energy/forces
error_code |= update_bias();
// update grid content to reflect new bias
error_code |= update_grid_data();
if (use_grids) {
// update grid content to reflect new bias
error_code |= update_grid_data();
}
if (comm != single_replica &&
(cvm::step_absolute() % replica_update_freq) == 0) {
@ -539,9 +504,9 @@ int colvarbias_meta::update_grid_params()
// map everything into new grids
colvar_grid_scalar *new_hills_energy =
new colvar_grid_scalar(*hills_energy);
new colvar_grid_scalar(*hills_energy);
colvar_grid_gradient *new_hills_energy_gradients =
new colvar_grid_gradient(*hills_energy_gradients);
new colvar_grid_gradient(*hills_energy_gradients);
// supply new boundaries to the new grids
@ -556,10 +521,8 @@ int colvarbias_meta::update_grid_params()
new_hills_energy->map_grid(*hills_energy);
new_hills_energy_gradients->map_grid(*hills_energy_gradients);
delete hills_energy;
delete hills_energy_gradients;
hills_energy = new_hills_energy;
hills_energy_gradients = new_hills_energy_gradients;
hills_energy.reset(new_hills_energy);
hills_energy_gradients.reset(new_hills_energy_gradients);
curr_bin = hills_energy->get_colvars_index();
if (cvm::debug())
@ -641,8 +604,7 @@ int colvarbias_meta::update_grid_data()
{
if ((cvm::step_absolute() % grids_freq) == 0) {
// map the most recent gaussians to the grids
project_hills(new_hills_begin, hills.end(),
hills_energy, hills_energy_gradients);
project_hills(new_hills_begin, hills.end(), hills_energy.get(), hills_energy_gradients.get());
new_hills_begin = hills.end();
// TODO: we may want to condense all into one replicas array,
@ -651,8 +613,8 @@ int colvarbias_meta::update_grid_data()
for (size_t ir = 0; ir < replicas.size(); ir++) {
replicas[ir]->project_hills(replicas[ir]->new_hills_begin,
replicas[ir]->hills.end(),
replicas[ir]->hills_energy,
replicas[ir]->hills_energy_gradients);
replicas[ir]->hills_energy.get(),
replicas[ir]->hills_energy_gradients.get());
replicas[ir]->new_hills_begin = replicas[ir]->hills.end();
}
}
@ -670,11 +632,20 @@ int colvarbias_meta::calc_energy(std::vector<colvarvalue> const *values)
replicas[ir]->bias_energy = 0.0;
}
std::vector<int> const curr_bin = values ?
hills_energy->get_colvars_index(*values) :
hills_energy->get_colvars_index();
bool index_ok = false;
std::vector<int> curr_bin;
if (hills_energy->index_ok(curr_bin)) {
if (use_grids) {
curr_bin = values ?
hills_energy->get_colvars_index(*values) :
hills_energy->get_colvars_index();
index_ok = hills_energy->index_ok(curr_bin);
}
if ( index_ok ) {
// index is within the grid: get the energy from there
for (ir = 0; ir < replicas.size(); ir++) {
@ -723,11 +694,20 @@ int colvarbias_meta::calc_forces(std::vector<colvarvalue> const *values)
}
}
std::vector<int> const curr_bin = values ?
hills_energy->get_colvars_index(*values) :
hills_energy->get_colvars_index();
bool index_ok = false;
std::vector<int> curr_bin;
if (hills_energy->index_ok(curr_bin)) {
if (use_grids) {
curr_bin = values ?
hills_energy->get_colvars_index(*values) :
hills_energy->get_colvars_index();
index_ok = hills_energy->index_ok(curr_bin);
}
if ( index_ok ) {
for (ir = 0; ir < replicas.size(); ir++) {
cvm::real const *f = &(replicas[ir]->hills_energy_gradients->value(curr_bin));
for (ic = 0; ic < num_variables(); ic++) {
@ -959,8 +939,7 @@ void colvarbias_meta::project_hills(colvarbias_meta::hill_iter h_first,
void colvarbias_meta::recount_hills_off_grid(colvarbias_meta::hill_iter h_first,
colvarbias_meta::hill_iter h_last,
colvar_grid_scalar * /* he */)
colvarbias_meta::hill_iter h_last)
{
hills_off_grid.clear();
@ -1078,9 +1057,13 @@ int colvarbias_meta::update_replicas_registry()
(replicas.back())->comm = multiple_replicas;
if (use_grids) {
(replicas.back())->hills_energy = new colvar_grid_scalar(colvars);
(replicas.back())->hills_energy_gradients = new colvar_grid_gradient(colvars);
(replicas.back())
->hills_energy.reset(new colvar_grid_scalar(colvars, hills_energy));
(replicas.back())
->hills_energy_gradients.reset(
new colvar_grid_gradient(colvars, nullptr, hills_energy));
}
if (is_enabled(f_cvb_calc_ti_samples)) {
(replicas.back())->enable(f_cvb_calc_ti_samples);
(replicas.back())->colvarbias_ti::init_grids();
@ -1336,34 +1319,40 @@ template <typename IST> IST &colvarbias_meta::read_state_data_template_(IST &is)
{
if (use_grids) {
colvar_grid_scalar *hills_energy_backup = NULL;
colvar_grid_gradient *hills_energy_gradients_backup = NULL;
std::shared_ptr<colvar_grid_scalar> hills_energy_backup;
std::shared_ptr<colvar_grid_gradient> hills_energy_gradients_backup;
if (has_data) {
bool const need_backup = has_data;
if (need_backup) {
if (cvm::debug())
cvm::log("Backupping grids for metadynamics bias \""+
this->name+"\""+
((comm != single_replica) ? ", replica \""+replica_id+"\"" : "")+".\n");
hills_energy_backup = hills_energy;
hills_energy_gradients_backup = hills_energy_gradients;
hills_energy = new colvar_grid_scalar(colvars);
hills_energy_gradients = new colvar_grid_gradient(colvars);
cvm::log("Backing up grids for metadynamics bias \"" + this->name + "\"" +
((comm != single_replica) ? ", replica \"" + replica_id + "\"" : "") + ".\n");
hills_energy_backup = std::move(hills_energy);
hills_energy_gradients_backup = std::move(hills_energy_gradients);
hills_energy.reset(new colvar_grid_scalar(colvars, hills_energy));
hills_energy_gradients.reset(new colvar_grid_gradient(colvars, nullptr, hills_energy));
}
read_grid_data_template_<IST, colvar_grid_scalar>(is, "hills_energy", hills_energy,
hills_energy_backup);
read_grid_data_template_<IST, colvar_grid_scalar>(is, "hills_energy", hills_energy.get(),
hills_energy_backup.get());
read_grid_data_template_<IST, colvar_grid_gradient>(
is, "hills_energy_gradients", hills_energy_gradients, hills_energy_gradients_backup);
read_grid_data_template_<IST, colvar_grid_gradient>(is, "hills_energy_gradients",
hills_energy_gradients.get(),
hills_energy_gradients_backup.get());
if (is) {
cvm::log(" successfully read the biasing potential and its gradients from grids.\n");
if (hills_energy_backup != nullptr) {
// Now that we have successfully updated the grids, delete the backup copies
delete hills_energy_backup;
delete hills_energy_gradients_backup;
}
} else {
if (need_backup) {
if (cvm::debug())
cvm::log("Restoring grids from backup for metadynamics bias \"" + this->name + "\"" +
((comm != single_replica) ? ", replica \"" + replica_id + "\"" : "") + ".\n");
// Restoring content from original grid
hills_energy->copy_grid(*hills_energy_backup);
hills_energy_gradients->copy_grid(*hills_energy_gradients_backup);
}
return is;
}
}
@ -1451,10 +1440,12 @@ void colvarbias_meta::rebin_grids_after_restart()
// read from the configuration file), and project onto them the
// grids just read from the restart file
colvar_grid_scalar *new_hills_energy =
new colvar_grid_scalar(colvars);
colvar_grid_gradient *new_hills_energy_gradients =
new colvar_grid_gradient(colvars);
// Create new grids based on the configuration parameters, because reading from the state
// file automatically sets the old parameters
std::shared_ptr<colvar_grid_scalar> new_hills_energy(
new colvar_grid_scalar(colvars, nullptr, false, grid_conf));
std::shared_ptr<colvar_grid_gradient> new_hills_energy_gradients(
new colvar_grid_gradient(colvars, nullptr, new_hills_energy));
if (cvm::debug()) {
std::ostringstream tmp_os;
@ -1468,9 +1459,9 @@ void colvarbias_meta::rebin_grids_after_restart()
if (restart_keep_hills && !hills.empty()) {
// if there are hills, recompute the new grids from them
cvm::log("Rebinning the energy and forces grids from "+
cvm::to_str(hills.size())+" hills (this may take a while)...\n");
project_hills(hills.begin(), hills.end(),
new_hills_energy, new_hills_energy_gradients, true);
cvm::to_str(hills.size())+" hills (this may take a bit)...\n");
project_hills(hills.begin(), hills.end(), new_hills_energy.get(),
new_hills_energy_gradients.get(), true);
cvm::log("rebinning done.\n");
} else {
@ -1481,15 +1472,13 @@ void colvarbias_meta::rebin_grids_after_restart()
new_hills_energy_gradients->map_grid(*hills_energy_gradients);
}
delete hills_energy;
delete hills_energy_gradients;
hills_energy = new_hills_energy;
hills_energy_gradients = new_hills_energy_gradients;
hills_energy = std::move(new_hills_energy);
hills_energy_gradients = std::move(new_hills_energy_gradients);
// assuming that some boundaries have expanded, eliminate those
// off-grid hills that aren't necessary any more
if (!hills.empty())
recount_hills_off_grid(hills.begin(), hills.end(), hills_energy);
recount_hills_off_grid(hills.begin(), hills.end());
}
}
@ -1718,29 +1707,17 @@ int colvarbias_meta::setup_output()
if (comm == multiple_replicas) {
// TODO: one may want to specify the path manually for intricated filesystems?
char *pwd = new char[3001];
if (GETCWD(pwd, 3000) == nullptr) {
if (pwd != nullptr) { //
delete[] pwd;
}
return cvm::error("Error: cannot get the path of the current working directory.\n",
COLVARS_BUG_ERROR);
}
auto const pwd = cvm::main()->proxy->get_current_work_dir();
replica_list_file =
(std::string(pwd)+std::string(PATHSEP)+
this->name+"."+replica_id+".files.txt");
cvm::main()->proxy->join_paths(pwd, this->name + "." + replica_id + ".files.txt");
// replica_hills_file and replica_state_file are those written
// by the current replica; within the mirror biases, they are
// those by another replica
replica_hills_file =
(std::string(pwd)+std::string(PATHSEP)+
cvm::output_prefix()+".colvars."+this->name+"."+replica_id+".hills");
replica_state_file =
(std::string(pwd)+std::string(PATHSEP)+
cvm::output_prefix()+".colvars."+this->name+"."+replica_id+".state");
delete[] pwd;
replica_hills_file = cvm::main()->proxy->join_paths(
pwd, cvm::output_prefix() + ".colvars." + this->name + "." + replica_id + ".hills");
replica_state_file = cvm::main()->proxy->join_paths(
pwd, cvm::output_prefix() + ".colvars." + this->name + "." + replica_id + ".state");
// now register this replica
@ -1842,7 +1819,7 @@ template <typename OST> OST &colvarbias_meta::write_state_data_template_(OST &os
// this is a very good time to project hills, if you haven't done
// it already!
project_hills(new_hills_begin, hills.end(), hills_energy, hills_energy_gradients);
project_hills(new_hills_begin, hills.end(), hills_energy.get(), hills_energy_gradients.get());
new_hills_begin = hills.end();
// write down the grids to the restart file

26
lib/colvars/colvarbias_meta.h
View File

@ -10,12 +10,16 @@
#ifndef COLVARBIAS_META_H
#define COLVARBIAS_META_H
#include <vector>
#include <list>
#include <iosfwd>
#include <list>
#include <memory>
#include <vector>
#include "colvarbias.h"
#include "colvargrid.h"
class colvar_grid_scalar;
class colvar_grid_gradient;
/// Metadynamics bias (implementation of \link colvarbias \endlink)
@ -123,8 +127,7 @@ protected:
hill_iter new_hills_off_grid_begin;
/// Regenerate the hills_off_grid list
void recount_hills_off_grid(hill_iter h_first, hill_iter h_last,
colvar_grid_scalar *ge);
void recount_hills_off_grid(hill_iter h_first, hill_iter h_last);
template <typename OST> OST &write_hill_template_(OST &os, colvarbias_meta::hill const &h);
@ -211,7 +214,7 @@ protected:
bool ebmeta;
/// Target distribution for EBmeta
colvar_grid_scalar* target_dist;
std::unique_ptr<colvar_grid_scalar> target_dist;
/// Number of equilibration steps for EBmeta
cvm::step_number ebmeta_equil_steps;
@ -223,15 +226,14 @@ protected:
bool safely_read_restart;
/// Hill energy, cached on a grid
colvar_grid_scalar *hills_energy;
std::shared_ptr<colvar_grid_scalar> hills_energy;
/// Hill forces, cached on a grid
colvar_grid_gradient *hills_energy_gradients;
std::shared_ptr<colvar_grid_gradient> hills_energy_gradients;
/// \brief Project the selected hills onto grids
void project_hills(hill_iter h_first, hill_iter h_last,
colvar_grid_scalar *ge, colvar_grid_gradient *gf,
bool print_progress = false);
/// Project the selected hills onto grids
void project_hills(hill_iter h_first, hill_iter h_last, colvar_grid_scalar *ge,
colvar_grid_gradient *gf, bool print_progress = false);
// Multiple Replicas variables and functions

1996
lib/colvars/colvarbias_opes.cpp Normal file
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File diff suppressed because it is too large Load Diff

176
lib/colvars/colvarbias_opes.h Normal file
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@ -0,0 +1,176 @@
#ifndef COLVARBIAS_OPES_H
#define COLVARBIAS_OPES_H
// This code is mainly adapted from the PLUMED opes module, which uses the
// LGPLv3 license as shown below:
/* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Copyright (c) 2020-2021 of Michele Invernizzi.
This file is part of the OPES plumed module.
The OPES plumed module is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
The OPES plumed module is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with plumed. If not, see <http://www.gnu.org/licenses/>.
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
#include "colvarbias.h"
#include <vector>
#include <memory>
// OPES_METAD implementation: swiped from OPESmetad.cpp of PLUMED
class colvarbias_opes: public colvarbias {
public:
/// The Gaussian kernel data structure
struct kernel {
cvm::real m_height;
std::vector<cvm::real> m_center;
std::vector<cvm::real> m_sigma;
kernel() {}
kernel(cvm::real h, const std::vector<cvm::real>& c,
const std::vector<cvm::real>& s):
m_height(h), m_center(c), m_sigma(s) {}
};
/// Communication between different replicas
enum Communication {
/// One replica (default)
single_replica,
/// Hills added concurrently by several replicas
multiple_replicas
};
/// Constructor
colvarbias_opes(char const *key);
/// Initializer
int init(std::string const &conf) override;
/// Per-timestep update
int update() override;
/// Save the state to a text file for restarting
std::ostream &write_state_data(std::ostream &os) override;
/// Read the state from a text file for restarting
std::istream &read_state_data(std::istream &is) override;
/// Save the state to a binary file for restarting
cvm::memory_stream &write_state_data(cvm::memory_stream &os) override;
/// Read the state from a binary file for restarting
cvm::memory_stream &read_state_data(cvm::memory_stream &is) override;
/// Write to files at restart steps
int write_output_files() override;
private:
int update_opes();
int calculate_opes();
void save_state();
cvm::real getProbAndDerivatives(const std::vector<cvm::real>& cv, std::vector<cvm::real>& der_prob) const;
cvm::real evaluateKernel(const kernel& G, const std::vector<cvm::real>& x) const;
cvm::real evaluateKernel(const kernel& G, const std::vector<cvm::real>& x, std::vector<cvm::real>& accumulated_derivative, std::vector<cvm::real>& dist) const;
void addKernel(const double height, const std::vector<cvm::real>& center, const std::vector<cvm::real>& sigma, const double logweight);
void addKernel(const double height, const std::vector<cvm::real>& center, const std::vector<cvm::real>& sigma);
size_t getMergeableKernel(const std::vector<cvm::real>& giver_center, const size_t giver_k) const;
void mergeKernels(kernel& k1, const kernel& k2) const;
void updateNlist(const std::vector<cvm::real>& center);
struct traj_line {
double rct;
double zed;
double neff;
double work;
size_t nker;
size_t nlker;
size_t nlsteps;
};
void writeTrajBuffer();
void showInfo() const;
template <typename OST> OST &write_state_data_template_(OST &os) const;
template <typename IST> IST &read_state_data_template_(IST &os);
std::string const traj_file_name(const std::string& suffix) const;
int collectSampleToPMFGrid();
int computePMF();
int writePMF(const std::unique_ptr<colvar_grid_scalar>& pmf_grid, const std::string &filename, bool keep_open);
private:
cvm::real m_kbt;
cvm::real m_barrier;
cvm::real m_biasfactor;
cvm::real m_bias_prefactor;
cvm::real m_temperature;
cvm::step_number m_pace;
cvm::step_number m_adaptive_sigma_stride;
cvm::step_number m_adaptive_counter;
unsigned long long m_counter;
cvm::real m_compression_threshold;
cvm::real m_compression_threshold2;
bool m_adaptive_sigma;
bool m_fixed_sigma;
bool m_no_zed;
// bool m_restart;
bool m_nlist;
bool m_recursive_merge;
std::vector<cvm::real> m_nlist_param;
std::vector<cvm::real> m_sigma0;
std::vector<cvm::real> m_sigma_min;
cvm::real m_epsilon;
cvm::real m_sum_weights;
cvm::real m_sum_weights2;
cvm::real m_cutoff;
cvm::real m_cutoff2;
cvm::real m_zed;
cvm::real m_old_kdenorm;
cvm::real m_kdenorm;
cvm::real m_val_at_cutoff;
cvm::real m_rct;
cvm::real m_neff;
std::vector<kernel> m_kernels;
std::vector<kernel> m_delta_kernels;
std::vector<cvm::real> m_av_cv;
std::vector<cvm::real> m_av_M2;
std::ostringstream m_kernels_output;
std::vector<cvm::real> m_nlist_center;
std::vector<size_t> m_nlist_index;
std::vector<cvm::real> m_nlist_dev2;
size_t m_nlist_steps;
bool m_nlist_update;
bool m_nlist_pace_reset;
size_t m_nker;
bool m_calc_work;
cvm::real m_work;
/// Communication between different replicas
Communication comm;
/// \brief Identifier for this replica
std::string replica_id;
size_t m_num_walkers;
size_t shared_freq;
size_t m_num_threads;
size_t m_nlker;
// size_t m_state_stride;
// std::unordered_map<std::string, std::string> m_kernel_output_components;
std::string m_kernels_output_headers;
cvm::step_number m_traj_output_frequency;
traj_line m_traj_line;
std::ostringstream m_traj_oss;
bool m_is_first_step;
std::vector<cvm::real> m_cv;
// For saving states
decltype(m_zed) m_saved_zed;
decltype(m_sum_weights) m_saved_sum_weights;
decltype(m_sum_weights2) m_saved_sum_weights2;
decltype(m_kernels) m_saved_kernels;
// PMF grid from reweighting
bool m_pmf_grid_on;
std::vector<colvar*> m_pmf_cvs;
std::string grid_conf;
std::shared_ptr<colvar_grid_scalar> m_reweight_grid;
std::unique_ptr<colvar_grid_scalar> m_pmf_grid;
cvm::step_number m_pmf_hist_freq;
bool m_pmf_shared; // shared PMF among replicas
std::unique_ptr<colvar_grid_scalar> m_global_reweight_grid;
std::unique_ptr<colvar_grid_scalar> m_global_pmf_grid;
bool m_explore;
bool m_inf_biasfactor;
};
#endif // COLVARBIAS_OPES_H

9
lib/colvars/colvarcomp.cpp
View File

@ -261,7 +261,6 @@ int colvar::cvc::init_dependencies() {
require_feature_children(f_cvc_explicit_gradient, f_ag_explicit_gradient);
init_feature(f_cvc_inv_gradient, "inverse_gradient", f_type_dynamic);
require_feature_self(f_cvc_inv_gradient, f_cvc_gradient);
init_feature(f_cvc_debug_gradient, "debug_gradient", f_type_user);
require_feature_self(f_cvc_debug_gradient, f_cvc_gradient);
@ -525,7 +524,7 @@ void colvar::cvc::calc_force_invgrads()
void colvar::cvc::calc_Jacobian_derivative()
{
cvm::error("Error: calculation of inverse gradients is not implemented "
cvm::error("Error: calculation of Jacobian derivatives is not implemented "
"for colvar components of type \""+function_type()+"\".\n",
COLVARS_NOT_IMPLEMENTED);
}
@ -533,8 +532,10 @@ void colvar::cvc::calc_Jacobian_derivative()
void colvar::cvc::calc_fit_gradients()
{
for (size_t ig = 0; ig < atom_groups.size(); ig++) {
atom_groups[ig]->calc_fit_gradients();
if (is_enabled(f_cvc_explicit_gradient)) {
for (size_t ig = 0; ig < atom_groups.size(); ig++) {
atom_groups[ig]->calc_fit_gradients();
}
}
}

12
lib/colvars/colvarcomp.h
View File

@ -233,8 +233,14 @@ public:
/// Forcibly set value of CVC - useful for driving an external coordinate,
/// eg. lambda dynamics
inline void set_value(colvarvalue const &new_value) {
inline void set_value(colvarvalue const &new_value, bool now=false) {
x = new_value;
// Cache value to be communicated to back-end between time steps
cvm::proxy->set_alch_lambda(x.real_value);
if (now) {
// If requested (e.g. upon restarting), sync to back-end
cvm::proxy->send_alch_lambda();
}
}
protected:
@ -1212,9 +1218,11 @@ protected:
// No atom groups needed
public:
alch_lambda();
int init_alchemy(int time_step_factor);
virtual ~alch_lambda() {}
virtual void calc_value();
virtual void calc_gradients();
virtual void calc_force_invgrads();
virtual void calc_Jacobian_derivative();
virtual void apply_force(colvarvalue const &force);
};

49
lib/colvars/colvarcomp_alchlambda.cpp
View File

@ -20,22 +20,46 @@ colvar::alch_lambda::alch_lambda()
{
set_function_type("alchLambda");
disable(f_cvc_explicit_gradient);
disable(f_cvc_gradient);
provide(f_cvc_explicit_gradient, false);
provide(f_cvc_gradient, false); // Cannot apply forces on this CVC
provide(f_cvc_collect_atom_ids, false);
provide(f_cvc_inv_gradient); // Projected force is TI derivative
provide(f_cvc_Jacobian); // Zero
x.type(colvarvalue::type_scalar);
// Query initial value from back-end
// Query initial value from back-end; will be overwritten if restarting from a state file
cvm::proxy->get_alch_lambda(&x.real_value);
}
int colvar::alch_lambda::init_alchemy(int factor)
{
// We need calculation every time step
// default in Tinker-HP and NAMD2, must be enforced in NAMD3
// Also checks back-end settings, ie. that alchemy is enabled
// (in NAMD3: alchType TI, computeEnergies at the right frequency)
// Forbid MTS until fully implemented
if (factor != 1) {
return cvm::error("Error: timeStepFactor > 1 is not yet supported for alchemical variables.");
}
cvm::proxy->request_alch_energy_freq(factor);
return COLVARS_OK;
}
void colvar::alch_lambda::calc_value()
{
// Special workflow:
// at the beginning of the timestep we get a force instead of calculating the value
// By default, follow external parameter
// This might get overwritten by driving extended dynamics
// (in apply_force() below)
cvm::proxy->get_alch_lambda(&x.real_value);
cvm::proxy->get_dE_dlambda(&ft.real_value);
ft.real_value *= -1.0; // Energy derivative to force
ft.real_value *= -1.0; // Convert energy derivative to force
// Include any force due to bias on Flambda
ft.real_value += cvm::proxy->indirect_lambda_biasing_force;
@ -43,19 +67,24 @@ void colvar::alch_lambda::calc_value()
}
void colvar::alch_lambda::calc_gradients()
void colvar::alch_lambda::calc_force_invgrads()
{
// All the work is done in calc_value()
}
void colvar::alch_lambda::calc_Jacobian_derivative()
{
jd = 0.0;
}
void colvar::alch_lambda::apply_force(colvarvalue const & /* force */)
{
// new value will be cached and sent at end of timestep
cvm::proxy->set_alch_lambda(x.real_value);
// Forces, if any, are applied in colvar::update_extended_Lagrangian()
}
colvar::alch_Flambda::alch_Flambda()
{
set_function_type("alch_Flambda");

76
lib/colvars/colvarcomp_angles.cpp
View File

@ -267,74 +267,22 @@ void colvar::dihedral::calc_value()
void colvar::dihedral::calc_gradients()
{
cvm::rvector A = cvm::rvector::outer(r12, r23);
cvm::real rA = A.norm();
cvm::rvector B = cvm::rvector::outer(r23, r34);
cvm::real rB = B.norm();
cvm::rvector C = cvm::rvector::outer(r23, A);
cvm::real rC = C.norm();
// Eqs. (27i) ~ (27l) from https://doi.org/10.1002/(SICI)1096-987X(19960715)17:9<1132::AID-JCC5>3.0.CO;2-T.
cvm::real const cos_phi = (A*B)/(rA*rB);
cvm::real const sin_phi = (C*B)/(rC*rB);
const cvm::rvector A = cvm::rvector::outer(r12, r23);
const cvm::rvector B = cvm::rvector::outer(r23, r34);
const cvm::real nG = r23.norm();
const cvm::real A2 = A.norm2();
const cvm::real B2 = B.norm2();
cvm::rvector f1, f2, f3;
rB = 1.0/rB;
B *= rB;
if (cvm::fabs(sin_phi) > 0.1) {
rA = 1.0/rA;
A *= rA;
cvm::rvector const dcosdA = rA*(cos_phi*A-B);
cvm::rvector const dcosdB = rB*(cos_phi*B-A);
// rA = 1.0;
cvm::real const K = (1.0/sin_phi) * (180.0/PI);
f1 = K * cvm::rvector::outer(r23, dcosdA);
f3 = K * cvm::rvector::outer(dcosdB, r23);
f2 = K * (cvm::rvector::outer(dcosdA, r12)
+ cvm::rvector::outer(r34, dcosdB));
}
else {
rC = 1.0/rC;
C *= rC;
cvm::rvector const dsindC = rC*(sin_phi*C-B);
cvm::rvector const dsindB = rB*(sin_phi*B-C);
// rC = 1.0;
cvm::real const K = (-1.0/cos_phi) * (180.0/PI);
f1.x = K*((r23.y*r23.y + r23.z*r23.z)*dsindC.x
- r23.x*r23.y*dsindC.y
- r23.x*r23.z*dsindC.z);
f1.y = K*((r23.z*r23.z + r23.x*r23.x)*dsindC.y
- r23.y*r23.z*dsindC.z
- r23.y*r23.x*dsindC.x);
f1.z = K*((r23.x*r23.x + r23.y*r23.y)*dsindC.z
- r23.z*r23.x*dsindC.x
- r23.z*r23.y*dsindC.y);
f3 = cvm::rvector::outer(dsindB, r23);
f3 *= K;
f2.x = K*(-(r23.y*r12.y + r23.z*r12.z)*dsindC.x
+(2.0*r23.x*r12.y - r12.x*r23.y)*dsindC.y
+(2.0*r23.x*r12.z - r12.x*r23.z)*dsindC.z
+dsindB.z*r34.y - dsindB.y*r34.z);
f2.y = K*(-(r23.z*r12.z + r23.x*r12.x)*dsindC.y
+(2.0*r23.y*r12.z - r12.y*r23.z)*dsindC.z
+(2.0*r23.y*r12.x - r12.y*r23.x)*dsindC.x
+dsindB.x*r34.z - dsindB.z*r34.x);
f2.z = K*(-(r23.x*r12.x + r23.y*r12.y)*dsindC.z
+(2.0*r23.z*r12.x - r12.z*r23.x)*dsindC.x
+(2.0*r23.z*r12.y - r12.z*r23.y)*dsindC.y
+dsindB.y*r34.x - dsindB.x*r34.y);
}
const cvm::real K = 180.0/PI;
const cvm::rvector f1 = K * nG / A2 * A;
const cvm::rvector f2 = K * ((r12 * r23 / (A2 * nG)) * A + (r34 * r23 / (B2 * nG)) * B);
const cvm::rvector f3 = K * nG / B2 * B;
group1->set_weighted_gradient(-f1);
group2->set_weighted_gradient(-f2 + f1);
group3->set_weighted_gradient(-f3 + f2);
group2->set_weighted_gradient( f2 + f1);
group3->set_weighted_gradient(-f3 - f2);
group4->set_weighted_gradient(f3);
}

33
lib/colvars/colvarcomp_distances.cpp
View File

@ -384,32 +384,30 @@ void colvar::distance_dir::apply_force(colvarvalue const &force)
cvm::real const iprod = force.rvector_value * x.rvector_value;
cvm::rvector const force_tang = force.rvector_value - iprod * x.rvector_value;
if (!group1->noforce)
group1->apply_force(-1.0 * force_tang);
if (!group2->noforce)
group2->apply_force( force_tang);
if (!group1->noforce) {
group1->apply_force(-1.0 / dist_v.norm() * force_tang);
}
if (!group2->noforce) {
group2->apply_force( 1.0 / dist_v.norm() * force_tang);
}
}
cvm::real colvar::distance_dir::dist2(colvarvalue const &x1,
colvarvalue const &x2) const
cvm::real colvar::distance_dir::dist2(colvarvalue const &x1, colvarvalue const &x2) const
{
return (x1.rvector_value - x2.rvector_value).norm2();
return x1.dist2(x2);
}
colvarvalue colvar::distance_dir::dist2_lgrad(colvarvalue const &x1,
colvarvalue const &x2) const
colvarvalue colvar::distance_dir::dist2_lgrad(colvarvalue const &x1, colvarvalue const &x2) const
{
return colvarvalue((x1.rvector_value - x2.rvector_value), colvarvalue::type_unit3vectorderiv);
return x1.dist2_grad(x2);
}
colvarvalue colvar::distance_dir::dist2_rgrad(colvarvalue const &x1,
colvarvalue const &x2) const
colvarvalue colvar::distance_dir::dist2_rgrad(colvarvalue const &x1, colvarvalue const &x2) const
{
return colvarvalue((x2.rvector_value - x1.rvector_value), colvarvalue::type_unit3vectorderiv);
return x2.dist2_grad(x1);
}
@ -1005,7 +1003,7 @@ void colvar::rmsd::calc_Jacobian_derivative()
for (size_t ia = 0; ia < atoms->size(); ia++) {
// Gradient of optimal quaternion wrt current Cartesian position
atoms->rot_deriv->calc_derivative_wrt_group1(ia, nullptr, &dq);
atoms->rot_deriv->calc_derivative_wrt_group1<false, true, false>(ia, nullptr, &dq);
g11 = 2.0 * (atoms->rot.q)[1]*dq[1];
g22 = 2.0 * (atoms->rot.q)[2]*dq[2];
@ -1304,7 +1302,7 @@ void colvar::eigenvector::calc_Jacobian_derivative()
// Gradient of optimal quaternion wrt current Cartesian position
// trick: d(R^-1)/dx = d(R^t)/dx = (dR/dx)^t
// we can just transpose the derivatives of the direct matrix
atoms->rot_deriv->calc_derivative_wrt_group1(ia, nullptr, &dq_1);
atoms->rot_deriv->calc_derivative_wrt_group1<false, true, false>(ia, nullptr, &dq_1);
g11 = 2.0 * quat0[1]*dq_1[1];
g22 = 2.0 * quat0[2]*dq_1[2];
@ -1403,11 +1401,12 @@ void colvar::cartesian::apply_force(colvarvalue const &force)
size_t ia, j;
if (!atoms->noforce) {
cvm::rvector f;
auto ag_force = atoms->get_group_force_object();
for (ia = 0; ia < atoms->size(); ia++) {
for (j = 0; j < dim; j++) {
f[axes[j]] = force.vector1d_value[dim*ia + j];
}
(*atoms)[ia].apply_force(f);
ag_force.add_atom_force(ia, f);
}
}
}

203
lib/colvars/colvarcomp_protein.cpp
View File

@ -28,34 +28,58 @@ colvar::alpha_angles::alpha_angles()
int colvar::alpha_angles::init(std::string const &conf)
{
int error_code = cvc::init(conf);
if (error_code != COLVARS_OK) return error_code;
std::string segment_id;
get_keyval(conf, "psfSegID", segment_id, std::string("MAIN"));
std::vector<int> residues;
{
std::string residues_conf = "";
key_lookup(conf, "residueRange", &residues_conf);
bool b_use_index_groups = false;
cvm::atom_group group_CA, group_N, group_O;
std::string residues_conf = "";
std::string prefix;
// residueRange is mandatory for the topology-based case
if (key_lookup(conf, "residueRange", &residues_conf)) {
if (residues_conf.size()) {
std::istringstream is(residues_conf);
int initial, final;
char dash;
if ( (is >> initial) && (initial > 0) &&
(is >> dash) && (dash == '-') &&
(is >> final) && (final > 0) ) {
(is >> dash) && (dash == '-') &&
(is >> final) && (final > 0) ) {
for (int rnum = initial; rnum <= final; rnum++) {
residues.push_back(rnum);
}
}
} else {
error_code |=
cvm::error("Error: no residues defined in \"residueRange\".\n", COLVARS_INPUT_ERROR);
return cvm::error("Error: no residues defined in \"residueRange\".\n", COLVARS_INPUT_ERROR);
}
}
if (residues.size() < 5) {
error_code |= cvm::error("Error: not enough residues defined in \"residueRange\".\n",
COLVARS_INPUT_ERROR);
if (residues.size() < 5) {
return cvm::error("Error: not enough residues defined in \"residueRange\".\n", COLVARS_INPUT_ERROR);
}
get_keyval(conf, "psfSegID", segment_id, std::string("MAIN"));
} else {
b_use_index_groups = true;
get_keyval(conf, "prefix", prefix, "alpha_");
// Not all groups are mandatory, parse silently
group_CA.add_index_group(prefix + "CA", true);
group_N.add_index_group(prefix + "N", true);
group_O.add_index_group(prefix + "O", true);
int na = group_CA.size();
int nn = group_N.size();
int no = group_O.size();
if ((nn != 0 || no != 0) && (nn != no)) {
return cvm::error("Error: If either is provided, atom groups " + prefix + "N and " + prefix + "O must have the same number of atoms.",
COLVARS_INPUT_ERROR);
}
if (nn != 0 && na != 0 && nn != na) {
return cvm::error("Error: If both are provided, atom groups " + prefix + "N and " + prefix + "CA must have the same number of atoms.",
COLVARS_INPUT_ERROR);
}
}
std::string const &sid = segment_id;
@ -64,8 +88,7 @@ int colvar::alpha_angles::init(std::string const &conf)
get_keyval(conf, "hBondCoeff", hb_coeff, hb_coeff);
if ((hb_coeff < 0.0) || (hb_coeff > 1.0)) {
error_code |=
cvm::error("Error: hBondCoeff must be defined between 0 and 1.\n", COLVARS_INPUT_ERROR);
return cvm::error("Error: hBondCoeff must be defined between 0 and 1.\n", COLVARS_INPUT_ERROR);
}
@ -73,14 +96,29 @@ int colvar::alpha_angles::init(std::string const &conf)
get_keyval(conf, "angleTol", theta_tol, theta_tol);
if (hb_coeff < 1.0) {
for (size_t i = 0; i < residues.size()-2; i++) {
theta.push_back(new colvar::angle(cvm::atom(r[i ], "CA", sid),
cvm::atom(r[i+1], "CA", sid),
cvm::atom(r[i+2], "CA", sid)));
register_atom_group(theta.back()->atom_groups[0]);
register_atom_group(theta.back()->atom_groups[1]);
register_atom_group(theta.back()->atom_groups[2]);
if (b_use_index_groups) {
if (group_CA.size() < 5) {
return cvm::error("Not enough atoms (" + cvm::to_str(group_CA.size()) + ") in index group \"" + prefix + "CA\"",
COLVARS_INPUT_ERROR);
}
for (size_t i = 0; i < group_CA.size()-2; i++) {
// Note: the angle constructor constructs copies of the atom objects
theta.push_back(new colvar::angle(group_CA[i],
group_CA[i+1],
group_CA[i+2]));
register_atom_group(theta.back()->atom_groups[0]);
register_atom_group(theta.back()->atom_groups[1]);
register_atom_group(theta.back()->atom_groups[2]);
}
} else {
for (size_t i = 0; i < residues.size()-2; i++) {
theta.push_back(new colvar::angle(cvm::atom(r[i ], "CA", sid),
cvm::atom(r[i+1], "CA", sid),
cvm::atom(r[i+2], "CA", sid)));
register_atom_group(theta.back()->atom_groups[0]);
register_atom_group(theta.back()->atom_groups[1]);
register_atom_group(theta.back()->atom_groups[2]);
}
}
} else {
@ -93,14 +131,27 @@ int colvar::alpha_angles::init(std::string const &conf)
get_keyval(conf, "hBondExpDenom", ed, ed);
if (hb_coeff > 0.0) {
for (size_t i = 0; i < residues.size()-4; i++) {
hb.push_back(new colvar::h_bond(cvm::atom(r[i ], "O", sid),
cvm::atom(r[i+4], "N", sid),
r0, en, ed));
register_atom_group(hb.back()->atom_groups[0]);
if (b_use_index_groups) {
if (group_N.size() < 5) {
return cvm::error("Not enough atoms (" + cvm::to_str(group_N.size()) + ") in index group \"" + prefix + "N\"",
COLVARS_INPUT_ERROR);
}
for (size_t i = 0; i < group_N.size()-4; i++) {
// Note: we need to call the atom copy constructor here because
// the h_bond constructor does not make copies of the provided atoms
hb.push_back(new colvar::h_bond(cvm::atom(group_O[i]),
cvm::atom(group_N[i+4]),
r0, en, ed));
register_atom_group(hb.back()->atom_groups[0]);
}
} else {
for (size_t i = 0; i < residues.size()-4; i++) {
hb.push_back(new colvar::h_bond(cvm::atom(r[i ], "O", sid),
cvm::atom(r[i+4], "N", sid),
r0, en, ed));
register_atom_group(hb.back()->atom_groups[0]);
}
}
} else {
cvm::log("The hBondCoeff specified will disable the hydrogen bond terms.\n");
}
@ -290,41 +341,62 @@ int colvar::dihedPC::init(std::string const &conf)
if (cvm::debug())
cvm::log("Initializing dihedral PC object.\n");
bool b_use_index_groups = false;
std::string segment_id;
get_keyval(conf, "psfSegID", segment_id, std::string("MAIN"));
std::vector<int> residues;
{
std::string residues_conf = "";
key_lookup(conf, "residueRange", &residues_conf);
size_t n_residues;
std::string residues_conf = "";
std::string prefix;
cvm::atom_group group_CA, group_N, group_C;
// residueRange is mandatory for the topology-based case
if (key_lookup(conf, "residueRange", &residues_conf)) {
if (residues_conf.size()) {
std::istringstream is(residues_conf);
int initial, final;
char dash;
if ( (is >> initial) && (initial > 0) &&
(is >> dash) && (dash == '-') &&
(is >> final) && (final > 0) ) {
(is >> dash) && (dash == '-') &&
(is >> final) && (final > 0) ) {
for (int rnum = initial; rnum <= final; rnum++) {
residues.push_back(rnum);
}
}
} else {
error_code |=
cvm::error("Error: no residues defined in \"residueRange\".\n", COLVARS_INPUT_ERROR);
return cvm::error("Error: no residues defined in \"residueRange\".\n", COLVARS_INPUT_ERROR);
}
}
n_residues = residues.size();
get_keyval(conf, "psfSegID", segment_id, std::string("MAIN"));
if (residues.size() < 2) {
} else {
b_use_index_groups = true;
get_keyval(conf, "prefix", prefix, "dihed_");
// All three groups are required
group_CA.add_index_group(prefix + "CA");
group_N.add_index_group(prefix + "N");
group_C.add_index_group(prefix + "C");
int na = group_CA.size();
int nn = group_N.size();
int nc = group_C.size();
if ((nn != na || na != nc)) {
return cvm::error("Error: atom groups " + prefix + "N, " + prefix + "CA, and " + prefix +
"C must have the same number of atoms.", COLVARS_INPUT_ERROR);
}
n_residues = nn;
}
if (n_residues < 2) {
error_code |=
cvm::error("Error: dihedralPC requires at least two residues.\n", COLVARS_INPUT_ERROR);
cvm::error("Error: dihedralPC requires at least two residues.\n", COLVARS_INPUT_ERROR);
}
std::string const &sid = segment_id;
std::vector<int> const &r = residues;
std::string vecFileName;
int vecNumber;
if (get_keyval(conf, "vectorFile", vecFileName, vecFileName)) {
int vecNumber;
get_keyval(conf, "vectorNumber", vecNumber, 0);
if (vecNumber < 1) {
error_code |=
@ -339,9 +411,8 @@ int colvar::dihedPC::init(std::string const &conf)
}
// TODO: adapt to different formats by setting this flag
bool eigenvectors_as_columns = true;
if (eigenvectors_as_columns) {
// bool eigenvectors_as_columns = true;
// if (eigenvectors_as_columns) {
// Carma-style dPCA file
std::string line;
cvm::real c;
@ -352,9 +423,7 @@ int colvar::dihedPC::init(std::string const &conf)
for (int i=0; i<vecNumber; i++) ls >> c;
coeffs.push_back(c);
}
}
/* TODO Uncomment this when different formats are recognized
else {
/* } else { // Uncomment this when different formats are recognized
// Eigenvectors as lines
// Skip to the right line
for (int i = 1; i<vecNumber; i++)
@ -380,28 +449,42 @@ int colvar::dihedPC::init(std::string const &conf)
get_keyval(conf, "vector", coeffs, coeffs);
}
if ( coeffs.size() != 4 * (residues.size() - 1)) {
if ( coeffs.size() != 4 * (n_residues - 1)) {
error_code |= cvm::error("Error: wrong number of coefficients: " + cvm::to_str(coeffs.size()) +
". Expected " + cvm::to_str(4 * (residues.size() - 1)) +
". Expected " + cvm::to_str(4 * (n_residues - 1)) +
" (4 coeffs per residue, minus one residue).\n",
COLVARS_INPUT_ERROR);
}
for (size_t i = 0; i < residues.size()-1; i++) {
for (size_t i = 0; i < n_residues-1; i++) {
// Psi
theta.push_back(new colvar::dihedral(cvm::atom(r[i ], "N", sid),
cvm::atom(r[i ], "CA", sid),
cvm::atom(r[i ], "C", sid),
cvm::atom(r[i+1], "N", sid)));
if (b_use_index_groups) {
theta.push_back(new colvar::dihedral( group_N[i],
group_CA[i],
group_C[i],
group_N[i+1]));
} else {
theta.push_back(new colvar::dihedral(cvm::atom(r[i ], "N", sid),
cvm::atom(r[i ], "CA", sid),
cvm::atom(r[i ], "C", sid),
cvm::atom(r[i+1], "N", sid)));
}
register_atom_group(theta.back()->atom_groups[0]);
register_atom_group(theta.back()->atom_groups[1]);
register_atom_group(theta.back()->atom_groups[2]);
register_atom_group(theta.back()->atom_groups[3]);
// Phi (next res)
theta.push_back(new colvar::dihedral(cvm::atom(r[i ], "C", sid),
cvm::atom(r[i+1], "N", sid),
cvm::atom(r[i+1], "CA", sid),
cvm::atom(r[i+1], "C", sid)));
if (b_use_index_groups) {
theta.push_back(new colvar::dihedral(group_C[i],
group_N[i+1],
group_CA[i+1],
group_C[i+1]));
} else {
theta.push_back(new colvar::dihedral(cvm::atom(r[i ], "C", sid),
cvm::atom(r[i+1], "N", sid),
cvm::atom(r[i+1], "CA", sid),
cvm::atom(r[i+1], "C", sid)));
}
register_atom_group(theta.back()->atom_groups[0]);
register_atom_group(theta.back()->atom_groups[1]);
register_atom_group(theta.back()->atom_groups[2]);

25
lib/colvars/colvarcomp_rotations.cpp
View File

@ -137,11 +137,14 @@ void colvar::orientation::apply_force(colvarvalue const &force)
if (!atoms->noforce) {
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
auto ag_force = atoms->get_group_force_object();
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
for (size_t i = 0; i < 4; i++) {
(*atoms)[ia].apply_force(FQ[i] * dq0_2[i]);
}
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
const auto f_ia = FQ[0] * dq0_2[0] +
FQ[1] * dq0_2[1] +
FQ[2] * dq0_2[2] +
FQ[3] * dq0_2[3];
ag_force.add_atom_force(ia, f_ia);
}
}
}
@ -205,7 +208,7 @@ void colvar::orientation_angle::calc_gradients()
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
(*atoms)[ia].grad = (dxdq0 * dq0_2[0]);
}
}
@ -265,7 +268,7 @@ void colvar::orientation_proj::calc_gradients()
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
(*atoms)[ia].grad = (dxdq0 * dq0_2[0]);
}
}
@ -314,7 +317,7 @@ void colvar::tilt::calc_gradients()
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
(*atoms)[ia].grad = cvm::rvector(0.0, 0.0, 0.0);
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
for (size_t iq = 0; iq < 4; iq++) {
(*atoms)[ia].grad += (dxdq[iq] * dq0_2[iq]);
}
@ -351,7 +354,7 @@ void colvar::spin_angle::calc_gradients()
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
(*atoms)[ia].grad = cvm::rvector(0.0, 0.0, 0.0);
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
for (size_t iq = 0; iq < 4; iq++) {
(*atoms)[ia].grad += (dxdq[iq] * dq0_2[iq]);
}
@ -399,7 +402,7 @@ void colvar::euler_phi::calc_gradients()
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
(*atoms)[ia].grad = (dxdq0 * dq0_2[0]) +
(dxdq1 * dq0_2[1]) +
(dxdq2 * dq0_2[2]) +
@ -448,7 +451,7 @@ void colvar::euler_psi::calc_gradients()
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
(*atoms)[ia].grad = (dxdq0 * dq0_2[0]) +
(dxdq1 * dq0_2[1]) +
(dxdq2 * dq0_2[2]) +
@ -495,7 +498,7 @@ void colvar::euler_theta::calc_gradients()
rot_deriv_impl->prepare_derivative(rotation_derivative_dldq::use_dq);
cvm::vector1d<cvm::rvector> dq0_2;
for (size_t ia = 0; ia < atoms->size(); ia++) {
rot_deriv_impl->calc_derivative_wrt_group2(ia, nullptr, &dq0_2);
rot_deriv_impl->calc_derivative_wrt_group2<false, true, false>(ia, nullptr, &dq0_2);
(*atoms)[ia].grad = (dxdq0 * dq0_2[0]) +
(dxdq1 * dq0_2[1]) +
(dxdq2 * dq0_2[2]) +

233
lib/colvars/colvarcomp_torchann.cpp Normal file
View File

@ -0,0 +1,233 @@
// -*- c++ -*-
// This file is part of the Collective Variables module (Colvars).
// The original version of Colvars and its updates are located at:
// https://github.com/Colvars/colvars
// Please update all Colvars source files before making any changes.
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
#include "colvar.h"
#include "colvarcomp.h"
#include "colvarmodule.h"
#include "colvarparse.h"
#include "colvarvalue.h"
#include "colvarcomp_torchann.h"
#ifdef COLVARS_TORCH
colvar::torchANN::torchANN()
{
set_function_type("torchANN");
provide(f_cvc_periodic);
}
colvar::torchANN::~torchANN() {}
int colvar::torchANN::init(std::string const &conf) {
int error_code = linearCombination::init(conf);
std::string model_file ;
get_keyval(conf, "modelFile", model_file, std::string(""));
try {
nn = torch::jit::load(model_file);
nn.to(torch::kCPU);
cvm::log("torch model loaded.") ;
} catch (const std::exception & e) {
return cvm::error("Error: couldn't load libtorch model (see below).\n" + cvm::to_str(e.what()),
COLVARS_INPUT_ERROR);
}
auto const legacy_keyword = get_keyval(conf, "m_output_index", m_output_index, m_output_index);
if (legacy_keyword) {
cvm::log("Warning: m_output_index is a deprecated keyword, please use output_component instead.\n");
}
get_keyval(conf, "output_component", m_output_index, m_output_index);
get_keyval(conf, "doubleInputTensor", use_double_input, use_double_input);
//get_keyval(conf, "useGPU", use_gpu, false);
cvc_indices.resize(cv.size(),0);
size_t num_inputs = 0;
// compute total number of inputs of neural network
for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv)
{
num_inputs += cv[i_cv]->value().size() ;
if (i_cv < cv.size() - 1)
cvc_indices[i_cv+1] = num_inputs;
}
cvm::log("Input dimension of model: " + cvm::to_str(num_inputs));
// initialize the input tensor
auto options = torch::TensorOptions().dtype(torch::kFloat32).requires_grad(true);
/*
if (use_gpu) {
if (torch::cuda::is_available()) {
try {
nn.to(torch::kCUDA);
} catch(const std::exception & e) {
cvm::error("Failed to move model to GPU.");
use_gpu = false;
}
} else {
use_gpu = false;
cvm::log("GPU not available.");
}
}
if (use_gpu) {
options = options.device(torch::kCUDA);
if (use_double_input) {
cvm::log("Data type reset to Float for GPU computation!");
use_double_input = false;
}
}
*/
if (use_double_input) { // set type to double
options = options.dtype(torch::kFloat64);
nn.to(torch::kFloat64);
cvm::log("Model's dtype: kFloat64.");
} else {
cvm::log("Model's dtype: kFloat32.");
}
input_tensor = torch::zeros({1,(long int) num_inputs}, options);
try { // test the model
std::vector<torch::jit::IValue> inputs={input_tensor};
nn_outputs = nn.forward(inputs).toTensor()[0][m_output_index];
cvm::log("Evaluating model with zero tensor succeeded.");
} catch (const std::exception & e) {
error_code |= cvm::error("Error: evaluating model with zero tensor failed (see below).\n" +
cvm::to_str(e.what()),
COLVARS_INPUT_ERROR);
}
return error_code;
}
void colvar::torchANN::calc_value() {
for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv)
cv[i_cv]->calc_value();
/*
if (use_gpu)
input_tensor = input_tensor.to(torch::kCPU);
*/
// set input tensor with no_grad
{
torch::NoGradGuard no_grad;
size_t l = 0;
for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) {
const colvarvalue& current_cv_value = cv[i_cv]->value();
if (current_cv_value.type() == colvarvalue::type_scalar) {
input_tensor[0][l++] = cv[i_cv]->sup_coeff * (cvm::pow(current_cv_value.real_value, cv[i_cv]->sup_np));
} else {
for (size_t j_elem = 0; j_elem < current_cv_value.size(); ++j_elem)
input_tensor[0][l++] = cv[i_cv]->sup_coeff * current_cv_value[j_elem];
}
}
}
/*
if (use_gpu)
input_tensor = input_tensor.to(torch::kCUDA);
*/
std::vector<torch::jit::IValue> inputs={input_tensor};
// evaluate the value of function
nn_outputs = nn.forward(inputs).toTensor()[0][m_output_index];
input_grad = torch::autograd::grad({nn_outputs}, {input_tensor})[0][0];
/*
if (use_gpu)
input_grad = input_grad.to(torch::kCPU);
*/
x = nn_outputs.item<double>() ;
this->wrap(x);
}
void colvar::torchANN::calc_gradients() {
for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) {
cv[i_cv]->calc_gradients();
if (cv[i_cv]->is_enabled(f_cvc_explicit_gradient)) {
const cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv);
// get the initial index of this cvc
size_t l = cvc_indices[i_cv];
for (size_t j_elem = 0; j_elem < cv[i_cv]->value().size(); ++j_elem) {
// get derivative of neural network wrt its input
const cvm::real factor = input_grad[l+j_elem].item<double>();
for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) {
for (size_t l_atom = 0; l_atom < (cv[i_cv]->atom_groups)[k_ag]->size(); ++l_atom) {
(*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad = factor_polynomial * factor * (*(cv[i_cv]->atom_groups)[k_ag])[l_atom].grad;
}
}
}
}
}
}
void colvar::torchANN::apply_force(colvarvalue const &force) {
for (size_t i_cv = 0; i_cv < cv.size(); ++i_cv) {
// If this CV uses explicit gradients, then atomic gradients is already calculated
// We can apply the force to atom groups directly
if (cv[i_cv]->is_enabled(f_cvc_explicit_gradient)) {
for (size_t k_ag = 0 ; k_ag < cv[i_cv]->atom_groups.size(); ++k_ag) {
(cv[i_cv]->atom_groups)[k_ag]->apply_colvar_force(force.real_value);
}
} else {
const colvarvalue& current_cv_value = cv[i_cv]->value();
colvarvalue cv_force(current_cv_value);
cv_force.reset();
const cvm::real factor_polynomial = getPolynomialFactorOfCVGradient(i_cv);
// get the initial index of this cvc
size_t l = cvc_indices[i_cv];
for (size_t j_elem = 0; j_elem < current_cv_value.size(); ++j_elem) {
cv_force[j_elem] = factor_polynomial * input_grad[l+j_elem].item<double>() * force.real_value;
}
cv[i_cv]->apply_force(cv_force);
}
}
}
#else
colvar::torchANN::torchANN()
{
set_function_type("torchANN");
}
colvar::torchANN::~torchANN() {}
int colvar::torchANN::init(std::string const &conf) {
return cvm::error(
"torchANN requires the libtorch library, but it is not enabled during compilation.\n"
"Please refer to the Compilation Notes section of the Colvars manual for more "
"information.\n",
COLVARS_NOT_IMPLEMENTED);
}
void colvar::torchANN::calc_value()
{
}
#endif

63
lib/colvars/colvarcomp_torchann.h Normal file
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@ -0,0 +1,63 @@
// -*- c++ -*-
// This file is part of the Collective Variables module (Colvars).
// The original version of Colvars and its updates are located at:
// https://github.com/Colvars/colvars
// Please update all Colvars source files before making any changes.
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
//
#ifndef COLVARCOMP_TORCH_H
#define COLVARCOMP_TORCH_H
// Declaration of torchann
#include <memory>
#include "colvar.h"
#include "colvarcomp.h"
#include "colvarmodule.h"
#ifdef COLVARS_TORCH
#include <torch/torch.h>
#include <torch/script.h>
class colvar::torchANN
: public colvar::linearCombination
{
protected:
torch::jit::script::Module nn;
/// the index of nn output component
size_t m_output_index = 0;
bool use_double_input = false;
//bool use_gpu;
// 1d tensor, concatenation of values of sub-cvcs
torch::Tensor input_tensor;
torch::Tensor nn_outputs;
torch::Tensor input_grad;
// record the initial index of of sub-cvcs in input_tensor
std::vector<int> cvc_indices;
public:
torchANN();
virtual ~torchANN();
virtual int init(std::string const &conf);
virtual void calc_value();
virtual void calc_gradients();
virtual void apply_force(colvarvalue const &force);
};
#else
class colvar::torchANN
: public colvar::cvc
{
public:
torchANN();
virtual ~torchANN();
virtual int init(std::string const &conf);
virtual void calc_value();
};
#endif // COLVARS_TORCH checking
#endif

46
lib/colvars/colvardeps.cpp
View File

@ -92,6 +92,8 @@ void colvardeps::restore_children_deps() {
void colvardeps::provide(int feature_id, bool truefalse) {
feature_states[feature_id].available = truefalse;
// Make sure that we don't leave this feature enabled
if (!truefalse) disable(feature_id);
}
@ -123,8 +125,9 @@ bool colvardeps::get_keyval_feature(colvarparse *cvp,
int colvardeps::enable(int feature_id,
bool dry_run /* default: false */,
bool toplevel /* default: true */)
bool dry_run /* default: false */,
bool toplevel /* default: true */,
bool error /*default: false */)
{
int res;
size_t i, j;
@ -137,9 +140,12 @@ int colvardeps::enable(int feature_id,
feature *f = features()[feature_id];
feature_state *fs = &feature_states[feature_id];
// dry_run can be true because parent object is not active, yet we are displaying an error message
// then error is set to true
if (cvm::debug()) {
cvm::log("DEPS: " + description +
(dry_run ? " testing " : " enabling ") +
(dry_run ? " testing " : " enabling ") + (error ? " [error] " : "") +
"\"" + f->description +"\"\n");
}
@ -159,7 +165,7 @@ int colvardeps::enable(int feature_id,
(is_dynamic(feature_id) ? "Dynamic" : "User-controlled");
if (!fs->available) {
if (!dry_run) {
if (!dry_run || error) {
if (toplevel) {
cvm::error("Error: " + feature_type_descr + " feature unavailable: \""
+ f->description + "\" in " + description + ".\n");
@ -172,7 +178,7 @@ int colvardeps::enable(int feature_id,
}
if (!toplevel && !is_dynamic(feature_id)) {
if (!dry_run) {
if (!dry_run || error) {
cvm::log(feature_type_descr + " feature \"" + f->description
+ "\" cannot be enabled automatically in " + description + ".\n");
if (is_user(feature_id)) {
@ -189,7 +195,7 @@ int colvardeps::enable(int feature_id,
if (cvm::debug())
cvm::log(f->description + " requires exclude " + g->description + "\n");
if (is_enabled(f->requires_exclude[i])) {
if (!dry_run) {
if (!dry_run || error) {
cvm::log("Feature \"" + f->description + "\" is incompatible with \""
+ g->description + "\" in " + description + ".\n");
if (toplevel) {
@ -204,10 +210,14 @@ int colvardeps::enable(int feature_id,
for (i=0; i<f->requires_self.size(); i++) {
if (cvm::debug())
cvm::log(f->description + " requires self " + features()[f->requires_self[i]]->description + "\n");
res = enable(f->requires_self[i], dry_run, false);
res = enable(f->requires_self[i], dry_run, false, error);
if (res != COLVARS_OK) {
if (!dry_run) {
cvm::log("...required by \"" + f->description + "\" in " + description + "\n");
if (!dry_run || error) {
if (toplevel) {
cvm::log("Cannot enable \"" + f->description + "\" in " + description + "\n");
} else {
cvm::log("...required by \"" + f->description + "\" in " + description + "\n");
}
if (toplevel) {
cvm::error("Error: Failed dependency in " + description + ".\n");
}
@ -225,11 +235,11 @@ int colvardeps::enable(int feature_id,
int g = f->requires_alt[i][j];
if (cvm::debug())
cvm::log(f->description + " requires alt " + features()[g]->description + "\n");
res = enable(g, true, false); // see if available
res = enable(g, true, false, error); // see if available
if (res == COLVARS_OK) {
ok = true;
if (!dry_run) {
enable(g, false, false); // Require again, for real
if (!dry_run || error) {
enable(g, false, false, error); // Require again, for real
fs->alternate_refs.push_back(g); // We remember we enabled this
// so we can free it if this feature gets disabled
}
@ -245,7 +255,7 @@ int colvardeps::enable(int feature_id,
for (j=0; j<f->requires_alt[i].size(); j++) {
int g = f->requires_alt[i][j];
cvm::log(cvm::to_str(j+1) + ". " + features()[g]->description + "\n");
enable(g, false, false); // Just for printing error output
enable(g, false, false, true); // Just for printing error output
}
cvm::decrease_depth();
cvm::log("-----------------------------------------\n");
@ -264,10 +274,14 @@ int colvardeps::enable(int feature_id,
for (i=0; i<f->requires_children.size(); i++) {
int g = f->requires_children[i];
for (j=0; j<children.size(); j++) {
res = children[j]->enable(g, dry_run || !is_enabled(), false);
res = children[j]->enable(g, dry_run || !is_enabled(), false, error);
if (res != COLVARS_OK) {
if (!dry_run) {
cvm::log("...required by \"" + f->description + "\" in " + description + "\n");
if (!dry_run || error) {
if (toplevel) {
cvm::log("Cannot enable \"" + f->description + "\" in " + description + "\n");
} else {
cvm::log("...required by \"" + f->description + "\" in " + description + "\n");
}
if (toplevel) {
cvm::error("Error: Failed dependency in " + description + ".\n");
}

22
lib/colvars/colvardeps.h
View File

@ -198,7 +198,9 @@ public:
/// \param toplevel False if this is called as part of a chain of dependency resolution.
/// This is used to diagnose failed dependencies by displaying the full stack:
/// only the toplevel dependency will throw a fatal error.
int enable(int f, bool dry_run = false, bool toplevel = true);
/// \param error Recursively enable, printing error messages along the way
/// Necessary when propagating errors across alternate dependencies
int enable(int f, bool dry_run = false, bool toplevel = true, bool error = false);
/// Disable a feature, decrease the reference count of its dependencies
/// and recursively disable them as applicable
@ -255,6 +257,8 @@ public:
f_cvb_scale_biasing_force,
/// \brief whether this bias is applied to one or more ext-Lagrangian colvars
f_cvb_extended,
/// Process this bias's data in parallel over multiple CPU threads
f_cvb_smp,
f_cvb_ntot
};
@ -263,8 +267,11 @@ public:
f_cv_active,
/// \brief Colvar is awake (active on its own accord) this timestep
f_cv_awake,
/// \brief Gradients are calculated and temporarily stored, so
/// that external forces can be applied
/// \brief External force can be applied, either to atoms or to an
/// extended DOF
f_cv_apply_force,
/// \brief Gradients are calculated and temporarily stored,
/// so that external forces can be propagated to atoms
f_cv_gradient,
/// \brief Collect atomic gradient data from all cvcs into vector
/// atomic_gradient
@ -277,7 +284,10 @@ public:
/// forces on the inverse gradient
f_cv_total_force,
/// \brief Calculate total force from atomic forces
/// or get it from the back-end for an external parameter
f_cv_total_force_calc,
/// \brief Total force is that of current time step
f_cv_total_force_current_step,
/// \brief Subtract the applied force from the total force
f_cv_subtract_applied_force,
/// \brief Estimate Jacobian derivative
@ -289,8 +299,10 @@ public:
/// center with fictitious mass; bias forces will be applied to
/// the center
f_cv_extended_Lagrangian,
/// \brief An extended variable that sets an external variable in the
/// back-end (eg. an alchemical coupling parameter for lambda-dynamics)
/// \brief A variable that constrains or follows an external parameter
/// in the back-end (eg. an alchemical coupling parameter for lambda-dynamics)
/// If extended Lagrangian, then we drive the external parameter
/// Otherwise we follow it
/// Can have a single component
f_cv_external,
/// \brief The extended system coordinate undergoes Langevin dynamics

124
lib/colvars/colvargrid.cpp
View File

@ -24,15 +24,14 @@ colvar_grid_count::colvar_grid_count()
mult = 1;
}
colvar_grid_count::colvar_grid_count(std::vector<int> const &nx_i,
size_t const &def_count)
: colvar_grid<size_t>(nx_i, def_count, 1)
colvar_grid_count::colvar_grid_count(std::vector<colvar *> &colvars,
std::string config)
: colvar_grid<size_t>(colvars, 0, 1, false, nullptr, config)
{}
colvar_grid_count::colvar_grid_count(std::vector<colvar *> &colvars,
size_t const &def_count,
bool margin)
: colvar_grid<size_t>(colvars, def_count, 1, margin)
std::shared_ptr<const colvar_grid_params> params)
: colvar_grid<size_t>(colvars, 0, 1, false, params)
{}
std::string colvar_grid_count::get_state_params() const
@ -132,13 +131,17 @@ colvar_grid_scalar::colvar_grid_scalar(colvar_grid_scalar const &g)
{
}
colvar_grid_scalar::colvar_grid_scalar(std::vector<int> const &nx_i)
: colvar_grid<cvm::real>(nx_i, 0.0, 1), samples(NULL)
colvar_grid_scalar::colvar_grid_scalar(std::vector<colvar *> &colvars,
std::shared_ptr<const colvar_grid_params> params,
bool add_extra_bin,
std::string config)
: colvar_grid<cvm::real>(colvars, 0.0, 1, add_extra_bin, params, config), samples(NULL)
{
}
colvar_grid_scalar::colvar_grid_scalar(std::vector<colvar *> &colvars, bool margin)
: colvar_grid<cvm::real>(colvars, 0.0, 1, margin), samples(NULL)
colvar_grid_scalar::colvar_grid_scalar(std::string const &filename)
: colvar_grid<cvm::real>(filename, 1),
samples(nullptr)
{
}
@ -330,89 +333,37 @@ cvm::real colvar_grid_scalar::grid_rmsd(colvar_grid_scalar const &other_grid) co
colvar_grid_gradient::colvar_grid_gradient()
: colvar_grid<cvm::real>(), samples(NULL), full_samples(0), min_samples(0)
: colvar_grid<cvm::real>(), samples(NULL)
{}
colvar_grid_gradient::colvar_grid_gradient(std::vector<int> const &nx_i)
: colvar_grid<cvm::real>(nx_i, 0.0, nx_i.size()), samples(NULL), full_samples(0), min_samples(0)
{}
// colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars, std::string config)
// : colvar_grid<cvm::real>(colvars, 0.0, colvars.size(), false, nullptr, config), samples(NULL)
// {}
// colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars,
// std::shared_ptr<colvar_grid_count> samples_in)
// : colvar_grid<cvm::real>(colvars, 0.0, colvars.size(), false, samples_in), samples(samples_in)
// {
// if (samples_in)
// samples_in->has_parent_data = true;
// }
colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars)
: colvar_grid<cvm::real>(colvars, 0.0, colvars.size()), samples(NULL), full_samples(0), min_samples(0)
{}
colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_count> samples_in)
: colvar_grid<cvm::real>(colvars, 0.0, colvars.size()), samples(samples_in), full_samples(0), min_samples(0)
colvar_grid_gradient::colvar_grid_gradient(std::vector<colvar *> &colvars,
std::shared_ptr<colvar_grid_count> samples_in,
std::shared_ptr<const colvar_grid_params> params,
std::string config)
: colvar_grid<cvm::real>(colvars, 0.0, colvars.size(), false, params, config), samples(samples_in)
{
samples_in->has_parent_data = true;
if (samples_in)
samples_in->has_parent_data = true;
}
colvar_grid_gradient::colvar_grid_gradient(std::string &filename)
: colvar_grid<cvm::real>(),
samples(NULL)
colvar_grid_gradient::colvar_grid_gradient(std::string const &filename)
: colvar_grid<cvm::real>(filename, 0),
samples(nullptr)
{
std::istream &is = cvm::main()->proxy->input_stream(filename,
"gradient file");
if (!is) {
return;
}
// Data in the header: nColvars, then for each
// xiMin, dXi, nPoints, periodic flag
std::string hash;
size_t i;
if ( !(is >> hash) || (hash != "#") ) {
cvm::error("Error reading grid at position "+
cvm::to_str(static_cast<size_t>(is.tellg()))+
" in stream(read \"" + hash + "\")\n");
return;
}
is >> nd;
if (nd > 50) {
cvm::error("Error: excessive number of dimensions in file \""+
filename+"\". Please ensure that the file is not corrupt.\n",
COLVARS_INPUT_ERROR);
return;
}
mult = nd;
std::vector<cvm::real> lower_in(nd), widths_in(nd);
std::vector<int> nx_in(nd);
std::vector<int> periodic_in(nd);
for (i = 0; i < nd; i++ ) {
if ( !(is >> hash) || (hash != "#") ) {
cvm::error("Error reading grid at position "+
cvm::to_str(static_cast<size_t>(is.tellg()))+
" in stream(read \"" + hash + "\")\n");
return;
}
is >> lower_in[i] >> widths_in[i] >> nx_in[i] >> periodic_in[i];
}
this->setup(nx_in, 0., mult);
widths = widths_in;
for (i = 0; i < nd; i++ ) {
lower_boundaries.push_back(colvarvalue(lower_in[i]));
periodic.push_back(static_cast<bool>(periodic_in[i]));
}
// Reset the istream for read_multicol, which expects the whole file
is.clear();
is.seekg(0);
read_multicol(is);
cvm::main()->proxy->close_input_stream(filename);
}
std::string colvar_grid_gradient::get_state_params() const
@ -586,12 +537,13 @@ cvm::real colvar_grid_gradient::grid_rmsd(colvar_grid_gradient const &other_grid
}
integrate_potential::integrate_potential(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_gradient> gradients)
: colvar_grid_scalar(colvars, true),
integrate_potential::integrate_potential(std::vector<colvar *> &colvars,
std::shared_ptr<colvar_grid_gradient> gradients)
: colvar_grid_scalar(colvars, gradients, true),
b_smoothed(false),
gradients(gradients)
{
// parent class colvar_grid_scalar is constructed with margin option set to true
// parent class colvar_grid_scalar is constructed with add_extra_bin option set to true
// hence PMF grid is wider than gradient grid if non-PBC
if (nd > 1) {

170
lib/colvars/colvargrid.h
View File

@ -19,17 +19,13 @@
#include "colvarparse.h"
/// \brief Grid of values of a function of several collective
/// variables \param T The data type
///
/// Only scalar colvars supported so far: vector colvars are treated as arrays
template <class T> class colvar_grid : public colvarparse {
//protected:
public: // TODO create accessors for these after all instantiations work
/// \brief Unified base class for grid of values of a function of several collective
/// variables
class colvar_grid_params {
public:
/// Number of dimensions
size_t nd;
size_t nd = 0;
/// Number of points along each dimension
std::vector<int> nx;
@ -37,6 +33,27 @@ public: // TODO create accessors for these after all instantiations work
/// Cumulative number of points along each dimension
std::vector<int> nxc;
/// Lower boundaries of the colvars in this grid
std::vector<colvarvalue> lower_boundaries;
/// Upper boundaries of the colvars in this grid
std::vector<colvarvalue> upper_boundaries;
/// Widths of the colvars in this grid
std::vector<cvm::real> widths;
};
/// \brief Grid of values of a function of several collective
/// variables \param T The data type
///
/// Only scalar colvars supported so far: vector colvars are treated as arrays
/// All common, type-independent members are collected in the base class colvar_grid_base
template <class T> class colvar_grid : public colvar_grid_params, public colvarparse {
//protected:
public: // TODO create accessors for these after all instantiations work
/// \brief Multiplicity of each datum (allow the binning of
/// non-scalar types such as atomic gradients)
size_t mult;
@ -73,13 +90,6 @@ public: // TODO create accessors for these after all instantiations work
}
public:
/// Lower boundaries of the colvars in this grid
std::vector<colvarvalue> lower_boundaries;
/// Upper boundaries of the colvars in this grid
std::vector<colvarvalue> upper_boundaries;
/// Whether some colvars are periodic
std::vector<bool> periodic;
@ -89,9 +99,6 @@ public:
/// Whether some colvars have hard upper boundaries
std::vector<bool> hard_upper_boundaries;
/// Widths of the colvars in this grid
std::vector<cvm::real> widths;
/// True if this is a count grid related to another grid of data
bool has_parent_data;
@ -218,19 +225,15 @@ public:
/// \brief "Almost copy-constructor": only copies configuration
/// parameters from another grid, but doesn't reallocate stuff;
/// setup() must be called after that;
colvar_grid(colvar_grid<T> const &g) : colvarparse(),
nd(g.nd),
nx(g.nx),
colvar_grid(colvar_grid<T> const &g) : colvar_grid_params(colvar_grid_params(g)),
colvarparse(),
mult(g.mult),
data(),
cv(g.cv),
use_actual_value(g.use_actual_value),
lower_boundaries(g.lower_boundaries),
upper_boundaries(g.upper_boundaries),
periodic(g.periodic),
hard_lower_boundaries(g.hard_lower_boundaries),
hard_upper_boundaries(g.hard_upper_boundaries),
widths(g.widths),
has_parent_data(false),
has_data(false)
{}
@ -247,22 +250,31 @@ public:
this->setup(nx_i, t, mult_i);
}
/// \brief Constructor from a vector of colvars
/// \brief Constructor from a vector of colvars or an optional grid config string
/// \param add_extra_bin requests that non-periodic dimensions are extended
/// by 1 bin to accommodate the integral (PMF) of another gridded quantity (gradient)
colvar_grid(std::vector<colvar *> const &colvars,
T const &t = T(),
size_t mult_i = 1,
bool add_extra_bin = false)
bool add_extra_bin = false,
std::shared_ptr<const colvar_grid_params> params = nullptr,
std::string config = std::string())
: has_parent_data(false), has_data(false)
{
(void) t;
this->init_from_colvars(colvars, mult_i, add_extra_bin);
this->init_from_colvars(colvars, mult_i, add_extra_bin, params, config);
}
/// \brief Constructor from a multicol file
/// \param filename multicol file containing data to be read
/// \param multi_i multiplicity of the data - if 0, assume gradient multiplicity (mult = nd)
colvar_grid(std::string const &filename, size_t mult_i = 1);
int init_from_colvars(std::vector<colvar *> const &colvars,
size_t mult_i = 1,
bool add_extra_bin = false)
bool add_extra_bin = false,
std::shared_ptr<const colvar_grid_params> params = nullptr,
std::string config = std::string())
{
if (cvm::debug()) {
cvm::log("Reading grid configuration from collective variables.\n");
@ -279,8 +291,7 @@ public:
" collective variables, multiplicity = "+cvm::to_str(mult_i)+".\n");
}
for (i = 0; i < cv.size(); i++) {
for (i = 0; i < nd; i++) {
if (cv[i]->value().type() != colvarvalue::type_scalar) {
cvm::error("Colvar grids can only be automatically "
"constructed for scalar variables. "
@ -298,7 +309,6 @@ public:
widths.push_back(cv[i]->width);
hard_lower_boundaries.push_back(cv[i]->is_enabled(colvardeps::f_cv_hard_lower_boundary));
hard_upper_boundaries.push_back(cv[i]->is_enabled(colvardeps::f_cv_hard_upper_boundary));
periodic.push_back(cv[i]->periodic_boundaries());
// By default, get reported colvar value (for extended Lagrangian colvars)
use_actual_value.push_back(false);
@ -310,22 +320,55 @@ public:
use_actual_value[i-1] = true;
}
// This needs to work if the boundaries are undefined in the colvars
lower_boundaries.push_back(cv[i]->lower_boundary);
upper_boundaries.push_back(cv[i]->upper_boundary);
}
// Replace widths and boundaries with optional custom configuration
if (!config.empty()) {
this->parse_params(config);
this->check_keywords(config, "grid");
if (params) {
cvm::error("Error: init_from_colvars was passed both a grid config and a template grid.", COLVARS_BUG_ERROR);
return COLVARS_BUG_ERROR;
}
} else if (params) {
// Match grid sizes with template
if (params->nd != nd) {
cvm::error("Trying to initialize grid from template with wrong dimension (" +
cvm::to_str(params->nd) + " instead of " +
cvm::to_str(this->nd) + ").");
return COLVARS_ERROR;
}
widths =params->widths;
lower_boundaries =params->lower_boundaries;
upper_boundaries =params->upper_boundaries;
}
// Only now can we determine periodicity
for (i = 0; i < nd; i++) {
periodic.push_back(cv[i]->periodic_boundaries(lower_boundaries[i].real_value,
upper_boundaries[i].real_value));
if (add_extra_bin) {
// Shift the grid by half the bin width (values at edges instead of center of bins)
lower_boundaries[i] -= 0.5 * widths[i];
if (periodic[i]) {
// Shift the grid by half the bin width (values at edges instead of center of bins)
lower_boundaries.push_back(cv[i]->lower_boundary.real_value - 0.5 * widths[i]);
upper_boundaries.push_back(cv[i]->upper_boundary.real_value - 0.5 * widths[i]);
// Just shift
upper_boundaries[i] -= 0.5 * widths[i];
} else {
// Make this grid larger by one bin width
lower_boundaries.push_back(cv[i]->lower_boundary.real_value - 0.5 * widths[i]);
upper_boundaries.push_back(cv[i]->upper_boundary.real_value + 0.5 * widths[i]);
// Widen grid by one bin width
upper_boundaries[i] += 0.5 * widths[i];
}
} else {
lower_boundaries.push_back(cv[i]->lower_boundary);
upper_boundaries.push_back(cv[i]->upper_boundary);
}
}
// Reset grid sizes based on widths and boundaries
this->init_from_boundaries();
return this->setup();
}
@ -966,14 +1009,12 @@ public:
virtual ~colvar_grid_count()
{}
/// Constructor
colvar_grid_count(std::vector<int> const &nx_i,
size_t const &def_count = 0);
/// Constructor from a vector of colvars
/// Constructor from a vector of colvars or a config string
colvar_grid_count(std::vector<colvar *> &colvars,
size_t const &def_count = 0,
bool add_extra_bin = false);
std::shared_ptr<const colvar_grid_params> params = nullptr);
colvar_grid_count(std::vector<colvar *> &colvars,
std::string config);
/// Increment the counter at given position
inline void incr_count(std::vector<int> const &ix)
@ -1255,12 +1296,14 @@ public:
/// Destructor
virtual ~colvar_grid_scalar();
/// Constructor from specific sizes arrays
colvar_grid_scalar(std::vector<int> const &nx_i);
/// Constructor from a vector of colvars
colvar_grid_scalar(std::vector<colvar *> &colvars,
bool add_extra_bin = false);
std::shared_ptr<const colvar_grid_params> params = nullptr,
bool add_extra_bin = false,
std::string config = std::string());
/// Constructor from a multicol file
colvar_grid_scalar(std::string const &filename);
/// Accumulate the value
inline void acc_value(std::vector<int> const &ix,
@ -1334,8 +1377,8 @@ public:
/// \brief Return the gradient of the scalar field from finite differences
/// Input coordinates are those of gradient grid, shifted wrt scalar grid
/// Should not be called on edges of scalar grid, provided the latter has margins
/// wrt gradient grid
/// Should not be called on edges of scalar grid, provided the latter has
/// margins (extra bins) wrt gradient grid
inline void vector_gradient_finite_diff( const std::vector<int> &ix0, std::vector<cvm::real> &grad)
{
cvm::real A0, A1;
@ -1566,17 +1609,21 @@ public:
virtual ~colvar_grid_gradient()
{}
/// Constructor from specific sizes arrays
colvar_grid_gradient(std::vector<int> const &nx_i);
// /// Constructor from specific sizes arrays
// colvar_grid_gradient(std::vector<int> const &nx_i);
/// Constructor from a vector of colvars
colvar_grid_gradient(std::vector<colvar *> &colvars);
// /// Constructor from a vector of colvars
// colvar_grid_gradient(std::vector<colvar *> &colvars,
// std::string config = std::string());
/// Constructor from a multicol file
colvar_grid_gradient(std::string &filename);
colvar_grid_gradient(std::string const &filename);
/// Constructor from a vector of colvars and a pointer to the count grid
colvar_grid_gradient(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_count> samples_in);
colvar_grid_gradient(std::vector<colvar *> &colvars,
std::shared_ptr<colvar_grid_count> samples_in = nullptr,
std::shared_ptr<const colvar_grid_params> params = nullptr,
std::string config = std::string());
/// Parameters for smoothing data with low sampling
int full_samples;
@ -1829,7 +1876,8 @@ class integrate_potential : public colvar_grid_scalar
{}
/// Constructor from a vector of colvars + gradient grid
integrate_potential(std::vector<colvar *> &colvars, std::shared_ptr<colvar_grid_gradient> gradients);
integrate_potential(std::vector<colvar *> &colvars,
std::shared_ptr<colvar_grid_gradient> gradients);
/// Constructor from a gradient grid (for processing grid files without a Colvars config)
integrate_potential(std::shared_ptr<colvar_grid_gradient> gradients);

64
lib/colvars/colvargrid_def.h
View File

@ -22,6 +22,62 @@
#include "colvars_memstream.h"
template <class T>
colvar_grid<T>::colvar_grid(std::string const &filename, size_t mult_i)
{
std::istream &is = cvm::main()->proxy->input_stream(filename, "multicol grid file");
if (!is) {
return;
}
// Data in the header: nColvars, then for each
// xiMin, dXi, nPoints, periodic flag
std::string hash;
size_t i;
if ( !(is >> hash) || (hash != "#") ) {
cvm::error("Error reading grid at position "+
cvm::to_str(static_cast<size_t>(is.tellg()))+
" in stream(read \"" + hash + "\")\n");
return;
}
is >> nd;
mult = (mult_i == 0) ? nd : mult_i;
std::vector<cvm::real> lower_in(nd), widths_in(nd);
std::vector<int> nx_in(nd);
std::vector<int> periodic_in(nd);
for (i = 0; i < nd; i++ ) {
if ( !(is >> hash) || (hash != "#") ) {
cvm::error("Error reading grid at position "+
cvm::to_str(static_cast<size_t>(is.tellg()))+
" in stream(read \"" + hash + "\")\n");
return;
}
is >> lower_in[i] >> widths_in[i] >> nx_in[i] >> periodic_in[i];
}
this->setup(nx_in, 0., mult);
widths = widths_in;
for (i = 0; i < nd; i++ ) {
lower_boundaries.push_back(colvarvalue(lower_in[i]));
periodic.push_back(static_cast<bool>(periodic_in[i]));
}
// Reset the istream for read_multicol, which expects the whole file
is.clear();
is.seekg(0);
read_multicol(is);
cvm::main()->proxy->close_input_stream(filename);
}
template <class T, class IST> IST &read_restart_template_(colvar_grid<T> &g, IST &is)
{
auto const start_pos = is.tellg();
@ -203,14 +259,16 @@ template <class T> int colvar_grid<T>::parse_params(std::string const &conf,
lower_boundaries, lower_boundaries, colvarparse::parse_silent);
colvarparse::get_keyval(conf, "upper_boundaries",
upper_boundaries, upper_boundaries, colvarparse::parse_silent);
// plural form is used in state file
colvarparse::get_keyval(conf, "widths", widths, widths, colvarparse::parse_silent);
// camel case keywords are used in config file
colvarparse::get_keyval(conf, "lowerBoundaries",
colvarparse::get_keyval(conf, "lowerBoundary",
lower_boundaries, lower_boundaries, parse_mode);
colvarparse::get_keyval(conf, "upperBoundaries",
colvarparse::get_keyval(conf, "upperBoundary",
upper_boundaries, upper_boundaries, parse_mode);
colvarparse::get_keyval(conf, "widths", widths, widths, parse_mode);
colvarparse::get_keyval(conf, "width", widths, widths, parse_mode);
// only used in state file
colvarparse::get_keyval(conf, "sizes", nx, nx, colvarparse::parse_silent);

80
lib/colvars/colvarmodule.cpp
View File

@ -24,6 +24,7 @@
#include "colvarbias_histogram_reweight_amd.h"
#include "colvarbias_meta.h"
#include "colvarbias_restraint.h"
#include "colvarbias_opes.h"
#include "colvarscript.h"
#include "colvaratoms.h"
#include "colvarcomp.h"
@ -109,23 +110,23 @@ colvarmodule::colvarmodule(colvarproxy *proxy_in)
" https://doi.org/10.1080/00268976.2013.813594\n"
"as well as all other papers listed below for individual features used.\n");
#if (__cplusplus >= 201103L)
cvm::log("This version was built with the C++11 standard or higher.\n");
#else
cvm::log("This version was built without the C++11 standard: some features are disabled.\n"
"Please see the following link for details:\n"
" https://colvars.github.io/README-c++11.html\n");
#endif
cvm::log("Summary of compile-time features available in this build:\n");
if (proxy->check_smp_enabled() == COLVARS_NOT_IMPLEMENTED) {
cvm::log(" - SMP parallelism: not available\n");
std::string cxx_lang_msg(" - C++ language version: " + cvm::to_str(__cplusplus));
#if defined(_WIN32) && !defined(__CYGWIN__)
cxx_lang_msg += std::string(" (warning: may not be accurate for this build)");
#endif
cxx_lang_msg += std::string("\n");
cvm::log(cxx_lang_msg);
if (proxy->check_replicas_enabled() == COLVARS_NOT_IMPLEMENTED) {
cvm::log(" - Multiple replicas: not available\n");
} else {
if (proxy->check_smp_enabled() == COLVARS_OK) {
cvm::log(" - SMP parallelism: enabled (num. threads = " + to_str(proxy->smp_num_threads()) + ")\n");
if (proxy->check_replicas_enabled() == COLVARS_OK) {
cvm::log(" - Multiple replicas: enabled (replica number " +
to_str(proxy->replica_index() + 1) + " of " + to_str(proxy->num_replicas()) + ")\n");
} else {
cvm::log(" - SMP parallelism: available, but not enabled\n");
cvm::log(" - Multiple replicas: available, but not (yet) enabled\n");
}
}
@ -201,6 +202,20 @@ std::vector<int> *colvarmodule::variables_active_smp_items()
}
int colvarmodule::calc_component_smp(int i)
{
colvar *x = (*(variables_active_smp()))[i];
int x_item = (*(variables_active_smp_items()))[i];
if (cvm::debug()) {
cvm::log("Thread "+cvm::to_str(proxy->smp_thread_id())+"/"+
cvm::to_str(proxy->smp_num_threads())+
": calc_component_smp(), i = "+cvm::to_str(i)+", cv = "+
x->name+", cvc = "+cvm::to_str(x_item)+"\n");
}
return x->calc_cvcs(x_item, 1);
}
std::vector<colvarbias *> *colvarmodule::biases_active()
{
return &(biases_active_);
@ -387,8 +402,26 @@ int colvarmodule::parse_global_params(std::string const &conf)
}
}
if (parse->get_keyval(conf, "smp", proxy->b_smp_active, proxy->b_smp_active)) {
if (proxy->b_smp_active == false) {
std::string smp;
if (parse->get_keyval(conf, "smp", smp, "cvcs")) {
if (smp == "cvcs" || smp == "on" || smp == "yes") {
if (proxy->set_smp_mode(colvarproxy_smp::smp_mode_t::cvcs) != COLVARS_OK) {
cvm::error("Colvars component-based parallelism is not implemented.\n");
return COLVARS_INPUT_ERROR;
} else {
cvm::log("SMP parallelism will be applied to Colvars components.\n");
cvm::log(" - SMP parallelism: enabled (num. threads = " + to_str(proxy->smp_num_threads()) + ")\n");
}
} else if (smp == "inner_loop") {
if (proxy->set_smp_mode(colvarproxy_smp::smp_mode_t::inner_loop) != COLVARS_OK) {
cvm::error("SMP parallelism inside the calculation of Colvars components is not implemented.\n");
return COLVARS_INPUT_ERROR;
} else {
cvm::log("SMP parallelism will be applied inside the Colvars components.\n");
cvm::log(" - SMP parallelism: enabled (num. threads = " + to_str(proxy->smp_num_threads()) + ")\n");
}
} else {
proxy->set_smp_mode(colvarproxy_smp::smp_mode_t::none);
cvm::log("SMP parallelism has been disabled.\n");
}
}
@ -589,6 +622,9 @@ int colvarmodule::parse_biases(std::string const &conf)
/// initialize reweightaMD instances
parse_biases_type<colvarbias_reweightaMD>(conf, "reweightaMD");
/// initialize OPES instances
parse_biases_type<colvarbias_opes>(conf, "opes_metad");
if (use_scripted_forces) {
cvm::log(cvm::line_marker);
cvm::increase_depth();
@ -922,7 +958,7 @@ int colvarmodule::calc_colvars()
}
// if SMP support is available, split up the work
if (proxy->check_smp_enabled() == COLVARS_OK) {
if (proxy->get_smp_mode() == colvarproxy_smp::smp_mode_t::cvcs) {
// first, calculate how much work (currently, how many active CVCs) each colvar has
@ -948,8 +984,10 @@ int colvarmodule::calc_colvars()
}
cvm::decrease_depth();
// calculate colvar components in parallel
error_code |= proxy->smp_colvars_loop();
// calculate active colvar components in parallel
error_code |= proxy->smp_loop(variables_active_smp()->size(), [](int i) {
return cvm::main()->calc_component_smp(i);
});
cvm::increase_depth();
for (cvi = variables_active()->begin(); cvi != variables_active()->end(); cvi++) {
@ -1013,7 +1051,7 @@ int colvarmodule::calc_biases()
}
// If SMP support is available, split up the work (unless biases need to use main thread's memory)
if (proxy->check_smp_enabled() == COLVARS_OK && !biases_need_main_thread) {
if (proxy->get_smp_mode() == colvarproxy::smp_mode_t::cvcs && !biases_need_main_thread) {
if (use_scripted_forces && !scripting_after_biases) {
// calculate biases and scripted forces in parallel
@ -1097,7 +1135,7 @@ int colvarmodule::update_colvar_forces()
cvm::log("Communicating forces from the colvars to the atoms.\n");
cvm::increase_depth();
for (cvi = variables_active()->begin(); cvi != variables_active()->end(); cvi++) {
if ((*cvi)->is_enabled(colvardeps::f_cv_gradient)) {
if ((*cvi)->is_enabled(colvardeps::f_cv_apply_force)) {
(*cvi)->communicate_forces();
if (cvm::get_error()) {
return COLVARS_ERROR;
@ -1986,7 +2024,7 @@ size_t & colvarmodule::depth()
{
// NOTE: do not call log() or error() here, to avoid recursion
colvarmodule *cv = cvm::main();
if (proxy->check_smp_enabled() == COLVARS_OK) {
if (proxy->get_smp_mode() == colvarproxy::smp_mode_t::cvcs) {
int const nt = proxy->smp_num_threads();
if (int(cv->depth_v.size()) != nt) {
proxy->smp_lock();

53
lib/colvars/colvarmodule.h
View File

@ -18,6 +18,11 @@
#define COLVARS_DEBUG false
#endif
#if defined(__FAST_MATH__)
// NOTE: This is used for fixing https://github.com/Colvars/colvars/issues/767
#define COLVARS_BOUNDED_INV_TRIGONOMETRIC_FUNC
#endif
/*! \mainpage Main page
This is the Developer's documentation for the Collective Variables module (Colvars).
@ -147,17 +152,44 @@ public:
return ::cos(static_cast<double>(x));
}
/// Reimplemented to work around MS compiler issues
static inline real asin(real const &x)
{
return ::asin(static_cast<double>(x));
}
#ifndef PI
#define PI 3.14159265358979323846
#endif
#ifndef PI_2
#define PI_2 1.57079632679489661923
#endif
/// Reimplemented to work around MS compiler issues
static inline real acos(real const &x)
{
/// Reimplemented to work around compiler issues; return hard-coded values for boundary conditions
static inline real asin(real const &x)
{
#ifdef COLVARS_BOUNDED_INV_TRIGONOMETRIC_FUNC
if (x <= -1.0) {
return -PI_2;
} else if (x >= 1.0) {
return PI_2;
} else {
return ::asin(static_cast<double>(x));
}
#else
return ::asin(static_cast<double>(x));
#endif
}
/// Reimplemented to work around compiler issues; return hard-coded values for boundary conditions
static inline real acos(real const &x)
{
#ifdef COLVARS_BOUNDED_INV_TRIGONOMETRIC_FUNC
if (x <= -1.0) {
return PI;
} else if (x >= 1.0) {
return 0.0;
} else {
return ::acos(static_cast<double>(x));
}
#else
return ::acos(static_cast<double>(x));
}
#endif
}
/// Reimplemented to work around MS compiler issues
static inline real atan2(real const &x, real const &y)
@ -307,6 +339,9 @@ public:
/// Indexes of the items to calculate for each colvar
std::vector<int> *variables_active_smp_items();
/// Calculate the value of the specified component (to be called in a SMP loop)
int calc_component_smp(int i);
/// Array of collective variable biases
std::vector<colvarbias *> biases;

151
lib/colvars/colvarmodule_refs.h
View File

@ -129,6 +129,23 @@
" url = {https://doi.org/10.1002/jcc.26075}\n"
"}\n";
paper_count_[std::string("Fiorin2024")] = 0;
paper_url_[std::string("Fiorin2024")] = "https://doi.org/10.1021/acs.jpcb.4c05604";
paper_bibtex_[std::string("Fiorin2024")] =
"\n"
"@article{Fiorin2024,\n"
" author = {Fiorin, Giacomo and Marinelli, Fabrizio and Forrest, Lucy R. and Chen, Haochuan and Chipot, Christophe and Kohlmeyer, Axel and Santuz, Hubert and H{\\'e}nin, J{\\'e}rôme},\n"
" title = {Expanded Functionality and Portability for the Colvars Library},\n"
" journal = {J. Phys. Chem. {B}},\n"
" volume = {128},\n"
" number = {45},\n"
" pages = {11108--11123},\n"
" year = {2024},\n"
" doi = {10.1021/acs.jpcb.4c05604},\n"
" pmid = 39501453,\n"
" url = { https://doi.org/10.1021/acs.jpcb.4c05604}\n"
"}\n";
paper_count_[std::string("Fu2016")] = 0;
paper_url_[std::string("Fu2016")] = "https://doi.org/10.1021/acs.jctc.6b00447";
paper_bibtex_[std::string("Fu2016")] =
@ -227,6 +244,20 @@
" url = {https://doi.org/10.1016/0263-7855(96)00018-5}\n"
"}\n";
paper_count_[std::string("Lagardere2023")] = 0;
paper_url_[std::string("Lagardere2023")] = "https://arxiv.org/abs/2307.08006";
paper_bibtex_[std::string("Lagardere2023")] =
"\n"
"@misc{Lagardere2023,\n"
" title={Lambda-ABF: Simplified, Accurate and Cost-effective Alchemical Free Energy Computations},\n"
" author={Louis Lagard\\`ere and Lise Maurin and Olivier Adjoua and Krystel El Hage and Pierre Monmarch\\'e and Jean-Philip Piquemal and J\\'er\\^ome H\\'enin},\n"
" year={2023},\n"
" eprint={2307.08006},\n"
" archivePrefix={arXiv},\n"
" primaryClass={physics.chem-ph},\n"
" url = {https://arxiv.org/abs/2307.08006}\n"
"}\n";
paper_count_[std::string("Lesage2017")] = 0;
paper_url_[std::string("Lesage2017")] = "https://doi.org/10.1021/acs.jpcb.6b10055";
paper_bibtex_[std::string("Lesage2017")] =
@ -344,6 +375,45 @@
" url = {https://doi.org/10.1021/ct500320c}\n"
"}\n";
paper_count_[std::string("Invernizzi2020")] = 0;
paper_url_[std::string("Invernizzi2020")] = "https://pubs.acs.org/doi/10.1021/acs.jpclett.0c00497";
paper_bibtex_[std::string("Invernizzi2020")] =
"\n"
"@article{Invernizzi2020,\n"
" title = {Rethinking {Metadynamics}: {From} {Bias} {Potentials} to {Probability} {Distributions}},\n"
" volume = {11},\n"
" issn = {1948-7185, 1948-7185},\n"
" shorttitle = {Rethinking {Metadynamics}},\n"
" url = {https://pubs.acs.org/doi/10.1021/acs.jpclett.0c00497},\n"
" doi = {10.1021/acs.jpclett.0c00497},\n"
" number = {7},\n"
" urldate = {2020-09-30},\n"
" journal = {J. Phys. Chem. Lett.},\n"
" author = {Invernizzi, Michele and Parrinello, Michele},\n"
" month = apr,\n"
" year = {2020},\n"
" pages = {2731--2736},\n"
"}\n";
paper_count_[std::string("Invernizzi2022")] = 0;
paper_url_[std::string("Invernizzi2022")] = "https://doi.org/10.1021/acs.jctc.2c00152";
paper_bibtex_[std::string("Invernizzi2022")] =
"\n"
"@article{Invernizzi2022,\n"
" title = {Exploration vs {Convergence} {Speed} in {Adaptive}-{Bias} {Enhanced} {Sampling}},\n"
" volume = {18},\n"
" issn = {1549-9618},\n"
" url = {https://doi.org/10.1021/acs.jctc.2c00152},\n"
" doi = {10.1021/acs.jctc.2c00152},\n"
" number = {6},\n"
" urldate = {2024-07-02},\n"
" journal = {J. Chem. Theory Comput.},\n"
" author = {Invernizzi, Michele and Parrinello, Michele},\n"
" month = jun,\n"
" year = {2022},\n"
" pages = {3988--3996},\n"
"}\n";
paper_count_[std::string("n/a")] = 0;
paper_url_[std::string("n/a")] = "";
paper_bibtex_[std::string("n/a")] = "";
@ -489,6 +559,42 @@
feature_count_[std::string("Multi-Map collective variables")] = 0;
feature_paper_map_[std::string("Multi-Map collective variables")] = "Fiorin2020";
feature_count_[std::string("Colvars-GROMACS interface")] = 0;
feature_paper_map_[std::string("Colvars-GROMACS interface")] = "Fiorin2024";
feature_count_[std::string("gspath colvar component")] = 0;
feature_paper_map_[std::string("gspath colvar component")] = "Fiorin2024";
feature_count_[std::string("gzpath colvar component")] = 0;
feature_paper_map_[std::string("gzpath colvar component")] = "Fiorin2024";
feature_count_[std::string("linearCombination colvar component")] = 0;
feature_paper_map_[std::string("linearCombination colvar component")] = "Fiorin2024";
feature_count_[std::string("gspathCV colvar component")] = 0;
feature_paper_map_[std::string("gspathCV colvar component")] = "Fiorin2024";
feature_count_[std::string("gzpathCV colvar component")] = 0;
feature_paper_map_[std::string("gzpathCV colvar component")] = "Fiorin2024";
feature_count_[std::string("aspathCV colvar component")] = 0;
feature_paper_map_[std::string("aspathCV colvar component")] = "Fiorin2024";
feature_count_[std::string("azpathCV colvar component")] = 0;
feature_paper_map_[std::string("azpathCV colvar component")] = "Fiorin2024";
feature_count_[std::string("Custom functions (Lepton)")] = 0;
feature_paper_map_[std::string("Custom functions (Lepton)")] = "Fiorin2024";
feature_count_[std::string("Scripted functions (Tcl)")] = 0;
feature_paper_map_[std::string("Scripted functions (Tcl)")] = "Fiorin2024";
feature_count_[std::string("ABMD bias")] = 0;
feature_paper_map_[std::string("ABMD bias")] = "Fiorin2024";
feature_count_[std::string("Updated multiple-walker ABF implementation")] = 0;
feature_paper_map_[std::string("Updated multiple-walker ABF implementation")] = "Fiorin2024";
feature_count_[std::string("Umbrella-integration eABF estimator")] = 0;
feature_paper_map_[std::string("Umbrella-integration eABF estimator")] = "Fu2016";
@ -525,6 +631,15 @@
feature_count_[std::string("VMD engine")] = 0;
feature_paper_map_[std::string("VMD engine")] = "Humphrey1996";
feature_count_[std::string("alchLambda colvar component")] = 0;
feature_paper_map_[std::string("alchLambda colvar component")] = "Lagardere2023";
feature_count_[std::string("alchFLambda colvar component")] = 0;
feature_paper_map_[std::string("alchFLambda colvar component")] = "Lagardere2023";
feature_count_[std::string("Tinker-HP interface")] = 0;
feature_paper_map_[std::string("Tinker-HP interface")] = "Lagardere2023";
feature_count_[std::string("eABF implementation")] = 0;
feature_paper_map_[std::string("eABF implementation")] = "Lesage2017";
@ -555,38 +670,14 @@
feature_count_[std::string("ALB colvar bias implementation")] = 0;
feature_paper_map_[std::string("ALB colvar bias implementation")] = "White2014";
feature_count_[std::string("Colvars-GROMACS interface")] = 0;
feature_paper_map_[std::string("Colvars-GROMACS interface")] = "n/a";
feature_count_[std::string("OPES")] = 0;
feature_paper_map_[std::string("OPES")] = "Invernizzi2020";
feature_count_[std::string("gspath colvar component")] = 0;
feature_paper_map_[std::string("gspath colvar component")] = "n/a";
feature_count_[std::string("gzpath colvar component")] = 0;
feature_paper_map_[std::string("gzpath colvar component")] = "n/a";
feature_count_[std::string("linearCombination colvar component")] = 0;
feature_paper_map_[std::string("linearCombination colvar component")] = "n/a";
feature_count_[std::string("gspathCV colvar component")] = 0;
feature_paper_map_[std::string("gspathCV colvar component")] = "n/a";
feature_count_[std::string("gzpathCV colvar component")] = 0;
feature_paper_map_[std::string("gzpathCV colvar component")] = "n/a";
feature_count_[std::string("aspathCV colvar component")] = 0;
feature_paper_map_[std::string("aspathCV colvar component")] = "n/a";
feature_count_[std::string("azpathCV colvar component")] = 0;
feature_paper_map_[std::string("azpathCV colvar component")] = "n/a";
feature_count_[std::string("OPES explore or adaptive kernels")] = 0;
feature_paper_map_[std::string("OPES explore or adaptive kernels")] = "Invernizzi2022";
feature_count_[std::string("coordNum pairlist")] = 0;
feature_paper_map_[std::string("coordNum pairlist")] = "n/a";
feature_count_[std::string("Custom functions (Lepton)")] = 0;
feature_paper_map_[std::string("Custom functions (Lepton)")] = "n/a";
feature_count_[std::string("Scripted functions (Tcl)")] = 0;
feature_paper_map_[std::string("Scripted functions (Tcl)")] = "n/a";
feature_count_[std::string("ABMD bias")] = 0;
feature_paper_map_[std::string("ABMD bias")] = "n/a";
feature_count_[std::string("torchANN colvar component")] = 0;
feature_paper_map_[std::string("torchANN colvar component")] = "n/a";

5
lib/colvars/colvarparse.cpp
View File

@ -592,7 +592,7 @@ int colvarparse::check_keywords(std::string &conf, char const *key)
{
if (cvm::debug())
cvm::log("Configuration string for \""+std::string(key)+
"\": \"\n"+conf+"\".\n");
"\":\n\""+conf+"\".\n");
strip_values(conf);
// after stripping, the config string has either empty lines, or
@ -833,7 +833,8 @@ bool colvarparse::key_lookup(std::string const &conf,
data_end) + 1;
}
if (data != NULL) {
// data_end < data_begin means that the data or block contains only whitespace
if (data != NULL && data_end > data_begin) {
data->append(line, data_begin, (data_end-data_begin));
if (cvm::debug()) {

56
lib/colvars/colvarproxy.cpp
View File

@ -243,7 +243,7 @@ void colvarproxy_atom_groups::compute_max_atom_groups_applied_force()
colvarproxy_smp::colvarproxy_smp()
{
b_smp_active = true; // May be disabled by user option
smp_mode = smp_mode_t::cvcs; // May be disabled by user option
omp_lock_state = NULL;
#if defined(_OPENMP)
if (omp_get_thread_num() == 0) {
@ -265,41 +265,45 @@ colvarproxy_smp::~colvarproxy_smp()
#endif
}
int colvarproxy_smp::check_smp_enabled()
{
colvarproxy::smp_mode_t colvarproxy_smp::get_smp_mode() const {
#if defined(_OPENMP)
if (b_smp_active) {
return COLVARS_OK;
}
return COLVARS_ERROR;
return smp_mode;
#else
return COLVARS_NOT_IMPLEMENTED;
return colvarproxy::smp_mode_t::none;
#endif
}
int colvarproxy_smp::set_smp_mode(smp_mode_t mode) {
#if defined(_OPENMP)
smp_mode = mode;
return COLVARS_OK;
#else
if (mode != colvarproxy::smp_mode_t::none) {
return COLVARS_NOT_IMPLEMENTED;
} else {
smp_mode = colvarproxy::smp_mode_t::none;
}
return COLVARS_OK;
#endif
}
int colvarproxy_smp::smp_colvars_loop()
int colvarproxy_smp::smp_loop(int n_items, std::function<int (int)> const &worker)
{
int error_code = COLVARS_OK;
#if defined(_OPENMP)
colvarmodule *cv = cvm::main();
colvarproxy *proxy = cv->proxy;
cvm::increase_depth();
#pragma omp parallel for
for (int i = 0; i < static_cast<int>(cv->variables_active_smp()->size()); i++) {
colvar *x = (*(cv->variables_active_smp()))[i];
int x_item = (*(cv->variables_active_smp_items()))[i];
if (cvm::debug()) {
cvm::log("["+cvm::to_str(proxy->smp_thread_id())+"/"+
cvm::to_str(proxy->smp_num_threads())+
"]: calc_colvars_items_smp(), i = "+cvm::to_str(i)+", cv = "+
x->name+", cvc = "+cvm::to_str(x_item)+"\n");
}
x->calc_cvcs(x_item, 1);
for (int i = 0; i < n_items; i++) {
int const retcode = worker(i);
#pragma omp atomic
error_code |= retcode;
}
return cvm::get_error();
cvm::decrease_depth();
#else
return COLVARS_NOT_IMPLEMENTED;
error_code |= COLVARS_NOT_IMPLEMENTED;
#endif
return error_code;
}
@ -470,8 +474,8 @@ colvarproxy::~colvarproxy()
bool colvarproxy::io_available()
{
return (check_smp_enabled() == COLVARS_OK && smp_thread_id() == 0) ||
(check_smp_enabled() != COLVARS_OK);
return ((get_smp_mode() != smp_mode_t::none) && smp_thread_id() == 0) ||
(get_smp_mode() == smp_mode_t::none);
}

52
lib/colvars/colvarproxy.h
View File

@ -10,9 +10,12 @@
#ifndef COLVARPROXY_H
#define COLVARPROXY_H
#include <functional>
#include "colvarmodule.h"
#include "colvartypes.h"
#include "colvarproxy_io.h"
#include "colvarproxy_replicas.h"
#include "colvarproxy_system.h"
#include "colvarproxy_tcl.h"
#include "colvarproxy_volmaps.h"
@ -447,21 +450,22 @@ class colvarproxy_smp {
public:
enum class smp_mode_t {cvcs, inner_loop, none};
/// Constructor
colvarproxy_smp();
/// Destructor
virtual ~colvarproxy_smp();
/// Whether threaded parallelization should be used (TODO: make this a
/// cvm::deps feature)
bool b_smp_active;
/// Get the current SMP mode
virtual smp_mode_t get_smp_mode() const;
/// Whether threaded parallelization is available (TODO: make this a cvm::deps feature)
virtual int check_smp_enabled();
/// Set the current SMP mode
virtual int set_smp_mode(smp_mode_t mode);
/// Distribute calculation of colvars (and their components) across threads
virtual int smp_colvars_loop();
/// Distribute computation over threads using OpenMP, unless overridden in the backend (e.g. NAMD)
virtual int smp_loop(int n_items, std::function<int (int)> const &worker);
/// Distribute calculation of biases across threads
virtual int smp_biases_loop();
@ -488,38 +492,10 @@ protected:
/// Lock state for OpenMP
omp_lock_t *omp_lock_state;
};
/// \brief Methods for multiple-replica communication
class colvarproxy_replicas {
public:
/// Constructor
colvarproxy_replicas();
/// Destructor
virtual ~colvarproxy_replicas();
/// \brief Indicate if multi-replica support is available and active
virtual int replica_enabled();
/// \brief Index of this replica
virtual int replica_index();
/// \brief Total number of replicas
virtual int num_replicas();
/// \brief Synchronize replica with others
virtual void replica_comm_barrier();
/// \brief Receive data from other replica
virtual int replica_comm_recv(char* msg_data, int buf_len, int src_rep);
/// \brief Send data to other replica
virtual int replica_comm_send(char* msg_data, int msg_len, int dest_rep);
/// Whether threaded parallelization should be used (TODO: make this a
/// cvm::deps feature)
smp_mode_t smp_mode;
};

69
lib/colvars/colvarproxy_io.cpp
View File

@ -7,10 +7,28 @@
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
#if defined(_WIN32) && !defined(__CYGWIN__)
// Using access() to check if a file exists (until we can assume C++14/17)
#if !defined(_WIN32) || defined(__CYGWIN__)
#include <unistd.h>
#include <direct.h>
#if defined(__has_include)
# if __has_include(<filesystem>)
# include <filesystem> // MSVC only defines __cpp_lib_filesystem after include
# endif
#endif
#else
#include <unistd.h>
#ifdef __cpp_lib_filesystem
#include <filesystem>
#endif
#endif
#if defined(_WIN32)
#include <io.h>
#endif
@ -64,6 +82,53 @@ int colvarproxy_io::set_frame(long int)
}
std::string colvarproxy_io::get_current_work_dir() const
{
#ifdef __cpp_lib_filesystem
return std::filesystem::current_path().string();
#else
// Legacy code
size_t constexpr buf_size = 3001;
char buf[buf_size];
#if defined(_WIN32) && !defined(__CYGWIN__)
char *getcwd_result = ::_getcwd(buf, buf_size);
#else
char *getcwd_result = ::getcwd(buf, buf_size);
#endif
if (getcwd_result == nullptr) {
cvm::error("Error: cannot read the current working directory.\n", COLVARS_INPUT_ERROR);
return std::string("");
}
return std::string(getcwd_result);
#endif
}
std::string colvarproxy_io::join_paths(std::string const &path1, std::string const &path2) const
{
#ifdef __cpp_lib_filesystem
return (std::filesystem::path(path1) / std::filesystem::path(path2)).string();
#else
// Legacy code
#if defined(_WIN32) && !defined(__CYGWIN__)
return (path1 + "\\" + path2);
#else
return (path1 + "/" + path2);
#endif
#endif
}
int colvarproxy_io::backup_file(char const *filename)
{
// Simplified version of NAMD_file_exists()

6
lib/colvars/colvarproxy_io.h
View File

@ -38,6 +38,12 @@ public:
// Returns error code
virtual int set_frame(long int);
/// Get the current working directory of this process
std::string get_current_work_dir() const;
/// Join two paths using the operating system's path separation
std::string join_paths(std::string const &path1, std::string const &path2) const;
/// \brief Rename the given file, before overwriting it
virtual int backup_file(char const *filename);

83
lib/colvars/colvarproxy_replicas.cpp
View File

@ -7,50 +7,103 @@
// If you wish to distribute your changes, please submit them to the
// Colvars repository at GitHub.
#include "colvarmodule.h"
#include "colvarproxy.h"
#include "colvarproxy_replicas.h"
colvarproxy_replicas::colvarproxy_replicas() {}
colvarproxy_replicas::colvarproxy_replicas()
{
#ifdef COLVARS_MPI
replicas_mpi_comm = MPI_COMM_NULL;
#endif
}
colvarproxy_replicas::~colvarproxy_replicas() {}
int colvarproxy_replicas::replica_enabled()
void colvarproxy_replicas::set_replicas_mpi_communicator(replicas_mpi_comm_t comm)
{
replicas_mpi_comm = comm;
#ifdef COLVARS_MPI
if (comm != MPI_COMM_NULL) {
MPI_Comm_rank(comm, &replicas_mpi_rank);
MPI_Comm_size(comm, &replicas_mpi_num);
cvm::log("Enabling multiple replicas: this is replica number " +
cvm::to_str(replica_index() + 1) + " of " + cvm::to_str(num_replicas()) + ".\n");
}
#endif
}
int colvarproxy_replicas::check_replicas_enabled()
{
#ifdef COLVARS_MPI
if (replicas_mpi_comm != MPI_COMM_NULL) {
return num_replicas() > 1 ? COLVARS_OK : COLVARS_ERROR;
}
return COLVARS_ERROR;
#else
return COLVARS_NOT_IMPLEMENTED;
#endif
}
int colvarproxy_replicas::replica_index()
{
return 0;
return replicas_mpi_rank;
}
int colvarproxy_replicas::num_replicas()
{
return 1;
return replicas_mpi_num;
}
void colvarproxy_replicas::replica_comm_barrier() {}
int colvarproxy_replicas::replica_comm_recv(char* /* msg_data */,
int /* buf_len */,
int /* src_rep */)
void colvarproxy_replicas::replica_comm_barrier()
{
return COLVARS_NOT_IMPLEMENTED;
#ifdef COLVARS_MPI
MPI_Barrier(replicas_mpi_comm);
#endif
}
int colvarproxy_replicas::replica_comm_send(char* /* msg_data */,
int /* msg_len */,
int /* dest_rep */)
int colvarproxy_replicas::replica_comm_recv(char *buffer, int buffer_length, int source_rank)
{
#ifdef COLVARS_MPI
MPI_Status status;
int retval = MPI_Recv(buffer, buffer_length, MPI_CHAR, source_rank, 0, replicas_mpi_comm, &status);
if (retval == MPI_SUCCESS) {
MPI_Get_count(&status, MPI_CHAR, &retval);
} else {
retval = 0;
}
return retval;
#else
(void)buffer;
(void)buffer_length;
(void)source_rank;
return COLVARS_NOT_IMPLEMENTED;
#endif
}
int colvarproxy_replicas::replica_comm_send(char *buffer, int buffer_length, int destination_rank)
{
#ifdef COLVARS_MPI
int retval = MPI_Send(buffer, buffer_length, MPI_CHAR, destination_rank, 0, replicas_mpi_comm);
if (retval == MPI_SUCCESS) {
retval = buffer_length;
} else {
retval = 0;
}
return retval;
#else
(void)buffer;
(void)buffer_length;
(void)destination_rank;
return COLVARS_NOT_IMPLEMENTED;
#endif
}

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