First push, taken from the previous Spintrum software model
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||||
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|
||||
<watches-manager>
|
||||
<configuration name="PythonConfigurationType">
|
||||
<watch expression="names" />
|
||||
<watch expression="self._all_projection_types" />
|
||||
</configuration>
|
||||
</watches-manager>
|
||||
</component>
|
||||
<component name="editorHistoryManager">
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||||
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||||
<entry file="file://$PROJECT_DIR$/Spintrum.py" />
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||||
<entry file="file://$PROJECT_DIR$/examples/MR.py" />
|
||||
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<entry file="file://$PROJECT_DIR$/examples/MR.py" />
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||||
<entry file="file://$PROJECT_DIR$/Spintrum.py" />
|
||||
<entry file="file://$PROJECT_DIR$/examples/spectrum.py" />
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|
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|
||||
<entry file="file:///usr/lib/python3/dist-packages/matplotlib/projections/__init__.py" />
|
||||
<entry file="file://$PROJECT_DIR$/Spintrum.py" />
|
||||
<entry file="file://$PROJECT_DIR$/__init__.py" />
|
||||
<entry file="file://$PROJECT_DIR$/spintrum/spintrumpy.py" />
|
||||
<entry file="file://$PROJECT_DIR$/examples/MR.py" />
|
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<entry file="file://$PROJECT_DIR$/spintrum/__init__.py">
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</provider>
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</entry>
|
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<entry file="file://$PROJECT_DIR$/examples/fit.py" />
|
||||
<entry file="file://$PROJECT_DIR$/examples/spectrum.py" />
|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/spectrum.py" />
|
||||
<entry file="file://$PROJECT_DIR$/run_build" />
|
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<entry file="file://$PROJECT_DIR$/Makefile">
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<entry file="file://$PROJECT_DIR$/README.md" />
|
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<entry file="file://$PROJECT_DIR$/run_build.sh" />
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<entry file="file://$PROJECT_DIR$/setup.py">
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<entry file="file://$PROJECT_DIR$/examples/data/benzeneFitResult.txt">
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|
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<entry file="file://$PROJECT_DIR$/examples/data/ethanolSignal.txt">
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|
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<entry file="file://$PROJECT_DIR$/examples/data/formamideSignal.txt">
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<folding />
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</state>
|
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</provider>
|
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</entry>
|
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<entry file="file://$PROJECT_DIR$/examples/TimeDependent/MagneticResonance.py">
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</folding>
|
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</state>
|
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</provider>
|
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</entry>
|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/acetonitrile.py">
|
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<provider selected="true" editor-type-id="text-editor">
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<caret line="2" column="0" selection-start-line="2" selection-start-column="0" selection-end-line="2" selection-end-column="0" />
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</folding>
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</state>
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</provider>
|
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</entry>
|
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<entry file="file://$PROJECT_DIR$/spintrum/meta.py">
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<provider selected="true" editor-type-id="text-editor">
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<caret line="1" column="0" selection-start-line="1" selection-start-column="0" selection-end-line="1" selection-end-column="0" />
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<folding />
|
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</state>
|
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</provider>
|
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|
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<entry file="file://$PROJECT_DIR$/examples/ZULF/benzene_fit.py">
|
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</folding>
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</state>
|
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|
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|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/ethanol_fit.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
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<caret line="2" column="0" selection-start-line="2" selection-start-column="0" selection-end-line="2" selection-end-column="0" />
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|
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|
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|
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<entry file="file://$PROJECT_DIR$/examples/ZULF/formicacid_fit.py">
|
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|
||||
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|
||||
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|
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</entry>
|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/methylformate.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
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<caret line="0" column="0" selection-start-line="0" selection-start-column="0" selection-end-line="0" selection-end-column="0" />
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|
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|
||||
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|
||||
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|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/methylformate_fit.py">
|
||||
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|
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|
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<caret line="2" column="0" selection-start-line="2" selection-start-column="0" selection-end-line="2" selection-end-column="0" />
|
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|
||||
<element signature="e#20#35#0" expanded="true" />
|
||||
</folding>
|
||||
</state>
|
||||
</provider>
|
||||
</entry>
|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/toluene.py">
|
||||
<provider selected="true" editor-type-id="text-editor">
|
||||
<state relative-caret-position="0">
|
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<caret line="0" column="0" selection-start-line="0" selection-start-column="0" selection-end-line="0" selection-end-column="0" />
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|
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|
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</folding>
|
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</state>
|
||||
</provider>
|
||||
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|
||||
<entry file="file://$PROJECT_DIR$/examples/ZULF/propylenecarbonate.py">
|
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|
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|
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|
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|
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|
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</provider>
|
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|
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<entry file="file://$PROJECT_DIR$/examples/ZULF/benzene.py">
|
||||
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|
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<entry file="file://$PROJECT_DIR$/examples/ZULF/formamide.py">
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|
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|
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<component name="masterDetails">
|
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<states>
|
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<state key="ScopeChooserConfigurable.UI">
|
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<settings>
|
||||
<splitter-proportions>
|
||||
<option name="proportions">
|
||||
<list>
|
||||
<option value="0.2" />
|
||||
</list>
|
||||
</option>
|
||||
</splitter-proportions>
|
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</settings>
|
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</state>
|
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</states>
|
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</component>
|
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</project>
|
||||
|
|
@ -0,0 +1,123 @@
|
|||
cmake_minimum_required(VERSION 3.0)
|
||||
PROJECT(Spintrum)
|
||||
|
||||
if(NOT DEFINED SpintrumPath)
|
||||
set(SpintrumPath ../)
|
||||
endif()
|
||||
if(NOT DEFINED PolymathPath)
|
||||
set(PolymathPath ../Polymath/)
|
||||
endif()
|
||||
if(NOT DEFINED OpenBLASPath)
|
||||
set(OpenBLASPath ../OpenBLAS_install/)
|
||||
endif()
|
||||
set(CMAKE_BUILD_TYPE Release)
|
||||
#add_definitions(-DPOLYMATH_DEBUG)
|
||||
|
||||
|
||||
set(VERSION 0.1.5)
|
||||
add_definitions(-DSPINTRUM_VERSION="${VERSION}")
|
||||
|
||||
INCLUDE_DIRECTORIES(${PolymathPath}/include)
|
||||
INCLUDE_DIRECTORIES(${PYTHON_INCLUDE_PATH})
|
||||
INCLUDE_DIRECTORIES(${SpintrumPath})
|
||||
INCLUDE_DIRECTORIES(${OpenBLASPath})
|
||||
|
||||
file(GLOB_RECURSE PolymathSrc
|
||||
"${PolymathPath}/src/*.cpp"
|
||||
)
|
||||
|
||||
file(GLOB_RECURSE includesList
|
||||
"${PolymathPath}/include/*.h"
|
||||
"${SpintrumPath}/common/*.h"
|
||||
)
|
||||
|
||||
OPTION(BUILD_SHARED_LIBS "turn OFF for .a libs" ON)
|
||||
|
||||
SET(SpintrumMain src/Spintrum.cpp)
|
||||
|
||||
ADD_LIBRARY(spintrum SHARED
|
||||
${SpintrumMain}
|
||||
${PolymathSrc}
|
||||
${includesList}
|
||||
)
|
||||
if(NOT WIN32)
|
||||
string(ASCII 27 Esc)
|
||||
set(ColourReset "${Esc}[m")
|
||||
set(ColourBold "${Esc}[1m")
|
||||
set(Red "${Esc}[31m")
|
||||
set(Green "${Esc}[32m")
|
||||
set(Yellow "${Esc}[33m")
|
||||
set(Blue "${Esc}[34m")
|
||||
set(Magenta "${Esc}[35m")
|
||||
set(Cyan "${Esc}[36m")
|
||||
set(White "${Esc}[37m")
|
||||
set(BoldRed "${Esc}[1;31m")
|
||||
set(BoldGreen "${Esc}[1;32m")
|
||||
set(BoldYellow "${Esc}[1;33m")
|
||||
set(BoldBlue "${Esc}[1;34m")
|
||||
set(BoldMagenta "${Esc}[1;35m")
|
||||
set(BoldCyan "${Esc}[1;36m")
|
||||
set(BoldWhite "${Esc}[1;37m")
|
||||
endif()
|
||||
|
||||
if (UNIX)
|
||||
IF(CMAKE_BUILD_TYPE MATCHES Release)
|
||||
message("${Blue}Building in Release mode${ColourReset}")
|
||||
message("${Red}Be aware that the optimization Ofast is used. If results don't make sense, change that to O3${ColourReset}")
|
||||
SET( CMAKE_CXX_FLAGS_RELEASE "-Ofast")
|
||||
SET( CMAKE_C_FLAGS_RELEASE "-Ofast")
|
||||
ELSE()
|
||||
message("${BoldRed}Building in Debug mode${ColourReset}")
|
||||
SET( CMAKE_CXX_FLAGS_RELEASE "-g")
|
||||
SET( CMAKE_C_FLAGS_RELEASE "-g")
|
||||
ENDIF(CMAKE_BUILD_TYPE MATCHES Release)
|
||||
|
||||
function(FindOpenBLAS path found)
|
||||
if(EXISTS "${path}/lib/libopenblas.so" OR EXISTS "${path}/lib/libopenblas.so.0")
|
||||
set(${found} "ON" PARENT_SCOPE)
|
||||
else()
|
||||
set(${found} "OFF" PARENT_SCOPE)
|
||||
endif()
|
||||
endfunction()
|
||||
|
||||
#find OpenBLAS
|
||||
set(OpenBLASTestPath ${OpenBLASPath})
|
||||
set(foundOpenBLAS "OFF")
|
||||
FindOpenBLAS("${OpenBLASTestPath}" "foundOpenBLAS")
|
||||
if(NOT ${foundOpenBLAS})
|
||||
set(OpenBLASTestPath "../${OpenBLASTestPath}")
|
||||
FindOpenBLAS("${OpenBLASTestPath}" "foundOpenBLAS")
|
||||
endif()
|
||||
|
||||
if(${foundOpenBLAS})
|
||||
message("${BoldGreen}I found a compiled version of OpenBLAS in ${OpenBLASPath}. Everything looks great!${ColourReset}")
|
||||
TARGET_LINK_LIBRARIES(spintrum -L"${OpenBLASPath}/lib")
|
||||
TARGET_LINK_LIBRARIES(spintrum -L"../${OpenBLASPath}/lib")
|
||||
else()
|
||||
message("${BoldRed}WARNING: OpenBLAS shared library was not found in ${OpenBLASPath}. This leads to a failure in compilation. Consider pulling and compiling OpenBLAS, or alternatively change CMakeLists.txt to fit your configuration.${ColourReset}")
|
||||
message("${BoldGreen}I will try to fix this problem by considering that your system may have OpenBLAS installed.${ColourReset}")
|
||||
add_definitions(-DOPENBLAS_FROM_SYSTEM)
|
||||
endif()
|
||||
|
||||
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -fPIC -shared -pedantic-errors")
|
||||
file(MAKE_DIRECTORY ${CMAKE_SOURCE_DIR}/spintrum/lib/)
|
||||
SET(LIBRARY_OUTPUT_PATH ${CMAKE_SOURCE_DIR}/spintrum/lib/) #output libspintrum.so to this directory
|
||||
TARGET_LINK_LIBRARIES(spintrum libopenblas.so)
|
||||
TARGET_LINK_LIBRARIES(spintrum)
|
||||
endif (UNIX)
|
||||
|
||||
if (MSVC)
|
||||
include (GenerateExportHeader)
|
||||
set(openblasdir D:/libs/OpenBLAS-0.2.19)
|
||||
set(openblasbuilddir D:/libs/OpenBLAS-0.2.19-build-32/)
|
||||
add_definitions(-DISWIN32)
|
||||
TARGET_LINK_LIBRARIES(spintrum -lopenblas)
|
||||
TARGET_LINK_LIBRARIES(spintrum D:/libs/OpenBLAS-0.2.19-build-32/lib/libopenblas.lib)
|
||||
TARGET_LINK_LIBRARIES(spintrum)
|
||||
INCLUDE_DIRECTORIES(include ${openblasdir})
|
||||
GENERATE_EXPORT_HEADER(m
|
||||
BASE_NAME m
|
||||
EXPORT_MACRO_NAME M_EXPORTS
|
||||
EXPORT_FILE_NAME m_exports.h
|
||||
STATIC_DEFINE SHARED_EXPORTS_BUILT_AS_STATIC)
|
||||
endif(MSVC)
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
default:
|
||||
chmod +x ./run_build.sh
|
||||
chmod +x ./run_install.sh
|
||||
./run_build.sh
|
||||
|
||||
install:
|
||||
./run_install.sh
|
||||
|
||||
clean:
|
||||
rm -rf dist
|
||||
rm -rf build
|
||||
rm -rf __pycache__
|
||||
rm -rf spintrum.egg-info
|
||||
rm -rf spintrum/lib
|
||||
rm -rf spintrum/*.pyc
|
||||
rm -rf spintrum/__pycache__
|
||||
|
|
@ -0,0 +1,65 @@
|
|||
# Spintrum
|
||||
A high-performance library for spin simulations, written by Samer Afach
|
||||
|
||||
|
||||
####purpose
|
||||
Spintrum creates an interface between a high-performance and low-level language (C/C++) and an easy to use and high level language (Python).
|
||||
|
||||
##Installation
|
||||
|
||||
Spintrum is supported only on Linux/Unix systems, and is primarily tested on Debian. For explanation, look at the FAQ below. If you'd like to compile Spintrum on operating systems other than debian, your efforts to do it will be minimal.
|
||||
|
||||
#####Prerequisites
|
||||
- Linux/Unix (preferably Debian)
|
||||
- OpenBLAS (read below)
|
||||
- Polymath (read below)
|
||||
- cmake
|
||||
- Python 3.4+
|
||||
- g++ 4.8+
|
||||
|
||||
#####In Python, the following libraries are required
|
||||
- numpy
|
||||
- scipy
|
||||
- mpmath
|
||||
- matplotlib
|
||||
|
||||
|
||||
#####Do I need to compile OpenBLAS?
|
||||
This depends on the performance you're trying to achieve. OpenBLAS, when compiled, creates binaries that are processor-specific, in order to achieve the best possible performance. In order to exploit this feature, it's recommended that you compile OpenBLAS.
|
||||
|
||||
Don't panic, as you don't have to do this yourself from scratch. The script `get_openblas.sh` should do this for you. It clones the OpenBLAS repository, and changes the optimization level of the compiler settings, and does the compilation. Run it using `sh get_openblas.sh`.
|
||||
|
||||
#####What optimization level should I take for OpenBLAS?
|
||||
The default optimization level for OpenBLAS is `-O2`, which is fair. The script `get_openblas.sh` changes all optimization flags by default to `-Ofast`. This is an extreme exaggeration, and may cause [problems](http://gcc.gnu.org/onlinedocs/gcc/Optimize-Options.html). I recommend using O2 for tests, and going to Ofast once everything is prepared. Please read [the link](http://gcc.gnu.org/onlinedocs/gcc/Optimize-Options.html) that explains what these optimization flags mean. Then, edit the file `set_openblas_optimization.py`, and change the variable `target_optimization` to the desired optimization level.
|
||||
|
||||
#####What if I don't want to compile OpenBLAS?
|
||||
The compilation script in the directory Spintrum expects a compiled version of OpenBLAS, either in the default directory that the script `get_openblas.sh` downloads and installs to, or an installed version of OpenBLAS in the operating system. Keep in mind that the default OpenBLAS in the Linux operating systems are not generally optimized for your processor.
|
||||
|
||||
#####Do I need Polymath?
|
||||
Definitely! Polymath is a C++ interface to BLAS. It was also written by Spintrum team to separate the Maths library from the programming. Use the script `get_polymath.sh` to clone Polymath.
|
||||
|
||||
#####How to install?
|
||||
In the directory `Spintrum`, there's a `Makefile` that will do everything for you. Simply run the command `make` in that directory, and then if everything runs correctly, and no error messages are issued, run `make install` as root/superuser to install spintrum on your Python installation.
|
||||
|
||||
#####How to install missing prerequisites on Debian?
|
||||
Simply run the following in the terminal (as superuser/root):
|
||||
|
||||
```sh
|
||||
# apt-get install build-essential cmake g++ gcc python3
|
||||
# pip3 install numpy scipy mpmath matplotlib
|
||||
```
|
||||
|
||||
Note: The `#` means that these commands have to be executed as root. Don't literally type that `#` in the terminal.
|
||||
|
||||
#####Testing whether it works
|
||||
After a successful installation, simply try the examples in the `examples` directory. They should all work, assuming you have
|
||||
|
||||
|
||||
#####Caveat about Jupyter
|
||||
Spintrum works fine on Jupyter, except that the `stdout` and `stderr` output cannot be seen on Jupyter notebooks for technical reasons. So, if there's a message from the low-level C/C++, it won't be seen. Although unlikely, but in case you have an error and you can't figure out the reason, try running the script in terminal, and see whether the C/C++ interface is reporting an error.
|
||||
|
||||
|
||||
##FAQ
|
||||
- **Q:** Why is spintrum not supported on Windows?
|
||||
- **A:** Ignoring that Windows is way slower than Linux for calculations; Spintrum uses the well-known high-performance linear algebra library OpenBLAS. And since Python 3.5+ is compiled on Visual Studio 2015, and since Spintrum uses ctypes, which is the shared-library interface of Python, binary compatibility has to be achieved between Python and the compiled Spintrum library. On the other hand, OpenBLAS does not support compilation on Visual Studio with 64-bit (it supports only 32-bit), meaning that only small spin systems will be properly supported, since memory of 4+ GB cannot be used, which is not worth the effort, as too many changes have to be done to make Spintrum compatible with Windows. In the worst case, use a VMWare Workstation on your Windows Machine, and you'll get the best performance.
|
||||
|
||||
|
|
@ -0,0 +1,52 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import matplotlib as mpl
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
|
||||
|
||||
def run(dirs):
|
||||
gammas = [10] #Hz/T
|
||||
jCouplings = [[0]]
|
||||
|
||||
BThermal = 10e0
|
||||
T2 = 10
|
||||
sampleRate = 1e4
|
||||
T= 1/sampleRate
|
||||
B0=10.
|
||||
B1=0.3e0
|
||||
points = 1650
|
||||
f = B0*gammas[0]
|
||||
bx = np.array([np.sin(2*math.pi*f*t/sampleRate)*B1 for t in range(points)])
|
||||
by = np.array([np.cos(2*math.pi*f*t/sampleRate)*B1 for t in range(points)])
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': B0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_DEPENDENT,
|
||||
{'threads': 4, 'samplingRate': sampleRate, 'store': dirs,
|
||||
'input': {'Bx': bx, 'By': by}})
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinOperations=spinOp)
|
||||
return signal
|
||||
|
||||
#this will result in points in the form xyzxyzxyz (order doesn't make a difference)
|
||||
data = run('xyz')
|
||||
|
||||
mpl.rcParams['legend.fontsize'] = 10
|
||||
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
datanp = np.transpose(np.split(np.array(data),len(data)/3))
|
||||
|
||||
ax.plot(datanp[0], datanp[1], datanp[2], label='parametric curve')
|
||||
ax.legend()
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,61 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,1070.8e4,1070.8e4,-431.6e4]
|
||||
multips = [2,2,2,2,2,2]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,0,0,136.25,-9.94,-2.03],
|
||||
[0,0,0,136.25,-9.94,-2.03],
|
||||
[0,0,0,136.25,-9.94,-2.03],
|
||||
[0,0,0,0,56.94,2.9],
|
||||
[0,0,0,0,0,-17.53],
|
||||
[0,0,0,0,0,0],
|
||||
]
|
||||
|
||||
BThermal = 1.8e0
|
||||
T2 = 10
|
||||
sampleRate = 2e3
|
||||
T= 1/sampleRate
|
||||
points = 80000
|
||||
|
||||
gammah = 2*math.pi*4257.7
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': 4})
|
||||
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
spinOperations=spinOp)
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
print("Simulation lastet: " + repr(time.time()-start_time) + "s")
|
||||
|
||||
plt.plot(signal)
|
||||
plt.show()
|
||||
|
||||
fft = spintrum.FFTSpectralDensity(signal, sampleRate)
|
||||
|
||||
plt.plot(fft['x'], fft['y'])
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,62 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,1070.8e4]
|
||||
multips = [2,2,2,2,2,2,2]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,7.54,1.38,0.661,1.38,7.54,158.354],
|
||||
[0,0,7.543,1.377,0.658,1.373,1.133],
|
||||
[0,0,0,7.535,1.382,0.658,7.607],
|
||||
[0,0,0,0,7.535,1.377,-1.296],
|
||||
[0,0,0,0,0,7.543,7.607],
|
||||
[0,0,0,0,0,0,1.133],
|
||||
[0,0,0,0,0,0,0]
|
||||
]
|
||||
|
||||
BThermal = 1.8e0
|
||||
T2 = 10
|
||||
sampleRate = 1e3
|
||||
T= 1/sampleRate
|
||||
points = 80000
|
||||
|
||||
gammah = 2*math.pi*4257.7
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': 4})
|
||||
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
spinOperations=spinOp)
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
print("Simulation lastet: " + repr(time.time()-start_time) + "s")
|
||||
|
||||
plt.plot(signal)
|
||||
plt.show()
|
||||
|
||||
fft = spintrum.FFTSpectralDensity(signal, sampleRate)
|
||||
|
||||
plt.plot(fft['x'], fft['y'])
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,155 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import scipy.optimize
|
||||
import multiprocessing
|
||||
import mpmath
|
||||
|
||||
mpmath.mp.dps = 25
|
||||
|
||||
|
||||
def filter_spectrum(spec, freq_lim):
|
||||
x_axis = np.array([])
|
||||
y_axis = np.array([])
|
||||
for i in range(len(freq_lim)):
|
||||
for j in range(len(spec["x"])):
|
||||
if freq_lim[i][0] <= spec["x"][j] <= freq_lim[i][1]:
|
||||
x_axis = np.append(x_axis,spec["x"][j])
|
||||
y_axis = np.append(y_axis,spec["y"][j])
|
||||
return {"x": x_axis, "y": y_axis}
|
||||
|
||||
|
||||
with open("../data/benzeneSignal.txt") as f:
|
||||
data = f.readlines()
|
||||
data = np.array(list(map(np.double,data)))
|
||||
data = data - np.mean(data)
|
||||
|
||||
#defining initial parameters
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,1070.8e4]
|
||||
multiplicities = [2, 2, 2, 2, 2, 2, 2]
|
||||
|
||||
gammah = 2*math.pi*4257.7e4
|
||||
BThermal = 1.8e0
|
||||
T2 = 1
|
||||
points = len(data)
|
||||
sample_rate = 2000
|
||||
spectrum_range = [[5, 50], [80, 119], [121, 179], [181, 239], [241, 299]]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0,0],
|
||||
]
|
||||
|
||||
|
||||
experimental_spectrum = filter_spectrum(spintrum.FFTSpectralDensity(data, sample_rate), spectrum_range)
|
||||
|
||||
|
||||
gen = spintrum.SpinSimulator(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multiplicities,
|
||||
doPrint=False)
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sample_rate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': multiprocessing.cpu_count()})
|
||||
|
||||
gen.update_parameters(spinOperations=spinOp, jCouplings=jCouplings, gyromagneticRatios=gammas)
|
||||
|
||||
|
||||
def generate_spectrum(params):
|
||||
|
||||
amplitude = params[13]
|
||||
T2 = params[14]
|
||||
jCouplings = \
|
||||
[
|
||||
[0, params[0], params[1], params[2],params[1],params[0],params[3]],
|
||||
[0, 0, params[4], params[5], params[6], params[7], params[8]],
|
||||
[0, 0, 0, params[9], params[10], params[6], params[11]],
|
||||
[0, 0, 0, 0, params[9], params[5], params[12]],
|
||||
[0, 0, 0, 0, 0, params[4], params[11]],
|
||||
[0, 0, 0, 0, 0, 0, params[8]],
|
||||
[0, 0, 0, 0, 0, 0, 0],
|
||||
]
|
||||
|
||||
|
||||
gen.update_parameters(jCouplings=jCouplings)
|
||||
|
||||
signal = amplitude*gen.simulate()
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i] * math.exp(-i / sample_rate / T2) for i in range(len(signal))]
|
||||
|
||||
fft = filter_spectrum(spintrum.FFTSpectralDensity(signal, sample_rate), spectrum_range)
|
||||
|
||||
# plt.plot(fft['x'],fft['y'],realSpectrum['x'],realSpectrum['y'])
|
||||
# plt.show()
|
||||
|
||||
return fft
|
||||
|
||||
def objective_func(params):
|
||||
print(params)
|
||||
spect = generate_spectrum(params)
|
||||
func_value = np.sqrt(np.sum((spect['y'] - experimental_spectrum['y']) ** 2))
|
||||
print('Objective function value:', func_value)
|
||||
return func_value
|
||||
|
||||
pars = np.array([7.54,1.38,0.661,158.354,7.543,1.377,0.658,1.373,1.133,7.535,1.382,7.607,-1.296,0.00002,6])
|
||||
#pars = np.array([-1.06785235e+00,2.26791767e+02,4.26684847e+00,4.53620118e-05,2.73284204e+00])
|
||||
|
||||
# get_objective_func(pars)
|
||||
|
||||
optimum_params = scipy.optimize.fmin(objective_func, pars, ftol = 5.0e-13, maxfun = 1)
|
||||
|
||||
opt_j_couplings = mpmath.matrix([
|
||||
[0, optimum_params[0], optimum_params[1], optimum_params[2], optimum_params[1], optimum_params[0], optimum_params[3]],
|
||||
[0, 0, optimum_params[4], optimum_params[5], optimum_params[6], optimum_params[7], optimum_params[8]],
|
||||
[0, 0, 0, optimum_params[9], optimum_params[10], optimum_params[6], optimum_params[11]],
|
||||
[0, 0, 0, 0, optimum_params[9], optimum_params[5], optimum_params[12]],
|
||||
[0, 0, 0, 0, 0, optimum_params[4], optimum_params[11]],
|
||||
[0, 0, 0, 0, 0, 0, optimum_params[8]],
|
||||
[0, 0, 0, 0, 0, 0, 0],
|
||||
])
|
||||
|
||||
CorrelationMatrix = spintrum.get_correlation_matrix(optimum_params, generate_spectrum, objective_func)
|
||||
print('Correlation matrix: ', '\n', CorrelationMatrix)
|
||||
|
||||
print('Parameters at minimum: ','\n', optimum_params)
|
||||
errorbars = spintrum.get_errorbars(CorrelationMatrix)
|
||||
print('Standard deviations of parameters: ','\n',errorbars)
|
||||
|
||||
#writout to file
|
||||
np.set_printoptions(suppress=True, precision=20)
|
||||
fr = open("../data/benzeneFitResult.txt","w")
|
||||
fr.write('Minimum at J-couplings:\n')
|
||||
fr.write(str(opt_j_couplings) + '\n')
|
||||
fr.write('Minimum at paramters:\n')
|
||||
fr.write(str(optimum_params) + '\n')
|
||||
fr.write('Parameters standard deviations:\n')
|
||||
fr.write(str(errorbars)+'\n')
|
||||
fr.write('Parameters correlation matrix:\n')
|
||||
fr.write(str(CorrelationMatrix)+'\n')
|
||||
fr.write('Minimum objective function value: ' + str(objective_func(optimum_params)))
|
||||
fr.close()
|
||||
|
||||
fft_final = generate_spectrum(optimum_params)
|
||||
|
||||
plt.plot(fft_final['x'], fft_final['y'], experimental_spectrum['x'], experimental_spectrum['y'])
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,155 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import scipy.optimize
|
||||
import multiprocessing
|
||||
import mpmath as mp
|
||||
|
||||
mp.mp.dps = 25
|
||||
|
||||
|
||||
def filter_spectrum(spec, freq_lim):
|
||||
x_axis = np.array([])
|
||||
y_axis = np.array([])
|
||||
for i in range(len(freq_lim)):
|
||||
for j in range(len(spec["x"])):
|
||||
if freq_lim[i][0] <= spec["x"][j] <= freq_lim[i][1]:
|
||||
x_axis = np.append(x_axis,spec["x"][j])
|
||||
y_axis = np.append(y_axis,spec["y"][j])
|
||||
return {"x": x_axis, "y": y_axis}
|
||||
|
||||
|
||||
#defining initial parameters
|
||||
|
||||
with open("../data/ethanolSignal.txt") as f:
|
||||
data = f.readlines()
|
||||
data = np.array(list(map(np.double,data)))
|
||||
data = data - np.mean(data)
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,1070.8e4]
|
||||
multips = [2,2,2,2,2,2]
|
||||
|
||||
gammah = 2*math.pi*4257.7e4
|
||||
BThermal = 1.8e0
|
||||
T2 = 1
|
||||
points = len(data)
|
||||
sampleRate = 2000
|
||||
spectrumRange = [[0,299]]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0],
|
||||
[0,0,0,0,0,0],
|
||||
]
|
||||
|
||||
experimental_spectrum = filter_spectrum(spintrum.FFTSpectralDensity(data, 2000), spectrumRange)
|
||||
|
||||
|
||||
gen = spintrum.SpinSimulator(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
doPrint=False)
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': multiprocessing.cpu_count()})
|
||||
|
||||
gen.update_parameters(spinOperations=spinOp, jCouplings=jCouplings, gyromagneticRatios=gammas)
|
||||
|
||||
|
||||
|
||||
def generate_spectrum(params):
|
||||
|
||||
amplitude = params[3]
|
||||
T2 = params[4]
|
||||
jCouplings = \
|
||||
[
|
||||
[0, 0, 0, params[0],params[1],params[1]],
|
||||
[0, 0, 0, params[0],params[1],params[1]],
|
||||
[0, 0, 0, params[0],params[1],params[1]],
|
||||
[0, 0, 0, 0, 0, params[2]],
|
||||
[0, 0, 0, 0, 0, params[2]],
|
||||
[0, 0, 0, 0, 0, 0],
|
||||
]
|
||||
|
||||
|
||||
gen.update_parameters(jCouplings=jCouplings)
|
||||
|
||||
signal = amplitude*gen.simulate()
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
fft = filter_spectrum(spintrum.FFTSpectralDensity(signal, 2000), spectrumRange)
|
||||
|
||||
# plt.plot(fft['x'],fft['y'],realSpectrum['x'],realSpectrum['y'])
|
||||
# plt.show()
|
||||
|
||||
return fft
|
||||
|
||||
|
||||
def objective_func(params):
|
||||
print(params)
|
||||
spect = generate_spectrum(params)
|
||||
funcValue = np.sqrt(np.sum((spect['y'] - experimental_spectrum['y']) ** 2))
|
||||
print('Objective function value: ',funcValue)
|
||||
return funcValue
|
||||
|
||||
|
||||
|
||||
pars = np.array([7.1,141.0,-4.65,0.00002,6])
|
||||
#pars = np.array([-1.06785235e+00,2.26791767e+02,4.26684847e+00,l4.53620118e-05,2.73284204e+00])
|
||||
|
||||
# get_objective_func(pars)
|
||||
|
||||
optimum_params = scipy.optimize.fmin(objective_func, pars, ftol = 5.0e-13, maxfun = 1)
|
||||
|
||||
opt_j_couplings = mp.matrix([
|
||||
[0, 0, 0, optimum_params[0], optimum_params[1], optimum_params[1]],
|
||||
[0, 0, 0, optimum_params[0], optimum_params[1], optimum_params[1]],
|
||||
[0, 0, 0, optimum_params[0], optimum_params[1], optimum_params[1]],
|
||||
[0, 0, 0, 0, 0, optimum_params[2]],
|
||||
[0, 0, 0, 0, 0, optimum_params[2]],
|
||||
[0, 0, 0, 0, 0, 0],
|
||||
])
|
||||
|
||||
CorrelationMatrix = spintrum.get_correlation_matrix(optimum_params, generate_spectrum, objective_func)
|
||||
print('Correlation matrix: ','\n',CorrelationMatrix)
|
||||
|
||||
print('Parameters at minimum: ','\n', optimum_params)
|
||||
errorbars = spintrum.get_errorbars(CorrelationMatrix)
|
||||
print('Standard deviations of parameters: ','\n',errorbars)
|
||||
|
||||
#writout to file
|
||||
np.set_printoptions(suppress=True,precision=20)
|
||||
fr = open("../data/ethanolFitResult.txt","w")
|
||||
fr.write('Minimum at J-couplings:\n')
|
||||
fr.write(str(opt_j_couplings) + '\n')
|
||||
fr.write('Minimum at paramters:\n')
|
||||
fr.write(str(optimum_params) + '\n')
|
||||
fr.write('Parameters standard deviations:\n')
|
||||
fr.write(str(errorbars)+'\n')
|
||||
fr.write('Parameters correlation matrix:\n')
|
||||
fr.write(str(CorrelationMatrix)+'\n')
|
||||
fr.write('Minimum objective function value: ' + str(objective_func(optimum_params)))
|
||||
fr.close()
|
||||
|
||||
fft_final = generate_spectrum(optimum_params)
|
||||
|
||||
plt.plot(fft_final['x'], fft_final['y'], experimental_spectrum['x'], experimental_spectrum['y'])
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,80 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
gammas = [-431.6e4,4257.7e4,4257.7e4,4257.7e4]
|
||||
multips = [2,2,2,2]
|
||||
|
||||
jCouplings = \
|
||||
[
|
||||
[0,-89.3,-89.3,-13.5],
|
||||
[0,0,0,8],
|
||||
[0,0,0,8],
|
||||
[0,0,0,0],
|
||||
|
||||
]
|
||||
|
||||
BThermal = 1.8e0
|
||||
T2 = 5
|
||||
sampleRate = 2e3
|
||||
T= 1/sampleRate
|
||||
points = 80000
|
||||
specRange = [[0,50],[100,200]]
|
||||
|
||||
gammah = 2*math.pi*4257.7e4
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': 4})
|
||||
|
||||
def filterSpectrum(spec, freqLim):
|
||||
xAxis = np.array([])
|
||||
yAxis = np.array([])
|
||||
for i in range(len(freqLim)):
|
||||
for j in range(len(spec["x"])):
|
||||
if spec["x"][j] >= freqLim[i][0] and spec["x"][j] <= freqLim[i][1]:
|
||||
xAxis = np.insert(xAxis,-0,spec["x"][j])
|
||||
yAxis = np.insert(yAxis,-0,spec["y"][j])
|
||||
|
||||
return {"x": xAxis, "y": yAxis}
|
||||
|
||||
|
||||
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
spinOperations=spinOp)
|
||||
|
||||
print("Simulation lastet: " + repr(time.time()-start_time) + "s")
|
||||
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
|
||||
plt.plot(signal)
|
||||
plt.show()
|
||||
|
||||
FFT = spintrum.FFTSpectralDensity(signal, sampleRate)
|
||||
|
||||
fft = filterSpectrum(FFT,specRange)
|
||||
|
||||
|
||||
plt.plot(fft['x'], fft['y'])
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,142 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import scipy.optimize
|
||||
import multiprocessing
|
||||
import mpmath as mp
|
||||
|
||||
|
||||
def filter_spectrum(spec, freq_lim):
|
||||
x_axis = np.array([])
|
||||
y_axis = np.array([])
|
||||
for i in range(len(freq_lim)):
|
||||
for j in range(len(spec["x"])):
|
||||
if freq_lim[i][0] <= spec["x"][j] <= freq_lim[i][1]:
|
||||
x_axis = np.append(x_axis,spec["x"][j])
|
||||
y_axis = np.append(y_axis,spec["y"][j])
|
||||
return {"x": x_axis, "y": y_axis}
|
||||
|
||||
|
||||
with open("../data/formicacidSignal.txt") as f:
|
||||
data = f.readlines()
|
||||
data = np.array(list(map(np.double,data)))
|
||||
data = data - np.mean(data)
|
||||
|
||||
|
||||
gammas = [4257.7e4,1070.8e4]
|
||||
multips = [2,2]
|
||||
|
||||
gammah = 2*math.pi*4257.7e4
|
||||
BThermal = 1.8e0
|
||||
T2 = 1
|
||||
points = len(data)
|
||||
sampleRate = 2000
|
||||
spectrumRange = [[210,230]]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,0],
|
||||
[0,0],
|
||||
]
|
||||
|
||||
|
||||
realSpectrum = filter_spectrum(spintrum.FFTSpectralDensity(data, 2000), spectrumRange)
|
||||
|
||||
|
||||
gen = spintrum.SpinSimulator(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
doPrint=False)
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': multiprocessing.cpu_count()})
|
||||
|
||||
gen.update_parameters(spinOperations=spinOp, jCouplings=jCouplings, gyromagneticRatios=gammas)
|
||||
|
||||
|
||||
def generate_spectrum(params):
|
||||
|
||||
amplitude = params[1]
|
||||
T2 = params[2]
|
||||
jCouplings = \
|
||||
[
|
||||
[0, params[0]],
|
||||
[0, 0],
|
||||
|
||||
]
|
||||
|
||||
|
||||
gen.update_parameters(jCouplings=jCouplings)
|
||||
|
||||
signal = amplitude*gen.simulate()
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
fft = filter_spectrum(spintrum.FFTSpectralDensity(signal, 2000), spectrumRange)
|
||||
|
||||
# plt.plot(fft['x'],fft['y'],realSpectrum['x'],realSpectrum['y'])
|
||||
# plt.show()
|
||||
|
||||
return fft
|
||||
|
||||
|
||||
|
||||
def objective_func(params):
|
||||
print(params)
|
||||
spect = generate_spectrum(params)
|
||||
funcValue = np.sqrt(np.sum((spect['y'] - realSpectrum['y'])**2))
|
||||
print('Objective function value: ',funcValue)
|
||||
return funcValue
|
||||
|
||||
|
||||
|
||||
pars = np.array([222.5,0.000003,6])
|
||||
#pars = np.array([-1.06785235e+00,2.26791767e+02,4.26684847e+00,4.53620118e-05,2.73284204e+00])
|
||||
|
||||
# get_objective_func(pars)
|
||||
|
||||
optimum_params = scipy.optimize.fmin(objective_func, pars, ftol = 5.0e-13, maxfun = 1e6)
|
||||
|
||||
optjCouplings = mp.matrix([
|
||||
[0, optimum_params[0]],
|
||||
[0, 0],
|
||||
])
|
||||
|
||||
CorrelationMatrix = spintrum.get_correlation_matrix(optimum_params, generate_spectrum, objective_func)
|
||||
print('Correlation matrix: ','\n',CorrelationMatrix)
|
||||
|
||||
print('Parameters at minimum: ','\n', optimum_params)
|
||||
errorbars = spintrum.get_errorbars(CorrelationMatrix)
|
||||
print('Standard deviations of parameters: ','\n',errorbars)
|
||||
|
||||
#writout to file
|
||||
np.set_printoptions(suppress=True,precision=20)
|
||||
fr = open("../data/formicacidFitResult.txt","w")
|
||||
fr.write('Minimum at J-couplings:\n')
|
||||
fr.write(str(optjCouplings)+'\n')
|
||||
fr.write('Minimum at paramters:\n')
|
||||
fr.write(str(optimum_params) + '\n')
|
||||
fr.write('Parameters standard deviations:\n')
|
||||
fr.write(str(errorbars)+'\n')
|
||||
fr.write('Parameters correlation matrix:\n')
|
||||
fr.write(str(CorrelationMatrix)+'\n')
|
||||
fr.write('Minimum objective function value: ' + str(objective_func(optimum_params)))
|
||||
fr.close()
|
||||
|
||||
fft_final = generate_spectrum(optimum_params)
|
||||
|
||||
plt.plot(fft_final['x'],fft_final['y'],realSpectrum['x'],realSpectrum['y'])
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,60 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,4257.7e4,1070.8e4]
|
||||
multips = [2,2,2,2,2]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,-0.8,-0.8,-0.8,226.8],
|
||||
[0,0,0,0,4.0],
|
||||
[0,0,0,0,4.0],
|
||||
[0,0,0,0,4.0],
|
||||
[0,0,0,0,0],
|
||||
]
|
||||
|
||||
BThermal = 1.8e0
|
||||
T2 = 10
|
||||
sampleRate = 2e3
|
||||
T= 1/sampleRate
|
||||
points = 80000
|
||||
|
||||
gammah = 2*math.pi*4257.7
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': 4})
|
||||
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
spinOperations=spinOp)
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
print("Simulation lastet: " + repr(time.time()-start_time) + "s")
|
||||
|
||||
plt.plot(signal)
|
||||
plt.show()
|
||||
|
||||
fft = spintrum.FFTSpectralDensity(signal, sampleRate)
|
||||
|
||||
plt.plot(fft['x'], fft['y'])
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,156 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import scipy.optimize
|
||||
import multiprocessing
|
||||
import mpmath as mp
|
||||
|
||||
|
||||
def filter_spectrum(spec, freq_lim):
|
||||
x_axis = np.array([])
|
||||
y_axis = np.array([])
|
||||
for i in range(len(freq_lim)):
|
||||
for j in range(len(spec["x"])):
|
||||
if freq_lim[i][0] <= spec["x"][j] <= freq_lim[i][1]:
|
||||
x_axis = np.append(x_axis,spec["x"][j])
|
||||
y_axis = np.append(y_axis,spec["y"][j])
|
||||
return {"x": x_axis, "y": y_axis}
|
||||
|
||||
|
||||
#defining initial parameters
|
||||
|
||||
with open("../data/methylformateSignal.txt") as f:
|
||||
data = f.readlines()
|
||||
data = np.array(list(map(np.double,data)))
|
||||
data = data - np.mean(data)
|
||||
|
||||
gammas = [4257.7e4,4257.7e4,4257.7e4,4257.7e4,1070.8e4]
|
||||
multips = [2,2,2,2,2]
|
||||
|
||||
gammah = 2*math.pi*4257.7e4
|
||||
BThermal = 1.8e0
|
||||
T2 = 1
|
||||
points = len(data)
|
||||
sampleRate = 2000
|
||||
spectrumRange = [[70,119],[121,179],[181,239],[241,299]]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,0,0,0,0],
|
||||
[0,0,0,0,0],
|
||||
[0,0,0,0,0],
|
||||
[0,0,0,0,0],
|
||||
[0,0,0,0,0],
|
||||
]
|
||||
|
||||
experimental_spectrum = filter_spectrum(spintrum.FFTSpectralDensity(data, 2000), spectrumRange)
|
||||
|
||||
|
||||
gen = spintrum.SpinSimulator(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
doPrint=False)
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': multiprocessing.cpu_count()})
|
||||
|
||||
gen.update_parameters(spinOperations=spinOp, jCouplings=jCouplings, gyromagneticRatios=gammas)
|
||||
|
||||
|
||||
def generate_spectrum(params):
|
||||
|
||||
amplitude = params[3]
|
||||
T2 = params[4]
|
||||
jCouplings = \
|
||||
[
|
||||
[0, params[0], params[0], params[0],params[1]],
|
||||
[0, 0, 0, 0, params[2]],
|
||||
[0, 0, 0, 0, params[2]],
|
||||
[0, 0, 0, 0, params[2]],
|
||||
[0, 0, 0, 0, 0],
|
||||
|
||||
]
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4 * math.pi / gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': np.float(params[5]), 'By': 0, 'Bz': np.float(params[6])})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': multiprocessing.cpu_count()})
|
||||
|
||||
gen.update_parameters(jCouplings=jCouplings, spinOperations=spinOp)
|
||||
|
||||
signal = amplitude*gen.simulate()
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
fft = filter_spectrum(spintrum.FFTSpectralDensity(signal, 2000), spectrumRange)
|
||||
|
||||
# plt.plot(fft['x'],fft['y'],realSpectrum['x'],realSpectrum['y'])
|
||||
# plt.show()
|
||||
|
||||
return fft
|
||||
|
||||
|
||||
|
||||
def objective_func(params):
|
||||
print(params)
|
||||
spect = generate_spectrum(params)
|
||||
funcValue = np.sqrt(np.sum((spect['y'] - experimental_spectrum['y']) ** 2))
|
||||
print('Objective function value: ',funcValue)
|
||||
return funcValue
|
||||
|
||||
|
||||
|
||||
pars = np.array([-1.06785235e+00,2.26791767e+02,4.26684847e+00,4.53620118e-05,2.73284204e+00,3.11541220e-09,2.80718054e-09])
|
||||
#pars = np.array([-1.06785235e+00,2.26791767e+02,4.26684847e+00,4.53620118e-05,2.73284204e+00])
|
||||
|
||||
# get_objective_func(pars)
|
||||
|
||||
optimum_params = scipy.optimize.fmin(objective_func, pars, ftol = 5.0e-13, maxfun = 1)
|
||||
optjCouplings = mp.matrix([[0, optimum_params[0], optimum_params[0], optimum_params[0], optimum_params[1]], [0, 0, 0, 0, optimum_params[2]], [0, 0, 0, 0, optimum_params[2]], [0, 0, 0, 0, optimum_params[2]], [0, 0, 0, 0, 0]])
|
||||
|
||||
CorrelationMatrix = spintrum.get_correlation_matrix(optimum_params, generate_spectrum, objective_func)
|
||||
print('Correlation matrix: ','\n',CorrelationMatrix)
|
||||
|
||||
print('Parameters at minimum: ','\n', optimum_params)
|
||||
errorbars = spintrum.get_errorbars(CorrelationMatrix)
|
||||
print('Standard deviations of parameters: ','\n',errorbars)
|
||||
|
||||
#writout to file
|
||||
np.set_printoptions(suppress=True,precision=20)
|
||||
fr = open("../data/methylformateFitResult.txt","w")
|
||||
fr.write('Minimum at J-couplings:\n')
|
||||
fr.write(str(optjCouplings)+'\n')
|
||||
fr.write('Minimum at paramters:\n')
|
||||
fr.write(str(optimum_params) + '\n')
|
||||
fr.write('Parameters standard deviations:\n')
|
||||
fr.write(str(errorbars)+'\n')
|
||||
fr.write('Parameters correlation matrix:\n')
|
||||
fr.write(str(CorrelationMatrix)+'\n')
|
||||
fr.write('Minimum objective function value: ' + str(objective_func(optimum_params)))
|
||||
fr.close()
|
||||
|
||||
fft_final = generate_spectrum(optimum_params)
|
||||
|
||||
plt.plot(fft_final['x'], fft_final['y'], experimental_spectrum['x'], experimental_spectrum['y'])
|
||||
|
||||
plt.show()
|
||||
|
|
@ -0,0 +1,64 @@
|
|||
#!/usr/bin/python3
|
||||
|
||||
import spintrum
|
||||
import math
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import time
|
||||
|
||||
gammas = [1070.8e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4,4257.7e4]
|
||||
multips = [2,2,2,2,2,2,2,2,2]
|
||||
jCouplings = \
|
||||
[
|
||||
[0,125.99,125.99,125.99,4.53,0.63,0.56,0.63,4.53],
|
||||
[0,0,0,0,-0.69,0.3,-0.52,0.3,-0.69],
|
||||
[0,0,0,0,-0.69,0.3,-0.52,0.3,-0.69],
|
||||
[0,0,0,0,-0.69,0.3,-0.52,0.3,-0.69],
|
||||
[0,0,0,0,0,7.655,1.273,0.61,1.902],
|
||||
[0,0,0,0,0,0,7.417,1.442,0.61],
|
||||
[0,0,0,0,0,0,0,7.417,1.273],
|
||||
[0,0,0,0,0,0,0,0,7.655],
|
||||
[0,0,0,0,0,0,0,0,0],
|
||||
]
|
||||
|
||||
BThermal = 1.8e0
|
||||
T2 = 10
|
||||
sampleRate = 2e3
|
||||
T= 1/sampleRate
|
||||
points = 80000
|
||||
|
||||
gammah = 2*math.pi*4257.7
|
||||
|
||||
|
||||
spinOp = spintrum.SpinOperations()
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__THERMAL_POPULATE,
|
||||
{'Bx': 0, 'By': 0, 'Bz': BThermal, 'T': 293.778})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__TIP_SPINS,
|
||||
{'direction': 'y', 'BVsTArea': 4*math.pi/gammah})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__SET_HAMILTONIAN,
|
||||
{'Bx': 0, 'By': 0, 'Bz': 0})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION,
|
||||
{'samplingRate': sampleRate, 'measurementDirection': 'z'})
|
||||
spinOp.add_operation(spintrum.SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT,
|
||||
{'points': points, 'threads': 4})
|
||||
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
signal = spintrum.simulate(gyromagneticRatios=gammas,
|
||||
jCouplings=jCouplings,
|
||||
spinMultiplicities=multips,
|
||||
spinOperations=spinOp)
|
||||
|
||||
signal = signal - np.mean(signal)
|
||||
signal = [signal[i]*math.exp(-i/sampleRate/T2) for i in range(len(signal))]
|
||||
|
||||
print("Simulation lastet: " + repr(time.time()-start_time) + "s")
|
||||
|
||||
#plt.plot(signal)
|
||||
#plt.show()
|
||||
|
||||
fft = spintrum.FFTSpectralDensity(signal, sampleRate)
|
||||
|
||||
#plt.plot(fft['x'], fft['y'])
|
||||
#plt.show()
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
Minimum at J-couplings:
|
||||
[0.0 7.540000000000000035527137 1.37999999999999989341859 0.6940500000000000557776048 1.37999999999999989341859 7.540000000000000035527137 158.3540000000000134150469]
|
||||
[0.0 0.0 7.543000000000000149213975 1.377000000000000001776357 0.6580000000000000293098879 1.372999999999999998223643 1.133000000000000007105427]
|
||||
[0.0 0.0 0.0 7.535000000000000142108547 1.381999999999999895194946 0.6580000000000000293098879 7.607000000000000206057393]
|
||||
[0.0 0.0 0.0 0.0 7.535000000000000142108547 1.377000000000000001776357 -1.296000000000000040856207]
|
||||
[0.0 0.0 0.0 0.0 0.0 7.543000000000000149213975 7.607000000000000206057393]
|
||||
[0.0 0.0 0.0 0.0 0.0 0.0 1.133000000000000007105427]
|
||||
[0.0 0.0 0.0 0.0 0.0 0.0 0.0]
|
||||
Minimum at paramters:
|
||||
[ 7.54000000000000003553 1.37999999999999989342
|
||||
0.69405000000000005578 158.35400000000001341505
|
||||
7.54300000000000014921 1.37700000000000000178
|
||||
0.65800000000000002931 1.37299999999999999822
|
||||
1.13300000000000000711 7.53500000000000014211
|
||||
1.38199999999999989519 7.60700000000000020606
|
||||
-1.29600000000000004086 0.00002 6. ]
|
||||
Parameters standard deviations:
|
||||
[ 0.01213036128028350744 0.01200338965431838219 0.0210108319218480534
|
||||
0.00136520954965830372 0.00207036522512347001 0.0015403380168111558
|
||||
0.002411457870921565 0.00388774145155117157 0.0115697414734789103
|
||||
0.00197797340829316192 0.00378925067269910397 0.01309609727481571284
|
||||
0.02228143292531298975 0.00000013041758667639 0.08099564331836582587]
|
||||
Parameters correlation matrix:
|
||||
[ 0.0001471456647902013181383402 0.00001463222969485299177267973 -0.00006909596379679264589945903 -0.000009879358894976308872795249 -0.0000009910243900245024325036503 -0.000002509748557468651844392826 -0.000002380514305191314647678003 -0.000001532797369848477294597076 -0.0001398171521420891800876204 0.000001422052124704963073199576 -0.00001037268069958482290642726 -0.00001290226212709788198467148 0.00007096566048036505325667219 -1.702553129336511984544059e-10 0.00004275020004048705398448456]
|
||||
[ 0.00001463222969485299177267973 0.0001440813631933975880817379 0.00002299492026289425009574231 0.00001037831140663546812973995 0.000004641419189000230273160295 0.0000003481765790202689986629226 0.000005497366076771748661640629 0.000002877276454724989752027814 -0.00001362792654992391090535695 0.0000004161081524168458245327233 -0.000002483428954058797310899994 -0.0001558767501752093491889536 -0.00002141545832708516017103168 -6.012359324553393495710444e-11 -0.00002327038396238911095653417]
|
||||
[ -0.00006909596379679264589945903 0.00002299492026289425009574231 0.0004414550580481491548513489 0.000001108435560228381067375232 -0.00001975420180487688038510312 0.00001453060280812084487906817 0.00002318209036413609021209115 0.00001039593258646703331312574 0.00006364589864333445436952719 -0.000009398587641029470657017377 0.00002622272826720824973467517 -0.000008764476892287513000476972 -0.000466746002920191158409556 1.248762095118255000331241e-10 0.00001130020472156932208081689]
|
||||
[ -0.000009879358894976308872795249 0.00001037831140663546812973995 0.000001108435560228381067375232 0.000001863797114478228603607421 0.0000007476440865756702094209745 1.123978176405166973781769e-8 0.0000002553464654493212747923789 0.0000003195064918052377525208331 0.000009443194729269174453253087 7.221575647409583548534879e-8 0.000000349931576923391013309441 -0.00001190107927369451519111038 -0.0000008315685547761382561697822 6.700368978239857808480007e-12 -0.000005586326111486780414234254]
|
||||
[-0.0000009910243900245024325036503 0.000004641419189000230273160295 -0.00001975420180487688038510312 0.0000007476440865756702094209745 0.000004286412165400555968378269 -0.00000148069638031103530582914 -0.00000173209322151311247953546 -0.0000005677951950371133070047416 0.0000009378771834264744655292185 0.000001247272798757033414925511 -0.000001274930289723080766708529 -0.000006204113311550526544923224 0.00002140476713125757962515133 -2.303859357294487235932149e-11 -0.0000003321116977367169408111833]
|
||||
[ -0.000002509748557468651844392826 0.0000003481765790202689986629226 0.00001453060280812084487906817 1.123978176405166973781769e-8 -0.00000148069638031103530582914 0.000002372641206033724645831738 0.0000003949086502734464393062185 0.000001888143503238488927826451 0.000002307832893099388443109272 -0.000001330141506298025966824523 0.000001023838420449584372820466 8.810992240617305314994453e-8 -0.00001532057310382572305396533 6.464365426716748781623857e-13 0.000008235154837073978975731815]
|
||||
[ -0.000002380514305191314647678003 0.000005497366076771748661640629 0.00002318209036413609021209115 0.0000002553464654493212747923789 -0.00000173209322151311247953546 0.0000003949086502734464393062185 0.000005815129063229567994669581 -0.0000008188514962362312139895792 0.000001586158863679219511860753 -0.000001061890629089395632567779 0.0000006323002134620725592762107 -0.000004645446730989817348446203 -0.00002427101958370795139270938 1.038492242263116564566961e-11 -0.000008219887074829020900351506]
|
||||
[ -0.000001532797369848477294597076 0.000002877276454724989752027814 0.00001039593258646703331312574 0.0000003195064918052377525208331 -0.0000005677951950371133070047416 0.000001888143503238488927826451 -0.0000008188514962362312139895792 0.00001511453359410921012152708 0.000000999587640990087513467813 -0.000001931320208821247224439329 0.0000055775471016662317599875 -0.000003803551035702625255040296 -0.00001044948729450380108855006 1.538488794122819589494189e-11 -0.00000190273597974101894946311]
|
||||
[ -0.0001398171521420891800876204 -0.00001362792654992391090535695 0.00006364589864333445436952719 0.000009443194729269174453253088 0.0000009378771834264744655292185 0.000002307832893099388443109272 0.000001586158863679219511860753 0.0000009995876409900875134678131 0.0001338589177631379405020443 -0.000001347004704046966658459637 0.000009310637780617520017116411 0.00001131355875911897408321388 -0.00006530765877458676341747736 1.506546328775637756433659e-10 -0.0000301979608076350653658923]
|
||||
[ 0.000001422052124704963073199576 0.0000004161081524168458245327232 -0.000009398587641029470657017377 7.221575647409583548534879e-8 0.000001247272798757033414925511 -0.000001330141506298025966824523 -0.000001061890629089395632567779 -0.000001931320208821247224439329 -0.000001347004704046966658459637 0.00000391237880391486694459757 -0.0000006379463858305498051696242 -0.0000002334284653952341494558095 0.000008643432009244179075330804 1.758741509731881657071911e-12 -0.00000487121626283840634144112]
|
||||
[ -0.00001037268069958482290642726 -0.000002483428954058797310899994 0.00002622272826720824973467517 0.000000349931576923391013309441 -0.000001274930289723080766708529 0.000001023838420449584372820466 0.0000006323002134620725592762107 0.0000055775471016662317599875 0.000009310637780617520017116411 -0.0000006379463858305498051696242 0.00001435842066055061071562628 0.000003028275428748878192197676 -0.00002776991450362346709938132 2.814838265884042881741137e-11 -0.00001169416998368706644677807]
|
||||
[ -0.00001290226212709788198467148 -0.0001558767501752093491889536 -0.000008764476892287513000476973 -0.00001190107927369451519111038 -0.000006204113311550526544923224 8.810992240617305314994455e-8 -0.000004645446730989817348446203 -0.000003803551035702625255040296 0.00001131355875911897408321388 -0.0000002334284653952341494558095 0.000003028275428748878192197676 0.0001715077638314355195700391 0.000005116547306256408779515563 7.767623556078226544272074e-11 0.000019275139606341545706687]
|
||||
[ 0.00007096566048036505325667219 -0.00002141545832708516017103168 -0.000466746002920191158409556 -0.0000008315685547761382561697822 0.00002140476713125757962515133 -0.00001532057310382572305396532 -0.00002427101958370795139270938 -0.00001044948729450380108855006 -0.00006530765877458676341747736 0.000008643432009244179075330805 -0.00002776991450362346709938132 0.000005116547306256408779515563 0.0004964622532052218464903146 -1.304877543835054883828051e-10 -0.00001404076566819395902521567]
|
||||
[ -1.702553129336511984544059e-10 -6.012359324553393495710443e-11 1.248762095118255000331241e-10 6.700368978239857808480007e-12 -2.303859357294487235932149e-11 6.464365426716748781623857e-13 1.038492242263116564566961e-11 1.538488794122819589494189e-11 1.506546328775637756433659e-10 1.758741509731881657071911e-12 2.814838265884042881741137e-11 7.767623556078226544272074e-11 -1.304877543835054883828051e-10 1.700874691449460977731785e-14 -7.720781640183639711727769e-9]
|
||||
[ 0.00004275020004048705398448456 -0.00002327038396238911095653417 0.00001130020472156932208081689 -0.000005586326111486780414234254 -0.0000003321116977367169408111833 0.000008235154837073978975731815 -0.000008219887074829020900351506 -0.00000190273597974101894946311 -0.0000301979608076350653658923 -0.00000487121626283840634144112 -0.00001169416998368706644677807 0.00001927513960634154570668701 -0.00001404076566819395902521567 -7.720781640183639711727769e-9 0.006560294236555937715697575]
|
||||
Minimum objective function value: 0.00103043119564
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,20 @@
|
|||
Minimum at J-couplings:
|
||||
[0.0 0.0 0.0 7.099999999999999644728632 141.0 141.0]
|
||||
[0.0 0.0 0.0 7.099999999999999644728632 141.0 141.0]
|
||||
[0.0 0.0 0.0 7.099999999999999644728632 141.0 141.0]
|
||||
[0.0 0.0 0.0 0.0 0.0 -4.882500000000000284217094]
|
||||
[0.0 0.0 0.0 0.0 0.0 -4.882500000000000284217094]
|
||||
[0.0 0.0 0.0 0.0 0.0 0.0]
|
||||
Minimum at paramters:
|
||||
[ 7.09999999999999964473 141. -4.88250000000000028422
|
||||
0.00002 6. ]
|
||||
Parameters standard deviations:
|
||||
[ 0.03322511176186732779 0.00875703636437601129 0.00859062850557597291
|
||||
0.00000523277859604197 3.77791757313063492063]
|
||||
Parameters correlation matrix:
|
||||
[ 0.001103908051588574804254193 -0.0001006480358644767479148856 0.00005611320233879484823628018 -2.237414104467287731378798e-11 0.0002700305105131311016724805]
|
||||
[-0.0001006480358644767479148856 0.00007668568588700384258089065 -0.00004179674357134708614132537 -5.925975514198601921081523e-9 0.004471293184115583646988029]
|
||||
[0.00005611320233879484823628018 -0.00004179674357134708614132537 0.00007379889812081447682909023 1.350386848067927730816378e-8 -0.0102277945204446472126845]
|
||||
[-2.237414104467287731378797e-11 -5.925975514198601921081523e-9 1.350386848067927730816378e-8 2.738197183519495203009604e-11 -0.00001880755267537564555294751]
|
||||
[ 0.0002700305105131311016724805 0.004471293184115583646988029 -0.0102277945204446472126845 -0.00001880755267537564555294751 14.27266118936926548689719]
|
||||
Minimum objective function value: 0.0125706965818
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,13 @@
|
|||
Minimum at J-couplings:
|
||||
[0.0 222.1877481194236167993949493393302]
|
||||
[0.0 0.0]
|
||||
Minimum at paramters:
|
||||
[ 222.18774811942361679939 0.00000700376782247602
|
||||
1.69818437855777837342]
|
||||
Parameters standard deviations:
|
||||
[ 0.00777056220300333632 0.00000037317354042493 0.15122981127762022413]
|
||||
Parameters correlation matrix:
|
||||
[ 0.000060381636950744068972239730989777295 0.00000000071197799223094697619657741707518772 -0.00034401826493826866573828698109969613]
|
||||
[0.00000000071197799223094697619657741707518772 1.3925849127327319427483753807104422e-13 -0.000000047394629923508054151430233544667943]
|
||||
[ -0.00034401826493826866573828698109969613 -0.000000047394629923508054151430233544667943 0.02287045581906462914171822272631652]
|
||||
Minimum objective function value: 0.000654933531164
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,23 @@
|
|||
Minimum at J-couplings:
|
||||
[0.0 -1.0678523499999998946918822184670717 -1.0678523499999998946918822184670717 -1.0678523499999998946918822184670717 226.79176699999999300416675396263599]
|
||||
[0.0 0.0 0.0 0.0 4.266848470000000226320935325929895]
|
||||
[0.0 0.0 0.0 0.0 4.266848470000000226320935325929895]
|
||||
[0.0 0.0 0.0 0.0 4.266848470000000226320935325929895]
|
||||
[0.0 0.0 0.0 0.0 0.0]
|
||||
Minimum at paramters:
|
||||
[ -1.06785234999999989469 226.79176699999999300417
|
||||
4.26684847000000022632 0.0000453620118 2.73284203999999997237
|
||||
0.0000000031154122 0.00000000280718054 ]
|
||||
Parameters standard deviations:
|
||||
[ 0.02242942966348998243 0.00190541137555014835 0.02303976419604812642
|
||||
0.00000028974733647283 0.07572279537417966888 0.00000000003027146215
|
||||
0.00000000004010792718]
|
||||
Parameters correlation matrix:
|
||||
[ 0.00050307931502944447178626360068638525 0.000029995480328595218968415826471918807 -0.00051359745782623199683628427562180084 0.000000000251280842447412138296006599769143 -0.00025439816330555875699204056496202219 1.9773403201808349316594111150447776e-14 7.0782623258978496584017170158219388e-15]
|
||||
[ 0.000029995480328595218968415826471918807 0.0000036305925100759085887128102540087185 -0.000031545306263632570913346524380184319 -2.8590806792482291405525580037517663e-11 0.00000099665502856831515009376374925722041 5.2053844502032590732856596844496641e-15 5.6557052486419077136597636259362455e-16]
|
||||
[ -0.00051359745782623199683628427562180084 -0.000031545306263632570913346524380184319 0.00053083073420950117280621071233900746 -0.00000000023963740826851480843983608530501171 0.00025228083948647103053486958411894584 -2.6259436597096508763502191603902104e-14 -5.617433835087409035349599078746469e-15]
|
||||
[0.000000000251280842447412138296006599769143 -2.8590806792482291405525580037517663e-11 -0.00000000023963740826851480843983608530501171 8.3953518993101093428195753947557931e-14 -0.000000016426706608716963060350415785300258 -1.2389127603544075455328883147971448e-19 3.4049961328862909668053015097419539e-18]
|
||||
[ -0.00025439816330555875699204056496202219 0.00000099665502856831515009376374925722041 0.00025228083948647103053486958411894584 -0.000000016426706608716963060350415785300258 0.0057339417392798879484838245926050435 8.3848437595250813682163955020503337e-13 -1.7808587170356099750124293395687296e-13]
|
||||
[ 1.9773403201808349316594111150447776e-14 5.2053844502032590732856596844496641e-15 -2.6259436597096508763502191603902104e-14 -1.2389127603544075455328883147971448e-19 8.3848437595250813682163955020503337e-13 9.1636142048929983066902979806790567e-22 6.2746417676452346808851531983373244e-22]
|
||||
[ 7.0782623258978496584017170158219388e-15 5.6557052486419077136597636259362455e-16 -5.617433835087409035349599078746469e-15 3.4049961328862909668053015097419539e-18 -1.7808587170356099750124293395687296e-13 6.2746417676452346808851531983373244e-22 1.608645822742293354407757298544296e-21]
|
||||
Minimum objective function value: 0.00132379434362
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,32 @@
|
|||
#!/bin/bash
|
||||
|
||||
#go to the directory of the script
|
||||
reldir=`dirname $0`
|
||||
cd $reldir
|
||||
directory=`pwd`
|
||||
|
||||
rm -rf dist
|
||||
rm -rf build
|
||||
rm -rf spintrum.egg-info/
|
||||
|
||||
mkdir build
|
||||
cd build
|
||||
cmake -DOpenBLASPath=../OpenBLAS_install/ ..
|
||||
|
||||
if [ $? -ne 0 ]; then
|
||||
echo 'CMake failed to run. Are you sure that CMake is installed?'
|
||||
exit
|
||||
fi
|
||||
|
||||
make
|
||||
if [ $? -ne 0 ]; then
|
||||
echo 'make failed to run.'
|
||||
exit
|
||||
fi
|
||||
|
||||
cd ..
|
||||
python3 setup.py --verbose sdist
|
||||
if [ $? -ne 0 ]; then
|
||||
echo 'Python package creator installation script failed.'
|
||||
exit
|
||||
fi
|
||||
|
|
@ -0,0 +1,20 @@
|
|||
#!/bin/bash
|
||||
|
||||
#go to the directory of the script
|
||||
reldir=`dirname $0`
|
||||
cd $reldir
|
||||
directory=`pwd`
|
||||
|
||||
RED='\033[1;31m'
|
||||
NC='\033[0m' # No Color
|
||||
|
||||
if [ "$(id -u)" != "0" ]; then
|
||||
echo -e "${RED}ERROR: This script must be run as root${NC}" 1>&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
pip3 install dist/spintrum* --upgrade
|
||||
if [ $? -ne 0 ]; then
|
||||
echo 'Package installation failed. Did you build the package? Do you have pip3 installed?'
|
||||
exit
|
||||
fi
|
||||
|
|
@ -0,0 +1,28 @@
|
|||
from setuptools import setup, find_packages
|
||||
from spintrum import meta
|
||||
import os
|
||||
import sys
|
||||
|
||||
del os.link #solve hardlinking problem when using NTFS drive
|
||||
|
||||
def _print_error(msg):
|
||||
sys.stderr.write("\n\nERROR: " + msg + "\n\n\n")
|
||||
|
||||
dirname = "spintrum"
|
||||
lib_file = "lib/libspintrum.so"
|
||||
|
||||
if not os.path.isfile(os.path.join(dirname,lib_file)):
|
||||
_print_error("Unable to find the compiled library header. Please compile Spintrum before installing it.")
|
||||
os._exit(1)
|
||||
|
||||
setup(name='spintrum',
|
||||
version=meta.__version__,
|
||||
description='Software for spin systems simulation',
|
||||
url='http://www.afach.de',
|
||||
author='Samer Afach',
|
||||
author_email='samer@afach.de',
|
||||
license='MPL',
|
||||
packages=['spintrum'],
|
||||
package_data={'': ['lib/libspintrum.so']},
|
||||
zip_safe=False
|
||||
)
|
||||
|
|
@ -0,0 +1,8 @@
|
|||
try:
|
||||
from spintrum import *
|
||||
from meta import *
|
||||
except:
|
||||
from spintrum.spintrum import *
|
||||
from spintrum.meta import *
|
||||
|
||||
__all__ = ['spintrum','meta']
|
||||
|
|
@ -0,0 +1 @@
|
|||
__version__ = "0.1.6"
|
||||
|
|
@ -0,0 +1,747 @@
|
|||
import sys
|
||||
import traceback
|
||||
import copy
|
||||
import ctypes as c
|
||||
import numpy as np
|
||||
import os
|
||||
import mpmath
|
||||
|
||||
_SpintrumLibPath = os.path.join(os.path.dirname(os.path.abspath(__file__)),"lib/libspintrum.so")
|
||||
|
||||
mpmath.mp.dps = 50
|
||||
|
||||
|
||||
def fft_spectral_density(data_list, sampling_rate):
|
||||
"""
|
||||
Calculates the amplitude spectral density with both x and y axes
|
||||
:param data_list: Data, for which the FFT to be taken
|
||||
:param sampling_rate: the sample rate of the data
|
||||
:return: a dict with two elements, "x" for the x-axis (frequency axis),
|
||||
and "y" for the y-axis (the amplitude axis with units Amplitude/sqrt(Hz))
|
||||
"""
|
||||
N = len(data_list)
|
||||
fft_data = np.fft.rfft(data_list)[0:int(N / 2 + 1)]
|
||||
bandwidth = np.double(sampling_rate / 2)
|
||||
scaling_factor = np.sqrt(1/bandwidth/np.double(N))
|
||||
x_axis = sampling_rate * np.array(range(int(N / 2 + 1))) / (np.double(N))
|
||||
abs_fft_data = scaling_factor*np.array(list(map(np.absolute,fft_data)))
|
||||
return {"x": x_axis, "y": abs_fft_data}
|
||||
|
||||
|
||||
def FFTSpectralDensity(data_list, sampling_rate):
|
||||
"""
|
||||
Deprecated. Please use fft_spectral_density()
|
||||
"""
|
||||
return fft_spectral_density(data_list, sampling_rate)
|
||||
|
||||
|
||||
def who_am_i():
|
||||
stack = traceback.extract_stack()
|
||||
filename, code_line, func_name, text = stack[-2]
|
||||
|
||||
return func_name
|
||||
|
||||
|
||||
def _print_error(msg_str):
|
||||
sys.stderr.write(msg_str + "\n")
|
||||
|
||||
|
||||
if not os.path.exists(_SpintrumLibPath):
|
||||
msg = "WARNING: Could not load the spintrum shared library in path " \
|
||||
+ _SpintrumLibPath + ". This means that the installation is not valid " \
|
||||
"and will most likely not work."
|
||||
_print_error(msg)
|
||||
print(msg)
|
||||
|
||||
|
||||
def _raise_error(msg_str):
|
||||
sys.stderr.write(msg_str + "\n")
|
||||
raise Exception(msg_str)
|
||||
|
||||
|
||||
def _is_var_type_correct(value, type_or_types):
|
||||
if type(type_or_types) is list:
|
||||
for tp in type_or_types:
|
||||
if type(value) is tp:
|
||||
return True
|
||||
return False
|
||||
|
||||
else:
|
||||
if type(value) is type_or_types:
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
def _get_types_list_types_names(type_or_types):
|
||||
if type(type_or_types) is list:
|
||||
return str([tp.__name__ for tp in type_or_types])
|
||||
else:
|
||||
return str(type_or_types.__name__)
|
||||
|
||||
|
||||
def _check_dict_elements_types(input_dict, types_dict):
|
||||
for val in input_dict:
|
||||
if val in types_dict:
|
||||
if _is_var_type_correct(input_dict[val], types_dict[val]) is False:
|
||||
_raise_error("Error: Type is not of expected type for variable: " + str(val) +
|
||||
". Possible allowed type(s) are: " + _get_types_list_types_names(types_dict[val]))
|
||||
|
||||
|
||||
def _check_elements_exist_in_dict(input_dict, must_exist, can_exist):
|
||||
for el in must_exist:
|
||||
if el not in input_dict:
|
||||
_raise_error("Error: You should specify a value for: " + el)
|
||||
joined_elements = must_exist + can_exist
|
||||
|
||||
for el in input_dict:
|
||||
if el not in joined_elements:
|
||||
_raise_error("Error: You have specified an unknown variable: " + el)
|
||||
|
||||
|
||||
def _analyze_direction_string(dirs):
|
||||
activated_directions = {'x': 0, 'y': 0, 'z': 0, 'dirs': dirs}
|
||||
if (len(dirs) != 0) and ("x" not in dirs) and ("y" not in dirs) and ("z" not in dirs):
|
||||
_raise_error("Directions, for which trace has to be stored must be given as a string; eg x or xyz or xz, etc.")
|
||||
else:
|
||||
for c in dirs:
|
||||
if c == 'x':
|
||||
activated_directions['x'] = 1
|
||||
elif c == 'y':
|
||||
activated_directions['y'] = 1
|
||||
elif c == 'z':
|
||||
activated_directions['z'] = 1
|
||||
return activated_directions
|
||||
|
||||
|
||||
class SpinOperations:
|
||||
_OPERATION_NAME_IDENTIFIER = '_OperationIdentifier'
|
||||
OPERATION__THERMAL_POPULATE = 0
|
||||
OPERATION__TIP_SPINS = 1
|
||||
OPERATION__SET_HAMILTONIAN = 2
|
||||
OPERATION__EVOLVE_TIME_INDEPENDENT = 3
|
||||
OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION = 4
|
||||
OPERATION__EVOLVE_TIME_DEPENDENT = 5
|
||||
|
||||
def __init__(self):
|
||||
self.operations_stack = None
|
||||
self.total_num_of_points = 0
|
||||
self.clear_operations()
|
||||
|
||||
def clear_operations(self):
|
||||
self.operations_stack = []
|
||||
|
||||
def add_operation(self, operation, parameters={}):
|
||||
if type(parameters) is not dict:
|
||||
_raise_error(who_am_i() + ": Error: parameters should be a dict.")
|
||||
|
||||
if operation == SpinOperations.OPERATION__THERMAL_POPULATE:
|
||||
argument_types = {'Bx': [int, float], 'By': [int, float], 'Bz': [int, float],'T': [int,float]}
|
||||
must_exist_arguments = ['Bx', 'By', 'Bz','T']
|
||||
optional_arguments = []
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
elif operation == SpinOperations.OPERATION__TIP_SPINS:
|
||||
argument_types = {'direction': str, 'BVsTArea': [int, float]}
|
||||
must_exist_arguments = ['direction', 'BVsTArea']
|
||||
optional_arguments = []
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
elif operation == SpinOperations.OPERATION__SET_HAMILTONIAN:
|
||||
argument_types = {'Bx': [int, float], 'By': [int, float],
|
||||
'Bz': [int, float], 'samplingRate': [int, float]}
|
||||
must_exist_arguments = []
|
||||
optional_arguments = ['Bx', 'By', 'Bz']
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
elif operation == SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT:
|
||||
argument_types = {'points': int, 'threads': int}
|
||||
must_exist_arguments = ['points', 'threads']
|
||||
optional_arguments = []
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.total_num_of_points += parameters['points']
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
elif operation == SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION:
|
||||
argument_types = {'samplingRate': [int, float], 'measurementDirection': str}
|
||||
must_exist_arguments = ['samplingRate', 'measurementDirection']
|
||||
optional_arguments = []
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
elif operation == SpinOperations.OPERATION__EVOLVE_TIME_DEPENDENT:
|
||||
argument_types = {'threads': int, 'input': dict, 'samplingRate': [int, float], 'store': str}
|
||||
must_exist_arguments = ['threads', 'input', 'samplingRate', ]
|
||||
optional_arguments = ['store']
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
# use set to remove duplicates, and restore in dirs_to_store to get the reduced version
|
||||
# (removing duplicates preserves order by using key=parameters['store'].index)
|
||||
parameters['dirs_to_store'] = \
|
||||
_analyze_direction_string(''.join(sorted(set(parameters['store']), key=parameters['store'].index)))
|
||||
# total number of points = number of input values*number of directions to measure
|
||||
self.total_num_of_points += \
|
||||
len(list(parameters['input'].values())[0])*len(parameters['dirs_to_store']['dirs'])
|
||||
params_copy = copy.deepcopy(parameters)
|
||||
params_copy.update({SpinOperations._OPERATION_NAME_IDENTIFIER: operation})
|
||||
self.operations_stack.append(params_copy)
|
||||
|
||||
else:
|
||||
_raise_error("Error: Operation Unknown!")
|
||||
|
||||
|
||||
def _check_j_couplings_sanity(j_couplings):
|
||||
"""
|
||||
raises an error if j couplings don't make sense
|
||||
:param j_couplings:
|
||||
:return:
|
||||
"""
|
||||
if j_couplings is None: #no j-couplings provided
|
||||
return
|
||||
for i in range(len(j_couplings)):
|
||||
if len(j_couplings[i]) != len(j_couplings):
|
||||
_raise_error("Error: j-couplings must be a square matrix.")
|
||||
for j in range(len(j_couplings[i])):
|
||||
if j_couplings[i][j] != 0 and i >= j:
|
||||
_raise_error("Error: j-couplings must be an upper triangular matrix. "
|
||||
"All other elements must be exactly 0.")
|
||||
|
||||
|
||||
def simulate(**kwargs):
|
||||
argument_types = {'gyromagneticRatios': list, 'jCouplings': list, 'spinMultiplicities': list,
|
||||
'spinOperations': SpinOperations}
|
||||
must_exist_arguments = ['gyromagneticRatios', 'spinOperations']
|
||||
optional_arguments = ['jCouplings','spinMultiplicities']
|
||||
_check_elements_exist_in_dict(kwargs, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(kwargs, argument_types)
|
||||
|
||||
if 'jCouplings' not in kwargs:
|
||||
kwargs['jCouplings'] = None
|
||||
if 'spinMultiplicities' not in kwargs:
|
||||
kwargs['spinMultiplicities'] = None
|
||||
|
||||
_check_j_couplings_sanity(kwargs['jCouplings'])
|
||||
if kwargs['spinMultiplicities'] is not None and \
|
||||
len(kwargs['gyromagneticRatios']) != len(kwargs['spinMultiplicities']):
|
||||
_raise_error("Spin multiplicities must have a length equal to the gyromagnetic ratios, "
|
||||
"or alternatively, if you keep it empty, then it is assumed that all spins are 1/2")
|
||||
# print(kwargs)
|
||||
return _get_signal_c_call(kwargs)
|
||||
|
||||
|
||||
class _CSpinOperation(c.Structure):
|
||||
_fields_ = [("OperationIdentifier", c.c_long),
|
||||
("Params_int_count", c.c_long),
|
||||
("Params_int", c.POINTER(c.c_long)),
|
||||
("Params_real_count", c.c_long),
|
||||
("Params_real", c.POINTER(c.c_double)),
|
||||
("Params_array_count", c.c_long),
|
||||
("Params_array_lengths", c.POINTER(c.c_long)),
|
||||
("Params_array_names", c.POINTER(c.POINTER(c.c_char))),
|
||||
("Params_array", c.POINTER(c.POINTER(c.c_double)))
|
||||
]
|
||||
|
||||
|
||||
def _direction_str_to_int(dir_str):
|
||||
if dir_str.lower() == 'x':
|
||||
return 0
|
||||
elif dir_str.lower() == 'y':
|
||||
return 1
|
||||
elif dir_str.lower() == 'z':
|
||||
return 2
|
||||
else:
|
||||
_raise_error("Direction of the tipping magnetic field can be either x, y or z. "
|
||||
"You've entered \"" + dir_str + "\"")
|
||||
|
||||
|
||||
def _create_c_operation(operation_id, int_params, real_params, array_params):
|
||||
|
||||
# if int params exist, make them in a pointer to an array, otherwise, make it NULL (None)
|
||||
if len(int_params) > 0:
|
||||
int_params_c = (c.c_long * len(int_params))(*int_params) #convert list to c-array
|
||||
int_params_ptr = c.cast(int_params_c, c.POINTER(c.c_long)) #cast array to pointer
|
||||
else:
|
||||
int_params_ptr = None
|
||||
|
||||
#if real params exist, make them in a pointer to an array, otherwise, make it NULL (None)
|
||||
if len(real_params) > 0:
|
||||
real_params_c = (c.c_double * len(real_params))(*real_params) #convert list to c-array
|
||||
real_params_ptr = c.cast(real_params_c, c.POINTER(c.c_double)) #cast array to pointer
|
||||
else:
|
||||
real_params_ptr = None
|
||||
|
||||
if len(array_params) > 0:
|
||||
# arrays lengths
|
||||
array_lengths_list = list(map(len,array_params.values()))
|
||||
data_array_lengths_c = (c.c_long * len(array_params))(*array_lengths_list) #convert list to c-array
|
||||
data_array_lengths_ptr = c.cast(data_array_lengths_c, c.POINTER(c.c_long)) #cast array to pointer
|
||||
|
||||
# arrays labels
|
||||
labels_array_type = (c.POINTER(c.c_char)*len(array_params))
|
||||
labels_c_array = labels_array_type()
|
||||
labels_keys_list = list(array_params.keys())
|
||||
for i in range(len(labels_keys_list)):
|
||||
labels_c_array[i] = c.create_string_buffer(str.encode(labels_keys_list[i]))
|
||||
|
||||
# arrays data arrays
|
||||
arrays_array_type = (c.POINTER(c.c_double) * len(array_params))
|
||||
arrays_c_array = arrays_array_type()
|
||||
arrays_list = list(array_params.values())
|
||||
for i in range(len(arrays_list)):
|
||||
single_array_c_type = (c.c_double * len(arrays_list[i]))(*arrays_list[i]) # convert list to c-array
|
||||
single_array_c = single_array_c_type
|
||||
arrays_c_array[i] = c.cast(single_array_c, c.POINTER(c.c_double)) #cast array to pointer
|
||||
|
||||
else:
|
||||
data_array_lengths_ptr = None
|
||||
labels_c_array = None
|
||||
arrays_c_array = None
|
||||
|
||||
op_values = _CSpinOperation(operation_id,
|
||||
len(int_params), int_params_ptr,
|
||||
len(real_params), real_params_ptr,
|
||||
len(array_params),
|
||||
data_array_lengths_ptr,
|
||||
labels_c_array,
|
||||
arrays_c_array)
|
||||
return c.byref(op_values)
|
||||
|
||||
|
||||
def _get_operations_pointers(operations_stack):
|
||||
num_of_ops = len(operations_stack)
|
||||
structs_ptr_array_type = c.c_void_p * num_of_ops
|
||||
structs_ptr_array_obj = structs_ptr_array_type()
|
||||
structs_array = []
|
||||
for op in operations_stack:
|
||||
if op["_OperationIdentifier"] == SpinOperations.OPERATION__THERMAL_POPULATE:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"], [], [op['Bx'],op['By'],op['Bz'],op['T']], {}))
|
||||
|
||||
elif op["_OperationIdentifier"] == SpinOperations.OPERATION__TIP_SPINS:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"],[_direction_str_to_int(op['direction'])], [op['BVsTArea']], {}))
|
||||
|
||||
elif op["_OperationIdentifier"] == SpinOperations.OPERATION__SET_HAMILTONIAN:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"], [], [op["Bx"], op["By"], op["Bz"]], {}))
|
||||
|
||||
elif op["_OperationIdentifier"] == SpinOperations.OPERATION__EVOLVE_TIME_INDEPENDENT:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"], [op["points"],op["threads"]], [], {}))
|
||||
|
||||
elif op["_OperationIdentifier"] == SpinOperations.OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"], [_direction_str_to_int(op['measurementDirection'])], [op["samplingRate"]], {}))
|
||||
|
||||
elif op["_OperationIdentifier"] == SpinOperations.OPERATION__EVOLVE_TIME_DEPENDENT:
|
||||
structs_array.append(_create_c_operation(op["_OperationIdentifier"],
|
||||
[op["threads"], op['dirs_to_store']['x'], op['dirs_to_store']['y'],
|
||||
op['dirs_to_store']['z']], [op['samplingRate']], op["input"]))
|
||||
return structs_array
|
||||
|
||||
|
||||
def _get_signal_c_call(parameters):
|
||||
structs_array = _get_operations_pointers(parameters['spinOperations'].operations_stack)
|
||||
operations_stack = parameters['spinOperations'].operations_stack
|
||||
num_of_ops = len(operations_stack)
|
||||
structs_ptr_array_type = c.c_void_p * num_of_ops
|
||||
structs_ptr_array_obj = structs_ptr_array_type()
|
||||
|
||||
# print(structs_ptr_array_obj)
|
||||
|
||||
# This next loop cannot be included in the function _get_operations_pointers
|
||||
# because taking c-pointers to structs_array elements doesn't make python preserve them, which causes them to
|
||||
# be deleted when exiting the function
|
||||
for i in range(len(structs_array)):
|
||||
structs_ptr_array_obj[i] = c.cast(structs_array[i], c.c_void_p)
|
||||
|
||||
gammas = parameters['gyromagneticRatios']
|
||||
mults = parameters['spinMultiplicities']
|
||||
j_couplings = _convert_j_couplings_to_1d_array(parameters['jCouplings'])
|
||||
|
||||
gammas_c_version = (c.c_double * len(gammas))(*gammas)
|
||||
gammas_ptr = c.cast(gammas_c_version, c.POINTER(c.c_double * len(gammas)))
|
||||
|
||||
if mults is None:
|
||||
mults_ptr = c.c_void_p(None)
|
||||
else:
|
||||
mults_c_version = (c.c_int * len(mults))(*mults)
|
||||
mults_ptr = c.cast(mults_c_version, c.POINTER(c.c_int * len(mults)))
|
||||
|
||||
if j_couplings == []:
|
||||
j_couplings_ptr = c.c_void_p(None)
|
||||
else:
|
||||
j_couplings_c_version = (c.c_double * len(j_couplings))(*j_couplings)
|
||||
j_couplings_ptr = c.cast(j_couplings_c_version, c.POINTER(c.c_double * len(j_couplings)))
|
||||
|
||||
mylib = c.CDLL(_SpintrumLibPath)
|
||||
|
||||
num_of_points = parameters['spinOperations'].total_num_of_points
|
||||
|
||||
return_array_type = c.c_double * num_of_points
|
||||
returned_array_ptr_type = c.POINTER(return_array_type)
|
||||
return_array = return_array_type()
|
||||
returned_array_ptr = c.byref(return_array)
|
||||
prototype = c.CFUNCTYPE(
|
||||
c.c_long, # return type
|
||||
c.c_void_p,
|
||||
c.c_void_p,
|
||||
c.c_void_p,
|
||||
c.c_void_p,
|
||||
c.c_int,
|
||||
c.c_int,
|
||||
c.c_long,
|
||||
returned_array_ptr_type
|
||||
)
|
||||
create_signal_function = prototype(('SimulateSignal', mylib))
|
||||
|
||||
res = create_signal_function(structs_ptr_array_obj,
|
||||
gammas_ptr,
|
||||
j_couplings_ptr,
|
||||
mults_ptr,
|
||||
c.c_int(len(gammas)),
|
||||
c.c_int(len(structs_ptr_array_obj)),
|
||||
c.c_long(num_of_points),
|
||||
returned_array_ptr)
|
||||
# print(res)
|
||||
output = np.array(c.cast(returned_array_ptr,returned_array_ptr_type).contents)
|
||||
# print(output)
|
||||
return output
|
||||
|
||||
|
||||
def _convert_j_couplings_to_1d_array(j_couplings):
|
||||
if j_couplings is None:
|
||||
return []
|
||||
|
||||
output_array = []
|
||||
for i in range(len(j_couplings)):
|
||||
output_array += j_couplings[i][i + 1:len(j_couplings)]
|
||||
|
||||
return output_array
|
||||
|
||||
|
||||
def _get_derivative(params, param_index, fitted_function, epsilon=np.sqrt(np.finfo(float).eps)):
|
||||
"""
|
||||
Calculates the derivatives of the fitted function (after having fitted a function) to some model
|
||||
:param params: list of parameter values at the point where the derivative has to be calculated
|
||||
:param param_index: index of the parameter, for which the derivative has to be taken
|
||||
:param fitted_function: the function, for which the derivative has to be calculated, where
|
||||
this function has to take "params" as an argument
|
||||
:param epsilon: the small step to calculate the numerical difference; the default value uses Python floats' epislon
|
||||
:return: the derivative value of the i-th parameter in params in the function fitted_function
|
||||
"""
|
||||
h = params[param_index] * epsilon
|
||||
|
||||
low_point__1 = np.delete(np.insert(params, param_index, params[param_index] - h), param_index + 1)
|
||||
high_point_1 = np.delete(np.insert(params, param_index, params[param_index] + h), param_index + 1)
|
||||
|
||||
low_point__2 = np.delete(np.insert(params, param_index, params[param_index] - 2 * h), param_index + 1)
|
||||
high_point_2 = np.delete(np.insert(params, param_index, params[param_index] + 2 * h), param_index + 1)
|
||||
|
||||
low_point__3 = np.delete(np.insert(params, param_index, params[param_index] - 3 * h), param_index + 1)
|
||||
high_point_3 = np.delete(np.insert(params, param_index, params[param_index] + 3 * h), param_index + 1)
|
||||
|
||||
func_value_lp1 = fitted_function(low_point__1)
|
||||
func_value_hp1 = fitted_function(high_point_1)
|
||||
func_value_lp2 = fitted_function(low_point__2)
|
||||
func_value_hp2 = fitted_function(high_point_2)
|
||||
func_value_lp3 = fitted_function(low_point__3)
|
||||
func_value_hp3 = fitted_function(high_point_3)
|
||||
|
||||
derivative = 1.5*(func_value_hp1['y'] - func_value_lp1['y'])/(2*h) - \
|
||||
0.6*(func_value_hp2['y'] - func_value_lp2['y'])/(4*h) + \
|
||||
0.1*(func_value_hp3['y'] - func_value_lp3['y'])/(6*h)
|
||||
|
||||
return derivative
|
||||
|
||||
|
||||
def get_correlation_matrix(optimum_params, fitted_function, objective_function):
|
||||
"""
|
||||
A function that calculates the correlation matrix according to the book:
|
||||
Wolberg 2005: Data analysis using least-squares method
|
||||
:param optimum_params: list of optimum fitted parameters
|
||||
:param fitted_function: function that is fitted, that takes optimum_params as a parameter
|
||||
:param objective_function: the objective function used to fit. It should take optimum_params as parameter
|
||||
:return: the correlation matrix calculated
|
||||
"""
|
||||
n = len(optimum_params) # number of parameters
|
||||
p = len(fitted_function(optimum_params)['x']) # number of fitted points
|
||||
min_obj_func_val = objective_function(optimum_params) # minimum objective_function value
|
||||
|
||||
derivatives_matrix = \
|
||||
[_get_derivative(optimum_params, i, fitted_function).tolist() for i in range(len(optimum_params))]
|
||||
|
||||
derivatives_matrix_high_precision = mpmath.matrix(derivatives_matrix)
|
||||
|
||||
c_matrix = derivatives_matrix_high_precision*derivatives_matrix_high_precision.T
|
||||
|
||||
factor = (min_obj_func_val**2/(p-n))
|
||||
correlation_matrix = (c_matrix**-1)*factor
|
||||
|
||||
return correlation_matrix
|
||||
|
||||
|
||||
def get_errorbars(matrix):
|
||||
error_bars = np.array([])
|
||||
for i in range(matrix.cols):
|
||||
error_bars = np.append(error_bars, np.float(np.sqrt(matrix[i,i])))
|
||||
return error_bars
|
||||
|
||||
|
||||
class AtomicSpecies:
|
||||
GyromagneticRatio = None
|
||||
Name = None
|
||||
@staticmethod
|
||||
def _get_species_class_list():
|
||||
return AtomicSpecies.__subclasses__()
|
||||
|
||||
@staticmethod
|
||||
def get_species_names():
|
||||
return list([cls.Name for cls in AtomicSpecies._get_species_class_list()])
|
||||
|
||||
@staticmethod
|
||||
def get_species_gyromagnetic_ratios():
|
||||
return dict({cls.Name: cls.GyromagneticRatio for cls in AtomicSpecies._get_species_class_list()})
|
||||
|
||||
@staticmethod
|
||||
def get_species_list_gyromagnetic_ratios(listOfNames):
|
||||
gyromagnetic_ratios = dict({cls.Name: cls.GyromagneticRatio for cls in AtomicSpecies._get_species_class_list()})
|
||||
output = []
|
||||
for atom in listOfNames:
|
||||
output.append(gyromagnetic_ratios[atom])
|
||||
return output
|
||||
|
||||
def __init(self):
|
||||
pass
|
||||
|
||||
|
||||
class AtomC13(AtomicSpecies):
|
||||
Name = "C13"
|
||||
GyromagneticRatio = 1070.8
|
||||
|
||||
def __init__(self):
|
||||
AtomicSpecies.__init__(self)
|
||||
|
||||
|
||||
class AtomH1(AtomicSpecies):
|
||||
Name = "H1"
|
||||
GyromagneticRatio = 4257.7
|
||||
|
||||
def __init__(self):
|
||||
AtomicSpecies.__init__(self)
|
||||
|
||||
|
||||
class SpinSimulator:
|
||||
def __init__(self, **kwargs):
|
||||
self._is_initialized = False
|
||||
self._spin_operations = None
|
||||
self.init(kwargs)
|
||||
|
||||
def init(self,parameters):
|
||||
# pointer to object
|
||||
self.c_spin_ptr_to_object_type = c.c_void_p
|
||||
# pointer to pointer to object. Necessary to modify the pointer to object
|
||||
self.c_spin_ptr_to_ptr_type = c.POINTER(self.c_spin_ptr_to_object_type)
|
||||
self.c_spin_ptr_to_object = self.c_spin_ptr_to_object_type()
|
||||
self.c_spin_ptr_to_ptr = c.byref(self.c_spin_ptr_to_object)
|
||||
|
||||
argument_types = {'gyromagneticRatios': list, 'jCouplings': list, 'doPrint': bool}
|
||||
|
||||
must_exist_arguments = ['gyromagneticRatios']
|
||||
optional_arguments = ['jCouplings', 'spinMultiplicities', 'doPrint']
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
|
||||
if 'jCouplings' not in parameters:
|
||||
parameters['jCouplings'] = None
|
||||
if 'spinMultiplicities' not in parameters:
|
||||
parameters['spinMultiplicities'] = None
|
||||
|
||||
_check_j_couplings_sanity(parameters['jCouplings'])
|
||||
if parameters['spinMultiplicities'] is not None and \
|
||||
len(parameters['gyromagneticRatios']) != len(parameters['spinMultiplicities']):
|
||||
_raise_error("Spin multiplicities must have a length equal to the gyromagnetic ratios, "
|
||||
"or alternatively, if you keep it empty, then it is assumed that all spins are 1/2")
|
||||
|
||||
gammas = parameters['gyromagneticRatios']
|
||||
mults = parameters['spinMultiplicities']
|
||||
jCouplings = _convert_j_couplings_to_1d_array(parameters['jCouplings'])
|
||||
|
||||
gammas_c_version = (c.c_double * len(gammas))(*gammas)
|
||||
gammas_ptr = c.cast(gammas_c_version, c.POINTER(c.c_double * len(gammas)))
|
||||
|
||||
if mults is None:
|
||||
mults_ptr = c.c_void_p(None)
|
||||
else:
|
||||
mults_c_version = (c.c_int * len(mults))(*mults)
|
||||
mults_ptr = c.cast(mults_c_version, c.POINTER(c.c_int * len(mults)))
|
||||
|
||||
if jCouplings == []:
|
||||
jCouplings_ptr = c.c_void_p(None)
|
||||
else:
|
||||
jCouplings_c_version = (c.c_double * len(jCouplings))(*jCouplings)
|
||||
jCouplings_ptr = c.cast(jCouplings_c_version, c.POINTER(c.c_double * len(jCouplings)))
|
||||
|
||||
mylib = c.CDLL(_SpintrumLibPath)
|
||||
|
||||
prototype = c.CFUNCTYPE(
|
||||
c.c_int, # return type
|
||||
c.c_void_p,
|
||||
c.c_void_p,
|
||||
c.c_void_p,
|
||||
c.c_int,
|
||||
c.c_bool,
|
||||
self.c_spin_ptr_to_ptr_type
|
||||
)
|
||||
|
||||
initSimulatorCreatorFunction = prototype(('InitializeSimulator', mylib))
|
||||
|
||||
res = initSimulatorCreatorFunction(gammas_ptr,
|
||||
jCouplings_ptr,
|
||||
mults_ptr,
|
||||
c.c_int(len(gammas)),
|
||||
parameters['doPrint'],
|
||||
self.c_spin_ptr_to_ptr)
|
||||
|
||||
if res >= 0:
|
||||
self._is_initialized = True
|
||||
else:
|
||||
self._is_initialized = False
|
||||
_raise_error("An error occurred while initializing the spin simulator. Possibly a memory issue.")
|
||||
return res
|
||||
|
||||
def update_parameters(self,**parameters):
|
||||
argument_types = {'gyromagneticRatios': list, 'jCouplings': list,
|
||||
'spinOperations': SpinOperations}
|
||||
|
||||
must_exist_arguments = []
|
||||
optional_arguments = ['gyromagneticRatios',
|
||||
'spinOperations', 'jCouplings']
|
||||
_check_elements_exist_in_dict(parameters, must_exist_arguments, optional_arguments)
|
||||
_check_dict_elements_types(parameters, argument_types)
|
||||
|
||||
there_are_gammas = False
|
||||
there_are_j_couplings = False
|
||||
there_are_spin_operations = False
|
||||
|
||||
if 'gyromagneticRatios' in parameters:
|
||||
gammas = parameters['gyromagneticRatios']
|
||||
gammas_c_version = (c.c_double * len(gammas))(*gammas)
|
||||
gammas_ptr = c.cast(gammas_c_version, c.POINTER(c.c_double * len(gammas)))
|
||||
there_are_gammas = True
|
||||
|
||||
if 'jCouplings' in parameters:
|
||||
_check_j_couplings_sanity(parameters['jCouplings'])
|
||||
jCouplings = _convert_j_couplings_to_1d_array(parameters['jCouplings'])
|
||||
jCouplings_c_version = (c.c_double * len(jCouplings))(*jCouplings)
|
||||
jCouplings_ptr = c.cast(jCouplings_c_version, c.POINTER(c.c_double * len(jCouplings)))
|
||||
there_are_j_couplings = True
|
||||
|
||||
if 'spinOperations' in parameters:
|
||||
spin_ops = parameters['spinOperations']
|
||||
there_are_spin_operations = True
|
||||
|
||||
if there_are_gammas or there_are_j_couplings:
|
||||
mylib = c.CDLL(_SpintrumLibPath)
|
||||
|
||||
prototype = c.CFUNCTYPE(
|
||||
c.c_int, # return type
|
||||
c.c_void_p,
|
||||
c.c_void_p
|
||||
)
|
||||
|
||||
#set gammas values
|
||||
if there_are_gammas:
|
||||
set_gammas_function = prototype(('SetGammasInSimulator', mylib))
|
||||
res = set_gammas_function(gammas_ptr,
|
||||
self.c_spin_ptr_to_object)
|
||||
|
||||
if res >= 0:
|
||||
pass
|
||||
else:
|
||||
_raise_error("An error was found while trying to set gamma values.")
|
||||
|
||||
|
||||
# set j-couplings values
|
||||
if there_are_j_couplings:
|
||||
set_j_couplings_function = prototype(('SetJCouplingsInSimulator', mylib))
|
||||
res = set_j_couplings_function(jCouplings_ptr,
|
||||
self.c_spin_ptr_to_object)
|
||||
|
||||
if res >= 0:
|
||||
pass
|
||||
else:
|
||||
_raise_error("An error was found while trying to set j-couplings values.")
|
||||
|
||||
if there_are_spin_operations:
|
||||
self._spin_operations = spin_ops
|
||||
|
||||
def simulate(self):
|
||||
if self._spin_operations is None:
|
||||
_raise_error("SpinOperations not initialized. Use update_parameters() and set spinOperations.")
|
||||
structs_array = _get_operations_pointers(self._spin_operations.operations_stack)
|
||||
num_of_ops = len(self._spin_operations.operations_stack)
|
||||
structs_ptr_array_type = c.c_void_p * num_of_ops
|
||||
structs_ptr_array_obj = structs_ptr_array_type()
|
||||
|
||||
for i in range(len(structs_array)):
|
||||
structs_ptr_array_obj[i] = c.cast(structs_array[i], c.c_void_p)
|
||||
|
||||
mylib = c.CDLL(_SpintrumLibPath)
|
||||
|
||||
num_of_points = self._spin_operations.total_num_of_points
|
||||
|
||||
returnArrayType = c.c_double * num_of_points
|
||||
returnedArrayPtrType = c.POINTER(returnArrayType)
|
||||
returnArray = returnArrayType()
|
||||
returnedArrayPtr = c.byref(returnArray)
|
||||
prototype = c.CFUNCTYPE(
|
||||
c.c_long, #return type
|
||||
self.c_spin_ptr_to_object_type,
|
||||
c.c_void_p,
|
||||
c.c_int,
|
||||
c.c_long,
|
||||
returnedArrayPtrType
|
||||
)
|
||||
createSpectFunction = prototype(('CreateSignalFromInitializedSimulator', mylib))
|
||||
|
||||
res = createSpectFunction(self.c_spin_ptr_to_object,
|
||||
structs_ptr_array_obj,
|
||||
c.c_int(len(structs_ptr_array_obj)),
|
||||
c.c_long(num_of_points),
|
||||
returnedArrayPtr)
|
||||
# print(res)
|
||||
|
||||
output = np.array(c.cast(returnedArrayPtr,returnedArrayPtrType).contents)
|
||||
# print(output)
|
||||
return output
|
||||
|
||||
def __del__(self):
|
||||
# print("System initialization state: " + str(self._is_initialized))
|
||||
if self._is_initialized:
|
||||
mylib = c.CDLL(_SpintrumLibPath)
|
||||
|
||||
prototype = c.CFUNCTYPE(
|
||||
c.c_int, # return type
|
||||
c.c_void_p
|
||||
)
|
||||
deinitSimulatorFunction = prototype(('DenitializeSimulator', mylib))
|
||||
|
||||
res = deinitSimulatorFunction(self.c_spin_ptr_to_object)
|
||||
if res >= 0:
|
||||
self._is_initialized = False
|
||||
else:
|
||||
_raise_error("An error was found while trying to free the memory.")
|
||||
|
|
@ -0,0 +1,358 @@
|
|||
#ifdef _MSC_VER //If the compiler is the Visual Studio Compiler
|
||||
#define NOMINMAX //solves a problem with std::max on Windows
|
||||
#pragma warning(disable: 4297) //remove throw warnings
|
||||
#endif
|
||||
|
||||
#include "common/definitions.h"
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
|
||||
#include "common/SpinSystem.h"
|
||||
|
||||
const bool debug = false;
|
||||
|
||||
const char* get_version()
|
||||
{
|
||||
return SPINTRUM_VERSION;
|
||||
}
|
||||
|
||||
void print_software_info()
|
||||
{
|
||||
std::cout<<"Spintrum version "<<get_version()<<". ";
|
||||
std::cout<<"This software is provided under the MPL license. "
|
||||
"For more information, contact Samer Afach: samer@afach.de."<<std::endl<<std::endl;
|
||||
}
|
||||
|
||||
/**
|
||||
* A quantum mechanics operation (populate spins, tip spins, etc...) is a struct that contains a specific, predefined number of parameters.
|
||||
* Each operation has an Identifier, which is simply an integer. From this identifier, the code knows what parameters to seek
|
||||
* and how many parameters should be expected.
|
||||
* There are integer parameters, real parameters, and array of real parameters.
|
||||
*/
|
||||
struct SpinOperation
|
||||
{
|
||||
long OperationIdentifier;
|
||||
long Params_int_count; //number of integer parameters
|
||||
long* Params_int; //integer parameters
|
||||
long Params_real_count; //number of real parameters
|
||||
double* Params_real; //real parameters
|
||||
long Params_array_count; //number of arrays
|
||||
long* Params_array_lengths; //lengths of suppled arrays
|
||||
char** Params_array_names; //names of the parameters of the arrays
|
||||
double** Params_array; //array data
|
||||
};
|
||||
const static int OPERATION__THERMAL_POPULATE = 0;
|
||||
const static int OPERATION__TIP_SPINS = 1;
|
||||
const static int OPERATION__SET_HAMILTONIAN = 2;
|
||||
const static int OPERATION__EVOLVE_TIME_INDEPENDENT = 3;
|
||||
const static int OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION = 4;
|
||||
const static int OPERATION__EVOLVE_TIME_DEPENDENT = 5;
|
||||
|
||||
typedef double Real;
|
||||
|
||||
typedef SpinSystem<Real,std::complex<Real>,VEC,CX_VEC,MAT,CX_MAT> SpinSystemType;
|
||||
|
||||
struct SpinInfo
|
||||
{
|
||||
CX_MAT jCouplings;
|
||||
CX_VEC gammas;
|
||||
G_MAT<int> multiplicities;
|
||||
};
|
||||
|
||||
void devectorizeJCouplings(const long numOfSpins, const double* const jCouplingsInput, CX_MAT& jCouplingsOutput)
|
||||
{
|
||||
if(jCouplingsInput == 0)
|
||||
{
|
||||
jCouplingsOutput.resize(0,0);
|
||||
return;
|
||||
}
|
||||
int i = 0; //element of given array
|
||||
int j = 0; //element of current row
|
||||
int row = 0;
|
||||
while (i < numOfSpins*(numOfSpins-1)/2)
|
||||
{
|
||||
if(j <= row)
|
||||
{
|
||||
j++;
|
||||
continue;
|
||||
}
|
||||
if(j >= numOfSpins)
|
||||
{
|
||||
j = 0;
|
||||
row++;
|
||||
continue;
|
||||
}
|
||||
jCouplingsOutput.at(row,j) = jCouplingsInput[i];
|
||||
j++;
|
||||
i++;
|
||||
}
|
||||
}
|
||||
extern "C" int InitializeSimulator(double* gammas, double* jCouplings, int* spinMultiplicities, int numOfSpins, bool doPrintOutput, void** SpinSystemObject)
|
||||
{
|
||||
try
|
||||
{
|
||||
print_software_info();
|
||||
// std::cout<<"Number of spins: "<<numOfSpins<<std::endl;
|
||||
SpinInfo spinInfo;
|
||||
spinInfo.gammas.resize(numOfSpins,1);
|
||||
spinInfo.multiplicities.resize(numOfSpins,1);
|
||||
spinInfo.jCouplings.resize(numOfSpins,numOfSpins);
|
||||
for(int i = 0; i < numOfSpins; i++)
|
||||
{
|
||||
// std::cout<<gammas[i]<<"\t";
|
||||
spinInfo.gammas[i] = gammas[i];
|
||||
}
|
||||
// std::cout<<spinInfo.gammas<<std::endl;
|
||||
if(spinMultiplicities == 0)
|
||||
{
|
||||
for(int i = 0; i < numOfSpins; i++)
|
||||
spinInfo.multiplicities[i] = 2;
|
||||
}
|
||||
else
|
||||
{
|
||||
for(int i = 0; i < numOfSpins; i++)
|
||||
spinInfo.multiplicities[i] = spinMultiplicities[i];
|
||||
}
|
||||
|
||||
devectorizeJCouplings(numOfSpins, jCouplings, spinInfo.jCouplings);
|
||||
// std::cout<<spinInfo.jCouplings<<std::endl;
|
||||
|
||||
SpinSystemType *Spins = new SpinSystem<Real,std::complex<Real>,VEC,CX_VEC,MAT,CX_MAT>();
|
||||
Spins->print = doPrintOutput;
|
||||
Spins->init(spinInfo.gammas,spinInfo.jCouplings,spinInfo.multiplicities);
|
||||
*SpinSystemObject = static_cast<void*>(Spins);
|
||||
return 0;
|
||||
}
|
||||
catch(std::exception &ex)
|
||||
{
|
||||
std::cout<<"An exception was thrown while trying to initialize the spin system. Exception message is: " << ex.what() << std::endl;
|
||||
return -1;
|
||||
}
|
||||
catch(...)
|
||||
{
|
||||
std::cout<<"An unhandled exception was thrown while trying to initialize the spin system."<< std::endl;
|
||||
return -2;
|
||||
}
|
||||
}
|
||||
|
||||
extern "C" int DenitializeSimulator(void* SpinSystemObject)
|
||||
{
|
||||
try
|
||||
{
|
||||
delete (static_cast<SpinSystemType*>(SpinSystemObject));
|
||||
return 0;
|
||||
}
|
||||
catch(std::exception &ex)
|
||||
{
|
||||
std::cout<<"An exception was thrown while trying to delete the spin system from memory. Exception message is: " << ex.what() << std::endl;
|
||||
return -1;
|
||||
}
|
||||
catch(...)
|
||||
{
|
||||
std::cout<<"An unhandled exception was thrown while trying to delete the spin system from memory."<< std::endl;
|
||||
return -2;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
extern "C" int SetGammasInSimulator(double* gammas, void* SpinSystemObject)
|
||||
{
|
||||
try
|
||||
{
|
||||
CX_VEC gammasVec((static_cast<SpinSystemType*>(SpinSystemObject))->getNumOfSpins(),1);
|
||||
for(int i = 0; i < gammasVec.size(); i++)
|
||||
{
|
||||
gammasVec[i] = gammas[i];
|
||||
}
|
||||
(static_cast<SpinSystemType*>(SpinSystemObject))->setGammas(gammasVec);
|
||||
return 0;
|
||||
}
|
||||
catch(std::exception &ex)
|
||||
{
|
||||
std::cout<<"An exception was thrown while trying to delete the spin system from memory. Exception message is: " << ex.what() << std::endl;
|
||||
return -1;
|
||||
}
|
||||
catch(...)
|
||||
{
|
||||
std::cout<<"An unhandled exception was thrown while trying to delete the spin system from memory."<< std::endl;
|
||||
return -2;
|
||||
}
|
||||
}
|
||||
|
||||
extern "C" int SetJCouplingsInSimulator(double* jCouplings, void* SpinSystemObject)
|
||||
{
|
||||
try
|
||||
{
|
||||
CX_MAT jCouplingsMat((static_cast<SpinSystemType*>(SpinSystemObject))->getNumOfSpins(),(static_cast<SpinSystemType*>(SpinSystemObject))->getNumOfSpins());
|
||||
devectorizeJCouplings((static_cast<SpinSystemType*>(SpinSystemObject))->getNumOfSpins(), jCouplings, jCouplingsMat);
|
||||
(static_cast<SpinSystemType*>(SpinSystemObject))->setJCouplings(jCouplingsMat);
|
||||
return 0;
|
||||
}
|
||||
catch(std::exception &ex)
|
||||
{
|
||||
std::cout<<"An exception was thrown while trying to delete the spin system from memory. Exception message is: " << ex.what() << std::endl;
|
||||
return -1;
|
||||
}
|
||||
catch(...)
|
||||
{
|
||||
std::cout<<"An unhandled exception was thrown while trying to delete the spin system from memory."<< std::endl;
|
||||
return -2;
|
||||
}
|
||||
}
|
||||
void _do_operation_evolve_time_dependent(SpinOperation* op, SpinSystemType* SpinsPtr, double* outputArray, long ¤tDataPoint)
|
||||
{
|
||||
if(debug) std::cout<<"Printing received data:"<<std::endl;
|
||||
if(op->Params_array_count == 0)
|
||||
{
|
||||
throw std::runtime_error("There's no data provided for the time-dependent evolution.");
|
||||
}
|
||||
else
|
||||
{
|
||||
//make sure that all lengths are equal
|
||||
long initialLength = op->Params_array_lengths[0];
|
||||
for(long i = 1; i < op->Params_array_count; i++)
|
||||
{
|
||||
if(op->Params_array_lengths[i] != initialLength)
|
||||
{
|
||||
throw std::length_error("Data arrays in time-dependent evolution are expected all to be of the same length.");
|
||||
}
|
||||
}
|
||||
}
|
||||
std::vector<std::string> varsNames(static_cast<std::vector<std::string>::size_type>(op->Params_array_count));
|
||||
std::copy(op->Params_array_names,op->Params_array_names+op->Params_array_count,varsNames.begin()); //copy names to vector<string>
|
||||
|
||||
CX_MAT evData(op->Params_array_lengths[0],op->Params_array_count);
|
||||
for(long i = 0; i < op->Params_array_count; i++)
|
||||
{
|
||||
std::copy(&op->Params_array[i][0],&op->Params_array[i][op->Params_array_lengths[i]],evData.begin()+evData.rows()*i);
|
||||
}
|
||||
std::set<char> dirString;
|
||||
if(op->Params_int[1]) dirString.insert('x');
|
||||
if(op->Params_int[2]) dirString.insert('y');
|
||||
if(op->Params_int[3]) dirString.insert('z');
|
||||
std::vector<Real> tr = SpinsPtr->evolveDensityMatrix(op->Params_real[0],varsNames,evData,static_cast<int>(op->Params_int[0]),dirString);
|
||||
std::copy(std::make_move_iterator(tr.begin()), std::make_move_iterator(tr.end()), outputArray + currentDataPoint);
|
||||
currentDataPoint += op->Params_array_lengths[0]*static_cast<long>(dirString.size());
|
||||
}
|
||||
|
||||
long ExecuteOperations(void* SpinSystemObject, void** ops, int numOfOperations, double* output, bool debug)
|
||||
{
|
||||
if(debug)
|
||||
{
|
||||
std::cout<<"Number of operations: "<<numOfOperations<<std::endl;
|
||||
}
|
||||
|
||||
SpinSystemType* SpinsPtr = static_cast<SpinSystemType*>(SpinSystemObject);
|
||||
long currentDataPoint = 0; //for a simulation with many operations that consecutively fill the output, this keeps track of the current point
|
||||
for(int i = 0; i < numOfOperations; i++) {
|
||||
void** currOperationBytePosition = (static_cast<void**>(ops));
|
||||
long OperationIdentifier = *(static_cast<long*>(currOperationBytePosition[i]));
|
||||
if(debug) std::cout<<"Identifier: "<<OperationIdentifier<<std::endl;
|
||||
if(OperationIdentifier == OPERATION__THERMAL_POPULATE) {
|
||||
SpinOperation* op;
|
||||
op = static_cast<SpinOperation*>(currOperationBytePosition[i]);
|
||||
SpinsPtr->populate_thermal(op->Params_real[0],op->Params_real[1],op->Params_real[2],op->Params_real[3]);
|
||||
}
|
||||
else if (OperationIdentifier == OPERATION__TIP_SPINS) {
|
||||
SpinOperation* op;
|
||||
op = static_cast<SpinOperation*>(currOperationBytePosition[i]);
|
||||
SpinsPtr->tipSpins(static_cast<int>(op->Params_int[0]),op->Params_real[0]);
|
||||
}
|
||||
else if (OperationIdentifier == OPERATION__SET_HAMILTONIAN) {
|
||||
SpinOperation* op;
|
||||
op = static_cast<SpinOperation*>(currOperationBytePosition[i]);
|
||||
SpinsPtr->calculateHamiltonians(op->Params_real[0],op->Params_real[1],op->Params_real[2]);
|
||||
}
|
||||
else if (OperationIdentifier == OPERATION__EVOLVE_TIME_INDEPENDENT) {
|
||||
SpinOperation* op;
|
||||
op = static_cast<SpinOperation*>(currOperationBytePosition[i]);
|
||||
std::vector<Real> trVals = SpinsPtr->solveMagnetization_parallel(op->Params_int[0],static_cast<int>(op->Params_int[1]));
|
||||
std::copy(trVals.begin(), trVals.end(), output + currentDataPoint);
|
||||
currentDataPoint += op->Params_int[0];
|
||||
}
|
||||
else if (OperationIdentifier == OPERATION__INIT_TIME_INDEPENDENT_EVOLUTION) {
|
||||
SpinOperation* op;
|
||||
op = static_cast<SpinOperation*>(currOperationBytePosition[i]);
|
||||
SpinsPtr->initTimeIndependentEvolution(op->Params_real[0],static_cast<int>(op->Params_int[0]));
|
||||
}
|
||||
else if (OperationIdentifier == OPERATION__EVOLVE_TIME_DEPENDENT) {
|
||||
_do_operation_evolve_time_dependent(static_cast<SpinOperation*>(currOperationBytePosition[i]), SpinsPtr, output, currentDataPoint);
|
||||
}
|
||||
else {
|
||||
std::cout << "Error: An unknown operation was requested... Exiting." << std::endl;
|
||||
exit(1);
|
||||
}
|
||||
}
|
||||
return currentDataPoint;
|
||||
}
|
||||
|
||||
extern "C" long CreateSignalFromInitializedSimulator(void* SpinSystemObject, void** ops, int numOfOperations, long numOfPoints, double* output)
|
||||
{
|
||||
try {
|
||||
if(debug)
|
||||
{
|
||||
std::cout<<"Number of operations: "<<numOfOperations<<std::endl;
|
||||
std::cout<<"Number of points: "<<numOfPoints<<std::endl;
|
||||
}
|
||||
|
||||
long processedNumOfPoints = ExecuteOperations(SpinSystemObject,ops,numOfOperations,output,debug);
|
||||
if (debug) std::cout<<processedNumOfPoints<<std::endl;
|
||||
return processedNumOfPoints;
|
||||
}
|
||||
catch(std::exception& ex) {
|
||||
std::cerr << "An exception was thrown by Spintrum. It says: " << ex.what() << std::endl;
|
||||
return 0;
|
||||
}
|
||||
catch(...) {
|
||||
std::cerr << "An unknown exception was thrown by Spintrum. " << std::endl;
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
void _fill_spin_info(int numOfSpins, double* gammas, double* jCouplings, int* spinMultiplicities, SpinInfo& spinInfo)
|
||||
{
|
||||
spinInfo.gammas.resize(numOfSpins,1);
|
||||
spinInfo.multiplicities.resize(numOfSpins,1);
|
||||
spinInfo.jCouplings.resize(numOfSpins,numOfSpins);
|
||||
for(int i = 0; i < numOfSpins; i++) {
|
||||
spinInfo.gammas[i] = gammas[i];
|
||||
}
|
||||
if(spinMultiplicities == 0) {
|
||||
for(int i = 0; i < numOfSpins; i++)
|
||||
spinInfo.multiplicities[i] = 2;
|
||||
}
|
||||
else {
|
||||
for(int i = 0; i < numOfSpins; i++)
|
||||
spinInfo.multiplicities[i] = spinMultiplicities[i];
|
||||
}
|
||||
if(debug) std::cout<<"Gammas:"<<std::endl;
|
||||
if(debug) std::cout<<spinInfo.gammas<<std::endl;
|
||||
devectorizeJCouplings(numOfSpins, jCouplings, spinInfo.jCouplings);
|
||||
if(debug) std::cout<<"J-couplings:"<<std::endl;
|
||||
if(debug) std::cout<<spinInfo.jCouplings<<std::endl;
|
||||
}
|
||||
|
||||
extern "C" long SimulateSignal(void** ops, double* gammas, double* jCouplings, int* spinMultiplicities, int numOfSpins, int numOfOperations, long numOfPoints, double* output)
|
||||
{
|
||||
try {
|
||||
print_software_info();
|
||||
if(debug) {
|
||||
std::cout<<"Number of operations: "<<numOfOperations<<std::endl;
|
||||
std::cout<<"Number of points: "<<numOfPoints<<std::endl;
|
||||
std::cout<<"Number of spins: "<<numOfSpins<<std::endl;
|
||||
}
|
||||
SpinInfo spinInfo;
|
||||
_fill_spin_info(numOfSpins, gammas, jCouplings, spinMultiplicities, spinInfo);
|
||||
SpinSystem<Real,std::complex<Real>,VEC,CX_VEC,MAT,CX_MAT > Spins(spinInfo.gammas,spinInfo.jCouplings,spinInfo.multiplicities);
|
||||
long processedNumOfPoints = ExecuteOperations(static_cast<void*>(&Spins),ops,numOfOperations,output,debug);
|
||||
if (debug) std::cout<<processedNumOfPoints<<std::endl;
|
||||
return processedNumOfPoints;
|
||||
}
|
||||
catch(std::exception& ex) {
|
||||
std::cerr << "An exception was thrown by Spintrum. It says: " << ex.what() << std::endl;
|
||||
return 0;
|
||||
}
|
||||
catch(...) {
|
||||
std::cerr << "An unknown exception was thrown by Spintrum. " << std::endl;
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue