added flexibility
This commit is contained in:
parent
4b8922ab55
commit
1c8befac3f
@ -3,33 +3,6 @@ project(RWSim VERSION 1.0)
|
||||
|
||||
set(CMAKE_CXX_STANDARD 17)
|
||||
|
||||
add_executable(rwsim main.cpp
|
||||
utils/functions.h
|
||||
utils/functions.cpp
|
||||
utils/io.cpp
|
||||
utils/io.h
|
||||
motions/base.cpp
|
||||
motions/base.h
|
||||
motions/random.cpp
|
||||
motions/random.h
|
||||
times/base.cpp
|
||||
times/base.h
|
||||
times/delta.cpp
|
||||
times/delta.h
|
||||
simulation/sims.cpp
|
||||
simulation/sims.h
|
||||
utils/ranges.cpp
|
||||
utils/ranges.h
|
||||
motions/tetrahedral.cpp
|
||||
motions/tetrahedral.h
|
||||
motions/isosmallangle.cpp
|
||||
motions/isosmallangle.h
|
||||
motions/coordinates.cpp
|
||||
motions/coordinates.h
|
||||
motions/bimodalangle.cpp
|
||||
motions/bimodalangle.h
|
||||
times/lognormal.cpp
|
||||
times/lognormal.h
|
||||
)
|
||||
add_subdirectory(src)
|
||||
|
||||
target_compile_options(rwsim PUBLIC -Werror -Wall -Wextra -Wconversion -O2)
|
||||
|
78
README.md
78
README.md
@ -3,24 +3,80 @@
|
||||
1. Clone repository with `git clone https://gitea.pkm.physik.tu-darmstadt.de/NMRRWSims/cpp.git`
|
||||
2. After download, change permissions of build.sh in terminal with `chmod a+x build.sh`
|
||||
|
||||
# Setup the simulation
|
||||
# Build
|
||||
|
||||
The workflows leaves yet much to be desired, it will become better (maybe)
|
||||
This
|
||||
|
||||
## Changes in `test.py`
|
||||
# Running
|
||||
|
||||
## Command line
|
||||
|
||||
To run a random walk simulation Execute `rwsim` in the command line with
|
||||
|
||||
```bash
|
||||
./rwsim /path/to/config.txt MotionModel DistributionModel --ste --spectrum -ARG1 1 -ARG2 2
|
||||
```
|
||||
|
||||
It needs three positional arguments: the path to your basic configuration file (see below) and the names of the motional model and of the distribution of correlation times.
|
||||
Set the optional arguments `--ste` and/or `--spectrum` to create Stimulated Echos or normal echo spectra, respectively.
|
||||
You can overwrite any parameter given in the configuration file by adding it as optional argument with a numerical value, e.g. `-TAU 1e-3` for a correlation time of 1 ms.
|
||||
|
||||
|
||||
## Configuration file `config.txt`
|
||||
|
||||
Change the values of delta, eta, mixing times, echo times,... in this file. If a paramter is defined multiple times, only the last one is used.
|
||||
|
||||
### General parameter
|
||||
|
||||
This list of general parameter are necessary for all simulations:
|
||||
|
||||
| Parameter | Description |
|
||||
|------------|----------------------------|
|
||||
| num_walker | Number of trajectories |
|
||||
| delta | Anisotropy parameter in Hz |
|
||||
| eta | Asymmetry parameter |
|
||||
|
||||
### Distribution of correlation times
|
||||
|
||||
Two distributions are available: A delta distribution `Delta`, i.e. the same correlation time for every walker, and a log-normal distribution `LogNormal`.
|
||||
|
||||
+ Parameters for delta distribution `Delta`
|
||||
|
||||
| Parameter | Description |
|
||||
|-----------|-----------------------|
|
||||
| tau | Jump time in s |
|
||||
|
||||
+ Parameters for log-normal distribution `LogNormal`
|
||||
|
||||
| Parameter | Description |
|
||||
|-----------|--------------------------------------------|
|
||||
| tau | Maximum jump time of the distribution in s |
|
||||
| sigma | Standard deviation of the distribution |
|
||||
|
||||
### Motion models
|
||||
|
||||
Four different jump models are implemented: Isotropic random jump `RandomJump`, isotropic jump with a certain angle, isotropic jump with a bimodal distribution of angles, and a tetrahedral jump `TetrahedralJump`.
|
||||
|
||||
+ Isotropic random jump `RandomJump` does not have additional parameters.
|
||||
+ Tetrahedral jump `TetrahedralJump` does not have additional parameters.
|
||||
+ Parameters for isotropic jump by an angle `IsotropicAngle`
|
||||
|
||||
| Parameter | Description |
|
||||
|-----------|----------------------|
|
||||
| angle | Jump angle in degree |
|
||||
|
||||
+ Parameters for isotropic jump with bimodal angle distribution `BimodalAngle`
|
||||
|
||||
| Parameter | Description |
|
||||
|--------------|--------------------------------------|
|
||||
| angle1 | First jump angle in degree |
|
||||
| angle2 | Second jump angle in degree |
|
||||
| probability1 | Probality that jump has angle1 (0-1) |
|
||||
|
||||
1. To run spectra, add `-spectrum` in line 14
|
||||
2. To run STE, add `-ste` in line 14
|
||||
3. Change values for tau, line broadening and pulse length in lines 88-90 (to simulate one tau value, set length of array to 1)
|
||||
4. Comment / Uncomment `post_process_ste` or `post_process_spectrum`.
|
||||
|
||||
## Change of models
|
||||
|
||||
1. In `main.cpp`, uncomment the motional model and distribution of correlation times you want to use, comment every other model
|
||||
|
||||
## Setting more parameters in `config.txt`
|
||||
|
||||
1. Change the values of delta, eta, mixing times, echo times,... in this file. If a paramter is defined multiple times, only the last one is used.
|
||||
|
||||
# Running
|
||||
|
||||
|
5
build.sh
5
build.sh
@ -4,7 +4,4 @@ cd build || exit
|
||||
cmake ..
|
||||
cmake --build .
|
||||
|
||||
cd ..
|
||||
|
||||
python test.py
|
||||
|
||||
cp ./src/rwsim ../rwsim
|
||||
|
16
config.txt
16
config.txt
@ -4,24 +4,20 @@ num_walker=20000
|
||||
delta=126e3
|
||||
eta=0.0
|
||||
# Distribution part
|
||||
# this tau value is overwritten if sim is run with test.py
|
||||
tau=1e-1
|
||||
tau=1e-2
|
||||
angle1=2
|
||||
angle2=30
|
||||
probability1=0.98
|
||||
probability1=0
|
||||
# Spectrum part
|
||||
dwell_time=1e-6
|
||||
dwell_time=1e-8
|
||||
num_acq=4096
|
||||
techo_start=0e-6
|
||||
techo_stop=40e-6
|
||||
techo_steps=5
|
||||
# STE part
|
||||
tevo_start=1e-6
|
||||
tevo_start=2e-6
|
||||
tevo_stop=120e-6
|
||||
tevo_steps=8
|
||||
tevo_steps=121
|
||||
tmix_start=1e-5
|
||||
tmix_stop=1e1
|
||||
tmix_steps=31
|
||||
tau=0.01
|
||||
tau=0.01
|
||||
tau=0.01
|
||||
tmix_steps=61
|
||||
|
49
main.py
Normal file
49
main.py
Normal file
@ -0,0 +1,49 @@
|
||||
from python.ste import *
|
||||
from python.helpers import *
|
||||
|
||||
# Simulation parameter
|
||||
motion = 'IsotropicAngle'
|
||||
distribution = 'Delta'
|
||||
parameter = {
|
||||
"angle": [3, 10, 30, 109.4],
|
||||
}
|
||||
|
||||
parameter = prepare_rw_parameter(parameter)
|
||||
|
||||
fig_tau_cc, ax_tau_cc = plt.subplots()
|
||||
ax_tau_cc.set_title('tau_cc')
|
||||
|
||||
fig_beta_cc, ax_beta_cc = plt.subplots()
|
||||
ax_beta_cc.set_title('beta_cc')
|
||||
|
||||
fig_finfty_cc, ax_finfty_cc = plt.subplots()
|
||||
ax_finfty_cc.set_title('f_infty_cc')
|
||||
|
||||
fig_tau_ss, ax_tau_ss = plt.subplots()
|
||||
ax_tau_ss.set_title('tau_cc')
|
||||
|
||||
fig_beta_ss, ax_beta_ss = plt.subplots()
|
||||
ax_beta_ss.set_title('beta_cc')
|
||||
|
||||
fig_finfty_ss, ax_finfty_ss = plt.subplots()
|
||||
ax_finfty_ss.set_title('f_infty_cc')
|
||||
|
||||
for variation in parameter:
|
||||
print(f"\nRun RW for {motion}/{distribution} with arguments {variation}\n")
|
||||
run_sims(motion, distribution, ste=True, spectrum=True, **variation)
|
||||
|
||||
conf_file = find_config_file(variation)
|
||||
print(conf_file)
|
||||
|
||||
vary_string, tau_cc, beta_cc, finfty_cc, tau_ss, beta_ss, finfty_ss = fit_and_save_ste(conf_file, plot_decays=False, verbose=False)
|
||||
|
||||
ax_tau_cc.semilogy(*tau_cc.T, label=vary_string)
|
||||
ax_beta_cc.plot(*beta_cc.T, label=vary_string)
|
||||
ax_finfty_cc.plot(*finfty_cc.T, label=vary_string)
|
||||
ax_tau_ss.semilogy(*tau_ss.T, label=vary_string)
|
||||
ax_beta_ss.plot(*beta_ss.T, label=vary_string)
|
||||
ax_finfty_ss.plot(*finfty_ss.T, label=vary_string)
|
||||
|
||||
for ax in [ax_tau_cc, ax_beta_cc, ax_finfty_cc, ax_tau_ss, ax_beta_ss, ax_finfty_ss]:
|
||||
ax.legend()
|
||||
plt.show()
|
0
python/__init__.py
Normal file
0
python/__init__.py
Normal file
77
python/helpers.py
Normal file
77
python/helpers.py
Normal file
@ -0,0 +1,77 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import pathlib
|
||||
import re
|
||||
import subprocess
|
||||
from itertools import product
|
||||
|
||||
def prepare_rw_parameter(parameter: dict) -> list:
|
||||
"""
|
||||
Converts a dictionary of iterables to list of dictionaries
|
||||
|
||||
Example:
|
||||
If Input is {'a': [1, 2, 3], 'b' = [4, 5]}, output is cartesian product of dictionary values, i.e.,
|
||||
[{'a': 1, 'b': 4}, {'a': 1, 'b': 5}, {'a': 2, 'b': 4}, {'a': 2, 'b': 5}, {'a': 3, 'b': 4}, {'a': 3, 'b': 5}]
|
||||
|
||||
:param parameter: dictionary of list values
|
||||
:return: list of dictionaries
|
||||
"""
|
||||
output = {}
|
||||
for k, v in parameter.items():
|
||||
if isinstance(v, (float, int)):
|
||||
v = [v]
|
||||
|
||||
output[k] = v
|
||||
|
||||
output = list(dict(zip(parameter.keys(), step)) for step in product(*output.values()))
|
||||
|
||||
return output
|
||||
|
||||
|
||||
def run_sims(
|
||||
motion: str,
|
||||
distribution: str,
|
||||
ste: bool = True,
|
||||
spectrum: bool = False,
|
||||
exec_file: str = './rwsim',
|
||||
config_file: str = './config.txt',
|
||||
**kwargs
|
||||
) -> None:
|
||||
|
||||
# set positional arguments
|
||||
arguments = [exec_file, config_file, motion, distribution]
|
||||
|
||||
if ste:
|
||||
arguments += ['--ste']
|
||||
if spectrum:
|
||||
arguments += ['--spectrum']
|
||||
|
||||
# add optional parameters that overwrite those given by config file
|
||||
for k, v in kwargs.items():
|
||||
arguments += [f'-{k.upper()}', f'{v}']
|
||||
|
||||
subprocess.run(arguments)
|
||||
|
||||
|
||||
def find_config_file(var_params: dict) -> pathlib.Path:
|
||||
# TODO handle situation if multiple files fit
|
||||
pattern = re.compile('|'.join(([f'{k}={v:1.6e}' for (k, v) in var_params.items()])).replace('.', '\.').replace('+', '\+'))
|
||||
|
||||
for p_file in pathlib.Path('.').glob('*_parameter.txt'):
|
||||
if len(re.findall(pattern, str(p_file))) == len(var_params):
|
||||
return p_file
|
||||
|
||||
|
||||
def read_parameter_file(path: str | pathlib.Path) -> dict[str, float]:
|
||||
path = pathlib.Path(path)
|
||||
if not path.exists():
|
||||
raise ValueError(f"No parameter file found at {path}")
|
||||
|
||||
parameter_dict = {}
|
||||
with path.open('r') as f:
|
||||
for line in f.readlines():
|
||||
k, v = line.split('=')
|
||||
parameter_dict[k] = float(v)
|
||||
|
||||
k, v = line.split('=')
|
||||
return parameter_dict
|
70
python/spectrum.py
Normal file
70
python/spectrum.py
Normal file
@ -0,0 +1,70 @@
|
||||
import numpy
|
||||
import numpy as np
|
||||
from matplotlib import pyplot
|
||||
|
||||
|
||||
|
||||
# parameter for spectrum simulations
|
||||
lb = 2e3
|
||||
pulse_length = 2e-6
|
||||
|
||||
|
||||
def dampening(x: np.ndarray, apod: float) -> np.ndarray:
|
||||
"""
|
||||
Calculate additional dampening to account e.g. for field inhomogeneities.
|
||||
|
||||
:param x: Time axis in seconds
|
||||
:param apod: Dampening factor in 1/seconds
|
||||
:return: Exponential dampening
|
||||
"""
|
||||
|
||||
return np.exp(-apod * x)
|
||||
|
||||
|
||||
def pulse_attn(freq: np.ndarray, t_pulse: float) -> np.ndarray:
|
||||
"""
|
||||
Calculate attenuation of signal to account for finite pulse lengths.
|
||||
|
||||
See Schmitt-Rohr/Spieß, eq. 2.126 for more information.
|
||||
|
||||
:param freq: Frequency axis in Hz
|
||||
:param t_pulse: Assumed pulse length in s
|
||||
:return: Attenuation factor.
|
||||
"""
|
||||
# cf. Schmitt-Rohr/Spieß eq. 2.126; omega_1 * t_p = pi/2
|
||||
pi_half_squared = np.pi**2 / 4
|
||||
omega = 2 * np.pi * freq
|
||||
|
||||
numerator = np.sin(np.sqrt(pi_half_squared + omega**2 * t_pulse**2 / 2))
|
||||
denominator = np.sqrt(pi_half_squared + omega**2 * t_pulse**2 / 4)
|
||||
|
||||
return np.pi * numerator / denominator / 2
|
||||
|
||||
|
||||
def post_process_spectrum(taus, apod, tpulse):
|
||||
reduction_factor = np.zeros((taus.size, 5)) # hard-coded t_echo :(
|
||||
|
||||
for i, tau in enumerate(taus):
|
||||
try:
|
||||
raw_data = np.loadtxt(f'fid_tau={tau:.6e}.dat')
|
||||
except OSError:
|
||||
continue
|
||||
|
||||
t = raw_data[:, 0]
|
||||
timesignal = raw_data[:, 1:]
|
||||
|
||||
timesignal *= dampening(t, apod)[:, None]
|
||||
timesignal[0, :] /= 2
|
||||
|
||||
# FT to spectrum
|
||||
freq = np.fft.fftshift(np.fft.fftfreq(t.size, d=1e-6))
|
||||
spec = np.fft.fftshift(np.fft.fft(timesignal, axis=0), axes=0).real
|
||||
spec *= pulse_attn(freq, t_pulse=tpulse)[:, None]
|
||||
|
||||
reduction_factor[i, :] = 2*timesignal[0, :]
|
||||
|
||||
plt.plot(freq, spec)
|
||||
plt.show()
|
||||
|
||||
plt.semilogx(taus, reduction_factor, '.')
|
||||
plt.show()
|
102
python/ste.py
Normal file
102
python/ste.py
Normal file
@ -0,0 +1,102 @@
|
||||
import pathlib
|
||||
|
||||
import numpy
|
||||
import numpy as np
|
||||
from matplotlib import pyplot as plt
|
||||
from scipy.optimize import curve_fit
|
||||
|
||||
from python.helpers import read_parameter_file
|
||||
|
||||
|
||||
def ste_decay(x: np.ndarray, m0: float, t: float, beta: float, finfty: float) -> np.ndarray:
|
||||
"""
|
||||
Calculate stimulated-echo decay.
|
||||
|
||||
:param x: Mixing times in seconds.
|
||||
:param m0: Amplitude
|
||||
:param t: Correlation time in seconds
|
||||
:param beta: Stretching parameter
|
||||
:param finfty: Final plateau
|
||||
:return: Stimulated-echo decay
|
||||
"""
|
||||
return m0 * ((1-finfty) * np.exp(-(x/t)**beta) + finfty)
|
||||
|
||||
|
||||
def fit_decay(x: np.ndarray, y: np.ndarray, tevo: np.ndarray, verbose: bool = True) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
|
||||
num_evo = y.shape[1]
|
||||
|
||||
tau_fit = np.empty((num_evo, 2))
|
||||
tau_fit[:, 0] = tevo
|
||||
|
||||
beta_fit = np.empty((num_evo, 2))
|
||||
beta_fit[:, 0] = tevo
|
||||
|
||||
finfty_fit = np.empty((num_evo, 2))
|
||||
finfty_fit[:, 0] = tevo
|
||||
|
||||
scaled_y = (y-y[-1, :]) / (y[0, :]-y[-1, :])
|
||||
|
||||
for j in range(num_evo):
|
||||
p0 = [scaled_y[0, 1], x[np.argmin(np.abs(scaled_y[:, j]-np.exp(-1)))], 0.5, 0.1]
|
||||
|
||||
try:
|
||||
res = curve_fit(ste_decay, x, y[:, j], p0, bounds=[(0, 0, 0., 0), (np.inf, np.inf, 1, 1)])
|
||||
except RuntimeError as e:
|
||||
print(f'Fit {j+1} of {num_evo} failed with {e.args}')
|
||||
continue
|
||||
|
||||
m0, tauc, beta, finfty = res[0]
|
||||
|
||||
if verbose:
|
||||
print(f'Fit {j+1} of {num_evo}: tau_c = {tauc:.6e}, beta={beta:.4e}, amplitude = {m0: .4e}, f_infty={finfty:.4e}')
|
||||
|
||||
tau_fit[j, 1] = tauc
|
||||
beta_fit[j, 1] = beta
|
||||
finfty_fit[j, 1] = finfty
|
||||
|
||||
return tau_fit, beta_fit, finfty_fit
|
||||
|
||||
|
||||
def fit_and_save_ste(parameter_file: pathlib.Path, plot_decays: bool = True, verbose: bool = True):
|
||||
# read simulation parameters
|
||||
parameter = read_parameter_file(parameter_file)
|
||||
|
||||
# files have form ste_arg=0.000000e+01_parameter.txt, first remove ste part then parameter.txt to get variables
|
||||
varied_string = str(parameter_file).partition('_')[-1].rpartition('_')[0]
|
||||
|
||||
# make evolution times
|
||||
tevo = np.linspace(parameter['tevo_start'], parameter['tevo_stop'], num=int(parameter['tevo_steps']))
|
||||
|
||||
raw_data_cc = np.loadtxt(f'coscos_{varied_string}.dat')
|
||||
raw_data_ss = np.loadtxt(f'sinsin_{varied_string}.dat')
|
||||
|
||||
t_mix = raw_data_cc[:, 0]
|
||||
cc_decay = raw_data_cc[:, 1:]
|
||||
ss_decay = raw_data_ss[:, 1:]
|
||||
|
||||
if plot_decays:
|
||||
fig_cc, ax_cc = plt.subplots()
|
||||
ax_cc.set_title('Cos-Cos')
|
||||
ax_cc.semilogx(t_mix, cc_decay, '.')
|
||||
|
||||
fig_ss, ax_ss = plt.subplots()
|
||||
ax_ss.set_title('Sin-Sin')
|
||||
ax_ss.semilogx(t_mix, ss_decay, '.')
|
||||
|
||||
plt.show()
|
||||
|
||||
print('Fit Cos-Cos')
|
||||
tau_cc, beta_cc, finfty_cc = fit_decay(t_mix, cc_decay, tevo, verbose=verbose)
|
||||
|
||||
np.savetxt(f'tau_cc_{varied_string}.dat', tau_cc)
|
||||
np.savetxt(f'beta_cc_{varied_string}.dat', beta_cc)
|
||||
np.savetxt(f'finfty_cc_{varied_string}.dat', finfty_cc)
|
||||
|
||||
print('Fit Sin-Sin')
|
||||
tau_ss, beta_ss, finfty_ss = fit_decay(t_mix, ss_decay, tevo, verbose=verbose)
|
||||
|
||||
np.savetxt(f'tau_ss_{varied_string}.dat', tau_ss)
|
||||
np.savetxt(f'beta_ss_{varied_string}.dat', beta_ss)
|
||||
np.savetxt(f'finfty_ss_{varied_string}.dat', finfty_ss)
|
||||
|
||||
return varied_string, tau_cc, beta_cc, finfty_cc, tau_ss, beta_ss, finfty_ss
|
35
src/CMakeLists.txt
Normal file
35
src/CMakeLists.txt
Normal file
@ -0,0 +1,35 @@
|
||||
cmake_minimum_required(VERSION 3.18)
|
||||
|
||||
set(CMAKE_CXX_STANDARD 17)
|
||||
|
||||
|
||||
add_executable(rwsim main.cpp
|
||||
utils/functions.h
|
||||
utils/functions.cpp
|
||||
utils/io.cpp
|
||||
utils/io.h
|
||||
motions/base.cpp
|
||||
motions/base.h
|
||||
motions/random.cpp
|
||||
motions/random.h
|
||||
times/base.cpp
|
||||
times/base.h
|
||||
times/delta.cpp
|
||||
times/delta.h
|
||||
simulation/sims.cpp
|
||||
simulation/sims.h
|
||||
utils/ranges.cpp
|
||||
utils/ranges.h
|
||||
motions/tetrahedral.cpp
|
||||
motions/tetrahedral.h
|
||||
motions/isosmallangle.cpp
|
||||
motions/isosmallangle.h
|
||||
motions/coordinates.cpp
|
||||
motions/coordinates.h
|
||||
motions/bimodalangle.cpp
|
||||
motions/bimodalangle.h
|
||||
times/lognormal.cpp
|
||||
times/lognormal.h
|
||||
)
|
||||
|
||||
target_compile_options(rwsim PUBLIC -Werror -Wall -Wextra -Wconversion -O2)
|
@ -2,8 +2,7 @@
|
||||
#include "utils/io.h"
|
||||
#include "simulation/sims.h"
|
||||
#include "motions/base.h"
|
||||
#include "times/delta.h"
|
||||
#include "times/lognormal.h"
|
||||
#include "times/base.h"
|
||||
|
||||
|
||||
#include <iostream>
|
||||
@ -39,15 +38,12 @@ int main (const int argc, char *argv[]) {
|
||||
std::mt19937_64 rng(rd());
|
||||
|
||||
Motion *motion = Motion::createFromInput(args.motion_type, rng);
|
||||
|
||||
auto dist = DeltaDistribution(rng);
|
||||
// auto dist = LogNormalDistribution(1, 2, rng); // arguments: tau_max, sigma
|
||||
|
||||
Distribution *dist = Distribution::createFromInput(args.distribution_type, rng);
|
||||
if (args.spectrum) {
|
||||
run_spectrum(parameter, *motion, dist);
|
||||
run_spectrum(parameter, args.optional, *motion, *dist);
|
||||
}
|
||||
if (args.ste) {
|
||||
run_ste(parameter, *motion, dist);
|
||||
run_ste(parameter, args.optional, *motion, *dist);
|
||||
}
|
||||
|
||||
return 0;
|
@ -1,21 +1,13 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#include <random>
|
||||
#include <cmath>
|
||||
|
||||
#include "base.h"
|
||||
|
||||
#include <stdexcept>
|
||||
#include <utility>
|
||||
|
||||
#include "coordinates.h"
|
||||
#include "bimodalangle.h"
|
||||
#include "isosmallangle.h"
|
||||
#include "random.h"
|
||||
#include "tetrahedral.h"
|
||||
|
||||
#include <stdexcept>
|
||||
|
||||
Motion::Motion(std::string name, const double delta, const double eta, std::mt19937_64& rng) : m_name(std::move(name)), m_delta(delta), m_eta(eta), m_rng(rng) {
|
||||
m_uni_dist = std::uniform_real_distribution(0., 1.);
|
||||
}
|
@ -1,11 +1,8 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_MOTIONBASE_H
|
||||
#define RWSIM_MOTIONBASE_H
|
||||
|
||||
#include "coordinates.h"
|
||||
|
||||
#include <random>
|
||||
#include <unordered_map>
|
||||
|
||||
@ -34,7 +31,7 @@ public:
|
||||
static Motion* createFromInput(const std::string& input, std::mt19937_64& rng);
|
||||
|
||||
protected:
|
||||
std::string m_name{"Base motion"};
|
||||
std::string m_name{"BaseMotion"};
|
||||
double m_delta{1.};
|
||||
double m_eta{0.};
|
||||
std::mt19937_64& m_rng;
|
@ -1,16 +1,13 @@
|
||||
//
|
||||
// Created by dominik on 8/23/24.
|
||||
//
|
||||
|
||||
#include "bimodalangle.h"
|
||||
#include "base.h"
|
||||
|
||||
BimodalAngle::BimodalAngle(const double delta, const double eta, const double angle1, const double angle2, const double prob, std::mt19937_64 &rng) :
|
||||
Motion(std::string("Bimodal Angle Jump"), delta, eta, rng),
|
||||
Motion(std::string("BimodalAngle"), delta, eta, rng),
|
||||
m_angle1(angle1 * M_PI / 180.0),
|
||||
m_angle2(angle2 * M_PI / 180.0),
|
||||
m_prob(prob) {};
|
||||
BimodalAngle::BimodalAngle(std::mt19937_64 &rng) : Motion(std::string("Bimodal Angle Jump"), rng) {}
|
||||
BimodalAngle::BimodalAngle(std::mt19937_64 &rng) : Motion(std::string("BimodalAngle"), rng) {}
|
||||
|
||||
void BimodalAngle::initialize() {
|
||||
m_prev_pos = draw_position();
|
@ -1,6 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/23/24.
|
||||
//
|
||||
|
||||
#ifndef BIMODALANGLE_H
|
||||
#define BIMODALANGLE_H
|
@ -1,11 +1,7 @@
|
||||
//
|
||||
// Created by dominik on 8/22/24.
|
||||
//
|
||||
|
||||
#include "coordinates.h"
|
||||
|
||||
#include <cmath>
|
||||
#include <iostream>
|
||||
#include <ostream>
|
||||
|
||||
SphericalPos rotate(const SphericalPos& old_pos, const double alpha, const double beta) {
|
||||
const double sin_alpha{std::sin(alpha)};
|
@ -1,6 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/22/24.
|
||||
//
|
||||
|
||||
#ifndef COORDINATES_H
|
||||
#define COORDINATES_H
|
@ -1,18 +1,13 @@
|
||||
//
|
||||
// Created by dominik on 8/21/24.
|
||||
//
|
||||
|
||||
#include "isosmallangle.h"
|
||||
#include "coordinates.h"
|
||||
|
||||
#include <iostream>
|
||||
#include <ostream>
|
||||
|
||||
#include "coordinates.h"
|
||||
|
||||
|
||||
SmallAngle::SmallAngle(const double delta, const double eta, const double chi, std::mt19937_64 &rng) :
|
||||
Motion(std::string("Isotropic Angle Jump"), delta, eta, rng), m_chi(chi * M_PI / 180.0) {};
|
||||
SmallAngle::SmallAngle(std::mt19937_64 &rng) : Motion(std::string("Isotropic Angle Jump"), rng) {}
|
||||
Motion(std::string("IsotropicAngle"), delta, eta, rng), m_chi(chi * M_PI / 180.0) {};
|
||||
SmallAngle::SmallAngle(std::mt19937_64 &rng) : Motion(std::string("IsotropicAngle"), rng) {}
|
||||
|
||||
void SmallAngle::initialize() {
|
||||
m_prev_pos = draw_position();
|
@ -1,6 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/21/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_MOTIONISOSMALLANGLE_H
|
||||
#define RWSIM_MOTIONISOSMALLANGLE_H
|
@ -1,13 +1,10 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#include "random.h"
|
||||
|
||||
|
||||
RandomJump::RandomJump(const double delta, const double eta, std::mt19937_64 &rng) : Motion(std::string("Random Jump"), delta, eta, rng) {}
|
||||
RandomJump::RandomJump(const double delta, const double eta, std::mt19937_64 &rng) : Motion(std::string("RandomJump"), delta, eta, rng) {}
|
||||
|
||||
RandomJump::RandomJump(std::mt19937_64 &rng) : Motion(std::string("Random Jump"), rng) {}
|
||||
RandomJump::RandomJump(std::mt19937_64 &rng) : Motion(std::string("RandomJump"), rng) {}
|
||||
|
||||
void RandomJump::initialize() {}
|
||||
|
@ -1,7 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_MOTIONRANDOMJUMP_H
|
||||
#define RWSIM_MOTIONRANDOMJUMP_H
|
||||
|
@ -1,14 +1,13 @@
|
||||
//
|
||||
// Created by dominik on 8/16/24.
|
||||
//
|
||||
#include "tetrahedral.h"
|
||||
|
||||
#include <random>
|
||||
|
||||
#include "tetrahedral.h"
|
||||
|
||||
TetrahedralJump::TetrahedralJump(const double delta, const double eta, std::mt19937_64& rng) :
|
||||
Motion(std::string{"TetrahedralJump"}, delta, eta, rng) {}
|
||||
Motion(std::string{"FourSiteTetrahedral"}, delta, eta, rng) {}
|
||||
|
||||
TetrahedralJump::TetrahedralJump(std::mt19937_64& rng) : Motion(std::string{"TetrahedralJump"}, rng) {}
|
||||
TetrahedralJump::TetrahedralJump(std::mt19937_64& rng) : Motion(std::string{"FourSiteTetrahedral"}, rng) {}
|
||||
|
||||
void TetrahedralJump::initialize() {
|
||||
const auto pos = draw_position();
|
@ -1,7 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/16/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_MOTIONTETRAHEDRAL_H
|
||||
#define RWSIM_MOTIONTETRAHEDRAL_H
|
||||
|
@ -15,8 +15,12 @@
|
||||
#include <chrono>
|
||||
|
||||
|
||||
|
||||
void run_spectrum(std::unordered_map<std::string, double>& parameter, Motion& motion, Distribution& dist) {
|
||||
void run_spectrum(
|
||||
std::unordered_map<std::string, double>& parameter,
|
||||
std::unordered_map<std::string, double> optional,
|
||||
Motion& motion,
|
||||
Distribution& dist
|
||||
) {
|
||||
const int num_walker = static_cast<int>(parameter["num_walker"]);
|
||||
|
||||
// time axis for all time signals
|
||||
@ -26,23 +30,20 @@ void run_spectrum(std::unordered_map<std::string, double>& parameter, Motion& mo
|
||||
|
||||
// make timesignal vectors and set them to zero
|
||||
std::map<double, std::vector<double>> fid_dict;
|
||||
for (auto t_evo_i: echo_times) {
|
||||
fid_dict[t_evo_i] = std::vector<double>(num_acq);
|
||||
std::fill(fid_dict[t_evo_i].begin(), fid_dict[t_evo_i].end(), 0.);
|
||||
for (auto t_echo_i: echo_times) {
|
||||
fid_dict[t_echo_i] = std::vector<double>(num_acq);
|
||||
std::fill(fid_dict[t_echo_i].begin(), fid_dict[t_echo_i].end(), 0.);
|
||||
}
|
||||
|
||||
// calculate min length of a trajectory
|
||||
const double tmax = *std::max_element(echo_times.begin(), echo_times.end()) * 2 + t_fid.back();
|
||||
|
||||
// set parameter in distribution and motion model
|
||||
const double tau = parameter.at("tau");
|
||||
dist.setTau(tau);
|
||||
dist.setParameters(parameter);
|
||||
motion.setParameters(parameter);
|
||||
|
||||
const auto start = std::chrono::system_clock::now();
|
||||
const auto start = printStart(optional);
|
||||
auto last_print_out = std::chrono::system_clock::now();
|
||||
const time_t start_time = std::chrono::system_clock::to_time_t(start);
|
||||
std::cout << "Start tau = " << tau << "s : " << ctime(&start_time);
|
||||
|
||||
// let the walker walk
|
||||
for (int mol_i = 0; mol_i < num_walker; mol_i++){
|
||||
@ -70,19 +71,19 @@ void run_spectrum(std::unordered_map<std::string, double>& parameter, Motion& mo
|
||||
}
|
||||
|
||||
// write fid to files
|
||||
fid_write_out("fid", t_fid, fid_dict, tau);
|
||||
|
||||
const auto end = std::chrono::system_clock::now();
|
||||
|
||||
std::chrono::duration<float> duration = end - start;
|
||||
const time_t end_time = std::chrono::system_clock::to_time_t(end);
|
||||
std::cout << "End tau = " << tau << "s : " << ctime(&end_time);
|
||||
std::cout << "Duration: " << duration.count() << "s\n" << std::endl;
|
||||
save_parameter_to_file("timesignal", motion.getName(), dist.getName(), parameter, optional);
|
||||
save_data_to_file("timesignal", motion.getName(), dist.getName(), t_fid, fid_dict, optional);
|
||||
|
||||
printEnd(start);
|
||||
}
|
||||
|
||||
|
||||
void run_ste(std::unordered_map<std::string, double>& parameter, Motion& motion, Distribution& dist) {
|
||||
void run_ste(
|
||||
std::unordered_map<std::string, double>& parameter,
|
||||
std::unordered_map<std::string, double> optional,
|
||||
Motion& motion,
|
||||
Distribution& dist
|
||||
) {
|
||||
const int num_walker = static_cast<int>(parameter[std::string("num_walker")]);
|
||||
|
||||
const int num_mix_times = static_cast<int>(parameter[std::string("tmix_steps")]);
|
||||
@ -102,14 +103,11 @@ void run_ste(std::unordered_map<std::string, double>& parameter, Motion& motion,
|
||||
const double tmax = *std::max_element(evolution_times.begin(), evolution_times.end()) * 2 + *std::max_element(mixing_times.begin(), mixing_times.end());
|
||||
|
||||
// set parameter in distribution and motion model
|
||||
const double tau = parameter.at("tau");
|
||||
dist.setTau(tau);
|
||||
dist.setParameters(parameter);
|
||||
motion.setParameters(parameter);
|
||||
|
||||
const auto start = std::chrono::system_clock::now();
|
||||
const auto start = printStart(optional);
|
||||
auto last_print_out = std::chrono::system_clock::now();
|
||||
const time_t start_time = std::chrono::system_clock::to_time_t(start);
|
||||
std::cout << "Start tau = " << tau << "s : " << ctime(&start_time);
|
||||
|
||||
// let the walker walk
|
||||
for (int mol_i = 0; mol_i < num_walker; mol_i++){
|
||||
@ -148,20 +146,21 @@ void run_ste(std::unordered_map<std::string, double>& parameter, Motion& motion,
|
||||
}
|
||||
|
||||
// write to files
|
||||
fid_write_out("coscos", mixing_times, cc_dict, tau);
|
||||
fid_write_out("sinsin", mixing_times, ss_dict, tau);
|
||||
|
||||
const auto end = std::chrono::system_clock::now();
|
||||
|
||||
const std::chrono::duration<float> duration = end - start;
|
||||
const time_t end_time = std::chrono::system_clock::to_time_t(end);
|
||||
std::cout << "End tau = " << tau << "s : " << ctime(&end_time);
|
||||
std::cout << "Duration: " << duration.count() << "s\n" << std::endl;
|
||||
save_parameter_to_file("ste", motion.getName(), dist.getName(), parameter, optional);
|
||||
save_data_to_file("coscos", motion.getName(), dist.getName(), mixing_times, cc_dict, optional);
|
||||
save_data_to_file("sinsin", motion.getName(), dist.getName(), mixing_times, ss_dict, optional);
|
||||
|
||||
printEnd(start);
|
||||
}
|
||||
|
||||
|
||||
void make_trajectory(Motion& motion, Distribution& dist, const double t_max, std::vector<double>& out_time, std::vector<double>& out_phase) {
|
||||
void make_trajectory(
|
||||
Motion& motion,
|
||||
Distribution& dist,
|
||||
const double t_max,
|
||||
std::vector<double>& out_time,
|
||||
std::vector<double>& out_phase
|
||||
) {
|
||||
// Starting position
|
||||
double t_passed = 0;
|
||||
double phase = 0;
|
||||
@ -181,3 +180,28 @@ void make_trajectory(Motion& motion, Distribution& dist, const double t_max, std
|
||||
out_phase.emplace_back(phase);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
std::chrono::system_clock::time_point printStart(std::unordered_map<std::string, double> &optional) {
|
||||
const auto start = std::chrono::system_clock::now();
|
||||
const time_t start_time = std::chrono::system_clock::to_time_t(start);
|
||||
|
||||
std::cout << "Random walk for ";
|
||||
for (const auto& [key, value] : optional) {
|
||||
std::cout << key << " = " << value << "; ";
|
||||
}
|
||||
std::cout << std::endl;
|
||||
std::cout << "Start: " << ctime(&start_time);
|
||||
|
||||
return start;
|
||||
}
|
||||
|
||||
|
||||
void printEnd(const std::chrono::system_clock::time_point start) {
|
||||
const auto end = std::chrono::system_clock::now();
|
||||
|
||||
const std::chrono::duration<float> duration = end - start;
|
||||
const time_t end_time = std::chrono::system_clock::to_time_t(end);
|
||||
std::cout << "End: " << ctime(&end_time);
|
||||
std::cout << "Duration: " << duration.count() << "s\n" << std::endl;
|
||||
}
|
@ -1,7 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/14/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_SIMS_H
|
||||
#define RWSIM_SIMS_H
|
||||
|
||||
@ -10,24 +6,27 @@
|
||||
|
||||
#include <unordered_map>
|
||||
#include <string>
|
||||
#include <chrono>
|
||||
|
||||
/**
|
||||
* @brief Run simulation for spectra
|
||||
*
|
||||
* @param parameter Dictionary of parameter for simulation
|
||||
* @param optional Dictionary of parameter set via command line
|
||||
* @param motion Motion model
|
||||
* @param dist Distribution of correlation times
|
||||
*/
|
||||
void run_spectrum(std::unordered_map<std::string, double>& parameter, Motion& motion, Distribution& dist);
|
||||
void run_spectrum(std::unordered_map<std::string, double>& parameter, std::unordered_map<std::string, double> optional, Motion& motion, Distribution& dist);
|
||||
|
||||
/**
|
||||
* @brief Run simulation for stimulated echoes
|
||||
*
|
||||
* @param parameter Dictionary of parameter for simulation
|
||||
* @param optional Dictionary of parameter set via command line
|
||||
* @param motion Motion model
|
||||
* @param dist Distribution of correlation times
|
||||
*/
|
||||
void run_ste(std::unordered_map<std::string, double>& parameter, Motion& motion, Distribution& dist);
|
||||
void run_ste(std::unordered_map<std::string, double>& parameter, std::unordered_map<std::string, double> optional, Motion& motion, Distribution& dist);
|
||||
|
||||
/**
|
||||
* @brief Create trajectory of a single walker
|
||||
@ -40,4 +39,7 @@ void run_ste(std::unordered_map<std::string, double>& parameter, Motion& motion,
|
||||
*/
|
||||
void make_trajectory(Motion& motion, Distribution& dist, double t_max, std::vector<double>& out_time, std::vector<double>& out_phase);
|
||||
|
||||
std::chrono::system_clock::time_point printStart(std::unordered_map<std::string, double> &optional);
|
||||
void printEnd(std::chrono::system_clock::time_point start);
|
||||
|
||||
#endif //RWSIM_SIMS_H
|
27
src/times/base.cpp
Normal file
27
src/times/base.cpp
Normal file
@ -0,0 +1,27 @@
|
||||
#include "base.h"
|
||||
#include "delta.h"
|
||||
#include "lognormal.h"
|
||||
|
||||
#include <stdexcept>
|
||||
|
||||
Distribution::Distribution(std::string name, const double tau, std::mt19937_64 &rng) : m_name(std::move(name)), m_tau(tau), m_tau_jump(tau), m_rng(rng) {}
|
||||
|
||||
Distribution::Distribution(std::string name, std::mt19937_64 &rng) : m_name(std::move(name)), m_rng(rng) {}
|
||||
|
||||
double Distribution::tau_wait() const {
|
||||
return std::exponential_distribution(1./m_tau_jump)(m_rng);
|
||||
}
|
||||
|
||||
void Distribution::setParameters(const std::unordered_map<std::string, double> ¶meters) {
|
||||
m_tau = parameters.at("tau");
|
||||
}
|
||||
|
||||
Distribution* Distribution::createFromInput(const std::string& input, std::mt19937_64& rng) {
|
||||
if (input == "Delta")
|
||||
return new DeltaDistribution(rng);
|
||||
|
||||
if (input == "LogNormal")
|
||||
return new LogNormalDistribution(rng);
|
||||
|
||||
throw std::invalid_argument("Invalid input " + input);
|
||||
}
|
33
src/times/base.h
Normal file
33
src/times/base.h
Normal file
@ -0,0 +1,33 @@
|
||||
#ifndef RWSIM_TIMESBASE_H
|
||||
#define RWSIM_TIMESBASE_H
|
||||
|
||||
#include <random>
|
||||
#include <unordered_map>
|
||||
|
||||
class Distribution {
|
||||
public:
|
||||
virtual ~Distribution() = default;
|
||||
|
||||
Distribution(std::string, double, std::mt19937_64&);
|
||||
explicit Distribution(std::string, std::mt19937_64&);
|
||||
|
||||
[[nodiscard]] double getTau() const { return m_tau; }
|
||||
void setTau(const double tau) { m_tau = tau; }
|
||||
[[nodiscard]] std::string getName() const { return m_name; };
|
||||
|
||||
virtual void setParameters(const std::unordered_map<std::string, double>&);
|
||||
|
||||
virtual void initialize() = 0;
|
||||
virtual void draw_tau() = 0;
|
||||
[[nodiscard]] double tau_wait() const;
|
||||
|
||||
static Distribution* createFromInput(const std::string& input, std::mt19937_64& rng);
|
||||
|
||||
protected:
|
||||
std::string m_name{"BaseDistribution"};
|
||||
double m_tau{1.};
|
||||
double m_tau_jump{1.};
|
||||
std::mt19937_64& m_rng;
|
||||
};
|
||||
|
||||
#endif //RWSIM_TIMESBASE_H
|
@ -1,10 +1,7 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
#include "delta.h"
|
||||
|
||||
DeltaDistribution::DeltaDistribution(const double tau, std::mt19937_64& rng) : Distribution(tau, rng) {}
|
||||
DeltaDistribution::DeltaDistribution(std::mt19937_64& rng) : Distribution(rng) {}
|
||||
DeltaDistribution::DeltaDistribution(const double tau, std::mt19937_64& rng) : Distribution(std::string("Delta"), tau, rng) {}
|
||||
DeltaDistribution::DeltaDistribution(std::mt19937_64& rng) : Distribution(std::string("Delta"), rng) {}
|
||||
|
||||
void DeltaDistribution::initialize() {
|
||||
m_tau_jump = m_tau;
|
@ -1,7 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_TIMESDELTA_H
|
||||
#define RWSIM_TIMESDELTA_H
|
||||
|
@ -1,12 +1,13 @@
|
||||
//
|
||||
// Created by dominik on 8/24/24.
|
||||
//
|
||||
|
||||
#include "lognormal.h"
|
||||
#include <cmath>
|
||||
|
||||
LogNormalDistribution::LogNormalDistribution(const double tau, const double sigma, std::mt19937_64& rng) : Distribution(tau, rng), m_sigma(sigma), m_distribution(std::log(tau), sigma) {}
|
||||
LogNormalDistribution::LogNormalDistribution(std::mt19937_64& rng) : Distribution(rng) {}
|
||||
LogNormalDistribution::LogNormalDistribution(const double tau, const double sigma, std::mt19937_64& rng) : Distribution(std::string("LogNormal"), tau, rng), m_sigma(sigma), m_distribution(std::log(tau), sigma) {}
|
||||
LogNormalDistribution::LogNormalDistribution(std::mt19937_64& rng) : Distribution(std::string("LogNormal"), rng) {}
|
||||
|
||||
void LogNormalDistribution::setParameters(const std::unordered_map<std::string, double> ¶meters) {
|
||||
m_sigma = parameters.at("sigma");
|
||||
Distribution::setParameters(parameters);
|
||||
}
|
||||
|
||||
void LogNormalDistribution::initialize() {
|
||||
m_distribution = std::lognormal_distribution(std::log(m_tau), m_sigma);
|
@ -1,15 +1,17 @@
|
||||
|
||||
#ifndef LOGNORMAL_H
|
||||
#define LOGNORMAL_H
|
||||
|
||||
#include "base.h"
|
||||
#include <random>
|
||||
#include <set>
|
||||
|
||||
class LogNormalDistribution final : public Distribution {
|
||||
public:
|
||||
LogNormalDistribution(double, double, std::mt19937_64&);
|
||||
explicit LogNormalDistribution(std::mt19937_64 &rng);
|
||||
|
||||
void setParameters(const std::unordered_map<std::string, double> &) override;
|
||||
|
||||
void initialize() override;
|
||||
void draw_tau() override;
|
||||
|
@ -57,7 +57,7 @@ Arguments parse_args(const int argc, char* argv[]) {
|
||||
continue;
|
||||
}
|
||||
|
||||
// all other optional parameter are
|
||||
// all other arguments are optional parameter
|
||||
auto [option_name, option_value] = get_optional_parameter(it);
|
||||
args.optional[option_name] = option_value;
|
||||
continue;
|
||||
@ -74,10 +74,15 @@ Arguments parse_args(const int argc, char* argv[]) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (args.distribution_type.empty()) {
|
||||
args.distribution_type = *it;
|
||||
continue;
|
||||
}
|
||||
|
||||
throw std::invalid_argument("too many positional arguments");
|
||||
}
|
||||
|
||||
if (args.parameter_file.empty() || args.motion_type.empty()) {
|
||||
if (args.parameter_file.empty() || args.motion_type.empty() || args.distribution_type.empty()) {
|
||||
throw std::invalid_argument("Missing argument");
|
||||
}
|
||||
|
||||
@ -85,8 +90,6 @@ Arguments parse_args(const int argc, char* argv[]) {
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
std::unordered_map<std::string, double> read_parameter(const std::filesystem::path& infile) {
|
||||
if (!std::filesystem::exists(infile)) {
|
||||
std::cerr << "File " << infile << " does not exist" << std::endl;
|
||||
@ -121,44 +124,72 @@ std::unordered_map<std::string, double> read_parameter(const std::filesystem::pa
|
||||
}
|
||||
|
||||
|
||||
void fid_write_out(const std::string& filename, const std::vector<double>& x, const std::vector<double>& y, const double tau, const double t_evo) {
|
||||
auto size = x.size();
|
||||
void save_parameter_to_file(
|
||||
const std::string& resulttype,
|
||||
const std::string& motiontype,
|
||||
const std::string& disttype,
|
||||
std::unordered_map<std::string, double>& parameter,
|
||||
std::unordered_map<std::string, double>& optional
|
||||
) {
|
||||
|
||||
std::ostringstream parameter_filename;
|
||||
parameter_filename << resulttype << "_" << motiontype << "_" << disttype;
|
||||
|
||||
parameter_filename << std::setprecision(6) << std::scientific;
|
||||
for (const auto& [key, value]: optional) {
|
||||
parameter_filename << "_" << key << "=" << value;
|
||||
}
|
||||
parameter_filename << "_parameter.txt";
|
||||
|
||||
std::ostringstream sfile;
|
||||
sfile << filename << "_";
|
||||
sfile << std::setprecision(6) << std::scientific;
|
||||
sfile << "tau=" << tau << "_tevo=" << t_evo << ".dat";
|
||||
{
|
||||
std::string outfile = sfile.str();
|
||||
std::ofstream fid_file(outfile, std::ios::out);
|
||||
for (unsigned int i = 0; i < size; i++) {
|
||||
fid_file << x[i] << "\t" << y[i] << "\n";
|
||||
// write data to file, columns are secondary axis (echo delay, evolution times)
|
||||
std::string datafile = parameter_filename.str();
|
||||
std::ofstream filestream(datafile, std::ios::out);
|
||||
|
||||
for (const auto& [key, value]: parameter) {
|
||||
filestream << key << "=" << value << "\n";
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void fid_write_out(const std::string& filename, const std::vector<double>& x, const std::map<double, std::vector<double>>& y, const double tau) {
|
||||
auto size = x.size();
|
||||
|
||||
std::ostringstream sfile;
|
||||
sfile << filename << "_";
|
||||
sfile << std::setprecision(6) << std::scientific;
|
||||
sfile << "tau=" << tau << ".dat";
|
||||
void save_data_to_file(
|
||||
const std::string& resulttype,
|
||||
const std::string& motiontype,
|
||||
const std::string& disttype,
|
||||
const std::vector<double>& x,
|
||||
const std::map<double, std::vector<double>>& y,
|
||||
std::unordered_map<std::string, double>& optional
|
||||
) {
|
||||
// make file name
|
||||
std::ostringstream datafile_name;
|
||||
datafile_name << resulttype << "_" << motiontype << "_" << disttype;
|
||||
datafile_name << std::setprecision(6) << std::scientific;
|
||||
for (const auto& [key, value]: optional) {
|
||||
datafile_name << "_" << key << "=" << value;
|
||||
}
|
||||
datafile_name << ".dat";
|
||||
|
||||
{
|
||||
std::string outfile = sfile.str();
|
||||
std::ofstream fid_file(outfile, std::ios::out);
|
||||
fid_file << "#";
|
||||
// write data to file, columns are secondary axis (echo delay, evolution times)
|
||||
std::string datafile = datafile_name.str();
|
||||
std::ofstream filestream(datafile, std::ios::out);
|
||||
|
||||
// first line are values of secondary axis
|
||||
filestream << "#";
|
||||
for (const auto& [t_echo_j, _] : y) {
|
||||
fid_file << t_echo_j << "\t";
|
||||
filestream << t_echo_j << "\t";
|
||||
}
|
||||
fid_file << std::endl;
|
||||
filestream << std::endl;
|
||||
|
||||
// write values to file
|
||||
auto size = x.size();
|
||||
for (unsigned int i = 0; i < size; i++) {
|
||||
fid_file << x[i];
|
||||
filestream << x[i];
|
||||
for (const auto& [_, fid_j] : y) {
|
||||
fid_file << "\t" << fid_j[i];
|
||||
filestream << "\t" << fid_j[i];
|
||||
}
|
||||
fid_file << "\n";
|
||||
filestream << "\n";
|
||||
}
|
||||
}
|
||||
}
|
@ -1,4 +1,3 @@
|
||||
|
||||
#ifndef RWSIM_IO_H
|
||||
#define RWSIM_IO_H
|
||||
|
||||
@ -13,6 +12,7 @@ struct Arguments {
|
||||
bool ste = false;
|
||||
bool spectrum = false;
|
||||
std::string motion_type{};
|
||||
std::string distribution_type{};
|
||||
std::unordered_map<std::string, double> optional;
|
||||
};
|
||||
|
||||
@ -21,7 +21,7 @@ std::pair<std::string, double> get_optional_parameter(std::vector<std::string>::
|
||||
|
||||
std::unordered_map<std::string, double> read_parameter(const std::filesystem::path&);
|
||||
|
||||
void fid_write_out(const std::string&, const std::vector<double>&, const std::vector<double>&, double, double);
|
||||
void fid_write_out(const std::string&, const std::vector<double>&, const std::map<double, std::vector<double>>&, double tau);
|
||||
void save_parameter_to_file(const std::string&, const std::string&, const std::string&, std::unordered_map<std::string, double>&, std::unordered_map<std::string, double>&);
|
||||
void save_data_to_file(const std::string&, const std::string&, const std::string&, const std::vector<double>&, const std::map<double, std::vector<double>>&, std::unordered_map<std::string, double>&);
|
||||
|
||||
#endif
|
@ -1,8 +1,3 @@
|
||||
//
|
||||
// Created by dominik on 8/14/24.
|
||||
//
|
||||
|
||||
|
||||
#include <vector>
|
||||
#include <algorithm>
|
||||
#include <cmath>
|
219
test.py
219
test.py
@ -1,219 +0,0 @@
|
||||
import pathlib
|
||||
import subprocess
|
||||
|
||||
import numpy as np
|
||||
from scipy.optimize import curve_fit
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
||||
|
||||
def run_sims(taus, ste: bool = True, spectrum: bool = False, exec_file: str = './build/rwsim', config_file: str = './config.txt'):
|
||||
for tau in taus:
|
||||
arguments = [exec_file, config_file]
|
||||
if ste:
|
||||
arguments += ['--ste']
|
||||
if spectrum:
|
||||
arguments += ['--spectrum']
|
||||
|
||||
arguments += ['BimodalAngle']
|
||||
|
||||
arguments += ['-TAU', f'{tau}']
|
||||
|
||||
subprocess.run(arguments)
|
||||
|
||||
|
||||
|
||||
def dampening(x: np.ndarray, apod: float) -> np.ndarray:
|
||||
return np.exp(-apod * x)
|
||||
|
||||
|
||||
def pulse_attn(freq: np.ndarray, t_pulse: float):
|
||||
# cf. Schmitt-Rohr/Spieß eq. 2.126; omega_1 * t_p = pi/2
|
||||
pi_half_squared = np.pi**2 / 4
|
||||
omega = 2 * np.pi * freq
|
||||
|
||||
numerator = np.sin(np.sqrt(pi_half_squared + omega**2 * t_pulse**2 / 2))
|
||||
denominator = np.sqrt(pi_half_squared + omega**2 * t_pulse**2 / 4)
|
||||
|
||||
return np.pi * numerator / denominator / 2
|
||||
|
||||
|
||||
def post_process_spectrum(taus, apod, tpulse):
|
||||
reduction_factor = np.zeros((taus.size, 5)) # hard-coded t_echo :(
|
||||
|
||||
for i, tau in enumerate(taus):
|
||||
try:
|
||||
raw_data = np.loadtxt(f'fid_tau={tau:.6e}.dat')
|
||||
except OSError:
|
||||
continue
|
||||
|
||||
t = raw_data[:, 0]
|
||||
timesignal = raw_data[:, 1:]
|
||||
|
||||
timesignal *= dampening(t, apod)[:, None]
|
||||
timesignal[0, :] /= 2
|
||||
|
||||
# FT to spectrum
|
||||
freq = np.fft.fftshift(np.fft.fftfreq(t.size, d=1e-6))
|
||||
spec = np.fft.fftshift(np.fft.fft(timesignal, axis=0), axes=0).real
|
||||
spec *= pulse_attn(freq, t_pulse=tpulse)[:, None]
|
||||
|
||||
reduction_factor[i, :] = 2*timesignal[0, :]
|
||||
|
||||
plt.plot(freq, spec)
|
||||
plt.show()
|
||||
|
||||
plt.semilogx(taus, reduction_factor, '.')
|
||||
plt.show()
|
||||
|
||||
|
||||
def post_process_ste(taus):
|
||||
tevo = np.linspace(1e-6, 120e-6, num=121)
|
||||
|
||||
for i, tau in enumerate(taus):
|
||||
try:
|
||||
raw_data_cc = np.loadtxt(f'coscos_tau={tau:.6e}.dat')
|
||||
raw_data_ss = np.loadtxt(f'sinsin_tau={tau:.6e}.dat')
|
||||
except OSError:
|
||||
continue
|
||||
|
||||
t_mix = raw_data_cc[:, 0]
|
||||
|
||||
fig_cc_raw, ax_cc_raw = plt.subplots()
|
||||
fig_ss_raw, ax_ss_raw = plt.subplots()
|
||||
|
||||
# ax_cc_raw.semilogx(t_mix, raw_data_cc[:, 1:], '.')
|
||||
ax_ss_raw.semilogx(t_mix, raw_data_ss[:, 1:], '.')
|
||||
|
||||
scaled_cc = (raw_data_cc[:, 1:]-raw_data_cc[-1, 1:])/(raw_data_cc[0, 1:]-raw_data_cc[-1, 1:])
|
||||
scaled_ss = (raw_data_ss[:, 1:]-raw_data_ss[-1, 1:])/(raw_data_ss[0, 1:]-raw_data_ss[-1, 1:])
|
||||
|
||||
fig_tau, ax_tau = plt.subplots()
|
||||
fig_beta, ax_beta= plt.subplots()
|
||||
fig_finfty, ax_finfty = plt.subplots()
|
||||
|
||||
tau_cc_fit = []
|
||||
beta_cc_fit = []
|
||||
finfty_cc_fit = []
|
||||
|
||||
tau_ss_fit = []
|
||||
beta_ss_fit = []
|
||||
finfty_ss_fit = []
|
||||
|
||||
tau_plus_fit = []
|
||||
beta_plus_fit = []
|
||||
finfty_plus_fit = []
|
||||
|
||||
for j in range(1, raw_data_cc.shape[1]-1):
|
||||
p0 = [
|
||||
raw_data_cc[0, 1],
|
||||
t_mix[np.argmin(np.abs(scaled_cc[:, j]-np.exp(-1)))],
|
||||
0.5,
|
||||
0.1
|
||||
]
|
||||
|
||||
res = curve_fit(ste, t_mix, raw_data_cc[:, j+1], p0, bounds=[(0, 0, 0., 0), (np.inf, np.inf, 1, 1)])
|
||||
m0, tauc, beta, finfty = res[0]
|
||||
# print(f'Cos-Cos-Fit for {tevo[j]}: tau_c = {tauc:.6e}, beta={beta:.4e}, amplitude = {m0: .4e}, f_infty={finfty:.4e}')
|
||||
l = ax_cc_raw.semilogx(t_mix, raw_data_cc[:, j+1], 'x', label=f'{tevo[j]}')
|
||||
ax_cc_raw.semilogx(t_mix, ste(t_mix, *res[0]), linestyle='--', color = l[0].get_color())
|
||||
|
||||
tau_cc_fit.append(res[0][1])
|
||||
beta_cc_fit.append(res[0][2])
|
||||
finfty_cc_fit.append(res[0][3])
|
||||
|
||||
p0 = [
|
||||
raw_data_cc[0, 1],
|
||||
t_mix[np.argmin(np.abs(scaled_ss[:, j]-np.exp(-1)))],
|
||||
0.5,
|
||||
0.1
|
||||
]
|
||||
|
||||
res = curve_fit(ste, t_mix, raw_data_ss[:, j+1], p0, bounds=[(0, 0, 0, 0), (np.inf, np.inf, 1, 1)])
|
||||
m0, tauc, beta, finfty = res[0]
|
||||
# print(f'Sin-Sin-Fit for {tevo[j]}: tau_c = {tauc:.6e}, beta={beta:.4e}, amplitude = {m0: .4e}, f_infty={finfty:.4e}')
|
||||
|
||||
tau_ss_fit.append(res[0][1])
|
||||
beta_ss_fit.append(res[0][2])
|
||||
finfty_ss_fit.append(res[0][3])
|
||||
|
||||
p0 = [
|
||||
raw_data_cc[0, 1],
|
||||
t_mix[np.argmin(np.abs(scaled_ss[:, j]-np.exp(-1)))],
|
||||
0.5,
|
||||
0.1
|
||||
]
|
||||
|
||||
res = curve_fit(ste, t_mix, raw_data_ss[:, j+1] + raw_data_cc[:, j+1], p0, bounds=[(0, 0, 0, 0), (np.inf, np.inf, 1, 1)])
|
||||
m0, tauc, beta, finfty = res[0]
|
||||
# print(f'Sin-Sin-Fit for {tevo[j]}: tau_c = {tauc:.6e}, beta={beta:.4e}, amplitude = {m0: .4e}, f_infty={finfty:.4e}')
|
||||
|
||||
tau_plus_fit.append(res[0][1])
|
||||
beta_plus_fit.append(res[0][2])
|
||||
finfty_plus_fit.append(res[0][3])
|
||||
|
||||
# ax_tau.axhline(tau)
|
||||
|
||||
ax_tau.semilogy(tevo[1:], np.array(tau_cc_fit)/tau_cc_fit[0], 'C0-')
|
||||
ax_beta.plot(tevo[1:], beta_cc_fit, 'C0-')
|
||||
ax_finfty.plot(tevo[1:], finfty_cc_fit, 'C0-')
|
||||
|
||||
ax_tau.semilogy(tevo[1:], np.array(tau_ss_fit)/tau_ss_fit[0], 'C1-')
|
||||
ax_beta.plot(tevo[1:], beta_ss_fit, 'C1-')
|
||||
ax_finfty.plot(tevo[1:], finfty_ss_fit, 'C1-')
|
||||
|
||||
ax_tau.semilogy(tevo[1:], np.array(tau_plus_fit)/tau_plus_fit[0], 'C2-')
|
||||
ax_beta.plot(tevo[1:], beta_plus_fit, 'C2-')
|
||||
ax_finfty.plot(tevo[1:], finfty_plus_fit, 'C2-')
|
||||
|
||||
ax_cc_raw.legend()
|
||||
plt.show()
|
||||
|
||||
# np.savetxt('cc_tauc.dat', list(zip(tevo[1:], tau_cc_fit)))
|
||||
# np.savetxt('cc_beta.dat', list(zip(tevo[1:], beta_cc_fit)))
|
||||
# np.savetxt('cc_finfty.dat', list(zip(tevo[1:], finfty_cc_fit)))
|
||||
# np.savetxt('ss_tauc.dat', list(zip(tevo[1:], tau_ss_fit)))
|
||||
# np.savetxt('ss_beta.dat', list(zip(tevo[1:], beta_ss_fit)))
|
||||
# np.savetxt('ss_finfty.dat', list(zip(tevo[1:], finfty_ss_fit)))
|
||||
|
||||
|
||||
|
||||
# for i, tau in enumerate(taus):
|
||||
#
|
||||
# try:
|
||||
# raw_data_cc = np.loadtxt(f'coscos_tau={tau:.6e}.dat')
|
||||
# raw_data_ss = np.loadtxt(f'sinsin_tau={tau:.6e}.dat')
|
||||
# except OSError:
|
||||
# continue
|
||||
#
|
||||
# t_mix = raw_data_cc[:, 0]
|
||||
#
|
||||
# plt.semilogx(t_mix, raw_data_cc[:, 1:])
|
||||
# plt.show()
|
||||
#
|
||||
# plt.semilogx(t_mix, raw_data_ss[:, 1:])
|
||||
# plt.show()
|
||||
#
|
||||
# plt.plot(raw_data_cc[0, 1:])
|
||||
# plt.plot(raw_data_ss[0, 1:])
|
||||
# plt.show()
|
||||
#
|
||||
# plt.plot(raw_data_cc[-1, 1:]/raw_data_cc[0, 1:])
|
||||
# plt.plot(raw_data_ss[-1, 1:]/raw_data_ss[0, 1:])
|
||||
# plt.show()
|
||||
|
||||
|
||||
def ste(x, m0, t, beta, finfty):
|
||||
return m0 * ((1-finfty) * np.exp(-(x/t)**beta) + finfty)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
tau_values = np.geomspace(1e-2, 1e2, num=2) # if num=1, tau is first value
|
||||
|
||||
# parameter for spectrum simulations
|
||||
lb = 2e3
|
||||
pulse_length = 2e-6
|
||||
|
||||
run_sims(tau_values)
|
||||
post_process_ste(tau_values)
|
||||
# post_process_spectrum(tau_values, lb, pulse_length)
|
@ -1,13 +0,0 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
#include "base.h"
|
||||
|
||||
Distribution::Distribution(const double tau, std::mt19937_64 &rng) : m_tau(tau), m_tau_jump(tau), m_rng(rng) {}
|
||||
|
||||
Distribution::Distribution(std::mt19937_64 &rng) : m_rng(rng) {}
|
||||
|
||||
double Distribution::tau_wait() const {
|
||||
return std::exponential_distribution(1./m_tau_jump)(m_rng);
|
||||
}
|
||||
|
30
times/base.h
30
times/base.h
@ -1,30 +0,0 @@
|
||||
//
|
||||
// Created by dominik on 8/12/24.
|
||||
//
|
||||
|
||||
#ifndef RWSIM_TIMESBASE_H
|
||||
#define RWSIM_TIMESBASE_H
|
||||
|
||||
#include <random>
|
||||
|
||||
class Distribution {
|
||||
public:
|
||||
virtual ~Distribution() = default;
|
||||
|
||||
Distribution(double, std::mt19937_64&);
|
||||
explicit Distribution(std::mt19937_64&);
|
||||
|
||||
[[nodiscard]] double getTau() const { return m_tau; }
|
||||
void setTau(const double tau) { m_tau = tau;}
|
||||
|
||||
virtual void initialize() = 0;
|
||||
virtual void draw_tau() = 0;
|
||||
[[nodiscard]] double tau_wait() const;
|
||||
|
||||
protected:
|
||||
double m_tau{1.};
|
||||
double m_tau_jump{1.};
|
||||
std::mt19937_64& m_rng;
|
||||
};
|
||||
|
||||
#endif //RWSIM_TIMESBASE_H
|
Loading…
Reference in New Issue
Block a user