added flexibility

CMakeLists.txt

@@ -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)

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
 

build.sh

@@ -4,7 +4,4 @@ cd build || exit
 cmake ..
 cmake --build .
 
-cd ..
-
-python test.py
-
+cp ./src/rwsim ../rwsim

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

main.py

@@ -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()

python/helpers.py

@@ -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

python/spectrum.py

@@ -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()

python/ste.py

@@ -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

src/CMakeLists.txt

@@ -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)

src/main.cpp

@@ -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;

src/motions/base.cpp

@@ -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.);
 }

src/motions/base.h

@@ -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;

src/motions/bimodalangle.cpp

@@ -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();

src/motions/bimodalangle.h

@@ -1,6 +1,3 @@
-//
-// Created by dominik on 8/23/24.
-//
 
 #ifndef BIMODALANGLE_H
 #define BIMODALANGLE_H

src/motions/coordinates.cpp

@@ -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)};

src/motions/coordinates.h

@@ -1,6 +1,3 @@
-//
-// Created by dominik on 8/22/24.
-//
 
 #ifndef COORDINATES_H
 #define COORDINATES_H

src/motions/isosmallangle.cpp

@@ -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();

src/motions/isosmallangle.h

@@ -1,6 +1,3 @@
-//
-// Created by dominik on 8/21/24.
-//
 
 #ifndef RWSIM_MOTIONISOSMALLANGLE_H
 #define RWSIM_MOTIONISOSMALLANGLE_H

src/motions/random.cpp

@@ -1,6 +1,3 @@
-//
-// Created by dominik on 8/12/24.
-//
 
 #include "random.h"
 

src/motions/random.h

@@ -1,7 +1,3 @@
-//
-// Created by dominik on 8/12/24.
-//
-
 #ifndef RWSIM_MOTIONRANDOMJUMP_H
 #define RWSIM_MOTIONRANDOMJUMP_H
 

src/motions/tetrahedral.cpp

@@ -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();

src/motions/tetrahedral.h

@@ -1,7 +1,3 @@
-//
-// Created by dominik on 8/16/24.
-//
-
 #ifndef RWSIM_MOTIONTETRAHEDRAL_H
 #define RWSIM_MOTIONTETRAHEDRAL_H
 

src/simulation/sims.cpp

@@ -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;
+}

src/simulation/sims.h

@@ -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

src/times/base.cpp

@@ -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> &parameters) {
+    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);
+}

src/times/base.h

@@ -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

src/times/delta.cpp

@@ -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;

src/times/delta.h

@@ -1,7 +1,3 @@
-//
-// Created by dominik on 8/12/24.
-//
-
 #ifndef RWSIM_TIMESDELTA_H
 #define RWSIM_TIMESDELTA_H
 

src/times/lognormal.cpp

@@ -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> &parameters) {
+    m_sigma = parameters.at("sigma");
+    Distribution::setParameters(parameters);
+}
 
 void LogNormalDistribution::initialize() {
     m_distribution = std::lognormal_distribution(std::log(m_tau), m_sigma);

src/times/lognormal.h

@@ -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;
 

src/utils/io.cpp

@@ -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";
         }
     }
 }

src/utils/io.h

@@ -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

src/utils/ranges.cpp

@@ -1,8 +1,3 @@
-//
-// Created by dominik on 8/14/24.
-//
-
-
 #include <vector>
 #include <algorithm>
 #include <cmath>

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)

times/base.cpp

@@ -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);
-}
-

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