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If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/README.md b/README.md new file mode 100644 index 0000000..2cc2c12 --- /dev/null +++ b/README.md @@ -0,0 +1,29 @@ +# Download + +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 + +The workflows leaves yet much to be desired, it will become better (maybe) + +## Changes in `test.py` + +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 + +**Because filenames are always the same, previous simulations and results are overwritten!** + +1. Execute `build.sh` (in terminal with `./build.sh`). It compiles the source code and executes test.py diff --git a/config.txt b/config.txt index 1d278ce..3f4fa1e 100644 --- a/config.txt +++ b/config.txt @@ -1,9 +1,10 @@ # Simulation part -num_walker=50000 +num_walker=20000 # Motion model part delta=161e3 -eta=0.0 +eta=0.2 # Distribution part +# this tau value is overwritten if sim is run with test.py tau=1e-1 # Spectrum part dwell_time=1e-6 @@ -17,5 +18,4 @@ tevo_stop=60e-6 tevo_steps=121 tmix_start=1e-5 tmix_stop=1e1 -tmix_steps=61 -tau=0.001 +tmix_steps=61 \ No newline at end of file diff --git a/main.cpp b/main.cpp index 82629de..19ccda8 100644 --- a/main.cpp +++ b/main.cpp @@ -21,20 +21,18 @@ int main (const int argc, char *argv[]) { return 1; } - std::unordered_map parameter { read_parameter(args.parameter_file) }; std::random_device rd; std::mt19937_64 rng(rd()); - // auto motion = BimodalAngle(1, 1, 2, 30, 0.98, rng); - // auto motion = TetrahedralJump(rng); + // auto motion = BimodalAngle(1, 1, 2, 30, 0.98, rng); // arguments: delta, eta, angle1, angle2, probability of angle1 + auto motion = TetrahedralJump(rng); // auto motion = RandomJump(rng); - auto motion = SmallAngle(1, 1, 20, rng); + // auto motion = SmallAngle(1, 1, 4, rng); // arguments: delta, eta, angle auto dist = DeltaDistribution(rng); - // auto dist = LogNormalDistribution(1, 2, rng); - + // auto dist = LogNormalDistribution(1, 2, rng); // arguments: tau_max, sigma if (args.spectrum) { run_spectrum(parameter, motion, dist); diff --git a/test.py b/test.py index aa4cd76..790aec1 100644 --- a/test.py +++ b/test.py @@ -2,13 +2,13 @@ import pathlib import subprocess import numpy as np +from scipy.optimize import curve_fit import matplotlib.pyplot as plt def run_sims(taus): for tau in taus: - print('tau') with pathlib.Path('./config.txt').open('a') as f: f.write(f'tau={tau}\n') subprocess.run(['./build/rwsim', '-ste', './config.txt']) @@ -59,8 +59,9 @@ def post_process_spectrum(taus, apod, tpulse): def post_process_ste(taus): - for i, tau in enumerate(taus): + tevo = np.linspace(1e-6, 60e-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') @@ -69,23 +70,112 @@ def post_process_ste(taus): t_mix = raw_data_cc[:, 0] - plt.semilogx(t_mix, raw_data_cc[:, 1:]) + 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 = [] + + 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)))], + 1, + 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}') + + 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)))], + 1, + 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]) + + ax_tau.semilogy(tevo[1:], tau_cc_fit, 'C0-') + ax_tau.axhline(tau) + ax_beta.plot(tevo[1:], beta_cc_fit, 'C0-') + ax_finfty.plot(tevo[1:], finfty_cc_fit, 'C0-') + + ax_tau.semilogy(tevo[1:], tau_ss_fit, 'C1-') + ax_tau.axhline(tau) + ax_beta.plot(tevo[1:], beta_ss_fit, 'C1-') + ax_finfty.plot(tevo[1:], finfty_ss_fit, 'C1-') + plt.show() - plt.semilogx(t_mix, raw_data_ss[:, 1:]) - 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))) - 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() + + # 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.logspace(-2, -6, 1) + tau_values = np.geomspace(1e-2, 1e-6, num=1) # if num=1, tau is first value + + # parameter for spectrum simulations lb = 2e3 pulse_length = 2e-6