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How to use relax method in fMBT

Best Python code snippet using fMBT_python

relaxation_test.py

Source:relaxation_test.py

...27    msd = 4 * time * known_diffusion + offset28    diff, diff_err = relaxation.diffusion_constant(time, msd)29    assert np.isclose(diff, known_diffusion)30    assert np.isclose(diff_err, 0)31def test_exponential_relax():32    """Ensure the exponential_relaxation function working appropriately."""33    known_decay = 1e434    time = np.arange(100000)35    value = np.exp(-time / known_decay)36    relax, *_ = relaxation.exponential_relaxation(time, value)37    assert np.isclose(relax, known_decay)38@pytest.fixture39def linear_relax():40    num_values = 100041    time = np.arange(num_values)42    values = np.arange(num_values) / num_values43    return time, values44class TestThresholdRelaxation:45    def test_decay(self, linear_relax):46        time, values = linear_relax47        # This is to turn the linear growth into linear decay48        values = 1 - values49        logger.debug("Values: %s", values)50        relax, _ = relaxation.threshold_relaxation(51            time, values, threshold=0.5, decay=True52        )53        assert relax == len(time) / 2 + 1...

problem_3.py

Source:problem_3.py

1# import the code for the simulation2from simulator import Simulation3import matplotlib.pyplot as plt4import matplotlib5matplotlib.use("TkAgg")6import numpy as np7from time import time8plt.rc('font', family='serif')9plt.rcParams['text.usetex'] = False10fs = 1811# update various fontsizes to match12params = {'figure.figsize': (12, 8),13          'legend.fontsize': fs,14          'axes.labelsize': fs,15          'xtick.labelsize': 0.9 * fs,16          'ytick.labelsize': 0.9 * fs,17          'axes.linewidth': 1.1,18          'xtick.major.size': 7,19          'xtick.minor.size': 4,20          'ytick.major.size': 7,21          'ytick.minor.size': 4}22plt.rcParams.update(params)23def t_relax_analytic(N, size, radius, E, mass):24    n = N / size**225    sigma = radius * 226    v0 = np.sqrt(2 * E / mass)27    return (n * sigma * v0)**(-1)28def get_N_comparison(size=1000, radius=20, E=0.1, mass=1, repeats=10):29    start = time()30    N_range = np.array([25, 50, 75, 100, 125, 150, 175, 200])31    t_relax_list = []32    for N in N_range:33        t_relax = []34        for _ in range(repeats):35            sim = Simulation(N=N, E=E, size=size, radius=radius, masses=mass, visualise=False)36            t_relax.append(sim.run_simulation(run_until_steadystate=True))37        print("N =", N, "done", t_relax)38        t_relax_list.append(t_relax)39    np.save("data/t_relax_N.npy", t_relax_list)40    print("Runtime {:1.2f}s".format(time() - start))41    return N_range, t_relax_list42def get_r_comparison(N=100, size=1000, E=0.1, mass=1, repeats=10):43    start = time()44    r_range = np.array([10, 12.5, 15, 17.5, 20, 22.5, 25, 27.5, 30])45    t_relax_list = []46    for radius in r_range:47        t_relax = []48        for _ in range(repeats):49            sim = Simulation(N=N, E=E, size=size, radius=radius, masses=mass, visualise=False)50            t_relax.append(sim.run_simulation(run_until_steadystate=True))51        print("r =", radius, "done", t_relax)52        t_relax_list.append(t_relax)53    np.save("data/t_relax_r.npy", t_relax_list)54    print("Runtime {:1.2f}s".format(time() - start))55    return r_range, t_relax_list56def main():57    N = 10058    radius = 2059    size = 100060    E = 0.161    mass = 162    fig, axes = plt.subplots(1, 2, figsize=(18, 7))63    N_range, t_relax_N = get_N_comparison(radius=radius, size=size, E=E, mass=mass)64    r_range, t_relax_r = get_r_comparison(N=N, size=size, E=E, mass=mass)65    ax = axes[0]66    t_relax = t_relax_N67    N_range_smooth = np.linspace(N_range.min(), N_range.max(), 1000)68    ax.plot(N_range_smooth, t_relax_analytic(N_range_smooth, size, radius, E, mass) * 1.2,69            linestyle="dotted", lw=3, color=plt.get_cmap("plasma")(0.8),70            label=r"Analytic function, $X = 1.2$")71    ax.set_xlabel(r"Number of Particles")72    ax.set_ylabel(r"Relaxation Time, $\tau_{\rm relax} \, [\rm s]$")73    ax.errorbar(N_range, np.median(t_relax, axis=1), xerr=0.0,74                yerr=[np.median(t_relax, axis=1) - np.min(t_relax, axis=1),75                      np.max(t_relax, axis=1) - np.median(t_relax, axis=1)],76                marker="o", color=plt.get_cmap("plasma")(0.2), label="Simulated results")77    ax.legend()78    ax = axes[1]79    t_relax = t_relax_r80    r_range_smooth = np.linspace(r_range.min(), r_range.max(), 1000)81    ax.plot(r_range_smooth, t_relax_analytic(N=N, size=size, radius=r_range_smooth, E=E, mass=mass) * 1.2,82            linestyle="dotted", lw=3, color=plt.get_cmap("plasma")(0.8),83            label=r"Analytic function, $X = 1.2$")84    ax.set_xlabel(r"Radius, $r \, [\rm cm]$")85    ax.set_ylabel(r"Relaxation Time, $\tau_{\rm relax} \, [\rm s]$")86    ax.errorbar(r_range, np.median(t_relax, axis=1), xerr=0.0,87                yerr=[np.median(t_relax, axis=1) - np.min(t_relax, axis=1),88                      np.max(t_relax, axis=1) - np.median(t_relax, axis=1)],89                marker="o", color=plt.get_cmap("plasma")(0.2), label="Simulated results")90    ax.legend()91    plt.savefig("figures/3c.pdf", format="pdf", bbox_inches="tight")92    plt.show()93if __name__ == "__main__":...

relax.py

Source:relax.py

1import os2import yaml3import sys4import logging5def check_package(package_name,import_name):6    from importlib.util import find_spec7    has_lib = find_spec(package_name)8    if not has_lib:9        print("%s is not installed!!"%(import_name))10        return False11       12if __name__ == "__main__":13    package_list = {"biopython":"Bio","pandas":"pandas"}14    config_path = os.path.join(os.path.dirname(sys.argv[0]),"config.yaml")15    with open(config_path,"r") as f:16        config = yaml.load(f,Loader=yaml.FullLoader)17    #relax18    19        #score_jd220    if config["relax"]["need_prepare"]:21        cmd = os.path.join(os.path.dirname(sys.argv[0]),"jd2.run.sh") + " " +\22            config["input"]["path"] +" " +\23            os.path.join(config["input"]["rosetta_bin"],config["relax"]["score_jd2_exec"])24        ex = os.system(cmd)25        if ex:26            logging.error("run score_jd2 failed !")27            sys.exit(1)28        jd2_file = os.path.abspath(config["input"]["path"]) + "/jd2_pdb.list"29    else:30        jd2_file = config["input"]["path"]31    #if mpi_run relax32    if config["relax"]["mpi_run"]["use_mpi"]:33        mpi_cores = str(config["relax"]["mpi_run"]["mpi_cores"])34    else:35        mpi_cores = "0"36    #run relax37    cmd = os.path.join(os.path.dirname(sys.argv[0]),"relax.run.sh") + " " +\38        str(mpi_cores) + " " +\39        str(config["relax"]["relax_threads"])+ " " +\40        os.path.abspath(os.path.join(os.path.dirname(sys.argv[0]),config["relax"]["flag"])) + " " +\41        os.path.join(config["input"]["rosetta_bin"],config["relax"]["relax_exec"]) + " " +\42        jd2_file + " " +\43        config["input"]["path"]44    ex = os.system(cmd)45    if ex:46        logging.error("run relax failed !")47        sys.exit(1)48    relax_file = os.path.abspath(config["input"]["path"]) + "/relax_sc.list"49    could_flex = True50    51        ...

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