Worked out example for static properties
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bins = np.linspace(0, 1, 101)
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# %%
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from functools import partial
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import numpy as np
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import matplotlib.pyplot as plt
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import mdevaluate as md
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data_dir = "/data/skloth/python_packages/mdevaluate_examples/plots"
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path_to_sim = "/data/skloth/sim/IL_water/C4MIM_BF4_x50/T300_nvt"
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trajectory = md.open(path_to_sim, topology="run.tpr", trajectory="out/traj_full.xtc")
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oxygen_water = trajectory.subset(atom_name="OW", residue_name="SOL")
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# %%
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bins = np.arange(0, 1, 0.01)
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result_rdf = md.distribution.rdf(oxygen_water[-1], bins=bins)
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plt.figure()
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plt.plot(bins[:-1], result_rdf)
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plt.xlabel(r"$r$ in nm", fontsize=16)
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plt.ylabel(r"$g(r)$", fontsize=16)
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plt.savefig(f"{data_dir}/rdf.png", dpi=300, bbox_inches="tight")
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plt.show()
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plt.close()
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# %%
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bins = np.arange(0, 1, 0.01)
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result_rdf = md.distribution.time_average(
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partial(md.distribution.rdf, bins=bins), oxygen_water, segments=1000, skip=0.1
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)
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plt.figure()
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plt.plot(bins[:-1], result_rdf)
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plt.xlabel(r"$r$ in nm", fontsize=16)
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plt.ylabel(r"$g(r)$", fontsize=16)
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plt.show()
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plt.close()
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bins = np.linspace(0, 1, 101)
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# %%
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boron_anion = trajectory.subset(atom_name="B", residue_name="BF4")
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bins = np.arange(0, 1, 0.01)
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result_rdf = md.distribution.time_average(
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partial(md.distribution.rdf, bins=bins), oxygen_water, segments=100, skip=0.1
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partial(md.distribution.rdf, bins=bins),
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oxygen_water,
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coordinates_b=boron_anion,
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segments=1000,
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skip=0.1,
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)
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plt.figure()
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plt.plot(bins[:-1], result_rdf)
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plt.xlabel(r"$r$ in nm", fontsize=16)
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plt.ylabel(r"$g(r)$", fontsize=16)
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plt.show()
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plt.close()
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plt.close()
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