def RDF(self, type1, type2):
import MDAnalysis
import MDAnalysis.analysis.rdf
import matplotlib.pyplot as plt
# import matplotlib as plt
import os
os.chdir(self.dire)
print(os.getcwd())
u = MDAnalysis.Universe('XDATCAR.pdb', permissive=True)
g1 = u.select_atoms(type1)
g2 = u.select_atoms(type2)
rdf = MDAnalysis.analysis.rdf.InterRDF(
g1, g2, nbins=75, range=(0.0, min(u.dimensions[:3]) / 2.0))
rdf.run()
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111)
ax.plot(rdf.bins, rdf.rdf, 'g-', label="rdf")
font1 = {
'family': 'Times New Roman',
'weight': 'bold',
}
ax.legend(frameon=True, edgecolor='none', facecolor='none', prop=font1)
ax.set_xlabel(r"Distance ($\AA$)")
ax.set_ylabel(r"RDF")
fig.savefig("RDF_all.png",
bbox_inches='tight',
transparent=True,
dpi=600,
format='png')
plt.show()
def plot_traj_rdf(trajs, labels, ax):
'''Plot the RDF'''
for t, l in zip(trajs, labels):
u = MDAnalysis.Universe(t)
g = u.select_atoms('name O')
rdf = MDAnalysis.analysis.rdf.InterRDF(g, g)
rdf.run()
print(rdf.rdf)
ax.plot(rdf.bins, rdf.rdf, label=l)
ax.legend(loc='best')
ax.set_xlabel('$r$ [Å]')
ax.set_ylabel('$g(r)$')
plt.tight_layout()
def test_double_run(sels):
# running rdf twice should give the same result
s1, s2 = sels
rdf = InterRDF(s1, s2).run()
rdf.run()
assert len(rdf.count[rdf.count == 3]) == 7
import MDAnalysis
import MDAnalysis.analysis.rdf
import matplotlib.pyplot as plt
u = MDAnalysis.Universe('XDATCAR.pdb', permissive=True)
g1 = u.select_atoms('type O')
g2 = u.select_atoms('type H')
rdf = MDAnalysis.analysis.rdf.InterRDF(g1,
g2,
nbins=75,
range=(0.0,
min(u.dimensions[:3]) / 2.0))
rdf.run()
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111)
ax.plot(rdf.bins, rdf.rdf, 'k-', label="rdf")
ax.legend(loc="best")
ax.set_xlabel(r"Distance ($\AA$)")
ax.set_ylabel(r"RDF")
fig.savefig("RDF_all.png")
#plt.show()
def POSTAIMD(
self,
filename,
rdf_fir,
rdf_sec,
):
from ase.io import read, write
import os
import MDAnalysis
import MDAnalysis.analysis.rdf
import MDAnalysis.analysis.rms
import matplotlib.pyplot as plt
import pandas as pd
os.chdir(self.dire)
# write('traj.pdb', read(filename))
u = MDAnalysis.Universe(filename, permissive=True)
u.dimensions = [73, 73, 73, 90, 90, 90]
u.atoms.write("traj.pdb", frames='all')
u.atoms.write("crystal.xyz")
g1 = u.select_atoms(rdf_fir)
g2 = u.select_atoms(rdf_sec)
rdf = MDAnalysis.analysis.rdf.InterRDF(
g1, g2, nbins=75, range=(0.0, min(u.dimensions[:3]) / 2.0))
rdf.run()
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111)
ax.plot(rdf.bins, rdf.rdf, 'k-', label="rdf")
ax.legend(loc="best")
ax.set_xlabel(r"Distance ($\AA$)")
ax.set_ylabel(r"RDF")
fig.savefig("RDF_all.png")
ref = MDAnalysis.Universe(filename, permissive=True)
ref.trajectory[0]
R = MDAnalysis.analysis.rms.RMSD(
u,
ref,
select=
"all", # superimpose on whole backbone of all atoms # align based on all atoms
groupselections=[rdf_fir, rdf_sec],
filename="rmsd_all.dat",
center=True) #, # CORE
timestep = 0.0005 #0.5fs from fs to ps as Reader has no dt information, set to 1.0 ps
R.run()
rmsd = R.rmsd.T # transpose makes it easier for plotting
time = rmsd[1] * timestep
da = {'time': time, 'all': rmsd[2], rdf_fir: rmsd[3], rdf_sec: rmsd[4]}
df = pd.DataFrame(da) #构造原始数据文件
df.to_excel("RMSD.xlsx") #生成Excel文件，并存到指定文件路径下
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111)
ax.plot(time, rmsd[2], 'k-', label="all")
ax.plot(time, rmsd[3], 'r--', label=rdf_fir)
ax.plot(time, rmsd[4], 'b--', label=rdf_sec)
ax.legend(loc="best")
ax.set_xlabel("time (ps)")
ax.set_ylabel(r"RMSD ($\AA$)")
fig.savefig("rmsd_md_analysis.png")