It will print the state of the system, and make several figures.
"""
import numpy as np
import matplotlib.pyplot as plt
import pykbi
# first generate a range of values, we use excessively many points
range_data = np.linspace(0.001, 250, 10000)
# then we generate the function, based on the input
gr = pykbi.odf(range_data, chi=2.0)
rdf = pykbi.RDF(range_data, gr, name="ODF, chi=2.0")
# we integrate the function using the open integration method.
rdf.Integrate()
## and we read out the value of the integral. if no argument is given, this is done
# in the last point in the integral
rdf.FindValues(position=(None, 0.10))
# Then print the values
print("Value of KBI at end of integral for '{}': {}".format(
rdf.name, rdf.ReturnKBI()))
# We then print the state of the system
rdf.PrintState()
def test_wrong_input(self):
self.assertRaises(TypeError, lambda: pykbi.RDF(np.array([]), 1.0))
self.assertRaises(TypeError, lambda: pykbi.RDF(1.0, np.array([])))
def setUp(self):
n = 10
self.rdf = pykbi.RDF(np.linspace(0.1, 1.1, n),
np.ones(n),
closed=False)
self.rdf.Integrate()
It will print the state of the system, and make several figures.
"""
import numpy as np
import matplotlib.pyplot as plt
import pykbi
# first generate a range of values, we use excessively many points
range_data = np.linspace(0.001, 250, 10000)
# then we generate the function, based on the input
gr = pykbi.odf(range_data, chi=2.0)
rdf = pykbi.RDF(range_data, gr, closed=False, name="ODF, chi=2.0")
# we integrate the function using the open integration method.
rdf.Integrate()
## and we read out the value of the integral. if no argument is given, this is done
# in the last point in the integral
rdf.FindValues()
# Then print the values
print("Value of KBI at end of integral for '{}': {}".format(
rdf.name, rdf.ReturnKBI()))
# We then print the state of the system
rdf.PrintState()
"""
import numpy as np
import matplotlib.pyplot as plt
import pykbi
# read data from file
lt = 14.8245984505
data = np.loadtxt("rdf1.txt")
rdf11 = pykbi.RDF(data[:, 0],
data[:, 1],
closed=False,
npart=1200,
box_size=lt,
eqint=True,
name="rdf_11")
rdf22 = pykbi.RDF(data[:, 0],
data[:, 2],
closed=False,
npart=600,
box_size=lt,
eqint=True,
name="rdf_22")
rdf33 = pykbi.RDF(data[:, 0],
data[:, 3],
closed=False,
npart=600,
box_size=lt,
Will work with the integral of a rdf
"""
import numpy as np
import matplotlib.pyplot as plt
import pykbi
# read data from file
data = np.loadtxt("rdf1.txt")
rdf11 = pykbi.RDF(data[:,0],data[:,1], closed=True, name="rdf_11")
rdf22 = pykbi.RDF(data[:,0],data[:,2], closed=True, name="rdf_22")
rdf33 = pykbi.RDF(data[:,0],data[:,3], closed=True, name="rdf_33")
# we integrate them using the closed integration methods
rdf11.Integrate()
rdf22.Integrate()
rdf33.Integrate()
## and we read out the value of the integral. if no argument is given, this is done
# in the last point in the integral
rdf11.FindValues(position=(0.35,0.45))
rdf22.FindValues(position=(0.35,0.45))
rdf33.FindValues(position=(0.35,0.45))