Data Sources¶
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Data Sources¶
Below are examples of how to grab cross sections from the EAF and simple data sources and re-discretize them.
In [15]:
from pyne.xs.data_source import *
from pyne.bins import stair_step
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rc('font', family='serif', size=14)
import numpy as np
dst_e_g = np.logspace(1, -7, 11)
EAF Data Source¶
In [16]:
eds = EAFDataSource()
rx = eds.reaction('U235', 'gamma')
rx
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In [17]:
eds.dst_group_struct = dst_e_g
rxc = eds.discretize('U235', 'gamma')
In [18]:
fig = plt.figure(figsize=(7,7))
plt.loglog(*stair_step(eds.src_group_struct, rx), figure=fig)
plt.loglog(*stair_step(eds.dst_group_struct, rxc), figure=fig)
plt.xlabel('E [MeV]')
plt.ylabel('Cross Section [barns]')
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Simple Data Source¶
In [19]:
sds = SimpleDataSource(dst_group_struct=dst_e_g)
print(sds.exists)
rx = sds.reaction('U233', 'absorption')
rxc = sds.discretize('U233', 'absorption')
In [20]:
fig = plt.figure(figsize=(7,7))
plt.loglog(sds.src_group_struct[:-1], rx, figure=fig)
plt.loglog(sds.dst_group_struct[:-1], rxc, figure=fig)
plt.xlabel('E [MeV]')
plt.ylabel('Cross Section [barns]')
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The data sources are caches, which means that subsequent requests for the same data are very fast!
In [21]:
%time sds.reaction('U238', 'fiss')
print()
%time sds.reaction('U238', 'fission')
print()
%time sds.reaction('U238', 'fiss')
print()
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