def _plot_group_flux(self, e_g, phi_g):
fig = plt.figure(figsize=(12, 8))
plt.loglog(*stair_step(e_g, phi_g), figure=fig)
plt.title("Flux vs Energy in")
plt.xlabel('E [MeV]')
plt.ylabel('Flux [N/cm$^2\cdot$s]')
plt.savefig("flux")
plt.close()
def test_stair_step():
x = [0.1, 1.0, 10.0, 100.0]
y = [2.0, 3.0, 4.0]
xobs, yobs = bins.stair_step(x, y)
xexp = [0.1, 1.0, 1.0, 10.0, 10.0, 100.0]
yexp = [2.0, 2.0, 3.0, 3.0, 4.0, 4.0]
assert_equal(len(xobs), len(yobs))
assert_equal(len(yobs), 2 * len(y))
assert_array_almost_equal(xobs, xexp)
assert_array_almost_equal(yobs, yexp)
def _plot_group_flux(self, e_g, phi_g):
"""Plot the group flux output by OpenMC and save plot to file.
Parameters
----------
e_g : array
Energy bins
phi_g : array
Flux values
"""
fig = plt.figure(figsize=(12, 8))
plt.loglog(*stair_step(e_g, phi_g), figure=fig)
plt.title("Flux vs Energy in")
plt.xlabel('E [MeV]')
plt.ylabel('Flux [N/cm$^2\cdot$s]')
plt.savefig("flux")
plt.close()
def stairstep_plot(energy, data, data_name):
# Munge the data into a plotable form
x, y = stair_step(energy, data)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="line",
marker="circle",
index_sort="ascending",
color="red",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = data_name
plot.line_width = 0.5
plot.padding = 100
plot.x_axis.title = "Energy [MeV]"
plot.x_axis.title_font = "Roman 16"
plot.x_axis.tick_label_font = "Roman 12"
plot.y_axis.title = "Data"
plot.y_axis.title_font = "Roman 16"
plot.y_axis.tick_label_font = "Roman 12"
plot.index_scale = 'log'
plot.value_scale = 'log'
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
