plotting seds

Author: koepferl

sed.py

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+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+
+from hyperion.model import ModelOutput
+from hyperion.util.constants import pc
+
+# Open the model - we specify the name without the .rtout extension
+m = ModelOutput('tutorial_model.rtout')
+
+# Create the plot
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+
+# Extract the SED for the smallest inclination and largest aperture, and
+# scale to 300pc. In Python, negative indices can be used for lists and
+# arrays, and indicate the position from the end. So to get the SED in the
+# largest aperture, we set aperture=-1.
+wav, nufnu = m.get_sed(inclination=0, aperture=-1, distance=300 * pc)
+
+# Plot the SED. The loglog command is similar to plot, but automatically
+# sets the x and y axes to be on a log scale.
+ax.loglog(wav, nufnu)
+
+# Add some axis labels (we are using LaTeX here)
+ax.set_xlabel(r'$\lambda$ [$\mu$m]')
+ax.set_ylabel(r'$\lambda F_\lambda$ [ergs/s/cm$^2$]')
+
+# Set view limits
+ax.set_xlim(0.1, 5000.)
+ax.set_ylim(1.e-12, 2.e-6)
+
+# Write out the plot
+fig.savefig('sed.png')

sed_incl.py

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+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+
+from hyperion.model import ModelOutput
+from hyperion.util.constants import pc
+
+m = ModelOutput('tutorial_model.rtout')
+
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+
+# Extract all SEDs
+wav, nufnu = m.get_sed(inclination='all', aperture=-1, distance=300 * pc)
+
+# Plot SED for each inclination
+for i in range(nufnu.shape[0]):
+    ax.loglog(wav, nufnu[i, :], color='black')
+
+ax.set_xlabel(r'$\lambda$ [$\mu$m]')
+ax.set_ylabel(r'$\lambda F_\lambda$ [ergs/s/cm$^2$]')
+ax.set_xlim(0.1, 5000.)
+ax.set_ylim(1.e-12, 2.e-6)
+fig.savefig('sed_incl.png')

sed_origin.py

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+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+
+from hyperion.model import ModelOutput
+from hyperion.util.constants import pc
+
+m = ModelOutput('tutorial_model.rtout')
+
+fig = plt.figure()
+ax = fig.add_subplot(1, 1, 1)
+
+# Direct stellar photons
+wav, nufnu = m.get_sed(inclination=0, aperture=-1, distance=300 * pc,
+                       component='source_emit')
+ax.loglog(wav, nufnu, color='blue')
+
+# Scattered stellar photons
+wav, nufnu = m.get_sed(inclination=0, aperture=-1, distance=300 * pc,
+                       component='source_scat')
+ax.loglog(wav, nufnu, color='teal')
+
+# Direct dust photons
+wav, nufnu = m.get_sed(inclination=0, aperture=-1, distance=300 * pc,
+                       component='dust_emit')
+ax.loglog(wav, nufnu, color='red')
+
+# Scattered dust photons
+wav, nufnu = m.get_sed(inclination=0, aperture=-1, distance=300 * pc,
+                       component='dust_scat')
+ax.loglog(wav, nufnu, color='orange')
+
+ax.set_xlabel(r'$\lambda$ [$\mu$m]')
+ax.set_ylabel(r'$\lambda F_\lambda$ [ergs/s/cm$^2$]')
+ax.set_xlim(0.1, 5000.)
+ax.set_ylim(1.e-12, 2.e-6)
+fig.savefig('sed_origin.png')