Check Loading starfish models compared to manually convolving.

In [1]:

    

from spectrum_overload import Spectrum
from mingle.utilities.phoenix_utils import load_starfish_spectrum

from astropy.io import fits
import matplotlib.pyplot as plt


    

    




/home/jneal/anaconda3/envs/sims/lib/python3.6/site-packages/matplotlib/__init__.py:1405: UserWarning: 
This call to matplotlib.use() has no effect because the backend has already
been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot,
or matplotlib.backends is imported for the first time.

  warnings.warn(_use_error_msg)

In [2]:

    

params1 = [6000, 4.5, 0.0]
params2 = [5800, 4.5, 0.0]
gamma = -90
rv = 25

normalization_limits = [2000, 2300]

mod1_spec_scaled = load_starfish_spectrum(params1, limits=normalization_limits,
                                       hdr=True, normalize=False, area_scale=True,
                                       flux_rescale=False)
mod1_spec_unscaled = load_starfish_spectrum(params1, limits=normalization_limits,
                                       hdr=True, normalize=False, area_scale=False,
                                       flux_rescale=False)

mod2_spec_scaled = load_starfish_spectrum(params2, limits=normalization_limits,
                                       hdr=True, normalize=False, area_scale=True,
                                       flux_rescale=False)
mod2_spec_unscaled = load_starfish_spectrum(params2, limits=normalization_limits,
                                       hdr=True, normalize=False, area_scale=False,
                                       flux_rescale=False)


for name, mod1_spec, mod2_spec in zip(["area scaled", "area unscaled"],
                                  [mod1_spec_scaled, mod1_spec_unscaled],
                                  [mod2_spec_scaled, mod2_spec_unscaled]):

    mod1_spec = mod1_spec.remove_nans()
    mod2_spec = mod2_spec.remove_nans()
    mod1_spec.wav_select(2000, 2200)
    mod2_spec.wav_select(2000, 2200)

    plt.plot(mod1_spec.xaxis, mod1_spec.flux, label="mod1")
    plt.plot(mod2_spec.xaxis, mod2_spec.flux, label="mod2")
    plt.title(name)
    plt.show()


    

In [3]:

    

# Manually load Phoenix spectra
import simulators
#phoenix_path = simulators...
phoenix_path = "/home/jneal/Phd/data/PHOENIX-ALL/PHOENIX/"

phoenix_1 = "Z-0.0/lte06000-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits"
phoenix_2 = "Z-0.0/lte05800-4.50-0.0.PHOENIX-ACES-AGSS-COND-2011-HiRes.fits"

wav = fits.getdata(phoenix_path + "WAVE_PHOENIX-ACES-AGSS-COND-2011.fits")
phoenix1 = fits.getdata(phoenix_path + phoenix_1)
phoenix2 = fits.getdata(phoenix_path + phoenix_2)

spec1 = Spectrum(xaxis=wav/10, flux=phoenix1)
spec2 = Spectrum(xaxis=wav/10, flux=phoenix2)
spec1.wav_select(2000,2200)
spec2.wav_select(2000,2200)
spec1.plot(label="1")
spec2.plot(label="2")

plt.legend()
plt.show()


    

In [4]:

    

from Convolution.IP_multi_Convolution import ip_convolution, convolve_spectrum

# Convolve to 50000
conv1 = convolve_spectrum(spec1, [2100, 2150], 50000, numProcs=4)
conv2 = convolve_spectrum(spec2, [2100, 2150], 50000, numProcs=4)


    

    




100%|██████████| 12499/12499 [00:00<00:00, 25244.20it/s]






    













    




100%|██████████| 12499/12499 [00:00<00:00, 26470.98it/s]






    

In [5]:

    

(1e12 + conv1).plot(label="1")
(1e12 + conv2).plot(label="2")
conv3.plot(label="3")
conv4.plot(label="4")
plt.legend()
plt.show()

(conv3 - conv1).plot()
plt.show()


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-5-0af6a111d46c> in <module>()
      1 (1e12 + conv1).plot(label="1")
      2 (1e12 + conv2).plot(label="2")
----> 3 conv3.plot(label="3")
      4 conv4.plot(label="4")
      5 plt.legend()

NameError: name 'conv3' is not defined

In [ ]:

    

# Comparion to Starfish
conv1.plot(label="phoenix")
mod1_spec_unscaled.wav_select(2100, 2150)
mod1_spec_unscaled.plot(label="starfish")
plt.legend()
plt.show()


(conv1 / 1e11).plot(label="phoenix")
(mod1_spec_unscaled / 1e4).plot(label="starfish")
plt.legend()
plt.show()


    

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((conv1 / 1e7)/(mod1_spec_unscaled)).plot()
plt.show()


    

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# Seems to be a 1e7 factor between them here. (This should not matter afternormalization I think)


    

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