Visual Test of Specturm Class

Jason Neal, September 2016

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from __future__ import division, print_function
import numpy as np
import PyAstronomy as pyasl
from astropy.io import fits
import matplotlib.pyplot as plt

import copy
from spectrum_overload.Spectrum import Spectrum

%matplotlib inline
In [ ]:
# Load some data and put in the spectrum class

filename = "../../../Codes/Phd-codes/Notebooks/HD30501_data/1/CRIRE.2012-04-07T00-08-29.976_1.nod.ms.norm.sum.wavecal.fits"
data = fits.getdata(filename)
print(data)
data.columns
data["Extracted_DRACS"]
HD30501_1 = Spectrum(flux=data["Extracted_DRACS"], xaxis=data["Wavelength"], calibrated=True)
#HD30501_1_org = Spectrum.Spectrum(flux=data["Extracted_DRACS"], xaxis=data["Wavelength"], calibrated=True)
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# Try to make a copy of a spectrum
HD30501_1_copy = copy.copy(HD30501_1)

# Test slice and doppler shift
plt.figure()
plt.plot(HD30501_1.xaxis, HD30501_1.flux, label="Orginal")
HD30501_1.wav_select(2113,2120)
plt.plot(HD30501_1.xaxis, HD30501_1.flux, "+-",label="wave_select")
RV = 10  # km/s
#nflux, wlprime = pyasl.dopplerShift(HD30501_1.xaxis, HD30501_1.flux, RV)
HD30501_1.doppler_shift(RV)    
plt.plot(HD30501_1.xaxis, HD30501_1.flux, "--", label="Doppler shift Pos")
HD30501_1_copy.doppler_shift(-RV)    
plt.plot(HD30501_1_copy.xaxis, HD30501_1_copy.flux, "--", label="Doppler shift Neg")
#plt.plt(wlprime, HD30501_1.flux, "PyAstronomy Doopler")
#plt.axis.xaxis.
plt.xlim([2112,2118])
plt.legend()
plt.show()
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# Test Calibration polynomial
orginal_axis = [2,3,4,5,6,7]
spec = Spectrum(xaxis=orginal_axis, calibrated=False)
spec.calibrate_with([10, 5.5, 0.2])
print(spec.xaxis)

plt.plot(orginal_axis, spec.xaxis)
plt.title("Test Wavelenght mapping")
plt.xlabel("Old xaxis")
plt.ylabel("New xaxis")
plt.show()

Testing Interpolation

Looks to be working ok

In [ ]:
HD30501_1_interp = copy.copy(HD30501_1)
HD30501_1_upsampled = copy.copy(HD30501_1)
HD30501_1_linear = copy.copy(HD30501_1)
HD30501_1_interp.interpolate_to(np.linspace(np.min(HD30501_1.xaxis), np.max(HD30501_1.xaxis), 500))
HD30501_1_upsampled.interpolate_to(np.linspace(np.min(HD30501_1.xaxis), np.max(HD30501_1.xaxis), 2000))
HD30501_1_linear.interpolate_to(np.linspace(np.min(HD30501_1.xaxis), np.max(HD30501_1.xaxis), 2000), kind='linear')

plt.figure()
plt.plot(HD30501_1.xaxis, HD30501_1.flux, '.-', label='orginal')
plt.plot(HD30501_1_interp.xaxis, HD30501_1_interp.flux, '.', label='interp')
plt.plot(HD30501_1_upsampled.xaxis, HD30501_1_upsampled.flux, '+', label='upsampled')
plt.plot(HD30501_1_linear.xaxis, HD30501_1_linear.flux, '*', label='linear')
plt.xlim([2118.6,2118.7])
plt.legend(loc=0)
plt.show()

#plt difference between llinear and default (cubic)
Diff =  HD30501_1_upsampled - HD30501_1_linear   # use overloaded operators
plt.figure()
plt.plot(HD30501_1_upsampled.xaxis, Diff.flux)
plt.title("Difference between cubic and linear interpolation")
plt.show()
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