Spectrum Tools

Overview

This section tools to simulate and analyze spectra.

Simulated Data

This package provides tools to simulate the data that is expected during science operations.

A plot of the sample X class flare time series (SOL2002-07-23):

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import astropy.units as u
>>> import padre_meddea.calibration.spectrum
>>> from padre_meddea.calibration.spectrum import get_flare_rate, flare_timeseries
>>> time = np.arange(10000) * u.s
>>> cts = get_flare_rate()(time)
>>> data_limiter = flare_timeseries['sec_from_start'] < time.max()
>>> y = flare_timeseries['xrsb'][data_limiter] / flare_timeseries['xrsb'].max() * 22421.0
>>> total_counts = cts.sum() * 4
>>> plt.plot(flare_timeseries['sec_from_start'][data_limiter], y, label='data [GOES xrbs]')
>>> plt.plot(time, cts, label='Interpolated', alpha=0.5, linewidth=3.0)
>>> plt.legend()
>>> plt.ylabel('cts/s/detector')
>>> plt.xlabel('seconds from start')
>>> plt.title(f'SOL2002-07-23 {total_counts/1e6:.2f} Mcounts')

(Source code, png, hires.png, pdf)

A plot of the spectrum of our sample X class flare (SOL2002-07-23):

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import astropy.units as u
>>> import padre_meddea.calibration.spectrum
>>> from padre_meddea.calibration.spectrum import flare_spectrum, flare_spectrum_data
>>> energy = np.arange(5, 100, 1) * u.keV
>>> flux = flare_spectrum(1)(energy)
>>> data_limiter = flare_spectrum_data['Bin mean (keV)'] < energy.max()
>>> y = flare_spectrum_data['Flux (photon/s/cm ** 2/keV)'][data_limiter]
>>> plt.plot(flare_spectrum_data['Bin mean (keV)'][data_limiter], y, label='data [RHESSI]')
>>> plt.plot(energy, flux, label='Interpolated', alpha=0.5, linewidth=3.0)
>>> plt.legend()
>>> plt.yscale('log')
>>> plt.xscale('log')
>>> plt.ylabel('photon/s/cm ** 2/keV')
>>> plt.xlabel('energy [keV]')
>>> plt.title('SOL2002-07-23')

(Source code)

A plot of our Ba-133 calibration source:

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import astropy.units as u
>>> import padre_meddea.calibration.spectrum
>>> from padre_meddea.calibration.spectrum import barium_spectrum, ba133_lines, cd_kalpha1, te_kalpha1
>>> energy = np.arange(5, 150, 0.3) * u.keV
>>> flux = barium_spectrum(fwhm = 1 * u.keV)(energy)
>>> plt.plot(energy, flux, label='Simulated', alpha=0.5, linewidth=3.0)
>>> for i, this_line in enumerate(ba133_lines):
>>>     cd_escape_line = this_line['energy (eV)'] - cd_kalpha1
>>>     te_escape_line = this_line['energy (eV)'] - te_kalpha1
>>>     if cd_escape_line > 0 * u.eV:
>>>         plt.axvline(x=cd_escape_line.to('keV').value, label=f'{cd_escape_line.to("keV"):.2f} Cd escape', color='red')
>>>     if te_escape_line > 0 * u.eV:
>>>         plt.axvline(x=te_escape_line.to('keV').value, label=f'{te_escape_line.to("keV"):.2f} Te escape', color='red')
>>>     plt.axvline(x=this_line['energy (eV)'].to('keV').value, label=f'{this_line["energy (eV)"].to("keV"):.2f} {this_line["name"]}')
>>> plt.legend(loc='center left', bbox_to_anchor=(0.60, 0.5))
>>> plt.ylabel('')
>>> plt.xlabel('energy [keV]')
>>> plt.title('Ba-133 Calibration source')

(Source code, png, hires.png, pdf)