Querying the Database¶

The database currently consists of two tables: Spectra and Events. These tables host the spectrum-specific and SN-specific metadata respectively. Currently the only way to interact with the database is via an SQL join on these tables. Right now, you should run your code from the /src directory. Our documentation will focus on the routines available in the kaepora.py. Start by importing this module:

import kaepora as kpora

You can then define an array containing SQL queries and obtain spectra from the database. For example:

example_query = ["SELECT * from Spectra inner join Events ON Spectra.SN = Events.SN where phase >= -1 and phase <= 1 and ((dm15_source < 1.8) or (dm15_from_fits < 1.8))"]
spec_array = kpora.grab(example_query[0])

If you would like to remove atypical SNe Ia, SNe with flagged artifacts, and SNe with poor host reddening corrections use:

spec_array = kpora.grab(example_query[0], make_corr=True)

These spectra have been already been corrected for MW reddening. To correct these spectra for host-galaxy reddening (and exclude SNe with A_V > 2) with a F99 reddening law use:

spec_array = kpora.host_dereddening(spec_array, cutoff=2.)

Spectrum Objects¶

spec_array now contains an array of objects that contain our homogenized spectra and all of the spectrum- and SN-specific metadata. Currently these objects are made to represent single spectra, so objects generated from the same SNe will contain some redundant SN metadata. These spectra are normalized to their maximum flux. Basic information on these objects can be viewed with:

for spec in spec_array_dered:
    print spec.name, spec.filename, spec.source, spec.phase, spec.wavelength[spec.x1], spec.wavelength[spec.x2]

A spectrum and its variance can be plotted with:

import matplotlib.pyplot as plt
fig, ax = plt.subplots(2,1)
example_spec = spec_array_dered[20]
ax[0].plot(example_spec.wavelength, example_spec.flux)
ax[1].plot(example_spec.wavelength, 1/example_spec.ivar)
plt.show()

Below we describe other attributes of these objects that are also queryable parameters of the database.

Schema¶

Spectral Attributes¶

Attribute	SQL Format	Description	Type
name	“SN”	SN name	String
filename	“Filename”	Filename from data source	String
source	“Source”	Data source	String
minwave	“Minwave”	Minimum wavelength of original spectrum	float
maxwave	“Maxwave”	Maximum wavelength of original spectrum	float
SNR	“snr”	Median S/N of the spectrum	float
mjd	“MJD”	Modified Julian Date of the spectrum	float
phase	“Phase”	Rest-frame days from B-Band maximum	float
ref	“Ref”	Bibtex code	String

SN Attributes¶

These attributes contain the most metadata. We also include (but do not list) metadata from the results of several different light curve fits. If you would like to construct a query based on these metadata please contact me.

Attribute	SQL Format	Description	Type
redshift	“Redshift”	Redshift from NED	float
mjd_max	“MJD_max”	Modified Julian date corresponding to the time of maximum-light	float
dm15_source	“Dm15_source”	Dm15 from the source survey	float
dm15_from_fits	“Dm15_from_fits”	Dm15 calculated from the polynomial relationship with a light-curve shape parameter	float
e_dm15	“e_dm15”	Error in dm15	float
av_25	“Av_25”	Estimated host galaxy extinction from an MLCS fit using R_v = 2.5	float
m_b_cfa	“M_b_cfa”	Absolute B-Band magnitude at maximum light from the CfA sample	float
m_b_cfa_err	“M_b_cfa_err”	Error in m_b_cfa	float
b_minus_v_cfa	“B_minus_V_cfa”	B-V color at maximum light	float
b_minus_v_cfa_err	“B_minus_V_cfa_err”	Error in b_minus_v_cfa	float
v_at_max	“V_at_max”	Estimated velocity at maximum light	float
v_err	“V_err”	Error in v_at_max	float
ned_host	“NED_host”	A simplified version of NED host galaxy morphology based on cross-listed objects	String
carbon	“Carbon_presence”	‘A’: carbon detected, ‘F’; marginal carbon detected, ‘N’: no carbon detected	String
hubble_res	“Hubble_res”	Hubble residual from a SALT fit	float

You can view all attributes of the spectrum object with the code below:

spec_attributes = dir(spec_array[0])
print spec_attributes