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// This code is generated by generate_code.py, do not modify it manually.
//! This module contains all the known columns in the cepheid table.
use crate::traits::{Column, Table};
/// This table describes the Cepheid stars identified in table
/// VariableSummary as classification=“CEP”. In the analyses only
/// observations with rejectedByVariabilityProcessing=false are included, as
/// found in table PhotVariableTimeSeriesGfov.
#[allow(non_camel_case_types)]
pub struct cepheid;
impl Table for cepheid {
fn string(&self) -> String {
"cepheid".to_string()
}
}
/// The columns in the cepheid table.
#[allow(non_camel_case_types)]
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, strum::Display)]
pub enum Col {
/// Classification of a Cepheid into “DCEP”, “T2CEP” or “ACEP” using the
/// period-luminosity relations, which are different for the three different
/// types of Cepheids.
type_best_classification,
/// Sub-classification of a T2CEP Cepheids into BL Herculis (“BL_HER”), W
/// Virginis (“W_VIR”) or RV Tauris (“RV_TAU”) sub-types depending on the
/// source periodicity.
type2_best_sub_classification,
/// Best mode classification estimate:
///
/// - “FUNDAMENTAL”: fundamental mode for typeBestClassification=“DCEP” or
/// “ACEP”
///
/// - “FIRST_OVERTONE”: first overtone for typeBestClassification=“DCEP”
/// or “ACEP”
///
/// - “SECOND_OVERTONE”: second overtone for typeBestClassification=“DCEP”
/// or “ACEP”
///
/// - “UNDEFINED”: if mode could not be clearly determined for
/// typeBestClassification=“DCEP” or “ACEP”
///
/// - “NOT_APPLICABLE”: when typeBestClassification=“T2CEP”
///
/// Cepheid pulsation mode is assigned using the period-luminosity
/// relations, which are different for the various pulsation modes, and the
/// plot of the Fourier parameter R21 vs Period.
mode_best_classification,
/// All Gaia data processed by the Data Processing and Analysis Consortium
/// comes tagged with a solution identifier. This is a numeric field
/// attached to each table row that can be used to unequivocally identify
/// the version of all the subsystems that where used in the generation of
/// the data as well as the input data used. It is mainly for internal DPAC
/// use but is included in the published data releases to enable end users
/// to examine the provenance of processed data products. To decode a given
/// solution ID visit
solution_id,
/// A unique single numerical identifier of the source obtained from
/// GaiaSource (for a detailed description see GaiaSource.sourceId)
source_id,
/// This parameter is filled with the period of the maximum power peak in
/// the frequencygram obtained from the modeling of the time series. The
/// light curve of the target star is modeled with a truncated Fourier
/// series (mag(t_j)=zp+\sum[A_i sin(i \times 2 \pi \nu_{max}t_j +\phi_i)]).
/// Zero-point (zp), period (1/\nu_{max}), number of harmonics (i),
/// amplitudes (A_i), and phases (\phi_i) of the harmonics, for the G-band
/// light curve are determined using the Levenberg-Marquardt non linear
/// fitting algorithm.
p1,
/// This parameter is filled with the uncertainty value of the p1 parameter.
/// Its value is derived with Monte Carlo simulations that generate several
/// (100) time series with the same time path as the data points but with
/// magnitudes generated randomly around the corresponding data value. For
/// each of these time series the period is derived from the non linear
/// modeling with a truncated Fourier series of the light curve. The mean of
/// all the periods found and its standard deviation are then computed, and
/// the latter value is kept as value to fill the p1Error parameter.
p1_error,
/// The epoch of maximum light for the Gaia integrated G band. It
/// corresponds to the Baricentric Julian day (BJD) of the maximum value of
/// the light curve model which is closest to the BJD of the first
/// observations -3\timesp1.
///
/// The mentioned BJD is offset by JD 2455197.5 (= J2010.0).
epoch_g,
/// The uncertainty value of the epochG parameter. Its value is three times
/// the error on the p1.
epoch_g_error,
/// The intensity-averaged magnitude in the G-band. The intensity-averaged
/// magnitude is obtained by computing the average flux and then converting
/// the average flux to magnitude.
int_average_g,
/// This parameter is filled with the uncertainty value of the intAverageG
/// parameter. The uncertainty is computed as the error(zp), where zp is the
/// zero point obtained by the non linear Fourier modeling of the light
/// curve.
int_average_g_error,
/// This parameter is filled with the peak-to-peak amplitude value of the G
/// band light curve. The peak-to-peak amplitude is calculated as the
/// (maximum) - (minimum) of the folded modeled light curve in the G band.
/// The light curve of the target star is modeled with a truncated Fourier
/// series (mag(t_j)=zp+\sum[A_i sin(i \times 2 \pi \nu_{max}t_j
/// +\phi_i)]). Zero-point (zp), period (1/\nu_{max}), number of harmonics
/// (i), amplitudes (A_i), and phases (\phi_i) of the harmonics, for the
/// G-band light curve are determined using the Levenberg-Marquardt non
/// linear fitting algorithm.
peak_to_peak_g,
/// This parameter is filled with the uncertainty value of the peakToPeakG
/// parameter. The uncertainty is computed as the \sqrt{2}\times error(zp),
/// where zp is the zero point obtained by the non linear Fourier modeling
/// of the light curve.
peak_to_peak_g_error,
/// This parameter is filled with the number of harmonics used to model P1
/// of the light curve. The light curve of the target star is modeled with a
/// truncated Fourier series
/// (mag(t_j)=zp+\sum[A_i sin(i \times 2 \pi \nu_{max}t_j +\phi_i)]).
/// Zero-point (zp), period (1/\nu_{max}), number of harmonics (i),
/// amplitudes (A_i), and phases (\phi_i) of the harmonics are determined
/// using the Levenberg-Marquardt non linear fitting algorithm.
num_harmonics_for_p1,
/// This parameter is filled with the Fourier decomposition parameter
/// R_{21} = A_2/A_1, where A_2 is the amplitude of the 2nd harmonic and
/// A_{1} is the amplitude of the fundamental harmonic of the truncated
/// Fourier series defined hereafter. The light curve of the target star is
/// modeled with a truncated Fourier series
/// (mag(t_j)=zp+\sum[A_i sin(i \times 2 \pi \nu_{max}t_j +\phi_i)]).
/// Zero-point (zp), period (1/\nu_{max}), number of harmonics (i),
/// amplitudes (A_i), and phases (\phi_i) of the harmonics, are determined
/// using the Levenberg-Marquardt non linear fitting algorithm.
r21_g,
/// This parameter is filled with the uncertainty value on the r21G
/// parameter. Its value isderived by propagation of the errors in the A2
/// and A1 parameters. Errors in A1,A2 are computed from Monte Carlo
/// simulations that generate several (100) time series with the same time
/// path as the data points but with magnitudes generated randomly around
/// the corresponding data value. The mean for each of these values and
/// their standard deviations are then computed, and the latter values are
/// kept as value to fill the uncertainty of the A1, A2 parameters.
r21_g_error,
/// This parameter is filled with the Fourier decomposition parameter
/// \phi_{21}: \phi_2 - 2\phi_1 value. The light curve of the target star is
/// modeled with a truncated Fourier series (mag(t_j)=zp+\sum[A_i
/// sin(i \times 2 \pi \nu_{max} t_j +\phi_i)]). Zero-point (zp), period
/// (1/\nu_{max}), number of harmonics (i), amplitudes (A_i), and phases
/// (\phi_i) of the harmonics, for the G-band light curve are determined
/// using the Levenberg-Marquardt non linear fitting algorithm.
phi21_g,
/// This parameter is filled with the uncertainty of the phi21G parameter.
/// Its value is derived by propagation of the errors in the phi1 and phi2
/// parameters. Errors in phi1,phi2 are computed from Monte Carlo
/// simulations that generate several (100) time series with the same time
/// path as the data points but with magnitudes generated randomly around
/// the corresponding data value. For each of these time series the phi1,
/// phi2 values are computed. The mean for each of these values and their
/// standard deviation are then computed, and the latter values are kept as
/// value to fill the uncertainty of the phi1 and phi2 parameters.
phi21_g_error,
}
impl Column for Col {}
#[cfg(test)]
/// Collects all the known columns in the cepheid table.
pub fn collect_known(map: &mut std::collections::HashMap<String, Vec<String>>) {
let mut col_strings = Vec::new();
col_strings.push(Col::type_best_classification.to_string());
col_strings.push(Col::type2_best_sub_classification.to_string());
col_strings.push(Col::mode_best_classification.to_string());
col_strings.push(Col::solution_id.to_string());
col_strings.push(Col::source_id.to_string());
col_strings.push(Col::p1.to_string());
col_strings.push(Col::p1_error.to_string());
col_strings.push(Col::epoch_g.to_string());
col_strings.push(Col::epoch_g_error.to_string());
col_strings.push(Col::int_average_g.to_string());
col_strings.push(Col::int_average_g_error.to_string());
col_strings.push(Col::peak_to_peak_g.to_string());
col_strings.push(Col::peak_to_peak_g_error.to_string());
col_strings.push(Col::num_harmonics_for_p1.to_string());
col_strings.push(Col::r21_g.to_string());
col_strings.push(Col::r21_g_error.to_string());
col_strings.push(Col::phi21_g.to_string());
col_strings.push(Col::phi21_g_error.to_string());
map.insert(cepheid.string(), col_strings);
}