inSpec documentation

Version:

0.6 of 22/12/08, 18:49

Author:

Yannick Copin <@ipnl.in2p3.fr>

This code addresses the different modules in SGS-SPE PE-5300 Spectral Features Measurement:

• M1 Global continuum fit

• M2 Spectrum smoothing

• M3 Emission lines Gaussian fitting

• M4 Absorption lines Gaussian fitting

• M5 Emission lines direct integration

• M6 Continuum indices computation

• M7 Line indices computation

• M8 Synthetic magnitudes computation

• M9 Spectral measurements output table

It now further includes SIR-validation tools:

• spectra extraction

• spectra combination

Links:

• Code repository

• Documentation

Contents

• spectrum - Spectrum manipulations
• formatwarning()
• get_extension()
• Table
  • Table.isSorted()
  • Table.sort()
  • Table.interpolate()
• Spectrum
  • Spectrum.hasVar
  • Spectrum.hasCov
  • Spectrum.close()
  • Spectrum.readKey()
  • Spectrum.setKey()
  • Spectrum.resetHeader()
  • Spectrum.writeto()
  • Spectrum.read_spectrum()
  • Spectrum.get_varname()
  • Spectrum.from_vecs()
  • Spectrum.from_simtables()
  • Spectrum.extend()
  • Spectrum.plot()
  • Spectrum.fracs()
• SimSpectrum
  • SimSpectrum.from_idx()
  • SimSpectrum.select_refspec()
  • SimSpectrum.merge_specs()
  • SimSpectrum.writeto()
• fit_adaptive()
• plot_specs()
• statistics - Statistical utilities
• rms()
• mad()
• sample_mean()
• sample_std()
• get_range()
• hist_binwidth()
• hist_nbin()
• hist_bins()
• savitzky_golay()
• p_better_fit()
• RobustFitter
  • RobustFitter.get_loss()
  • RobustFitter.loss_squared()
  • RobustFitter.loss_squaredtop()
  • RobustFitter.loss_biweight()
  • RobustFitter.loss_pseudo_huber()
  • RobustFitter.loss_cauchy()
  • RobustFitter.derivative()
  • RobustFitter.residuals()
  • RobustFitter.statistic()
  • RobustFitter.plot_losses()
• fit_adaptive_polynom()
• find_peak()
• fit_adaptive_emilines()
• fit_adaptive_spectrum()
• combine - Spectral combination utilities
• sample_mean()
• sample_weighted_mean()
• sample_median()
• weights_AS()
• mean_AS()
• zscore()
• pull()
• outlier_clipping()
• grubbs_gmax()
• grubbs_test()
• chauvenet_dmax()
• chauvenet_criterion()
• detection_rates()
• plot_pull()
• probplot()
• plot_rv()
• plot_samples()
• plot_comparison()
• tools - Miscellaneous tools
• parse_json()
• synth - Flux integration and synthetic magnitudes
• CLIGHT
• HPLANCK
• SynthComputationWarning
• Filter
  • Filter.bandpass()
  • Filter.read()
  • Filter.effLambda()
  • Filter.interpolate()
  • Filter.integrate()
  • Filter.zeroPoint()
  • Filter.magn()
• pixel_fracs()
• indices - Spectral indices
• IndexComputationWarning
• flambda_integ()
• flambda_ratio()
• flambda_normed()
• D4000_ratio()
• lines - Emission/absorption line adjustment
• GaussianNormed1D
  • GaussianNormed1D.flux
  • GaussianNormed1D.mean
  • GaussianNormed1D.stddev
  • GaussianNormed1D.evaluate()
  • GaussianNormed1D.fit_deriv()
  • GaussianNormed1D.param_names
• ComplexHa
  • ComplexHa.Halpha
  • ComplexHa.NIIa
  • ComplexHa.NIIb
  • ComplexHa.rNIIa
  • ComplexHa.rNIIb
  • ComplexHa.fNIIa
  • ComplexHa.fNIIb
  • ComplexHa.wHa
  • ComplexHa.iHa
  • ComplexHa.iNII
  • ComplexHa.sigma
  • ComplexHa.Ha_line()
  • ComplexHa.NII_lines()
  • ComplexHa.evaluate()
  • ComplexHa.fit_deriv()
  • ComplexHa.param_names
• DoubletOIII
  • DoubletOIII.OIII
  • DoubletOIII.OIIIb
  • DoubletOIII.rOIIIb
  • DoubletOIII.fOIII
  • DoubletOIII.fOIIIb
  • DoubletOIII.wOIII
  • DoubletOIII.iOIII
  • DoubletOIII.sigma
  • DoubletOIII.evaluate()
  • DoubletOIII.fit_deriv()
  • DoubletOIII.param_names
• FitterWithPrior
  • FitterWithPrior.priors
  • FitterWithPrior.objective_function()
  • FitterWithPrior.set_priors()
  • FitterWithPrior.get_hterms()
• mpl - Matplotlib utilities
• get_backend()
• save_figures()
• sir - SIR spectrum manipulations
• warning_simple()
• ma_sliding_window_view()
• Spectrum
  • Spectrum.binwidth
  • Spectrum.plot()
  • Spectrum.smooth()
  • Spectrum.smooth_deprecated()
• Dithers
  • Dithers.get_dithers()
  • Dithers.init_from_combspec()
  • Dithers.combined_dither_masks()
  • Dithers.basename
  • Dithers.combine()
  • Dithers.plot()
  • Dithers.get_pull()
  • Dithers.plot_pull()
  • Dithers.smooth()
• decipher_strategy()
• plot_spectra()
• get_pulls()
• plot_pull_hist()
• plot_pull_probplot()
• plot_ndith_stats()
• Input data
  • Noticeable emission lines
  • Continuum indices
  • Line indices
• Simulation 140425
• read_sim_input()
• fig_hist_survey()

Examples

Notebooks

• Outlier detection in small samples using pull-clipping
  • Introduction
  • Outlier detection
  • Implementation and numerical experiments
  • Conclusions
  • Appendix
• Pull-clipping
  • Typical usage for inverse-variance weighted mean
  • Implementation tests
  • Memory profiling

To-do list

Todo

merge and validate these 2 sources into a single file including flux ratio constraints (excluding internal reddening).

(The original entry is located in /builds/ycopin/inSpec/doc/data.rst, line 36.)

Todo

take into account covariance between bandpasses.

(The original entry is located in /usr/local/lib/python3.8/site-packages/inspec/indices.py:docstring of inspec.indices, line 10.)

Todo

• split this function into elementary parts, and compute integral from linear algebraic expression (easier to manipulate for variance/covariance computations).

• validate computations.

(The original entry is located in /usr/local/lib/python3.8/site-packages/inspec/synth.py:docstring of inspec.synth.Filter.integrate, line 22.)

Todo

convert to Notebook.

(The original entry is located in /builds/ycopin/inSpec/doc/test_sim5.rst, line 85.)

Indices and tables

• Index

• Module Index

• Search Page