spectrograph guide

import os
import cmocean as cmo
import colorcet as cc
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

from popurri import spectrograph as spc
from popurri import plotutils

# mpl.rcdefaults()
plotutils.mpl_custom_basic()
plotutils.mpl_size_same(font_size=18)

# Testing
%load_ext autoreload
%autoreload 2

dirout = './spectrograph/'

All instrument properties

Load and show available instruments and their properties

dfinstprop = spc.SpectrographsProperties(dirout=dirout)
dfinstprop.data

	R	spectral_sampling_px	pixel_ms	wmin_nm	wmax_nm	ndet	ndet_raw	nord	ord_ref	nslice	...	tel_nice	tel_acronym_nice	tel_diameter	observatory	observatory_nice	observatory_acronym_nice	year_start	year_end	ref	notes
inst
carmvis	94600	2.50	1258.0	520.0	960.0	NaN	NaN	61.0	36.0	1.0	...	NaN	NaN	3.6	caha	NaN	CAHA	2016.0	NaN	NaN	NaN
carmnir	80400	2.80	1356.0	960.0	1710.0	NaN	NaN	28.0	NaN	1.0	...	NaN	NaN	3.6	caha	NaN	CAHA	2016.0	NaN	NaN	NaN
crires	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
criresplus	[43000, 92000]	NaN	NaN	950.0	5300.0	3.0	3.0	NaN	NaN	NaN	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	NaN	NaN	NaN	Number of orders and resolution depend on spec...
espresso	[70000,190000]	NaN	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	General ESPRESSO key, mean of all modes
espresso_uhr11	190000	2.50	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
espresso_hr11	138000	4.50	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
espresso_hr21	138000	4.50	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
espresso_hr42	130000	2.25	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	8.2	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
espresso_mr42	72500	5.00	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	16.0	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
espresso_mr84	70000	2.50	NaN	NaN	NaN	1.0	2.0	NaN	NaN	2.0	...	Very Large Telescope	VLT	16.0	paranal	Paranal	Paranal	2017.0	NaN	pepe_et_al_2021	NaN
expres	NaN	3.60	NaN	NaN	NaN	NaN	NaN	86.0	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
harps	115000	3.20	820.0	380.0	690.0	NaN	NaN	72.0	55.0	NaN	...	NaN	NaN	NaN	lasilla	La Silla	La Silla	2003.0	NaN	mayor_et_al_2003	NaN
harpsn	115000	3.20	820.0	NaN	NaN	NaN	NaN	69.0	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	2012.0	NaN	NaN	NaN
igrins	45000	NaN	NaN	1450.0	2450.0	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
maroonx	[82000,88000]	NaN	NaN	500.0	920.0	NaN	NaN	NaN	NaN	3.0	...	Gemini North	NaN	NaN	NaN	NaN	NaN	2020.0	NaN	NaN	NaN
neid	NaN	NaN	NaN	380.0	930.0	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
nirps	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	lasilla	La Silla	La Silla	NaN	NaN	NaN	NaN
spirou	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

19 rows × 29 columns

Example plots

# Plot wavelength range of all available instruments
dfinstprop.fig_wrange(sh=True, sv=True, style='rectangle')  #default style
dfinstprop.fig_wrange(sh=True, sv=True, style='line')

# Plot wavelength range of selected instruments, ordered by year
fig, ax = plt.subplots(figsize=(8, 4))
dfinstprop.plot_wrange_line(ax=ax, lisinst=['harps', 'harpsn', 'espresso', 'carmvis', 'carmnir', 'neid', 'maroonx'], yprop='year_start', cmap='plasma', va=['bottom', 'bottom', 'bottom', 'top', 'bottom', 'bottom', 'bottom'])  # va='center', lw=25
plt.show()
plt.close()

# Thick lines: wrange changes
fig, ax = plt.subplots(figsize=(8, 4))
dfinstprop.plot_wrange_line(ax=ax, lisinst=['harps', 'harpsn', 'espresso', 'carmvis', 'carmnir', 'neid', 'maroonx'], yprop='year_start', cmap='plasma', va=['center', 'center', 'center', 'top', 'center', 'center', 'center'], lw=25)  # va='center', lw=25
plt.show()
plt.close()

# With the rectangle style, the wavelength range doesn't change
fig, ax = plt.subplots(figsize=(8, 4))
dfinstprop.plot_wrange_rectangle(ax=ax, lisinst=['harps', 'harpsn', 'espresso', 'carmvis', 'carmnir', 'neid', 'maroonx'], yprop='year_start', cmap='plasma')
plt.show()
plt.close()

Single instrument

# Initialise spectrograph

inst = 'harps'
harps = spc.Spectrograph(inst, dirout)

# Show basic properties
harps.print_properties_nice()

Instrument str: harps
R: 115000
Mean sampling: 3.2
Pixel sampling [m/s]: 820.0
$\lambda_\mathrm{min}$ [nm]: 380.0
$\lambda_\mathrm{max}$ [nm]: 690.0
Number of detectors: nan
Real number of detectors: nan
Number of orders: 72.0
Reference order: 55.0
Number of slices: nan
Real number of slices: nan
Number of pixels spectral direction: nan
Readout noise [e-]: nan
Conversion factor [e-/ADU]: nan
Position: nan
Type: fiber
Instrument: nan
Instrument acronym: HARPS
Telescope str: nan
Telescope: nan
Telescope acronym: nan
Telescope diameter: nan
Observatory str: lasilla
Observatory: La Silla
Observatory acronym: La Silla
Year start: 2003.0
Year end: nan
Reference: mayor_et_al_2003
Notes: nan

harps.dataord

	ord_real	w_central_nm	y_central_pix	y _central_arcsec	FSR_nm	FSR_min_nm	FSR_max_nm	wmin_nm	wmax_nm	TS_range_nm	CCD	ord	wmin_A	wmax_A
ord
0	161	380.25	47	12	2.36	378.75	381.11	377.96	382.20	4.24	linda	0	3779.6	3822.0
1	160	382.63	79	20	2.39	381.11	383.50	380.32	384.59	4.27	linda	1	3803.2	3845.9
2	159	385.03	111	28	2.42	383.50	385.92	382.71	387.00	4.29	linda	2	3827.1	3870.0
3	158	387.47	143	36	2.45	385.92	388.37	385.13	389.45	4.32	linda	3	3851.3	3894.5
4	157	389.94	176	44	2.48	388.37	390.85	387.58	391.93	4.35	linda	4	3875.8	3919.3
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
67	93	658.19	1601	400	7.07	654.19	661.26	654.20	661.57	7.37	jasmin	67	6542.0	6615.7
68	92	665.34	1694	423	7.23	661.26	668.49	661.31	668.76	7.45	jasmin	68	6613.1	6687.6
69	91	672.65	1788	447	7.39	668.49	675.88	668.57	676.11	7.54	jasmin	69	6685.7	6761.1
70	90	680.12	1885	471	7.55	675.88	683.43	676.00	683.62	7.62	jasmin	70	6760.0	6836.2
71	89	687.76	1984	496	7.72	683.43	691.15	683.59	691.30	7.71	jasmin	71	6835.9	6913.0

72 rows × 14 columns

Plot orders

# Quick default plot, saved in dirout with `fig_ords`
# --- Orders in 1 rows: strongly overlapped
harps.fig_ords(sh=True, sv=True, xunit='nm', nrows=1, title=f'{harps.inst_acronym_nice} orders')
# --- Orders in 2 different rows
harps.fig_ords(sh=True, sv=True, xunit='nm', nrows=2, title=f'{harps.inst_acronym_nice} orders')
# --- Orders in 3 different rows
harps.fig_ords(sh=True, sv=True, xunit='nm', nrows=3, title=f'{harps.inst_acronym_nice} orders')
# --- Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red)
harps.fig_ords(sh=True, sv=True, xunit='nm', nrows=3, title=f'{harps.inst_acronym_nice} orders', olabel='ord_real_num')
# --- Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red), style "line"
harps.fig_ords(sh=True, sv=True, style='line', xunit='nm', nrows=3, title=f'{harps.inst_acronym_nice} orders', olabel='ord_real_num')

# --- Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red), color, adjust figure height
fig, ax = plt.subplots(figsize=(16, 2.5), constrained_layout=True)
ax = harps.plot_ords_rectangle(ax=ax, xunit='nm', nrows=3, title=f'{harps.inst_acronym_nice} orders', olabel='ord_real_num', cmap='nipy_spectral')  # rainbow, turbo
plt.show(), plt.close()
# --- Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red), color, adjust figure height and row separation
fig, ax = plt.subplots(figsize=(16, 2.5), constrained_layout=True)
ax = harps.plot_ords_rectangle(ax=ax, xunit='nm', nrows=3, rowsep=0.5, title=f'{harps.inst_acronym_nice} orders', olabel='ord_real_num', cmap='nipy_spectral')  # rainbow, turbo
plt.show(), plt.close()
# --- Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red), color, adjust figure height, style "line"
fig, ax = plt.subplots(figsize=(16, 2.5), constrained_layout=True)
ax = harps.plot_ords_line(ax=ax, xunit='nm', nrows=3, rowsep=0.5, title=f'{harps.inst_acronym_nice} orders', olabel='ord_real_num', cmap='nipy_spectral')  # rainbow, turbo
plt.show(), plt.close()

(None, None)

# Test rainbow like colormaps
for cmap in ['nipy_spectral', 'rainbow', 'turbo', cc.cm.rainbow4]:
    fig, ax = plt.subplots(figsize=(16, 2.5), constrained_layout=True)
    ax = harps.plot_ords_rectangle(ax=ax, xunit='nm', nrows=3, rowsep=0.5, title=f'{harps.inst_acronym_nice} orders, {cmap}', olabel='ord_real_num', cmap=cmap)
    plt.show(), plt.close()

Plot orders several instruments

harps = spc.Spectrograph('harps', dirout)
harps2 = spc.Spectrograph('harps', dirout)

# Change the ybase of the second spectrograph (default is 0)
# Orders in 3 different rows, with the "real" number and the number from 0 (blue) to nord (red), color, adjust figure height and row separation
fig, ax = plt.subplots(figsize=(16, 5), constrained_layout=True)
# harps
ax = harps.plot_ords_rectangle(ax=ax, xunit='nm', nrows=3, rowsep=0.5, olabel='ord_real_num', color='k')

# harps2
ax = harps.plot_ords_rectangle(ax=ax, xunit='nm', nrows=3, rowsep=0.5, olabel='ord_real_num', color='r', ybase=6)

plt.show(), plt.close()

(None, None)