### Install CFITSIO, Boost, and OpenMPI with Homebrew

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Installs core non-Python dependencies using Homebrew on macOS.

```bash
ட்டுகள்%> brew install cfitsio
ட்டுகள்%> brew install boost
ட்டுகள்%> brew install openmpi
```

--------------------------------

### Execute DESI Software Installation Script

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Run the 'install.sh' script to install DESI software from source. Ensure the script is executable before running.

```bash
./install.sh
```

--------------------------------

### Create DESI Software Installation Script

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Create a bash script to automate the installation of DESI packages from their git source trees. This script cleans and installs each package.

```bash
%> cd $HOME/git-$NERSC_HOST
%> cat install.sh

#!/bin/bash

# This should be your actual install location...
pref="${HOME}/desi-${NERSC_HOST}"

cd specex
make clean
SPECEX_PREFIX=${pref} make -j 4 install
cd ..

for pkg in desiutil desimodel desitarget desisim specter desispec; do
    cd ${pkg}
    python setup.py clean
    python setup.py install --prefix=${pref}
    cd ..
done
```

--------------------------------

### Install Symlink for Development

Source: https://github.com/desihub/desispec/blob/main/README.rst

Use this command to install a symlink to your live git checkout for development purposes. Use the --uninstall flag to remove it.

```bash
python setup.py develop --prefix=/path/to/somewhere
```

```bash
python setup.py develop --prefix=/path/to/somewhere --uninstall
```

--------------------------------

### Displaying Coordinate and Guide File Paths

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Shows the determined paths for the coordinates and guide files.

```python
coordfile, guidefile
```

--------------------------------

### Install Fixed Version

Source: https://github.com/desihub/desispec/blob/main/README.rst

Installs a fixed version of the tools to a specified prefix. This is useful for creating stable installations.

```bash
python setup.py install --prefix=/path/to/somewhere
```

--------------------------------

### Execute DESI Environment Setup

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Run the 'desidev' shell function to load the DESI software environment.

```bash
%> desidev
```

--------------------------------

### Install DESI Dependencies on Ubuntu

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Installs essential non-Python and Python dependencies for DESI on Ubuntu using apt-get and pip. Use --no-binary :all: for fitsio and speclite to ensure they are built from source.

```bash
ட்டுகள்%> sudo apt-get install libboost-all-dev libcfitsio-dev \
    libopenblas-dev liblapack-dev python3-matplotlib \
    python3-scipy python3-astropy python3-requests \
    python3-yaml python3-mpi4py

ட்டுகள்%> pip install --no-binary :all: fitsio speclite iniparser
```

--------------------------------

### Install Remaining Python Dependencies on OS X

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Installs the rest of the required Python packages using pip3, with a specific flag for fitsio to ensure it's built from source.

```bash
ட்டுகள்%> pip3 install requests pyyaml iniparser speclite astropy
ட்டுகள்%> pip3 install --no-binary :all: fitsio
```

--------------------------------

### Record Input Guide and Coordinates Files

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Records the base filenames of the input guide and coordinate files into the fibermap header. If a file is not provided, 'MISSING' is recorded.

```python
if guidefile is not None:
    fibermap_header['GUIDEFIL'] = os.path.basename(guidefile)
else:
    fibermap_header['GUIDEFIL'] = 'MISSING'

if coordfile is not None:
    fibermap_header['COORDFIL'] = os.path.basename(coordfile)
else:
    fibermap_header['COORDFIL'] = 'MISSING'
```

--------------------------------

### Configure HARP Release Tarball Installation

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Configure the HARP package for installation from a release tarball. Use '--prefix' to specify the installation directory.

```bash
%> cd harp-1.0.1
%> ./configure --disable-python --disable-mpi \
   --prefix="${HOME}/desi-${NERSC_HOST}"
```

--------------------------------

### Finding Coordinates and Guide Files

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Locates the coordinates and guide files based on the fiber assignment file directory. Includes logic to handle cases with zero, one, or multiple matching files, and options to force continuation or raise errors.

```python
force=args.force
#- Find coordinates file in same directory
dirname, filename = os.path.split(rawfafile)
globfiles = glob.glob(dirname+'/coordinates-*.fits')
if len(globfiles) == 1:
    coordfile = globfiles[0]
elif len(globfiles) == 0:
    message = f'No coordinates*.fits file in fiberassign dir {dirname}'
    if force:
        log.error(message + '; continuing anyway')
        coordfile = None
    else:
        raise FileNotFoundError(message)

elif len(globfiles) > 1:
    raise RuntimeError(f'Multiple coordinates*.fits files in fiberassign dir {dirname}')

#- And guide file
dirname, filename = os.path.split(rawfafile)
globfiles = glob.glob(dirname+'/guide-????????.fits.fz')
if len(globfiles) == 0:
    #- try falling back to acquisition image
    globfiles = glob.glob(dirname+'/guide-????????-0000.fits.fz')

if len(globfiles) == 1:
    guidefile = globfiles[0]
elif len(globfiles) == 0:
    message = f'No guide-*.fits.fz file in fiberassign dir {dirname}'
    if force:
        log.error(message + '; continuing anyway')
        guidefile = None
    else:
        raise FileNotFoundError(message)

elif len(globfiles) > 1:
    raise RuntimeError(f'Multiple guide-*.fits.fz files in fiberassign dir {dirname}')
```

--------------------------------

### Edison Environment Setup and Sky Computation

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Frame.ipynb

Commands to set up the environment on Edison and run the desi_compute_sky.py script with specified input and output files.

```bash
[edison ~] source env.sh
    [edison ~] cd Python/desispec
    [edison ~] git pull
    [edison ~] cd
    [edison ~] module use ~xavier/modules
    [edison ~] module switch desispec/qa_exposure
    [edison ~] cd qa_test

    desi_compute_sky.py \
        --infile /project/projectdirs/desi/spectro/redux/sjb/dogwood/exposures/20150211/00000002/frame-b0-00000002.fits \
        --fibermap /project/projectdirs/desi/spectro/sim/alpha-5/20150211/fibermap-00000002.fits \
        --fiberflat /project/projectdirs/desi/spectro/redux/sjb/dogwood/calib2d/20150211/fiberflat-b0-00000001.fits \
        --outfile sky-b0-00000002.fits \
        --qafile qa-b0-00000002.yaml \
        --qafig qa-b0-00000002.pdf \
        > qa_tst.log
```

--------------------------------

### Process DESI Guide Star FITS Files

Source: https://github.com/desihub/desispec/blob/main/doc/nb/cosmic-joiner.ipynb

Iterates through guide star FITS files for a given date, extracting and printing TILEID, TARGTRA, and TARGTDEC from the headers. Requires the 'glob', 'os', and 'fits' libraries.

```python
import glob
import os
from astropy.io import fits

def guides(date):
    names = glob.glob(os.path.join("/exposures","desi", date, "*", "guide-0*.fits.fz"))
    for n in names:
        with fits.open(n) as hdus:
            print(n)
            print("TILE", hdus[0].header["TILEID"])
            print("RA", hdus[0].header["TARGTRA"])
            print("DEC", hdus[0].header["TARGTDEC"])
            print()

```

--------------------------------

### Example Call to `desi_preproc`

Source: https://github.com/desihub/desispec/blob/main/doc/nb/PreprocConstructionTest.ipynb

Demonstrates how to call the `desi_preproc` script with various arguments, including night, exposure ID, camera, fibermap, and output file. This is useful for understanding the script's basic usage.

```bash
desi_preproc -n 20210412 -e 84523 --cameras r0 \
    --fibermap $DESI_ROOT/spectro/redux/f3/preproc/20210412/00084523/fibermap-00084523.fits \
    --outfile preproc-r0-00084523.fits --model-variance
```

--------------------------------

### Setup database connection for target schema

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Establishes a database connection to a specific schema ('specprod_target') on a given host, with options for overwriting and verbosity.

```python
postgresql = dsr.setup_db(schema=specprod+'_target', overwrite=overwrite, hostname='nerscdb03.nersc.gov', verbose=True)
```

--------------------------------

### Show Image with Ginga (Commented Out)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Preproc.ipynb

A commented-out example showing how to display image data using the pypeit.ginga viewer. This is typically used for interactive inspection of astronomical images.

```python
#ginga.show_image(z2_hdu.data)
```

--------------------------------

### Install Homebrew on OS X

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Installs Homebrew, a package manager for macOS, which is used to install other dependencies.

```bash
ட்டுகள்%> /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
```

--------------------------------

### srun Command for `desi_preproc`

Source: https://github.com/desihub/desispec/blob/main/doc/nb/PreprocConstructionTest.ipynb

Shows an example of how to run `desi_preproc` using `srun` for parallel processing. This command includes options for node and task count, CPU binding, and various pre-processing flags.

```bash
srun -N 3 -n 200 -c 4 --cpu-bind=cores desi_proc   --traceshift --nostdstarfit --nofluxcalib --cameras a0123456789 -n 20210412 -e 84523 --timingfile /global/cfs/cdirs/desi/spectro/redux/f3/run/scripts/night/20210412/prestdstar-20210412-00084523-a0123456789-timing-$SLURM_JOBID.json --mpi --nofluxcalib
```

--------------------------------

### Install DESI Coadd Development Branch

Source: https://github.com/desihub/desispec/blob/main/doc/coadd.md

Clone the desispec repository and checkout the co-add development branch for testing.

```bash
git clone git@github.com:desihub/desispec.git
cd desispec
git checkout #6
```

--------------------------------

### Create Python Package Directory

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Pre-create the necessary directory for Python packages before installing software.

```bash
%> mkdir -p ${HOME}/desi-${NERSC_HOST}/lib/python3.5/site-packages
```

--------------------------------

### Spectra Object Construction and Basic Usage

Source: https://context7.com/desihub/desispec/llms.txt

Demonstrates how to construct a Spectra object manually and perform basic operations like getting the number of spectra and targets.

```APIDOC
## Spectra Object Construction and Basic Usage

### Description
This section shows how to create a `Spectra` object from scratch using provided data for different bands, and then how to query basic properties like the number of spectra and targets.

### Method
`Spectra(bands, wave, flux, ivar, mask, fibermap, ...)`

### Parameters
- **bands** (list of str) - List of band names (e.g., ['b', 'r', 'z']).
- **wave** (dict) - Dictionary where keys are band names and values are numpy arrays of wavelengths.
- **flux** (dict) - Dictionary where keys are band names and values are numpy arrays of flux.
- **ivar** (dict) - Dictionary where keys are band names and values are numpy arrays of inverse variance.
- **mask** (dict) - Dictionary where keys are band names and values are numpy arrays of masks.
- **fibermap** (Table) - Astropy Table containing fiber information.

### Request Example
```python
import numpy as np
from desispec.spectra import Spectra
from astropy.table import Table

bands = ['b', 'r', 'z']
nspec = 5
wave = {
    'b': np.linspace(3600., 5800., 1000),
    'r': np.linspace(5800., 7600., 1000),
    'z': np.linspace(7600., 9800., 1000),
}
flux = {b: np.random.normal(0, 1, (nspec, 1000)).astype(np.float32) for b in bands}
ivar = {b: np.ones((nspec, 1000),   dtype=np.float32)              for b in bands}
mask = {b: np.zeros((nspec, 1000),  dtype=np.uint32)               for b in bands}
fmap = Table({'TARGETID': np.arange(nspec, dtype=np.int64),
              'TARGET_RA':  np.zeros(nspec),
              'TARGET_DEC': np.zeros(nspec)})

sp = Spectra(bands=bands, wave=wave, flux=flux, ivar=ivar, mask=mask, fibermap=fmap)
print(sp.num_spectra())   # 5
print(sp.num_targets())   # 5
```

### Response
#### Success Response (200)
- **num_spectra()** (int) - Returns the total number of spectra.
- **num_targets()** (int) - Returns the total number of unique targets.

#### Response Example
```
5
5
```
```

--------------------------------

### Display Image with Ginga

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Overscan.ipynb

Displays an image using the Ginga toolkit. Ensure Ginga is installed and configured.

```python
ginga.show_image(img_z3.pix)
```

--------------------------------

### Add Header Info from Guide File

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Adds header keywords from a guide file to the fibermap. It handles cases where the full header might be in HDU 0 or HDU 1 and raises an error if TILEIDs do not match.

```python
if guidefile is not None:
    log.debug(f'Adding header keywords from {guidefile}')
    guideheader = fits.getheader(guidefile, 0)
    if 'TILEID' not in guideheader:
        guideheader = fits.getheader(guidefile, 1)

    if fibermap_header['TILEID'] != guideheader['TILEID']:
        raise RuntimeError('fiberassign tile {} != guider tile {}'.format(
            fibermap_header['TILEID'], guideheader['TILEID']))

    # addkeys(fibermap.meta, guideheader, skipkeys=skipkeys)
    fibermap_header.extend(guideheader, strip=True)
    fibermap_header.remove('EXPTIME')
```

--------------------------------

### Define potential target photometry file path

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Defines the file path for potential target photometry data. This is a commented-out example.

```python
# targetphot_potential_file = os.path.join(os.environ['DESI_ROOT'], 'public', release, 'vac', 'lsdr9-photometry', os.environ['SPECPROD'], targetphot_version, 'potential-targets', f"targetphot-potential-{os.environ['SPECPROD']}.fits")

```

--------------------------------

### Import DESI Libraries

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Intro_to_DESI_spectra.ipynb

Imports essential libraries for DESI spectral analysis, including numpy, healpy, fitsio, and matplotlib. Ensure these are installed before running.

```python
import os
import numpy as np
import healpy as hp
from glob import glob
import fitsio
from collections import defaultdict

from desitarget import desi_mask

import matplotlib.pyplot as plt
%pylab inline
```

--------------------------------

### Get HEALPix Pixel Area using healpy

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Intro_to_DESI_spectra.ipynb

This snippet demonstrates a more direct method to obtain the area of a HEALPix pixel for a given nside using the healpy library. It requires the healpy library to be installed.

```python
hp.nside2pixarea(64,degrees=True)
```

--------------------------------

### Set Up Preprocessing Variables

Source: https://github.com/desihub/desispec/blob/main/doc/nb/PreprocConstructionTest.ipynb

Configures environment variables and defines input/output file paths for the preprocessing step. This includes setting the log level, night, exposure ID, camera, and constructing the full paths for input raw data, fibermap, and output preproc file.

```python
os.environ['DESI_LOGLEVEL'] = 'DEBUG'
night = 20210412
expid = 84523
camera = 'r0'
infile = findfile('raw', night, expid)
fibermap = os.path.join(os.environ['DESI_SPECTRO_REDUX'], os.environ['SPECPROD'], 'preproc', str(night), f'{expid:08d}', f'fibermap-{expid:08d}.fits')
outfile = os.path.join(os.environ['CSCRATCH'], f'preproc-{camera}-{expid:08d}.fits')
infile, fibermap, outfile
```

--------------------------------

### Run desi_bootcalib for z0 (Wavelengths)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Execute the `desi_bootcalib.py` script for the z0 band using files from the Wavelengths directory, specifying fiberflat, arcfile, output, and QA files. Use the `--test` flag for testing.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/Wavelengths/pix-z0-00000001.fits \
        --arcfile /Users/xavier/DESI/Wavelengths/pix-z0-00000000.fits \
        --outfile /Users/xavier/DESI/Wavelengths/boot_psf-z0.fits \
        --qafile /Users/xavier/DESI/Wavelengths/qa_boot-z0.pdf \
        --test
```

--------------------------------

### Run script_bootcalib with Python

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Import and execute the `script_bootcalib` function from `desispec.bootcalib` in Python, passing lists of integers as arguments.

```python
from desispec.bootcalib import script_bootcalib as scb
scb([0,1,2,3,4,5,6,7,8,9], [10,11,12,13,14])
```

--------------------------------

### Set up DESI Environment

Source: https://github.com/desihub/desispec/blob/main/doc/coadd.md

Source the DESI environment script to set up necessary paths and configurations for using DESI software.

```bash
source /project/projectdirs/desi/software/desi_environment.sh
```

--------------------------------

### Define file loading configuration

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Sets up a list of dictionaries, where each dictionary specifies parameters for loading different targetphot FITS files into the database, including file paths, table class, HДУ, expansion rules, and chunking.

```python
loader = [{'filepaths': [os.path.join('/global/cscratch1/sd/ioannis/photocatalog', os.environ['SPECPROD'], 'targetphot-{specprod}.fits'.format(specprod=os.environ['SPECPROD'])),
                         os.path.join('/global/cscratch1/sd/ioannis/photocatalog', os.environ['SPECPROD'], 'targetphot-potential-targets-{specprod}.fits'.format(specprod=os.environ['SPECPROD'])),
                         os.path.join('/global/cscratch1/sd/ioannis/photocatalog', os.environ['SPECPROD'], 'targetphot-missing-{specprod}.fits'.format(specprod=os.environ['SPECPROD']))],
            'tcls': dsr.Target,
            'hdu': 'TARGETPHOT',
            'expand': {'DCHISQ': ('dchisq_psf', 'dchisq_rex', 'dchisq_dev', 'dchisq_exp', 'dchisq_ser',)},
            'q3c': 'ra',
            'chunksize': 100000,
            'maxrows': 0
            },]
```

--------------------------------

### Install Python Dependencies with Homebrew on OS X

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Installs Python 3 versions of mpi4py and scipy using Homebrew on macOS. The --with-python3 flag ensures compatibility.

```bash
ட்டுகள்%> brew install homebrew/python/mpi4py --with-python3
ட்டுகள்%> brew install homebrew/python/scipy --with-python3
ட்டுகள்%> brew install homebrew/python/matplotlib --with-python3
```

--------------------------------

### Run desi_bootcalib for r0

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Execute the `desi_bootcalib.py` script for the r0 band, specifying fiberflat, arcfile, output, and QA files. Use the `--test` flag for testing.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/Wavelengths/pix-r0-00000001.fits \
        --arcfile /Users/xavier/DESI/Wavelengths/pix-r0-00000000.fits \
        --outfile /Users/xavier/DESI/Wavelengths/boot_psf-r0.fits \
        --qafile /Users/xavier/DESI/Wavelengths/qa_boot-r0.pdf \
        --test
```

--------------------------------

### Run desi_bootcalib for z0 (NERSC_TED)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Execute the `desi_bootcalib.py` script for the z0 band using files from the NERSC_TED directory, specifying fiberflat, arcfile, output, and QA files. Use the `--test` flag for testing.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/NERSC_TED/pix-z0-00000000.fits \
        --arcfile /Users/xavier/DESI/NERSC_TED/pix-z0-00000001.fits \
        --outfile /Users/xavier/DESI/NERSC_TED/boot_psf-z0.fits \
        --qafile /Users/xavier/DESI/NERSC_TED/qa_boot-z0.pdf \
        --test
```

--------------------------------

### Run desi_bootcalib for b0

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Execute the `desi_bootcalib.py` script for the b0 band, specifying fiberflat, arcfile, output, and QA files. Use the `--test` flag for testing.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/Wavelengths/pix-b0-00000001.fits \
        --arcfile /Users/xavier/DESI/Wavelengths/pix-b0-00000000.fits \
        --outfile /Users/xavier/DESI/Wavelengths/boot_psf-b0.fits \
        --qafile /Users/xavier/DESI/Wavelengths/qa_boot-b0.pdf \
        --test
```

--------------------------------

### Get Image Shape

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Overscan.ipynb

Retrieves the shape (dimensions) of the image data processed with the Savitzky-Golay filter.

```python
img_savgol.pix.shape
```

--------------------------------

### Get PSF Dimensions

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_firsttry.ipynb

Retrieves the number of pixels along the x and y dimensions of the PSF model.

```python
desi_psf.npix_x, desi_psf.npix_y
```

--------------------------------

### Initialize and Fit Fiber Traces

Source: https://github.com/desihub/desispec/blob/main/doc/nb/BootCalib_CRs.ipynb

Performs a crude initialization of fiber traces and then fits polynomial traces to the identified fiber positions. This involves two steps: crude initialization and polynomial fitting.

```python
xset, xerr = desiboot.trace_crude_init(flat,xpk,ypos)
xfit, fdicts = desiboot.fit_traces(xset,xerr)
```

--------------------------------

### Get Wavelength Array for Fiber

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_firsttry.ipynb

Retrieves the wavelength array for a specific fiber across all its pixels.

```python
wave0 = desi_psf.wavelength(0,np.arange(desi_psf.npix_y))
```

--------------------------------

### Initialize and Load QA Production Data

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Prod.ipynb

Initializes the `QA_Prod` object and loads the production QA data. This is a prerequisite for most subsequent analysis steps.

```python
reload(dqap)
qa_prod = dqap.QA_Prod()
```

```python
qa_prod.load_data()
```

--------------------------------

### Get Filtered Target IDs

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Lya-tsnr-signal.ipynb

Retrieves the TARGETIDs from the fiber map that match the target quasar list.

```python
fmap_ids = dat['FIBERMAP'].data['TARGETID'][isin]
```

--------------------------------

### Get Magnitudes Array Size

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_S2N_Develop.ipynb

Calculates the total number of elements in the 'MAGNITUDES' array within 's2n_dict'.

```python
np.array(s2n_dict['MAGNITUDES']).size
```

--------------------------------

### Initialize Matching Variables and Loop

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Initializes arrays for matching spectral line identifications and ions. It then begins a nested loop structure to calculate median and mean offsets between observed and theoretical line positions, preparing for spectral matching.

```python
# Match up (ugly loops)
ids = np.zeros(aparm['Nstrong'])
ids2 = np.zeros(aparm['Nstrong'])
ions = np.array(['12345']*aparm['Nstrong'])
for kk in range(aparm['Nstrong']):
    med_off = np.zeros(nlist)
    mean_off = np.zeros(nlist)
    for ss in range(nlist):
        dpix = dpix_list[ss]
        min_off = []
        for jj in range(aparm['Nstrong']):
            min_off.append(np.min(np.abs(dpix_obs[kk,jj]-dpix)))
        min_off.sort()
        mean_off[ss] = np.mean(min_off[:-1])
        med_off[ss] = np.median(min_off)
    #xdb.set_trace()
#        if (kk == 1) & ((ss == 13) or (ss==8)):

```

--------------------------------

### Load a line triplet

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Loads the first line triplet from the line_triplets list. This is a setup step for further analysis.

```python
ltrip = line_triplets[0]
```

--------------------------------

### Import necessary libraries

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Lya-tsnr-signal.ipynb

Imports essential libraries for data manipulation, calculations, and plotting. Ensure these are installed in your environment.

```python
import pandas
import numpy as np
import pylab as pl
import astropy.io.fits as fits
import matplotlib.pyplot as plt

from   astropy.table import Table, join
from   astropy.convolution import convolve, Gaussian1DKernel
from   desiutil.dust import mwdust_transmission
```

--------------------------------

### Get unique TILEIDs from ztile

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Finds and returns an array of unique TILEIDs present in the filtered ztile table.

```python
np.unique(ztile['TILEID'])
```

--------------------------------

### Get Median SNR Array Size

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_S2N_Develop.ipynb

Calculates the total number of elements in the 'MEDIAN_SNR' array within 's2n_dict'.

```python
np.array(s2n_dict['MEDIAN_SNR']).size
```

--------------------------------

### Import Libraries for Bootcalib

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Bootcalib_r.ipynb

Imports necessary libraries for boot calibration, including desispec, desiutil, astropy, and numpy. It also sets up seaborn for plotting.

```python
%matplotlib inline
```

```python
# imports
try:
    import seaborn as sns; sns.set(context="notebook",font_scale=2)
except:
    pass

from desispec import bootcalib as desiboot
from desiutil import funcfits as dufits
from astropy.io import fits
from astropy.stats import sigma_clip

import numpy as np
from astropy.modeling import models, fitting
```

--------------------------------

### Run desi_bootcalib script

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Bootstrap_tests.ipynb

Executes the desi_bootcalib script with specified input arc and fiberflat files, output PSF file, and QA file.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/Wavelengths/pix-sub_b0-00000001.fits \
        --arcfile /Users/xavier/DESI/Wavelengths/pix-sub_b0-00000000.fits \
        --outfile /Users/xavier/DESI/Wavelengths/boot_psf-sub_b0.fits \
        --qafile /Users/xavier/DESI/Wavelengths/qa_boot-sub_b0.pdf
```

--------------------------------

### Set Per-Login Paths for DESI Coadd

Source: https://github.com/desihub/desispec/blob/main/doc/coadd.md

Manually set the PATH and PYTHONPATH environment variables for using the desispec installation.

```bash
cd desispec
export PATH=$PWD/bin:$PATH
export PYTHONPATH=$PWD/py:$PYTHONPATH
```

--------------------------------

### Compute Fiber Flat using command line

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Frame.ipynb

Command-line execution of desi_compute_fiberflat.py script. Requires input frame, output file, fibermap, and QA file paths.

```bash
desi_compute_fiberflat.py \
        --infile /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000001/frame-b0-00000001.fits \
        --outfile /Users/xavier/DESI/TST/dogwood/calib2d/20150211/jxp-fflat-b0-00000001.fits \
        --fibermap /Users/xavier/DESI/TST/data/20150211/fibermap-00000002.fits \
        --qafile /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000001/qa-b0-00000001.yaml \
        --qafig /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000001/qa-fflat-b0-00000001.pdf
```

--------------------------------

### Get Unique Programs (Tiles)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Extracts and returns the unique program names directly from the 'PROGRAM' column of the 'tiles_fits' table.

```python
np.unique(tiles_fits['PROGRAM'])
```

--------------------------------

### Get Unique Goal Types (Exposures)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Extracts and returns the unique goal types from the 'GOALTYPE' column of the 'exposures_fits' table.

```python
np.unique(exposures_fits['GOALTYPE'])
```

--------------------------------

### Get Unique Programs (Exposures)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Extracts and returns the unique program names directly from the 'PROGRAM' column of the 'exposures_fits' table.

```python
np.unique(exposures_fits['PROGRAM'])
```

--------------------------------

### Initialize Configuration

Source: https://github.com/desihub/desispec/blob/main/doc/nb/tsnr_ensemble.ipynb

Initializes the configuration dictionary with tracer type and its corresponding SV1 map value. This sets up essential parameters for data reduction.

```python
config = {'tracer': tracer_type, 'sv1_tracer': sv1_map[tracer_type]}
```

--------------------------------

### Initializing the Fitter

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Sets up the Levenberg-Marquardt least-squares fitter from astropy.modeling.fitting. This fitter is commonly used for non-linear least squares problems.

```python
fitter = fitting.LevMarLSQFitter()
```

--------------------------------

### Get indices of detected peaks

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Extracts the pixel indices where spectral lines are detected based on the refined peak detection.

```python
xpk = np.where(gdp)[0]
```

--------------------------------

### Get Unique Target IDs

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Combines TARGETID data from both observed and potential target tables and finds the unique values.

```python
all_targetids = np.unique(np.hstack((tractorphot_ids['TARGETID'].data, tractorphot_potential_ids['TARGETID'])))

```

--------------------------------

### Run desi_bootcalib for trace only

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Boot_Calibs_fulltest.ipynb

Execute `desi_bootcalib.py` with the `--trace_only` flag to process only the trace, specifying fiberflat, output, and QA files.

```bash
desi_bootcalib.py \
        --fiberflat /Users/xavier/DESI/Wavelengths/pix-b0-00000001.fits \
        --outfile /Users/xavier/DESI/Wavelengths/boot_psf_trace_only-b0.fits \
        --qafile /Users/xavier/DESI/Wavelengths/qa_boot-b0.pdf \
        --test --trace_only
```

--------------------------------

### Import desispec.io module

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Intro_to_DESI_spectra.ipynb

Import the necessary I/O module from the desispec library to read spectral data.

```python
from desispec import io
```

--------------------------------

### Get Bounding Box

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Cosmics.ipynb

Retrieves the current bounding box coordinates (xmin, xmax, ymin, ymax) of the blob group.

```python
    def getBoundingBox(self):
        """Get the bounding rectangle of the group."""
        return (self.xmin, self.xmax, self.ymin, self.ymax)
```

--------------------------------

### Download flat file from URL

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Bootstrap_tests.ipynb

Downloads the flat FITS file from the specified URL and saves it locally with a .gz extension. This is part of setting up for unit tests.

```python
f = urllib2.urlopen(url_flat)
tst_fil = 'tmp_flat.fits.gz'
with open(tst_fil, "wb") as code:
    code.write(f.read())
```

--------------------------------

### Retrieving Wavelength Values

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Extracts a list of wavelength values from a specific range. Used to get the initial set of wavelengths for fitting.

```python
wvval0 = list(gd_lines[icen-2:icen+3])
wvval0
```

--------------------------------

### Get Unique Programs from FAFLAVOR (Tiles)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Extracts and returns the unique program names associated with FAFLAVOR entries in the 'tiles_fits' table.

```python
np.unique(faflavor2program(tiles_fits['FAFLAVOR']))
```

--------------------------------

### Compute Sky using command line

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Frame.ipynb

Command-line execution of desi_compute_sky.py script. Requires input frame, fibermap, fiberflat, output file, and QA file paths. Output is redirected to tmp.log.

```bash
desi_compute_sky.py \
        --infile /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000002/frame-b0-00000002.fits \
        --fibermap /Users/xavier/DESI/TST/data/20150211/fibermap-00000002.fits \
        --fiberflat /Users/xavier/DESI/TST/dogwood/calib2d/20150211/fiberflat-b0-00000001.fits \
        --outfile /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000002/sky2-b0-00000002.fits \
        --qafile /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000002/qa-b0-00000002.yaml \
        --qafig /Users/xavier/DESI/TST/dogwood/exposures/20150211/00000002/qa-b0-00000002.pdf \
        > tmp.log
```

--------------------------------

### Get Unique Programs from FAFLAVOR (Exposures)

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Extracts and returns the unique program names associated with FAFLAVOR entries in the 'exposures_fits' table.

```python
np.unique(faflavor2program(exposures_fits['FAFLAVOR']))
```

--------------------------------

### Initialize matching arrays

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Initializes arrays to store the wavelengths and indices of matched spectral lines. These arrays will be populated during the matching process.

```python
#
mtch_wv = np.zeros( (tcent.size, gdp.size))
mtch_idx = np.zeros( (tcent.size, gdp.size),dtype=int)
```

--------------------------------

### Set DESI log level and get logger

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Configures the logging level for DESI operations to DEBUG and retrieves the logger instance.

```python
os.environ['DESI_LOGLEVEL'] = 'DEBUG'
dsr.log = get_logger()
```

--------------------------------

### Open FITS File and Access 'z3' Extension

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Overscan.ipynb

Opens a FITS file and accesses the 'z3' extension. Ensure 'fits' and 'ifile' are defined. This prepares the data for further preprocessing.

```python
hdulist = fits.open(ifile)
#hdulist.info()
z3 = hdulist['z3']
```

--------------------------------

### Get Science Object Index

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_S2N_Develop.ipynb

Finds the index of the 'SCIENCE' object within the list of object types for which S/N metrics were calculated.

```python
sci_idx = qa_data['20200316'][21]['b1']['S2N']['METRICS']['OBJLIST'].index('SCIENCE')
sci_idx
```

--------------------------------

### Initialize QA_Frame with 'science' flavor and sky subtraction

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Frame.ipynb

Initializes a QA_Frame object with the 'science' flavor, initializes sky subtraction, and prints the data.

```python
reload(qa_exp)
qaframe = qa_exp.QA_Frame(flavor='science')
qaframe.init_skysub()
print(qaframe.data)
```

--------------------------------

### Create DESI Environment Shell Function

Source: https://github.com/desihub/desispec/blob/main/doc/install.md

Define a bash function to load DESI software into your environment. Customize the installation path if not at NERSC.

```bash
desidev () {
    # This is the install location of our desi software.
    # If you are not at NERSC, then change this to something
    # without "NERSC_HOST" in the name.
    desisoft="${HOME}/desi-${NERSC_HOST}"

    # Set environment variables
    export CPATH=${desisoft}/include:${CPATH}
    export LIBRARY_PATH=${desisoft}/lib:${LIBRARY_PATH}
    export LD_LIBRARY_PATH=${desisoft}/lib:${LD_LIBRARY_PATH}
    export PYTHONPATH=${desisoft}/lib/python3.5/site-packages:${PYTHONPATH}

    # Special setup for redmonster
    red="${HOME}/git-${NERSC_HOST}/redmonster"
    export PYTHONPATH=${red}/python:${PYTHONPATH}
    export REDMONSTER_TEMPLATES_DIR=${red}/templates

    # Choose what data files to use- these locations
    # are for NERSC.
    export DESI_ROOT=/project/projectdirs/desi
    export DESIMODEL=${DESI_ROOT}/software/edison/desimodel/master
    export DESI_BASIS_TEMPLATES=${DESI_ROOT}/spectro/templates/basis_templates/v2.2
    export STD_TEMPLATES=${DESI_ROOT}/spectro/templates/star_templates/v1.1/star_templates_v1.1.fits
}
```

--------------------------------

### Construct FITS File Path for 'z3'

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Overscan.ipynb

Constructs the full path to a FITS file for the 'z3' extension. Ensure 'exp_path' and 'night' are defined. This is similar to constructing paths for other extensions.

```python
iid = 20655
ifile = os.path.join(exp_path, night, '000{}'.format(iid), 'desi-000{}.fits.fz'.format(iid))
ifile
```

--------------------------------

### Load targetphot files into the database

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Initiates the loading process for targetphot files using the configuration defined in the 'loader' list.

```python
dsr.load_file(**(loader[0]))
```

--------------------------------

### Set Package Version from Git

Source: https://github.com/desihub/desispec/blob/main/README.rst

If you have tagged a version, use this command to set the package version based on your current git location before installing.

```bash
python setup.py version
```

--------------------------------

### Define Target Photometry File Path

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Constructs the file path for potential target photometry data, incorporating environment variables for project and product information.

```python
targetphot_potential_file = os.path.join(os.environ['DESI_ROOT'], 'users', os.environ['USER'], 'lsdr9-photometry', os.environ['SPECPROD'], targetphot_version, 'potential-targets', f"targetphot-potential-{os.environ['SPECPROD']}.fits")
targetphot_potential = Table.read(targetphot_potential_file, hdu=1)
```

--------------------------------

### Stacking Spectra Objects

Source: https://context7.com/desihub/desispec/llms.txt

Illustrates how to combine multiple Spectra objects into a single one.

```APIDOC
## Stacking Spectra Objects

### Description
This section describes how to stack multiple `Spectra` objects together. This operation requires that all spectra being stacked share the same bands and wavelength grid.

### Method
`stack(list_of_spectra)`

### Parameters
- **list_of_spectra** (list of Spectra) - A list containing `Spectra` objects to be combined.

### Request Example
```python
# Assuming 'sp' and 'sp2' are Spectra objects with compatible bands and wave grids
combined = stack([sp, sp2])
print(combined.num_spectra())  # 8
```

### Response
#### Success Response (200)
- **combined** (Spectra) - A new Spectra object containing the combined spectra from the input list.

#### Response Example
```
8
```
```

--------------------------------

### Initialize a 3x3 NumPy Array

Source: https://github.com/desihub/desispec/blob/main/doc/nb/JoinCosmics.ipynb

Initializes a 3x3 NumPy array filled with zeros. This can serve as a starting point for various array manipulations.

```python
n1 = np.zeros((3,3))
```

--------------------------------

### Get Overscan Column Data

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Overscan.ipynb

Extracts the overscan column data from the raw image using the provided header information. Requires the get_oscan_col function.

```python
oscan_col = get_oscan_col(rawimage, header)
```

--------------------------------

### Create and Write FITS Header with Comments and History

Source: https://github.com/desihub/desispec/blob/main/doc/nb/PreprocConstructionTest.ipynb

Generates a FITS PrimaryHDU with random data, adds multiple COMMENT and HISTORY keywords, and writes it to a file. This demonstrates how fitsio handles multiple entries for the same keyword.

```python
img = fits.PrimaryHDU(np.random.uniform(size=(10,10)))
img.header['COMMENT'] = 'This is the first comment.'
img.header['COMMENT'] = 'This is the second comment.'
img.header['HISTORY'] = 'This is the first history.'
img.header['HISTORY'] = 'This is the second history.'
img.header['EXTNAME'] = 'TEST'
img.header['PLANCK'] = (6.62607015e-34, "[J s] Planck's Constant")
hdulist = fits.HDUList([img])
hdulist.writeto(os.path.join(os.environ['CSCRATCH'], 'fitsio_header_test.fits'), overwrite=True)
```

--------------------------------

### Create and Save Binary Image

Source: https://github.com/desihub/desispec/blob/main/doc/nb/JoinCosmics.ipynb

Generates a dummy binary image and saves it as a PDF file. Demonstrates the usage of the `plot_binary` function.

```python
dummy = np.zeros((28, 28))
dummy[3:4,4:10] = 1
dummy[3:4,12:15] = 1
dummy[5:6,5:12] = 1
dummy[5:6,15:18] = 1
dummy[11:12,6:20] = 1
dummy[11:12,22:24] = 1
dummy[20:21,5:12] = 1
dummy[20:21,14:24] = 1

fig = plot_binary(dummy)
fig.savefig('binary_img.pdf')
```

--------------------------------

### Get shape of DFLUX_B HDU

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Lya-tsnr-signal.ipynb

Retrieves and displays the shape of the 'DFLUX_B' ImageHDU from the loaded FITS file. This helps in understanding the dimensions of the data array.

```python
ens['DFLUX_B'].shape
```

--------------------------------

### Import necessary libraries

Source: https://github.com/desihub/desispec/blob/main/doc/nb/DatabaseConsistencyChecks.ipynb

Imports essential libraries for data manipulation, plotting, and specific DESI functionalities. Includes setup for IERS table freezing.

```python
%matplotlib inline
import os
import glob
import json
from pytz import utc
import numpy as np
import matplotlib.pyplot as plt
import fitsio

from astropy.io import fits
from astropy.table import Table, Column, MaskedColumn, join
from astropy.time import Time

from desiutil.iers import freeze_iers
from desiutil.log import get_logger, DEBUG, INFO

from desispec.io.meta import faflavor2program
from desispec.io.util import checkgzip
import desispec.database.redshift as dsr
from desispec.database.util import targetphotid, surveyid

from desitarget.targets import decode_targetid
freeze_iers()
```

--------------------------------

### Get Survey and Program for a Specific Exposure

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Finds the survey and program for a specific exposure ID (77952) on a given night (20210224) and returns it as a formatted string.

```python
exposures_row = np.nonzero((exposures['NIGHT'] == 20210224) & (exposures['EXPID'] == 77952))[0][0]
survey_program = "{0}-{1}".format(exposures['SURVEY'][exposures_row], program[exposures_row])
survey_program
```

--------------------------------

### Loading Raw Data and Fiberassign Files

Source: https://github.com/desihub/desispec/blob/main/doc/nb/FibermapCombinationTest.ipynb

Loads raw spectrographic data and its corresponding fiber assignment file. Includes error handling for different header types and attempts to find the fiber assignment file.

```python
log = get_logger()

rawfile = findfile('raw', night, int(expid))
try:
    rawheader = fits.getheader(rawfile, 'SPEC', disable_image_compression=True)
except KeyError:
    rawheader = fits.getheader(rawfile, 'SPS', disable_image_compression=True)
rawfafile = fafile = find_fiberassign_file(night, int(expid))
```

--------------------------------

### Sort spectral lines and get count

Source: https://github.com/desihub/desispec/blob/main/doc/nb/Holy_grail.ipynb

Sorts the spectral lines by wavelength and returns the total number of lines. This is a common preprocessing step for spectral analysis.

```python
llist.sort('wave')
nline = len(llist)
nline
```

--------------------------------

### Load QA Exposure data

Source: https://github.com/desihub/desispec/blob/main/doc/nb/QA_Exposure.ipynb

Initializes the QA_Exposure object by loading data for a specific exposure, night, and type, using the provided spectro production directory and multi-root name.

```python
# Load data
reload(dqaexp)
qaexp = dqaexp.QA_Exposure(expid, night, 'science', specprod_dir=specprod_dir, multi_root=multi_root)
```