Python IO.readmosfits方法代碼示例

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
def imcombine(files, maskname, options, flat, outname=None, shifts=None,
    extension=None):
    '''
    From a list of files it imcombine returns the imcombine of several values.
    The imcombine code also estimates the readnoise ad RN/sqrt(numreads) so
    that the variance per frame is equal to (ADU + RN^2) where RN is computed
    in ADUs.

    Arguments:
        files[]: list of full path to files to combine
        maskname: Name of mask
        options: Options dictionary
        flat[2048x2048]: Flat field (values should all be ~ 1.0)
        outname: If set, will write (see notes below for details)
            eps_[outname].fits: electron/sec file
            itimes_[outname].fits: integration time
            var_[outname].fits: Variance files
        shifts[len(files)]: If set, will "roll" each file by the 
            amount in the shifts vector in pixels. This argument
            is used when telescope tracking is poor. If you need
            to use this, please notify Keck staff about poor 
            telescope tracking.

    Returns 6-element tuple:
        header: The combined header
        electrons [2048x2048]:  e- (in e- units)
        var [2048x2048]: electrons + RN**2 (in e-^2 units)
        bs: The MOSFIRE.Barset instance
        itimes [2048x2048]: itimes (in s units)
        Nframe: The number of frames that contribute to the summed
            arrays above. If Nframe > 5 I use the sigma-clipping
            Cosmic Ray Rejection tool. If Nframe < 5 then I drop
            the max/min elements.

    Notes:

        header -- fits header
        ADUs -- The mean # of ADUs per frame
        var -- the Variance [in adu] per frame. 
        bs -- Barset
        itimes -- The _total_ integration time in second
        Nframe -- The number of frames in a stack.

        
        Thus the number of electron per second is derived as: 
            e-/sec = (ADUs * Gain / Flat) * (Nframe/itimes)

        The total number of electrons is:
            el = ADUs * Gain * Nframe


    '''

    ADUs = np.zeros((len(files), 2048, 2048))
    itimes = np.zeros((len(files), 2048, 2048))
    prevssl = None
    prevmn = None
    patternid = None
    maskname = None

    header = None

    if shifts is None:
        shifts = np.zeros(len(files))

    warnings.filterwarnings('ignore')
    for i in xrange(len(files)):
        fname = files[i]
        thishdr, data, bs = IO.readmosfits(fname, options, extension=extension)
        itimes[i,:,:] = thishdr["truitime"]

        base = os.path.basename(fname).rstrip(".fits")
        fnum = int(base.split("_")[1])
        
        if shifts[i] == 0:
            ADUs[i,:,:] = data.filled(0.0) / flat
        else:
            ADUs[i,:,:] = np.roll(data.filled(0.0) / flat, np.int(shifts[i]), axis=0)

        ''' Construct Header'''
        if header is None:
            header = thishdr

        header["imfno%3.3i" % (fnum)] =  (fname, "img%3.3i file name" % fnum)

        map(lambda x: rem_header_key(header, x), ["CTYPE1", "CTYPE2", "WCSDIM",
            "CD1_1", "CD1_2", "CD2_1", "CD2_2", "LTM1_1", "LTM2_2", "WAT0_001",
            "WAT1_001", "WAT2_001", "CRVAL1", "CRVAL2", "CRPIX1", "CRPIX2",
            "RADECSYS"])

        for card in header.cards:
            if card == '': continue
            key,val,comment = card
            
            if key in thishdr:
                if val != thishdr[key]:
                    newkey = key + ("_img%2.2i" % fnum)
                    try: header[newkey.rstrip()] = (thishdr[key], comment)
                    except: pass

#.........這裏部分代碼省略.........

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
def handle_flats(flatlist, maskname, band, options, extension=None,edgeThreshold=450,lampOffList=None,longslit=None):
    '''
    handle_flats is the primary entry point to the Flats module.

    handle_flats takes a list of individual exposure FITS files and creates:
    1. A CRR, dark subtracted, pixel-response flat file.
    2. A set of polynomials that mark the edges of a slit

    Inputs:
    flatlist: 
    maskname: The name of a mask
    band: A string indicating the bandceil

    Outputs:

    file {maskname}/flat_2d_{band}.fits -- pixel response flat
    file {maskname}/edges.np
    '''

    tick = time.time()

    # Check
    bpos = np.ones(92) * -1

    #Retrieve the list of files to use for flat creation.
    flatlist = IO.list_file_to_strings(flatlist)
    # Print the filenames to Standard-out
    for flat in flatlist:
        info(str(flat))

    #Determine if flat files headers are in agreement
    for fname in flatlist:

        hdr, dat, bs = IO.readmosfits(fname, options, extension=extension)
        try: bs0
        except: bs0 = bs

        if np.any(bs0.pos != bs.pos):
            print "bs0: "+str(bs0.pos)+" bs: "+str(bs.pos)
            error("Barset do not seem to match")
            raise Exception("Barsets do not seem to match")

        if hdr["filter"] != band:
            error ("Filter name %s does not match header filter name "
                    "%s in file %s" % (band, hdr["filter"], fname))
            raise Exception("Filter name %s does not match header filter name "
                    "%s in file %s" % (band, hdr["filter"], fname))
        for i in xrange(len(bpos)):
            b = hdr["B{0:02d}POS".format(i+1)]
            if bpos[i] == -1:
                bpos[i] = b
            else:
                if bpos[i] != b:
                    error("Bar positions are not all the same in "
                            "this set of flat files")
                    raise Exception("Bar positions are not all the same in "
                            "this set of flat files")
    bs = bs0

    # Imcombine the lamps ON flats
    info("Attempting to combine previous files")
    combine(flatlist, maskname, band, options)

    # Imcombine the lamps OFF flats and subtract the off from the On sets
    if lampOffList != None: 
        #Retrieve the list of files to use for flat creation. 
        lampOffList = IO.list_file_to_strings(lampOffList)
        # Print the filenames to Standard-out
        for flat in lampOffList:
            info(str(flat))
        print "Attempting to combine Lamps off data"
        combine(lampOffList, maskname, band, options, lampsOff=True)
        combine_off_on( maskname, band, options)

    debug("Combined '%s' to '%s'" % (flatlist, maskname))
    info("Comgined to '%s'" % (maskname))
    path = "combflat_2d_%s.fits" % band
    (header, data) = IO.readfits(path, use_bpm=True)

    info("Flat written to %s" % path)

    # Edge Trace
    if bs.long_slit:
        info( "Long slit mode recognized")
        info( "Central row position:   "+str(longslit["row_position"]))
        info( "Upper and lower limits: "+str(longslit["yrange"][0])+" "+str(longslit["yrange"][1]))
        results = find_longslit_edges(data,header, bs, options, edgeThreshold=edgeThreshold, longslit=longslit)
    elif bs.long2pos_slit:
        info( "Long2pos mode recognized")
        results = find_long2pos_edges(data,header, bs, options, edgeThreshold=edgeThreshold, longslit=longslit)
    else:
        results = find_and_fit_edges(data, header, bs, options,edgeThreshold=edgeThreshold)
    results[-1]["maskname"] = maskname
    results[-1]["band"] = band
    np.save("slit-edges_{0}".format(band), results)
    save_ds9_edges(results, options)

    # Generate Flat
    out = "pixelflat_2d_%s.fits" % (band)
    if lampOffList != None: 
#.........這裏部分代碼省略.........

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]

#.........這裏部分代碼省略.........
        ITIME = IO.read_drpfits(maskname, fname, options)
        ITIME[1] = np.ma.masked_array(ITIME[1], theBPM, fill_value=0)


        dats = EPS
        vars = VAR
        itimes = ITIME

        EPS[0]["ORIGFILE"] = fname

        tock = time.time()
        sols = range(len(edges)-1,-1,-1)

        shifts = all_shifts[cntr]
        cntr += 1
        p = Pool()
        solutions = p.map(handle_rectification_helper, sols)
        #solutions = map(handle_rectification_helper, [15])
        p.close()

        all_solutions.append(solutions)

    tick = time.time()
    print "-----> Mask took %i. Writing to disk." % (tick-tock)


    output = np.zeros((1, len(fidl)))
    snrs = np.zeros((1, len(fidl)))
    sdout= np.zeros((1, len(fidl)))
    itout= np.zeros((1, len(fidl)))


    # the barset [bs] is used for determining object position
    x, x, bs = IO.readmosfits(barset_file, options)
    

    for i_slit in xrange(len(solutions)):
        solution = all_solutions[0][i_slit]
        header = EPS[0].copy()
        obj = header['OBJECT']

        target_name = bs.ssl[-(i_slit+1)]['Target_Name']
        header['OBJECT'] = target_name

        pixel_dist = np.float(bs.ssl[-(i_slit+1)]['Target_to_center_of_slit_distance'])/0.18

        pixel_dist -= solution['offset']

        ll = solution["lambda"]

        header["wat0_001"] = "system=world"
        header["wat1_001"] = "wtype=linear"
        header["wat2_001"] = "wtype=linear"
        header["dispaxis"] = 1
        header["dclog1"] = "Transform"
        header["dc-flag"] = 0
        header["ctype1"] = "AWAV"
        header["cunit1"] = "Angstrom"
        header["crval1"] = ll[0]
        header["crval2"] = -solution["eps_img"].shape[0]/2 - pixel_dist
        header["crpix1"] = 1
        header["crpix2"] = 1
        header["cdelt1"] = 1
        header["cdelt2"] = 1
        header["cname1"] = "angstrom"
        header["cname2"] = "pixel"

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
fs = ['m120406_0291.fits']

maskname = 'NGC5053'
options = Options.wavelength

path = os.path.join(options["outdir"], maskname)
if not os.path.exists(path):
    raise Exception("Output directory '%s' does not exist. This " 
            "directory should exist." % path)

if False:
    for fname in fs:
        fp = os.path.join(path, fname)

        mfits = IO.readmosfits(fp)
        header, data, bs = mfits

        Wavelength.plot_mask_solution_ds9(fname, maskname, options)
        Wavelength.fit_lambda(mfits, fname, maskname, options)
        Wavelength.apply_lambda(mfits, fname, maskname, options)
        Wavelength.plot_data_quality(maskname, fname, options)
        Wavelength.plot_sky_spectra(maskname, fname, options)
        Wavelength.plot_mask_fits(maskname, fname, options)

if True:
    for fname in fs:
        pass

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]

import numpy as np
import time

import pylab as pl
import scipy as sp
from scipy import interpolate as II
import spline

import MOSFIRE.Options as options
from MOSFIRE import IO, Fit, Wavelength

path = "/scr2/mosfire/c9_npk/npk_calib4_q1700_pa_0/"

mdat = IO.readmosfits(path + "m110323_2737.fits")
fdat = IO.readfits(path + "pixelflat_2d_H.fits")
ldat = IO.readfits(path + "lambda_solution_m110323_2737.fits")

dat = mdat[1]/fdat[1]
lam = ldat[1]

yroi=slice(707,736)
slit = dat[yroi,:]
lslit = lam[yroi,:]

DRAW = False
if DRAW:
    pl.figure(1)
    pl.clf()
    pl.subplot(2,2,1)

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
        nums = [26, 27, 28, 29]
        roll = 0
    elif False: # test_marc H
        name = "test_marc"
        band = "H"
        nums = [19, 20, 21, 22, 23, 24]
        roll = 0

    flatlist = []

    if roll == 0:
        for num in nums:
            flatlist.append("/users/npk/desktop/5apr/m120406_%4.4i.fits" % num)
    else:
        for num in nums:
            header, ff, bs, targs, ssl, msl, asl = IO.readmosfits(
                    "/users/npk/desktop/5apr/m120406_%4.4i.fits" % num)
            hdu = pyfits.PrimaryHDU(np.roll(ff, -5, 0), header)
            hdulist = pyfits.HDUList([hdu])

            for tbl in [targs, ssl, msl, asl]:
                hdu = pyfits.new_table(tbl)
                hdulist.append(hdu)

            fn = "/users/npk/desktop/5apr/roll_m120406_%4.4i.fits" % num
            os.remove(fn)
            hdulist.writeto(fn)

            flatlist.append(fn)

    
    print flatlist

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
def handle_flats(flatlist, maskname, band, options, extension=None):
    '''
    handle_flats is the primary entry point to the Flats module.

    handle_flats takes a list of individual exposure FITS files and creates:
    1. A CRR, dark subtracted, pixel-response flat file.
    2. A set of polynomials that mark the edges of a slit

    Inputs:
    flatlist: Either a string of an input file or a list of file names
    maskname: The name of a mask
    band: A string indicating the bandceil

    Outputs:

    file {maskname}/flat_2d_{band}.fits -- pixel response flat
    file {maskname}/edges.np
    '''

    tick = time.time()

    # Check
    bpos = np.ones(92) * -1

    
    flatlist = IO.list_file_to_strings(flatlist)

    print flatlist

    for fname in flatlist:

        hdr, dat, bs = IO.readmosfits(fname, options, extension=extension)
        try: bs0
        except: bs0 = bs

        if np.any(bs0.pos != bs.pos):
            raise Exception("Barsets do not seem to match")

        if hdr["filter"] != band:
            print ("Filter name %s does not match header filter name "
                    "%s in file %s" % (band, hdr["filter"], fname))
        for i in xrange(len(bpos)):
            b = hdr["B{0:02d}POS".format(i+1)]
            if bpos[i] == -1:
                bpos[i] = b
            else:
                if bpos[i] != b:
                    raise Exception("Bar positions are not all the same in "
                            "this set of flat files")
    bs = bs0
    # Imcombine
    if True:
        print "Attempting to combine: ", flatlist
        combine(flatlist, maskname, band, options)

        print "Combined '%s' to '%s'" % (flatlist, maskname)
    path = "combflat_2d_%s.fits" % band
    (header, data) = IO.readfits(path, use_bpm=True)

    print "Flat written to %s" % path


    # Edge Trace
    results = find_and_fit_edges(data, header, bs, options)
    results[-1]["maskname"] = maskname
    results[-1]["band"] = band
    np.save("slit-edges_{0}".format(band), results)
    save_ds9_edges(results, options)

    # Generate Flat
    out = "pixelflat_2d_%s.fits" % (band)
    make_pixel_flat(data, results, options, out, flatlist)
    print "Pixel flat took {0:6.4} s".format(time.time()-tick)

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
def go(maskname,
        band,
        filenames,
        wavefile,
        wavoptions,
        longoptions,
        use_flat=False):

    '''
    The go command is the main entry point into this module.

    Inputs:
        maskname: String of the mask name
        band: String of 'Y', 'J', 'H', or 'K'
        filenames: List of filenames to reduce
        wavefile: String of path to FITS file with the wavelength solution
        wavoptions: The Wavelength Options dictionary
        longoptions: Dictionary containing:
            {'yrange': The pixel range to extract over
            'row_position': The row to solve the initial wavelength solution on}
        use_flat: Boolean False [default] means to use no flat field
            Boolean True means to divide by the pixelflat
    '''
    wavename = Wavelength.filelist_to_wavename(filenames, band, maskname,
            wavoptions).rstrip(".fits")

    print "Wavefile: {0}".format(wavefile)
    lamhdr, lamdat = IO.readfits(wavefile)

    positions = []
    objname = None
    for listfile in filenames:
        fnames = IO.list_file_to_strings(listfile)
        if len(fnames) != 1:
            raise Exception("I currently expect only one file per position. Remove multiple entries and try again")

        header, data, bs = IO.readmosfits(fnames[0], wavoptions)

        if objname is None:
            objname = header["object"]

        if objname != header["object"]:
            print ("Trying to combine longslit stack of object {0} " 
                    "with object {1}".format(objname, header["object"]))

        print("{0:18s} {1:30s} {2:2s} {3:4.1f}".format(file, header["object"],
            header["frameid"], header["yoffset"]))

        positions.append([fnames[0], header, data, bs])

    print("{0:2g} nod positions found. Producing stacked difference" \
           " image.".format(len(positions)))

    for i in xrange(len(positions)-1):
        A = positions[i]
        B = positions[i+1]

        print("----------- -----".format(A,B))
        
        dname, varname = imdiff(A, B, maskname, band, header, wavoptions)
        if use_flat:
            apply_flat(dname, maskname, band)
            apply_flat(varname, maskname, band)

        rectify(dname, lamdat, A, B, maskname, band, wavoptions,
                longoptions)
        rectify(varname, lamdat, A, B, maskname, band, wavoptions,
                longoptions)
        print dname

    dname, vname = imdiff(B, A, maskname, band, header, wavoptions)
    if use_flat:
        apply_flat(dname, maskname, band)
        apply_flat(vname, maskname, band)
    rectify(dname, lamdat, B, A, maskname, band, wavoptions,
            longoptions)
    rectify(vname, lamdat, B, A, maskname, band, wavoptions,
            longoptions)
    
    if False:
        fname = os.path.join(path, wavename + ".fits")
        B = IO.readfits(fname)
        B = [fname, B[0], B[1]]
        for i in xrange(len(positions)):
            A = positions[i]
            imdiff(A, B, maskname, band, wavoptions)
            rectify(path, dname, lamdat, A, B, maskname, band, wavoptions,
                longoptions)
        imdiff(B, A, maskname, band, wavoptions)
        rectify(path, dname, lamdat, B, A, maskname, band, wavoptions,
                longoptions)

# 需要導入模塊: from MOSFIRE import IO [as 別名]
# 或者: from MOSFIRE.IO import readmosfits [as 別名]
from scipy import signal
import scipy.ndimage
import matplotlib

import pyfits as pf

import MOSFIRE.Options as options
from MOSFIRE import IO, Fit, Wavelength

pl.ion()

path = "/users/npk/desktop/c9_reduce/npk_calib3_q1700_pa_0/"
path = "/scr2/mosfire/c9_npk/npk_calib3_q1700_pa_0/"
path = "/scr2/mosfire/firstlight/NGC5053"

mdat = IO.readmosfits(path + "m120406_0291.fits")
fdat = IO.readfits(path + "pixelflat_2d_J.fits")
ldat = IO.readfits(path + "lambda_solution_m120406_0291.fits")

gain = 2.15

dat = mdat[1]/fdat[1] * gain
dat = mdat[1] * gain
lam = ldat[1]

dat[np.logical_not(np.isfinite(dat))] = 0.


yroi=slice(86, 160)
yroi=slice(173, 203)
yroi=slice(1015, 1090)